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Enhanced electrochemical performance of a LiFePO4 cathode with an environmentally friendly pectin/polyethylene glycol binder

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Journal of Power Sources 2024年 613卷

作者： Chen, Yan-Ruei Chen, Liang-Yu Chung, Chin-Yi Su, Yu-Hsuan Wu, Feng-Yu Hsu, Tsung-Ming Chi, Po-Wei Wu, Phillip M. Chang-Liao, Kuei-Shu Tang, Hong-Yi Wu, Maw-Kuen Institute of Physics Academia Sinica 128 Section 2 Academia Road Taipei11529 Taiwan Nano Science and Technology Program Taiwan International Graduate Program Academia Sinica and National Tsing Hua University 128 Section 2 Academia Road Taipei11529 Taiwan Department of Engineering and System Science National Tsing Hua University 101 Section 2 Kuang-Fu Road Hsinchu300044 Taiwan College of Science National Chung Hsing University 145 Xingda Road South District Taichung402 Taiwan Department of Applied Chemistry National Chi-Nan University 1 University Road Puli Nantou545301 Taiwan

The advancement of lithium-ion battery technology relies on the development of materials that not only improve performance but also align with environmental sustainability. This work presents a novel water-based pectin-PEG binder for LiFePO4 cathodes that combines eco-friendliness with electrochemical innovation. The binder material is made by mixing pectin, a flexible natural substance, with polyethylene glycol through a radical copolymerization process. This combination gives the binder both flexibility and a boost in electrical performance. Our experimental results demonstrate that LFP cathodes with this binder have an intriguing self-healing ability in comparison with the conventional PVDF binder, enhanced charge-discharge capacities, improved cycling stability, and higher ionic conductivity. Specifically, electrodes utilizing the pectin-PEG binder exhibit an impressive retention of discharge capacity. They maintain roughly 150 mAh g−1 after 500 cycles at 1C with 99% retention, and about 141 mAh g−1 with 97% retention at 3C. Cyclic voltammetry (CV) confirms that the PP binder maintains its ionic diffusion properties at high sweep rates, whereas galvanostatic intermittent titration technique reveals a much higher lithium ion diffusion coefficient (DLi+) within the operational voltage range of the LFP-PP250 electrodes. These findings establish an attractive direction for the development of electrodes for high-energy density, sustainable lithium-ion batteries. © 2024 Elsevier B.V.

关键词： Lithium compounds

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FetalNet: Low-light fetal echocardiography enhancement and dense convolutional network classifier for improving heart defect prediction

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Informatics in Medicine Unlocked 2022年 35卷

作者： Sutarno, Sutarno Nurmaini, Siti Partan, Radiyati Umi Sapitri, Ade Iriani Tutuko, Bambang Naufal Rachmatullah, Muhammad Darmawahyuni, Annisa Firdaus, Firdaus Bernolian, Nuswil Sulistiyo, Deny Intelligent System Research Group Faculty of Computer Science Universitas Sriwijaya Indonesia Doctoral Program Faculty of Engineering Universitas Sriwijaya Indonesia Faculty of Medicine Universitas Sriwijaya Indonesia Division of Fetomaternal Department of Obstetrics and Gynaecology Mohammad Hoesin General Hospital Indonesia

Background: Fetal heart defect (FHD) examination by ultrasound (US) is challenging because it involves low light, contrast, and brightness. Inadequate US images of fetal echocardiography play an important role in the failure to detect FHDs manually. The automatic interpretation of fetal echocardiography was proposed in a previous study. However, the low quality of US images reduces the prediction rate of computer-assisted diagnosis results. Methods: To increase the FHD prediction rate, we propose low-light fetal echocardiography enhancement stacking with a dense convolutional network classifier named “FetalNet.” Our proposed FetalNet model was developed using 460 US images to produce an image enhancement model. The results showed that all raw US images could be improved with satisfactory performance in terms of increasing the peak signal-to-noise ratio of 30.85 dB, a structural similarity index of 0.96, and a mean squared error of 18.16. Furthermore, all reconstructed images were used as inputs in a convolutional neural network to generate the best classifier for predicting FHD. Results: The proposed FetalNet model increased the FHD prediction rate by approximately 25% in terms of accuracy, sensitivity, and specificity and produced 100% predictive negative using unseen data. Conclusions: The proposed deep learning model has the potential to identify FHD accurately and shows potential for practical use in identifying congenital heart diseases in the future. © 2022 The Author(s)

关键词： Congenital heart disease Deep learning Low light image enhancement Ultrasound

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Generalization is not a universal guarantee: Estimating similarity to training data with an ensemble out-of-distribution metric

arXiv

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arXiv 2025年

作者： Schreyer, W. Max Anderson, Christopher Thompson, Reid F. Computational Biology Program Oregon Health & Science University PortlandOR United States Department of Biomedical Engineering Oregon Health & Science University PortlandOR United States Portland VA Research Foundation PortlandOR United States Department of Radiation Medicine Oregon Health & Science University PortlandOR United States Department of Medical Informatics and Clinical Epidemiology Oregon Health & Science University PortlandOR United States Division of Hospital and Specialty Medicine VA Portland Healthcare System PortlandOR United States

Failure of machine learning models to generalize to new data is a core problem limiting the reliability of AI systems, partly due to the lack of simple and robust methods for comparing new data to the original training dataset. We propose a standardized approach for assessing data similarity in a model-agnostic manner by constructing a supervised autoencoder for generalizability estimation (SAGE). We compare points in a low-dimensional embedded latent space, defining empirical probability measures for k-Nearest Neighbors (kNN) distance, reconstruction of inputs and task-based performance. As proof of concept for classification tasks, we use MNIST and CIFAR-10 to demonstrate how an ensemble output probability score can separate deformed images from a mixture of typical test examples, and how this SAGE score is robust to transformations of increasing severity. As further proof of concept, we extend this approach to a regression task using non-imaging data (UCI Abalone). In all cases, we show that out-of-the-box model performance increases after SAGE score filtering, even when applied to data from the model’s own training and test datasets. Our out-of-distribution scoring method can be introduced during several steps of model construction and assessment, leading to future improvements in responsible deep learning implementation. Copyright © 2025, The Authors. All rights reserved.

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Reconstructing suspended sediment concentrations in the Mekong River Basin via semi-supervised-based deep neural networks

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Science of the Total Environment 2024年 955卷 176758页

作者： Nguyen, Thi Thu Ha Vu, Duc Quang Doan, Ngoc Phu Chi, Huynh Thi Khanh Li, Peixin Binh, Doan Van An, Yimeng Dung, Pham Tuan Hoang, Tuan A. Son, Mai Thai Laboratory of Environmental Sciences and Climate Change Institute for Computational Science and Artificial Intelligence Van Lang University Ho Chi Minh City Viet Nam Faculty of Environment School of Technology Van Lang University Ho Chi Minh City Viet Nam Department of Computer Science and Information System Thai Nguyen University of Education Viet Nam School of Electronics Electrical Engineering and Computer Science Queen's University Belfast United Kingdom College of Economics and Management Nanjing University of Aeronautics and Astronautics China Master program in Water Technology Reuse and Management Faculty of Engineering Vietnamese-German University Binh Duong Province Ben Cat City Viet Nam

The Mekong River Basin (MRB) is crucial for the livelihoods of over 60 million people across six Southeast Asian countries. Understanding long-term sediment changes is crucial for management and contingency plans, but the sediment concentration data in the MRB are extremely sporadic, making analysis challenging. This study focuses on reconstructing long-term suspended sediment concentration (SSC) data using a novel semi-supervised machine learning (ML) model. The key idea of this approach is to exploit abundant available hydroclimate data to reduce training overfitting rather than solely relying on sediment concentration data, thus enhancing the accuracy of the employed ML models. Extensive experiments on daily hydroclimate and SSC data obtained from 1979 to 2019 at the three main stations (i.e., Chiang Saen, Nong Khai, and Mukdahan) are conducted to demonstrate the superior performance of the proposed method compared to the state-of-the-art supervised techniques (i.e., Random Forest, XGBoost, CatBoost, MLP, CNN, and LSTM), and surpasses existing semi-supervised methods (i.e., CoReg, ⊓ Model, ICT, and Mean Teacher). This approach is the first semi-supervised method to reconstruct sediment data in the field and has the potential for broader application in other river systems. © 2024 The Author(s)

关键词： Self-supervised learning

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Behavior of plane synthetic jets generated by an asymmetric stepped slot

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International Journal of Fluid Machinery and systems 2020年第1期13卷 253-265页

作者： Kobayashi, Ryota Terakado, Hiroaki Sato, Kotaro Taniguchi, Junya Nishibe, Koichi Yokota, Kazuhiko Mechanical Engineering Program in the Graduate School of Engineering Kogakuin University 1-24-2 Nishi-Shinjuku Shinjuku-ku Tokyo163-8677 Japan Mechanical Engineering Program in the Graduate School of Engineering Kogakuin University 1-24-2 Nishi-Shinjuku Shinjuku-ku Tokyo163-8677 Japan Department of Mechanical System Engineering Kogakuin University 1-24-2 Nishi-Shinjuku Shinjuku-ku Tokyo163-8677 Japan Graduate School of Integrative Science and Engineering Tokyo City University 1-28-1 Tamatsuzumi Setagaya-ku Tokyo158-8557 Japan Department of Mechanical Engineering Tokyo City University 1-28-1 Tamatsuzumi Setagaya-ku Tokyo158-8557 Japan Department of Mechanical Engineering Aoyama Gakuin University 5-10-1 Fuchinobe Sagamihara-shi Kanagawa252-5258 Japan

This paper presents a fundamental study of jet directional control, i.e., thrust vectoring, using a synthetic jet generated by an asymmetric stepped slot. We present and discuss the results for a synthetic jet generated by a one-sided asymmetric stepped slot and focus on the relationship between the traveling direction of the formed jet and the offset ratio of the stepped slot and/or dimensionless frequency of the synthetic jet, within a jet deflection angle range of 0–90°. We demonstrate that there is an optimum offset ratio for jet deflection under the same dimensionless frequency because the traveling direction of the synthetic jet is dependent on the offset ratio of the stepped slot and the dimensionless stroke length (dimensionless frequency). © 2020, Turbomachinery Society of Japan. All rights reserved.

关键词： Jets

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Blockchain Technology Based Credibility Verification in E-Journal Entities

Blockchain Technology Based Credibility Verification in E-Jo...

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Creative Communication and Innovative Technology (ICCIT), IEEE

作者： Sri Watini Zulkarnain Kedah Chandra Lukita Petrus Sokibi Gadis Mustika Reymund Rahardja Arsi Yulianjani Husni Teja Sukmana Early Childhood Teacher Education University of Panca Sakti Bekasi Bekasi Indonesia Vice Chancellor University of Malaysian Computer Science Selangor Malaysia Information System University of Catur Insan Cendekia Cirebon Indonesia Information System University of Raharja Tangerang Indonesia Digital Business University of Raharja Tangerang Indonesia Information Management Study Program University of Raharja Tangerang Indonesia Lecture of Information Engineering Syarif Hidayatullah Islamic University Jakarta Indonesia

In the industrial era 4.0, it has surpassed increasingly complex technological advances in the information system that required a very high infrastructure and facilities and prevented fraud. Counterfeiting is a procedure following an entity, statistics, or documents (observe forged documents) with plans to deceive. Falsification of extensive information certificates is exacerbated by the current economic situation in Indonesia, which is currently occurring due to the widespread epidemic, namely COVID-19. The spread of the COVID-19 outbreak has had a significant impact and changes in all sectors, especially certificate forgery in Indonesia. The imitation of busy certificates is the main focus of this journal, focusing on journal publications combined with Blockchain technology. The sophistication of blockchain technology as authentication is comparing two or more items or additional tests to ensure the accuracy, correctness, or correctness of the information. This method uses qualitative methods with data sources based on case studies in controlled supervision with the basic concept of cryptography as the basis of analysis. From the decisions made, it is hoped that this will minimize the level of forgery of certificates widely measured during the COVID-19 era.

关键词： COVID-19 Economics Epidemics Soft sensors Focusing Forgery Blockchains

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Doping Engineered InSe Flakes for High Mobility Phototransistor

Doping Engineered InSe Flakes for High Mobility Phototransis...

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Novel Optical Materials and Applications, NOMA 2020

作者： Inbaraj, Christy Roshini Paul Mathew, Roshan Jesus Sankar, Raman Lee, Chih-Hao Chen, Yang-Fang Department of Engineering and System Science National Tsing Hua University Hsinchu Taiwan Nano-Science and Technology Program Taiwan International Graduate Program Academia Sinica Taipei Taiwan Center for Condensed Matter Sciences National Taiwan University Taipei Taiwan Department of Physics National Taiwan University Taipei Taiwan

Sn doped InSe crystal has a reduced oxide phase and enhanced electron mobility. Along with the substrate modification, the mobility enhances to 2560 240 cm2 V-1s-1. Moreover, it exhibits a piezo-phototronic effect use... 详细信息

ISBN: (纸本)9781943580798

关键词： Indium compounds

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Effect of Ammonium Formate Addition on Corrosion Behavior of Trivalent Chromium Coatings Electrodeposited in Deep Eutectic Solvents

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International Journal of Electrochemical Science 2022年第7期17卷

作者： Sheu, Hung-Hua Lin, Tzu-Te Ger, Ming-Der Department of Chemical and Materials Engineering Chung Cheng Institute of Technology National Defense University Taoyuan Taiwan System Engineering and Technology Program National Yang Ming Chiao Tung University Hsin-Chu Taiwan Graduate School of National Defense Science Chung Cheng Institute of Technology National Defense University Taoyuan Taiwan

The Cr thin films were electrodeposited from trivalent chromium deep eutectic solvents. The conditions of deep eutectic solvents divided into without water (specimen C1), added 15 wt% water (specimen C2), added 15 wt% water with ammonium formate (specimen C3). The HR-TEM shows the structure of “C1” is amorphous structure, and both “C2” and “C3” belong to nano-crystalline structure. The best corrosion resistance of Cr thin film is “C3” which icorr value is approximately at 3.69×10^-7 A/cm², the worst corrosion resistance of Cr thin film is “C1” which icorr value is approximately at 3.05×10^-5 A/cm², it can be attributed to “C3” has a dense structure and “C1” has a loose structure. The EIS analysis also presents “C3” has the best corrosion resistance. The reason for the large difference in corrosion resistance can be attributed to the loose structure of the "C1" thin film and the gaps of film is perpendicular to substrate, the dense structure of the "C3" thin film can effectively protect the substrate. Moreover, the addition of ammonium formate into trivalent chromium deep eutectic solvents will promote the reduction reaction of Cr ions and form a dense film © 2022. The Authors. Published by ESG (***). This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://***/licenses/by/4.0/)

关键词： Ammonium formate Deep eutectic solvents Eis analysis

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Preparation of activated carbon derived from water hyacinth as electrode active material for li-ion supercapacitor 16th

Preparation of activated carbon derived from water hyacinth ...

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16th International Conference on Quality in Research, QiR 2019

作者： Paduraksa, Jagad Luthfi, Muhammad Verdianto, Ariono Subhan, Achmad Widayatno, Wahyu Bambang Prihandoko, Bambang Kartini, Evvy Hudaya, Chairul Department of Electrical Engineering Faculty of Engineering Universitas Indonesia Depok16424 Indonesia Energy System Engineering Study Program Faculty of Engineering Universitas Indonesia Depok16424 Indonesia Research Center for Physics Indonesian Institute of Sciences PUSPIPTEK SerpongTangerang Selatan15314 Indonesia Center for Science and Technology of Advanced Materials BATAN Kawasan Puspiptek Tangerang15314 Indonesia

ISBN: (纸本)9783035715996

Lithium-Ion Capacitor (LIC) has shown promising performance to meet the needs of high energy and power-density-energy storage system in the era of electric vehicles nowadays. The development of electrode materials and electrolytes in recent years has improvised LIC performance significantly. One of the active materials of LIC electrodes, activated carbon (AC), can be synthesized from various biomass, one of which is the water hyacinth. Its abundant availability and low utilization make the water hyacinth as a promising activated carbon source. To observe the most optimal physical properties of AC, this study also compares various activation temperatures. In this study, full cell LIC was fabricated using LTO based anode, and water hyacinth derived AC as the cathode. The LIC full cell was further characterized to see the material properties and electrochemical performance. Water hyacinth derived LIC can achieve a specific capacitance of 32.11 F/g, the specific energy of 17.83 Wh/kg, and a specific power of 160.53 W/kg. © 2020 Trans Tech Publications Ltd, Switzerland.

关键词： Activated carbon

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Development of high on/off current ratio in p-type copper oxide thin-film transistors with a back-end-of-line compatible process

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Journal of Vacuum Science and Technology A: Vacuum, Surfaces and Films 2024年第5期42卷

作者： Kuo, Chi-Yuan Lin, Wei-Chen Lo, Tsung-Tien Shen, Ching-Hsuan Shen, Ming-Yu Lee, Chia-Chan Lin, Chi-Ping Lin, Yuang-Ming Huang, Haw-Tyng Yeh, Po-Chun Chen, Hsin-Chu Wu, Chih-I Graduate Institute of Photonics and Optoelectronic Department of Electrical Engineering National Taiwan University Taipei106 Taiwan Program of Quantum Technology and Advanced Material College of Science National Tsing Hua University Hsinchu300 Taiwan Institute of Innovative Semiconductor Manufacturing National Sun Yat-sen University Kaohsiung804 Taiwan Institute of Advanced Semiconductor Packaging and Testing National Sun Yat-sen University Kaohsiung804 Taiwan Department of Materials Science and Engineering National Taiwan University Taipei106 Taiwan Electronic and Optoelectronic System Research Laboratories Industrial Technology Research Institute Hsinchu300 Taiwan

The objective of this study is to develop an efficient process to synthesize wafer scale p-type cuprous oxide (Cu2O) with the back-end-of-line (BEOL) compatible process (2/Si substrates followed by rapid thermal oxidation to oxidize it into large-area, uniform Cu2O. Bottom-gate Cu2O thin-film transistors (TFTs) were fabricated as gate dielectric on 100 nm thermal oxide. The results of the ID-VG curve demonstrate that we have successfully fabricated BEOL-compatible p-type Cu2O TFTs. The drain-off current can be achieved to 0.1 pA, with the highest on/off ratio reaching up to 6 orders. Significantly, the TFT with an on/off ratio of 106 is sufficient to meet the requirements for digital circuit applications, including logic circuits, and the BEOL-compatible process (2O TFTs. © 2024 Author(s).

关键词： Thin film transistors

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