Identification and characterization of the dominant thermal resistance in lithium-ion batteries using operando 3-omega sensors

Poor thermal transport within lithium-ion batteries fundamentally limits their performance, safety, and lifetime, in spite of external thermal management systems. All prior efforts to understand the origin of batteries' mysteriously high thermal resistance have been confined to ex situ measurements without understanding the impact of battery operation. Here, we develop a frequency-domain technique that employs sensors capable of measuring spatially resolved intrinsic thermal transport properties within a live battery while it is undergoing cycling. Our results reveal that the poor battery thermal transport is due to high thermal contact resistance between the separator and both electrode layers and worsens as a result of formation cycling, degrading total battery thermal transport by up to 70%. We develop a thermal model of these contact resistances to explain their origin. These contacts account for up to 65% of the total thermal resistance inside the battery, leading to far-reaching consequences for the thermal design of batteries. Our technique unlocks new thermal measurement capabilities for future battery research

Temperature dependence of secondary electron emission: A new route to nanoscale temperature measurement using scanning electron microscopy

Scanning electron microscopy (SEM) is ubiquitous for imaging but is not generally regarded as a tool for thermal measurements. Here, the temperature dependence of secondary electron (SE) emission from a sample's surface is investigated. Spatially uniform SEM images and the net charge flowing through a sample were recorded at different temperatures to quantify the temperature dependence of SE emission and electron absorption. The measurements also demonstrated charge conservation during thermal cycling by placing the sample inside a Faraday cup to capture the emitted SEs and back-scattered electrons from the sample. The temperature dependence of SE emission was measured for four semiconducting materials (Si, GaP, InP, and GaAs) with response coefficients found to be of magnitudes ∼100-1000 ppm/K. The detection limits for temperature changes were no more than ±8 °C for 60 s acquisition time

Temperature dependence of secondary electron emission: A new route to nanoscale temperature measurement using scanning electron microscopy

Scanning electron microscopy (SEM) is ubiquitous for imaging but is not generally regarded as a tool for thermal measurements. Here, the temperature dependence of secondary electron (SE) emission from a sample's surface is investigated. Spatially uniform SEM images and the net charge flowing through a sample were recorded at different temperatures to quantify the temperature dependence of SE emission and electron absorption. The measurements also demonstrated charge conservation during thermal cycling by placing the sample inside a Faraday cup to capture the emitted SEs and back-scattered electrons from the sample. The temperature dependence of SE emission was measured for four semiconducting materials (Si, GaP, InP, and GaAs) with response coefficients found to be of magnitudes ∼100-1000 ppm/K. The detection limits for temperature changes were no more than ±8 °C for 60 s acquisition time

Identification and characterization of the dominant thermal resistance in lithium-ion batteries using operando 3-omega sensors

Poor thermal transport within lithium-ion batteries fundamentally limits their performance, safety, and lifetime, in spite of external thermal management systems. All prior efforts to understand the origin of batteries' mysteriously high thermal resistance have been confined to ex situ measurements without understanding the impact of battery operation. Here, we develop a frequency-domain technique that employs sensors capable of measuring spatially resolved intrinsic thermal transport properties within a live battery while it is undergoing cycling. Our results reveal that the poor battery thermal transport is due to high thermal contact resistance between the separator and both electrode layers and worsens as a result of formation cycling, degrading total battery thermal transport by up to 70%. We develop a thermal model of these contact resistances to explain their origin. These contacts account for up to 65% of the total thermal resistance inside the battery, leading to far-reaching consequences for the thermal design of batteries. Our technique unlocks new thermal measurement capabilities for future battery research

A review of thermal physics and management inside lithium-ion batteries for high energy density and fast charging

Traditionally it has been assumed that battery thermal management systems should be designed to maintain the battery temperature around room temperature. That is not always true as lithium-ion battery (LIB) R&D is pivoting towards the development of high energy density and fast charging batteries. Therefore, it is necessary to have a comprehensive review of thermal considerations for LIBs targeted for high energy density and fast charging, i.e., the optimal thermal condition, thermal physics (heat transport and generation) inside the battery, and thermal management strategies. As the energy density and charge rate increases, the optimal battery temperature can shift to be higher than room temperature. In the first part of the review various sources of heat generation inside LIBs and various approaches to minimizing battery heat generation are summarized. The importance of heat of mixing due to ion diffusion during fast charging is also highlighted. To improve the temperature uniformity and avoid excessive internal temperature rise, heat transfer inside the battery needs to be enhanced, and reducing the thermal contact resistance between the electrodes and separator can significantly increase the effective thermal conductivity of batteries. In the second part of the review various challenges and latest developments related to thermal transport and properties of LIBs are discussed. Finally, a summary of latest advancement on smart control of internal temperature of LIBs is discussed as depending on the ambient temperature and the optimal temperature; the battery heat needs to be retained or dissipated to elevate or avoid temperature rise

A review of thermal physics and management inside lithium-ion batteries for high energy density and fast charging

Traditionally it has been assumed that battery thermal management systems should be designed to maintain the battery temperature around room temperature. That is not always true as lithium-ion battery (LIB) R&D is pivoting towards the development of high energy density and fast charging batteries. Therefore, it is necessary to have a comprehensive review of thermal considerations for LIBs targeted for high energy density and fast charging, i.e., the optimal thermal condition, thermal physics (heat transport and generation) inside the battery, and thermal management strategies. As the energy density and charge rate increases, the optimal battery temperature can shift to be higher than room temperature. In the first part of the review various sources of heat generation inside LIBs and various approaches to minimizing battery heat generation are summarized. The importance of heat of mixing due to ion diffusion during fast charging is also highlighted. To improve the temperature uniformity and avoid excessive internal temperature rise, heat transfer inside the battery needs to be enhanced, and reducing the thermal contact resistance between the electrodes and separator can significantly increase the effective thermal conductivity of batteries. In the second part of the review various challenges and latest developments related to thermal transport and properties of LIBs are discussed. Finally, a summary of latest advancement on smart control of internal temperature of LIBs is discussed as depending on the ambient temperature and the optimal temperature; the battery heat needs to be retained or dissipated to elevate or avoid temperature rise

Interpretable Forward and Inverse Design of Particle Spectral Emissivity Using Common Machine-Learning Models

Radiative particles are ubiquitous in nature and in various technologies. Calculating radiative properties from known geometry and designs can be computationally expensive, and trying to invert the problem to come up with designs specific to desired radiative properties is even more challenging. Here, we report a machine-learning (ML)-based method for both the forward and inverse problem for dielectric and metallic particles. Our decision-tree-based model is able to provide explicit design rules for inverse problems. Furthermore, we can use the same trained model for both the forward and the inverse problem, which greatly simplifies the computation. Our methodology shows the promise of augmenting optical design optimizations by providing interpretable and actionable design rules for rapidly finding approximate solutions for the inverse design problem. Inverse design is usually done by expensive, slow, iterative optimization. Elzouka et al. show how a simple machine-learning model (decision trees) can efficiently perform inverse design in one shot, while recovering design rules understandable by humans. Inverse design of the spectral emissivity of particles is used as an example

Operando spatial mapping of lithium concentration using thermal-wave sensing

The development of battery sensing techniques is crucial for safe, reliable, and fast operation of lithium-ion batteries (LIBs). There is a growing realization that the spatially averaged chemical information provided by existing battery diagnostic tools is insufficient for understanding degradation of LIBs. Here, we report the use of thermal waves for operando probing of the local lithium concentration as a function of depth inside battery electrodes. The dependence of the thermal conductivity of electrodes on lithiation is used for lithium detection for the first time. A proof-of-concept study of graphite anodes demonstrates that thermal-wave sensing provides spatial information of lithium concentration comparable with experimental results using synchrotron X-ray diffraction. Therefore, a valuable battery sensing technique based on thermal waves is developed for studying the lithium concentration and the degradation of electrodes during fast charge, which may lead to much cheaper and faster sensing techniques compared with synchrotron-based techniques

Operando spatial mapping of lithium concentration using thermal-wave sensing

The development of battery sensing techniques is crucial for safe, reliable, and fast operation of lithium-ion batteries (LIBs). There is a growing realization that the spatially averaged chemical information provided by existing battery diagnostic tools is insufficient for understanding degradation of LIBs. Here, we report the use of thermal waves for operando probing of the local lithium concentration as a function of depth inside battery electrodes. The dependence of the thermal conductivity of electrodes on lithiation is used for lithium detection for the first time. A proof-of-concept study of graphite anodes demonstrates that thermal-wave sensing provides spatial information of lithium concentration comparable with experimental results using synchrotron X-ray diffraction. Therefore, a valuable battery sensing technique based on thermal waves is developed for studying the lithium concentration and the degradation of electrodes during fast charge, which may lead to much cheaper and faster sensing techniques compared with synchrotron-based techniques