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Long-Range Fit: A Software Package for the Representation and Study of Long-Range Molecular Interactions
Adrian L Batista-Planas1, Ernesto Quintas-Sánchez1, Richard Dawes1
1Department of Chemistry, Missouri University of Science and Technology, Rolla, Missouri 65409, United States.
We developed long-range-fit (LRF), a software package that automates the calculation of long-range molecular interactions. LRF simplifies complex calculations for predicting molecular system behavior, especially in low-temperature and low-density conditions.
Area of Science:
- * Computational chemistry and molecular modeling.
- * Quantum chemistry and theoretical physics.
Background:
- * Accurate description of intermolecular forces is crucial for molecular system modeling.
- * Long-range molecular interactions (electrostatic, induction, dispersion) are vital in low-temperature/low-density regimes.
- * Traditional methods using perturbation theory and multipolar expansions are complex and system-dependent.
Purpose of the Study:
- * To automate the generation and fitting of long-range interaction terms for arbitrary molecules.
- * To provide a user-friendly software package for simplifying complex theoretical calculations.
- * To enable accurate modeling of molecular systems by addressing the challenges of analytical expression derivation.
Main Methods:
- * Development of the long-range-fit (LRF) software package.
- * Derivation and implementation of all interaction terms up to 15th order without approximations.
- * Utilized spherical tensor representation with symmetry adaptation to all molecular point-group symmetries.
Main Results:
- * Automated generation and fitting of long-range interaction terms for diverse molecular systems.
- * Implementation of high-order (up to 15th) interaction terms without approximations.
- * Developed a software package compatible with various close-interaction region representations.
Conclusions:
- * The long-range-fit (LRF) software package successfully automates complex calculations of intermolecular forces.
- * LRF provides a robust and efficient tool for researchers in computational chemistry and physics.
- * The generated potential energy surface enhances the accuracy and applicability of molecular modeling.
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