Abstract:

The functioning of Li metal-solid state batteries (LMSSB) requires that interfacial contact between the Li metal anode and the solid electrolyte (SE) be maintained during cycling. A reduction in contact area during Li stripping will increase the local current density during subsequent Li plating, fostering dendrite nucleation. The contact area is influenced by the rate of Li transport within the anode towards the interface. Relevant transport mechanisms include diffusion and creep, with faster rates of these processes resulting in improved performance. Given the importance of these transport modes, predicting them as a function of the anode’s microstructure, stress state, and temperature will be helpful in the design of LMSSB. Here, the rates of diffusion and creep in Li are predicted using atomic scale simulations. A primary goal is to understand if and how Li microstructure impacts the performance of LMSSB. First, molecular dynamics is used to estimate the rate of Li diffusion along dislocations and in grain boundary triple junctions. By combining this data with that from a prior study of grain boundary diffusion, the dominant diffusion mechanisms and overall rates of self-diffusion in Li polycrystals are predicted as a function of grain size, grain shape, dislocation density, and temperature. A 1D continuum model for interfacial contact is parameterized using the computed diffusion data. The model predicts that high dislocation densities (~10 12 /cm 2 ) and/or small grain sizes (~10 m) enable achieving battery performance targets. Secondly, the dominant creep deformation mechanisms are predicted as a function of applied stress, grain size, and temperature. Grain boundary sliding and coble creep are observed to be the primary mechanisms for micron-sized grains. Finally, a kinetic lattice Monte Carlo model is developed to monitor the dynamics of Li voids as a function of interfacial thermodynamics and the presenceof grain boundaries.

Bio:

Don Siegel is Professor and Chair of the Walker Department of Mechanical Engineering at the University of Texas at Austin. He also has appointments in the Oden Institute for Computational Engineering and Sciences and the Texas Materials Institute. At UT he is a Temple Foundation Endowed Professor and holds a Cockrell Family Chair for Departmental Leadership. Prior to joining UT in 2021, Prof. Siegel spent 12 years at the University of Michigan, with earlier posts in industry (Ford Motor Company) and at national laboratories (Sandia National Lab and the U.S. Naval Research Lab). Siegel is a computational materials scientist whose research targets the development of energy storage materials and lightweight alloys. He is a recipient of the NSF Career Award and a Gilbreth Lectureship from the National Academy of Engineering.

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Abstract:

We provide an overview of a recent NASA University Leadership Initiative project entitled “Development of an Ecosystem for Qualification of Additive Manufacturing Processes and Materials in Aviation”. This work demonstrated the dependence of fatigue on defect structures in AM Ti-6Al-4V. Our current NASA Science & Technology Research Institute “Institute for Model-Based Qualification & Certification of Additive Manufacturing (IMQCAM)” is creating a numerical digital twin (DT) for predicting fatigue as a function of process parameters. The key result of a systematic variation across power-velocity space was that the defect number density was anti-correlated with fatigue life. The fatigue-based process window was much narrower compared to typical reports and explainable in terms of observed variations based on spatter rates and intermittent lack of melt pool overlap. We report on recent developments in modeling microstructure, texture and pores along with variations in heat treatment. We conclude that establishing a qualified materials process is feasible via an efficient survey of a limited domain of process space. Linking models together in the DT requires substantial effort in terms of data exchange. In terms of predictability of fatigue, the limited data suggests that the scatter in life is smallest in the long crack (Paris Law) regime, intermediate for short cracks and largest for crack nucleation. This provides an important background for Uncertainty Quantification (UQ), which is a major focus for the IMQCAM team and which has already revealed a significant sensitivity to compositional variations, for example.

Support from multiple agencies is gratefully acknowledged, including NASA, DOE/BES, DOE/NNSA, ONR, NSF, OEA, Commonwealth of Pennsylvania, and Ametek. I am indebted to my many collaborators.

Bio:

I have been a member of the faculty at Carnegie Mellon University since 1995. I am also the Co-Director of the NextManufacturing Center on additive manufacturing. Previously, I worked for the University of California at the Los Alamos National Laboratory. I spent nine years in management with four years as a Group Leader (and then Deputy Division Director) at Los Alamos, followed by five years as Department Head at CMU (up to 2000). I have been a Fellow of ASM since 1996, Fellow of the Institute of Physics (UK) since 2004 and Fellow of TMS since 2011. I received the Cyril Stanley Smith Award from TMS in 2014, was elected as Member of Honor by the French Metallurgical Society in 2015 and then became the US Steel Professor of Metallurgical Engineering and Materials Science in 2017. I received Cyril Stanley Smith Award from the International Conference on Recrystallization and Grain Growth in 2019 and the Hans Bunge Award from the Intl. Conf. on Textures of Materials (ICOTOM) in 2024. I was an International Francqui Professor (Belgium) in 2022 and I received the ASM Gold Medal and was promoted to University Professor, both in 2024. My research focuses on processing-microstructure-properties relationships with interests in additive manufacturing, the measurement and prediction of microstructural evolution, the relationship between microstructure and properties, especially three-dimensional effects, texture & anisotropy and the use of synchrotron x-rays.