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Ma, Zhuang

Publications and source records attributed to Ma, Zhuang.

Solid-state interphases design for high-safety, high-voltage and long-cyclability practical batteries via ethylene carbonate-free electrolytes

In this study, ethylene carbonate (EC) plays a crucial role in current electrolytes for batteries. However, EC reacts exothermically with the electrode to trigger thermal runaway and undergoes continuous oxidative decomposition at high voltages, hindering it application for next-generation batteries. Here we report a simple and effective strategy to design sulfolane(SL)-based electrolyte with reshaped anions-dominated solvation structure, forming highly stable inorganic-dominated electrode-electrolyte interphases that efficiently stabilize nickel-rich cathode and graphite anode. Compared with the conventional electrolyte, practical pouch-type LiNi 0.8 Co 0.1 Mn 0.1 O 2 |Graphite cell with SL-based electrolyte significantly improve self-generated heat T 1 and thermal runaway triggering T 2 by 9.6 and 42.0 °C, respectively. More surprisingly, the pouch cell with SL-based electrolyte exhibits outstanding capacity retention of 88 % after 1000 cycles charged up to 4.5 V. The study brings new insights for unlocking advanced electrolyte candidates to build next-generation practical safer high-energy batteries.

25 ENERGY STORAGE↗

Demonstration of object location, classification, and characterization by developed deep learning dust ablation trail analysis code package using plasma jets

Based on deep learning, a Dust Ablation Trail Analysis (DATA) code package is developed to detect dust ablation trails in tokamaks, which is intended to analyze a large amount data of tokamak dusts. To validate and benchmark the DATA code package, 2440 plasma jet images are exploited for the training and test of the deep learning DATA code package, since plasma jets resemble the shape and size of dust ablation clouds in tokamaks. After being trained by 1920 plasma jet images, the DATA code package is able to locate 100% plasma jets, classify plasma jets with the accuracy of >99.9%, and output image skeleton information for classified plasma jets. The DATA code package trained by the plasma jet images is also used to analyze the dust ablation trails captured in the Experimental Advanced Superconducting (EAST) tokamak with the satisfactory performance, further verifying its applicability in the fusion dust ablation investigation. Based on its excellent performance presented here, it is demonstrated that our DATA code package is able to automatically identify and analyze dust ablation trails in tokamaks, which can be used for further detailed investigations, such as the three-dimensional reconstruction of dusts and their ablation trails.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Thermal Runaway of Nonflammable Localized High‐Concentration Electrolytes for Practical LiNi 0.8 Mn 0.1 Co 0.1 O 2 |Graphite‐SiO Pouch Cells

Abstract With continuous improvement of batteries in energy density, enhancing their safety is becoming increasingly urgent. Herein, practical high energy density LiNi 0.8 Mn 0.1 Co 0.1 O 2 |graphite‐SiO pouch cell with nonflammable localized high concentration electrolyte (LHCE) is proposed that presents unique self‐discharge characteristic before thermal runaway (TR), thus effectively reducing safety hazards. Compared with the reference electrolyte, pouch cell with nonflammable LHCE can increase self‐generated heat temperature by 4.4 °C, increase TR triggering temperature by 47.3 °C, decrease the TR highest temperature by 71.8 °C, and extend the time from self‐generated heat to triggering TR by ≈8 h. In addition, the cell with nonflammable LHCE presents superior high voltage cycle stability, attributed to the formation of robust inorganic‐rich electrode–electrolyte interphase. The strategy represents a pivotal step forward for practical high energy and high safety batteries.

36 MATERIALS SCIENCE↗