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Guan, Pin-Wen

Publications and source records attributed to Guan, Pin-Wen.

Differentiable modeling and optimization of non-aqueous Li-based battery electrolyte solutions using geometric deep learning

Electrolytes play a critical role in designing next-generation battery systems, by allowing efficient ion transfer, preventing charge transfer, and stabilizing electrode-electrolyte interfaces. In this work, we develop a differentiable geometric deep learning (GDL) model for chemical mixtures, DiffMix, which is applied in guiding robotic experimentation and optimization towards fast charging battery electrolytes. In particular, we extend mixture thermodynamic and transport laws by creating GDL-learnable physical coefficients. We evaluate our model with mixture thermodynamics and ion transport properties, where we show improved prediction accuracy and model robustness of Diff-Mix than its purely data-driven variants. Furthermore, with a robotic experimentation setup, Clio, we improve ionic conductivity of electrolytes by over 18.8% within 10 experimental steps, via differentiable optimization built on DiffMix gradients. By combining GDL, mixture physics laws, and robotic experimentation, DiffMix expands the predictive modeling methods for chemical mixtures and enables efficient optimization in large chemical spaces.

25 - ENERGY STORAGE↗

Phase Diagrams of Alloys and Their Hydrides via On-Lattice Graph Neural Networks and Limited Training Data

Efficient prediction of sampling-intensive thermodynamic properties is needed to evaluate material performance and permit high-throughput materials modeling for a diverse array of technology applications. To alleviate the prohibitive computational expense of high-throughput configurational sampling with density functional theory (DFT), surrogate modeling strategies like cluster expansion are many orders of magnitude more efficient but can be difficult to construct in systems with high compositional complexity. We therefore employ minimal-complexity graph neural network models that accurately predict and can even extrapolate to out-of-train distribution formation energies of DFT-relaxed structures from an ideal (unrelaxed) crystallographic representation. This enables the large-scale sampling necessary for various thermodynamic property predictions that may otherwise be intractable and can be achieved with small training data sets. Two exemplars, optimizing the thermodynamic stability of low-density high-entropy alloys and modulating the plateau pressure of hydrogen in metal alloys, demonstrate the power of this approach, which can be extended to a variety of materials discovery and modeling problems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Low-Pressure Electrochemical Synthesis of Complex High-Pressure Superconducting Superhydrides

There is great current interest in multicomponent superhydrides due to their unique quantum properties under pressure. A remarkable example is the ternary superhydride Li 2 MgH 16 computationally identified to have an unprecedented high superconducting critical temperature T c of ~470 K at 250 GPa. However, the very high synthesis pressures required remains a significant hurdle for detailed study and potential applications. In this Letter, we evaluate the feasibility of synthesizing ternary Li-Mg superhydrides by the recently proposed pressure-potential (P 2 ) method that uniquely combines electrochemistry and applied pressure to control synthesis and stability. Furthermore, the results indicate that it is possible to synthesize Li-Mg superhydrides at modest pressures by applying suitable electrode potentials. Using pressure alone, no Li-Mg ternary hydrides are predicted to be thermodynamically stable, but in the presence of electrode potentials, both Li 2 MgH 16 and Li 4 MgH 24 can be stabilized at modest pressures. Three polymorphs are predicted as ground states of Li 2 MgH 16 below 300 GPa, with transitions at 33 and 160 GPa. The highest pressure phase is superconducting, while the two at lower pressures are not. Our findings point out the potentially important role of the P 2 method in controlling phase stability of complex multicomponent superhydrides.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Combining pressure and electrochemistry to synthesize superhydrides

Significance Superhydrides are a materials system where near–room-temperature superconductivity has been achieved but only at very high (megabar) pressures. This work proposes an approach that combines pressure and electrochemistry to stabilize superhydrides at moderate pressures. Through a computational study of the palladium–hydrogen system, we construct electrochemical phase diagrams and show that electrochemically synthesizing superhydrides may be possible when combined with moderate pressures. We generalize this to other binary metal superhydrides of interest for superconductivity, including La, Y, and Mg hydrides.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Effect of heat treatment on microstructural evolution and hardness homogeneity in laser powder bed fusion of alloy 718

The thermal history developed in laser powder bed fusion (LPBF) processes has been shown to be complex resulting in equally complex microstructures and mechanical properties. Microscopic observations and Vickers micro-hardness mapping measurements were carried out on diff ;erent section planes of LPBF alloy 718 cuboids. Three-dimensional finite element analysis was used to simulate thermal history and to predict the residual stress distribution in the as-built material. Computational thermodynamics was used to predict the micro-segregation and nucleation driving force of various phases in the bulk and in segregated regions. Varied heat-treatments such as simulated hot isostatic pressing, and double aging were applied. Their influence on the microstructure, microsegregation, precipitate formation, and micro-hardness variations of LPBF alloy 718 were investigated. Hardness map results showed heterogeneous micro-hardness on the xy- and xz-planes of the as-built parts where the bottom plane and center regions had larger hardness of ~315 HV 0.5 while the top plane and contours showed hardness of ~300 HV 0.5 . It was found that the aging treatment increased the overall hardness of the as-built condition from ~310 HV 0.5 to 470 HV 0.5 but also increased the hardness gradient throughout the coupon. After simulated hot isostatic pressing process (i.e., without applied pressure) at 1020 °C for 4 h followed by water quench (HIPWQ), the hardness gradient and hardness was minimized (~210 HV 0.5 ) as the microstructure transitioned from heterogeneous columnar grains in the as-built condition to more uniform recrystallized grains. A double aging treatment was applied to enhance hardness from ~210 HV 0.5 to ~440 HV 0.5 . Finally, HIPWQ followed by double aging produced a homogeneous microstructure and more uniform hardness map with enhanced mechanical properties in LPBF alloy 718 coupons.

36 MATERIALS SCIENCE↗