Computational Approaches to Materials for Energy Applications: Session II
Sponsored by: TMS Extraction and Processing Division, TMS Light Metals Division, TMS: Energy Committee
Program Organizers: Laurent Chaput, LEMTA
Wednesday 2:00 PM
March 1, 2017
Location: San Diego Convention Ctr
Session Chair: Laurent Chaput, Lorraine University
2:00 PM Invited
Optimizing Materials for Solar Energy Conversion: In Search for Descriptors: Giulia Galli1; 1The University of Chicago
We discuss the results of first principles simulations of interfaces present in organic photovoltaic blends, between nanoparticles and ligands in inorganic, nanostructured solar cells and between photo-absorber, catalysts and water in photo-electrochemical cells. We focus on the identification of descriptors to be possibly used to optimize photo-conversion properties, and on the role of complex morphologies present in solar materials.
2:30 PM Invited
Different Aspects of Disorder in Materials for Energy Conversion Studied by the KKR-CPA Calculation: Janusz Tobola1; Bartłomiej Wiendlocha1; Janina Molenda1; Jakub Cieslak1; Stanisław Kaprzyk1; 1AGH University of Science and Technology
Real bulk materials that may convert various forms of energy (eg. thermoelectric, magnetocaloric or ion battery systems) commonly contain different types of chemical disorder that should be accounted for more reliable description of quantum mechanisms responsible for observed physical behaviors, and also for optimizing their performance. The KKR-CPA technique appears to be well-adapted approach to study electronic structure and physical properties in disordered systems. Ilustrative results of KKR-CPA calculations are presented, focusing on: (i) influence of electron states on Fermi surfaces, resonant-like vs. conventional-like impurity states and relativistic effects on thermoelectric performance from Boltzmann transport approach, (ii) crystal defects modifying DOS in relation to character of discharge curves in selected Li- or Na-ion battery systems, (iii) the effect of random vs. partial order of atom arrangements on phase stability and magnetic properties in high entropy alloys. This work was partly supported by the Polish National Center of Science (NCN, UMO-2015/17/B/ST3/01204).
Ab Initio Calculations of Carrier Radiative Lifetimes: Marco Bernardi1; 1Caltech
We discuss a novel approach to compute the radiative lifetime (RL) of charge carriers and excitons. The calculations employ the GW-BSE method to obtain the exciton dipole matrix elements, which are then combined with Fermi's golden rule to obtain the zero-temperature RLs. Temperature-dependent RLs are then computed by averaging over center-of-mass momenta (at low temperature) and also over excitonic states at room temperature. Derivations of the RLs for 1D, 2D, and bulk materials are presented, together with applications to materials for lighting, including 2D transition metal dichalcogenides and bulk GaN and InGaN, and for solar cells, including lead-iodide perovskites. Comparison of the computed RLs with time-resolved photoluminescence experiments is discussed. The technical challenges toward obtaining the quantum yield and carrier diffusion lengths from first principles are outlined.
Design of Heteroepitaxialy Grown Quantum Dots Under External Force Fields: Nur Seda Aydin1; Ersin Emre Oren1; 1Bionanodesign Laboratory, Department of Biomedical Engineering, TOBB University of Economics and Technology, Ankara, Turkey
Quantum dots (QDs) have discrete energy levels thus a well-defined band gap, which may be engineered by controlling their size and morphology. These unique features, plus dislocation-free obtainability via Stranski Krastanov growth, make QDs promising candidates for designing novel optoelectronic devices. We modeled the formation, spontaneous evolution and stability of quantum dots during heteroepitaxial growth under electric and stress fields, via irreversible thermodynamics treatment of surfaces and interfaces. The simulations demonstrated the interplay between the stable QDs and the material properties (e.g., crystallographic orientation and initial thickness of the film, diffusion and surface stiffness anisotropies, surface and interfacial energies, wetting contact angle and mismatch/external stresses). The investigation of stable QD morphologies enabled us to generate phase diagrams that show the stable QD configurations for a given set of material/process parameters. This information will provide design capability for QDs and hence desired QD-based device technologies. Supported by TUBITAK (grant no 315M222).
3:40 PM Break
4:00 PM Invited
Structure Prediction in Novel Energy Materials Design: Maximilian Amsler1; Chris Wolverton1; 1Northwestern University
Recently, novel approaches in computational materials science have led to significant advances in materials design, including high-throughput calculations, data-mining and machine learning. Another increasingly popular technique is ab-initio structure prediction, such as the Minima Hopping Method, which implements a highly efficient global geometry optimization algorithm to identify thermodynamically stable and metastable compounds. I will illustrate how this method can be used to tackle materials design challenges from different perspectives, supported by examples of its recent, successful application.
Energy Landscape of Point Defects in Body-centered-cubic Metals: Mihai-Cosmin Marinica1; 1DEN-Service de Recherches de Métallurgie Physique, CEA, Université Paris-Saclay
Progress in future energy systems depends critically on our ability to design new materials with adequate properties under extreme conditions. This study aims at improving our understanding of the free energy landscape of point defects in body-centered-cubic metals up to the melting temperature by resorting to atomistic simulations based on electronic structure calculations. The phase space is sampled using adaptive molecular dynamics methods and ab initio atomic forces. Moreover, taking advantage of versatility of adaptive free energy methods we combine the ab-initio force field with interatomic machine learning based interactions. The present approach merging ab initio – free energy – machine learning methods, can provide quantities such as formation free energies or diffusion transition rates as key input parameter for any subsequent multi-scale simulation. In the case of tungsten, candidate material for first wall and divertor components of future fusion reactors, our results will be directly compared with the experiment.
Systematic Search for Lithium Ion Conducting Compounds by Screening of Compositions Combined with
Atomistic Simulation: Daniel Mutter1; Daniel Urban2; Christian Elsaesser3; 1FMF, University of Freiburg; 2Fraunhofer IWM Freiburg; 3Fraunhofer IWM, and FMF, University of Freiburg
Solid state electrolytes (SSEs) with fast Li conductivity can significantly improve Li ion accumulators in terms of electrochemical efficiency, thermal and mechanical stability, and environmental compatibility. Compounds crystallizing in the structure of NaZr2(PO4)3 (NZP) are regarded as promising SSEs, mainly because of their three-dimensional network of migration channels. Starting from LiTi2(PO4)3, we analyzed a large variety of NZP-type materials by systematically screening the relevant parts of the periodic table, replacing Ti fully and partly by tri-, tetra-, and pentavalent cations, and the phosphate by silicate, vanadate, and arsenate anions. The influence of different elements on preferred Li sites, Li mobility, and possible migration paths were analyzed by means of a combination of computational methods, ranging from density functional theory to molecular dynamics simulations with ionic bond valence potentials. Minimum energy paths and migration barriers were identified by nudged-elastic-band and energy-lanscape-mapping calculations.