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N. Lubbers

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Aug 2026

ALF: Open-Source Active Learning Framework for Atomistic Modeling

The Active Learning Framework (ALF), an open-source Python package designed to streamline the design and deployment of MLIP training datasets on High Performance Computing resources, is introduced, illustrating ALF’s effectiveness in compiling datasets that capture essential chemical and structural regimes.

V. Grizzi, P. Lohr, Nikita Fedik et al. · 0 citations
Open access Jul 2026

Reactive Chemistry at the Unrestricted Coupled Cluster Level: High-Throughput Calculations for Training Machine Learning Potentials

New methods and workflows to overcome the challenges inherent to automating unrestricted coupled cluster calculations are developed and a transferable MLIP for gas-phase reactions, trained on unrestricted CCSD(T) data is developed.

Alice E. A. Allen, Rui Li, Sakib Matin et al. · 0 citations