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Can Machine Learning Potentials Be More Accurate Than the Methods They Are Trained On?
Pavlo O. Dral, Yi-Fan Hou, Yuxinxin Chen +4
Although machine learning potentials (MLPs) generalize across configurational and chemical compound spaces, their accuracy is commonly believed to be limited by their training meth…
Science Done on a Machine by a Machine: AI Agents in Computational Chemistry
Pavlo O. Dral, Hassan Nawaz, Arif Ullah
We are witnessing an explosion of agentic systems for computational chemistry: from four in 2024 to seventeen in 2025 and over sixty now, surveyed here. What is delegated to these…
Toward Machine Learning Enhancement of Accelerated Surface Hopping with Scaled Spin--Orbit Couplings
Jakub Martinka, Mahesh Kumar Sit, Pavlo O. Dral +1
Surface hopping (SH) methods are typically employed to simulate ultrafast nonadiabatic processes, but long timescales often remain beyond their reach. To address this, accelerated…