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Functional materials

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From predictive modelling to machine learning as versatile tools for materials design

The scope of the proposed symposium is to offer a survey of the most advanced modelling approaches used to gain fundamental and practical insights into a wide range of functional materials for multiple technological applications (optoelectronics, energy, biomaterials). Special attention is devoted to the recent forefront applications of first-principles methods as well as machine-learning techniques, bearing in mind the fundamental principles of Physics and Chemistry. The atomic-level knowledge provided by the combination of high-performance computing and advanced computational methods pave the route for a rational approach, based on an accurate assessment of materials’ Chemistry and Physics, to the design of novel materials with properties tailored for specific applications in next-generation technologies.

Scope:

Advanced computational methods in combination with huge progresses in computational machines have multiplied the predicting and support to experiments tools, becoming an unavoidable field in the European Community Materials Research. Indeed, theoretical characterization and simulations from either first- principles or empirical approaches are likely to provide important information complementary to experimental insights. In that respect, the scope of this symposium aims at exploring the wide range of theoretical methods developed in the recent years. An important part will be devoted to theoretical and numerical developments to overcome nowadays-physical challenges.

This symposium will meet the challenge of assessing the role of chemical bonding in complex materials by employing as a theoretical endeavour, a survey of advanced computational approaches. The goal of these innovating methods is to investigate structural, dynamical, optical, magnetic and electronic localization properties of specific materials of interest for next-generation devices (optoelectronics, energy harvesting and storage, electronic, spin or heat transport, thermoelectricity, biomaterials) coping with the current need for a sustainable technology.

Those approaches range from atomic-level first-principles methods to tight-binding models and molecular dynamics (MD) simulations. In addition, we will consider methods such as quantum Monte-Carlo or hybrid QM/MM methods for larger or biological systems. In parallel, machine-learning algorithms for material screening would give a nice opening on future methodological perspectives in Materials Science.

Hence, another goal of the symposium is to present a general overview of theory and simulation contribution in the field. For example, we will consider applications in nanosciences and nanostructure materials, bulk, surfaces and interfaces, disordered and low-dimensional materials including graphene and bi-dimensional materials, van der Waals heterostructures, organic molecules on metallic or oxide surfaces, molecular junctions, magnetic and spin cross-over molecules, self-assembled molecular networks, and biological molecules.

In summary, this symposium will provide a wide and unique state of the art overview on the most recent theoretical and numerical approaches used to predict, describe and characterize materials properties. It aims at having equilibrated contributions from important researchers in the community and young researchers to favor discussions and exchange, and draw some perspectives on the next challenges in the field.

Hot topics to be covered by the symposium:

  • Methods and developments in first-principles and semi-empirical methods
  • Molecular dynamics and Monte Carlo
  • Machine learning (Deep learning, Adaptive learning, )
  • High Performance Computing
  • QM/MM simulations
  • Graphene and 2D materials
  • Molecular electronics and spintronics, magnetism
  • Electronic transport and devices simulations, optical properties
  • Electron-phonon coupling, thermoelectricity
  • Metal/organic interfaces and frameworks
  • Biological molecules and mechanisms
  • Thermodynamics
  • Renewable energies and storage
  • Mass and heat transport
  • Surfaces and interfaces
  • Disordered, porous and hybrid organic-inorganic materials

List of scientific committee members:

  • Daniele Passerone, Empa, Switzerland
  • Tim Frolov, Lawrence Livermore National Laboratory, USA
  • Bemarek Alouani, IPCMS, Strasbourg University, France
  • Xavier Blase, Neel Institute, Grenoble, France
  • Giorgios Evangelakis, University of Ioannina, Greece
  • Denis Gentili, CNR, Bologna, Italy
  • Hélène Zapolsky, Group of Material Physics, University of Rouen Normandy, France

 

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08:30 Welcome message and introduction to the Symposium    
 
Predicting materials properties by first-principles and machine learning modeling - I : Elena Levchenko
08:45
Authors : Christopher Gaul, Santiago Cuesta-Lopez
Affiliations : Fundación ICAMCYL, International Center for Advanced Materials and Raw Materials of Castilla y León, León, Spain

Resume : Organic semiconductors are promising materials for cheap, scalable and sustainable electronics, light-emitting diodes and photovoltaics [1,2]. The challenge is to find molecules with the right properties in the vast chemical compound space. For example, the molecules should be durable, non-toxic, and easy to process. For organic photovoltaic cells, the ionization energy should fit to the optical spectrum of sun light. Due to the sheer number of conceivable compounds, it is prohibitively expensive to determine the properties of each compound with ab-initio methods. This is where machine-learning steps in. Recently, a variety of graph networks have been developed that can be trained to predict molecular properties, e.g. the binding energy, from the molecular structure. Here, we build upon the physics-motivated SchNet model [3], which is based on pairwise interactions in 3D space and respects all relevant symmetries. The SchNet model sums up atomic contributions to arrive at the total energy, which is the natural approach for extensive quantities. For organic photovoltaics, we are interested in more complex quantities like the HOMO and LUMO energies of a molecule. Therefore, we extend SchNet with the Set2Set unit [Vin16], which has more expressive power than a plain sum. Most previous models have been trained and evaluated on rather small molecules (in particular the "QM9" dataset). Here, we extend the scope of these machine learning-methods by adding also larger molecules from other sources and establish a consistent train-validation-test split. Both contributions improve the accuracy of graph networks to predict properties relevant for organic photovoltaics and other applications. Our model will be used in conjunction with geometry-generating methods and genetic algorithms [Hen20,Arap18] to discover better material. [1] Cheng and Yang, Accounts of Chemical Research 53, 1218 (2020). [2] Gaul et al., Nature Materials 17, 439 (2018). [3] Schütt et al., J. Chem. Phys. 148, 241722 (2018). [4] Vinyals, Bengio & Kudlur, arXiv:1511.06391 (2015). [5] Henault, Rasmussen, & Jensen, PeerJ Physical Chemistry 2, e11 (2020). [6] Arapan, Nieves & Cuesta-López, J. Appl. Phys. 123, 083904 (2018). This work is supported by the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 883256.

C.1.1
09:15
Authors : Doyoung kim, Kyeong-Mo Kang and Woong-Ryeol Yu
Affiliations : Department of Materials Science and Engineering, Seoul National University, 599 Gwanak-ro, Gwanak-gu, Seoul 151-742, Republic of Korea

Resume : Cylindrical pressure vessel should stand very high pressure, for which carbon fibers are wound on it to strengthen pressure vessel’s properties. Most of research is related to find the burst pressure of vessels to pursue optimal vessel design and optimal pattern of wounded filaments. This work is concerned with optimal patterns. Filament-wounded patterns consist of thickness, orientation and stacking sequence, determining the burst pressure. Usually, the number of patterns available for pressure vessel are restricted because filament winding process (helical, hoop and axial winding) constrains the angle and sequence. In this study, we focused on finding optimal pattern using mechanical simulation and artificial intelligence. For a given vessel design, the vessel was divided into three parts (top, dome, and cylinder sections). We defined the optimal pattern as having same performance to withstand burst pressure with less carbon filament. Then, various simulations were performed using different filament geometries to find design rules which can be applied to all vessel designs (details will be presented at the Conference). Next, we studied an optimum pattern and vessel geometry for a given pressure vessel using a neural network built to find the burst pressure based on pattern and vessel geometry. Finally, the inverse step of this neural network was developed to provide an optimal pattern and vessel geometry when a given burst pressure is satisfied.

C.1.2
09:30
Authors : Emmanouil Pervolarakis, Georgios A. Tritsaris, Phoebus Rosakis, Ioannis N. Remediakis
Affiliations : Department of Materials Science and Technology, University of Crete, Heraklion 70013, Greece; John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts 02138, United States of America; Department of Mathematics and Applied Mathematics, University of Crete, Heraklion 70013, Greece and Institute of Applied & Computational Mathematics, Foundation for Research and Technology Hellas, 71110 Heraklion, Crete, Greece; Department of Materials Science and Technology, University of Crete, Heraklion 70013, Greece and Institute of Electronic Structure and Laser, Foundation for Research and Technology Hellas, 71110 Heraklion, Crete, Greece;

Resume : Gold nanoparticles show interesting catalytic and optical properties and have been used in a plethora of applications ranging from energy harvesting to biomedical. These properties are greatly affected by the shape of the nanoparticle, hence it would be of great importance to be able to predict their shape. Typically, shape is predicted theoretically by means of the Wulff construction that only takes into account the surface energy. This method is excellent for large nanoparticles, but has limited accuracy for smaller nanoparticles in which the contributions from the edges become significant. Moreover, there is no consensus in the literature on the values of edge energies of common metals. In our work, we focus on the calculation of the edge energies of gold nanoparticles using a data-informed machine-learning (ML), multiple linear regression algorithm. The algorithm was provided with structural data for the nanoparticles along with the total energy as was calculated using either interatomic potentials or Density Functional Theory (DFT) and fitted the data to a relatively simple model. The latter considers the total energy of a nanoparticle to be a sum of contributions from bulk, surface, edge and vertex atoms. From the ML fit, the average energy of atoms based on their geometric position is directly extracted from the calculated coefficients of the model. Leave-one-out cross validation yielded excellent predictions for the total energy of the nanoparticles with a mean absolute percentage error of 1 meV. The present method reproduces correct bulk- and surface-energies of gold for DFT as well as several different interatomic potentials. The predicted edge energies are well converged with respect to the sample size. This research work was supported by the Hellenic Foundation for Research and Innovation (HFRI) under project "MULTIGOLD" (HFRI-FM17-1303, KA 10480)

C.1.3
09:45
Authors : Steve Dave Wansi Wendji,* Carlo Massobrio,* Guido Ori*
Affiliations : *Institute of Physics and Chemistry of Materials of Strasbourg (IPCMS), UMR 7504 CNRS - University of Strasbourg, France.

Resume : Amorphous chalcogenide systems such as GeSe2, can be considered prototypical binary chalcogen-based disordered materials and a nowadays appealing material for advanced memories, optical switches for neuromorphic, quantum computing and optical interconnects. However, key questions remain unanswered about the structural features characterizing chalcogenide materials, in particular for what concern the amorphous phase. This study focuses on the set-up of a computational procedure combining first-principles molecular dynamics (FPMD) and machine-learning interatomic potential (MLP) MD to quantitatively assess the structural properties of a prototypical chalcogenide liquid and glass. We first produce structural models of GeSe2 liquid and glass using first-principles molecular dynamics (FPMD) in quantitative agreement with available experimental data. Secondly, we use FPMD energies, forces and virials to develop through a Gaussian Process Regression (GPR) kernel-based scheme a Gaussian Approximation Potential-type of machine learning potential (GAP, MLP) for modelling, by classical MD, GeSe2 liquid and glass.

C.1.4
10:00
Authors : S. Sansotta, R. Costa, and P. B. Coto
Affiliations : Materials Physics Center (CFM)-Spanish National Research Council (CSIC), Chair of Biogenic Functional Materials, Technical University of Munich, Materials Physics Center (CFM)-Spanish National Research Council (CSIC)

Resume : Light emitting diodes (LED) have increasingly gained attention for being a good candidate to substitute the outdated incandescent, halogen, and compact fluorescent light bulbs. The reason for the increased popularity of LEDs is their energy efficiency. While LEDs greatly energetically outperform other light sources, their production has a severus ecological impact related to extraction and refining of rare-elements used in their fabrication. Recently the concept of bio-LEDs was introduced to substitute classical LEDs. Bio-LEDs are an innovative technology based on fluorescent proteins such as the green fluorescent protein (GFP). Fluorescent proteins can be obtained from bacteria reducing to a large extent the ecological impact. However, they are prone to denaturation in non-physiological conditions, which limits their use as active materials in optoelectronic applications. To overcome this issue, in Bio-Led they are placed in a polymer matrix. The process of creation of a matrix enclosing proteins goes through the dehydration of a polymer gel that, depending on the polymers used and the amount of water retained can affect the structural stability and optical properties of the fluorescent proteins. In this contribution, we use molecular dynamics simulations to elucidate the dehydration process in a realistic model of the protein-polymer box system and its impact on the structural and optical properties of the protein. For this, we have simulated the polymer matrix using a 4:1 mix in weight of PEO and TMPE in aqueous solution. Each PEO chain has a molecular weight of 4 millions. This has been done using a novel technique to efficiently obtain a relaxed box with a desired level of crystallinity. The second part of the work involves using a novel artificial intelligence algorithm that ranks water molecules based on the likelihood of evaporation. The artificial intelligence algorithm takes full advantage of the SOAP descriptors to describe the water molecules and a K-means clustering method to classify the water molecules.

C.1.5
10:15
Authors : Farnaz Kaboudvand, Yuzki Oey, Samuel ML Teicher, Brenden Ortiz, Michelle D Johannes, Stephen D Wilson, Ram Seshadri
Affiliations : Materials Department, Materials Research Laboratory, and California NanoSystems Institute, University of California, Santa Barbara, California 93106, USA; Center for Computational Materials Science, Naval Research Laboratory, Washington, DC 20375, USA

Resume : Kagome metals have recently attracted attention due to their fascinating electronic structures. Given their special geometry and depending on the degree of electron filling in their lattices, these materials are predicted to host a variety of instabilities like superconductivity (SC), spin liquid states, charge density waves (CDW), and more. One of the recently discovered non-magnetic kagome metals is AV3Sb5 (A = K, Rb, Cs). This family of layered metals exhibits CDW, unconventional superconductivity, and non-trivial band topology which believed to arise due to the proximity of saddle points in the vicinity of Fermi level. Among all the compounds, CsV3Sb5 is the heaviest member of the family which exhibits SC at 2.5 K and a CDW transition at 94 K. The charge density wave ordering manifests as a breathing-mode distortion in the kagome layers. It has been suggested that such ordering derives from nesting between saddle points on the Fermi surface. To aid in the understanding of this materials class, we present calculations of Fermi surface nesting and Lindhard susceptibility of CsV3Sb5. Additionally, we experimentally probed the coupling between the CDW and SC states via hole doping the system. The resulting phase diagram for CsV3Sb5?xSnx reveals that small carrier doping can have dramatic impacts on SC and CDW order in CsV3Sb5.

C.1.6
10:15
Authors : Farnaz Kaboudvand, Yuzki Oey, Samuel ML Teicher, Brenden Ortiz, Michelle D Johannes, Stephen D Wilson, Ram Seshadri
Affiliations : Materials Department, Materials Research Laboratory, and California NanoSystems Institute, University of California, Santa Barbara, California 93106, USA; Center for Computational Materials Science, Naval Research Laboratory, Washington, DC 20375, USA

Resume : Kagome metals have recently attracted attention due to their fascinating electronic structures. Given their special geometry and depending on the degree of electron filling in their lattices, these materials are predicted to host a variety of instabilities like superconductivity (SC), spin liquid states, charge density waves (CDW), and more. One of the recently discovered non-magnetic kagome metals is AV3Sb5 (A = K, Rb, Cs). This family of layered metals exhibits CDW, unconventional superconductivity, and non-trivial band topology which believed to arise due to the proximity of saddle points in the vicinity of Fermi level. Among all the compounds, CsV3Sb5 is the heaviest member of the family which exhibits SC at 2.5 K and a CDW transition at 94 K. The charge density wave ordering manifests as a breathing-mode distortion in the kagome layers. It has been suggested that such ordering derives from nesting between saddle points on the Fermi surface. To aid in the understanding of this materials class, we present calculations of Fermi surface nesting and Lindhard susceptibility of CsV3Sb5. Additionally, we experimentally probed the coupling between the CDW and SC states via hole doping the system. The resulting phase diagram for CsV3Sb5?xSnx reveals that small carrier doping can have dramatic impacts on SC and CDW order in CsV3Sb5.

C.1.6
10:30 Coffee break    
 
Predicting materials properties by first-principles and machine learning modeling - II : Michal Hermanowicz
11:00
Authors : Carlo Massobrio
Affiliations : Institut de Physique et Chimie des Matériaux de Strasbourg, 23 Rue du Loess, BP 43, F-67034 Strasbourg, France Carlo.Massobrio@ipcms.unistra.fr

Resume : At the beginning of the century, working with first-principles molecular dynamics to characterize and understand materials was limited to systems made of 100 atoms at most, not requiring a too high number of plane waves as a basis set and for time trajectories of a few ps. Effective potentials not accounting explicitly for chemical bonding were quite often preferred in spite of their intrinsic limits. Overall, there was still a great deal of skepticism on the idea that molecular dynamics could complement experiments and even go beyond them, despite the fact that the number of users and papers had already taken a quite sharp positive slope. Due to the increase in computational power and the improved reliability of available DFT schemes, the situation has evolved dramatically in recent years, to the point of making possible the prediction of properties on systems and trajectories comparable to those employed within classical MD 20-30 years before. This talk will provide some insight into the development of first-principles molecular dynamics over the past twenty years, by taking advantage of a number of results obtained for disordered systems and nanostructures. Some methodological features will be especially highlighted, like the proper choice of the exchange-correlation functionals and the inclusion of dispersion forces.

C.2.1
11:30
Authors : Botella R., Kistanov A. A., Celis, J., Cao, W.
Affiliations : Funmaters group, NANOMO research unit, Oulu University, Pentti Kaiteran katu 1, 90570 Oulu

Resume : Bi-dimensional (2D) semiconductors are central to many applications such as electronics, photocatalysis, energy harvesting. Their outstanding characteristics include high surface area, high exciton binding energy and mechanical properties enabling band gap engineering [1]. The combination of two semiconductors (heterostructure) is a good way to lift many technological deadlocks. Most 2D/2D heterostructures are van der Waals (vdW) heterostructures characterized by a weak interaction between the layers [2]. While ab initio calculations are useful to study physical properties of materials, the computational effort-accuracy tradeoff is limiting their application to few samples. Machine Learning (ML) methods are alleviating the computational demand and is applied in many fields both experimental and computational [3]. This work aims at using ML to select relevant candidates for further study through experimental work or computational calculation. First, a feature space representing the whole dataset of heterostructure samples (heterostructure space) is created. The engineered features are relating to different aspects of the crystal structure such as atomic charge and distribution, two important characteristics to assess the potential combinations of materials. Then, a meta-estimator is conceived and trained to predict feature values of samples having a defined band alignment. The chosen base model is k-nearest neighbors (KNN) regression, a robust non-generalizing model. The first degree of refinement is the separated training and convolution of four different KNN predicting different features. To further refine the regression, swarm intelligence principles [4] are used: several predictions of the same KNN convolution are collected and their boundaries are shared between each other, reducing the variance of the meta-estimator and finding regions of higher target density. The proposed algorithm is conceived with several degrees of versatility to tune the selection criteria: a tolerance factor on the value of band alignment and a sampling term to probe different parts of the heterostructure space. This new “swarm smart” algorithm is a powerful tool to select, among experimentally existing, computationally studied and not yet discovered vdW heterostructures, the most likely candidate materials enabling us to face the scientific challenges ahead. References:[1] Roldán R. et. al. (2017) Theory of 2D crystals: graphene and beyond. Chem. Soc. Rev., 46, 4387 [2] Geim A. K., Grigorieva I. V. (2013) Van der Waals heterostructures. Nature, 499, 419 [3] Strieth-Kalthoff F. (2020) Machine learning the ropes: principles, applications and directions in synthetic chemistry. Chem. Soc. Rev., 49, 6154 [4] del Valle Y. et. al. (2008) Particle Swarm Optimization: Basic Concepts, Variants and Applications in Power Systems. IEEE T. Evolut. Comput., 12, 2, 171

C.2.2
11:45
Authors : Pablo Aguado-Puente, Piotr Chudzinski
Affiliations : CIC Nanogune BRTA, E-20018 Donostia - SanSebastian, Spain; Institute of Fundamental Technological Research, Polish Academy of Sciences, Pawinskiego 5B, 02-105 Warsaw, Poland

Resume : One of the key issues in the physics of topological insulators is whether the topologically non-trivial properties survive at finite temperatures and, if so, whether they disappear only at the temperature of topological gap closing. Here we study this problem, using quantum fidelity as a measure, by means of ab-initio methods supplemented by an effective dissipative theory built on the top of the ab-initio electron and phonon band structures. In the case of SnTe, the prototypical crystal topological insulator, we reveal the presence of a characteristic temperature, much lower than the gap-closing one, that marks a loss of coherence of the topological state. The transition is not present in a purely electronic system but it appears once we invoke coupling with a dissipative bosonic bath. Features in the dependence with temperature of the fidelity susceptibility can be related to changes in the band curvature, but signatures of a topological phase transition appear in the fidelity only though the non-adiabatic coupling with soft phonons. Our argument is valid in valley topological insulators, but in principle can be generalized to the broader class of topological insulators which host any symmetry-breaking boson.

C.2.3
12:00
Authors : Mohammed GUERBOUB1, Maouro BOERO1, Evelyne MARTIN2, Assil BOUZID,3 Carlo MASSOBRIO1, Guido ORI1
Affiliations : 1 Université de Strasbourg, CNRS, Institut de Physique et Chimie des Matériaux de Strasbourg, UMR 7504, F-67034 Strasbourg, France 2 Université de Strasbourg, CNRS, Laboratoire ICube, UMR 7357, F-67037 Strasbourg, France 3 Institut de Recherche sur les Céramiques (IRCER), CNRS UMR 7315, Université de Limoges, Centre Européen de la Céramique, 12 rue Atlantis, 87068 Limoges, France

Resume : Disordered chalcogenides have a plethora of high-technological applications, from optoelectronic devices to computing memories. In particular, the ternary Ge-Sb-Te (GST) system received widespread interest in the last 20 years due to its application in so-called Phase Change Memory (PCM) which is a promising non-volatile memory (NVM)), they have many applications start from memories to neuromorphic computing and storage applications, it exhibits a high contrast between amorphous and crystalline phases [1], this type of application leans on the difference’s behaviour of amorphous and crystalline phase, the two phases display resistivity contrast, which is exploited in phase-change memory devices. In this scope, quantum modelling has led to a significative advanced in the understanding of its disordered phase over the last decade. However, if there is somehow a certain degree of agreement nowadays by many studies on its complex amorphous structure, other challenges still require further work: one being the thermal properties behaviour of such a system at the nanoscale. In this work as the first step, we investigate the structural properties of amorphous (GeTe)x(Sb2Te3)x-1 (GST225) including structure factors, pair distribution functions, and coordination numbers, and thermal properties (thermal conductivity) and compare our results with experimental findings. The goal of this work is to discuss the system produced by different FPMD schemes [2 and suggest the best one in terms of comparison with the experimental data. In a second step, we test the performance of a Machine Learning potential (MLP) based on Gaussian Approximation Potentials (GAP) scheme [3] for GST225 already developed and available [4] and one MLP-GAP developed in-house. For the prediction of thermal properties, the FPMD and MLP schemes are combined with the so-called approach-to-equilibrium MD (AEMD) [5] to cover the size scale of interest for practical applications. References: [1] Zhang et al. Nature Rev. Mater. 4, 150 2019. [2] Bouzid et al. Phys. Rev. B 96, 224204 2017. [3] Albert Bartok-Partay et al. Quantum Chemistry, 115(16), pp. 1051-1057 2015. [4] Mocanu et al. J. Phys. Chem. B 122, 8998 (2018). [5] Duong et al. RSC Advances 11, 10747 (2021).

C.2.4
12:15
Authors : Louis Bastogne, Philippe Ghosez
Affiliations : Theoretical Materials Physics, CESAM, Université  de Liège, B-4000 Liège, Belgium

Resume : Over the last 30 years, first-principles simulations have revealed particularly useful to explore the physics of ferroelectrics and have gone hand in hand with the development of fully-integrated and widely-accessible software packages. Many interesting problems are however beyond the scope of first-principles investigations (limited to relatively small systems and time scales) and boosted the development of second-principles methods – i.e. construction of effective models with parameters directly fitted from first-principles. A pioneering step in that direction was the development of effective hamiltonians (Heff ) relying on the concept of local mode. Then, alternative atomistic approaches have been considered, including shell models, bond-valence model or effective atomic potentials generalizing the Heff method. Although those approaches demonstrated their usefulness, their use remains relatively limited due to the absence of integrated package implementing them. Here, we will present the recently developed MULTIBINIT open software that is distributed with the ABINIT package (www.abinit.org) and provides a semi-automatized solution for the construction and use of effective atomic potentials. The power of the method for ferroelectric oxides and related compounds will be illustrated through the the modeling of various perovskites (CaTiO3, PbTiO3, BaTiO3, BaHfO3, SrTiO3), exhibiting different kinds of phase transitions and lattice properties. Work done in collaboration with J. Bieder, M. M. Schmitt and E. Bousquet and supported by F.R.S.-FNRS Belgium (project PROMOSPAN) and the European Union’s Horizon 2020 research and innovation program under grant agreement N  766726 (TSAR).

C.2.5
12:30 Lunch break    
 
Material design, comprehension and application by atomistic modeling: 2d materials, films and alloys -I : Guido Ori
14:00
Authors : Balaji Dhanabalan, Elana Borvick, Seda Kutkan, Roman Krahne, Liberato Manna, Assaf Anderson, Milena P. Arciniegas
Affiliations : Balaji Dhanabalan, Seda Kutkan, Roman Krahne, Liberato Manna,and Milena P. Arciniegas from Istituto italiano di tecnologia; E. Borvick and Assaf Anderson: Materials Zone

Resume : Two dimensional organic-inorganic layered perovskites have been investigated in optoelectronic devices with remarkable performances, providing greater stability compared to 3D counterparts. Their extremely flexible organic/inorganic intercalation has provided access to materials for applications also in the fields of chirality, ferroelectrics, and spintronics. Recent studies focused on the impact of organic cations on the material’s dimensionality, bandgap, and crystallographic structure, but the effect of the organic configuration on the emission properties has not yet fully investigated. In this work, we show first the building of a database of Pb-Br 2D structures that were synthesized by using ca. 50 different organic cations. Experimental data from both synthesis conditions and resulting structure and optical properties were collected in real-time and stored on an artificial-intelligence electronic notebook. This facilitated data aggregation, normalization, and visualization in real-time. We also enriched such database with the molecular fingerprints of the organic cations for generating correlation maps. We discovered a new set of white and blue-emitting platelets. We found that molecular weight and rotatable bonds of organic cations alone do not describe the periodicity of 2D layered perovskites and their optical properties. Instead, the addition of a heteroatom in different positions of the organic tail modulates the resulting colour of the emission. Our work provides experimental guidelines to design and control the emission of 2D layered perovskite through the effective integration of experimental data with machine learning tools.

C.3.1
14:30
Authors : Joran Celis, Andrey A. Kistanov, Romain Botella, Wei Cao
Affiliations : University of Oulu; Nano and Molecular Systems research unit (NANOMO); Functional Materials research group

Resume : Two-dimensional (2D) Van der Waals heterostructures consist of two atomically thin sheets of varying nature which often remain connected to each other mainly through Van der Waals interactions. The vast number of combinations of 2D materials, but also often-reported property-dependencies on strain and twist-angle, make the class of 2D Van der Waals heterostructures versatile. Density functional theory (DFT) has been a popular approach to investigate Van der Waals heterostructures. However, the widely and sensibly used periodic boundary conditions (BC) impose two fundamental limitations to the treatment of this specific class of systems. Firstly, the combining of two relaxed monolayers of varying nature into a single simulation box often requires one to be squeezed and/or the other to be stretched for the purpose of fulfilling BC. Secondly, rotating one monolayer relative to the other within a fixed simulation box generally breaks BC except for a limited set of angles. Consequently, all energetic minima plausibly derived by DFT for a certain 2D Van der Waals heterostructure contain strains and twist-angles imposed by BC. Yet, by varying the shape and size of the simulation box, the twist-angle and the magnitude and direction of applied strain, different combinations of strains and twist-angles become accessible. To the best of our knowledge, no previous work involving DFT-treatment of 2D Van der Waals heterostructures deeply focused on the BC-imposed limits, but instead elaborate on the most stable system out of few intuitively derived candidates. In our work, an algorithm was written which analytically derives a complete set of BC-fulfilling heterostructure candidates below selected threshold-strain and size, starting from any two monolayers. The algorithm was presented in a case-study of PC-WS2, a type II semiconducting 2D Van der Waals heterostructure of trigonal symmetry. Also, few of the physical properties of the system were elaborated on for several of the strain and twist-angle combinations. More specifically, geometric properties, electron density distributions, planar potentials, density of states and band structures were considered. In the end, the meaningfulness of the results for the different systems were discussed. Based on our findings, we suspect that elevating the awareness of the BC-imposed limits to DFT treatment of 2D Van der Waals heterostructures could allow researchers to choose more meaningful systems to be treated in their research. Regardless, our algorithm can be considered a tool for facile design of 2D Van der Waals heterostructures. Moreover, it can be considered as a viable option for database generation of 2D Van der Waals heterostructures.

C.3.2
14:45
Authors : Francis H. Davies, A.V. Krasheninnikov
Affiliations : Helmholtz-Zentrum Dresden-Rossendorf, Institute of Ion Beam Physics and Materials Research, 01328 Dresden, Germany; Helmholtz-Zentrum Dresden-Rossendorf, Institute of Ion Beam Physics and Materials Research, 01328 Dresden, Germany

Resume : The material interface is possibly the most important part of any electronic or optoelectronic device. Another cornerstone of modern device engineering is the development of heterostructures by joining materials with different characteristics. Our work [1] combines these two fields to investigate the material engineering of 2D lateral interfaces. Specifically, we employ first-principles modelling to examine the successfully grown interface between 2D TaS2 and MoS2, materials with incommensurate primitive cells. We show that the interface can have two distinct morphologies, "dislocation" or "coherent", and our investigations identify competing physical features that drive the system towards either one. The system is in a balance between the local bond symmetry and material strain. Dislocations give rise to a breakdown of local symmetry and have an energetic cost for their formation; however, preventing dislocations incurs a cost in strain energy. Using these new insights, we apply these techniques to a variety of other 2D interfaces that share structural symmetry and predict their interface transition point from "coherent" to "dislocation". This is a powerful methodology applicable to any 2D material pair that share structural symmetry, and the qualitative understanding is of great value to any experimental or theoretical study. Overall, our insights provide a guideline for controlling the morphology of the lateral interfaces between 2D materials, which should be of high importance for controlling device functionalities. [1] F. Davis & A.V. Krasheninnikov, submitted (2022).

C.3.3
15:00
Authors : Sandeep Sugathan, Krishnamohan Thekkepat, Soumya Bandyopadhyay, Jiyoung Kim, and Pil-Ryung Cha.
Affiliations : Sandeep Sugathan, Soumya Bandyopadhyay, Pil-Ryung Cha; School of Advanced Materials Engineering, Kookmin University, Seoul 02707, Korea. Krishnamohan Thekkepat; Electronic Materials Research Center, Korea Institute of Science and Technology, Seoul 02792, Republic of Korea. Jiyoung Kim; Department of Materials Science and Engineering, The University of Texas at Dallas, Texas 75080, USA.

Resume : Recent studies in ferroelectric hafnia thin films focus on their advantages over conventional perovskite ferroelectrics which broadened the application of ferroelectric materials. However, there are shortcomings in understanding ferroelectric switching, which is crucial in the operation of these devices. In this study, the polarization switching behavior of a polycrystalline hafnium zirconium oxide (HZO) under an applied electric field is simulated using a phase-field model. The model takes into account the bulk free energy density, gradient energy density, and additional contribution from the applied electric field. To reduce the complexity and high computational cost, we neglect elastic contributions in the model and consider the effective representation of the polarization state equation by merging the contribution of strain-polarization coupling with the Landau coefficients. The Landau coefficients describing the bulk free energy density for HZO are not well-defined in literature. For the polycrystalline thin film with random orientations, a novel approach is introduced to predict effective Landau coefficients from experimentally measured switching curves by combining the phase-field model with a genetic algorithm (GA). The simulated curve generated using optimized effective Landau polynomial from GA eliminates the discrepancies in remnant polarization and coercive field observed in the previous computational studies. The domain dynamics during switching predicted by phase field simulations are consistent with available experimental findings. We validate the model by accurately simulating switching curves for HZO thin films with different ferroelectric phase fractions. Furthermore, the phase-field model is also used to investigate the effects of grain morphology and crystalline texture of the thin film on the switching dynamics.

C.3.4
15:15
Authors : E. Marques, V. Voronenkov, B. Van Troeye, M.J. van Setten, P. Morin, B. Groven, S. De Gendt, I. Asselberghs, G. Pourtois
Affiliations : Department of Chemistry, University of Leuven, B-3001 Leuven, Belgium; Imec, 75 Kapeldreef, B-3001 Leuven, Belgium

Resume : The growth of high quality, large grain single monolayer transition metal dichalcogenides, such as WS2, through Metalorganic Chemical Vapour Deposition (MOCVD) is a complex chemical process that requires a tight control on the density of nucleation points [1][2][3] during the film growth, as well as the lateral growth from these nuclei. Critical process parameters control whether multilayer growth or single layer growth is obtained[2][4]. To control the nucleation process, it is critical to understand the thermodynamic forces driving the film formation. These individual steps are unfortunately extremely challenging to unravel experimentally[5]. In this work, we will demonstrate how first-principle calculations based on DFT, paired with classical nucleation theory provide fundamental insights in identifying the MOCVD reactor operation conditions that favour the WS2 growth . We will show how the Gibbs free energies computed for different grains [6] provide the necessary information on the factors that set the film critical nucleation size and identify the temperature, pressure and composition of the reacting gases, that enable reducing the nucleation seed density. Especially, we find that controlling the ratios of certain gas-phase components directly impacts the nucleation process to the point where growth can be completely inhibited. Finally, we will show how nucleation control through careful selection of growth operation conditions can lead to the suppression of undesired by-products through modelling as well as experimental insights. [1] C. Li, T. Kameyama, T. Takahashi, T. Kaneko, and T. Kato, Sci. Rep., vol. 9, no. 1, p. 12958, 2019 [2] B. Groven et al. Chem. Mater., vol. 30, no. 21, pp. 7648–7663, Nov. 2018, [3] X. Qiang et al., Sci. Rep., vol. 11, no. 1, p. 22285, 2021, [4] J. H. Kim et al., Appl. Surf. Sci., vol. 587, p. 152829, 2022 [5] P. A. G. O’Hare, W. N. Hubbard, G. K. Johnson, and H. E. Flotow, J. Chem. Thermodyn., vol. 16, no. 1, pp. 45–59, 1984 [6] R. A. Evarestov, A. V Bandura, V. V Porsev, and A. V Kovalenko, J. Comput. Chem., vol. 38, no. 30, pp. 2581–2593, Nov. 2017

C.3.5
15:30 Coffee break    
16:00 Poster (Session I) 3min Flash presentations    
17:30
Authors : Minjoo Kim, Jinhyung Tak, Jungha Kim, Janghoon Oh, Seungwoo Lee, Sunghun Park, Sungsoo Yim, Heeil Hong, Jooyoung Lee
Affiliations : DRAM Product Engineering Team, Memory Division, Samsung Electronics Co., Ltd

Resume : Wafer defect map images are generated by performing electrical tests on each chip on wafer. These images demonstrate specific failure patterns occurred from semi-conductor manufacturing process. Also, these patterns can cause another defects on post process, so it is crucial for engineers to classify what kind of defect patterns this wafer is early. However, it is such difficult because large-scale data sets of wafers are produced per day. So, in an attempt to automate the classification of wafer defect maps, which are currently manual dependent, various machine learning models have been introduced. Recently, Convolutional Neural Networks have been developed in computer vision society. This method shows the high performances in computer vision problems such as classifying or recognizing images. One of the state of the art methods called Inception was presented in 2015. However, this network still cannot handle the inference time for testing because of its complexity. Also, although the introduction of several deep learning models for wafer defect map classification has been continuously attempted, it has not been successfully applied to mass production environments in the real field due to problems in classification performance and computational volume. Therefore, we propose the deep learning model integrating the inception module and the skip-connection module for wafer defect map classification. This model has a fast training and inference speed with a small number of parameters, it is highly practical when processing large amounts of real-time test data in a semiconductor manufacturing environment because of its small computational volume and high classification performance. We applied our method on the real field wafer test data, and the result showed that the proposed model takes a significant improvement on inference time by over 59% with high performance compared to the baseline model. - Index Terms - convolutional neural networks, wafer defect map, classification, inception module, skip connection module

C.P1.2
17:30
Authors : Minjoo Kim, Jinhyung Tak, Jungha Kim, Janghoon Oh, Seungwoo Lee, Sunghun Park, Sungsoo Yim, Heeil Hong, Jooyoung Lee
Affiliations : DRAM Product Engineering Team, Memory Division, Samsung Electronics Co., Ltd

Resume : Wafer defect map images are generated by performing electrical tests on each chip on wafer. These images demonstrate specific failure patterns occurred from semi-conductor manufacturing process. Also, these patterns can cause another defects on post process, so it is crucial for engineers to classify what kind of defect patterns this wafer is early. However, it is such difficult because large-scale data sets of wafers are produced per day. So, in an attempt to automate the classification of wafer defect maps, which are currently manual dependent, various machine learning models have been introduced. Recently, Convolutional Neural Networks have been developed in computer vision society. This method shows the high performances in computer vision problems such as classifying or recognizing images. One of the state of the art methods called Inception was presented in 2015. However, this network still cannot handle the inference time for testing because of its complexity. Also, although the introduction of several deep learning models for wafer defect map classification has been continuously attempted, it has not been successfully applied to mass production environments in the real field due to problems in classification performance and computational volume. Therefore, we propose the deep learning model integrating the inception module and the skip-connection module for wafer defect map classification. This model has a fast training and inference speed with a small number of parameters, it is highly practical when processing large amounts of real-time test data in a semiconductor manufacturing environment because of its small computational volume and high classification performance. We applied our method on the real field wafer test data, and the result showed that the proposed model takes a significant improvement on inference time by over 59% with high performance compared to the baseline model. - Index Terms - convolutional neural networks, wafer defect map, classification, inception module, skip connection module

C.P1.2
17:30
Authors : Maciej J. Winiarski, Dorota A. Kowalska
Affiliations : Institute of Low Temperature and Structure Research, Polish Academy of Sciences, Okólna 2, 50-422 Wroclaw, Poland

Resume : Experimental studies and following theoretical predictions indicated that rare earth nitrides may form metastable hexagonal BN-type phases in bulk materials and solid solutions with group III nitride systems under tensile strain. In this presentation, the electronic structures of hexagonal ScN, YN, and LuN, obtained with the density functional theory calculations, are discussed with particular focus on band structures. The band gaps of bulk and monolayer rare earth nitrides are predicted to be in range from 1.12 up to 2.32 eV. The monolayer YN and LuN exhibit characteristic splittings of valence bands in the K point in the Brilouin zone, related to strong spin?orbit coupling, which are similar to those present in transition metal dichalcogenides. The 2D rare earth nitrides may be promising novel materials for applications in optoelectronics as bulk, monolayers and 2D heterostructures. This work was supported by the National Science Centre (Poland) under research Grant no. 2017/26/D/ST3/00447. Calculations were performed in Wroclaw Center for Networking and Supercomputing (Project nos. 158 and 175). [1] M.J. Winiarski and D. Kowalska, Mater. Res. Express. 6, 095910 (2019). [2] M.J. Winiarski and D. A. Kowalska, Scientific Reports 10, 16414 (2020).

C.P1.3
17:30
Authors : Maciej J. Winiarski, Dorota A. Kowalska
Affiliations : Institute of Low Temperature and Structure Research, Polish Academy of Sciences, Okólna 2, 50-422 Wroclaw, Poland

Resume : Experimental studies and following theoretical predictions indicated that rare earth nitrides may form metastable hexagonal BN-type phases in bulk materials and solid solutions with group III nitride systems under tensile strain. In this presentation, the electronic structures of hexagonal ScN, YN, and LuN, obtained with the density functional theory calculations, are discussed with particular focus on band structures. The band gaps of bulk and monolayer rare earth nitrides are predicted to be in range from 1.12 up to 2.32 eV. The monolayer YN and LuN exhibit characteristic splittings of valence bands in the K point in the Brilouin zone, related to strong spin?orbit coupling, which are similar to those present in transition metal dichalcogenides. The 2D rare earth nitrides may be promising novel materials for applications in optoelectronics as bulk, monolayers and 2D heterostructures. This work was supported by the National Science Centre (Poland) under research Grant no. 2017/26/D/ST3/00447. Calculations were performed in Wroclaw Center for Networking and Supercomputing (Project nos. 158 and 175). [1] M.J. Winiarski and D. Kowalska, Mater. Res. Express. 6, 095910 (2019). [2] M.J. Winiarski and D. A. Kowalska, Scientific Reports 10, 16414 (2020).

C.P1.3
17:30
Authors : Vladimir Lipp, Igor Milov, Nikita Medvedev
Affiliations : Vladimir Lipp (1,2), Igor Milov (3), Nikita Medvedev (4,5) (1) Center for Free-Electron Laser Science (CFEL), DESY, 22607 Hamburg, Germany (2) The Henryk Niewodniczański Institute of Nuclear Physics, Polish Academy of Sciences, Radzikowskiego 152, 31-342 Kraków (3) Industrial Focus Group XUV Optics, MESA Institute for Nanotechnology, University of Twente, Drienerlolaan 5, 7522 NB Enschede, The Netherlands (4) Institute of Physics, Czech Academy of Sciences, Na Slovance 2, Prague 8, 18221, Czech Republic (5) Institute of Plasma Physics, Czech Academy of Sciences, Za Slovankou 3, 182 00 Prague 8, Czech Republic

Resume : Studying electron- and X-ray-induced electron cascades in solids is essential for various research areas at free-electron laser facilities, such as X-ray imaging, crystallography, pulse diagnostics or X-ray-induced damage. To better understand the fundamental factors defining the duration and spatial size of such cascades, we investigate the electron propagation in ten solids relevant for the applications of X-ray lasers: Au, B4C, diamond, Ni, polystyrene, Ru, Si, SiC, Si3N4, W [1]. Using classical Monte Carlo in the atomic approximation, we study the dependence of the cascade size on the incident electron or photon energy and on the target parameters. The results show that an electron-induced cascade is systematically larger than a photon-induced cascade. Moreover, in contrast with the common assumption, the maximal cascade size does not necessarily coincide with the electron range. It is found that the cascade size can be controlled by a proper choice of the photon energy for a particular material. Photon energy closely above an ionization potential can essentially split the absorbed energy between two electrons -- photo- and Auger -- reducing their initial energy and thus shrinking the cascade size. Our analysis suggests a way of tailoring the electron cascades either for applications requiring small cascades with a high density of excited electrons in them, or for large-spread cascades with lower electron densities. [1] Lipp, Milov, Medvedev, J. Synchrotron Rad. 29, 323 (2022).

C.P1.5
17:30
Authors : Vladimir Lipp, Igor Milov, Nikita Medvedev
Affiliations : Vladimir Lipp (1,2), Igor Milov (3), Nikita Medvedev (4,5) (1) Center for Free-Electron Laser Science (CFEL), DESY, 22607 Hamburg, Germany (2) The Henryk Niewodniczański Institute of Nuclear Physics, Polish Academy of Sciences, Radzikowskiego 152, 31-342 Kraków (3) Industrial Focus Group XUV Optics, MESA Institute for Nanotechnology, University of Twente, Drienerlolaan 5, 7522 NB Enschede, The Netherlands (4) Institute of Physics, Czech Academy of Sciences, Na Slovance 2, Prague 8, 18221, Czech Republic (5) Institute of Plasma Physics, Czech Academy of Sciences, Za Slovankou 3, 182 00 Prague 8, Czech Republic

Resume : Studying electron- and X-ray-induced electron cascades in solids is essential for various research areas at free-electron laser facilities, such as X-ray imaging, crystallography, pulse diagnostics or X-ray-induced damage. To better understand the fundamental factors defining the duration and spatial size of such cascades, we investigate the electron propagation in ten solids relevant for the applications of X-ray lasers: Au, B4C, diamond, Ni, polystyrene, Ru, Si, SiC, Si3N4, W [1]. Using classical Monte Carlo in the atomic approximation, we study the dependence of the cascade size on the incident electron or photon energy and on the target parameters. The results show that an electron-induced cascade is systematically larger than a photon-induced cascade. Moreover, in contrast with the common assumption, the maximal cascade size does not necessarily coincide with the electron range. It is found that the cascade size can be controlled by a proper choice of the photon energy for a particular material. Photon energy closely above an ionization potential can essentially split the absorbed energy between two electrons -- photo- and Auger -- reducing their initial energy and thus shrinking the cascade size. Our analysis suggests a way of tailoring the electron cascades either for applications requiring small cascades with a high density of excited electrons in them, or for large-spread cascades with lower electron densities. [1] Lipp, Milov, Medvedev, J. Synchrotron Rad. 29, 323 (2022).

C.P1.5
17:30
Authors : Victor Rosendal, Walber Hugo Brito, Mads Brandbyge, Nini Pryds, Dirch Hjorth Petersen
Affiliations : Department of Energy Conversion and Storage, Technical University of Denmark, Kongens Lyngby, Denmark; Departamento de Física, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil; Department of Physics, Technical University of Denmark, Kongens Lyngby, Denmark; Department of Energy Conversion and Storage, Technical University of Denmark, Kongens Lyngby, Denmark; Department of Energy Conversion and Storage, Technical University of Denmark, Kongens Lyngby, Denmark

Resume : Perovskite oxides are a versatile class of materials showing exciting features such as ferroelectricity, piezoelectricity, thermoelectricity and superconductivity, just to name a few. The versatility stem from the huge number of combinations of possible cations (A and B) of the ABO3 structure. The connectivity of the oxygen in the octahedral network plays an important role in the properties of the perovskite oxide. Tilting of the oxygen octahedra alters the bond angles, which can affect the electronic band structure. An efficient way to tune and control octahedral tilting is via external strain. Octahedral tilt engineering can therefore provide an important route for designing future electronic devices.[1] Here we investigate how strain stabilizes the octahedral tilting in SrRO3 (R=Ti,Nb) using density functional theory within the generalized gradient approximation. It is found that compressive biaxial strain in SrTiO3 stabilizes octahedral tilting around the elongated out-of-plane c-axis. Furthermore, the tilting is out-of-phase, e.g., each octahedron is tilted in opposite direction to the octahedra above and below (in the out-of-plane direction). We found that the tilt angle increases with the applied strain. SrNbO3 has been recently considered as a correlated transparent conductor both in the visible and UV regime.[2,3] In contrast to SrTiO3, the d orbitals are partially filled (4d) in SrNbO3. According to our calculations, SrNbO3 shows stabilization of octahedral tilting around the out-of-plane axis under compressive biaxial strain. However, the in-phase tilt of SrNbO3 is found to have lower energy compared to the out-of-phase tilt. As the applied strain increases, the energy minima become lower and the difference between the two tilt modes increases. This suggests that the biaxial compressive strain stabilizes the octahedral tilting, and more precisely, compressive strain enhances the energy gain of the in-phase tilt relative to the out-of-phase tilt. This leads to the stabilization of the in-phase tilt in SrNbO3 under large compressive strain. Our predictions open up new design opportunities since the out-of-phase and in-phase tilts belong to different spacegroups corresponding to different symmetries. One might therefore expect different electronic states with different properties. Recently it was shown that the out-of-phase tilt exhibits gapless linear dispersion near the Fermi level.[3] Our preliminary investigation of the in-phase tilt hints that an electronic gap is introduced near the Fermi level. This suggests that SrNbO3 might exhibit both gapless and gapped linear dispersions, depending on which tilt is present. References: [1] James M. Rondinelli et al., MRS Bulletin 37.3 (2012) [2] Yoonsang Park et al., Communications Physics 3.1 (2020) [3] Jong M. Ok et al., Science Advances 7.38 (2021)

C.P1.6
17:30
Authors : Victor Rosendal, Walber Hugo Brito, Mads Brandbyge, Nini Pryds, Dirch Hjorth Petersen
Affiliations : Department of Energy Conversion and Storage, Technical University of Denmark, Kongens Lyngby, Denmark; Departamento de Física, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil; Department of Physics, Technical University of Denmark, Kongens Lyngby, Denmark; Department of Energy Conversion and Storage, Technical University of Denmark, Kongens Lyngby, Denmark; Department of Energy Conversion and Storage, Technical University of Denmark, Kongens Lyngby, Denmark

Resume : Perovskite oxides are a versatile class of materials showing exciting features such as ferroelectricity, piezoelectricity, thermoelectricity and superconductivity, just to name a few. The versatility stem from the huge number of combinations of possible cations (A and B) of the ABO3 structure. The connectivity of the oxygen in the octahedral network plays an important role in the properties of the perovskite oxide. Tilting of the oxygen octahedra alters the bond angles, which can affect the electronic band structure. An efficient way to tune and control octahedral tilting is via external strain. Octahedral tilt engineering can therefore provide an important route for designing future electronic devices.[1] Here we investigate how strain stabilizes the octahedral tilting in SrRO3 (R=Ti,Nb) using density functional theory within the generalized gradient approximation. It is found that compressive biaxial strain in SrTiO3 stabilizes octahedral tilting around the elongated out-of-plane c-axis. Furthermore, the tilting is out-of-phase, e.g., each octahedron is tilted in opposite direction to the octahedra above and below (in the out-of-plane direction). We found that the tilt angle increases with the applied strain. SrNbO3 has been recently considered as a correlated transparent conductor both in the visible and UV regime.[2,3] In contrast to SrTiO3, the d orbitals are partially filled (4d) in SrNbO3. According to our calculations, SrNbO3 shows stabilization of octahedral tilting around the out-of-plane axis under compressive biaxial strain. However, the in-phase tilt of SrNbO3 is found to have lower energy compared to the out-of-phase tilt. As the applied strain increases, the energy minima become lower and the difference between the two tilt modes increases. This suggests that the biaxial compressive strain stabilizes the octahedral tilting, and more precisely, compressive strain enhances the energy gain of the in-phase tilt relative to the out-of-phase tilt. This leads to the stabilization of the in-phase tilt in SrNbO3 under large compressive strain. Our predictions open up new design opportunities since the out-of-phase and in-phase tilts belong to different spacegroups corresponding to different symmetries. One might therefore expect different electronic states with different properties. Recently it was shown that the out-of-phase tilt exhibits gapless linear dispersion near the Fermi level.[3] Our preliminary investigation of the in-phase tilt hints that an electronic gap is introduced near the Fermi level. This suggests that SrNbO3 might exhibit both gapless and gapped linear dispersions, depending on which tilt is present. References: [1] James M. Rondinelli et al., MRS Bulletin 37.3 (2012) [2] Yoonsang Park et al., Communications Physics 3.1 (2020) [3] Jong M. Ok et al., Science Advances 7.38 (2021)

C.P1.6
17:30
Authors : Thomas Bornhake(1,2), Oskar Cheong(1,2,3) , Stefan Rudin(1) and Piotr M. Kowalski(1,2)
Affiliations : 1 Institute of Energy and Climate research (IEK-13, IEK-6), Forschungszentrum Jülich GmbH, 52425 Jülich, Germany 2 Jülich Aachen Research Alliance, JARA-CSD and JARA-ENERGY, 52425 Jülich, Germany 3 Chair of Theory and Computation of Energy Materials, Faculty of Georesources and Materials Engineering, RWTH Aachen University, 52062 Aachen, Germany

Resume : Interfacial phenomena are one of the main drivers of the performance of various functional materials. A correct description of chemistry at the electrode/electrolyte interface or precipitation, dissolution and degradation processes of solid phases is a key factor for formulation of a solid scientific basis that is essential for design of novel energy materials and understanding of the underlying processes that determine the materials performance. With the aid of atomistic modeling we investigate the role of the aqueous solvent on the various interface phenomena in selected systems of importance for electrochemistry and nuclear waste management. In particular we discuss the impact of aqueous solvent phase on: (1) the CO2 reduction reaction pathways leading to catalysis of HCOOH on different metal surfaces, (2) the oxygen evolution reaction at the NiOOH catalyst [3] and (3) dissolution/precipitation processes in Ba/RaSO4 system [4]. In particular we discuss the advantages and limitations of the available hybrid density functional theory (DFT) – implicit solvation models computational methods, including the self consistent continuum solvation (SCCS) [5,6], VASPsol [7,8] and ESM-RISM [9] approaches. [1] Fan et al., ACS Catal. 10, 10726 (2020). [2] Ringe et al., Chem. Rev Article ASAP. (2020) [3] Eslamibidgoli et al., Electrochimica Acta, 398, 139253 (2021) [4] Bracco et al., J. Phys. Chem. C 121, 12236 (2017) [5] Andreussi et al., J. Chem. Phys. 136, 064102 (2012) [6] Giannozzi et al., J. Phys-Condens. Mat. 29, 465901 (2017) [7] Mathew et al., J. Chem. Phys. 140, 084106 (2014) [8] Mathew et al., J. Chem. Phys. 151, 234101 (2019) [9] Otani et al., Phys. Rev. B 96, 115429 (2017)

C.P1.7
17:30
Authors : Thomas Bornhake(1,2), Oskar Cheong(1,2,3) , Stefan Rudin(1) and Piotr M. Kowalski(1,2)
Affiliations : 1 Institute of Energy and Climate research (IEK-13, IEK-6), Forschungszentrum Jülich GmbH, 52425 Jülich, Germany 2 Jülich Aachen Research Alliance, JARA-CSD and JARA-ENERGY, 52425 Jülich, Germany 3 Chair of Theory and Computation of Energy Materials, Faculty of Georesources and Materials Engineering, RWTH Aachen University, 52062 Aachen, Germany

Resume : Interfacial phenomena are one of the main drivers of the performance of various functional materials. A correct description of chemistry at the electrode/electrolyte interface or precipitation, dissolution and degradation processes of solid phases is a key factor for formulation of a solid scientific basis that is essential for design of novel energy materials and understanding of the underlying processes that determine the materials performance. With the aid of atomistic modeling we investigate the role of the aqueous solvent on the various interface phenomena in selected systems of importance for electrochemistry and nuclear waste management. In particular we discuss the impact of aqueous solvent phase on: (1) the CO2 reduction reaction pathways leading to catalysis of HCOOH on different metal surfaces, (2) the oxygen evolution reaction at the NiOOH catalyst [3] and (3) dissolution/precipitation processes in Ba/RaSO4 system [4]. In particular we discuss the advantages and limitations of the available hybrid density functional theory (DFT) – implicit solvation models computational methods, including the self consistent continuum solvation (SCCS) [5,6], VASPsol [7,8] and ESM-RISM [9] approaches. [1] Fan et al., ACS Catal. 10, 10726 (2020). [2] Ringe et al., Chem. Rev Article ASAP. (2020) [3] Eslamibidgoli et al., Electrochimica Acta, 398, 139253 (2021) [4] Bracco et al., J. Phys. Chem. C 121, 12236 (2017) [5] Andreussi et al., J. Chem. Phys. 136, 064102 (2012) [6] Giannozzi et al., J. Phys-Condens. Mat. 29, 465901 (2017) [7] Mathew et al., J. Chem. Phys. 140, 084106 (2014) [8] Mathew et al., J. Chem. Phys. 151, 234101 (2019) [9] Otani et al., Phys. Rev. B 96, 115429 (2017)

C.P1.7
17:30
Authors : Cyprian Mieszczynski 1, Przemysław Jozwik 1, Frederico Garrido 2, Kazimierz Skrobas 1,3, Kamila Stefanska-Skrobas 1, Renata Ratajczak 1, Jacek Jagielski 1,4, Eduardo Alves 5, Katharina Lorenz 5,6
Affiliations : 1 National Centre for Nuclear Research, Soltana 7, 05-400 Otwock, Poland; 2 IJCLab, Université Paris-Saclay-CNRS, 91405 Orsay Campus, France; 3 Institute of High-Pressure Physics PAS, ul. Sokolowska 29/37, 01-142 Warsaw Poland; 4 Lukasiewicz Research Network - Institute of Microelectronics and Photonics, Wolczynska 133, 01-926 Warszawa, Poland; 5 Instituto de Plasmas e Fusão Nuclear, Instituto Superior Técnico-Campus Tecnológico e Nuclear, Universidade de Lisboa, Estrada Nacional 10, 2695-066 Bobadela, Portugal; 6 Instituto de Engenharia de Sistemas e Computadores – Microsistemas e Nanotecnologias, Rua Alves Redol 9, 1000-029 Lisbon, Portugal

Resume : The constant increase in electricity consumption forces the dynamic development of a new generation of nuclear and thermonuclear reactors hence, new materials resistant to specific operating conditions (high temperature, corrosive environment). Despite the other parameters, one of the most significant factors having the biggest impact on the materials (fuel, cladding, etc.) considered for nuclear power plants is the resistance to the creation of point and extended defects (including dislocations) coming from irradiation and fission products incorporation. The model of dislocations (based on the Peierls-Nabarro approach) assumes that the bending of atomic planes adjacent to an extra half-plane follows the arctan function. The coefficients of the function that decrease with the distance from the dislocation core are usually determined using high-resolution Transmission Electron Microscopy (TEM). However, since TEM analysis is destructive, expensive, and time-consuming, there is a need to determine dislocation parameters more reasonably. In this work, the recent studies on the modeling of edge dislocations and dislocation loops using Molecular Dynamics (LAMMPS code) for uranium dioxide that is currently used in nuclear reactors and nickel, one of the most promising materials regarding possible usage in a new generation of power plants are presented. The single-crystal structures were deformed by introducing extra half-planes of atoms and relaxed to stabilize the system. Bent planes were fitted using the arctan function to determine the function coefficients. Eventually, the parameters of dislocations were used in the McChasy 1.0 code to simulate RBS/C spectra recorded for irradiated UO2 and Ni single crystals.

C.P1.8
17:30
Authors : Cyprian Mieszczynski 1, Przemysław Jozwik 1, Frederico Garrido 2, Kazimierz Skrobas 1,3, Kamila Stefanska-Skrobas 1, Renata Ratajczak 1, Jacek Jagielski 1,4, Eduardo Alves 5, Katharina Lorenz 5,6
Affiliations : 1 National Centre for Nuclear Research, Soltana 7, 05-400 Otwock, Poland; 2 IJCLab, Université Paris-Saclay-CNRS, 91405 Orsay Campus, France; 3 Institute of High-Pressure Physics PAS, ul. Sokolowska 29/37, 01-142 Warsaw Poland; 4 Lukasiewicz Research Network - Institute of Microelectronics and Photonics, Wolczynska 133, 01-926 Warszawa, Poland; 5 Instituto de Plasmas e Fusão Nuclear, Instituto Superior Técnico-Campus Tecnológico e Nuclear, Universidade de Lisboa, Estrada Nacional 10, 2695-066 Bobadela, Portugal; 6 Instituto de Engenharia de Sistemas e Computadores – Microsistemas e Nanotecnologias, Rua Alves Redol 9, 1000-029 Lisbon, Portugal

Resume : The constant increase in electricity consumption forces the dynamic development of a new generation of nuclear and thermonuclear reactors hence, new materials resistant to specific operating conditions (high temperature, corrosive environment). Despite the other parameters, one of the most significant factors having the biggest impact on the materials (fuel, cladding, etc.) considered for nuclear power plants is the resistance to the creation of point and extended defects (including dislocations) coming from irradiation and fission products incorporation. The model of dislocations (based on the Peierls-Nabarro approach) assumes that the bending of atomic planes adjacent to an extra half-plane follows the arctan function. The coefficients of the function that decrease with the distance from the dislocation core are usually determined using high-resolution Transmission Electron Microscopy (TEM). However, since TEM analysis is destructive, expensive, and time-consuming, there is a need to determine dislocation parameters more reasonably. In this work, the recent studies on the modeling of edge dislocations and dislocation loops using Molecular Dynamics (LAMMPS code) for uranium dioxide that is currently used in nuclear reactors and nickel, one of the most promising materials regarding possible usage in a new generation of power plants are presented. The single-crystal structures were deformed by introducing extra half-planes of atoms and relaxed to stabilize the system. Bent planes were fitted using the arctan function to determine the function coefficients. Eventually, the parameters of dislocations were used in the McChasy 1.0 code to simulate RBS/C spectra recorded for irradiated UO2 and Ni single crystals.

C.P1.8
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Atomistic modeling of complex hybrid and biological systems: materials and interfaces : Yannick Dappe
08:30
Authors : Danila AMOROSO
Affiliations : Université de Liège, NanoMat/Q-mat/CESAM, B-4000 Liège, Belgium

Resume : There is currently an increasing enthusiasm towards long-range magnetic order and multiferroicity in two-dimensional (2D) materials both from the fundamental and applicative point of view. In this respect, by means of first-principles-based simulations, we investigated magnetic properties in a single-layer of some of the triangular 3d transition metal dihalides [1], which belong to the promising class of van der Waals materials, with a special focus on the exotic NiI2 case [2,3]. Through also supporting Monte Carlo simulations, we show that a thermodynamically-stable skyrmionic lattice with a well-defined topology and chirality of the spin texture in absence of Dzyaloshinskii–Moriya (DM) and Zeeman interactions, can be stabilized by the anisotropic part of the short-range symmetric exchange, related to the relevant spin-orbit coupling (SOC) of the heavy ligands, assisted only by the exchange frustration. In detail, the symmetric anisotropic exchange tensor, also referred to as two-ion anisotropy (TIA), shows large off-diagonal terms, which - due to the peculiar non-coplanar arrangement of the spin-ligand plaquettes- induce frustration in the relative orientation of spins by setting non-coplanar principal axes. Combined with the exchange frustration from competing ferromagnetic first- and antiferromagnetic third-neighbor interactions, this results in a not-trivial spin-configuration with well-defined topology, making the TIA acting as an emergent chiral interaction. Particularly, in the centrosymmetric NiI2 monolayer, we predicted a spontaneous high-Q antiskyrmionic lattice (|Q|=2) with fixed chirality, undergoing a topological phase transition, under magnetic field, to a more conventional skyrmion lattice (|Q|=1). Additionally, we predicted a competing noncollinear single-q helimagnetic state, exhibiting low-dimensional magnetoelectric and multiferroic properties. Such a multiferroic state in single-layer NiI2 has been also experimentally detected by combined birefringence and second-harmonic-generation measurements [4]. Such findings, on the one hand, propose a novel mechanism able to drive stabilization of topological spin structures in magnetic semiconductors with short-range anisotropic interactions. On the other hand, they open the street towards new low-dimensional magnetoelectrics and/or multiferroics. References: [1] K. Riedl, D. Amoroso et al. “Microscopic origin of magnetism in monolayer 3d transition metal dihalides”. ArXiv:2206.00016 (2022) [2] D. Amoroso, P. Barone & S. Picozzi, “Spontaneous skyrmionic lattice from anisotropic symmetric exchange in a Ni-halide monolayer”. Nature Communications 11, 5784 (2020) [3] D. Amoroso, P. Barone and S. Picozzi. “Interplay between Single-Ion and Two-Ion Anisotropies in Frustrated 2D Semiconductors and Tuning of Magnetic Structures Topology”. Nanomaterials, 11(8), 1873 (2021) [4] Q. Song, […] , D. A. et al. “Evidence for a single-layer van der Waals multiferroic”. Nature, 601, 602 (2022)

C.6.1
08:30
Authors : Danila AMOROSO
Affiliations : Université de Liège, NanoMat/Q-mat/CESAM, B-4000 Liège, Belgium

Resume : There is currently an increasing enthusiasm towards long-range magnetic order and multiferroicity in two-dimensional (2D) materials both from the fundamental and applicative point of view. In this respect, by means of first-principles-based simulations, we investigated magnetic properties in a single-layer of some of the triangular 3d transition metal dihalides [1], which belong to the promising class of van der Waals materials, with a special focus on the exotic NiI2 case [2,3]. Through also supporting Monte Carlo simulations, we show that a thermodynamically-stable skyrmionic lattice with a well-defined topology and chirality of the spin texture in absence of Dzyaloshinskii–Moriya (DM) and Zeeman interactions, can be stabilized by the anisotropic part of the short-range symmetric exchange, related to the relevant spin-orbit coupling (SOC) of the heavy ligands, assisted only by the exchange frustration. In detail, the symmetric anisotropic exchange tensor, also referred to as two-ion anisotropy (TIA), shows large off-diagonal terms, which - due to the peculiar non-coplanar arrangement of the spin-ligand plaquettes- induce frustration in the relative orientation of spins by setting non-coplanar principal axes. Combined with the exchange frustration from competing ferromagnetic first- and antiferromagnetic third-neighbor interactions, this results in a not-trivial spin-configuration with well-defined topology, making the TIA acting as an emergent chiral interaction. Particularly, in the centrosymmetric NiI2 monolayer, we predicted a spontaneous high-Q antiskyrmionic lattice (|Q|=2) with fixed chirality, undergoing a topological phase transition, under magnetic field, to a more conventional skyrmion lattice (|Q|=1). Additionally, we predicted a competing noncollinear single-q helimagnetic state, exhibiting low-dimensional magnetoelectric and multiferroic properties. Such a multiferroic state in single-layer NiI2 has been also experimentally detected by combined birefringence and second-harmonic-generation measurements [4]. Such findings, on the one hand, propose a novel mechanism able to drive stabilization of topological spin structures in magnetic semiconductors with short-range anisotropic interactions. On the other hand, they open the street towards new low-dimensional magnetoelectrics and/or multiferroics. References: [1] K. Riedl, D. Amoroso et al. “Microscopic origin of magnetism in monolayer 3d transition metal dihalides”. ArXiv:2206.00016 (2022) [2] D. Amoroso, P. Barone & S. Picozzi, “Spontaneous skyrmionic lattice from anisotropic symmetric exchange in a Ni-halide monolayer”. Nature Communications 11, 5784 (2020) [3] D. Amoroso, P. Barone and S. Picozzi. “Interplay between Single-Ion and Two-Ion Anisotropies in Frustrated 2D Semiconductors and Tuning of Magnetic Structures Topology”. Nanomaterials, 11(8), 1873 (2021) [4] Q. Song, […] , D. A. et al. “Evidence for a single-layer van der Waals multiferroic”. Nature, 601, 602 (2022)

C.6.1
09:00
Authors : Clemence DEFEBVRE and Fabrizio CLERI*
Affiliations : University of Lille, IEMN and Department of Physics, 59652 Villeneuve d'Ascq (France)

Resume : Proteins are large and complex molecules essential for life. The recipes, or "assembly manuals" for proteins (ie, genes) are encoded in our DNA. But DNA only contains information about the basic chemical sequence of the protein, not its three-dimensional structure, that is how the atoms fold into a functional shape. As demonstrated by the "Levinthal paradox", it would take longer than the age of the Universe to randomly enumerate all possible configuration for a even a small protein, before finding its true 3D structure; yet, proteins fold spontaneously and exactly within milliseconds. Decades of research have made it possible to experimentally determine the shape of some proteins in the laboratory, by cryo-electron microscopy, nuclear magnetic resonance and X-ray crystallography, but each method requires years of work, and may cost tens or hundreds of thousands of euros, for each new protein. This is why we turn today to numerical methods of protein modelling and computer simulation based on artificial intelligence, the "Golem". In this talk, we will firstly introduce some generalities on proteins, DNA and the folding problem; then show benchmark results obtained with both molecular dynamics (direct exploration of the conformation space) and classic homology methods; and finally, move to recent techniques using deep-learning methods, publicly available as AlphaFold and RosettaFold. Examples of both "simple" and "difficult" proteins will be used as showcase applications. Open problems, such as protein-protein and protein-DNA interacting complexes will be also highlighted.

C.6.2
09:30
Authors : Oskar Cheong [1;2;3], Michael H. Eikerling [1;2], Piotr M. Kowalski [1;2]
Affiliations : 1 Theory and Computation of Energy Materials (IEK-13), Forschungszentrum Jülich GmbH, 52425 Jülich, Germany; 2 Jülich Aachen Research Alliance, JARA-CSD and JARA-ENERGY, 52425 Jülich, Germany; 3 Chair of Theory and Computation of Energy Materials, Faculty of Georesources and Materials Engineering, RWTH Aachen University, 52062 Aachen, Germany;

Resume : Realistic modeling of solid/aqueous interface is a main challenge for computational electrochemistry. Structuring of water at metal surfaces determines the local reaction conditions and electrocatalytic performance of a metal electrocatalyst. While ab initio molecular dynamics methods (AIMD) can be applied for investigation of surface water structures, being computationally intensive, these have severe limitations regarding simulated time- and length-scales. To overcome these limitations, we tested the capability of Interface Force Fields (IFF) with SPC water model [1] to reproduce the water structure at Pb (100) and (111) surfaces [2], for which a reference AIMD exist [3]. With the same simulation setup as the one used in the AIMD simulations (simulation time of 8 ps and simulated 2x2 surface unit cell), we reproduced the water structure simulated by AIMD. However, with much longer simulation times permitted by classical molecular dynamics (CMD, up to 1 ns) we obtained substantially different water structure, which stability was confirmed with subsequent DFT calculations. We found that to simulate realistic water structure, one needs to allow for equilibration time of at least a few hundred ps. Also, at least 4x4 surface unit cell must be applied in the simulations to prevent overstructuring of surface water layer due to small simulated cell size. Although the CMD allows for overcoming of the AIMD limitations, we will discuss the limitations of the method resulting from less accurate description of the metal surface – water interactions. [1] Heinz et al., Langmuir. 29, 1754 (2013). [2] Cheong et al., Appl. Surf. Sci. 589, 152838 (2022). [3] Lin et al., Beilstein J. Nanotechnol. 7, 533 (2016).

C.6.3
09:45
Authors : Irene AMIEHE ESSOMBA 1*, Guido ORI 1, Mauro BOERO 1,2
Affiliations : 1. Université de Strasbourg, CNRS, Institut de Physique et Chimie des Matériaux de Strasbourg, UMR 7504, F-67034 Strasbourg, France 2 2. Institute of Materials and Systems for Sustainability, Nagoya University, Nagoya 464-8601, Japan

Resume : This study focuses on establishing a computational procedure combining classical and first- principles molecular dynamics (CMD and FPMD respectively) to explore the complex interface interactions created by ionic liquids (ILs) deposited on the top of a 2D semiconductor material arranged Van der Waals layers of the TMDC type such as MoS2. The combination of IL with such 2D materials has been shown to promote exotic phenomena that could revolutionize the next generation of electronic devices (triboiontronics transistors[1], quantum interference[2], superconductivity[3], emerging memory devices for neuromorphic computing[4,5], electronic double layer transistors[6]). However, key questions remain unanswered about the specific interactions occurring between ILs and 2D materials. This work provides microscopic insight into a series of imidazolium-based IL (C1-6 MIM+ ; Cl- ,BF4- ,PF6- and TFSI-) in the bulk phase and at the interface with MoS2 layers. A detailed assessment of the structural properties (radial distribution functions, coordination analysis, ions, and charge density profiles), electronic structure and ion dynamics will be provided to explain the complex interplay of the interactions occurring in these systems. Combining classical and first-principles molecular dynamics allows targeting different size and time scales involved in these systems. Whenever possible, our theoretical results are discussed together with the available experimental findings. References: [1] G. Gao et al., Adv. Mater. 2019, 31.7, 1806905. [2] C. Jia et al., Sci. Adv. 2018, 4, 1-8 [3] J.T Ye et al. Science, 2012, 338, 1193-1196 [4] Zhang Y et al. Nat. Nanotechnol. 2014, 9, 372–377 [5] J. Joshua Yang et al. Adv. Mater Technol. 2019, 4, 1800589 [6] Kis A et al. Nature Nanotech. 2011, 6,147–150,

C.6.4
10:00
Authors : Aleksandr Shkatulov, Emre Genç, Ionut Tranca
Affiliations : German Aerospace Center ? DLR e.V., Institute of Engineering Thermodynamics, Pfaffenwaldring 38-40, 70569 Stuttgart, Germany; Gazi University, Faculty of Science, Department of Physics, Ankara, Turkey; Vrije Universiteit Brussel. Department of Chemistry (DSCH), Group Algemeine Chemie (ALGC),Brussels, Belgium

Resume : Storage and utilization of waste and renewable heat is crucial for implementation of sustainable energy systems of the future. Supply-demand mismatch for thermal energy hampers use of renewable energies and leads to waste of several exajoules of heat annually[1]. Thermal energy storage is one of the crucial technologies of thermal management, with thermochemical energy storage (TCES) providing the most advanced toolbox for storing and upgrading thermal energy[2]. Storage of thermal energy by means of reversible chemical reactions provides high energy storage density (comparable to modern Li-Ion batteries), very high storage duration, and allows thermal energy upgrade. All these features make this emerging technology attractive for domestic, renewable and industrial applications. The two processes popular for TCES at medium (200-500oC) and high (>500oC) temperatures are hydration/dehydration (MO + H2O = M(OH)2) and carbonation/decarbonation (MO + CO2 = MCO3) of metal oxides. To this day, only M = Ca, Mg have been extensively explored for both processes, and the proof of concept for TCES at medium temperatures was demonstrated [3]. One of the major reasons for such scarcity of candidates is the lack of thermodynamic data for hydration of oxides which would allow a guided screening for such materials. In this work, we develop an approach for high-throughput screening of oxides potentially promising for TCES at medium temperatures based on a reactivity descriptor. The descriptor for the set of 41 oxide-hydroxide conversion enthalpies was trained by using the SISSO algorithm of symbolic regression [4] with electronic properties of the oxides as inputs (i.e. primary features). The electronic primary features were calculated by using Kohn-Sham Density Functional Theory as implemented in the VASP code [5] followed by chemical bonding analysis by using the topological method developed by Bader [6]. In the developed method, only local properties of oxygen environment, such as the Bader charge and atomic volume of oxygen, were used for the training, which will allow the usage of this approach for any oxide. The resulted models were filtered based on criteria of physical constraints and 5-fold cross-validation. The final models give the RMSE of 10.5 kJ/mol/O for the training and cross-validation error of 12.5 kJ/mol, which would allow selection of prospective materials for TCES at T > 300oC potentially predicting the shift temperature with the accuracy of 60-70K. The resultant models were applied for the set of 83 binary and ternary oxides of earth-abundant elements to identify several prospective candidates for TCES. [1] Luberti M. et al. Energy 2022;238:121967. [2] Stengler J. et al. Applied Energy 2020;262:114530. [3] Sunku Prasad J. Applied Energy 2019;254:113733. [4] Ouyang R. et al. Physical Review Materials 2018;2. [5] Kresse G., et al. Phys Rev B 1996;54:11169?86. [6] Henkelman G. et al Comp. Mat. Sci. 2006;36:354?60.

C.6.6
10:15
Authors : Alaa Nahhas (a) and Thomas J. Webster (b)
Affiliations : a) Biochemistry Department, College of Science, King Abdulaziz University, Jeddah 21589, Saudi Arabia and the b) Universidade Federal do Piauí, Teresina, Brazil; Vellore Institute of Technology, Vellore, India; and Hebei University of Technology, Hebei, China

Resume : Nanomedicine has revolutionized medicine through the development of materials (such as nanoparticles, nanotubes, self-assembled nano materials, nano textured surfaces, etc.) that can penetrate skin and tissues, target intracellular components, selectively kill cancer cells, increase tissue growth, limit inflammation, inhibit infection, and more. However, predictive computational modeling has not been widely utilized in nanomedicine to date despite the fact that nanoscale events can be modeling through molecular dynamics as well as other more sophisticated approaches. This presentation will cover 25 years of research to computationally model nanomaterial interactions with tissues, cells, bacteria, and viruses (including SARS-CoV-2 that leads to COVID). It will cover what computational models work and what models do not work for developing nanomaterials that can improve disease prevention, detection, and treatment. It will further cover how such models can predict initial protein interactions and bioactivity with nanomaterials to enhance their ability to penetrate tumors, kill cancer cells and more. This presentation will also cover how such computational models can be used to predict in vivo events, such as tissue growth for orthopedic, cardiovascular, tendon, and other applications. Lastly, this presentation will emphasize what is needed for predictive computation models to become the normal in medicine, to create new emerging fields such as personalized medicine where nanomaterials can be tailored for specific patients, for which we are far away from today.

C.6.5
10:30 Coffee break    
 
Material design, comprehension and application by atomistic modeling: 2d materials, films and alloys -II : Michal Hermanowicz
11:00
Authors : František Karlický
Affiliations : Department of Physics, University of Ostrava, 30. dubna 22, 701 03 Ostrava, Czech Republic

Resume : The optical properties of two-dimensional (2D) materials are accurately described by many-body methods including specifically pronounced electron-electron and electron-hole effects. We used both accurate GW BSE calculations (computationally demanding and applicable on small computational cells only [1]) and time-dependent density functional theory (TD-DFT) based on specific screened hybrid functional (an approach that effectively accounts for all important physical effects including excitons [2]) to investigate the optical and excitonic properties of two-dimensional transition metal carbides, MXenes. We determined reliable optical gaps, optical absorbance spectra, and exciton features for a set of semiconducting MXenes containing 3d metals [3]. The optical gaps of Sc2CF2, Cr2CF2, Cr2C(OH)2, and anti-ferromagnetic Mn2CO2 (1.9 - 2.3 eV) lie in the energy region of visible (VIS) light. Sc2C(OH)2, Ti2CO2, and ferromagnetic Mn2CO2 with smaller optical gaps (0.4 - 1.2 eV) well absorb solar radiation, including VIS light. Moreover, Ti2C and ferromagnetic Mn2CO2 show high monolayer absorbance of 10 - 20% in the 1 - 3 eV energy range. Finally, we analyze the excitons in considered MXenes and find that the first bright excitons of Sc- and Ti-based MXenes are strongly localized in k-space while the corresponding excitons of Cr- and Mn-based systems are delocalized. References: [1] Dubecky M., Karlicky F., Minarik S., Mitas L.: J. Chem. Phys. 153(18), 184706 (2020) [2] Ketolainen T., Machacova N., Karlicky F.: J. Chem. Theory Comput. 16(9), 5876 (2020) [3] Ketolainen T., Karlicky F.: J. Mater. Chem. C, 10(10), 3919 (2022)

C.7.1
11:30
Authors : Asghar Aryanfar, Abdel Rahman El Tallis Jaime Marian
Affiliations : American University of Beirut Arizona State University University of California, Los Angeles

Resume : The corrosion in the pipelines of pressurized water reactor is a catastrophic event, leading to the ultimate fracture and failure. Herein, we develop a real-time framework for the accumulation of compressive stresses via coupling corrosion-induced and the internal/external fluid pressure, where the former causes the irreversible (plastic) deformation the latter leads to the reversible (elastic) compression. In this regard, we quantify the real-time infiltration of the oxygen within the metal matrix in the curved boundary, leading to the augmentation in the volume and we compute stoichiometrically the resulted equivalent oxide thickness. Subsequently, we compute the accumulated compressive stress in real time from both elastic and plastic events which could be used as a measure for anticipation of the onset of mechanical failure. The developed analytical framework could be utilized for quantifying the design parameters for safe operation of the transport pipes, particularly in applications related to the high-pressure and highly-corrosive environments.

C.7.2
12:00
Authors : D. Raciti1, G. Calogero1, R. Anzalone2, G. Morale2, D. Murabito2, G. Fisicaro1, I. Deretzis1, A. La Magna1
Affiliations : 1 CNR Institute for Microelectronics and Microsystems (CNR-IMM), Catania, Italy; 2 STMicroelectronics, Catania, Italy

Resume : Chemical Vapor Deposition (CVD) epitaxy is the method of choice to produce high-quality layers in semiconductor-based industrial applications. The demand for increasing performances at contained costs motivates the design of modelling strategies able to accurately predict growth rates and structure morphology. Lattice Kinetic Monte Carlo (LKMC) modelling is a standard approach for Si, SiGe, and Ge epitaxy and has been implemented within state-of-the-art TCAD process models. A delicate point is the multi-step nature of epitaxial processes, characterized by multiple chemical reactions occurring in the vapor phase and at the solid-vapor phase boundary, which must be taken into account for reliable simulations. We present a method for predicting the CVD growth (or etching) of SiGe-based structures, based on the open-source Kinetic Monte Carlo super-Lattice (KMCsL) code “MulSKiPS”, designed by our group to study at atomic resolution the growth kinetics of materials with sp3 bond symmetry [1,2,3]. Due to the super-lattice nature of the code, the evolution of point-like and extended defects can be simulated as a function of the initial substrate conditions, without labelling the substrate lattice points. In addition, the morphology evolution during the epitaxial processes can be simulated, correlating morphology and defect kinetics. The definition and calibration of the active MC events is a key element of the method. In our latest implementation, gas-phase reactions are preliminarily evaluated via the open-source software Cantera [4]. The surface reactions involving the gas species at equilibrium are then modelled by an analytical (continuum) model. Finally, the outputs are translated into MC rate event equations, in terms of absorption-desorption and attachment-detachment atomistic processes, and calibrated against experimental data. We discuss the method, illustrating the dependence of growth rates on process parameters, such as the nature and pressure of gas precursors, temperature and substrate orientation. Case studies include the growth of Si flat vs patterned substrates, and variously shaped nanoparticles. Quantitative predictions of the microstructural evolution of the studied systems can be compared with the growth kinetics and structural characterization of actual samples, obtained in collaboration with STMicroelectronics. We gratefully acknowledge funding from the EU Horizon 2020 Research and Innovation programme under grant agreement No. 871813 MUNDFAB. [1] https://github.com/MulSKIPS/MulSKIPS [2] G. Fisicaro, C. Bongiorno, I. Deretzis, F. Giannazzo, F. La Via, F. Roccaforte, M. Zielinski, M. Zimbone, A. La Magna, Appl. Phys. Rev. 7.2 (2020): 021402. [3] G. Calogero, D. Raciti, P. Acosta-Alba, F. Cristiano, I. Deretzis, G. Fisicaro, K. Huet, S. Kerdilès, A. Sciuto, A. La Magna, npj Comput. Mater. 8.1 (2022): 1-10. [4] https://cantera.org/index.html

C.7.3
12:15
Authors : Vladimir Lipp, Victor Tkachenko, Michal Stransky, Bálint Aradi, Thomas Frauenheim, and Beata Ziaja
Affiliations : Vladimir Lipp(1,2), Victor Tkachenko(3,1,2), Michal Stransky(3,4), Bálint Aradi(5), Thomas Frauenheim(5,6,7), and Beata Ziaja(2,1) (1) Institute of Nuclear Physics, Polish Academy of Sciences, 31-342 Krakow, Poland (2) Center for Free-Electron Laser Science CFEL, DESY, 22607 Hamburg, Germany (3) European XFEL, 22869 Schenefeld, Germany (4) Institute of Physics of the Czech Academy of Sciences, 182 21 Prague, Czech Republic 95) Bremen Center for Computational Materials Science, Universitaet Bremen, 28359 Bremen, Germany (6) Shenzhen JL Computational Science and Applied Research Institute, Shenzhen 518110, China (7) Beijing Computational Science Research Center, Beijing 100193, China

Resume : Modern computer simulations of structural transitions in solid materials became essential to characterize material properties and to support experimental findings. The high cost of ab initio simulation limits its applicability and makes empirical approaches necessary for larger computational supercells and/or longer timescales, which may be relevant for materials design. Here, we present a simulation tool based on Density Functional Tight Binding developed to study X-ray- and XUV-induced phase transitions in a broad range of solid materials, including complex materials. This is possible due to the modular structure of the tool and utilization of the well-known code, DFTB+ [1], to follow band structure evolution of the irradiated targets. The suggested computational scheme allows to simulate NVE thermodynamic ensemble for both atomic and electronic subsystems, which should make it also relevant for laser material processing and other applications. The outstanding performance of the implementation is demonstrated with a comparative study of the XUV-induced graphitization in diamond [2]. [1] https://dftbplus.org. [2] Lipp et al., Sci. Rep. 12, 1551 (2022).

C.7.4
12:15
Authors : Vladimir Lipp, Victor Tkachenko, Michal Stransky, Bálint Aradi, Thomas Frauenheim, and Beata Ziaja
Affiliations : Vladimir Lipp(1,2), Victor Tkachenko(3,1,2), Michal Stransky(3,4), Bálint Aradi(5), Thomas Frauenheim(5,6,7), and Beata Ziaja(2,1) (1) Institute of Nuclear Physics, Polish Academy of Sciences, 31-342 Krakow, Poland (2) Center for Free-Electron Laser Science CFEL, DESY, 22607 Hamburg, Germany (3) European XFEL, 22869 Schenefeld, Germany (4) Institute of Physics of the Czech Academy of Sciences, 182 21 Prague, Czech Republic 95) Bremen Center for Computational Materials Science, Universitaet Bremen, 28359 Bremen, Germany (6) Shenzhen JL Computational Science and Applied Research Institute, Shenzhen 518110, China (7) Beijing Computational Science Research Center, Beijing 100193, China

Resume : Modern computer simulations of structural transitions in solid materials became essential to characterize material properties and to support experimental findings. The high cost of ab initio simulation limits its applicability and makes empirical approaches necessary for larger computational supercells and/or longer timescales, which may be relevant for materials design. Here, we present a simulation tool based on Density Functional Tight Binding developed to study X-ray- and XUV-induced phase transitions in a broad range of solid materials, including complex materials. This is possible due to the modular structure of the tool and utilization of the well-known code, DFTB+ [1], to follow band structure evolution of the irradiated targets. The suggested computational scheme allows to simulate NVE thermodynamic ensemble for both atomic and electronic subsystems, which should make it also relevant for laser material processing and other applications. The outstanding performance of the implementation is demonstrated with a comparative study of the XUV-induced graphitization in diamond [2]. [1] https://dftbplus.org. [2] Lipp et al., Sci. Rep. 12, 1551 (2022).

C.7.4
12:30 Lunch break    
14:00 Poster (Session 2) 3min Flash presentations    
 
Poster Session 2 : Elena Levchenko and Yannick Dappe
17:30
Authors : F. J. Dominguez-Gutierrez(1,2), A. Aligayev(1), Q. Q. Xu(1), W. Y. Huo(1,3), S. Papanikolaou(1), M. Alava(1,4)
Affiliations : (1) NOMATEN CoE, National Centre for Nuclear Research, ul. A. Soltana 7, 05-400 Otwock, Poland; (2) Institute for Advance Computational Science, Stony Brook University, Stony Brook, NY 11749, USA; (3) College of Mechanical and Electrical Engineering, Nanjing Forestry University, Nanjing, 210037, China; (4) Department of Applied Physics, Aalto University, P.O. Box 11000, Aalto, 00076, Finland

Resume : The most thermodynamically stable form of aluminum oxide is alpha-Al2O3 or corundum form with a hexagonal close-packed (hcp) atomic arrangement. This material has been applied in medical, coatings, and electronic use. However, alumina can be exposed to different environments during manufacturing. In this work, we explore effects of O2, H2O, and CO2 adsorption on the electronic and mechanical properties of alpha alumina at room temperature for applications at extreme operating conditions industries like nuclear energy. In order to model the adsorption process, we perform quantum-classical molecular dynamics (QCMD) simulations by using the self-consistent-charge density-functional tight-binding (SCC-DFTB) approach, which offers a reduced complexity DFT method, being derived from a simplification of Kohn-Sham DFT to a tight binding form. Thus, we consider three cases of oxygen contamination by exposing the corundum surface to hundreds of O2, H2O, and CO2 molecules for 500 ps at room temperature where chemisorption process is tracked. Our QCMD calculations are however validated by nudged elastic band (NEB) DFT computations with Quantum Espresso considering the bonding energy of the molecules at different adsorption points of the surface. We report modifications of electronic and mechanical properties of alpha alumina after exposure to different atmospheres by computing the electronic density of states (DOS) and band structure, as well as tracking surface morphology and atomic strain mapping due to the molecular adsorption.

C.P2.1
17:30
Authors : P. Kwasniak(1) , F. Sun(2) , S. Mantri(3) , R. Banerjee(3), F. Prima(2)
Affiliations : (1). Center of Digital Science and Technology, Cardinal Stefan Wyszynski University in Warsaw, Woycickiego 1/3, 01-938 Warsaw, Poland (2). PSL Research University, Chimie ParisTech, CNRS, Institut de Recherche de Chimie Paris, 75005, Paris, France (3). Department of Materials Science and Engineering, University of North Texas, Denton, TX, 76207, USA

Resume : The shear-shuffle mechanism of {332}<113>β twinning is explored in detail with a particular focus on transformation trajectory on an atomic scale. We found that initial modulation of the β structure towards α′′ does not reduce the energy barrier of twinning transition and thus is not required as a separate, initial stage of plastic deformation, as proposed previously. Instead, the lattice strains and atomic shuffling needed to form α′′ are provided by {332}<113>β twinning itself. This dual nature of twin transformation arises from the fact that both β→βT and β→α′′ reconfigurations operate over the same set of atomic planes but use different displacement directions. As a result, a linear path of twinning transition produces the distorted α′′ structure. However, since the shear-shuffle mechanism involves the displacement of atoms along and perpendicular to the shearing direction, the accompanying relaxation of the structure is pronounced and strongly related to the chemical composition of the deformed alloy. Because of that, the minimum energy path of {332}<113>β twinning is far from rigid linear transformation, allowing to stabilize the α′′ or promoting a direct β→βT transition, depending on the β phase stability. The presented results provide extended knowledge about {332}<113>β twinning from a previously reported mechanism occurring in superelastic alloys to a broad group of Ti-based TWIP materials and uncover the unique, polymorphic nature of the studied twin mode also acting as a new mechanism of β→α′′ martensitic transformation.

C.P2.2
17:30
Authors : Jiri Kalmar, Frantisek Karlicky
Affiliations : Department of Physics, University of Ostrava, 30. dubna 22, 701 03 Ostrava, Czech Republic

Resume : We have recently shown that Mn-based MXenes are promising for (opto)electronic applications and that their properties are strongly influenced by the intrinsic magnetic state[1]. Further, unusual magnetic properties make the Mn2CF2 MXene an optimal material for applications in spintronics[2]. We present here a thorough study of magnetism in Mn2CO2 MXene using larger magnetic supercells. We show that different structural and spin isomers are energetically very close with total energy differences reaching up to 0.01 eV. The electronic properties in presented isomers vary significantly, with the band gap ranging from 0.70 eV to 0 eV in isomers with metallic behavior. Our predictions, using standard generalized gradient approximation (GGA) to density functional theory (DFT), were also extended using selected hybrid and meta-GGA functionals. Small energy differences imply that the magnetic phase of Mn2CO2 MXene can change by small external pressure, i.e., completely change its properties and potential use. References: [1] Ketolainen T., Karlicky F.: J. Mater. Chem. C 10, 3919 (2022) [2] He J., Lyua P., Nachtigall P.: J. Mater. Chem. C 4, 11143 (2016)

C.P2.3
17:30
Authors : Cyprian Sobczak, Piotr Kwaśniak
Affiliations : -Center of Digital Science and Technology, Cardinal Stefan Wyszynski University in Warsaw, Warsaw, Poland. (Cyprian Sobczak, Piotr Kwaśniak) -Institute of High Pressure Physics, of the Polish Academy of Sciences, Warsaw, Poland.(Cyprian Sobczak )

Resume : This study presents the theoretical results of adoption the electronic-based approach to design elastically isotropic and metastable β-Ti alloys with empirical validation of their structure and mechanical properties. The ab initio calculations were performed to predict the elastic properties of investigated systems and to clarify the influence of the band structure contribution to other electronic- and ionic-driven interactions which control the stability and mechanical properties of transition metal alloys with body centered cubic structure. Based on the two phase stability diagrams the binary Ti-V, Ti-Mo and ternary Ti-Fe-Cr, Ti-Fe-V lightweight systems were analyzed. It was found that selected alloys with adjusted chemical composition are essentially elastically isotropic with anisotropy ratio close to 1. Electronic structure investigation allows to unveil that such properties arise from the well balanced ionic-ionic and electronic-ionic iterations together with transition from covalent to metallic bonding character taking place at specific electron-to-atom ratio.

C.P2.4
17:30
Authors : F. Djeffal1, H. Ferhati1,2, A. Benyahia1 and Z. Dibi 3
Affiliations : 1 LEA, Department of Electronics, University of Batna 2, Batna 05000, Algeria 2 ISTA, University of Larbi Ben M’hidi, Oum El Bouaghi, Algeria 3 University of Larbi Ben M’hidi, Oum El Bouaghi, Algeria

Resume : Tin Sulfide (SnS) is emerged as interest and suitable material for thin films solar cells (TFSCs) due to its appropriate band gap energy (about 1.3 eV), high absorption coefficient and its native p-type conductivity. In this paper, SnO2 electron transport layer incorporating doping effects is proposed as a prospective buffer layer to improve the optoelectronic performances of SnS TFSCs. The impact of the doping on the optoelectronic properties of SnO2 buffer layer is analyzed using Density Functional Theory (DFT) calculations, including Perdew-Burke-Ernzerhof Generalized Gradient Approximation (PBE-GGA). It is revealed that the optical and electronic properties of SnO2 were substantially affected by the doping types and values, where the band gap energy decreases with increasing the doping. Moreover, it is found that the proposed buffer layer can provide enhanced electronic energy alignment and decreased optoelectronic losses, making it an alternative to the conventional toxic and CdS-based buffer layers for developing low cost and high-performance non-toxic SnS solar cells.

C.P2.5
17:30
Authors : Oskar Cheong [1;2;3], Joachim Pasel [4], Johannes Häusler [4], Ralf Peters [4], Piotr M. Kowalski [1;2]
Affiliations : 1 Theory and Computation of Energy Materials (IEK-13), Forschungszentrum Jülich GmbH, 52425 Jülich, Germany; 2 Jülich Aachen Research Alliance, JARA-CSD and JARA-ENERGY, 52425 Jülich, Germany; 3 Chair of Theory and Computation of Energy Materials, Faculty of Georesources and Materials Engineering, RWTH Aachen University, 52062 Aachen, Germany; 4Institute of Energy and Climate Research, Electrochemical Process Engineering (IEK-14), Forschungszentrum Jülich GmbH, 52425 Jülich, Germany;

Resume : In times of growing energy consumption and decreasing fossil feedstock, ethanol has become a potential renewable educt that can be catalytically converted to other organic products and intermediates such as methane, acetaldehyde, ethylene and other compounds. In order to get a better understanding of ethanol dehydrogenation reaction on a Pt/C catalyst, we performed both theoretical and experimental studies on this catalyst. Using Density Functional Theory (DFT) we have computed adsorption energies and activation barriers for the underlying ethanol dehydrogenation reaction in order to validate and explain the trends observed experimentally [1]. Good match to the measured adsorption energies was obtained. We discuss the reasoning behind desorption of CO – a species strongly bounded to the Pt surface. We show how a combined DFT/experimental effort can lead to an improved understanding of simple catalytic processes on metal catalysts. [1] Pasel et al., Catalysts 10, 1151 (2020).

C.P2.6
17:30
Authors : G. Calogero [1], D. Raciti [1], I. Deretzis [1], G. Fisicaro [1], A. Sciuto [1,5], P. Acosta-Alba [2], K. Huet [4], S. Kerdilès [2], F. Cristiano [3], A. La Magna [1]
Affiliations : [1] CNR-IMM, Zona Industriale VIII Strada 5, 95121 Catania, Italy [2] Université Grenoble Alpes, CEA-LETI, 38000 Grenoble, France [3] LAAS, CNRS and Université de Toulouse, 7av. Du Col. Roche, 31400 Toulouse, France [4] Laser Systems & Solutions of Europe (LASSE), 145 rue des Caboeufs, 92230 Gennevilliers, France [5] Dipartimento di Fisica e Astronomia, Università di Catania, Via Santa Sofia 64, 95125 Catania, Italy

Resume : Heating and melting solid materials over small space- and time-scales is a way to access the early stages of the melting phenomenon. Nanosecond-pulsed laser annealing (LA) is a powerful processing tool for both fundamental investigations of molten phase ultra-rapid kinetics and technological applications, such as nanoscale reshaping, or alloy fraction and defects manipulation, which are crucial for the fabrication of unconventional 3D sequentially integrated devices. Being able to predict with atomic resolution the effects of such ultrafast non-equilibrium melting phenomena is key to control the LA process parameters and design nanoscale devices with tailored features. However state-of-the-art LA process simulators, mostly based on continuum models, are blind to such fine details. In this contribution a multiscale hybrid approach is presented, coupling a µm-scale continuum model for laser-matter interaction and thermal diffusion with an atomistic Kinetic Monte Carlo code, which captures the highly crystal-orientation dependent evolution of liquid-solid interfaces during laser irradiation. Benchmarks against experimental data and non-atomistic phase-field models will be reported, validating the approach, along with LA simulations of Si(001) for various laser fluences and pulse shapes, also assuming inhomogeneous molten phase nucleation. LA simulations of SiGe alloys will also be presented, with an emphasis on the code capability of predicting laser-induced Ge segregation as well as defects formation and evolution with in an atom-by-atom fashion. Funding from EU Horizon 2020 Research and Innovation programme under grant agreement No. 871813 (MUNDFAB) is gratefully acknowledged. G. Calogero, D. Raciti, P. Acosta-Alba, F. Cristiano, I. Deretzis, G. Fisicaro, K. Huet, S. Kerdilès, A. Sciuto & A. La Magna. Multiscale modeling of ultrafast melting phenomena. npj Computational Materials 8, 36 (2022)

C.P2.7
17:30
Authors : Steve Dave Wansi Wendji,* Carlo Massobrio,* Guido Ori*
Affiliations : *Institute of Physics and Chemistry of Materials of Strasbourg (IPCMS), UMR 7504 CNRS - University of Strasbourg, France.

Resume : Amorphous vanophosphate (VP) systems are considered nowadays appealing materials for advanced applications as cathode components in solid-state batteries. However, key questions remain unanswered about the structural features characterizing such materials, in particular for what concern their structure and bonding properties. This study focuses on the set-up of a computational procedure based on first-principles molecular dynamics (FPMD) to quantitatively assess the structural properties and bonding fingerprints of pristine vanophosphate glasses and containing sodium ions (VP and NVP respectively). We first analyze the structure and bonding properties of VP and NVP glasses using the available (approximated) interatomic empirical potentials and classical MD. Secondly, on the grounds of a detailed comparison with experimental data, we discuss the level of quantitative agreement achievable by employing an approach based on FPMD. This dual effort shows the limits of the use of current interatomic potentials and paves the way on the detailed understanding of VP and NVP amorphous systems.

C.P2.8
17:30
Authors : R. Duddy1, Dr L. Stella1,2, and Dr M. Grüning1
Affiliations : 1 Atomistic Simulation Centre School of Mathematics and Physics, Queen’s University Belfast, Road Belfast, BT7 1NN, Belfast, UK 2 School of Chemistry and Chemical Engineering, Queen’s University Belfast, Stranmillis Road Belfast, Belfast, BT9 5AG, UK

Resume : Summary: The dielectric function of noble and alkaline metals is calculated using real-time time-dependent density functional theory (TDDFT). A Hubbard U term is included to account for localised d-orbitals in the noble metals and a Drude term is included to account for intraband transitions. The real-time method of calculating the plasma frequency is in good agreement with experiment and SIMPLE code benchmarks. Ab initio methods allow one to investigate candidate plasmonic materials without the influence of fabrication-dependent variables. Many-body perturbation theory is a well-established method of calculating the optical properties of metallic systems but is computationally expensive for non-stoichiometric candidate plasmonic materials. There is also potential in tuning the plasmonic response of ultra-thin films [1], which also require supercell calculations with a large number of atoms. This is motivation to explore more computationally favourable methods that can scale with larger systems and slab calculation to access surface dependent effects. To this end, we propose using the real-time TDDFT U method. The real-time propagation scales linearly with the number of states compared to linear-response methods which scale quadratically, this becomes beneficial for large unit cell calculations required for thin-films. The local density approximation (LDA) is known to overly delocalises the transition metal d-orbitals. The LDA+U method can be used to restore the atomic nature of localised orbital, improving the description of interband transitions of noble metals. We also present a method of accessing the plasma frequency using the real-time propagation which is required for describing the low energy intraband contribution to the dielectric function of metals. Results are benchmarked against integration over the Brillion zone as implemented in the SIMPLE approach [2]. We are grateful for use of the computing resources from the Northern Ireland High Performance Computing (NI-HPC) service funded by EPSRC (EP/T022175). This work was supported by the Engineering and Physical Research Council. 1. Deesha Shah, Alessandra Catellani, Harsha Reddy, Nathaniel Kinsey, Vladimir Shalaev, Alexandra Boltasseva, and Arrigo Calzolari, “Controlling the Plasmonic Properties of Ultrathin TiN Films at the Atomic Level”, ACS Photonics, 5, 2816−2824 Article (2018). 2. Gianluca Prandinia, Mario Galanteb,c, Nicola Marzaria, Paolo Umarib,” SIMPLE code: optical properties with optimal basis functions”, Computer Physics Communications 240 106–119 (2019).

C.P2.9
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14:00 SYMPOSIUM C AWARD ANNOUNCMENT    

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Symposium organizers
Elena LEVCHENKOUniversity of Newcastle

School of Mathematical and Physical Sciences, Faculty of Science, University Drive, Callaghan NSW 2308 Australia

Elena.Levchenko@newcastle.edu.au
Guido ORIInstitut de Physique et Chimie des Matériaux de Strasbourg

IPCMS, CNRS - University of Strasbourg, 23 Rue du Loess, F-67034 Strasbourg, France

guido.ori@ipcms.unistra.fr
Michał HERMANOWICZUniversity of Warsaw

Interdisciplinary Centre for Mathematical and Computational Modelling, ul. Tyniecka 15/17, 02-630 Warsaw, Poland

m.hermanowicz@icm.edu.pl
Yannick J. DAPPEService de Physique de l’Etat Condensé (SPEC – CNRS – CEA Saclay)

Bât. 771 Orme des Merisiers F-91191 Gif-sur-Yvette, France

yannick.dappe@cea.fr