San Diego Supercomputer Center, University of California San Diego, La Jolla, California 92093, United States.
Department of Chemistry and Biochemistry, University of California San Diego, La Jolla, California 92093, United States.
J Chem Theory Comput. 2021 Jul 13;17(7):3931-3945. doi: 10.1021/acs.jctc.1c00069. Epub 2021 May 24.
Dinitrogen pentoxide (NO) is an important intermediate in the atmospheric chemistry of nitrogen oxides. Although there has been much research, the processes that govern the physical interactions between NO and water are still not fully understood at a molecular level. Gaining a quantitative insight from computer simulations requires going beyond the accuracy of classical force fields while accessing length scales and time scales that are out of reach for high-level quantum-chemical approaches. To this end, we present the development of MB-nrg many-body potential energy functions for nonreactive simulations of NO in water. This MB-nrg model is based on electronic structure calculations at the coupled cluster level of theory and is compatible with the successful MB-pol model for water. It provides a physically correct description of long-range many-body interactions in combination with an explicit representation of up to three-body short-range interactions in terms of multidimensional permutationally invariant polynomials. In order to further investigate the importance of the underlying interactions in the model, a TTM-nrg model was also devised. TTM-nrg is a more simplistic representation that contains only two-body short-range interactions represented through Born-Mayer functions. In this work, an active learning approach was employed to efficiently build representative training sets of monomer, dimer, and trimer structures, and benchmarks are presented to determine the accuracy of our new models in comparison to a range of density functional theory methods. By assessing the binding curves, distortion energies of NO, and interaction energies in clusters of NO and water, we evaluate the importance of two-body and three-body short-range potentials. The results demonstrate that our MB-nrg model has high accuracy with respect to the coupled cluster reference, outperforms current density functional theory models, and thus enables highly accurate simulations of NO in aqueous environments.
五氧化二氮（NO）是氮氧化物大气化学中的重要中间体。尽管已经进行了大量研究，但在分子水平上，控制 NO 与水之间物理相互作用的过程仍未完全理解。从计算机模拟中获得定量见解需要超越经典力场的精度，同时访问超出高级量子化学方法可达范围的长度和时间尺度。为此，我们提出了用于非反应性模拟的 NO 在水中的 MB-nrg 多体势能函数的开发。该 MB-nrg 模型基于电子结构计算在耦合簇理论水平，并与成功的 MB-pol 水模型兼容。它结合了多维置换不变多项式表示的多达三体力的短程相互作用，为长程多体相互作用提供了物理正确的描述。为了进一步研究模型中基础相互作用的重要性，还设计了 TTM-nrg 模型。TTM-nrg 是一种更简单的表示形式，仅包含通过 Born-Mayer 函数表示的二体力短程相互作用。在这项工作中，采用主动学习方法来有效地构建单体、二聚体和三聚体结构的代表性训练集，并提出了基准来确定我们的新模型与一系列密度泛函理论方法相比的准确性。通过评估结合曲线、NO 的变形能和 NO 和水的簇的相互作用能，我们评估了二体和三体短程势的重要性。结果表明，我们的 MB-nrg 模型相对于耦合簇参考具有高精度，优于当前的密度泛函理论模型，从而能够对水相环境中的 NO 进行高度准确的模拟。
