Functional Optical Fiber Sensors Detecting Imperceptible Physical/Chemical Changes for Smart Batteries

The battery technology progress has been a contradictory process in which performance improvement and hidden risks coexist.Now the battery is still a“black box”,thus requiring a deep understanding of its internal state.The battery should“sense its internal physical/chemical conditions”,which puts strict requirements on embedded sensing parts.This paper summarizes the application of advanced optical fiber sensors in lithium-ion batteries and energy storage technologies that may be mass deployed,focuses on the insights of advanced optical fiber sensors into the processes of one-dimensional nano-micro-level battery material structural phase transition,electrolyte degradation,electrode-electrolyte interface dynamics to three-dimensional macro-safety evolution.The paper contributes to understanding how to use optical fiber sensors to achieve“real”and“embedded”monitoring.Through the inherent advantages of the advanced optical fiber sensor,it helps clarify the battery internal state and reaction mechanism,aiding in the establishment of more detailed models.These advancements can promote the development of smart batteries,with significant importance lying in essentially promoting the improvement of system consistency.Furthermore,with the help of smart batteries in the future,the importance of consistency can be weakened or even eliminated.The application of advanced optical fiber sensors helps comprehensively improve the battery quality,reliability,and life.

Mass‑Spring‑Damping Theory Based Equivalent Mechanical Model for Cylindrical Lithium‑ion Batteries under Mechanical Abuse

An equivalent mechanical model with the equivalent physical meaning of mass-spring-damping is proposed for cylindrical lithium-ion batteries through experiments and theory.The equivalent mechanical model of a cylindrical lithium-ion battery consists of a spring-damping parallel unit.Therefore,a spring-damping parallel unit connecting a damping unit in series is selected to construct the constitutive characteristics of the battery under mechanical abuse.Comparison results show that the equivalent mechanical model can more effectively describe the mechanical properties of the batteries than most cubic fitting models,of which the average relative error of the equivalent mechanical model under different states-of-charge is less than 6.75%.Combined with the proposed equivalent mechanical model,the failure process of the batteries was simulated and analyzed using LS-Dyna and HyperWorks.Under rigid rod tests,failure occurred at the core and bottom of the batteries;under hemispherical punch tests,failure occurred at the core and top,consistent with the experimental results.The average prediction error for the failure displacement under different abuse conditions is less than 4%in the simulations.The equivalent mechanical model requires only a few parameters and can be recognized easily.In the future,the model can be used in safety warning devices based on mechanical penetration.

The Correlations between the Lightning Density Distribution of Sichuan Province and the Seismic Area

We here report our observations of the intense lightning events during ~15:00, 23 September to ~12:00, 24 September 2008 along the fault of Wenchuan-Beichuan counties in Sichuan Province, China where a 8.0 magnitude earthquake strike on May 12th, 2008. This intense lightning period had the highest density in all available the lightning monitoring data of Sichuan. The altered lightning pattern is unlikely to be a coincidence. We also found that the spatial-temporal characteristic of lightning in Sichuan has changed after the earthquake. We studied the correlations and analyze the data between lightning and earthquake in order to understand the seemingly unrelated events.

Selective Targeting of Perirhinal Cortex Projection to Hippocampal CA1 Interneurons

Dear Editor,The perirhinal cortex (PER) is conceptually important in the recognition memory, especially in familiarity discrimination, whereas the hippocampus is important for association and recollection [1]. This notion is known as the dualprocess model of recognition memory.