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dynamic/operando observations, and the ability to “see” buried interfaces. The second is a computational framework that emphasizes continuum modeling capable of revealing the evolution of degradation processes while incorporating the fidelity of molecular-level modeling into a larger framework. Emphasis on continuum modeling is critical for its capability to address the behavior behind mesoscale aggregates of molecular, particle, or nanostructure components. Developing a multimodal array of sophisticated characterization techniques with improved specificity, resolution, and sensitivity, combined with multiscale frameworks converging in continuum modeling, can provide critical scientific insights for significantly improving function, safety, and robustness of electrochemical devices across a broad range of chemistries and architectures. In turn, these insights may stimulate creative approaches to mitigate degradation in the form of electrolyte additives; coatings on active material particle surfaces; entirely new materials, electrodes, or cell architectures; or other approaches not yet identified. Not only will this result in longer calendar and cycle lifetimes, but it can also potentially enable the adoption of energy storage devices with much higher energy densities than currently available, without compromising safety. Furthermore, this approach can result in shorter lab-to-market timelines for new chemistries or architectures with superior properties, as simulations validated by experiment provide lifetime and degradation predictions that reduce the need for extended and time-consuming accelerated testing. 2.5.2 RESEARCH THRUSTS Thrust 5a: Multimodal In Situ Experiments to Quantify Degradation and Failure Goal: The goal of this thrust is to develop multimodal, in situ and operando experimental tools with sufficient space and time resolution to see the individual steps in the degradation pathway, understand the cause-and- effect relationships among these coupled phenomena, and thus map the degradation pathway from start to finish to define directions that indicate how battery redesign, choice of materials, or other features can be successful in mitigating the degradation. The emphasis on multimodal techniques reflects the scientific importance of relating degradation metrics to the broader, causal behavior that drives degradation in the materials and architectures employed in the battery. The emphasis on in situ and operando approaches recognizes that ex situ characterization is not sufficient, as it sees only the static outcome of part of the degradation pathway and misses the history of the dynamic interactions of phenomena as they develop. While significant research advances have been made in the last decade in exploiting in situ and operando tools, they have generally not been applied to characterizing degradation pathways in batteries or deployed in multimodal characterization to examine multiple aspects of the same interacting phenomena over several length and time scales. Battery degradation and failure, like battery operation, is a complex interaction of many heterogeneous phenomena,15 involving numerous coupled electrochemical, chemical, thermal, and mechanical phenomena, each with its own kinetic signature. Figure 2.5.4 summarizes some of the relevant phenomena and their time and length scales. Leveraging Characterization Strategies to Understand and Mitigate Degradation: In typical practice, the outcomes of many coupled phenomena are lumped into a single performance metric (or related group thereof): for example, voltage-current measurements that can be obtained following different protocols. However, these do not reveal the controlling mechanical, chemical, or thermal origins. Similarly, measured temperature variations arise from several possible contributions, including resistive heating, entropic changes due to electrochemical reactions, and the enthalpy of unwanted side reactions. Anisotropic heat conduction creates non-uniform temperature distributions inside the battery, which, in turn, influence the kinetics of local electrochemical phenomena, mechanical expansion, strain, and possibly fracture. Multimodal characterization of the properties and behavior of the materials as they are configured in the battery architecture is a prerequisite for inferring the origins and evolution of degradation phenomena. Furthermore, since battery electrodes have spatial structure, ranging from abrupt interfaces and grain structure in polycrystalline material to particles in composite electrodes, high spatial resolution of the characterization techniques is an important element in at least some part of the multimodal portfolio. Moreover, such characterization adds value primarily in conveying a picture of how degradation proceeds. In turn, this places a large premium on in situ and operando experiments that resolve the individual phenomena and reveal their interactions, uncovering otherwise unknown degradation pathways and providing quantitative behavior to inform predictive continuum models of degradation and failure. Over the last decade, many NEXT GENERATION ELECTRICAL ENERGY STORAGE PRIORITY RESEARCH DIRECTION – 5 69PDF Image | Next Generation Electrical Energy Storage
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