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  • Formic Acid–Ammonia Heterodimer: A New Δ-Machine Learning CCSD(T)-Level Potential Energy Surface Allows Investigation of the Double Proton Transfer
Title: Formic Acid–Ammonia Heterodimer: A New Δ-Machine Learning CCSD(T)-Level Potential Energy Surface Allows Investigation of the Double Proton Transfer
The formic acid-ammonia dimer is an important example of a hydrogen-bonded complex in which a double proton transfer can occur. Its microwave spectrum has recently been reported and rotational constants and quadrupole coupling constants were determined. Calculated estimates of the double-well barrier and the internal barriers to rotation were also reported. Here we report a full-dimensional potential energy surface (PES) for this complex, using two closely related Δ-machine learning methods to bring it to the CCSD(T) level of accuracy. The PES dissociates smoothly and accurately. Using a 2d quantum model the ground vibrational-state tunneling splitting is estimted to be less than 10−4 cm−1. The dipole moment along the intrinsic reaction coordinate is calculated along with a Mullikan charge analysis and supports mildly ionic character of the minimum and strongly ionic character at the double-well barrier.  more » « less
Award ID(s):
1952289
PAR ID:
10518570
Author(s) / Creator(s):
; ; ; ; ; ; ;
Editor(s):
Gagliardi, Laura
Publisher / Repository:
American Chemical Society
Date Published:
Journal Name:
Journal of Chemical Theory and Computation
Edition / Version:
1
Volume:
20
Issue:
5
ISSN:
1549-9618
Page Range / eLocation ID:
1821 to 1828
Subject(s) / Keyword(s):
Energy Mathematical methods' Polarity' Potential energy Tunneling
Format(s):
Medium: X Size: 2.5Mb Other: pdf
Size(s):
2.5Mb
Sponsoring Org:
National Science Foundation
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