Reliability of universal ML interatomic potentials in real-world applications

Determine the reliability and effectiveness of universal machine learning interatomic potentials (uMLIPs) when applied to practical, real-world atomistic simulation tasks, establishing whether these models can robustly support downstream simulations and property predictions beyond fitting energies and forces.

Background

Universal machine learning interatomic potentials (uMLIPs) promise near–quantum accuracy with far lower computational cost and broad applicability across materials classes. Yet, most prior assessments emphasize training-aligned metrics (energy/force/stress fitting) rather than end-to-end, domain-relevant tasks encountered in realistic simulations.

This work focuses on challenging nanoporous materials, particularly metal–organic frameworks (MOFs), where porosity, diverse chemistries, and coordination bonds stress-test generalization. The stated open question motivates the development of a task-oriented benchmark (MOFSimBench) to assess whether uMLIPs are ready for practical deployment in such settings.

References

However, their reliability and effectiveness in practical, real-world applications remain an open question.

— MOFSimBench: Evaluating Universal Machine Learning Interatomic Potentials In Metal--Organic Framework Molecular Modeling  (2507.11806 - Kraß et al., 16 Jul 2025) in Abstract

Calibration of the uncertainty is itself an open methodological question, but the community can and should converge on a baseline practice now and refine it later.

— A strategic roadmap for an atomistic machine-learning ecosystem  (2609.39090 - Behler et al., 30 Sep 2026) in Section 4.3, “Uncertainty and validity”

Integrating time-dependent behavior into architectures designed for static property prediction remains an open challenge.

— Atoms to Processes: The Role of Artificial Intelligence and Machine Learning in Chemical Engineering  (2610.02014 - Baldea et al., 1 Oct 2026) in Section 7.4, “Implementation and Deployment Barriers”