The estimation of the second virial coefficients of He and N2 based on neural network potentials with quantum mechanical calculations

  • Kwon, Taejin
  • Song, Han Wook
  • Woo, Sam Yong
  • Kim, Jong-Ho
  • Sung, Bong June
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초록

We test the accuracy of the neural network interaction potentials against accurate thermodynamic data of He and N2. We perform single point energy calculations at CCSD(T) level, construct the intermolecular interactions by using neural networks, and perform Monte Carlo simulations to calculate virial coefficients. We find that the deviation of virial coefficients from previous studies is small for He while the difference is about 3 cm3mol- 1 for N2. Our results show that when trying to obtain accurate thermodynamic data from the neural network interaction potentials, not only the level of quantum chemical calculations should be an important factor, but also at least thousands of training data points would be required.

키워드

Second virial coefficientNeural network potentialDeep learningQuantum calculationTHERMOPHYSICAL PROPERTIESENERGY SURFACEMOLECULE PAIRGASHELIUMVALUESTEMPERATUREPRESSURESTANDARDNITROGEN
제목
The estimation of the second virial coefficients of He and N2 based on neural network potentials with quantum mechanical calculations
저자
Kwon, TaejinSong, Han WookWoo, Sam YongKim, Jong-HoSung, Bong June
DOI
10.1016/j.chemphys.2021.111231
발행일
2021-08-01
유형
Article
저널명
Chemical Physics
548