Magnetic micro‐fluidics in 3D microchannel at the micro‐scale: Unlocking nano‐porous electrode potential for lithium‐ion micro‐batteries

Author:

Ashraf Adeel12,Manzoor Tareq3,Iqbal Shaukat2,Anwar Tauseef4,Farooq‐i‐Azam Muhammad5,Khan Zeashan6,Manzoor Habib Ullah78ORCID

Affiliation:

1. Nanjing University of Science and Technology (NJUST) Nanjing China

2. Department of Computer Science, School of Systems and Technology University of Management and Technology Lahore Pakistan

3. Energy Research Center COMSATS University Lahore Pakistan

4. Department of Physics University of Education Lahore Pakistan

5. Department of Electrical and Computer Engineering COMSATS University Islamabad Lahore Pakistan

6. Interdisciplinary Research Center for Intelligent Manufacturing & Robotics (IRC‐IMR) King Fahd University of Petroleum & Minerals (KFUPM) Dhahran Saudi Arabia

7. James Watt School of Engineering University of Glasgow Glasgow UK

8. Faculty of Electrical Engineering UET Lahore Faisalabad Pakistan

Abstract

AbstractEnhancing the nanosized‐electrolyte's characteristics in Lithium‐driven micro‐batteries (LIMBs) is indispensable to improve the overall efficiency, security, and lifespan of these energy devices, designing nano‐sized electrolyte with a wide electrochemical stability window while keeping them compatible with electrode materials is one of the improvement goals. Battery technologies must go through this optimization process in order to be used practically. A sensing mechanism to keep an eye on the health of Li‐ion energy devices through the magnetization. Magnetic micro‐fluidic patterns that change could be a sign of battery deterioration or other problems with performance. Li‐ion battery health is one application of magnetic sensing that you can do with magnetic sensing. Battery health variations and other performance problems can be found using magnetic mass transport patterns. Present study examines the effects of magnetic field on Eyring–Powel mass transport in nano‐porous channels over a stretching sheet. The principal equations exhibiting the phenomenon are transformed into non‐linear differential equation by second‐order approximation by using a similarity transformation. Furthermore, a semi‐analytic technique named optimal homotopy asymptotic method (OHAM) is used to solve the transformed Eyring–Powell model. The numerical results demonstrated the impact of variations in velocity, skin‐friction coefficient and Sherwood number for the proposed scheme.

Publisher

Wiley

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