气候变化领域集成服务门户(CCPortal): Data driven analytics of porous battery microstructures

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DOI	10.1039/d1ee00454a
	Data driven analytics of porous battery microstructures
	Deva A.; Krs V.; Robinson L.D.; Adorf C.S.; Benes B.; Glotzer S.C.; García R.E.
发表日期	2021
ISSN	17545692
起始页码	2485
结束页码	2493
卷号	14 期号:4
英文摘要	The microstructural optimization of porous lithium ion battery electrodes has traditionally been driven by experimental trial and error efforts, based on anecdotal understanding and intuition, leading to the development of useful but qualitative rules of thumb to guide the design of porous energy storage technology. In this paper, an advanced data-driven framework is presented wherein the effect of experimentally accessible microstructural parameters such as active particle morphology and spacial arrangement, underlying porosity, cell thickness, etc., on the corresponding macroscopic power and energy density is systematically assessed. For the LixC6 \| LMO chemistry, an analysis performed on 53 356 battery architectures reported in the literature revealed that for commercial microstructures based on oblate-shaped particles, lightly textured samples deliver higher power and energy density responses as compared to highly textured samples, which suffer from large polarization losses. In contrast, high aspect ratio prolate-shaped particles deliver the highest energy and power density, particularly in the limit of wire-like morphologies. Polyhedra-based colloidal microstructures demonstrate high area densities, and low tortuosities, but provide no appreciable power and energy density benefit over currently manufactured particle morphologies. The developed framework enables to establish general microstructure design guidelines and propose optimal electrode microstructures based on the intended application, given an anode and cathode chemistry. This journal is © The Royal Society of Chemistry.
英文关键词	Aspect ratio; Chemical analysis; Digital storage; Electrodes; Energy storage; Lithium compounds; Morphology; Textures; Colloidal microstructure; Energy storage technologies; Experimental trials; Microstructural optimization; Microstructural parameters; Microstructure design; Optimal electrodes; Particle morphologies; Lithium-ion batteries; analytical method; data processing; energy storage; porous medium
语种	英语
来源期刊	Energy & Environmental Science
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/190702
作者单位	School of Materials Engineering, Purdue University, West Lafayette, IN 47907, United States; Department of Computer Graphics Technology, Purdue University, West Lafayette, IN 47907, United States; Chemical Engineering, University of Michigan, Ann Arbor, MI 48109, United States
推荐引用方式 GB/T 7714	Deva A.,Krs V.,Robinson L.D.,et al. Data driven analytics of porous battery microstructures[J],2021,14(4).
APA	Deva A..,Krs V..,Robinson L.D..,Adorf C.S..,Benes B..,...&García R.E..(2021).Data driven analytics of porous battery microstructures.Energy & Environmental Science,14(4).
MLA	Deva A.,et al."Data driven analytics of porous battery microstructures".Energy & Environmental Science 14.4(2021).