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RSS FeedsEnergies, Vol. 16, Pages 1424: Modulus Estimation of Composites with High Porosity, High Particle Volume Fraction, and Particle Eigenstrain: Application to the LIB Active Layer with a Bridged-Particle Mesostructure (Energies)

 
 

1 february 2023 07:20:01

 
Energies, Vol. 16, Pages 1424: Modulus Estimation of Composites with High Porosity, High Particle Volume Fraction, and Particle Eigenstrain: Application to the LIB Active Layer with a Bridged-Particle Mesostructure (Energies)
 


Due to the complex mesostructure and components of composite active layers in lithium-ion battery (LIB) electrodes, coupled with the concentration-dependent material properties and eigenstrains, efficiently estimating the effective modulus of the active layers remains a great challenge. In this work, the classic Mori–Tanaka method is found to be unable to estimate the modulus of the active layer. By realizing the importance of the mesostructure feature, a rod-rod model is proposed. The resulting modulus is expressed analytically. It is shown that the rod-rod model can accurately estimate the modulus evolution of the active layer if the material properties of the components and the evolution of volume fractions are known in advance. Moreover, a simplified rod-rod model is also developed to reduce the complexity of the proposed method. By knowing the volume fractions at two arbitrary states of charge and subsequently determining two constants, the simplified model can estimate the modulus efficiently. Considering both its accuracy and its simplicity, the simplified rod-rod model is the most suitable for the estimation. Thus, the methods developed in this work provide a new perspective for analyzing the material properties of composite active layers in LIB electrodes.


 
84 viewsCategory: Biophysics, Biotechnology, Physics
 
Energies, Vol. 16, Pages 1425: Evaluation of Numerical Methods for Predicting the Energy Performance of Windows (Energies)
Energies, Vol. 16, Pages 1429: Recent Trends, Opportunities and Challenges in Sustainable Management of Rice Straw Waste Biomass for Green Biorefinery (Energies)
 
 
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