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Recent advances in machine learning- assisted multiscale design of energy materials

1 Pith paper cite this work, alongside 153 external citations. Polarity classification is still indexing.

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153 external citations · OpenAlex

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2026 1

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Machine Learning Hamiltonians are Accurate Energy-Force Predictors

physics.comp-ph · 2026-02-18 · conditional · novelty 7.0

A Hamiltonian-predicting neural network, QHFlow2, reaches NequIP-level force accuracy and 20× lower energy errors than MLIPs when energies and forces are computed directly from its predicted Hamiltonians.

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  • Machine Learning Hamiltonians are Accurate Energy-Force Predictors physics.comp-ph · 2026-02-18 · conditional · none · ref 2021

    A Hamiltonian-predicting neural network, QHFlow2, reaches NequIP-level force accuracy and 20× lower energy errors than MLIPs when energies and forces are computed directly from its predicted Hamiltonians.