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Updated: May 13, 2026

Analyzing Melts and Fluids from Ab Initio Molecular Dynamics Simulations with the UMD Package
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relentless: Transparent, reproducible molecular dynamics simulations for optimization.

Adithya N Sreenivasan1,2, C Levi Petix3, Zachary M Sherman4

  • 1McKetta Department of Chemical Engineering, The University of Texas at Austin, Austin, Texas 78712, USA.

The Journal of Chemical Physics
|December 4, 2024
PubMed
Summary
This summary is machine-generated.

Relentless is an open-source Python package for optimizing molecular dynamics simulations. It streamlines computational materials design by enabling targeted structure design through pairwise interaction optimization.

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Area of Science:

  • Computational chemistry
  • Materials science
  • Software development

Background:

  • Molecular dynamics (MD) simulations are crucial for understanding materials at the atomic level.
  • Optimizing objective functions within MD requires specialized tools for parameterization and analysis.
  • Existing workflows can be complex, hindering transparency and reproducibility.

Purpose of the Study:

  • To introduce Relentless, an open-source Python package designed to optimize objective functions computed via MD simulations.
  • To provide a high-level, extensible interface for seamless integration with established MD software.
  • To facilitate gradient-based optimization for computational materials design.

Main Methods:

  • Development of the Relentless Python package with a focus on extensibility.
  • Implementation of interfaces for native simulation setup, execution, and analysis.
  • Application of Relentless within the framework of relative entropy minimization.
  • Demonstration of designing pairwise interactions for targeted structure formation.

Main Results:

  • Relentless successfully enables gradient-based optimization of MD simulations.
  • The package facilitates the design of specific inter-particle interactions to achieve desired material structures.
  • Demonstrated ability to streamline complex computational workflows.

Conclusions:

  • Relentless offers a powerful and flexible platform for advancing computational materials design.
  • The package enhances transparency and reproducibility in MD-driven research.
  • It simplifies the optimization process, accelerating the development of new materials methodologies.