Uncertainty-Quantified Hybrid Machine Learning/Density Functional Theory High Throughput Screening Method for Crystals

2020 ◽  
Vol 60 (4) ◽  
pp. 1996-2003 ◽  
Author(s):  
Juhwan Noh ◽  
Geun Ho Gu ◽  
Sungwon Kim ◽  
Yousung Jung
Keyword(s):  
Machine Learning ◽  
Density Functional Theory ◽  
High Throughput ◽  
High Throughput Screening ◽  
Density Functional ◽  
Screening Method ◽  
Functional Theory ◽  
Hybrid Machine

scholarly journals Application of DFT-based machine learning for developing molecular electrode materials in Li-ion batteries

RSC Advances ◽  
2018 ◽  
Vol 8 (69) ◽  
pp. 39414-39420 ◽  
Author(s):  
Omar Allam ◽  
Byung Woo Cho ◽  
Ki Chul Kim ◽  
Seung Soon Jang
Keyword(s):  
Machine Learning ◽  
Density Functional Theory ◽  
High Throughput Screening ◽  
Density Functional ◽  
Electrode Materials ◽  
Screening Method ◽  
Li Ion Batteries ◽  
Functional Theory ◽  
Learning Framework ◽  
Li Ion

In this study, we utilize a density functional theory-machine learning framework to develop a high-throughput screening method for designing new molecular electrode materials.

scholarly journals Study on Adsorption and Separation of Gas in Metal-organic Framework Materials Based on Density Functional Theory

2021 ◽  
Vol 257 ◽  
pp. 01012
Author(s):  
Du Zhehua ◽  
Lin Xin
Keyword(s):  
Density Functional Theory ◽  
High Throughput ◽  
High Throughput Screening ◽  
Density Functional ◽  
Gas Adsorption ◽  
Metal Organic Framework ◽  
Functional Theory ◽  
Main Challenge ◽  
Metal Organic ◽  
Organic Framework

This article reviews the recent progress on predicting the adsorption properties of metal-organic framework by using classical density functional theory and focused on the application of the classical density functional theory to the high-throughput screening, which is accelerated by fast Fourier Transform. Comparing to the conventional molecular simulations, the advantage of the accelerated classical density functional theory is the calculation speed, especially for simple small molecule systems, which makes the high-throughput screening on MOF materials feasible. However, it appears that there is a lack of efficient method to deal with the complicated molecules. How to construct a reasonable free energy functional of complicated fluid is the main challenge to state of art classical density functional theory. In a word, the improvement of CDFT theory and the combination of CDFT and molecular simulation are the two main ways for CDFT to predict gas adsorption in MOF.

scholarly journals Designing of magnetic MAB phases for energy applications

2021 ◽  
Vol 9 (13) ◽  
pp. 8805-8813
Author(s):  
Chen Shen ◽  
Qiang Gao ◽  
Nuno M. Fortunato ◽  
Harish K. Singh ◽  
Ingo Opahle ◽  
...  
Keyword(s):  
Density Functional Theory ◽  
Permanent Magnet ◽  
High Throughput ◽  
Density Functional ◽  
Density Functional Theory Calculations ◽  
Functional Theory ◽  
Energy Applications

Based on high-throughput density functional theory calculations, we performed screening for stable magnetic MAB compounds and predicted potential strong magnets for permanent magnet and magnetocaloric applications.

Predicting the stability of ternary intermetallics with density functional theory and machine learning

2018 ◽  
Vol 148 (24) ◽  
pp. 241728 ◽  
Author(s):  
Jonathan Schmidt ◽  
Liming Chen ◽  
Silvana Botti ◽  
Miguel A. L. Marques
Keyword(s):  
Machine Learning ◽  
Density Functional Theory ◽  
Density Functional ◽  
Functional Theory ◽  
The Stability
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