X-ray diffraction data-assisted structure searches

Gao, Pengyue; Tong, Qunchao; Lv, Jian; Wang, Yanchao; Ma, Yanming

doi:10.1016/j.cpc.2016.11.007

Cited by 34 publications

(19 citation statements)

References 35 publications

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“…This package is extremely popular and has been interfaced to a number of local structural optimization codes (VASP, QE, GULP, SIESTA, CP2K CASTEP) varying from highly accurate DFT methods to fast semiempirical approaches that can deal with large systems. Notably this PSObased algorithm [286,287,288,289] combined with a fingerprint and matrix bond analysis has been successfully used in solving numerous structural problems [290,291,292,293,294], including prediction of new high-pressure superconducting hydrides [295,182,296,297].…”

Section: Particle Swarm Optimizationmentioning

confidence: 99%

A perspective on conventional high-temperature superconductors at high pressure: Methods and materials

et al. 2020

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Two hydrogen-rich materials: H 3 S and LaH 10 , synthesized at megabar pressures have revolutionized the field of superconductivity by providing a first glimpse into the solution for the hundred-year-old problem of room-temperature superconductivity. The mechanism governing these exceptional superconductors is the conventional electron-phonon coupling. Here, we describe recent advances in experimental techniques, superconductivity theory and first-principles computational methods, which made this discovery possible. The aim of this work is to provide an up-to-date compendium of the available results on superconducting hydrides and explain the synergy of different methodologies that led to the extraordinary discoveries in the field. Furthermore, in an attempt to evidence empirical rules governing superconductivity in binary hydrides under pressure, we discuss general trends in electronic structure and chemical bonding. The last part of the Review introduces possible strategies to optimize pressure and transition temperatures in conventional superconducting materials. Directions for future research in areas of theory, computational methods and high-pressure experiments are proposed, in order to advance our understanding of superconductivity.

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Section: Particle Swarm Optimizationmentioning

confidence: 99%

A perspective on conventional high-temperature superconductors at high pressure: Methods and materials

et al. 2020

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“…Methods including simulated annealing, genetic algorithms, and particle swarm have all been used to deduce the atomic positions. [12,[16][17][18][19][20] While these approaches have been shown to be effective in solving a wide range of crystal structures across chemistries, many rely on the specification of an expected structure or atomic building blocks such as oxygen tetrahedra or prototype structures to reduce the free parameters as much as possible. [16][17][18][19][20] In some cases, these heuristics can introduce a barrier by limiting relevant degrees of freedom or a bias by way of structure sampling which can influence the structure solution technique.…”

Section: Introductionmentioning

confidence: 99%

“…[12,[16][17][18][19][20] While these approaches have been shown to be effective in solving a wide range of crystal structures across chemistries, many rely on the specification of an expected structure or atomic building blocks such as oxygen tetrahedra or prototype structures to reduce the free parameters as much as possible. [16][17][18][19][20] In some cases, these heuristics can introduce a barrier by limiting relevant degrees of freedom or a bias by way of structure sampling which can influence the structure solution technique. In addition, this task may be especially difficult in less common chemical systems such as sulfides and nitrides, which are becoming fertile grounds for materials discovery.…”

Section: Introductionmentioning

confidence: 99%

Solving Inorganic Crystal Structures from X-ray Powder Diffraction Using a Generative First-Principles Framework

Ling

Hung²,

Montoya³

et al. 2022

Preprint

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X-ray powder diffraction (XRD) is a powerful structure characterization technique, but solving unknown inorganic crystal structures from powder diffraction patterns can often be labor-intensive or speculative. We introduce an Automated XRD to Structure (AXS) solution method based on the crystal symmetry obtained from XRD patterns, an efficient search of candidate structures spanning the available degrees of freedom, and density functional theory (DFT). This methodology is completely agnostic to structural prototypes and robust in solving inorganic structures of various chemistries, crystal systems, and unit cell sizes; 92% of all crystal structures were accurately determined from the simulated XRD patterns in our benchmark set. In addition, we demonstrate the efficacy of this methodology on experimental XRD patterns by solving the crystal structures of Li8HfO6, Li3CrO4, and LiFeO2.

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“…Such an approach has been pursued before in the experimental community. Direct space methods [14] and data-assisted structure searches [15] have been used to optimize the atomic configuration so that experimental diffraction data is reproduced. There have been attempts to use an additional energy cost function to support efficient fitting; however, this has included the assumption that the observed data is sufficiently accurate [16][17][18].…”

mentioning

confidence: 99%

Crystal structure prediction supported by incomplete experimental data

Tsujimoto

Adachi

Akashi

et al. 2018

Phys. Rev. Materials

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The prediction of material structure from chemical composition has been a long-standing challenge in natural science. Although there have been various methodological developments and successes with computer simulations [1][2][3][4][5][6][7][8], the prediction of crystal structures comprising more than several tens of atoms in the unit cell still remains difficult due to the many degrees of freedom, which increase exponentially with the number of atoms. Here we show that when some experimental data is available, even if it is totally insufficient for conventional structure analysis, it can be utilized to support and substantially accelerate structure simulation. In particular, we formulate a cost function based on a weighted sum of interatomic potential energies and a penalty function referred to as "crystallinity", which is defined using limited X-ray diffraction data. This method is applied to well-known polymorphs of SiO 2 with up to 96 atoms in the simulation cell to find that it reproduces the correct structures efficiently with a very limited number of diffraction peaks. The penalty function is confirmed to destabilize the local minima of the potential energy surface, which facilitates finding the correct structure. This method opens a new avenue for determining and predicting structures that are difficult to determine by conventional methods, such as surface, interface, glass, and amorphous structures.

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X-ray diffraction data-assisted structure searches

Cited by 34 publications

References 35 publications

A perspective on conventional high-temperature superconductors at high pressure: Methods and materials

A perspective on conventional high-temperature superconductors at high pressure: Methods and materials

Solving Inorganic Crystal Structures from X-ray Powder Diffraction Using a Generative First-Principles Framework

Crystal structure prediction supported by incomplete experimental data

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