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Quantum rotational dynamics of l -C 4 ( 3 Σ-g) by H 2 at low temperatures employing a machine learning augmented potential energy surface.

Pooja ChahalApoorv KushwahaThogluva Janardhanan Dhilip Kumar
Published in: Physical chemistry chemical physics : PCCP (2024)
A new four dimensional (4D) ab initio potential energy surface (PES) is generated for the collision of C 4 ( 3 Σ g - ) with H 2 ( 1 Σ g ), considering both molecules as rigid rotors. A supervised neural network model is created to augment the ab initio PES and to get the missing data points. Furthermore, space fixed expansion of the augmented PES is carried out using a least squares fit over two spherical harmonics terms, resulting in radial coefficients ( λ 1 , λ 2 , and λ ). The centre of symmetry in both C 4 and H 2 forces λ 1 and λ 2 to have even values, respectively. Moreover, the rotational states of C 4 are only populated by odd levels due to its ground state triplet symmetry and the nuclear spin ( I = 0) of 12 C. The cross-sections and rate coefficients with para and ortho H 2 partners are studied for various odd state transitions, where the rate coefficients of the ortho are 10-20% higher than those of the latter. The de-excitation rates obtained by the para H 2 collisions are also compared to those of He and are found to be ∼1.7-2.8 times the He rates, across various order transitions. The simple scaling of He rates using a factor of 1.38 proves insufficient to describe para H 2 rates. Therefore, these results show the importance of explicitly studying H 2 as an important colliding partner, governing the kinetics of various rotational processes in the interstellar space.
Keyphrases
  • machine learning
  • neural network
  • big data
  • energy transfer
  • molecular dynamics
  • electronic health record
  • climate change
  • human health
  • room temperature