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VibroML toolkit automates material stability analysis and remediation with ML

By PulseAugur Editorial · Summary by gemini-2.5-flash-lite from 3 sources

Researchers have developed VibroML, an open-source Python toolkit designed to automate the remediation of dynamic instabilities in crystalline materials. This toolkit utilizes machine-learned potentials and an energy-guided genetic algorithm to efficiently discover stable polymorphs, surpassing traditional methods. VibroML also incorporates automated molecular dynamics for finite-temperature validation and can be coupled with structure prediction engines to stabilize complex crystal topologies through alloying. AI

Summary written by gemini-2.5-flash-lite from 3 sources. How we write summaries →

IMPACT Automates discovery of stable crystalline materials, accelerating materials science research and development.

RANK_REASON The cluster describes a new open-source toolkit for materials science research published on arXiv.

Read on arXiv cs.LG →

COVERAGE [3]

  1. arXiv cs.AI TIER_1 · Rog\'erio Almeida Gouv\^ea, Gian-Marco Rignanese ·

    VibroML: an automated toolkit for high-throughput vibrational analysis and dynamic instability remediation of crystalline materials using machine-learned potentials

    arXiv:2604.27685v1 Announce Type: cross Abstract: While machine-learned interatomic potentials (MLIPs) accelerate phonon dispersion calculations, merely identifying dynamical instabilities in computationally predicted materials is insufficient; automated pathways to resolve them …

  2. arXiv cs.LG TIER_1 · Gian-Marco Rignanese ·

    VibroML: an automated toolkit for high-throughput vibrational analysis and dynamic instability remediation of crystalline materials using machine-learned potentials

    While machine-learned interatomic potentials (MLIPs) accelerate phonon dispersion calculations, merely identifying dynamical instabilities in computationally predicted materials is insufficient; automated pathways to resolve them are required. We introduce VibroML, an open-source…

  3. Hugging Face Daily Papers TIER_1 ·

    VibroML: an automated toolkit for high-throughput vibrational analysis and dynamic instability remediation of crystalline materials using machine-learned potentials

    While machine-learned interatomic potentials (MLIPs) accelerate phonon dispersion calculations, merely identifying dynamical instabilities in computationally predicted materials is insufficient; automated pathways to resolve them are required. We introduce VibroML, an open-source…

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