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Xin Jiang

Researcher at Zhengzhou University

Publications -  20
Citations -  234

Xin Jiang is an academic researcher from Zhengzhou University. The author has contributed to research in topics: Chemistry & Computer science. The author has an hindex of 3, co-authored 6 publications receiving 78 citations.

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High-Energy-Density Solid-Electrolyte-Based Liquid Li-S and Li-Se Batteries

TL;DR: In this paper, a solid-electrolyte-based liquid Li-S and Li-Se (SELLS and SELL-Se in short) batteries are proposed, which use a Li6.4La3Zr1.4Ta0.6O12 (LLZTO) ceramic tube as electrolyte.
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Detection of Micro-Scale Li Dendrite via H2 Gas Capture for Early Safety Warning

TL;DR: In this article, Li-ion battery safety issues related to fires and explosions are frequently triggered by Li dendrite growth, which is the predominant reason for separator piercing and cell shorts and is difficult to detect in the early state.
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Vertical Crystal Plane Matching between AgZn3 (002) and Zn (002) Achieving a Dendrite-Free Zinc Anode.

TL;DR: In this article , a nanothickness (≈570nm) AgZn3-coating was used to regulate the Zn growth in zinc-ion batteries.
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Optimization of Battery Energy Storage System Capacity for Wind Farm with Considering Auxiliary Services Compensation

TL;DR: In this paper, an optimal sizing model of the battery energy storage system (BESS) for large-scale wind farm adapting to the scheduling plan is proposed based on the analysis of the variability and uncertainty of wind output, the cost of auxiliary services of systems that are eased by BESS, and the constraints of BESS accounting for the effect of wind power on system dispatching are proposed.
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Optimal configuration of hybrid energy systems considering power to hydrogen and electricity-price prediction: A two-stage multi-objective bi-level framework

TL;DR: In this article , a two-stage multi-objective bi-level framework is proposed to optimize the sizing of a grid-connected electricity-hydrogen system, where the CPLEX solver and non-dominated sorting genetic algorithm II are employed to obtain the solutions of the developed optimization model.