Lithium‐ion battery cells with high‐energy density and good fast charging properties are subject of current research. One approach to achieve high‐energy densities is the use of higher mass loadings. The challenges of these so called “thick” electrodes are transport limitations: lithium ions cannot reach all layers of the electrode, which results in a drop of performance. Possible concepts to overcome these limitations are the use of different active materials (silicon oxide, graphite, and hard carbon (HC)), and a two‐layer coating of the anode to create a defined pore network, which reduces the ionic resistance and ensure better fast charging capability even at higher mass loadings (8 mAh cm⁻²). It could be demonstrated that by using a two‐layered anode with HC in the upper layer, the electrical conductivity could be increased by a factor of 10 compared to the reference anode. Furthermore, the interporous HC leads to a capacity retention increase up to 20% with no loss of capacity at moderate C‐rates and a low electrode density. This can be explained by the low tortuosity that results in additional conductive paths for the ions through the coating, reduces the ionic resistance, and ultimately enables faster lithiation of the anode.

Current research focuses on lithium-ion battery cells with a high energy density and efficient fast-charging capabilities. However, transport limitations, and, therefore, the uniform diffusion of lithium-ions across the electrode layers, remain a challenge and could lead to reduced cell performance. One approach to overcome these transport challenges is the use of subsequently produced two-layer anodes with the particle size variation of spherical graphite (x₅₀ = 18 µm; x₅₀ = 11 µm). Thereby, a defined pore network is created, which reduces the ionic resistance and ensuring improved fast charging capabilities. The analysis focuses on the evaluation of electrode properties and the electrochemical performance. By examining the pore size distribution of the anodes, it has been found that during the manufacturing of the two-layer anodes, carbon black and binder particles are transported into the existing microstructure of the lower layer, resulting in localized densification between the anode layers. This could also be supported by color measurements. This effect also extends to electrochemical investigations, with electrochemical impedance spectroscopy showing significantly lower ionic resistances in all two-layer anodes. Reduced ionic resistance and tortuosity near the separator due to absorption effects enhance the ion diffusion and have a direct impact on anode performance. Cell ageing analysis showed a significant capacity decrease of almost 15 mAh g ⁻¹ in the single-layer references only, in contrast to the stability of the two-layer anodes. This could also be attributed to the reduced ionic resistance and active counteraction of binder migration. In conclusion, this study highlights how subsequently produced two-layer anodes significantly shape the electrode properties and cell performance of lithium-ion batteries.

Research on battery materials and systems is broader than ever and a large amount of data is being generated. The data collected is often challenging to correlate or compare because they are not compiled in a structured way since no generally uniform data structure exists yet in the battery field. Besides, manufacturing steps and analysis parameters vary enormously from laboratory scale to industrial scale, from research institutions to consortia. Within the "DigiBatMat project" we have created a digital platform for battery material data and processing data that combines collected material data and knowledge within a defined structure based on taxonomies and ontologies. The structure of the digital platform was developed to cover the Battery LabFactory Braunschweig (BLB) pilot-scale production line for lithium-ion cells while being compatible with other battery production processes, for example at the laboratory bench scale. The platform’s underlying data structure is divided into an “electrode production” and “cell production” taxonomy, providing input modules for the most typical battery material and cell characterization methods. This approach offers a commercially available platform with a defined structure, which still allows flexibility for individual electrode and cell productions through option based input. Due to this structure, we aim to go beyond simple data storage by implementing functionalities that allow users to work with and analyze the data within the digital platform. Beside the functionalities we have implemented so far, which are shown here, we also aim to develop further functionalities that enable the identification of new correlations that are otherwise difficult or even impossible to obtain. A consistent data set is necessary to build up and validate such a digital platform. Hence, we specifically generated “reference” data and tested their management and analysis with the platform. We focus on three key use cases of collecting process data and characterizing electrodes and cells properties along the production process. In one of these key use cases we compare state-of-the-art cathodes with Ni-rich active materials, namely NMC811 and NCA. Data are collected from cells with such cathodes with varying loadings and electrode densities. Characterization of the electrodes includes, among other things, microscope data analysis of the microstructure and electrochemical characterization such as electrochemical impedance spectroscopy and rate capability. By showing how raw data can be imported into the database, processed and analyzed, we aim to demonstrate the possibilities and advantages of our digital platform.