Title

Towards High-Performance Li-Ion Batteries Via Optimized Three-Dimensional Micro-Lattice Electrode Architectures

Abstract

Optimized three-dimensional (3D) electrode architectures hold the promise of improving battery performance, a goal that cannot be obtained via conventional laminated structures. This paper reports on the mechanisms by which 3D electrodes enhance battery performance. The diffusion/migration of electrons/ions inside the battery was comprehensively analyzed via a 3D electrochemical model and subsequently validated by experiments on 3D micro-lattice electrodes made by Aerosol Jet printing. Lithium concentration and potential distribution were mapped to correlate battery performance with different shapes, thicknesses, packing density, and porosities. The study revealed that the main factors determining battery performance are ion diffusion in the electrolyte and electron transport in the 3D electrode skeleton. Further, the emergence of a competition between available volume for intercalation and an easier electronic/ionic path was shown, which determined their areal/specific capacities. In order to fully reap the benefits offered by 3D structures for both energy and power performance, the length scale of members forming electrode structures needs to be optimized at a scale of the order of the intercalation diffusion length, which is tens of micrometers. This study reveals highly useful guidelines for optimized 3D electrode designs and the possible manufacturing routes to realize them in order to achieve superior battery performance.

Department(s)

Mechanical and Aerospace Engineering

Research Center/Lab(s)

Center for High Performance Computing Research

Comments

National Science Foundation, Grant 1747608

Keywords and Phrases

3D electrodes; Aerosol jet printing; Charge transport; Macro/micro deformation; Microstructure; Stress analysis

International Standard Serial Number (ISSN)

0378-7753

Document Type

Article - Journal

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2020 Elsevier, All rights reserved.

Publication Date

15 Nov 2020

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