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Gallium-based liquid metals for lithium-ion batteries

Interdisciplinary Materials 2022年第3期1卷 354-372页

作者： Bin-Wei Zhang Long Ren Yun-Xiao Wang Xun Xu Yi Du Shi-Xue Dou College of Chemistry and Chemical Engineering Chongqing UniversityChongqingChina Center of Advanced Energy Technology and Electrochemistry Chongqing UniversityChongqingChina Institute for Superconducting and Electronic Materials Australian Institute of Innovative MaterialsUniversity of WollongongNorth WollongongNew South WalesAustralia State Key Laboratory of Advanced Technology for Materials Synthesis and Processing International School of Materials Science and EngineeringWuhan University of TechnologyWuhanChina BUAA-UOW Joint Research Centre and School of Physics Beihang UniversityBeijingChina

Lithium-ion batteries(LIBs)are one of the most exciting inventions of the 20th century and have been widely employed in modern *** have powered many of our electronics,such as laptop computers,smartphones,and even large-scale energy storage *** the development of modern technology,next-generation LIBs with higher energy density are in demand.A number of electrode materials with high theoretical capacity,including Sn,Si,Li metal anode,and S cathode materials,have been ***,they usually suffer from structural or interface failure during cycling,limiting their practical ***-based liquid metals(LMs)possess self-healing capability,fluidity,and metallic advantages so they have been employed as self-healing skeletons or interfacial protective layers to minimize the negative impact of volume expansion or dendritic growth on the electrode ***,the features of Ga-based LMs are briefly discussed to indicate their potential for battery *** addition,recent developments on Ga-based LMs applied in LIBs have been summarized,including from the aspects of anodes,cathodes,and ***,future opportunities and challenges for the development of Ga-based LMs in LIBs are highlighted.

关键词： anode cathode electrolyte gallium-based liquid metals lithium-ion batteries

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A general and transferable deep learning framework for predicting phase formation in materials

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npj Computational Materials 2021年第1期7卷 89-98页

作者： Shuo Feng Huadong Fu Huiyu Zhou Yuan Wu Zhaoping Lu Hongbiao Dong School of Engineering University of LeicesterLeicester LE17RHUK Beijing Advanced Innovation Center of Materials Genome Engineering University of Science and Technology Beijing100083 BeijingChina School of Informatics University of LeicesterLeicester LE17RHUK State Key Laboratory for Advanced Metals and Materials University of Science and Technology Beijing100083 BeijingChina

Machine learning has been widely exploited in developing new ***,challenges still exist:small dataset is common for most tasks;new datasets,special descriptors and specific models need to be built from scratch when facing a new task;knowledge cannot be readily transferred between independent *** this paper we propose a general and transferable deep learning(GTDL)framework for predicting phase formation in *** proposed GTDL framework maps raw data to pseudoimages with some special 2-D structure,e.g.,periodic table,automatically extracts features and gains knowledge through convolutional neural network,and then transfers knowledge by sharing features extractors between *** of the GTDL framework in case studies on glass-forming ability and high-entropy alloys show that the GTDL framework for glass-forming ability outperformed previous models and can correctly predicted the newly reported amorphous alloy systems;for high-entropy alloys the GTDL framework can discriminate five types phases(BCC,FCC,HCP,amorphous,mixture)with accuracy and recall above 94%in fivefold *** addition,periodic table knowledge embedded in data representations and knowledge shared between models is beneficial for tasks with small *** method can be easily applied to new materials development with small dataset by reusing well-trained models for related materials.

关键词： materials alloys alloy

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Dual-Aspect Control of Lithium Nucleation and Growth with Hydroxyapatite and Liquid Crystal Polymers for High-Performance Lithium Metal Batteries

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advanced Energy Materials 2025年第0期

作者： Miao, Xiang Wu, Zhouhan Hu, Wei Guo, Lin Nan, Ce-Wen School of Chemistry Beijing Advanced Innovation Center for Biomedical Engineering Beihang University Beijing100191 China State Key Laboratory of New Ceramics and Fine Processing School of Materials Science and Engineering Tsinghua University Beijing100084 China Institute for Advanced Materials and Technology University of Science and Technology Beijing Beijing100083 China

Lithium (Li) metal is a promising anode material for next-generation high-energy-density batteries. However, safety concerns and the limited lifespan due to Li dendrite formation hinder its practical application. The complex dendrite formation process involves nonuniform nucleation and radial growth, requiring a holistic strategy to simultaneously regulate both processes. In this work, a dual-aspect control strategy is developed by designing a protective layer composed of hydroxyapatite (HA) and a liquid crystal polymer (LCP). Electrochemical, microstructural, and computational analyses revealed that HA provides homogenous Li0 adsorption sites, enhancing Li nucleation kinetics and uniformity. Meanwhile, the LCP self-assembles into cation-selective channels, promoting Li-ion diffusion and regulating growth direction. This dual-aspect control significantly improved Li plating kinetics and mitigated Li dendrite formation. Benefiting from this strategy, the symmetric cell achieved a critical current density of 5 mA cm−2 and maintained a lifespan of 500 h at 3 mA cm−2. Furthermore, in Li–sulfur batteries, the cell exhibited exceptional high-rate cycling performance (>10 mA cm−2) with an average capacity decay rate of only 0.056% over 1000 cycles. These results highlight the effectiveness of dual-aspect control in suppressing Li dendrites and improving high-rate cycling stability. © 2025 Wiley-VCH GmbH.

关键词： Liquid crystals

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Microstructure and mechanical properties of FeMnNiCrV high entropy alloy under ion irradiation

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Journal of Alloys and Compounds 2025年 1032卷

作者： Wang, S. Liu, P.P. Guo, Y.W. Zhang, J. Han, W.T. Yi, X.O. Zhan, Q. Ohnuki, S. Wan, F.R. School of Materials Science and Engineering USTB-BJHB Joint Laboratory of Beryllium and Advanced Materials for Fusion Energy University of Science and Technology Beijing Beijing100083 China USTB-BJHB Joint Laboratory of Beryllium and Advanced Materials for Fusion Energy University of Science and Technology Beijing Beijing100083 China State Key Laboratory of Advanced Metallurgy Department of Physical Chemistry of Metallurgy School of Metallurgical and Ecological Engineering University of Science and Technology Beijing Beijing100083 China Faculty of Engineering Hokkaido University Sapporo060-8628 Japan

A compositionally-complex but structurally-simple FeMnNiCrV high-entropy alloy were developed by incorporating the low-activation V element based on the Co-free FeMnNiCr alloy. The mechanical properties and microstructure of the FeMnNiCrV and FeMnNiCr high-entropy alloy before and after ion irradiation were analyzed by using TEM, STEM/EDS, XRD, Nano-indentation and Phase-field simulation. Both FeMnNiCrV and FeMnNiCr samples were irradiated with 2 MeV Au ions at 300 °C with peak damage up to 270 dpa. XRD results show that FeMnNiCrV high-entropy alloy has the same simple FCC structure as FeMnNiCr, and no new precipitate phase was found before and after irradiation. Nano-hardness of FeMnNiCrV high-entropy alloy is higher than that of FeMnNiCr alloy, CLAM steel and Fe9Cr model alloy. The FeMnNiCrV alloy exhibited a lower irradiation hardening rate (18.5 %) compared to that of the FeMnNiCr alloy (27.1 %) after the irradiation. There was no significant irradiation-induced precipitation and voids were observed by using TEM. In addition to the visible dislocation loops, the presence of "other factors" that contribute to irradiation hardening was identified. The impact of these factors on irradiation hardening of FeMnNiCrV and FeMnNiCr are different. The stacking fault and V segregation in FeMnNiCrV were also discussed. © 2025 Elsevier B.V.

关键词： Nanohardness

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Cross-Tokamak Deployment Study of Plasma Disruption Predictors Based on Convolutional Autoencoder

arXiv

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arXiv 2023年

作者： Ai, X.K. Zheng, W. Zhang, M. Ding, Y.H. Chen, D.L. Chen, Z.Y. Shen, C.S. Guo, B.H. Wang, N.C. Yang, Z.J. Chen, Z.P. Pan, Y. Shen, B. Xiao, B.J. Team, J-Text State Key Laboratory of Advanced Electromagnetic Technology International Joint Research Laboratory of Magnetic Confinement Fusion and Plasma Physics School of Electrical and Electronic Engineering Huazhong University of Science and Technology Wuhan430074 China Institute of Plasma Physics Chinese Academy of Sciences Hefei230031 China

In the initial stages of operation for future tokamak, facing limited data availability, deploying data-driven disruption predictors requires optimal performance with minimal use of new device data. This paper studies the issue of data utilization in data-driven disruption predictor during cross tokamak deployment. Current predictors primarily employ supervised learning methods and require a large number of disruption and non-disruption shots for training. However, the scarcity and high cost of obtaining disruption shots for future tokamaks result in imbalanced training datasets, reducing the performance of supervised learning predictors. To solve this problem, we propose the Enhanced Convolutional Autoencoder Anomaly Detection (E-CAAD) predictor. E-CAAD can be only trained by normal samples from non-disruption shots and can also be trained by disruption precursor samples when disruption shots occur. This model not only overcomes the sample imbalance in supervised learning predictors, but also overcomes the inefficient dataset utilization faced by traditional anomaly detection predictors that cannot use disruption precursor samples for training, making it more suitable for the unpredictable datasets of future tokamaks. Compared to traditional anomaly detection predictor, the E-CAAD predictor performs better in disruption prediction and is deployed faster on new devices. Additionally, we explore strategies to accelerate deployment of E-CAAD predictor on the new device by using data from existing devices. Two deployment strategies are presented: mixing data from existing devices and fine-tuning the predictor trained on existing devices. Our comparisons indicate that the data from existing device can accelerate the deployment of predictor on new device. Notably, the fine-tuning strategy yields the fastest deployment on new device among the designed strategies. Copyright © 2023, The Authors. All rights reserved.

关键词： Anomaly detection

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G-C3n4 as Ballistic Electron Transport "Tunnel" in Cspbbr3-Based Ternary Photocatalyst for Gas Phase Co2 Reduction

SSRN

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SSRN 2024年

作者： Li, Dong Li, Renyi Zhao, Yizhou Wang, Kaixuan Fan, Ke Guo, Wei Li, Yujing Chen, Qi Beijing Key Laboratory of Construction Tailorable Advanced Functional Materials and Green Applications Experimental Center of Advanced Materials School of Materials Science and Engineering Beijing Institute of Technology Beijing100081 China State Key Laboratory of Explosion Science and Technology School of Physics Beijing Institute of Technology Beijing100081 China State Key Laboratory of Fine Chemicals Institute of Artificial Photosynthesis Institute for Energy Science and Technology Dalian University of Technology Dalian116024 China

Perovskite CsPbBr3 quantum dot shows great potential in artificial photosynthesis due to its excellent optoelectronic properties. However, its photocatalytic activity is limited by the lack of catalytic active sites and severe charge recombination. In this work, a CsPbBr3@Ag-C3N4 ternary heterojunction photocatalyst is designed and synthesized for high-efficiency CO2 reduction. The CsPbBr3 quantum dots and Ag nanoparticles are chemically anchored on the surface of g-C3N4 sheets, forming an electron transfer tunnel from CsPbBr3 quantum dots to Ag nanoparticles via g-C3N4 sheets. The CsPbBr3@Ag-C3N4 ternary photocatalyst with spatial separation of photogenerated carriers generates a conversion rate of 19.49 μmol·g–1·h–1 with almost 100% CO selectivity, a 3.13-fold enhancement in photocatalytic performance as compared to CsPbBr3 quantum dots. Density functional theory calculations disclose the rapid CO2 adsorption/activation and the decreased free energy (0.66 eV) of *COOH formation at the interface of Ag nanoparticles and g-C3N4 compared to the g-C3N4 surface, leading to the superior photocatalytic performance, while the thermodynamically favored CO desorption contributes to the high CO selectivity. This work affords a novel strategy of constructing perovskite-based photocatalyst by modulating catalyst structure and provides in-depth insights for efficient CO2 conversion. © 2024, The Authors. All rights reserved.

关键词： Semiconductor quantum dots

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Locally Off-Centered Ge Atoms Contribute to High Thermoelectric Performance of Globally Averaged Cubic MnGeTe2 Alloys

SSRN

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SSRN 2024年

作者： Mei, Qicai Xie, Chenghao Cui, Jingjing Liao, Chengyun Li, Songlin Tang, Xinfeng Tan, Gangjian State Key Laboratory of Advanced Technology for Materials Synthesis and Processing Wuhan University of Technology Wuhan430070 China International School of Materials Science & Engineering Wuhan University of Technology Wuhan430070 China

Exploring high-performance and environment-benign thermoelectric materials free of phase change during their service is a long-standing challenge. Herein a maximum ZT of 1.4 at 878 K is reported for non-toxic Sb-doped MnGeTe2 alloys with a consistent cubic rock salt structure above room temperature. Pristine MnGeTe2 is a heavily self-doped p-type semiconductor with its hole density (pH) exceeding 1021 cm-3. Due to the strong contribution of localized 3d orbitals from Mn to the valence band maxima lying along the Γ–K direction with a high valley degeneracy of 4 , MnGeTe2 features a superb density of states (DOS) effective mass (m* ~ 10 me), endowing it a large Seebeck coefficient of ~105 μV K-1 at 300 K despite its over high pH. Moreover, Ge atoms are locally discordant in MnGeTe2 and displaced ∼0.33 Å off the octahedron center, inducing soft polar phonons that effectively scatter the heat carrying acoustic phonons and enable a low lattice thermal conductivity (κlat ~0.57 W m-1 K-1 at 871 K). Sb doping not only efficiently neutralizes the excess pH of MnGeTe2 leading to high Seebeck coefficient (> 250 μV K-1), but further drops κlat to ~0.49 W m-1 K-1 by reinforced point defect scattering. Our work highlights the significance of local off-centering atoms in developing high-performance bulk thermoelectric materials. © 2024, The Authors. All rights reserved.

关键词： Germanium alloys

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Simulations of monolayer SiC transistors with metallic 1T-phase MoS_(2) contact for high performance application

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Chinese Physics B 2021年第11期30卷 495-500页

作者： Hai-Qing Xie Dan Wu Xiao-Qing Deng Zhi-Qiang Fan Wu-Xing Zhou Chang-Qing Xiang Yue-Yang Liu Hunan Provincial Key Laboratory of Flexible Electronic Materials Genome Engineering School of Physics and Electronic ScienceChangsha University of Science and TechnologyChangsha 410114China School of Materials Science and Engineering&Hunan Provincial Key Laboratory of Advanced Materials for New Energy Storage and Conversion Hunan University of Science and TechnologyXiangtan 411201China College of Information Science and Engineering Jishou UniversityJishou 416000China State Key Laboratory for Superlattices and Microstructures Institute of SemiconductorsChinese Academy of SciencesBeijing 100083China

We preform a first-principles study of performance of 5 nm double-gated(DG)Schottky-barrier field effect transistors(SBFETs)based on two-dimensional SiC with monolayer or bilayer metallic 1T-phase MoS_(2) *** of the wide bandgap of SiC,the corresponding DG SBFETs can weaken the short channel *** calculated transfer characteristics also meet the standard of the high performance transistor summarized by international technology road-map for ***,the bilayer metallic 1T-phase MoS_(2) contacts in three stacking structures all can further raise the ON-state currents of DG SiC SBFETs in varying *** above results are helpful and instructive for design of short channel transistors in the future.

关键词： Schottky-barrier field effect transistor SiC band structure short channel effect

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Continuous-trajectory robust unit commitment considering beyond-the-resolution uncertainty

Continuous-trajectory robust unit commitment considering bey...

引用

2020 IEEE Power and Energy Society General Meeting, PESGM 2020

作者： Zhou, Bo Ai, Xiaomeng Fang, Jiakun Yao, Wei Wen, Jinyu Huazhong University of Science and Technology State Key Laboratory of Advanced Electromagnetic Engineering and Technology School of Electrical and Electronic Engineering Wuhan China

ISBN: (纸本)9781728155081

To guarantee the operational security of the renewable power system, the uncertainty of renewable energy generation (REG) should be fully considered. However, the traditional robust unit commitment (RUC) cannot access the variation of REG inside the operational period. Hence, this paper proposes the continuous-trajectory (CT) RUC considering the beyond-the-resolution (BtR) uncertainty. The critical impact factors characterizing the BtR variation are analyzed, and then the BtR uncertainty is modeled. The mathematical formulation of CT-RUC is derived and shifted from the time domain to the time-dependent function space so that the optimization can be tractably solved. The comparison between traditional RUC and CT-RUC demonstrates that the consideration of the BtR uncertainty can result in a more robust solution. © 2020 IEEE.

关键词： Trajectories

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An Improved Triple-Vector Modulated Model Predictive Control Method for Permanent Magnet Synchronous Motor

An Improved Triple-Vector Modulated Model Predictive Control...

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Workshop on Predictive Control of Electrical Drives and Power Electronics (PRECEDE)

作者： Dong Liu Wei Xu Han Xiao Pu Zhong Leilei Guo School of Electrical Engineering Zhengzhou Electric Power College Zhengzhou China State Key Laboratory of Advanced Electromagnetic Engineering and Technology Huazhong University of Science and Technology Wuhan China College of Electrical and Information Engineering Zhengzhou University of Light Industry Zhengzhou China State Grid Luohe Power Supply Company Luohe China

Model predictive control (MPC) has been widely used in motor control, and modulated model predictive control (MMPC) has been derived. However, in the conventional MMPC, the action time of the basic voltage vector is calculated by the inverse ratio of the cost function, which lacks a strictly theoretical basis. To enhance the theoretical basis of the MMPC, an improved triple-vector MMPC is proposed. First, two adjacent dual-vectors are synthesized by the conventional method. Then, the Helen’s formula and geometric relationship between the two dual-vectors are used to scale and synthesize the triple-vectors. Finally, the simulation verifies the effectiveness of the proposed method.

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