Molecular Interactions for Modeling of Oxygen System Using van der Waals Density Functional Approach

2015 ◽  
Author(s):  
Masao Obata ◽  
Ikutaro Hamada ◽  
Tatsuki Oda
Keyword(s):  
Molecular Interactions ◽  
Density Functional ◽  
Van Der Waals ◽  
Functional Approach ◽  
Oxygen System

Efficient Prediction of Structural and Electronic Properties of Hybrid 2D Materials Using DFT and Machine Learning

2018 ◽  
Author(s):  
Sherif Tawfik ◽  
Olexandr Isayev ◽  
Catherine Stampfl ◽  
Joseph Shapter ◽  
David Winkler ◽  
...  
Keyword(s):  
Machine Learning ◽  
Band Gap ◽  
Density Functional ◽  
2D Materials ◽  
Van Der Waals ◽  
Building Blocks ◽  
Machine Learning Techniques ◽  
Interlayer Distance ◽  
Computational Screening ◽  
Wide Range

Materials constructed from different van der Waals two-dimensional (2D) heterostructures offer a wide range of benefits, but these systems have been little studied because of their experimental and computational complextiy, and because of the very large number of possible combinations of 2D building blocks. The simulation of the interface between two different 2D materials is computationally challenging due to the lattice mismatch problem, which sometimes necessitates the creation of very large simulation cells for performing density-functional theory (DFT) calculations. Here we use a combination of DFT, linear regression and machine learning techniques in order to rapidly determine the interlayer distance between two different 2D heterostructures that are stacked in a bilayer heterostructure, as well as the band gap of the bilayer. Our work provides an excellent proof of concept by quickly and accurately predicting a structural property (the interlayer distance) and an electronic property (the band gap) for a large number of hybrid 2D materials. This work paves the way for rapid computational screening of the vast parameter space of van der Waals heterostructures to identify new hybrid materials with useful and interesting properties.

Thermodynamic Stability of Hexagonal and Rhombohedral Bn at Cvd Conditions from Van der Waals Corrected First Principles Calculations

2019 ◽  
Author(s):  
Henrik Pedersen ◽  
Björn Alling ◽  
Hans Högberg ◽  
Annop Ektarawong
Keyword(s):  
Thin Films ◽  
Thermodynamic Stability ◽  
First Principles ◽  
Thermal Equilibrium ◽  
Density Functional ◽  
Van Der Waals ◽  
Chemical Vapor ◽  
First Principles Calculations ◽  
Functional Theory ◽  
The Stability

Thin films of boron nitride (BN), particularly the sp<sup>2</sup>-hybridized polytypes hexagonal BN (h-BN) and rhombohedral BN (r-BN) are interesting for several electronic applications given band gaps in the UV. They are typically deposited close to thermal equilibrium by chemical vapor deposition (CVD) at temperatures and pressures in the regions 1400-1800 K and 1000-10000 Pa, respectively. In this letter, we use van der Waals corrected density functional theory and thermodynamic stability calculations to determine the stability of r-BN and compare it to that of h-BN as well as to cubic BN and wurtzitic BN. We find that r-BN is the stable sp<sup>2</sup>-hybridized phase at CVD conditions, while h-BN is metastable. Thus, our calculations suggest that thin films of h-BN must be deposited far from thermal equilibrium.

uMBD: A Materials-Ready Dispersion Correction that Uniformly Treats Metallic, Ionic, Covalent, and van der Waals Bonding

2019 ◽  
Author(s):  
Minho Kim ◽  
won june kim ◽  
Tim Gould ◽  
Eok Kyun Lee ◽  
Sébastien Lebègue ◽  
...  
Keyword(s):  
First Principles ◽  
Density Functional ◽  
Electrode Materials ◽  
Full Range ◽  
Van Der Waals ◽  
Dft Method ◽  
Dispersion Correction ◽  
Computational Overhead ◽  
System A ◽  
Battery Design

<p>Materials design increasingly relies on first-principles calculations for screening important candidates and for understanding quantum mechanisms. Density functional theory (DFT) is by far the most popular first-principles approach due to its efficiency and accuracy. However, to accurately predict structures and thermodynamics, DFT must be paired with a van der Waals (vdW) dispersion correction. Therefore, such corrections have been the subject of intense scrutiny in recent years. Despite significant successes in organic molecules, no existing model can adequately cover the full range of common materials, from metals to ionic solids, hampering the applications of DFT for modern problems such as battery design. Here, we introduce a universally optimized vdW-corrected DFT method that demonstrates an unbiased reliability for predicting molecular, layered, ionic, metallic, and hybrid materials without incurring a large computational overhead. We use our method to accurately predict the intercalation potentials of layered electrode materials of a Li-ion battery system – a problem for which the existing state-of-the-art methods fail. Thus, we envisage broad use of our method in the design of chemo-physical processes of new materials.</p>

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