论文标题
离子电子传递动力学的耦合理论
Theory of coupled ion-electron transfer kinetics
论文作者
论文摘要
化学反应的显微镜理论基于过渡状态理论,该理论在电子维持其基态时,原子或离子在能量屏障上经常转移。电子转移从根本上是不同的,并且通过响应溶剂波动而发生隧穿。在这里,我们发展了耦合离子电子转移的理论,其中离子和溶剂分子合作地波动以促进电子转移。我们得出了反应速率的一般公式,该公式取决于过电势,溶剂特性,电子供体/受体的电子结构以及离子在过渡态下的过量化学潜力。对于法拉达反应,该理论预测具有浓度依赖性反应限值电流的弯曲的Tafel图。对于中等电势,我们的公式将其简化为管制volmer方程,并解释了其相关性,不仅在众所周知的大电子转移(溶剂重组)能量的限制下,而且在大离子转移能量的相反极限上也相反。速率公式应用于锂离子电池,其中用离子插入的电极宿主材料夫妇还原。在铁磷酸锂的情况下,该理论准确地预测了由{\ it在Operando} X射线显微镜中测量的交换电流的浓度依赖性,而无需任何可调节的参数。这些结果为界面工程增强离子插入率的道路铺平了道路,不仅是电池,而且对于离子分离和神经形态计算。
The microscopic theory of chemical reactions is based on transition state theory, where atoms or ions transfer classically over an energy barrier, as electrons maintain their ground state. Electron transfer is fundamentally different and occurs by tunneling in response to solvent fluctuations. Here, we develop the theory of coupled ion-electron transfer, in which ions and solvent molecules fluctuate cooperatively to facilitate electron transfer. We derive a general formula of the reaction rate that depends on the overpotential, solvent properties, the electronic structure of the electron donor/acceptor, and the excess chemical potential of ions in the transition state. For Faradaic reactions, the theory predicts curved Tafel plots with a concentration-dependent reaction-limited current. For moderate overpotentials, our formula reduces to the Butler-Volmer equation and explains its relevance, not only in the well-known limit of large electron-transfer (solvent reorganization) energy, but also in the opposite limit of large ion-transfer energy. The rate formula is applied to Li-ion batteries, where reduction of the electrode host material couples with ion insertion. In the case of lithium iron phosphate, the theory accurately predicts the concentration dependence of the exchange current measured by {\it in operando} X-Ray microscopy without any adjustable parameters. These results pave the way for interfacial engineering to enhance ion intercalation rates, not only for batteries, but also for ionic separations and neuromorphic computing.