解锁机器学习原子间潜力的核心性能

原子模拟帮助研究者了解分子和材料的行为方式，从化学反应和相位向机械故障过渡。 这些模拟带有成本准确性的取舍。 密度功能理论(DFT)等量子-机械方法可以提供准确的能量和力，但其计算成本往往限制其对大型系统或长。

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Atomistic simulations help researchers understand how molecules and materials behave, from chemical reactions and phase transitions to mechanical failure. These simulations come with a cost-accuracy trade-off. Quantum-mechanical methods such as density functional theory (DFT) can provide accurate energies and forces, but their computational cost often limits their use for large systems or long…

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