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VibroML toolkit automates material stability analysis and remediation with ML

By PulseAugur Editorial · [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

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 →

AI-generated summary · Google Gemini · from 3 sources. How we write summaries →

VibroML toolkit automates material stability analysis and remediation with ML

COVERAGE [3]

  1. arXiv cs.AI TIER_1 English(EN) · 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 English(EN) · 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 English(EN) ·

    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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