首页|构建范德华复合物分子间势能面的神经网络方法

构建范德华复合物分子间势能面的神经网络方法

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本文提出了一种神经网络新方法用于构建范德华复合物的分子间势能面.该神经网络所使用的描述符分为两部分:径向部分表示单体的分子间伸缩振动,角度部分描述了分子间的相对取向.由于采用了束缚态计算中的对称性匹配转动基函数作为角度描述符,可以确保势能面具有正确的对称性.旋转基函数的数量可以由其中的角动量量子数最大值控制,并且可以通过限制量子数来描述刚性单体分子的对称性.本研究推导了五种范德华复合物的描述符,包括原子-线性、原子-非线性、线性-线性、线性-非线性和非线性-非线性分子复合物.利用该方法构建了两个范德华复合物的势能面:Ar-NaCl和N2-OCS.拟合能量与从头计算能量之间的均方根误差值分别为0.11 cm-1和0.26 cm-1,验证了该方法可以准确构建高精度范德华复合物势能面.
Neural Network Method for Constructing Intermolecular Potential Energy Surfaces of van der Waals Complexes
This study proposes a new ap-proach for constructing inter-molecular potential energy sur-faces(PESs)of van der Waals(vdW)complexes using neural networks.The descriptors uti-lized in this neural network model are split into two parts:radial parts representing the in-termolecular stretching vibra-tions between monomers and angular parts describing the relative orientation of these molecules.Specifically,the parity-adapted rotational basis functions used in the bound state calculation are taken as the angular descriptors,which ensure the correct symmetry of the PES.The number of orthogonal rotational basis functions is controlled by the maximum val-ue of the angular momentum quantum number.In addition,the symmetry of monomer molecules is achieved by restricting the quantum number of the rotational basis function.The descriptors for five types of van der Waals complexes,including atom-linear,atom-nonlinear,linear-linear,linear-nonlinear and nonlinear-nonlinear molecules complexes,have been de-rived in this work.The neural network models with these newly developed descriptors were then applied to construct PESs of two van der Waals complexes,Ar-NaCl and N2-OCS.The root-mean-square error values between the fitted and ab initio energies are found to be 0.11 cm-1 and 0.26 cm-1 for Ar-NaCl and N2-OCS,respectively.These results indicate that this method is accurate and effective for constructing high-precision PESs of vdW complexes.

Neural networkPotential energy surfaceVan der Waals complexSymmetry-adapted rotational basisDescriptor

程通、杨明娟、宋宏伟、郑利敏、郑锐、杨明晖

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华北水利电力大学电子工程学院,郑州 450011

中国科学院精密测量科学与技术创新研究院,波谱与原子分子物理国家重点实验室,武汉 430071

中国科学院大学,北京 100049

中原工学院,郑州 450007

华中科技大学武汉光电国家研究中心,武汉 430074

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神经网络 势能面 范德华复合物 对称性匹配转动基函数 描述符

国家自然科学基金国家自然科学基金国家自然科学基金国家自然科学基金Limin Zheng thanks the supports of Natural Science Foundation of Henan ProvinceState Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics,ChinaZhongyuan University of Technology

21973108219210042197310911304095222300420494T151907K2022TD002

2024

10.1063/1674-0068/cjcp2304040

化学物理学报(英文版)
中国物理学会

化学物理学报(英文版)

CSTPCDEI
影响因子：0.162
ISSN：1674-0068
年,卷(期)：2024.37(1)