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Overcoming the barrier of orbital-free density functional theory for molecular systems using deep learning - Nature Computational Science

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Overcoming the barrier of orbital-free density functional theory for molecular systems using deep learning - Nature Computational Science

Orbital-free density functional theory (OFDFT) is a quantum chemistry formulation that has a lower cost scaling than the prevailing Kohn–Sham DFT, which is increasingly desired for contemporary molecular research. However, its accuracy is limited by the kinetic energy density functional, which is notoriously hard to approximate for non-periodic molecular systems. Here we propose M-OFDFT, an OFDFT approach capable of solving molecular systems using a deep learning functional model.

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Overcoming the barrier of orbital-free density functional theory for molecular systems using deep learning - Nature Computational Science

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Overcoming the barrier of orbital-free density functional theory for molecular systems using deep learning - Nature Computational Science

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