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Liver microphysiological system for Drug-induced Liver Injury (DILI) Evaluation based on Kinetic-pump Integrated microfluidic Plate (KIM-Plate)

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IEEJ Transactions on Sensors and micromachines 2025年第3期145卷 46-52页

作者： Shinha, Kenta Nakamura, Hiroko Nishikawa, Masaki Sakai, Yasuyuki Kimura, Hiroshi Micro/Nano Technology Center Tokai University 4-1-1 Kitakaname Kanagawa Hiratsuka259-1292 Japan Department of Chemical System Engineering School of Engineering University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo113-8654 Japan

Prediction of the risk of developing Drug-induced liver injury (DILI) is very important in drug discovery. Although animal tests usually evaluate DILI, the prediction accuracy of DILI is low because experimental animals have different metabolic pathways from humans. A few microphysiological systems (MPS) have been developed as novel evaluation systems for DILI evaluation. However, the proposed system is not yet practical due to operability, throughput issues, and prediction accuracy. Our purpose is to develop a practical DILI evaluation system. In this study, we investigate the influence of perfusion culture on hepatotoxicity tests using our previously developed Kinetic pump integrated microfluidic plate (KIM-Plate). The results of acetaminophen toxicity tests showed that perfusion culture using KIM-Plate improved the detection sensitivity of hepatotoxicity. We suggest that the liver model MPS based on KIM-Plate could be a novel DILI evaluation system that integrates highly functional liver models and coculture with immune cells. © 2025 The Institute of Electrical Engineers of Japan.

关键词： Cell culture

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Nanoengineering silicon materials by metal-assisted chemical etching for thermal energy harvesting

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Materials Science in Semiconductor Processing 2025年 195卷

作者： Van Toan, Nguyen Tran, Ngoc Dang Khoa Kim Tuoi, Truong Thi Said, Suhana Mohd Mohd Sabri, Mohd Faizul Ono, Takahito of Engineering Tohoku University Japan Faculty of Mechanical Engineering Industrial University of Ho Chi Minh City Viet Nam Advanced Institute for Materials Research Tohoku University Japan Department of Electrical Engineering Faculty of Engineering Universiti Malaya Malaysia Department of Mechanical Engineering Faculty of Engineering Universiti Malaya Malaysia Micro System Integration Center Tohoku University Japan

Low-thermal heat waste energy harvesting represents a transformative technology for powering wireless sensing networks and electronic devices, particularly in remote and challenging environments. This review comprehensively examines the utilization of nanoporous silicon materials for thermal energy harvesting applications, focusing on their fabrication through metal-assisted chemical etching (MACE) and their unique properties that enhance energy conversion efficiency. The high surface area-to-volume ratio of nanoporous silicon significantly improves heat interaction and thermal-to-electrical energy conversion. We analyze the material properties and fabrication methods of nanoporous silicon, providing detailed evaluation of its performance in thermal energy harvesting applications. Experimental data demonstrates that nanoporous silicon achieves thermoelectric figures of merit (ZT) comparable to traditional materials while offering environmental and economic advantages. The review presents two innovative approaches for thermoelectric generators: solid-state configurations and ionic liquid implementations. Through systematic material evaluation and application demonstrations, we establish nanoporous silicon as an efficient and environmentally friendly solution for thermal energy harvesting. Our findings indicate that nanoporous silicon not only addresses the limitations of conventional thermoelectric materials but also provides a scalable and sustainable approach for enhancing energy harvesting system performance. This research contributes to advancing sustainable energy technologies and improving the viability of wireless sensing networks across various environmental conditions. © 2025 Elsevier Ltd

关键词： Energy conversion efficiency

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Data-driven approach for optimizing the Czochralski process and predictive modeling: A finite element and machine learning analysis

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The International Journal of Advanced Manufacturing Technology 2025年 1-11页

作者： Maurya, Swami Nath Dezfoli, Amir Reza Ansari Lin, Li-Shang Department of Intelligent Automation Engineering National Chin-Yi University of Technology Taichung Taiwan Graduate Institute of Precision Manufacturing National Chin-Yi University of Technology Taichung Taiwan Micro Precision System Research & Development Section Metal Industries Research & Development Centre Kaohsiung Taiwan

The ever-growing demand for semiconductors, fueled by advancements in integrated circuits (ICs), necessitates innovative approaches for efficient and high-quality growth of large-scale silicon single crystals using the Czochralski (CZ) method. In this context, machine learning emerges as a transformative tool to predict and optimize the complex, nonlinear CZ silicon growth process. A novel hybrid finite element method–machine learning (FEM-ML) model is proposed to enhance the accuracy of thermal stress predictions. The FEM simulation, incorporating 3D Navier–Stokes and thermal elastic stress equations, was used to evaluate the effects of four key process features: insulation thermal conductivity (0.184–0.736 W/m·K), melt level (448–672 mm), crucible rotation speed (1–7.5 rpm), and crystal rotation speed (7.5–12.5 rpm). Then, machine learning analyses including LASSO regression for feature selection and regression decision trees for predictive modeling, achieving a high coefficient of determination (R2 > 0.97) through tenfold cross-validation is employed. Results identified insulation thermal conductivity as the most significant factor, accounting for 75.4% of predictive performance, while melt level had negligible impact. Individual Conditional Expectation (ICE) results highlighted non-linear dependencies, such as the sharp increase in thermal stress with crucible rotation speeds up to 2.4 rpm. The hybrid model demonstrated superior performance in capturing key parameter interactions and predicting thermal stress distributions. This work underscores the potential of hybrid FEM-ML approaches for addressing complex industrial challenges in crystal growth.

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Neural-LAFC: A Neural Learning Adaptive Flight Controller for Tailless Flapping-Wing Robots Under Uncertain Wind Disturbance Conditions

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IEEE Transactions on Aerospace and Electronic systems 2025年

作者： Guo, Qingcheng Zhang, Yichen Mou, Jiawang Liu, Wu Wu, Xiaosheng Lu, Jun-Guo Shanghai Jiao Tong University Department of Automation China Key Laboratory of System Control and Information Processing Ministry of Education of China China National Key Laboratory of Advanced Micro and Nano Manufacture Technology Shanghai200240 China Shanghai Jiao Tong University National Key Laboratory of Advanced Micro and Nano Manufacture Technology China Shanghai Jiao Tong University Department of Micro/Nano Electronics School of Electronic Information and Electrical Engineering Shanghai200240 China Designing Institute of Hubei Space Technology Academy Wuhan China Ministry of Education of China Key Laboratory of System Control and Information Processing Shanghai200240 China

Enabling bio-inspired flapping-wing robots (FWRs) to maintain stable flight in windy environments, similar to real flying creatures, is of significant importance. In this work, a neural learning-based adaptive flight controller (Neural-LAFC) is proposed for the attitude and position control of a tailless FWR under uncertain wind conditions. The key approach involves employing a deep neural network (DNN) that incorporates not only attitude information but also instantaneous flapping angles of the wings to learn the aerodynamic torques that cannot be accurately modeled. The training data are obtained from flight experiments conducted with the FWR in a wind tunnel environment. Subsequently, a composite adaptive law is presented to update a set of linear coefficients. These linear coefficients are utilized to blend the pre-trained basis functions to represent the aerodynamic torques. The tracking errors are shown to exponentially converge to a bounded region, as guaranteed by a Lyapunov function. Based on the learning-based attitude controller, we also develop an adaptive controller for position control. Notably, apart from the training phase, the FWR operates without prior knowledge of wind speed. Experimental results demonstrate that the Neural-LAFC successfully achieves the desired attitude stabilization, target point tracking, and path tracking of the FWR in windy conditions. The proposed control scheme also outperforms baseline controllers in wind disturbance suppression, reducing the root mean square position errors by more than 40% when the FWR is subjected to a horizontal wind within the speed of 180 {cm s{-1}}. © 1965-2011 IEEE.

关键词： Wind tunnels

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RTN Analysis of Schottky p-GaN Gate HEMTs Under Forward Gate Stress: Impact of Temperature

RTN Analysis of Schottky p-GaN Gate HEMTs Under Forward Gate...

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Annual International Symposium on Reliability Physics

作者： M. Millesimo L. Valentini C. Fiegna E. Sangiorgi A.N. Tallarico M. Borga N. Posthuma S. Decoutere B. Bakeroot Department of Electrical Electronic and Information Engineering Advanced Research Center on Electronic System “Guglielmo Marconi” University of Bologna Campus of Cesena Cesena Italy imec - interuniversitair micro electronica centrum Heverlee Belgium Centre for Microsystems Technology imec and Ghent University Ghent Belgium

ISBN: (数字)9798331504779

ISBN: (纸本)9798331504786

This study presents a comprehensive analysis of random telegraph noise (RTN) to evaluate the impact of forward gate bias (VGS) and temperature (T) on defects creation and activation in the gate epi-stack of GaN-based Schottky p-GaN gate HEMTs. Results reveal three RTN components in the fresh device currents at elevated temperatures (90 °C to 150 °C), attributed to pre-existing defects within the AlGaN barrier, influencing both the gate leakage and the drain current. Temperature-dependent RTN analysis is used to extract the activation energies of these traps. Conversely, no RTN components are observed in fresh device currents at lower temperatures (≤70 °C), highlighting the role of thermal excitation in defects activation. Under forward gate stress, four additional RTN components emerge, suggesting new traps formation. Findings highlight the combined roles of temperature and VGS in activating pre-existing defects and inducing new ones within the gate epi-stack of Schottky p-GaN gate HEMTs.

关键词： Noise Logic gates HEMTs Threshold voltage Wide band gap semiconductors Object recognition MODFETs Stress Aluminum gallium nitride Physics

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Ultra-Sensitive Detection of Dopamine Using Oxygen Plasma-Treated Ti3c2tx-Modified Carbon Electrodes: Dft and Experimental Investigations

SSRN

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SSRN 2025年

作者： Wang, Jing Zhao, Long Su, Jing Du, Haiying Shao, Qiang Wang, Liding Dalian Minzu University College of Mechanical and Electronic Engineering Dalian116600 China Dalian University of Technology Key Laboratory for Micro/Nano Technology and System of Liaoning Province Dalian116085 China The Second Affiliated Hospital of Dalian Medical University Department of Neurosurgery Epilepsy Center Dalian116021 China

Dopamine (DA) is closely associated with neurological disorders such as Parkinson’s disease and schizophrenia. Accurate and ultra-sensitive detection of DA is crucial for early diagnosis and treatment of these diseases. In this study, a novel electrochemical sensor for DA detection based on monolayer Ti3C2Tx Mxene material treated with oxygen plasma was developed. The oxygen plasma treatment significantly enhanced the surface activity and electronic transport capabilities of Ti3C2Tx, enabling the sensor to achieve an ultra-low detection limit of 0.005 nM for DA. Electrochemical tests demonstrated the sensor's excellent sensitivity, detection limit, and stability. To study the sensitive mechanism of enhanced electrochemical performance, density functional theory (DFT) was employed to study the interaction between DA molecules and the oxygen-functionalized Ti3C2Tx surface. Theoretical studies revealed that oxygen plasma treatment introduced abundant active sites and optimized the electronic properties of Ti3C2Tx, thereby facilitating efficient charge transfer and enhancing the adsorption capacity for DA molecules. This research highlights the great potential of oxygen plasma-treated Ti3C2Tx as a high-performance electrochemical sensing material and provides new insights for developing biosensors. © 2025, The Authors. All rights reserved.

关键词： Neurodegenerative diseases

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Ultra-Sensitive Detection of Dopamine Using Oxygen Plasma-Treated Ti3c2tx-Modified Carbon Electrodes: Dft and Experimental Investigations

SSRN

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SSRN 2025年

Dopamine (DA) plays a key role in various neurological disorders, including Parkinson’s disease and schizophrenia. Accurate and ultra-sensitive detection of DA is crucial for early diagnosis and treatment of these diseases. In this study, a novel electrochemical sensor for DA detection based on monolayer Ti3C2Tx Mxene material treated with oxygen plasma was developed. The oxygen plasma treatment significantly enhanced the surface activity and electronic transport capabilities of Ti3C2Tx, enabling the sensor to achieve an ultra-low detection limit of 0.005 nM for DA. Electrochemical tests demonstrated the sensor's excellent sensitivity, detection limit, and stability. To study the sensitive mechanism of enhanced electrochemical performance, density functional theory (DFT) was used to investigate the interaction between DA molecules and the oxygen-functionalized Ti3C2Tx surface. Theoretical studies revealed that oxygen plasma treatment significantly increased the number of active sites and enhanced the electronic properties of Ti3C2Tx, thereby enhancing the adsorption capacity for DA molecules and facilitating efficient charge transfer. This research highlights the great potential of oxygen plasma-treated Ti3C2Tx as a high-performance electrochemical sensing material and provides new insights for developing biosensors. © 2025, The Authors. All rights reserved.

关键词： Neurodegenerative diseases

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Efficient Red Sn-Based Perovskite Light Emitting Diodes by A Competitive Antioxidation Strategy

IEEE Electron Device Letters

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IEEE Electron Device Letters 2025年

作者： Gong, Yingqun Shi, Yuxin Huo, Sitao Wang, Lin Zhang, Xiaofei Kong, Lingmei Wang, Sheng Yang, Yingguo Yang, Xuyong Shanghai University Key Laboratory of Advanced Display and System Application Ministry of Education Shanghai200072 China Seoul National University Department of Materials Science and Engineering Seoul08826 Korea Republic of Shanghai Tianma Micro-Electronics Co. Ltd China Zhangjiang Lab Shanghai Advanced Research Institute Shanghai China Fudan University School of Microelectronics Shanghai China

Tin (Sn)-based perovskite light-emitting diodes (PeLEDs) have emerged as a promising candidate for next-generation displays because of their eco-friendliness, exceptional optoelectronic properties, and cost-effective solution processability. However, their electroluminescence performance still lags behind their lead (Pb) counterparts, primarily due to the undesired Sn2+ oxidation to Sn4+ and the rapid crystallization of Sn-based perovskite, resulting in high defect density as well as poor film quality. Herein, we reported a competitive antioxidation strategy by utilizing a phosphorus ylide, namely (triphenylphosphoranilidene) acetaldehyde (TPPA), to suppress the oxidation of Sn2+ and regulate the growth kinetics, simultaneously. The TPPA with highly active polar phosphorus-carbon bonds can be oxidized prior to Sn2+, and their large steric hindrance can slow down the crystallization process of tin-based perovskite. Moreover, the main product from the oxidation reaction, namely triphenylphosphine oxide (TPPO), can further passivate defects by coordinating with SnI6 octahedra. The resulting Sn-based perovskite film exhibits enhanced optical properties and uniform, dense morphology. Leveraging these improvements, the optimized PeLED delivers pure-red light emission with Commission Internationale de L'Eclairage (CIE) color coordinates of (0.69, 0.30), an external quantum efficiency (EQE) of 8.1% and maximum luminance of 672 cd m-2. This work provides a facile route to enhance the overall performance of Sn-based PeLEDs. © 1980-2012 IEEE.

关键词： Perovskite

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PERFORMANCE IMPROVEMENT OF OPTICAL ACTUATOR BY DOUBLE SIDE IRRADIATION

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IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS 1995年第5期42卷 455-461页

作者： FUKUDA, T HATTORI, S ARAI, F NAKAMURA, H Mechanical Engineering Department University of Nagoya Nagoya Japan Department of Micro System Engineering University of Nagoya Nagoya Japan

This study is intended to improve the photoresponse of an optical actuator with a bimorph PLZT element. Known optical actuators have multiple merits for converting light energy to driving energy but have a slow response speed and large hysteresis. A method developed by us for exposing both sides of the bimorph element to light has been proved through a series of experiments that the response speed is increased and the hysteresis is reduced thus improving the photoresponse. More particularly, an optical servo system was fabricated for implementing the method and subjected to optical servo tests with PI control. As a result, the PI control was performed with much ease when both sides of the bimorph PLZT were irradiated indicating an advantage of the method.

关键词： Actuators Servomechanisms Nonlinear optics Optical noise Crystalline materials Dielectric materials Ceramics Optical materials Legged locomotion Hysteresis

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Dynamical reconfiguration method of cellular robotic system based on distance evaluation

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ROBOTICS AND AUTONOMOUS systemS 1996年第1期19卷 105-111页

作者： Ishihara, H Fukuda, T Nagoya University Department of Micro System Engineering Furo-cho Chikusa-ku Nagoya Japan

In this paper, we propose an algorithm of cell configuration based on distance estimation. In cellular robotic system (CEBOT) which has been proposed as a kind of distributed robotic system, cell, which is a robot constructing group robots, executes a task by constructing formation by connecting and detaching with other cells. Therefore, formation and configuration of cells play a very important role in CEBOT.

关键词： Industrial robots

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