Automatized Parameterization of the Density‐functional Tight‐binding Method. II. Two‐center Integrals

Witek, Henryk A.; Chou, Chien Pin; Mazur, Grzegorz; Nishimura, Yoshifumi; Irle, Stephan; Aradi, Bálint; Frauenheim, Thomas; Morokuma, Keiji

doi:10.1002/jccs.201500066

Cited by 15 publications

(12 citation statements)

References 80 publications

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“…To ensure the transferability of SCC-DFTB parameters, the band structures of metallic Li and Li 2 O were used in r 0 fitting. Although band structures closer to the DFT results can be obtained for the Li metal, 18,22,37 compromise has to be made to fit the lithium in both metallic (Li 0 ) and ionic (Li + ) states. Figure 2 shows that the SCC-DFTB and DFT computed band structures agree well for the valence bands and the conduction bands near the Fermi Table 1 compares the SCC-DFTB and DFT predicted values for the crystalline structures in the training set.…”

Section: Computational Detailsmentioning

confidence: 99%

Transferable Self-Consistent Charge Density Functional Tight-Binding Parameters for Li–Metal and Li-Ions in Inorganic Compounds and Organic Solvents

2018

J. Phys. Chem. C

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When a Li–metal electrode immerses in the electrolytes containing organic solvents, it is always covered by a thin layer of solid electrolyte interphase (SEI) containing both inorganic and organic compounds. While simulating the electrochemical reactions occurring at this interface is essential to understand electrolyte decomposition and Li dendrite formation that impact the life and safety of Li-ion batteries, conventional density functional theory (DFT) or force field methods are either limited by size or by accuracy. Therefore, the self-consistent-charge density functional tight-binding (SCC-DFTB) approach was taken in this research. We first developed a parametrization scheme for mixed valence lithium (Li0 and Li+) within the SCC-DFTB framework and then developed a new set of parameters for Li–X (X = Li, H, O, and C) interactions. The newly developed parameters were validated through comparison with DFT predictions for a range of materials, including Li, Li2O, and Li2CO3, and Li+ ions dissolved in ethylene carbonate (EC) solvent. The SCC-DFTB calculated properties, including electric, structural, surface, and interface properties, and Li+ solvation energy and diffusion coefficient in liquid EC agreed well with DFT results. The effect of SEI thickness in blocking electron transfer and preventing electrolyte reduction was captured by a Li/Li2CO3/liquid-EC interface model. The newly developed SCC-DFTB parameters provide a reliable and transferable method to simulate charge transfer reactions at the complex Li–metal/SEI/electrolyte for Li-ion batteries.

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Section: Computational Detailsmentioning

confidence: 99%

Transferable Self-Consistent Charge Density Functional Tight-Binding Parameters for Li–Metal and Li-Ions in Inorganic Compounds and Organic Solvents

2018

J. Phys. Chem. C

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“…The present electronic parameters for a Zr–Zr pair were generated for the 5s, 5p, and 4d valence shells using the relativistic parameterization process. The shape of the Woods–Saxon confining potential for the Zr pseudoatomic orbitals was determined following the band structure fitting strategy outlined by Witek et al , The reference DFT valence and low-lying conduction bands were calculated with the PBE functional and the projector-augmented wave (PAW) method for the HCP crystal structure (Figure a). We employed the PSO-based band structure fitting as implemented in the ADPT code. , …”

Section: Methodsmentioning

confidence: 99%

Density-Functional Tight-Binding Parameters for Bulk Zirconium: A Case Study for Repulsive Potentials

et al. 2021

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Density-functional tight-binding (DFTB) parameters are presented for the simulation of the bulk phases of zirconium. Electronic parameters were obtained using a band structure fitting strategy, while two-center repulsive potentials were created by particle swarm optimization. As objective functions for the repulsive potential fitting, we employed the Birch–Murnaghan equations of state for hexagonal close-packed (HCP), body-centered cubic (BCC) and ω phases of Zr from density-functional theory (DFT). When fractional atomic coordinates are not allowed to change in the generation of the equation-of-state curves, long-range repulsive DFTB potentials are able to almost perfectly reproduce equilibrium structures, relative DFT energies of the bulk phases, and bulk moduli. However, the same potentials lead to artifacts in the DFTB potential energy surfaces when atom positions in the unit cell are allowed to fully relax during the change of unit cell parameters. Conventional short-range repulsive DFTB potentials, while inferior in their ability to reproduce DFT bulk energetics, are able to correctly reproduce the qualitative shape of the DFT potential energy surfaces, including the location of global minima, and can therefore be considered more transferable.

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“…Conventionally the order σ of the confining potential was usually set to 2 or 4, and the distance

r_{0}

was usually set to roughly twice the atomic covalent radius. Recently, the parameters σ and

r_{0}

can be both set as real numbers and optimized to electronic band structures of the elementary bulk solids …”

Section: Dftb Parameterizationmentioning

confidence: 99%

“…Another form of the confining potential, that has been employed within the relativistic Dirac‐Kohn‐Sham (DKS) formalism for generating the AOs and density is represented by the Woods–Saxon potential, which has three parameters: height W , half‐height radius

r_{0}

, and slope a at distance r 0 , and is given as

true V_{conf} (r) = - \frac{W}{1 + prefixexp [- a (r - r_{0})]} .

…”

Section: Dftb Parameterizationmentioning

confidence: 99%

Development of Divide‐and‐Conquer Density‐Functional Tight‐Binding Method for Theoretical Research on Li‐Ion Battery

Chou

Sakti

Nishimura

et al. 2018

The Chemical Record

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The density‐functional tight‐binding (DFTB) method is one of the useful quantum chemical methods, which provides a good balance between accuracy and computational efficiency. In this account, we reviewed the basis of the DFTB method, the linear‐scaling divide‐and‐conquer (DC) technique, as well as the parameterization process. We also provide some refinement, modifications, and extension of the existing parameters that can be applicable for lithium‐ion battery systems. The diffusion constants of common electrolyte molecules and LiTFSA salt in solution have been estimated using DC‐DFTB molecular dynamics simulation with our new parameters. The resulting diffusion constants have good agreement to the experimental diffusion constants.

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Automatized Parameterization of the Density‐functional Tight‐binding Method. II. Two‐center Integrals

Cited by 15 publications

References 80 publications

Transferable Self-Consistent Charge Density Functional Tight-Binding Parameters for Li–Metal and Li-Ions in Inorganic Compounds and Organic Solvents

Transferable Self-Consistent Charge Density Functional Tight-Binding Parameters for Li–Metal and Li-Ions in Inorganic Compounds and Organic Solvents

Density-Functional Tight-Binding Parameters for Bulk Zirconium: A Case Study for Repulsive Potentials

Development of Divide‐and‐Conquer Density‐Functional Tight‐Binding Method for Theoretical Research on Li‐Ion Battery

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