Electrochemical impedance spectroscopy (EIS) is ubiquitously applied to identify physicochemical processes governing the performance of energy-conversion devices. However, deconvolution and interpretation of impedance phenomena are limited by measurement throughput and a dearth of scalable analysis methods. Here, we demonstrate an approach to quickly collect and coherently analyze large volumes of electrochemical data. We accelerate impedance characterization by combining rapid measurements in time and frequency domains, which are interpretably transformed using the distribution of relaxation times (DRT) and a new distribution of phasances (DOP) model. This method provides excellent agreement with EIS and decreases measurement time by an order of magnitude. High-throughput spectra are then distilled into detailed electrochemical maps. This approach is applied to a Li-ion battery and a protonic ceramic electrochemical cell as practical case studies, demonstrating how mapping can richly characterize physicochemical relationships that are difficult to decipher with conventional measurement and analysis methods.

电化学阻抗谱 (EIS) 广泛应用于识别控制能量转换设备性能的物理化学过程。然而，阻抗现象的反卷积和解释受到测量吞吐量和缺乏可扩展分析方法的限制。在这里，我们演示了一种快速收集和连贯分析大量电化学数据的方法。我们通过结合时域和频域的快速测量来加速阻抗表征，这些测量使用弛豫时间分布 (DRT) 和新的相分布 (DOP) 模型进行可解释的转换。该方法与 EIS 具有极好的一致性，并将测量时间缩短了一个数量级。然后将高通量光谱提炼成详细的电化学图。该方法作为实际案例研究应用于锂离子电池和质子陶瓷电化学电池，展示了绘图如何能够丰富地表征传统测量和分析方法难以破译的物理化学关系。