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

Abstract

A 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.

Edge-sharing water prisms

“…Note that the fragmentation-based molecular tailoring approach was recently proposed by Deshmukh and Gadre for directly estimating the individual hydrogen bond energies and cooperativity contributions in molecular clusters. 14,15 Applying this method for water clusters confirms the suitability of the SWEB model not only for polyhedral clusters, but also for nanostructures in which only a part of all H-bonds has a polyhedral environment. Indeed, in clusters in the form of a separate cube 14 and in the form of two adjacent cubes, 15 the energy of t 1-bonds is much greater.…”

“…14,15 Applying this method for water clusters confirms the suitability of the SWEB model not only for polyhedral clusters, but also for nanostructures in which only a part of all H-bonds has a polyhedral environment. Indeed, in clusters in the form of a separate cube 14 and in the form of two adjacent cubes, 15 the energy of t 1-bonds is much greater. In the second cluster, this bond classification applies only to the end 3-bonded H-bonds, which have a polyhedral environment.…”

Molecular Tailoring Approach for the Direct Estimation of Individual Noncovalent Interaction Energies in Molecular Systems

“…46 The MTA-based methodology and the computational strategies developed to overcome its limitations are now available in the form of an automated H-BEE (acronym of hydrogen bond energy estimation) Python code for molecular clusters. 92 The H-BEE software eliminates the laborious manual fragmentation and avoids tedious manual tracking of the common fragments in the Frags-in-Frags method. For instance, within the MTA-based method, the fragmentation can be done manually or with the help of an automated Python script called "Frgonl" encoded in MTASpec software.…”