DeepPolaron ML-MD simulations show rutile electrons form Ti-localized polarons hopping along [001] with 39 meV barrier and 4.4e-2 cm2/Vs mobility, while anatase holes form O-localized polarons hopping to second neighbors with 139 meV barrier and 1.4e-3 cm2/Vs mobility.
year = 2014
4 Pith papers cite this work. Polarity classification is still indexing.
4
Pith papers citing it
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Constraint-aware neural networks clone known semilocal XC functionals more accurately in self-consistent calculations, transfer well from molecules to solids, and outperform unconstrained models across multiple tests.
Ensemble TDDFT generalizes TDDFT and EDFT by ensemble-extending the Gross-Kohn equation and XC kernel and applying EDFT to time-dependent problems, illustrated on the 2-site Hubbard model.
Pulse-optimized implementations of single- and double-qubit excitations in VQE reduce runtimes by up to 15.3 times on silicon spin-qubit processors.
citing papers explorer
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Polaron Transport in TiO$_{2}$ from Machine Learning Molecular Dynamics
DeepPolaron ML-MD simulations show rutile electrons form Ti-localized polarons hopping along [001] with 39 meV barrier and 4.4e-2 cm2/Vs mobility, while anatase holes form O-localized polarons hopping to second neighbors with 139 meV barrier and 1.4e-3 cm2/Vs mobility.
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Constraint-aware functional cloning for stable and transferable machine-learned density functional theory
Constraint-aware neural networks clone known semilocal XC functionals more accurately in self-consistent calculations, transfer well from molecules to solids, and outperform unconstrained models across multiple tests.
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Ensemble Time-Dependent Density Functional Theory
Ensemble TDDFT generalizes TDDFT and EDFT by ensemble-extending the Gross-Kohn equation and XC kernel and applying EDFT to time-dependent problems, illustrated on the 2-site Hubbard model.
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Pulse-optimised circuit elements for scalable and noise-resilient quantum chemistry
Pulse-optimized implementations of single- and double-qubit excitations in VQE reduce runtimes by up to 15.3 times on silicon spin-qubit processors.