Zobrazeno 1 - 10
of 1 677
pro vyhledávání: '"Wang XiaoXu"'
Autor:
Zeng, Boshen, Chen, Sian, Liu, Xinxin, Chen, Changhong, Deng, Bin, Wang, Xiaoxu, Gao, Zhifeng, Zhang, Yuzhi, E, Weinan, Zhang, Linfeng
Advancements in lithium battery technology heavily rely on the design and engineering of electrolytes. However, current schemes for molecular design and recipe optimization of electrolytes lack an effective computational-experimental closed loop and
Externí odkaz:
http://arxiv.org/abs/2407.06152
Autor:
Wang, Ruoyu, Guo, Mingyu, Gao, Yuxiang, Wang, Xiaoxu, Zhang, Yuzhi, Deng, Bin, Chen, Xin, Shi, Mengchao, Zhang, Linfeng, Zhong, Zhicheng
Solid electrolytes with fast ion transport are one of the key challenges for solid state lithium metal batteries. To improve ion conductivity, chemical doping has been the most effective strategy, and atomistic simulation with machine-learning potent
Externí odkaz:
http://arxiv.org/abs/2406.18263
Autor:
Hu, Taiping, Huang, Haichao, Zhou, Guobing, Wang, Xinyan, Zhu, Jiaxin, Cheng, Zheng, Fu, Fangjia, Wang, Xiaoxu, Dai, Fuzhi, Yu, Kuang, Xu, Shenzhen
Uncontrollable dendrites growth during electrochemical cycles leads to low Coulombic efficiency and critical safety issues in Li metal batteries. Hence, a comprehensive understanding of the dendrite formation mechanism is essential for further enhanc
Externí odkaz:
http://arxiv.org/abs/2406.14025
Bundle recommendations strive to offer users a set of items as a package named bundle, enhancing convenience and contributing to the seller's revenue. While previous approaches have demonstrated notable performance, we argue that they may compromise
Externí odkaz:
http://arxiv.org/abs/2312.11018
Autor:
Song, Meiyue, Yu, Zhihua, Wang, Jiaxin, Wang, Jiarui, Lu, Yuting, Li, Baicun, Wang, Xiaoxu, Huang, Qinghua, Li, Zhijun, Kanellakis, Nikolaos I., Liu, Jiangfeng, Wang, Jing, Wang, Binglu, Yang, Juntao
The conventional pretraining-and-finetuning paradigm, while effective for common diseases with ample data, faces challenges in diagnosing data-scarce occupational diseases like pneumoconiosis. Recently, large language models (LLMs) have exhibits unpr
Externí odkaz:
http://arxiv.org/abs/2312.03490
The optimality of Bayesian filtering relies on the completeness of prior models, while deep learning holds a distinct advantage in learning models from offline data. Nevertheless, the current fusion of these two methodologies remains largely ad hoc,
Externí odkaz:
http://arxiv.org/abs/2310.17187
Autor:
Hu, Taiping, Yang, Teng, Liu, Jianchuan, Deng, Bin, Huang, Zhengtao, Wang, Xiaoxu, Dai, Fuzhi, Zhou, Guobing, Fu, Fangjia, Tuo, Ping, Xu, Ben, Xu, Shenzhen
Owing to the trade-off between the accuracy and efficiency, machine-learning-potentials (MLPs) have been widely applied in the battery materials science, enabling atomic-level dynamics description for various critical processes. However, the challeng
Externí odkaz:
http://arxiv.org/abs/2309.01146
Autor:
Lu, Yuting, Min, Lingtong, Wang, Binglu, Zheng, Le, Wang, Xiaoxu, Zhao, Yongqiang, Long, Teng
Remote sensing image super-resolution (RSISR) plays a vital role in enhancing spatial detials and improving the quality of satellite imagery. Recently, Transformer-based models have shown competitive performance in RSISR. To mitigate the quadratic co
Externí odkaz:
http://arxiv.org/abs/2307.02974
Accurate prediction for the electronic structure properties of halide perovskites plays a significant role in the design of highly efficient and stable solar cells. While density functional theory (DFT) within the generalized gradient approximation (
Externí odkaz:
http://arxiv.org/abs/2306.14486
In hybrid perovskites, the organic molecules and inorganic frameworks exhibit distinct static and dynamic characteristics. Their coupling will lead to unprecedented phenomena, which have attracted wide research interests. In this paper, we employed D
Externí odkaz:
http://arxiv.org/abs/2209.12445