Computational investigation of hydrogen storage on scandium–acetylene system

Ma, Lijuan; Jia, Jianfeng; Wu, Hai‐Shun

doi:10.1016/j.ijhydene.2014.10.136

Cited by 30 publications

(8 citation statements)

References 50 publications

(44 reference statements)

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“…Optimization of the usable capacity for typical fixed operating pressures of 5 and 100 bar gives an optimal value for the Gibbs free energy of adsorption (Δ G ads ). Assuming a correlation between enthalpy and entropy of adsorption in porous materials gives a range of −15 to −25 kJ/mol for the optimal value for enthalpy of adsorption (Δ H ads ). − The internal energy of binding, which is the largest component of Δ H ads , can be computed using different quantum chemistry methods, including, but not limited to, density functional theory (DFT), ,,, Møller-Plesset perturbation theory (MP2), − and different variants of coupled-cluster theory. − Each of these methods have different accuracies and computational costs associated with them.…”

Section: Introductionmentioning

confidence: 99%

Assessment of Performance of Density Functionals for Predicting Potential Energy Curves in Hydrogen Storage Applications

Veccham

Head‐Gordon

2021

J. Phys. Chem. A

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The availability of accurate computational tools for modeling and simulation is vital to accelerate the discovery of materials capable of storing hydrogen (H2) under given parameters of pressure swing and temperature. Previously, we compiled the H2Bind275 data set consisting of equilibrium geometries and assessed the performance of 55 density functionals over this data set (J. Chem. Theory Comput.20201649634982). As it is crucial for computational tools to accurately model the entire potential energy curve (PEC), in addition to the equilibrium geometry, we extended this data set with 389 new data points to include two compressed and three elongated geometries along 78 PECs for H2 binding, forming the H2Bind78 × 7 data set. By assessing the performance of 55 density functionals on this significantly larger and more comprehensive H2Bind78 × 7 data set, we identified the best performing density functionals for H2 binding applications: PBE0-DH, ωB97X-V, ωB97M-V, and DSD-PBEPBE-D3(BJ). The addition of Hartree–Fock exchange improves the performance of density functionals, albeit not uniformly throughout the PEC. We recommend the usage of ωB97X-V and ωB97M-V density functionals as they offer good performance for both geometries and energies. In addition, we also identified B97M-V and B97M-rV as the best semilocal density functionals for predicting H2 binding energy at its equilibrium geometry.

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Section: Introductionmentioning

confidence: 99%

Assessment of Performance of Density Functionals for Predicting Potential Energy Curves in Hydrogen Storage Applications

Veccham

Head‐Gordon

2021

J. Phys. Chem. A

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“…[11][12][13] The internal energy of binding, which is the largest component of ∆H ads , can be computed using different quantum chemistry methods, including, but not limited to, density functional theory (DFT), 9,10,14,15 Møller-Plesset perturbation theory (MP2), [16][17][18] and different variants of coupled-cluster theory. [19][20][21] Each of these methods have different accuracies and computational costs associated with them.…”

Section: Introductionmentioning

confidence: 99%

Assessment of the Performance of Density Functionals for Predicting Potential Energy Curves in Hydrogen Storage Applications

Veccham¹,

Head‐Gordon²

2021

Preprint

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The availability of accurate computational tools for modeling and simulation is vital to accelerate the discovery of materials capable of storing hydrogen (H 2 ) under given parameters of pressure swing and temperature. Previously, we compiled the H2Bind275 dataset consisting of equilibrium geometries and assessed the performance of 55 density functionals over this dataset (Veccham, S. P.; Head-Gordon, M. J. Chem. Theory Comput., 2020, 16, 4963-4982). As it is crucial for computational tools to accurately model the entire potential energy curve (PEC), in addition to the equilibrium geometry, we have extended this dataset with 389 new data points to include two compressed and three elongated geometries along 78 PECs for H 2 binding, forming the H2Bind78×7 dataset. Assessing the performance of 55 density functionals on this significantly larger and more comprehensive H2Bind78×7 dataset, we have identified the best performing density functionals for H 2 binding applications: PBE0-DH, ωB97X-V, ωB97M-V, and DSD-PBEPBE-D3(BJ). Addition of Hartree Fock exchange improves the performance

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“…Related to the computational study in the chemical trapping of dihydrogen, noncovalent interactions must be taken into account [12], given the relatively weak attracting force-mostly dispersive-derived from two neutral molecules, leading to general complexes with formula Z:nH 2 , where Z is a neutral molecule and n is the number of H 2 molecules attached to the Z neutral system. A number of theoretical articles have been devoted to the interaction of dihydrogen with metallic systems [13][14][15][16][17][18][19][20][21][22].…”

Section: Introductionmentioning

confidence: 99%

Complexes Between Adamantane Analogues B4X6 -X = {CH2, NH, O ; SiH2, PH, S} - and Dihydrogen, B4X6:nH2 (n = 1–4)

2020

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In this work, we study the interactions between adamantane-like structures B4X6 with X = {CH2, NH, O ; SiH2, PH, S} and dihydrogen molecules above the Boron atom, with ab initio methods based on perturbation theory (MP2/aug-cc-pVDZ). Molecular electrostatic potentials (MESP) for optimized B4X6 systems, optimized geometries, and binding energies are reported for all B4X6:nH2 (n = 1–4) complexes. All B4X6:nH2 (n = 1–4) complexes show attractive patterns, with B4O6:nH2 systems showing remarkable behavior with larger binding energies and smaller B···H2 distances as compared to the other structures with different X.

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Computational investigation of hydrogen storage on scandium–acetylene system

Cited by 30 publications

References 50 publications

Assessment of Performance of Density Functionals for Predicting Potential Energy Curves in Hydrogen Storage Applications

Assessment of Performance of Density Functionals for Predicting Potential Energy Curves in Hydrogen Storage Applications

Assessment of the Performance of Density Functionals for Predicting Potential Energy Curves in Hydrogen Storage Applications

Complexes Between Adamantane Analogues B4X6 -X = {CH2, NH, O ; SiH2, PH, S} - and Dihydrogen, B4X6:nH2 (n = 1–4)

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