Author

Subramanian K. R. S. Sankaranarayanan

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Open access Sep 2026

Symbolic ensemble learning enables discovery of fast accurate physics-based interatomic potentials

A hybrid symbolic-neural framework is introduced that unifies the interpretability of the Embedded Atom Method with the adaptability of data-driven learning, and derives a composite potential that surpasses the fidelity of its constituent models.

Bilvin Varughese, Aditya Koneru, Adil Muhammad et al. · PHYSICAL REVIEW MATERIALS · 0 citations

#software testing Preprint Sep 2026

Agent-E2MD: Autonomous Translation of Interatomic Potential Equations into Physically Validated Pair Styles for Molecular Dynamics in LAMMPS

Agent-E2MD is introduced, a knowledge-guided agentic workflow that translates user-specified interatomic models into executable LAMMPS pair styles and demonstrates that the software architecture for an interatomic potential can be inferred from its physical and mathematical structure.

Bilvin Varughese, Orcun Yildiz, Aditya Koneru et al. · 0 citations

Preprint Aug 2026

AutoMOOSE: Use Case and Logical Views of Agentic Phase-Field Simulation Software

This work deploys AutoMOOSE as a agentic software, complementing the prior work which focused on development of the agentic tool, and describes its software framework and architecture through Use Case and logical views of the 1+5 architectural-views model.

Sukriti Manna, Henry Chan, Subramanian K. R. S. Sankaranarayanan · 0 citations