Can lithium form phases with molybdenum?

Caputo, Riccarda; Tekin, Adem

doi:10.1016/j.jssc.2018.12.057

Cited by 5 publications

(5 citation statements)

References 19 publications

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“…FFCASP is basically a modernized and enhanced version of our old predictor named CASPESA, ,− and its overall flowchart is shown in Figure . When designing our new CSP approach, we dissected the CSP problem to four distinct parts: global optimization, lattice prototypes, movement system, and fitness function.…”

Section: Methodsmentioning

confidence: 99%

“…Recently, we developed a CSP algorithm, called CrsytAl Structure PrEdiction via Simulated Annealing (CASPESA), to predict the crystal structures of covalent crystals such as hydrogen storage ,− and Li-ion battery materials. , The main motivation of CASPESA is to globally optimize the number of peculiar interactions that might lead to lowering the energy of the crystal structure. Here, we extended the capability of CASPESA to handle molecular crystals together with enhancing the strategy used in the global optimization.…”

Section: Introductionmentioning

confidence: 99%

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FFCASP: A Massively Parallel Crystal Structure Prediction Algorithm

Demir

Tekin

2021

J. Chem. Theory Comput.

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A new algorithm called Fast and Flexible CrystAl Structure Predictor (FFCASP) was developed to predict the structure of covalent and molecular crystals. FFCASP is massively parallel and able to handle more than 200 atoms in the unit cell (in other terms, it allows global optimization around 100 individual parameters). It uses a global optimizer specialized for Crystal Structure Prediction (CSP) which combines particle swarm and simulated annealing optimizers. Three different molecular crystals, including diverse intermolecular interactions, namely, cytosine, coumarin, and pyrazinamide, have been selected to evaluate the performance of FFCASP. While cytosine polymorphs have been searched by employing two different force fields (a DFT-SAPT based intermolecular potential and generalized amber force field (GAFF)) up to Z = 16, only GAFF has been used both in coumarin and pyrazinamide polymorph searches up to Z = 4. For these three molecular crystals, FFCASP generated more than 20 000 crystal structures, and the unique ones have been further treated by DFT-D3. A combination of data mining and a machine learning approach was introduced to determine the unique structures and their distribution into different clusters, which ultimately gives an opportunity to retrieve the common features and relations between the resulting structures. There are two known experimental crystal structures of cytosine, and both were successfully located with FFCASP. Two of the reported crystal structures of coumarin have been reproduced. Similarly, in pyrazinamide, three known experimental structures have been rediscovered. In addition to finding the experimentally known structures, FFCASP also located other low-energy structures for each considered molecular crystals. These successes of FFCASP offer the possibility to discover the polymorphic nature of other important molecular crystals (e.g., drugs) as well.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

FFCASP: A Massively Parallel Crystal Structure Prediction Algorithm

Demir

Tekin

2021

J. Chem. Theory Comput.

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“…Through these topological considerations, we modeled our initial structures by taking into account the conformations suggested in the literature, though the structure data reported to date − ,, are either not accurate enough or insufficient to build correctly the model structures of the two phases. Nevertheless, the conformation and the structure description therein are important pieces of information that helped us set up the model used in the crystal structure predictions (CSPs) performed with the modernized version of CASPESA − called the Fast and Flexible CrystAl Structure Predictor (FFCASP), which is a parallel global crystal structure prediction tool.…”

Section: Methodsmentioning

confidence: 99%

“…While CASPESA includes only simulated annealing (SA) as a global optimization algorithm, FFCASP consists a hybrid combination of particle swarm optimization (PSO) , and SA. PSO is known for its ability to overcome large barriers, and SA has already shown its very good potential in CSP problems. − We experienced that this hybrid approach performs better compared with the standalone global optimizations carried out with SA. In FFCASP, first PSO is activated to make big search steps and then SA finalizes the global optimization by preventing premature convergence and enhancing the PSO outcome.…”

Section: Methodsmentioning

confidence: 99%

First-Principles Crystal Structure Prediction of Cu(I)-TCNQ Polymorphs

2019

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There is a lack of consensus on the crystal structure and polymorphism of Cu(I)-TCNQ, even though an enormous work and great achievements have been reported for decades. This motivated us to perform a crystal structure prediction study [by using the Fast and Flexible CrystAl Structure Predictor (FFCASP)] combined with total energy calculations at the dispersion-corrected density functional theory (DFT-D) level. The ensemble of the optimized structures falls in two distinct regions based on the energy-density phase space. Our predictions located the thermodynamic phase (as a global minimum) and a conformationally similar local minimum structure to the experimentally proposed phase I, in the low- and high-density regions, respectively. The Rietveld refinement of the P21212 local minimum structure to the experimental X-ray diffraction (XRD) pattern resulted in a structure with a density between the two regions. This polymorph, the kinetic product, becomes a high-energy local minimum structure after the full geometry optimization, being 35.03 kJ/mol above the global minimum. In addition, we found that the transition from the high- to the low-density region occurs via square planar coordination of copper atoms.

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“…There are a growing number of reports pertaining to reactions of Li and Na with wide variety of materials ranging from transition metal dichalcogenides (TMDCs) to TM oxides (TMOs) both from bulk exfoliated flakes as well as chemically synthesized nanostructures. Qualitative features have been invariably shown in terms of change in contrast during reaction with Li, which may be a signature of insertion of Li into TMDCs/TMOs [3]. However, The viewing direction can complicate the issue in particular for reactions with nanostructures with a range of possible orientations in addition to the challenges of performing the in-situ reactions inside TEM itself [4].…”

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confidence: 99%