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个人简介
I am a computational materials scientist / theoretical condensed matter physicist. My research consists most frequently of using first principles computational tools, such as density functional theory (DFT), to understand and predict the properties of useful new materials. These calculations are used to both lead experiments into useful new areas and help understand previous experimental findings.
Within that framework, I have worked on many different materials types and materials properties, including surfaces and interfaces, ferroelectrics, topological insulators, thermoelectrics, catalysts, and semiconductors, as well as on computational techniques like pseudopotentials.
Some of my work at NIST has focused on using high-throughput computational techniques, where a large database of materials is screened computationally to assess the suitability of individual materials for a particular application. First principles calculations are ideal for an initial screening procedure, as they do not require experimental input and can potentially be applied to hundreds or thousands of materials automatically. After the initial computationally efficient screening, the most promising materials can be subjected to further theoretical or experimental consideration.
In addition, I use modeling of large databases to prediction new materials properties, for example with advanced tight-binding.
Within that framework, I have worked on many different materials types and materials properties, including surfaces and interfaces, ferroelectrics, topological insulators, thermoelectrics, catalysts, and semiconductors, as well as on computational techniques like pseudopotentials.
Some of my work at NIST has focused on using high-throughput computational techniques, where a large database of materials is screened computationally to assess the suitability of individual materials for a particular application. First principles calculations are ideal for an initial screening procedure, as they do not require experimental input and can potentially be applied to hundreds or thousands of materials automatically. After the initial computationally efficient screening, the most promising materials can be subjected to further theoretical or experimental consideration.
In addition, I use modeling of large databases to prediction new materials properties, for example with advanced tight-binding.
研究兴趣
论文共 74 篇作者统计合作学者相似作者
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Digital Discoveryno. 7 (2024): 1365-1377
Kamal Choudhary,Daniel Wines,Kangming Li,Kevin F. Garrity,Vishu Gupta,Aldo H. Romero,Jaron T. Krogel,Kayahan Saritas,Addis Fuhr,Panchapakesan Ganesh,Paul R. C. Kent,Keqiang Yan,Yuchao Lin,Shuiwang Ji,Ben Blaiszik,Patrick Reiser,Pascal Friederich,Ankit Agrawal,Pratyush Tiwary,Eric Beyerle,Peter Minch,Trevor David Rhone,Ichiro Takeuchi,Robert B. Wexler,Arun Mannodi-Kanakkithodi,Elif Ertekin,Avanish Mishra,Nithin Mathew,Mitchell Wood, Andrew Dale Rohskopf,Jason Hattrick-Simpers,Shih-Han Wang,Luke E. K. Achenie,Hongliang Xin,Maureen Williams,Adam J. Biacchi,Francesca Tavazza
NPJ COMPUTATIONAL MATERIALSno. 1 (2024)
NANO LETTERSno. 3 (2023): 969-978
arXiv (Cornell University) (2022)
Spectroscopy and Characterization of Nanomaterials and Novel Materialspp.239-260, (2022)
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作者统计
#Papers: 74
#Citation: 5399
H-Index: 28
G-Index: 64
Sociability: 5
Diversity: 2
Activity: 24
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