This article is part of the Computational Electrochemistry special issue. Advancing our understanding of electrochemical phenomena, and ultimately improving the operation and design of electrochemical systems, is aided by the use of advanced computational tools and theories that enable researchers to deconvolute complex, interacting phenomena at multiple length and time scales. Electrochemical phenomena range from atomistic and picosecond interactions and reactions within double layers up to meters and years for cells and lifetime predictions. Bridging these scales and complex nonlinear interactions is a daunting task, but advancements in understanding and computation have made it more attainable than ever. It is the hope that melding of computational power, data informatics, and experimental studies can become intertwined in the future, where virtual representations of real systems can greatly advance the scientific discovery process. In this thematic issue, experts from around the world discuss the current state of the art approaches and understanding in computational electrochemistry. At the smallest length scales of individual reaction events and electron transfer, an understanding of the importance of electronic structure and, in particular, the electrochemical potential is critical. The review of Santos and Schmickler examines such electron transfer events at different electrode materials, elucidating the principles governing charge transfer. The review of Hammes-Schiffer and colleagues provides a similar level of insight on the critical issues of proton-coupled electron transfer, a process that is common in many molecular systems and an expanding area for electrochemical research in general. In a detailed review of atomistic simulations of the interface, Schwarz and colleagues explore ways to improve realism and accuracy and move toward more predictive simulations. While new materials are continuously synthesized, computational approaches are now being leveraged to understand and guide such design, in both traditional and nontraditional electrochemical reactions. Examining specific electrochemically active materials, the review of Liu and colleagues explores atomistic understanding for the newly utilized two-dimensional electrocatalysts. This review is complemented by the multiscale analysis and techniques for solid-state polymer electrolytes provided by Paddison and colleagues. Here, it is shown again how the material and polymer interactions are important in such solid-state proton conductors, where true understanding and modeling of these complex systems is still relatively in its infancy. There is a growing awareness of the important roles that electrolyte species and solvent play in electrochemical reactions. The reviews by Groß and Sakong and Ringe and colleagues both tackle the importance of solvent and water, but from different perspectives. Similarly, interest in the importance of the electrochemical interface, which drives almost all electrochemical reactions, is seeing a resurgence, especially in the formation of the double layer, which ions must traverse to react, under different conditions. The review by Wu examines double layer structures and behavior from a fundamental perspective and provides insight into the many coupled material interactions and processes. In a related review, Salanne and colleagues explore double layers in the context of capacitors, another heralded electrochemical energy storage device. This review explores the governing design criteria and equations and methodologies for describing their behavior. Advances in theory have also enabled better approaches toward analyzing vast data sets, but physics-based understanding is critical. In the review by Franco and colleagues, they tackle the challenge of bridging scales and the question of whether artificial intelligence and machine learning are good approaches for the nuances of electrochemical devices and, specifically, batteries. In another multiscale analysis, Zhang and colleagues examine how different techniques can be used and their inherent trade-offs for electrolytes in rechargeable batteries. Computational approaches at the continuum scale provide methods to examine multiple interactions and phenomena, and they predict and guide overall material and integration methodologies. While such models have been utilized for decades, especially in the battery and fuel-cell realms, only now are we being able to expand their reach into coupled length and time scales as well as more complex and nuanced interactions at interfaces and reactions. To this end, Weber and colleagues examine how modeling can be conducted for electrochemical synthesis flow cells in general. This review is complemented by the multiscale modeling review of López and colleagues, who look at electrochemical CO₂ reduction and provide a more focused view of the reaction pathways. Finally, critical for exploring electrochemical systems is the interrogation using such techniques as electrochemical impedance spectroscopy. The review by Orazem and colleagues explores how computational electrochemistry is critical for interpreting such complex signals and for a variety of different cases and conditions. In conclusion, computational electrochemistry is more accessible than ever, but one needs to ensure that the correct approaches are being used to solve specific problems and questions. This thematic issue is timely in that newfound approaches toward machine learning, big and small data problems, and the importance of provenance and metadata are in a period of discovery and renaissance. It is our hope that the issue acts as a guide and reference for both those new to and those familiar with the field. Finally, we would like to give our heartfelt thanks to our colleagues that enthusiastically agreed to contribute excellent reviews to this thematic issue, even during the COVID pandemic. From our perspective, the future looks more promising than ever for computational approaches in elucidating electrochemical phenomena. This article has not yet been cited by other publications.

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简介：计算电化学

本文是部分计算电化学特刊。先进的计算工具和理论的使用有助于促进我们对电化学现象的理解，并最终改进电化学系统的操作和设计，这些工具和理论使研究人员能够在多个长度和时间尺度上解卷积复杂的、相互作用的现象。电化学现象的范围从双层内的原子和皮秒相互作用和反应，到电池和寿命预测的米和年。弥合这些尺度和复杂的非线性相互作用是一项艰巨的任务，但理解和计算方面的进步使其比以往任何时候都更容易实现。希望计算能力、数据信息学和实验研究的融合在未来能够交织在一起，真实系统的虚拟表示可以极大地推进科学发现过程。在本期专题中，来自世界各地的专家讨论了当前最先进的计算电化学方法和理解。在单个反应事件和电子转移的最小长度尺度上，了解电子结构的重要性，特别是电化学势是至关重要的。Santos 和 Schmickler 的评论检查了不同电极材料上的此类电子转移事件，阐明了控制电荷转移的原理。Hammes-Schiffer 及其同事的评论对质子耦合电子转移的关键问题提供了类似的见解，这一过程在许多分子系统中很常见，并且通常是电化学研究的扩展领域。在对界面原子模拟的详细回顾中，Schwarz 及其同事探索了提高真实性和准确性并转向更具预测性的模拟的方法。在不断合成新材料的同时，现在正在利用计算方法来理解和指导这种设计，无论是在传统的还是非传统的电化学反应中。通过检查特定的电化学活性材料，Liu 及其同事探索了对新使用的二维电催化剂的原子理解。Paddison 及其同事提供的固态聚合物电解质的多尺度分析和技术对本综述进行了补充。这里，再次展示了材料和聚合物相互作用在这种固态质子导体中的重要性，对这些复杂系统的真正理解和建模仍处于起步阶段。人们越来越意识到电解质种类和溶剂在电化学反应中的重要作用。Groß 和 Sakong 以及 Ringe 及其同事的评论都解决了溶剂和水的重要性，但从不同的角度。同样，对驱动几乎所有电化学反应的电化学界面的重要性的兴趣正在重新抬头，特别是在形成双层时，离子必须在不同条件下穿过该双层才能发生反应。Wu 的评论从基本角度检查了双层结构和行为，并提供了对许多耦合材料相互作用和过程的洞察。在一篇相关评论中，Salanne 及其同事在电容器的背景下探索了双层，这是另一种预示着电化学储能装置。本综述探讨了描述其行为的主导设计标准和方程式和方法。理论的进步也为分析大量数据集提供了更好的方法，但基于物理的理解至关重要。在 Franco 及其同事的评论中，他们解决了桥接尺度的挑战以及人工智能和机器学习是否是解决电化学设备，特别是电池细微差别的好方法的问题。在另一个多尺度分析中，Zhang 及其同事研究了如何使用不同的技术以及它们对可充电电池中电解质的内在权衡。连续尺度的计算方法提供了检查多种相互作用和现象的方法，它们预测和指导整体材料和集成方法。虽然这些模型已经使用了几十年，特别是在电池和燃料电池领域，但直到现在我们才能够将它们的范围扩展到耦合的长度和时间尺度，以及界面和反应中更复杂和细微的相互作用。为此，Weber 及其同事研究了如何对一般的电化学合成流通池进行建模。López 及其同事对电化学 CO 连续尺度的计算方法提供了检查多种相互作用和现象的方法，它们预测和指导整体材料和集成方法。虽然这些模型已经使用了几十年，特别是在电池和燃料电池领域，但直到现在我们才能够将它们的范围扩展到耦合的长度和时间尺度，以及界面和反应中更复杂和细微的相互作用。为此，Weber 及其同事研究了如何对一般的电化学合成流通池进行建模。López 及其同事对电化学 CO 连续尺度的计算方法提供了检查多种相互作用和现象的方法，它们预测和指导整体材料和集成方法。虽然这些模型已经使用了几十年，特别是在电池和燃料电池领域，但直到现在我们才能够将它们的范围扩展到耦合的长度和时间尺度，以及界面和反应中更复杂和细微的相互作用。为此，Weber 及其同事研究了如何对一般的电化学合成流通池进行建模。López 及其同事对电化学 CO 虽然这些模型已经使用了几十年，特别是在电池和燃料电池领域，但直到现在我们才能够将它们的范围扩展到耦合的长度和时间尺度，以及界面和反应中更复杂和细微的相互作用。为此，Weber 及其同事研究了如何对一般的电化学合成流通池进行建模。López 及其同事对电化学 CO 尽管此类模型已经使用了数十年，尤其是在电池和燃料电池领域，但直到现在我们才能够将它们的范围扩展到耦合的长度和时间尺度以及界面和反应中更复杂和细微的相互作用。为此，Weber 及其同事研究了如何对一般的电化学合成流通池进行建模。López 及其同事对电化学 CO Weber 及其同事研究了如何对一般的电化学合成流通池进行建模。López 及其同事对电化学 CO Weber 及其同事研究了如何对一般的电化学合成流通池进行建模。López 及其同事对电化学 CO₂还原并提供更集中的反应途径视图。最后，探索电化学系统的关键是使用电化学阻抗谱等技术进行询问。Orazem 及其同事的综述探讨了计算电化学对于解释此类复杂信号以及各种不同情况和条件的重要性。总之，计算电化学比以往任何时候都更容易获得，但需要确保使用正确的方法来解决特定问题。这个主题是及时的，因为机器学习、大小数据问题的新方法以及出处和元数据的重要性正处于发现和复兴时期。我们希望这个问题能为那些刚接触和熟悉该领域的人提供指导和参考。最后，我们要衷心感谢我们的同事，即使在 COVID 大流行期间，他们也热情地同意为本专题提供出色的评论。从我们的角度来看，在阐明电化学现象的计算方法方面，未来看起来比以往任何时候都更有希望。这篇文章尚未被其他出版物引用。