We present results illustrating the effects of using explicit summation terms for the $r^{-6}$ dispersion term on the interfacial properties of a Lennard-Jones fluid and SPC/E water. For the Lennard-Jones fluid, we find that the use of long-range summations, even with a short ``crossover radius,'' yields results that are consistent with simulations using large cutoff radii. Simulations of SPC/E water demonstrate that the long-range dispersion forces are of secondary importance to the Coulombic forces. In both cases, we find that the ratio of box size $L_{\parallel}$ to crossover radius $r_{\rm c}^{\mathbf k}$ plays an important role in determining the magnitude of the long-range dispersion correction, although its effect is secondary when Coulombic interactions are also present.
Ewald-based Long-Range Message Passing for Molecular Graphs
Max Planck Institute for the Science of Light（马克斯·普朗克光科学研究所）；Friedrich-Alexander-Universität Erlangen-Nürnberg（埃尔朗根-纽伦堡弗里德里希-亚历山大大学）；Ludwig-Maximilians-Universität München（慕尼黑路德维希-马克西米利安大学）；Technical University of Munich（慕尼黑工业大学）；Google Research（谷歌研究院）
Physics-Informed Long-Range Coulomb Correction for Machine-learning Hamiltonians
Key Laboratory of Computational Physical Sciences (Ministry of Education)（计算物理科学国家重点实验室（教育部））；Institute of Computational Physical Sciences（计算物理科学研究院）；State Key Laboratory of Surface Physics（表面物理国家重点实验室）；Department of Physics, Fudan University, Shanghai, 200433, China.（复旦大学物理系，上海，200433，中国）
Learning charges and long-range interactions from energies and forces
UC Berkeley（加州大学伯克利分校）；Bakar Institute of Digital Materials for the Planet, UC Berkeley（加州大学伯克利分校行星数字材料巴卡尔研究所）；The Institute of Science and Technology Austria（奥地利科学技术研究所）
Long-range electrostatics for machine learning interatomic potentials is easier than we thought
Department of Chemistry, UC Berkeley, California 94720, United States（加州大学伯克利分校化学系）；Chemical Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, California, 94720, United States（伯克利国家实验室化学科学部）；Bakar Institute of Digital Materials for the Planet, UC Berkeley, California 94720, United States（为地球数字化材料研究所）；The Institute of Science and Technology Austria, Am Campus 1, 3400 Klosterneuburg, Austria（奥地利科学与技术研究所）
