LTERA: A Physics-Guided Multi-Architecture Framework for Long-Term Energy Retention Analysis in Advanced Battery Systems

Abstract

Elham Khalesi

Long-term energy retention in advanced battery systems is governed by coupled degradation processes that are strongly influenced by material selection, multilayer architecture, and structural design. Conventional material-screening approaches do not necessarily capture the system-level interactions among these variables. Here, we present LTERA (Long-Term Energy Retention Analysis), a physics-guided computational framework for architecture-level analysis and optimization of multilayer protective structures for long-term energy-retention applications. The framework integrates constituent material and layer parameters into an effective degradation-loss formulation and evaluates candidate architectures using long-term retention, effective loss rate, structural mass, specific energy, and a mechanism-level performance score. In the final LTERA V9.0 analysis, five candidate $ ext{Al}_2 ext{O}_3$ / COF-polymer / $ ext{LiF}$ architectures were systematically evaluated. The covalent organic framework (COF)-polymer layer was maintained at a nominal thickness of 5000extnm, while the atomic layer deposition (ALD)-derived $ ext{Al}_2 ext{O}_3$ barrier and artificial $ ext{LiF}$ interphase thicknesses were varied among candidate configurations. Architecture D, consisting of 30extnmextAl2 extO3 , 5000extnmextCOF-polymer, and 20extnmextLiF, produced the highest predicted long-term retention within the evaluated design space, reaching 98.7583%. The corresponding effective loss rate was 3.4233imes 10-5 extday-1, with a modeled LTERA structural mass of 5.6713imes10-5 extkg, a specific energy of 117.1678extWhextkg-1, and an overall mechanism score of 0.5945. The comparative results demonstrate that monotonically increasing the thickness of individual protective layers does not yield linear improvements in retention due to transport and mass penalties. Instead, the findings support a thickness-balanced architecture in which functional and protective layers are jointly optimized. LTERA offers a quantitative methodology for reducing the architectural search space and translating physics-guided modeling into experimentally testable multilayer designs.

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