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Related Experiment Video

Updated: Jan 15, 2026

The Effect of Charging and Discharging Lithium Iron Phosphate-graphite Cells at Different Temperatures on Degradation
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Failure-Mechanism-Driven Inverse Design and Optimization Procedure for Battery Lifetime Extension.

Ruyu Xi1,2, Yiyang Peng1,2, Jinhan Li1,2

  • 1Key Laboratory of Advanced Energy Materials Chemistry (Ministry of Education), Engineering Research Center of High-efficiency Energy Storage (Ministry of Education), College of Chemistry, Nankai University, Tianjin, 300071, China.

Angewandte Chemie (International Ed. in English)
|October 7, 2025
PubMed
Summary
This summary is machine-generated.

Optimizing lithium-ion battery (LIB) design is complex. This study introduces an inverse design and optimization procedure (IDOP) to significantly extend battery lifetime by analyzing key degradation factors.

Keywords:
Capacity degradation trajectoryInverse optimizationLifetime predictionLithium‐ion batteriesParameter sensitivity analysis

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Area of Science:

  • Materials Science
  • Electrochemistry
  • Battery Technology

Background:

  • Lithium-ion battery (LIB) design and optimization face challenges due to complex degradation mechanisms and competing interactions.
  • Existing models often struggle to capture the dynamic nature of battery performance over time.

Purpose of the Study:

  • To develop an Inverse Design and Optimization Procedure (IDOP) for enhancing LIB lifetime prediction and design.
  • To integrate Parameter Sensitivity Analysis (PSA) and Multiobjective Optimization (MOO) into a unified framework.

Main Methods:

  • Developed a mechanism-driven LIB lifetime prediction model based on capacity degradation.
  • Employed PSA to identify critical design parameters influencing battery lifespan.
  • Utilized MOO to optimize direct (anode, electrolyte) and indirect (interfacial) characteristics.

Main Results:

  • Parameter Sensitivity Analysis identified areal density, particle radius, and interface characteristics as key factors for battery lifetime.
  • Multiobjective Optimization predicted potential battery lifetime extensions of up to 26.63% (at 25 °C) and 32.76% (at 45 °C) by optimizing direct factors.
  • Further optimization of indirect factors showed even greater lifetime extensions: 70.97% (at 25 °C) and 138.41% (at 45 °C).
  • Optimized parameters demonstrated excellent agreement with capacity degradation trajectories in the failure-mechanism-driven model.

Conclusions:

  • The IDOP framework effectively improves the efficiency of LIB design and optimization.
  • This approach offers a promising pathway for developing next-generation LIBs with extended operational lifespans.
  • Understanding and optimizing interfacial characteristics are crucial for maximizing battery performance and longevity.