Hydrogen bond energy estimation (H‐BEE) in large molecular clusters: A Python program for quantum chemical investigations

Author:

Ahirwar Mini Bharati1ORCID,Khire Subodh S.2ORCID,Gadre Shridhar R.34ORCID,Deshmukh Milind M.1ORCID

Affiliation:

1. Department of Chemistry Dr. Harisingh Gour Vishwavidyalaya (A Central University) Sagar India

2. RIKEN Center for Computational Science Kobe Japan

3. Department of Scientific Computing, Modelling & Simulation Savitribai Phule Pune University Pune India

4. Department of Chemistry Savitribai Phule Pune University Pune India

Abstract

AbstractA procedure, derived from the fragmentation‐based molecular tailoring approach (MTA), has been proposed and extensively applied by Deshmukh and Gadre for directly estimating the individual hydrogen bond (HB) energies and cooperativity contributions in molecular clusters. However, the manual fragmentation and high computational cost of correlated quantum chemical methods make the application of this method to large molecular clusters quite formidable. In this article, we report an in‐house developed software for automated hydrogen bond energy estimation (H‐BEE) in large molecular clusters. This user‐friendly software is essentially written in Python and executed on a Linux platform with the Gaussian package at the backend. Two approximations to the MTA‐based procedure, viz. the first spherical shell (SS1) and the Fragments‐in‐Fragments (Frags‐in‐Frags), enabling cost‐effective, automated evaluation of HB energies and cooperativity contributions, are also implemented in this software. The software has been extensively tested on a variety of molecular clusters and is expected to be of immense use, especially in conjunction with correlated methods such as MP2, CCSD(T), and so forth.

Publisher

Wiley

Subject

Computational Mathematics,General Chemistry

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3