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Improved methods for theoretical materials design

English title Improved methods for theoretical materials design
Applicant Amsler Maximilian
Number 158407
Funding scheme Advanced Postdoc.Mobility
Research institution
Laboratory of Atomic and Solid State Physics Cornell University
Dept. of Materials Science and Engineering Northwestern University, Chicago
Institution of higher education Institution abroad - IACH
Main discipline Condensed Matter Physics
Start/End 01.03.2015 - 31.08.2017
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All Disciplines (2)

Discipline
Condensed Matter Physics
Material Sciences

Keywords (6)

Electronic Structure; Structure Prediction; Materials Design; Simulation; Data Mining; Machine Learning

Lay Summary (German)

Lead
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.
Lay summary

Inhalt und Ziel des Forschungsprojekts

Das Hauptziel dieses Forschungsprojekts ist die Entwicklung neuer computergestützter Methoden, um die Entdeckung neuer Materialien zu beschleunigen. Anstatt im Labor in langwierigen Experimenten durch "Versuch und Irrtum" das geeignetste Material für eine bestimmte Anwendung zu suchen, sollen Computersimulationen genutzt werden, um neue Materialien zusammen mit deren potentiellen Eigenschaften vorherzusagen. Um solche Vorhersagen zu treffen muss nicht nur die korrekte chemische Komposition des Materials bestimmt werden, sondern auch die Kristallstruktur, so dass sich der Suchraum gleichzeitig über die Chemie und Struktur erstreckt. Durch die gigantische Anzahl möglicher chemischer Verbindungen und deren atomaren Anordnungen wurde das Problem bisher jedoch oft getrennt behandelt, so dass zuverlässige Vorhersagen nur bedingt möglich waren. Das Ziel des vorliegenden Projekts ist es, die Vorteile beider Ansätze zu Verbinden und eine neue Methode zu entwickeln, welche die Vorhersage eines Materials in seinem Grundzustand erlaubt und welche gleichzeitig eine bestimmte Materialeigenschaft optimiert. So wird es zum Beispiel in Zukunft möglich sein, neue Materialien mit guter Lichtabsorption für verbesserte Solarzellen oder andere Energieanwendungen vorherzusagen.


 

Direct link to Lay Summary Last update: 23.03.2015

Responsible applicant and co-applicants

Publications

Publication
Dense superconducting phases of copper-bismuth at high pressure
Amsler Maximilian, Wolverton Chris (2017), Dense superconducting phases of copper-bismuth at high pressure, in Physical Review Materials, 1(3), 031801-031801.
Surface reconstruction of fluorites in vacuum and aqueous environment
Fisicaro Giuseppe, Sicher Michael, Amsler Maximilian, Saha Santanu, Genovese Luigi, Goedecker Stefan (2017), Surface reconstruction of fluorites in vacuum and aqueous environment, in Physical Review Materials, 1(3), 033609-033609.
Energy landscape of ZnO clusters and low-density polymorphs
Rasoulkhani Robabe, Tahmasbi Hossein, Ghasemi S. Alireza, Faraji Somayeh, Rostami Samare, Amsler Maximilian (2017), Energy landscape of ZnO clusters and low-density polymorphs, in Physical Review B, 96(6), 064108-064108.
Creating Binary Cu–Bi Compounds via High-Pressure Synthesis: A Combined Experimental and Theoretical Study
Clarke Samantha M., Amsler Maximilian, Walsh James P. S., Yu Tony, Wang Yanbin, Meng Yue, Jacobsen Steven D., Wolverton Chris, Freedman Danna E. (2017), Creating Binary Cu–Bi Compounds via High-Pressure Synthesis: A Combined Experimental and Theoretical Study, in Chemistry of Materials, 29(12), 5276-5285.
Achieving zT > 1 in Inexpensive Zintl Phase Ca 9 Zn 4+x Sb 9 by Phase Boundary Mapping
Ohno Saneyuki, Aydemir Umut, Amsler Maximilian, Pöhls Jan-Hendrik, Chanakian Sevan, Zevalkink Alex, White Mary Anne, Bux Sabah K., Wolverton Chris, Snyder G. Jeffrey (2017), Achieving zT > 1 in Inexpensive Zintl Phase Ca 9 Zn 4+x Sb 9 by Phase Boundary Mapping, in Advanced Functional Materials, 27(20), 1606361-1606361.
High accuracy and transferability of a neural network potential through charge equilibration for calcium fluoride
Faraji Somayeh, Ghasemi S. Alireza, Rostami Samare, Rasoulkhani Robabe, Schaefer Bastian, Goedecker Stefan, Amsler Maximilian (2017), High accuracy and transferability of a neural network potential through charge equilibration for calcium fluoride, in Physical Review B, 95(10), 104105-104105.
High-pressure discovery of β-NiBi
Powderly K. M., Clarke S. M., Amsler M., Wolverton C., Malliakas C. D., Meng Y., Jacobsen S. D., Freedman D. E. (2017), High-pressure discovery of β-NiBi, in Chem. Commun., 53(81), 11241-11244.
Prediction of superconducting iron–bismuth intermetallic compounds at high pressure
Amsler Maximilian, Naghavi S. Shahab, Wolverton Chris (2017), Prediction of superconducting iron–bismuth intermetallic compounds at high pressure, in Chem. Sci., 8(3), 2226-2234.
Two-Dimensional Hexagonal Sheet of TiO2
Eivari Hossein Asnaashari, Ghasemi S. Alireza, Tahmasbi Hossein, Rostami Samare, Faraji Somayeh, Rasoulkhani Robabe, Goedecker Stefan, Amsler Maximilian (2017), Two-Dimensional Hexagonal Sheet of TiO2, in Chemistry of Materials, 0(0), 0.
Ultralow Thermal Conductivity in Full Heusler Semiconductors
He Jiangang, Amsler Maximilian, Xia Yi, Naghavi S. Shahab, Hegde Vinay I., Hao Shiqiang, Goedecker Stefan, Ozoliņš Vidvuds, Wolverton Chris (2016), Ultralow Thermal Conductivity in Full Heusler Semiconductors, in Physical Review Letters, 117(4), 046602-046602.
A fingerprint based metric for measuring similarities of crystalline structures.
Zhu Li, Amsler Maximilian, Fuhrer Tobias, Schaefer Bastian, Faraji Somayeh, Rostami Samare, Ghasemi S Alireza, Sadeghi Ali, Grauzinyte Migle, Wolverton Chris, Goedecker Stefan (2016), A fingerprint based metric for measuring similarities of crystalline structures., in The Journal of chemical physics, 144(3), 034203-034203.
Novel crystal structures for lithium–silicon alloy predicted by minima hopping method
Valencia-Jaime Irais, Sarmiento-Pérez Rafael, Botti Silvana, Marques Miguel A.L., Amsler M., Goedecker S., Romero Aldo H. (2016), Novel crystal structures for lithium–silicon alloy predicted by minima hopping method, in Journal of Alloys and Compounds, 655, 147-154.
Superconductivity in metastable phases of phosphorus-hydride compounds under high pressure
Flores-Livas José A., Amsler Maximilian, Heil Christoph, Sanna Antonio, Boeri Lilia, Profeta Gianni, Wolverton Chris, Goedecker Stefan, Gross E. K. U. (2016), Superconductivity in metastable phases of phosphorus-hydride compounds under high pressure, in Phys. Rev. B, 93, 020508-020508.
ZnSb Polymorphs with Improved Thermoelectric Properties
Amsler Maximilian, Goedecker Stefan, Zeier Wolfgang G., Snyder G Jeffrey, Wolverton Chris, Chaput Laurent (2016), ZnSb Polymorphs with Improved Thermoelectric Properties, in Chemistry of Materials, 0-0.

Collaboration

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

Scientific events

Active participation

Title Type of contribution Title of article or contribution Date Place Persons involved
Materials Science & Technology Conference Talk given at a conference Structure Predictions with the Minima Hopping Method 10.10.2017 Pittsburgh, PA, United States of America Amsler Maximilian;
254th American Chemical Society National Meeting & Exposition Talk given at a conference Computational discovery of high-pressure materials 21.08.2017 Washington, DC, United States of America Amsler Maximilian;
APS March Meeting Talk given at a conference High-Pressure Intermetallic Compounds and Their Properties in Ambient- Immiscible Systems 06.03.2017 New Orleans, LA, United States of America Amsler Maximilian;
TMS 2017 146th Annual Meeting and Exhibition Talk given at a conference Computational Approaches to Materials for Energy Applications 28.02.2017 San Diego, United States of America Amsler Maximilian;
ES 2016 Workshop Talk given at a conference Materials Genome and Structure Optimization: Theory and Application of Structural Optimization via Minima Hopping 26.06.2016 Albuquerque, NM, United States of America Amsler Maximilian;
APS March Meeting Talk given at a conference Novel Energy Materials Through Structural Search 14.03.2016 Baltimore, MD, United States of America Amsler Maximilian;
The 18th Asian Workshop on First-Principles Electronic Structure Calculations Poster Novel Energy Materials Through Structural Search 19.10.2015 Tokyo, Japan Amsler Maximilian;
Ψk- 2015 Conference Talk given at a conference Novel Low-Density Silicon Allotropes for Photovoltaic Applications 21.09.2015 San Sebastian, Spain Amsler Maximilian;


Self-organised

Title Date Place

Associated projects

Number Title Start Funding scheme
174475 Improved methods for theoretical materials design 01.09.2017 Advanced 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 intime-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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