Influence of Layer Thickness on the Drying of Lithium‐Ion Battery Electrodes—Simulation and Experimental Validation

Kumberg, Jana; Baunach, Michael; Eser, Jochen C.; Altvater, Andreas; Scharfer, Philip; Schabel, Wilhelm

doi:10.1002/ente.202100013

Cited by 14 publications

(18 citation statements)

References 22 publications

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“…This phenomenon has been shown by Kumberg et al for Li‐ion battery anodes. [ 53 ] The verification of this phenomenon for this material system will be addressed in further studies. The film fully dries in the third section of the dryer.…”

Section: Determination Of Drying Ratesmentioning

confidence: 94%

Simulation of Structure Formation during Drying of Lithium‐Ion Battery Electrodes using Discrete Element Method

et al. 2022

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Lithium‐ion batteries are state‐of‐the‐art and still their performance is subject to constant improvement. These enhancements are based, among other things, on optimization in the electrode production process chain. High optimization potential exists for the drying process of electrodes, as aiming for high drying speeds can greatly reduce both, investment costs and operating costs of the drying. However, high drying rates without appropriate precautions go hand in hand with poorer cell performance and adhesive strength, leading to a conflict between the required performance and production costs of the electrodes. Herein, a numerical approach based on the discrete element method to describe the formation of the electrode structure during drying is presented. The focus is placed on the active material structure and the effects due to particle interactions. Herein, a direct numerical description of the fluid phase is avoided by using various fluid substitute models, so that the simulation time and the computational costs can be greatly reduced. The model is validated by simulating different electrode areal loadings and comparing the achieved layer thicknesses to experimental results of the electrode drying process. A high agreement between experiment and simulation regarding density is obtained for different areal loadings.

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Section: Determination Of Drying Ratesmentioning

confidence: 94%

Simulation of Structure Formation during Drying of Lithium‐Ion Battery Electrodes using Discrete Element Method

et al. 2022

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“…The adhesion force, measured by 90 peel tests, provides an indirect quantification of the binder migration and the mechanical properties of electrodes. [15,[35][36][37] The drying rate is varied for the same heat transfer coefficient by adjusting the isothermal drying temperature. For this purpose, the slurry is dried convectively via drying nozzles in a batch dryer with a heated plate.…”

Section: Adhesionmentioning

confidence: 99%

“…The drying rate decreases due to the additional mass transfer resistance within the electrode (falling rate period). [14,22,23,26,37] This work focuses on the effects of nanostructuring active particles for NCM cathodes on electrode production. It has to be clarified whether the penetration of the binder into the particles has an influence on the processing.…”

Section: Introductionmentioning

confidence: 99%

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Drying of NCM Cathode Electrodes with Porous, Nanostructured Particles Versus Compact Solid Particles: Comparative Study of Binder Migration as a Function of Drying Conditions

et al. 2022

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1/3 Mn 1/3 )O 2 (NCM111), morphologies such as preferentially oriented crystals in the particles, [2] nanobrick morphology, [3] one-dimensional hierarchical microrods, [4] and hierarchically structured particles [5][6][7][8][9] were investigated. The latter is achieved by forming secondary particles with open intraparticle pore structure from assembled primary particles. The advantages of such structures are higher rate capability and improved cycling stability, due to a larger interface between active material and electrolyte, smaller diffusion paths and lower mechanical stress during cycling. By modifying the particle morphology of commercial compact materials in a few additional process steps, a comparison can be made between the commercial starting material and the produced structured material. This approach was applied in the work of Wagner et al. [9] by grinding, spray drying and calcination commercial NCM111. The influences of the process parameters in the production of such structures on the electrochemical properties as a function of the particle morphology were investigated. The optimum sintering temperature was found to be between 850 and 900 C, resulting in primary particle diameters of 350 and 550 nm. It is the optimum between the demands of the ionic conductivity of the primary particles and the electrical conductivity of the secondary particles. During the sintering process, the primary particles grow, which aggravates ion diffusion but increases the electrical conductivity due to sinter necks. The specific capacity was improved from 20 to 100 mAh g À1 at 10C for the original and the structured particles, respectively. [9]

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“…Kumberg et al explained, modeled, and validated this complex interaction for graphite-based anodes with a water-soluble binder system. [52,53] This model is adapted to the material system of N-methyl-2-pyrrolidone (NMP)-based cathode by implementing respective material properties. The physical properties of the solvent NMP along with the thermal material properties of the solids assure the adequate representation of the cathode slurry in the drying model.…”

Section: Process-oriented Modelsmentioning

confidence: 99%

Digitalization Platform for Sustainable Battery Cell Production: Coupling of Process, Production, and Product Models

et al. 2022

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Lithium‐ion batteries are used in a wide range of applications, with the electromobility sector being the main contributor to the increasing demand predicted for the next decade. Although batteries play an important role in decarbonizing the transportation sector, their production includes energy‐intensive processes that hinder a more sustainable production. Moreover, the production processes are characterized by a manifold of parameters leading to complex cause–effect relations along the process chain which influences the battery cell quality. Therefore, a sustainable future for battery production and the electromobility sector depends on the environmentally and economically efficient production of high‐performance batteries. Against this background, this work presents a digitalization platform based on the coupling of mechanistic models to digitally reproduce the battery cell production and provide a deeper understanding of the interdependencies on the process, production, and product levels. In addition to a description of the individual models contained in the platform, this work demonstrates their coupling on a use case to study the effects of different solids contents of the coating suspension. Besides providing a multilevel assessment of the parameter interdependencies, considering quality, environmental and economic aspects, the presented framework contributes to knowledge‐based decision support and improvement of production and battery cell performance.

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Influence of Layer Thickness on the Drying of Lithium‐Ion Battery Electrodes—Simulation and Experimental Validation

Cited by 14 publications

References 22 publications

Simulation of Structure Formation during Drying of Lithium‐Ion Battery Electrodes using Discrete Element Method

Simulation of Structure Formation during Drying of Lithium‐Ion Battery Electrodes using Discrete Element Method

Drying of NCM Cathode Electrodes with Porous, Nanostructured Particles Versus Compact Solid Particles: Comparative Study of Binder Migration as a Function of Drying Conditions

Digitalization Platform for Sustainable Battery Cell Production: Coupling of Process, Production, and Product Models

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