Article
Chemistry, Analytical
Meng Yan, Yi Wu, Zhongqiu Hua, Ning Lu, Wentao Sun, Jinbao Zhang, Shurui Fan
Summary: A compensation model for humidity in Metal oxide semiconductor sensors was proposed for detecting volatile organic compounds vapor. Water vapor was considered a reactant in the response, and a power law model was introduced. The model showed good verification in experimental systems and could be applied to electronic noses for improved recognition results.
SENSORS AND ACTUATORS B-CHEMICAL
(2021)
Article
Chemistry, Physical
I-Kai Cheng, Chun-Yu Lin, Fu-Ming Pan
Summary: The sensing reaction mechanism of ZnO towards H-2 was investigated, showing distinct response features at temperatures above 150 degrees C. Humidity affects sensor performance, while Pt decoration greatly improves sensor performance in both dry and humid environments. This improvement is attributed to hydrogen spillover from Pt nanoparticles to the ZnO support.
APPLIED SURFACE SCIENCE
(2021)
Article
Chemistry, Multidisciplinary
Alberto Rubin Pedrazzo, Andrea Jouve, Sara Morandi, Maela Manzoli, Claudio Cecone, Pierangiola Bracco, Marco Zanetti
Summary: Metal oxide-based semiconductors (MOS) are promising materials for sensors due to their high efficiency, fast response, stability, simple preparation, and low cost. In this study, a new synthetic route of nanosized MOS was proposed using a solvent-free approach based on the kneading of metal precursors and cyclodextrins (CDs). The resulting metal oxide nanoparticles were characterized and the influence of CD size on the final oxide properties was observed.
ACS SUSTAINABLE CHEMISTRY & ENGINEERING
(2022)
Article
Nanoscience & Nanotechnology
Matteo Farronato, Margherita Melegari, Saverio Ricci, Shahin Hashemkhani, Alessandro Bricalli, Daniele Ielmini
Summary: This article presents a three-terminal memtransistor device based on 2D semiconductors, which combines transistor behavior with resistive switching memory operation. The volatile switching behavior is explained by Ag cation migration. The researchers also demonstrate a chain-type memory array architecture similar to a NAND flash structure, paving the way for high-density 3D memories based on 2D semiconductors.
ADVANCED ELECTRONIC MATERIALS
(2022)
Article
Engineering, Environmental
Jin-Young Kim, Somalapura Prakasha Bharath, Ali Mirzaei, Hyoun Woo Kim, Sang Sub Kim
Summary: This study addresses the cross-sensitivity issue of metal oxide sensors by using a sensor array and machine learning techniques. The sensors built with In2O3, Au-ZnO, Au-SnO2, and Pt-SnO2 were operated simultaneously with different concentrations of NO2, CO, and their mixtures. By conducting experiments at different humidity levels, the researchers trained deep neural network-based models using principal component analysis and achieved an accuracy of 100% in classification using a convolutional neural network. This approach eliminates the time-consuming feature extraction process.
JOURNAL OF HAZARDOUS MATERIALS
(2023)
Review
Chemistry, Physical
Hongyu Liu, Gang Meng, Zanhong Deng, Meng Li, Junqing Chang, Tiantian Dai, Xiaodong Fang
Summary: Metal oxide semiconductor (MOS) gas sensors have been widely used in various industries due to their small size, low power consumption, high sensitivity, and good silicon chip compatibility. However, the poor selectivity of MOS sensors has limited their potential application in the Internet of Things (IoT) era. This paper reviews the progress in addressing the selectivity issues of MOS sensors and introduces three strategies for selective MOS sensors and performance improvements.
ACTA PHYSICO-CHIMICA SINICA
(2022)
Article
Engineering, Electrical & Electronic
Tong Jin, Yuting Liu, Yan Xiong, Jincong Pang, Haodi Wu, Shunsheng Yuan, Ling Xu, Zhiping Zheng, Jiang Tang, Guangda Niu
Summary: This study presents a method to enhance the high-voltage stability of CsPbBr3 single crystals by surface polishing, passivation, and using a carbon electrode. These measures effectively reduce leakage current amplification and stability reduction, while improving the radiation detection capability of the device.
IEEE ELECTRON DEVICE LETTERS
(2023)
Article
Computer Science, Information Systems
Ya-Wen Ho, Tejender Singh Rawat, Zheng-Kai Yang, Sparsh Pratik, Guan-Wen Lai, Yen-Liang Tu, Albert Lin
Summary: Artificial neural networks and multilayer perceptrons are efficient in designing semiconductor device models, but require a large number of parameters and longer simulation time. Optimizing network architecture for better learning is important yet tedious. Neuro-evolution method can achieve lower RMSE and faster convergence for semiconductor device compact models compared to traditional MLP models.
Article
Chemistry, Physical
Navneet Bhardwaj, Bhanu B. Upadhyay, Yogendra K. Yadav, Sreenadh Surapaneni, Swaroop Ganguly, Dipankar Saha
Summary: In this study, 10 nm of amorphous Nb2O5 was successfully grown on an AlGaN/GaN heterostructure, with ideal stoichiometry and a band gap of 4.15 eV determined by XPS analysis. Additionally, TEM confirmed the thickness and crystallinity of the oxide, while AFM measured a RMS roughness of 1.32 nm. The capacitive behavior of Nb2O5 and its interface characteristics with AlGaN were estimated by CV characteristics.
APPLIED SURFACE SCIENCE
(2022)
Review
Chemistry, Multidisciplinary
Andreas Pfenning, Sebastian Krueger, Fauzia Jabeen, Lukas Worschech, Fabian Hartmann, Sven Hoefling
Summary: Optical quantum information science and technologies require the ability to generate, control, and detect single or multiple quanta of light. Superconducting nanowire single-photon detectors and single-photon avalanche diodes are currently the top performers in this field, but other promising devices are emerging. This review article focuses on a specific alternative single-photon detector - the resonant tunneling diode - and discusses its advantages, limitations, and potential improvements.
Review
Engineering, Electrical & Electronic
Hongfeng Chai, Zichen Zheng, Kewei Liu, Jinyong Xu, Kaidi Wu, Yifan Luo, Hanlin Liao, Marc Debliquy, Chao Zhang
Summary: This article reviews the research advances on the stability of metal oxide semiconductor gas sensors in the past five years, discussing the impact of structure, environment, toxicity, and sensor array on sensor stability, and summarizing the improvement schemes of existing materials and structure design.
IEEE SENSORS JOURNAL
(2022)
Article
Chemistry, Analytical
Jin-Young Kim, Somalapura Prakasha Bharath, Ali Mirzaei, Sang Sub Kim, Hyoun Woo Kim
Summary: By using composite materials of metal oxides decorated with catalytic gold nanoparticles, five sensors based on In2O3, SnO2, and TiO2 were designed to enhance the sensor selectivity. An array of these sensors was used to detect three pollutant gases (CO, NO2, and NH3) with various concentrations. Furthermore, a sensor array was used to detect two types of binary mixtures with different concentrations. A principal component analysis and a deep neural network-based model were utilized to evaluate and differentiate the gases and their mixtures with high accuracy.
SENSORS AND ACTUATORS B-CHEMICAL
(2023)
Article
Engineering, Electrical & Electronic
Andrea Vici, Robin Degraeve, Jacopo Franco, Ben Kaczer, Philippe J. Roussel, Ingrid De Wolf
Summary: An analytical approach for calculating the time-to-breakdown of metal-oxide-semiconductor (MOS) systems under different stress conditions is proposed. This method relies solely on fresh I-g V-g measurements and accurately determines the voltage, gate oxide thickness, and temperature dependencies of time-to-breakdown. By comparing these calculated values with experimental data, a comprehensive assessment of the system's performance under various operating conditions can be made. The introduced time-to-breakdown map in the {Temperature-Voltage} space allows for immediate identification of the maximum stress condition for any target lifetime.
IEEE TRANSACTIONS ON ELECTRON DEVICES
(2023)
Article
Chemistry, Physical
Marco Girolami, Valerio Serpente, Matteo Mastellone, Marco Tardocchi, Marica Rebai, Qinglei Xiu, Jinlong Liu, Zhijia Sun, Yubin Zhao, Veronica Valentini, Daniele M. Trucchi
Summary: This study demonstrates the fabrication of vertical metal-semiconductor-metal detectors for UV-C radiation using single-crystal chemical vapour deposition (CVD) diamond samples with asymmetric Schottky contacts. The detectors show solar blindness and zero power consumption under photovoltaic operating conditions, with a high UV/Vis rejection ratio. The excellent structural quality and charge transport properties of the diamond bulk enable the detectors to achieve excellent performance even at low electric fields.
Article
Chemistry, Multidisciplinary
Xingtai Chen, Tao Liu, Zhaoru Li, Xi-Tao Yin
Summary: Gas sensors, especially metal oxide semiconductors, have been widely used in various fields, and modification methods such as special structures, doping, and precious metal loading can improve their gas-sensitive performance. This review summarizes the progress in the modification of metal oxides, including their response, selectivity, and operating temperature, and focuses on the gas-sensitive mechanisms. The bottlenecks and future development prospects of current metal oxide semiconductor n-Butanol gas sensors are also discussed.
MATERIALS TODAY CHEMISTRY
(2023)
Article
Chemistry, Analytical
Marius Rodner, Donatella Puglisi, Sebastian Ekeroth, Ulf Helmersson, Ivan Shtepliuk, Rositsa Yakimova, Andreas Skallberg, Kajsa Uvdal, Andreas Schutze, Jens Eriksson
Article
Environmental Sciences
Caroline Schultealbert, Johannes Amann, Tobias Baur, Andreas Schuetze
Summary: Hydrogen, often neglected in indoor air studies, can be effectively monitored using selective MOS sensors and analytical reference devices. The results demonstrate the importance of monitoring hydrogen in indoor air for quality control, although further attention is needed in this area.
Article
Environmental Sciences
Tobias Baur, Johannes Amann, Caroline Schultealbert, Andreas Schutze
Summary: The potential and limitations of MOS gas sensors for IAQ monitoring have been discussed in this study, highlighting the importance of advanced calibration and data evaluation for accurate VOC measurements.
Article
Chemistry, Analytical
Christopher Schnur, Payman Goodarzi, Yevgeniya Lugovtsova, Jannis Bulling, Jens Prager, Kilian Tschoeke, Jochen Moll, Andreas Schuetze, Tizian Schneider
Summary: This paper proposes a machine learning-based automated damage detection method that harnesses data-driven analysis for structural health monitoring systems. Experimental results demonstrate that the method is capable of reliably detecting structural damage automatically, and it can identify damaged structures at different damage locations and temperatures even without prior training.
Article
Environmental Sciences
Yannick Robin, Johannes Amann, Tobias Baur, Payman Goodarzi, Caroline Schultealbert, Tizian Schneider, Andreas Schuetze
Summary: This paper introduces a systematic approach based on deep neural networks, dynamic operation, and randomized calibration for volatile organic compound measurements in indoor air quality monitoring.
Article
Instruments & Instrumentation
Sebastian Schorr, Dirk Baehre, Andreas Schuetze
Summary: The integration of process data and machine learning methods in manufacturing processes opens up new possibilities for quality control and condition monitoring. Predicting workpiece quality in early machining stages can lead to efficient utilization of resources. However, the implementation of machine learning methods in real manufacturing processes is limited due to the need for validation and proving their capability for quality prediction.
TM-TECHNISCHES MESSEN
(2022)
Article
Instruments & Instrumentation
Payman Goodarzi, Andreas Schuetze, Tizian Schneider
Summary: This paper explores the issue of performance degradation in machine learning methods and data-driven models when facing real-life situations. It compares the prediction results of traditional machine learning and deep neural networks in industrial condition monitoring. The study finds that domain shift can be visualized using feature extraction and principal component analysis, and the cross-domain validated results of FESC/R are comparable to state-of-the-art methods.
TM-TECHNISCHES MESSEN
(2022)
Editorial Material
Instruments & Instrumentation
Klaus-Dieter Sommer, Michael Heizmann, Andreas Schuetze
TM-TECHNISCHES MESSEN
(2022)
Article
Instruments & Instrumentation
Tanja Dorst, Tizian Schneider, Sascha Eichstaedt, Andreas Schuetze
Summary: This paper proposes the application of measurement uncertainty propagation in machine learning (ML) and extends the automated ML toolbox (AMLT) to consider uncertainty. By applying the principles described in the Guide to the Expression of Uncertainty in Measurement (GUM), uncertainty propagation is carried out for each step in the AMLT. The results show that considering measurement uncertainty in machine learning can effectively assess the reliability of results and the basis of decisions.
TM-TECHNISCHES MESSEN
(2023)
Article
Environmental Sciences
Yannick Robin, Johannes Amann, Payman Goodarzi, Tizian Schneider, Andreas Schuetze, Christian Bur
Summary: In this study, deep learning methods are used to calibrate MOS gas sensors in a complex environment and mitigate the problem of long calibration times and transferring calibrations between sensors. The results show that transfer learning significantly reduces calibration time while maintaining good prediction accuracy.
Editorial Material
Instruments & Instrumentation
Andreas Schuetze
TM-TECHNISCHES MESSEN
(2022)
Editorial Material
Instruments & Instrumentation
Klaus-Dieter Sommer, Michael Heizmann, Andreas Schutze
TM-TECHNISCHES MESSEN
(2023)
Article
Instruments & Instrumentation
Dennis Arendes, Johannes Amann, Cyril Tessier, Oliver Brieger, Andreas Schuetze, Christian Bur
Summary: This article presents a novel gas mixing apparatus (GMA) that can provide welldefined gas mixtures for calibrating gas sensors. The GMA has been optimized for settling speed and self-monitoring, and can provide up to 14 individual test gases with a wide concentration range. The system is controlled by Python software and can exchange gas mixtures quickly. The article also demonstrates the analytical quantification of the system and the use of photoionization detectors for internal leakage detection.
TM-TECHNISCHES MESSEN
(2023)
Article
Instruments & Instrumentation
Caroline Schultealbert, Tobias Baur, Tilman Sauerwald, Andreas Schuetze
Summary: This study investigates the poisoning effect of cyclic siloxane octamethylcyclotetrasiloxane on a commercially available semiconductor gas sensor in temperature cycled operation. The data is assessed using the Sauerwald-Baur model and the DSR method, and compared with a sensor in constant temperature operation mode. The research identifies a feature, the differential surface oxidation (DSO), derived from the Sauerwald-Baur model, which quantitatively expresses the sensor condition in terms of siloxane poisoning. The study also demonstrates the sensor's self-compensation ability using this feature.
TM-TECHNISCHES MESSEN
(2023)
Article
Chemistry, Multidisciplinary
Marius Rodner, Adam Icardi, Margus Kodu, Raivo Jaaniso, Andreas Schuetze, Jens Eriksson
