H + HO → H + HO 反应在精确的基本不变量神经网络势能面上的速率系数。

Rate coefficients of the H + HO → H + HO reaction on an accurate fundamental invariant-neural network potential energy surface.

机构信息

Department of Chemical Physics, University of Science and Technology of China, Jinzhai Road 96, Hefei 230026, China.

Department of Applied Chemistry, Northwestern Polytechnical University, Youyi West Road 127, Xi'an 710072, China.

出版信息

J Chem Phys. 2018 Nov 7;149(17):174303. doi: 10.1063/1.5063613.

DOI:10.1063/1.5063613

PMID:30409010

Abstract

The rate coefficients of the H + HO → H + HO reaction are calculated using the ring polymer molecular dynamics (RPMD), quasi-classical trajectory (QCT), and canonical variational transition state theory (CVT) with small curvature tunneling (SCT) correction, in conjunction with the recently constructed fundamental invariant-neural network (FI-NN) potential energy surface (PES) [X. Lu , Phys. Chem. Chem. Phys. , 23095 (2018)]. In RPMD calculations, 32, 16, and 8 beads are used for computing the rate coefficients at 200 K ≤ ≤ 400 K, 500 K ≤ ≤ 700 K, and 700 K < ≤ 1000 K, respectively. Given that the previous experimental rate coefficients vary widely, in particular, at low temperatures, the present RPMD rate coefficients agree well with most of the experimental results. In addition, comparing with some experimental values, the present QCT and CVT/SCT calculations on the FI-NN PES also predict accurate results at some temperatures. These results strongly support the accuracy of the present dynamics calculations as well as the full-dimensional FI-NN PES.

摘要

使用环聚合物分子动力学（RPMD）、准经典轨迹（QCT）和正则变分过渡态理论（CVT）与小曲率隧穿（SCT）修正，结合最近构建的基本不变量神经网络（FI-NN）势能面（PES）[X. Lu, Phys. Chem. Chem. Phys.，23095（2018）]，计算了 H + HO → H + HO 反应的速率系数。在 RPMD 计算中，分别使用 32、16 和 8 个珠来计算 200 K ≤ ≤ 400 K、500 K ≤ ≤ 700 K 和 700 K < ≤ 1000 K 的速率系数。由于先前的实验速率系数差异很大，特别是在低温下，本研究的 RPMD 速率系数与大多数实验结果吻合良好。此外，与一些实验值相比，FI-NN PES 上的本研究 QCT 和 CVT/SCT 计算在一些温度下也预测出了准确的结果。这些结果有力地支持了本动力学计算以及全维 FI-NN PES 的准确性。