Coupling Mechanism of Electrical Double Layer and Mass Transport for Bubble Nucleation at Electrode Interfaces by Jiaxuan HU, Changqing GUO, Zhida WANG, Yan SHI, Lisha SHEN, Hongyu HUANG, Changfeng YAN

“…During the process of water electrolysis,the "bubble effect" will significantly reduce the overall performance of the system.The classical nucleation theory (CNT model） fails to reveal the regulatory mechanism of the electrical double layer (EDL),surface microstructure,and mass transfer synergy on nucleation kinetics in actual electrochemical systems.This study develops an electrode interface bubble nucleation model with the synergistic effect of electrical double layer⁃mass transfer⁃surface microstructure,considering the synergistic regulation mechanism of ion migration diffusion behavior,electrode surface nano microstructure,and concentration boundary layer on the nucleation process.The research results show that the synergistic effect of EDL and microporous structurel generates significant potential gradients at the surface micropores,leading to an increase in local supersaturation and prioritizing bubble nucleation.At high overpotentials,the effect of the concentration boundary layer on nucleation energy barrier exhibits a nonlinear relationship.The thinner the concentration boundary layer is,the more significant the decreasing trend of the nucleation rate at high potential will be.The growth of bubbles is dominated by the net concentration flux near the three⁃phase contact line (TPCL),exhibiting a two⁃stage growth characteristic.The study provides a theoretical basis for optimizing the surface design of gas evolution electrodes.…”
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Effect of biochar application on the mobility of the textile dye drimaren red in an alluvial soil layer by Josielly Braz da Silva, Severino Martins dos Santos Neto, Luan Alves Furtado, Antonio Celso Dantas Antonino, Artur Paiva Coutinho

“…Kinetic data best fit the pseudo-second-order model, and intra-particle diffusion was not the determining mass transfer process nor the occurrence of the adsorption process. …”
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Turbo detection-decoding method for bit-interleavered random layered space-time codes by LI Xiao-wei, CHEN Fang-jiong, WEI Gang

“…Based on one kind of layered space-time code which used bit-interleavered and random-layered model,a joint detection-decoding method based on the Turbo principle was proposed.The new method used soft-interference canceller and SISO decoder and improved the exchange of soft information between them.By iterative procession it improved the performance of the whole system.The potential practice capability is proved by simulation results and computational complexity analysis.…”
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Turbo detection-decoding method for bit-interleavered random layered space-time codes by LI Xiao-wei, CHEN Fang-jiong, WEI Gang

“…Based on one kind of layered space-time code which used bit-interleavered and random-layered model,a joint detection-decoding method based on the Turbo principle was proposed.The new method used soft-interference canceller and SISO decoder and improved the exchange of soft information between them.By iterative procession it improved the performance of the whole system.The potential practice capability is proved by simulation results and computational complexity analysis.…”
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The High Performance of Multi-Metal Layered Double Hydroxides (LDHs) in the Removal of Organic Dyes by Soumaya Talbi, Amal El Khanchaoui, Latifa Bouissane, Abderrafia Hafid, Mostafa Khouili, Souad Rabi, Abdellatif Essoumhi

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Large eddy simulation of near-surface boundary layer dynamics over patchy snow by Michael Haugeneder, Michael Haugeneder, Michael Lehning, Michael Lehning, Océane Hames, Océane Hames, Mahdi Jafari, Dylan Reynolds, Dylan Reynolds, Rebecca Mott

“…The near-surface boundary layer over patchy snow is highly heterogeneous and dynamic. …”
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Layer‐Level Adaptive Gradient Perturbation Protecting Deep Learning Based on Differential Privacy by Zhang Xiangfei, Zhang Qingchen, Jiang Liming

“…However, classic differentially private learning introduces the same level of noise into the gradients across training iterations, which affects the trade‐off between model utility and privacy guarantees. To address this issue, an adaptive differential privacy mechanism was proposed in this paper, which dynamically adjusts the privacy budget at the layer‐level as training progresses to resist member inference attacks. …”
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Machine Learning-Based 3D Soil Layer Reconstruction in Foundation Pit Engineering by Chenxi Zhang, Nan Li, Xiuping Dong, Bin Liu, Meilian Liu

“…First, various types of borehole and soil layer data are generated by simulating the formation process of Earth’s soil layers, thereby providing sufficient training data. …”
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Layered energy equalization structure for series battery pack based on multiple optimal matching by Jianfang Jiao, Hongwei Wang, Feng Gao, Serdar Coskun, Guang Wang, Jiale Xie, Fei Feng

“…Firstly, to achieve energy equalization under complex conditions, a two-layer equalization circuit topology is designed, and the efficiency and loss of energy transfer in the equalization process are studied. …”
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Vehicle detection method based on multi-layer selective feature for UAV aerial images by Yinbao Ma, Yuyu Meng, Jiuyuan Huo

“…To address these issues, a lightweight vehicle detection model is developed based on UAV aerial imagery. In the backbone, a Receptive-Field Attention Convolution (RFAConv) module is introduced to retain detailed features during the downsampling process. …”
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Forensic Characterization of Gel Pen Inks with Thin Layer Chromatography and Ultraviolet Spectroscopy Technique by Harjot Kaur, Tina Sharma, Archana Gautam, Vaibhav Mishra

“…Background: Using a comprehensive approach that combines Thin Layer Chromatography (TLC), UV-visible spectroscopy, and Adobe Photoshop image manipulation, this study aims to authenticate and identify Gen gel pens. …”
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High‐frequency gravity waves and homogeneous ice nucleation in tropical tropopause layer cirrus by Eric J. Jensen, Rei Ueyama, Leonhard Pfister, Theopaul V. Bui, M. Joan Alexander, Aurélien Podglajen, Albert Hertzog, Sarah Woods, R. Paul Lawson, Ji‐Eun Kim, Mark R. Schoeberl

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Molecular dynamics simulation and analysis of pre-crystallization layer between liquid and solid states by Pavel V. Chirkov, Vladimir V. Dremov, Roman M. Kichigin, Alexey V. Karavaev, Filipp A. Sapozhnikov, Elena B. Cherepetskaya, Vladimir S. Dub, Ivan A. Ivanov, Sergey V. Salikhov

“…The simulations were carried out for model Fe–Ni–Cr alloy that is crystallized into face centered cubic lattice. …”
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Understanding the impact of the gas diffusion layer structure on catalyst utilization in the PEM water electrolyzer by Yuyao Huang, Samuel Williams, Tae Wook Heo, Aaron Marshall, Brandon Wood, John Kennedy, James Metson, Meng Wai Woo, Jingjing Liu

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The influence of firn layer material properties on surface crevasse propagation in glaciers and ice shelves by T. Clayton, R. Duddu, R. Duddu, T. Hageman, E. Martínez-Pañeda, E. Martínez-Pañeda

“…Thus, our study shows that the firn layer can increase the vulnerability of ice shelves to fracture and calving, highlighting the importance of considering depth-dependent firn layer material properties in LEFM models for estimating crevasse penetration depths and predicting rift propagation.…”
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Effects of Driving Current Ripple Fluctuations on the Liquefied Layer of the Armature–Rail Interface in Railguns by Wen Tian, Gongwei Wang, Ying Zhao, Weikang Zhao, Weiqun Yuan, Ping Yan

“…Consequently, it is imperative to conduct an in-depth analysis of the influence of current ripple on the liquefied layer during electromagnetic launching. In this paper, a thermoelastic magnetohydrodynamic model is constructed by coupling temperature, stress, and electromagnetic fields, which are predicated on the Reynolds equation of the metal liquefied layer at the armature–rail contact interface. …”
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An approach for fault-related monitoring variables selection based on dual-layer correlation networks by Zhenjie Zhang, Xinjiu Chen, Xiaobin Xu, Yi Li, Pingzhi Hou, Zehui Zhang, Haohao Guo

“…Purpose – Fault-related monitoring variables selection is a process of obtaining a subset of variables from the original set, which is of great significance for reducing information redundancy and improving the performance of the fault diagnosis models. …”
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Surface Layer Turbulent Characteristics over the Complex Terrain of the Loess Plateau Semiarid Region by Zhida Zhang, Jiening Liang, Min Zhang, Qi Guo, Lei Zhang

“…Surface layer turbulence has an important influence on land-air interactions and pollutant dispersion, and studying the characteristics of surface layer turbulence in complex terrain can contribute to understanding land-air interactions, improving model surface layer parameterization, and enhancing pollution prediction capabilities. …”
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Correlations between the Crustal Field and the Magnetization Layer’s Geometry in the Martian Magnetic Lineation Area by Jipeng Qin, Can Huang, Hao Luo, Yasong Ge, Lin Tian, Kuixiang Zhang, Lei Wang, Ying Zhang, Lican Shan, Aimin Du

“…However, a missing link remains between the magnetization layer’s geometry, controlled by these processes, and the scale and magnitude of magnetic signals in the satellite orbit. …”
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Expert System for Detection of Diseases in Layers Using Forward Chaining and Certainty Factor Methods by Kevin Febrianto, Erika Devi Udayanti, Bonifacius Vicky Indriyono, Wildan Mahmud, Iqlima Zahari

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