Projects per year
Abstract
The characteristics and performance of lithium-ion batteries typically rely on the precise combination of materials in their component electrodes. Understanding the impact of this formulation and the interdependencies between each component is critical in optimising cell performance. Such optimisation is difficult as the cost and effort for the myriad of possible combinations is too high. This problem is addressed by combining a design of experiments (DoE) and advanced statistical machine learning approach with comprehensive experimental characterisation of electrode slurries and coatings. An industry relevant graphite anode system is used, and with the aid of DoE, less than 30 experiments are defined to map impact of different weight fractions of active material (80–96 wt%), conductive additive (Carbon Black at 1–10 wt%) and a two-component binder system (Carboxymethyl Cellulose (CMC) at 1–3 wt% and Styrene Butadiene Rubber (SBR), at 1–7 wt%). Using Explainable Machine Learning (XML) methods, correlations between the formulation, slurry weight percentage (30–50 wt% in water) and coating speed (1–15 m/min) are quantified. Slurry viscosity, while known to depend on the CMC concentration, is also heavily influenced by carbon black and SBR when at high concentration, as is common in research. Viscosity increasing components also improve adhesion, by improving dispersion and hindering binder migration. Conductivity of the coating on current collector is sensitive to the current collector-coating interface, which makes it a highly useful probe. Improvements in cell capacity are observed with higher viscosity formulations (High weight percentage, CMC content), attributed to reduction in migration and slumping of the slurry on the current collector. SBR had a negative impact at any concentration due to its insulating nature, and carbon black reduces gravimetric capacity when included at high concentrations. The insights from this study facilitate the formulation optimisation of electrodes providing improved slurry design rules for future high performance electrode manufacturing.
Original language | English |
---|---|
Article number | e202300396 |
Number of pages | 19 |
Journal | Batteries & Supercaps |
DOIs | |
Publication status | Published - 7 Dec 2023 |
Keywords
- attery Electrode Manufacturing
- Data science
- Lithium-ion
- Formulation
- Slurry Properties
Fingerprint
Dive into the research topics of 'Impact of Formulation and Slurry Properties on Lithium‐ion Electrode Manufacturing'. Together they form a unique fingerprint.Projects
- 1 Finished
-
Next Generation Electrodes (via Oxford, Faraday)
Simmons, M., Kendrick, E. & Slater, P.
1/09/19 → 30/09/23
Project: Other Government Departments