Mechanistic understanding of a bifunctional carbonate additive for enhanced performance in lithium-sulfur battery
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Engineering topics
Publications and source records attributed to Du, Yonghua.
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The aqueous zinc-sulfur battery holds promise for significant capacity and energy density with low cost and safe operation based on environmentally benign materials. However, it suffers from the sluggish kinetics of the conversion reaction. Here, we highlight the efficacy of molybdenum(IV) sulfide (MoS 2 ) to reduce the overpotential of S-ZnS conversion in aqueous electrolytes and study the discharge products formed at the solid-solid and solid-liquid interfaces using experimental and theoretical approaches. Specifically, the MoS 2 -catalyzed electrochemical conversion reaction is characterized via ex situ X-ray diffraction (XRD), transmission electron microscopy (TEM) with energy dispersive spectroscopy (EDS), Raman spectroscopy, synchrotron-based Mo K-edge X-ray absorption spectroscopy (XAS), and in situ synchrotron-based X-ray computed tomography (XCT). Additionally, operando synchrotron-based S K-edge XAS and X-ray fluorescence (XRF) maps are collected to determine the spatial evolution of sulfur-based species at the electrode-electrolyte interface. Further, coupling the operando S K-edge XAS data with the simulated spectra and fitting the data suggested a possible ZnS 2 intermediate phase.
Autonomous methods to align beamlines can decrease the amount of time spent on diagnostics, and also uncover better global optima leading to better beam quality. The alignment of these beamlines is a high-dimensional expensive-to-sample optimization problem involving the simultaneous treatment of many optical elements with correlated and nonlinear dynamics. Bayesian optimization is a strategy of efficient global optimization that has proved successful in similar regimes in a wide variety of beamline alignment applications, though it has typically been implemented for particular beamlines and optimization tasks. In this paper, we present a basic formulation of Bayesian inference and Gaussian process models as they relate to multi-objective Bayesian optimization, as well as the practical challenges presented by beamline alignment. We show that the same general implementation of Bayesian optimization with special consideration for beamline alignment can quickly learn the dynamics of particular beamlines in an online fashion through hyperparameter fitting with no prior information. We present the implementation of a concise software framework for beamline alignment and test it on four different optimization problems for experiments on X-ray beamlines at the National Synchrotron Light Source II and the Advanced Light Source, and an electron beam at the Accelerator Test Facility, along with benchmarking on a simulated digital twin. We discuss new applications of the framework, and the potential for a unified approach to beamline alignment at synchrotron facilities.
Metal cutting is a crucial process in modern manufacturing. Enhancing the machinability of metals can significantly improve their production efficiency and surface integrity. Coating surface-active media (SAM) on the free surface of the metals before cutting is an easy method to improve machinability, which usually pertains to the category of the renowned Rehbinder effect. However, the existing SAM is usually hazardous and complex materials. Besides, the effect of SAM on the local structure of the metal surface remains unclear. In this study, water is employed as a simple yet often overlooked SAM in the microcutting of copper. Using water as SAM also allows the employment of X-ray absorption fine structure spectroscopy (XAFS) to study the local structure of copper with and without water coating. Results show that water coating on the free surface of copper can significantly reduce the cutting force and chip thickness, and improve the surface finish. Interestingly, removing the water coating enables the recovery of the cutting force, demonstrating a reversible effect. Based on the XAFS results and molecular dynamics simulation, a water-induced surface ordering mechanism is proposed to explain the findings from the microcutting experiments. This mechanism suggests that water molecules can induce surface ordering in copper, resulting in reduced surface energy and fracture toughness of copper, thus enhancing machinability. In conclusion, this work provides valuable insights into the comprehension of the Rehbinder effect and shows that picometer-scale modifications of the surface atom arrangement can considerably alter the deformation mode of metals, paving the way for the development of new manufacturing processes.
Alkaline metal sulfur (AMS) batteries offer a promising solution for grid-level energy storage due to their low cost and long cycle life. However, the formation of solid compounds such as M 2 S 2 and M 2 S (M = Na, K) during cycling limits their performance. Here we unveil intermediate-temperature K-Na/S batteries utilizing advanced electrolytes that dissolve all polysulfides and sulfides (K 2 S x , x = 1–8), significantly enhancing reaction kinetics, specific capacity, and energy density. These batteries achieve near-theoretical capacity (1655 mAh g -1 sulfur) at 75 °C with a 1 M sulfur concentration. At a 4 M sulfur concentration, they deliver 830 mAh g -1 at 2 mA cm -2 , retaining 71% capacity after 1000 cycles. This new K-Na/S battery with specific energy of 150-250 Wh kg -1 only employs earth-abundant elements, making it attractive for long-duration energy storage.