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Improved methods for theoretical materials design

English title Improved methods for theoretical materials design
Applicant Amsler Maximilian
Number 174475
Funding scheme Advanced Postdoc.Mobility
Research institution Dept. of Materials Science and Engineering Northwestern University, Chicago
Institution of higher education Institution abroad - IACH
Main discipline Condensed Matter Physics
Start/End 01.09.2017 - 28.02.2018
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All Disciplines (2)

Discipline
Condensed Matter Physics
Material Sciences

Keywords (4)

Electronic Structure; Simulation; Structure Prediction; Materials Design

Lay Summary (German)

Lead
Neue Materialien für technologischen Fortschritt.
Lay summary
Mit der Entdeckung neuer Materialien geht oft die Erschliessung neuer technologischer Möglichkeiten einher. Insbesondere mit der Energiewende steigt der Bedarf an neuer Materialien zur nachhaltigen Energiegewinnung, um einen Abkehr von fossilen Rohstoffen und eine Lösung zu den damit verbundenen ökologischen und ökonomischen Problemen zu ermöglichen. Die Synthese neuer Materialien im Labor ist oft langwierig und kostspielig, so dass oft mehrere Jahrzehnte vergehen bis ein neues Material nach deren Entdeckung in marktreifen Produkten Verwendung findet. Um den zukünftigen Energiebedarf nachhaltig zu decken bedarf es der Reduktion dieser Zeitspanne zwischen Synthese und industrieller Nutzung.
Direct link to Lay Summary Last update: 13.01.2018

Responsible applicant and co-applicants

Publications

Publication
Linear scaling DFT calculations for large tungsten systems using an optimized local basis
Stephan Mohr Marc Eixarch Maximilian Amsler Mervi J.Mantsinen Luigi Genovese (2018), Linear scaling DFT calculations for large tungsten systems using an optimized local basis, in Nuclear Materials and Energy.
Cubine, a Quasi Two-Dimensional Copper–Bismuth Nanosheet
Maximilian Amsler Zhenpeng Yao and Chris Wolverton (2017), Cubine, a Quasi Two-Dimensional Copper–Bismuth Nanosheet, in Chem. Mater., 29(22), 9819.
First-principles Study of Lithium Cobalt Spinel Oxides: Correlating Structure and Electrochemistry
Kim S Hegde VI Yao Z Lu Z Amsler M He J Hao S Croy JR Lee E Thackeray M Wolvert C, First-principles Study of Lithium Cobalt Spinel Oxides: Correlating Structure and Electrochemistry, in ACS Appl. Mater. Interfaces.

Collaboration

Group / person Country
Types of collaboration
Danna Freedman, Northwestern University United States of America (North America)
- in-depth/constructive exchanges on approaches, methods or results
- Publication
Roald Hoffmann, Cornell United States of America (North America)
- in-depth/constructive exchanges on approaches, methods or results
- Publication
- Research Infrastructure
Steven Jacobsen, Northwestern University United States of America (North America)
- in-depth/constructive exchanges on approaches, methods or results
- Publication
- Research Infrastructure

Scientific events

Active participation

Title Type of contribution Title of article or contribution Date Place Persons involved
APS March Meeting Talk given at a conference Phase Stability of High-Pressure Materials 06.05.2018 Los Angeles, United States of America Amsler Maximilian;
Materials Science & Technology Conference Talk given at a conference Structure Predictions with the Minima Hopping Method 08.10.2017 Pittsburgh, United States of America Amsler Maximilian;


Associated projects

Number Title Start Funding scheme
158407 Improved methods for theoretical materials design 01.03.2015 Advanced Postdoc.Mobility
180669 Improved methods for theoretical materials design 01.03.2019 Return CH Postdoc.Mobility

Abstract

Materials design has become one of the most rapidly increasing fields of condensed matter science during the last years. Discovery of novel materials are called for with potential applications in various technologically relevant fields such as energy production and storage, novel electronic devices, data storage, medical application and catalysis. Instead of synthesizing and characterizing novel materials in time-consuming, expensive experiments, theoretical material scientists have started to create databases obtained from all materials known to date and to systematically analyze them with high-throughput computation methods, trying to gain insight on how chemistry and structures are linked to material properties and to extract patterns from the underlying data. New, innovative computational methods are needed to efficiently characterize the continuously growing amount of materials data, and techniques need to be developed to extrapolate materials properties to design novel, undiscovered compounds with improved properties. The presented project is aimed at solving two key limitations in materials design. First, most structure prediction methods do not access the knowledge stored in the large structural databases. By combining the Minima Hopping structure prediction scheme and machine-learning techniques a sophisticated method will be developed to explore new chemistries and to discover compounds with improved or new properties in energy applications. The new method will be applied to real-life challenges in materials design to find thermoelectric and hydrogen storage materials, or materials for use in photovoltaic applications. Second, Quantum Monte Carlo methods will be used to refine the energetic ordering of different phases in various compounds to significantly improve the predictive power by going beyond the accuracy of conventional density functional theory calculations used in current approaches. The outcome of this project will be of great value for many material scientists and will considerably accelerate the theoretical discovery of novel materials.
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