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The mathematical expression known as the wave function, ψ, contains information about each orbital and the wavelike properties of electrons in an isolated atom. When atoms are bound together in a molecule, the wave functions combine to produce new mathematical descriptions that have different shapes. This process of combining the wave functions for atomic orbitals is called hybridization and is mathematically accomplished by the linear combination of atomic orbitals. The new orbitals that...

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Updated: Sep 10, 2025

Computation of Atmospheric Concentrations of Molecular Clusters from ab initio Thermochemistry

Computation of Atmospheric Concentrations of Molecular Clusters from ab initio Thermochemistry

Published on: April 8, 2020

An Automated Intermolecular Reaction Discovery Approach Relying on Heuristic Atom-Partitioned Frontier Orbital

Ying Chen¹, Christoph Bannwarth¹

¹Institute of Physical Chemistry, RWTH Aachen University, Melatener Str. 20, 52074 Aachen, Germany.

Journal of Chemical Information and Modeling

|August 19, 2025

Summary

This summary is machine-generated.

This study introduces a new algorithm for rapidly exploring chemical reaction products using computational methods. The automated approach, based on electronic structure calculations, significantly reduces manual effort and achieves high accuracy in predicting reaction outcomes.

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Last Updated: Sep 10, 2025

Computation of Atmospheric Concentrations of Molecular Clusters from ab initio Thermochemistry

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Published on: April 8, 2020

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NMR-Based Fragment Screening in a Minimum Sample but Maximum Automation Mode

NMR-Based Fragment Screening in a Minimum Sample but Maximum Automation Mode

Published on: June 4, 2021

Area of Science:

Computational Chemistry
Chemical Reaction Dynamics

Background:

Computational exploration of chemical reactions aids understanding but is labor-intensive.
Existing methods often require significant chemical intuition and manual intervention.

Purpose of the Study:

To develop a novel, automated algorithm for fast exploration of products in bimolecular reactions.
To reduce manual effort and enhance efficiency in chemical reaction discovery.

Main Methods:

Algorithm utilizes atomistic features from inexpensive electronic structure theory calculations.
Automated workflow includes reactivity site assessment, trial coordinate construction, and autonomous exploration.
Product exploration employs harmonic force field optimization.

Main Results:

The algorithm significantly reduces manual effort in reaction exploration.
The harmonic force field optimization approach achieves ~97% success in reproducing reference outcomes.
The method ensures both reliability and computational efficiency.

Conclusions:

The developed algorithm and associated package (aRST) offer an efficient and reliable tool for computational reaction exploration.
This approach democratizes large-scale reaction discovery by minimizing the need for expert intuition.