Structure Prediction at High Pressures

Author(s):  
Miriam Marqués ◽  
Ángel Morales ◽  
José Menéndez
Author(s):  
Elia Schneider ◽  
Leslie Vogt ◽  
Mark E. Tuckerman

Prediction and exploration of possible polymorphism in organic crystal compounds are of great importance for industries ranging from organic electronics to pharmaceuticals to high-energy materials. Here we apply our crystal structure prediction procedure and the enhanced molecular dynamics based sampling approach called the Crystal-Adiabatic Free Energy Dynamics (Crystal-AFED) method to benzene and naphthalene. Crystal-AFED allows the free energy landscape of structures to be explored efficiently at any desired temperature and pressure. For each system, we successfully predict the most stable crystal structures at atmospheric pressure and explore the relative Gibbs free energies of predicted polymorphs at high pressures. Using Crystal-AFED sampling, we find that mixed structures, which typically cannot be discovered by standard crystal structure prediction methods, are prevalent in the solid forms of these compounds at high pressure.


2020 ◽  
Vol 34 (12) ◽  
pp. 2050119
Author(s):  
Zhen-Wei Niu ◽  
Mei Tang ◽  
Ling-Cang Cai

Iron silicides provide extensive applications in functional device and earth science. Very little is known about these alloys at high pressures and temperatures. Here, combining swarm-intelligence-based structure prediction methodology and quasi-harmonic approximation (QHA), we investigate Fe-Si compounds at pressures of up to 500 GPa. Evolutionary simulations correctly find the known B20-FeSi structure and some other experimentally observed compounds at atmospheric pressure and finite temperature. It is shown that among the possible iron silicides, only B2-FeSi is thermodynamically stable at high pressures, and the increasing temperature tends to stabilize B2-FeSi compound rather than other iron silicides.


2019 ◽  
Vol 5 (1) ◽  
Author(s):  
Ziji Shao ◽  
Defang Duan ◽  
Yanbin Ma ◽  
Hongyu Yu ◽  
Hao Song ◽  
...  

Abstract Inspired by the diverse properties of sulfur hydrides and phosphorus hydrides, we combine first-principles calculations with structure prediction to search for stable structures of Li−P−H ternary compounds at high pressures with the aim of finding novel superconductors. It is found that phosphorus hydrides can be stabilized under pressure via additional doped lithium. Four stable stoichiometries LiPH3, LiPH4, LiPH6, and LiPH7 are uncovered in the pressure range of 100–300 GPa. Notably, we find an atomic LiPH6 with $$Pm\overline 3$$ P m 3 ¯ symmetry which is predicted to be a potential high-temperature superconductor with a Tc value of 150–167 K at 200 GPa and the Tc decreases upon compression. All the predicted stable ternary hydrides contain the P–H covalent frameworks with ionic lithium staying beside, but not for $$Pm\overline 3$$ P m 3 ¯ -LiPH6. We proposed a possible synthesis route for ternary lithium phosphorus hydrides: LiP + H2 → LiPHn, which could provide helpful and clear guidance to further experimental studies. Our work may provide some advice on further investigations on ternary superconductive hydrides at high pressure.


1998 ◽  
Vol 77 (4) ◽  
pp. 1063-1075
Author(s):  
W. C. Mackrodt, E.-A. Williamson, D. W

1970 ◽  
Vol 19 (2) ◽  
pp. 217-226
Author(s):  
S. M. Minhaz Ud-Dean ◽  
Mahdi Muhammad Moosa

Protein structure prediction and evaluation is one of the major fields of computational biology. Estimation of dihedral angle can provide information about the acceptability of both theoretically predicted and experimentally determined structures. Here we report on the sequence specific dihedral angle distribution of high resolution protein structures available in PDB and have developed Sasichandran, a tool for sequence specific dihedral angle prediction and structure evaluation. This tool will allow evaluation of a protein structure in pdb format from the sequence specific distribution of Ramachandran angles. Additionally, it will allow retrieval of the most probable Ramachandran angles for a given sequence along with the sequence specific data. Key words: Torsion angle, φ-ψ distribution, sequence specific ramachandran plot, Ramasekharan, protein structure appraisal D.O.I. 10.3329/ptcb.v19i2.5439 Plant Tissue Cult. & Biotech. 19(2): 217-226, 2009 (December)


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