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Zhang, Xiaoman

Publications and source records attributed to Zhang, Xiaoman.

Fluoride-Rich, Organic–Inorganic Gradient Interphase Enabled by Sacrificial Solvation Shells for Reversible Zinc Metal Batteries

Zinc metal batteries are strongly hindered by water corrosion, as solvated zinc ions would bring the active water molecules to the electrode/electrolyte interface constantly. Herein, we report a sacrificial solvation shell to repel active water molecules from the electrode/electrolyte interface and assist in forming a fluoride-rich, organic-inorganic gradient solid electrolyte interface (SEI) layer. Additionally, the simultaneous sacrificial process of methanol and Zn(CF 3 SO 3 ) 2 results in the gradient SEI layer with an organic-rich surface (CH 2 OC- and C 5 product) and an inorganic-rich (ZnF 2 ) bottom, which combines the merits of fast ion diffusion and high flexibility. As a result, the methanol additive enables corrosion-free zinc stripping/plating on copper foils for 300 cycles with an average coulombic efficiency of 99.5%, a record high cumulative plating capacity of 10 A h/cm 2 at 40 mA/cm 2 in Zn/Zn symmetrical batteries. More importantly, at an ultralow N/P ratio of 2, the practical VO 2 //20 mu m thick Zn plate full batteries with a high areal capacity of 4.7 mAh/cm 2 stably operate for over 250 cycles, establishing their promising application for grid-scale energy storage devices. Furthermore, directly utilizing the 20 μm thick Zn for the commercial-level areal capacity (4.7 mAh/cm 2 ) full zinc battery in our work would simplify the manufacturing process and boost the development of the commercial zinc battery for stationary storage.

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↗

On the failure mechanisms of Cr-coated 316 stainless steel in bending fatigue tests

Here, fully-reversed cyclic bending tests were conducted on uncoated and Cr-coated 316 stainless steel specimens. At high stresses, the uncoated specimens outperformed the Cr-coated ones, while the trend reversed at low stresses. For Cr-coated specimens subjected to high stress amplitude loading, experimental observations showed crack initiation at the Cr/substrate interface due to shear steps formed from dislocation activities in the substrate—a conclusion supported by accompanying finite element analysis. Interfacial crack initiation was not observed under low stress amplitudes. This difference in fatigue crack initiation mechanisms induced an opposite trend in fatigue life between high and low stress amplitudes.

36 MATERIALS SCIENCE↗