Molecular dynamics (MD) has evolved into a ubiquitous, versatile and powerful computational method for fundamental research in science branches such as biology, chemistry, biomedicine and physics over the past 60 years. Powered by rapidly advanced supercomputing technologies in recent decades, MD has entered the engineering domain as a first-principle predictive method for material properties, physicochemical processes, and even as a design tool. Such developments have far-reaching consequences, and are covered for the first time in the present paper, with a focus on MD for combustion and energy systems encompassing topics like gas/liquid/solid fuel oxidation, pyrolysis, catalytic combustion, heterogeneous combustion, electrochemistry, nanoparticle synthesis, heat transfer, phase change, and fluid mechanics. First, the theoretical framework of the MD methodology is described systemically, covering both classical and reactive MD. The emphasis is on the development of the reactive force field (ReaxFF) MD, which enables chemical reactions to be simulated within the MD framework, utilizing quantum chemistry calculations and/or experimental data for the force field training. Second, details of the numerical methods, boundary conditions, post-processing and computational costs of MD simulations are provided. This is followed by a critical review of selected applications of classical and reactive MD methods in combustion and energy systems. It is demonstrated that the ReaxFF MD has been successfully deployed to gain fundamental insights into pyrolysis and/or oxidation of gas/liquid/solid fuels, revealing detailed energy changes and chemical pathways. Moreover, the complex physico-chemical dynamic processes in catalytic reactions, soot formation, and flame synthesis of nanoparticles are made plainly visible from an atomistic perspective. Flow, heat transfer and phase change phenomena are also scrutinized by MD simulations. Unprecedented details of nanoscale processes such as droplet collision, fuel droplet evaporation, and CO₂ capture and storage under subcritical and supercritical conditions are examined at the atomic level. Finally, the outlook for atomistic simulations of combustion and energy systems is discussed in the context of emerging computing platforms, machine learning and multiscale modelling.

在过去的 60 年里，分子动力学 (MD) 已经发展成为一种普遍存在、用途广泛且功能强大的计算方法，用于生物学、化学、生物医学和物理学等科学分支的基础研究。近几十年来，在快速发展的超级计算技术的推动下，MD 已进入工程领域，作为材料特性、物理化学过程的第一性原理预测方法，甚至作为设计工具。这些发展具有深远的影响，并且在本文中首次涵盖，重点是燃烧和能源系统的 MD，包括气体/液体/固体燃料氧化、热解、催化燃烧、异相燃烧、电化学等主题、纳米粒子合成、传热、相变和流体力学。第一的，系统地描述了 MD 方法的理论框架，涵盖经典和反应式 MD。重点是反应力场 (ReaxFF) MD 的发展，它可以在 MD 框架内模拟化学反应，利用量子化学计算和/或力场训练的实验数据。其次，提供了 MD 模拟的数值方法、边界条件、后处理和计算成本的详细信息。随后对经典和反应性 MD 方法在燃烧和能源系统中的选定应用进行了严格审查。事实证明，ReaxFF MD 已成功部署，以获得对气体/液体/固体燃料的热解和/或氧化的基本见解，揭示详细的能量变化和化学途径。而且，从原子的角度看，纳米粒子的催化反应、烟灰形成和火焰合成中复杂的物理化学动态过程变得清晰可见。流动、传热和相变现象也通过 MD 模拟进行了详细检查。前所未有的纳米级过程细节，例如液滴碰撞、燃料液滴蒸发和 CO₂在原子级别检查亚临界和超临界条件下的捕获和存储。最后，在新兴计算平台、机器学习和多尺度建模的背景下讨论了燃烧和能源系统原子模拟的前景。