Reproducible Orchestration of Best Practices for Reaction Path Optimization with the Nudged Elastic Band

Fuente: arXiv
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Main Author: Goswami, Rohit
Format: Preprint
Published: 2026
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author Goswami, Rohit
author_facet Goswami, Rohit
contents The nudged elastic band (NEB) method is the standard approach for finding minimum energy paths and transition states on potential energy surfaces. Practical NEB calculations require several pre-processing steps: endpoint minimization, structural alignment, and initial path generation. These steps are typically handled by ad-hoc scripts or manual intervention, introducing errors and hindering reproducibility. We present a fully automated, open-source Snakemake workflow for small gas phase molecules that couples modern machine learning potentials (PET-MAD) to the eOn saddle point search software. Each step of the calculation lifecycle is encoded as an explicit dependency graph, from model retrieval and endpoint preparation through path initialization and band optimization. The workflow resolves all software dependencies from conda-forge, ensuring identical execution across platforms. Validation on the HCN to HNC isomerization demonstrates that the automated pipeline recovers the known single-barrier energy profile and product energy without manual intervention.
format Preprint
id arxiv_https___arxiv_org_abs_2603_14737
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Reproducible Orchestration of Best Practices for Reaction Path Optimization with the Nudged Elastic Band
Goswami, Rohit
Chemical Physics
The nudged elastic band (NEB) method is the standard approach for finding minimum energy paths and transition states on potential energy surfaces. Practical NEB calculations require several pre-processing steps: endpoint minimization, structural alignment, and initial path generation. These steps are typically handled by ad-hoc scripts or manual intervention, introducing errors and hindering reproducibility. We present a fully automated, open-source Snakemake workflow for small gas phase molecules that couples modern machine learning potentials (PET-MAD) to the eOn saddle point search software. Each step of the calculation lifecycle is encoded as an explicit dependency graph, from model retrieval and endpoint preparation through path initialization and band optimization. The workflow resolves all software dependencies from conda-forge, ensuring identical execution across platforms. Validation on the HCN to HNC isomerization demonstrates that the automated pipeline recovers the known single-barrier energy profile and product energy without manual intervention.
title Reproducible Orchestration of Best Practices for Reaction Path Optimization with the Nudged Elastic Band
topic Chemical Physics
url https://arxiv.org/abs/2603.14737