PASTA: Python Algorithms for Searching Transition stAtes
Sudipta Kundu, Satadeep Bhattacharjee, Seung-Cheol Lee, Manish Jain

TL;DR
PASTA is a Python module that efficiently calculates energy barriers and locates transition states in chemical reactions, compatible with multiple DFT packages and adaptable to various computational resources.
Contribution
It introduces a user-friendly, extendable Python tool for transition state searches that integrates with popular DFT codes and supports resource-efficient calculations.
Findings
Supports multiple DFT packages: VASP, Quantum Espresso, SIESTA.
Enables both sequential and parallel calculations for large systems.
Flexible for users with limited or abundant computational resources.
Abstract
Chemical reactions are often associated with an energy barrier along the reaction pathway which hinders the spontaneity of the reaction. Changing the energy barrier along the reaction pathway allows one to modulate the performance of a reaction. We present a module, Python Algorithms for Searching Transition stAtes (PASTA), to calculate the energy barrier and locate the transition state of a reaction efficiently. The module is written in python and can perform nudged elastic band, climbing image nudged elastic band and automated nudged elastic band calculations. These methods require the knowledge of the potential energy surface (and its gradient along some direction). This module is written such that it works in conjunction with density functional theory (DFT) codes to obtain this information. Presently it is interfaced with three well known DFT packages: Vienna Ab initio Simulation…
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