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arXiv 2024年

作者： Kim, Dasom Hou, Jin Lee, Geon Agrawal, Ayush Kim, Sunghwan Zhang, Hao Bao, Di Baydin, Andrey Wu, Wenjing Tay, Fuyang Huang, Shengxi Chia, Elbert E.M. Kim, Dai-Sik Seo, Minah Mohite, Aditya D. Hagenmüller, David Kono, Junichiro Applied Physics Graduate Program Smalley–Curl Institute Rice University HoustonTX77005 United States Department of Electrical and Computer Engineering Rice University HoustonTX77005 United States Department of Materials Science and NanoEngineering Rice University HoustonTX77005 United States Sensor System Research Center Korea Institute of Science and Technology Seoul02792 Korea Republic of Department of Physics and Astronomy Seoul National University Seoul08826 Korea Republic of Department of Chemical and Biomolecular Engineering Rice University Houston77005 United States Ulsan44919 Korea Republic of Division of Physics and Applied Physics School of Physical and Mathematical Sciences Nanyang Technological University Singapore637371 Singapore Smalley–Curl Institute Rice University HoustonTX77005 United States Rice Advanced Materials Institute Rice University HoustonTX77005 United States KU–KIST Graduate School of Converging Science and Technology Korea University Seoul02841 Korea Republic of Université de Strasbourg CNRS Strasbourg67200 France Department of Physics and Astronomy Rice University HoustonTX77005 United States

Phonons, or vibrational quanta, are behind some of the most fundamental physical phenomena in solids, including superconductivity, Raman processes, and broken-symmetry phases. It is therefore of fundamental importance to find ways to harness phonons for controlling these phenomena and developing novel quantum technologies. However, the majority of current phonon control techniques rely on the use of intense external driving fields or strong anharmonicities, which restricts their range of applications. Here, we present a scheme for controlling the intensity fluctuations in phonon emission at room temperature based on multimode ultrastrong light–matter coupling. The multimode ultrastrong coupling regime is achieved by coupling two optical phonon modes in lead halide perovskites to an array of nanoslots, which operates as a single-mode cavity. The extremely small mode volume of the nanoslots enables unprecedented coupling strengths in a cavity phonon-polariton system. In the far-detuned, low-cavity-frequency regime, we demonstrate that the nanoslot resonator mediates an effective coupling between the phonon modes, resulting in superthermal phonon bunching in thermal equilibrium, both within the same mode and between different modes. Experimental results are in good agreement with a multimode Hopfield model. Our work paves the way for the tailoring of phonons to modify charge and energy transport in perovskite materials, with potential applications in light-collecting or emitting devices. Copyright © 2024, The Authors. All rights reserved.

关键词： Perovskite

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Corrigendum to “Scalable molten salt strategy synthesis of large-size 2D MoS 2(1-x) Se 2x alloy for boosting potassium-ion storage performance” [Mater. Today Chem. 38 (2024) 102044]

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Materials Today Chemistry 2024年 39卷

作者： Jing Li Lei Yang Tianxiang Liang Hui Wei Honglin Li Feng Hu Jinpei Hei Yefeng Liu Nannan Wang Hehe Wei Engineering Research Center of High-frequency Soft Magnetic Materials and Ceramic Powder Materials of Anhui Province Engineering Technology Research Center of Preparation and Application of Industrial Ceramics of Anhui Province School of Chemistry and Material Engineering Chaohu University 1 Bantang Road Hefei 238000 PR China Key Laboratory of Biomimetic Sensor and Detecting Technology of Anhui Province School of Materials and Chemical Engineering West Anhui University Lu'an Anhui 237012 PR China Key Laboratory for Advanced Materials Center for Computational Chemistry and Research Institute of Industrial Catalysis East China University of Science and Technology 130 Meilong Road Shanghai 200237 PR China

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A Web-Based Campus Navigation System with Mobile Augmented Reality Intervention

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Journal of Physics: Conference Series 2021年第1期1997卷

作者： Noradila Nordin Marni Azira Markom Farhana Aqilah Suhaimi Syaimaa' Ishak School of Computing Universiti Utara Malaysia 06010 Sintok Kedah Malaysia Advanced Sensor Technology Center of Excellence Universiti Malaysia Perlis Kampus Pauh Putra 02600 Arau Perlis Malaysia

In this era of information technology, the introduction of new and greatly improved technologies is becoming vital especially with the progressive development of computing power to fulfill current technological needs. Augmented Reality (AR) is a part of the emerging technologies that are gaining great attention and interest with new and better innovations being developed. AR is an immersive technology where it complements real-world objects together with computer-generated objects to give more details and meaning to the objects in the real world. AR has been successfully growing nowadays in many industries, mainly in gaming and entertainment, education and navigation. However, AR has not been standardized and to be widely used in navigation systems even though there are many applications developed for this purpose. This paper proposed a web-based AR-UUM Campus Navigation System using ARToolKit, that is accessible via mobile devices that uses AR to overlay the information as images of the searched location on campus, especially for indoor navigations for lecture halls, tutorial rooms, laboratories, and offices which rarely are covered by the normal maps. Based on the respondents' evaluation, they managed to successfully interact with the AR-UUM Campus Navigation System, however, some improvements are required in terms of the functions expected from the system. Nevertheless, the use of AR in a navigation system shows promising results and has the potential to be widely used due to high interest in augmented reality.

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Electrochemical formation of ‘synthetic receptors’ based on conducting polymers

Electrochemical formation of ‘synthetic receptors’ based o...

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International Conference on Nanomaterials in Biomedical Application and Biosensors, NAP 2019

作者： Ramanavicius, A. Tereshchenko, A. Plikusiene, I. Ratautaite, V. Deshmukh, M.A. Smyntyna, V. Oztekin, Ya. Bubniene, U. Ramanaviciene, A. Department of Physical Chemistry Faculty of Chemistry and Geosciences Vilnius University Vilnius Lithuania Laboratory of Nanotechnology State Research Institute Center for Physical Sciences and Technology Vilnius Lithuania Faculty of Chemistry and Geosciences NanoTechnas-Centre of Nanotechnology and Material Science Vilnius University Vilnius Lithuania Department of Experimental Physics Faculty of Mathematics Physics and Information Technologies Odesa I.I. Mechnikov National University Odesa Ukraine Department of Physics RUSA-Center for Advanced Sensor Technology Dr. Babasaheb Ambedkar Marathwada University AurangabadMaharashtra431 004 India Faculty of Science Department of Chemistry Selcuk University Konya Turkey

ISBN: (纸本)9789811539954

Analysis of pharmaceuticals and biologically active materials recently can be performed by biosensors, which can be based on conducting polymers. Therefore, in this Mini Review some achievements in the synthesis and application of conducting polymer—polypyrrole (Ppy), which is often used in the design of sensors and biosensors, are overviewed. Some perspective methods of conducting polymer synthesis are outlined. Significant attention has been paid to electrochemical, chemical and biochemical synthesis of conducting polymers (CPs), which were developed by authors. The applicability of polypyrrole based functional layers in the design of electrochemical biosensors is overviewed. The adaptability of enzyme— glucose oxidase (GOx), which can be applied as (i) biological recognition element— in the design of glucose biosensors, (ii) a biocatalyst—in the synthesis of some above mentioned conducting polymers, is discussed. Part of biocompatibility related aspects of some conducting polymers are also discussed and some insights in the application of polypyrrole-based coatings for implantable sensors are outlined. © Springer Nature Singapore Pte Ltd. 2020.

关键词： Conducting polymers

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The first technology can compete with piezoelectricity to harvest ultrasound energy for powering medical implants

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Science Bulletin 2019年第21期64卷 1565-1566页

作者： Han Ouyang Zhou Li CAS Center for Excellence in Nanoscience Beijing Key Laboratory of Micro-Nano Energy and SensorBeijing Institute of Nanoenergy and NanosystemsChinese Academy of SciencesBeijing 100083China Beijing Advanced Innovation Centre for Biomedical Engineering Key Laboratory for Biomechanics and Mechanobiology of Ministry of EducationSchool of Biological Science and Medical EngineeringBeihang UniversityBeijing 100083China School of Nanoscience and Technology University of Chinese Academy of SciencesBeijing 100049China Center on Nanoenergy Research School of Physical Science and Technology Guangxi UniversityNanning 530004China

Sustainable operation of implanted medical devices is essential for clinic ***,limited battery capacity is a key challenge for most implantable medical electronics[1].Higher-capacity battery is not an ideal choice,because battery capacity is usually linearly dependent on battery volume[2].New energy harvesters have been developed as promising alternative solutions,which extracted energy from the ambient environment and biosystem for powering implantable devices[3],However,the energy reclaimed from body and ambient environment also have power lim让ation,such as thermal gradient and bioelectric *** ultrasound or RF energy into the body and generate electrical power by a converter is a reliable solution.

关键词： battery power ambient

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Classification of Multiple Visual Field Defects using Deep Learning

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Journal of Physics: Conference Series 2021年第1期1755卷

作者： M Abu N A H Zahri A Amir M I Ismail L M Kamarudin H Nishizaki Advanced Communication Engineering Centre (ACE) School of Computer and Communication Engineering Universiti Malaysia Perlis School of Mechatronic Engineering Univeriti Malaysia Perlis Advanced Sensor Technology (CEASTech) School of Computer and Communication Engineering Universiti Malaysia Perlis Faculty of Engineering University of Yamanashi

In this work, a custom deep learning method is proposed to develop a detection of visual fields defects which are the markers for serious optic pathway disease. Convolutional Neural Networks (CNN) is a deep learning method that is mostly used in images processing. Therefore, a custom 10 layers of CNN algorithm is built to detect the visual field defect. In this work, 1200 visual field defect images acquired from the Humphrey Field Analyzer 24–2 collected from Google Image have been used to classify 6 types of visual field defect. The defect patterns are including defects at central scotoma, right/left/upper/lower quadratopia, right/left hemianopia, vision tunnel, superior/inferior field defect and normal as baseline. The custom designed CNN is trained to discriminate between defect patterns in visual field images. In the proposed method, a mechanism of pre-processing is included to improve the classification of visual field defects. Then, the 6 visual field defect patterns are detected using a convolutional neural network. The dataset is evaluated using 5-fold cross-validation. The results of this work have shown that the proposed algorithm achieved a high classification rate with 96%. As comparison, traditional machine learning Support Vector Machine (SVM) and Classical Neural Network (NN) is chose and obtained classification rate at 74.54% and 90.72%.

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Cycling performance prediction based on cadence analysis by using multiple regression

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Journal of Physics: Conference Series 2021年第1期2107卷

作者： Sukhairi Sudin Azizi Naim Abdul Aziz Fathinul Syahir Ahmad Saad Nurul Syahirah Khalid Ismail Ishaq Ibrahim Faculty of Electrical Engineering Technology Universiti Malaysia Perlis Kampus Pauh Putra 02600 Arau Perlis Malaysia Centre of Excellence for Advanced Sensor Technology Universiti Malaysia Perlis Kompleks Pengajian Jejawi 2 02600 Arau Perlis Malaysia

This project examined the influence of the cadence, speed, heart rate and power towards the cycling performance by using Garmin Edge 1000. Any change in cadence will affect the speed, heart rate and power of the novice cyclist and the changes pattern will be observed through mobile devices installed with Garmin Connect application. Every results will be recorded for the next task which analysis the collected data by using machine learning algorithm which is Regression analysis. Regression analysis is a statistical method for modelling the connection between one or more independent variables and a dependent (target) variable. Regression analysis is required to answer these types of prediction problems in machine learning. Regression is a supervised learning technique that aids in the discovery of variable correlations and allows for the prediction of a continuous output variable based on one or more predictor variables. A total of forty days' worth of events were captured in the dataset. Cadence act as dependent variable, (y) while speed, heart rate and power act as independent variable, (x) in prediction of the cycling performance. Simple linear regression is defined as linear regression with only one input variable (x). When there are several input variables, the linear regression is referred to as multiple linear regression. The research uses a linear regression technique to predict cycling performance based on cadence analysis. The linear regression algorithm reveals a linear relationship between a dependent (y) variable and one or more independent (y) variables, thus the name. Because linear regression reveals a linear relationship, it determines how the value of the dependent variable changes as the value of the independent variable changes. This analysis use the Mean Squared Error (MSE) expense function for Linear Regression, which is the average of squared errors between expected and real values. Value of R squared had been recorded in this project. A low R-s

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Multi faces recognition using deep learning approach

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AIP Conference Proceedings 2024年第1期2898卷

作者： Kristine Chin Sze Wen Marni Azira Markom Erdy Sulino Mohd Muslim Tan Abdul Hamid Adom Arni Munira Markom SMD Semiconductor Sdn Bhd Level 5 No.1 HSL Tower Lorong La Promenade 2 La Promenade Kuching-Samarahan Expressway 94300 Kota Samarahan Sarawak Malaysia Faculty of Electronic Engineering Technology Universiti Malaysia Perlis Kampus Pauh Putra 02600 Arau Perlis Malaysia Center of Excellence Advanced Sensor Technology Universiti Malaysia Perlis Kampus Pauh Putra 02600 Arau Perlis Malaysia Faculty of Electrical Engineering Technology Universiti Malaysia Perlis Kampus Pauh Putra 02600 Arau Perlis Malaysia School of Electrical Engineering College of Engineering Universiti Teknologi MARA Shah Alam 40450 Selangor Malaysia

Face recognition is a technology that is used to identify and verify the identity of a person by their face. The process is carried out by matching human faces from an image or video against a database of faces. It consists of three stages: face detection, face capture (feature extraction) and face matching (classification). Face recognition is implemented in many applications nowadays. A few examples of face recognition applications are attendance systems and security systems. Due to the COVID-19 pandemic, the traditional and existing attendance systems are not suitable to be used because there is a risk of COVID-19 transmission through the attendance system. Moreover, the existing technology that is implemented in some applications is time-consuming and the common web authentication methods such as password-based and token-based authentication are insecure. In this project, the dataset was collected from 10 subjects. The collected images are cropped and resized to the required input size. In order to increase the dataset number, the resized images undergo image augmentation. During the classification, 5 types of deep learning-based models are trained and used to predict the subject's images. Then, the performance of the models (VGG16, VGG19, ResNet50, ResNet101 and ResNet152) is compared. Both VGG16 and VGG19 have a high validation accuracy of 100% compared to ResNet50 (96%), ResNet101 (94%) and ResNet152 (98%). However, VGG16 performed better than VGG19 as VGG16 had no misclassifications while VGG19 had one misclassification.

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In-Situ Electrostatic Field Regulating the Recrystallization Behavior of P(Vdf-Trfe) Films with High Β-Phase Content and Enhanced Piezoelectric Properties

SSRN

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SSRN 2022年

作者： Lv, Fu Lin, Jiamin Zhou, Zheng Hong, Zijian Wu, Yongjun Ren, Zhaohui Zhang, Qilong Dong, Shurong Luo, Jikui Shi, Junhui Chen, Ruimin Liu, Bing Su, Yuanjie Huang, Yuhui School of Materials Science and Engineering State Key Laboratory of Silicon Materials Cyrus Tang Center for Sensor Materials and Applications Zhejiang University Zhejiang Hangzhou310027 China School of Materials Science and Engineering State Key Lab of Silicon Materials Zhejiang University Zhejiang Hangzhou310027 China College of Information Science and Electronic Engineering Key Lab of Advanced Micro Nano Electronic Devices & Smart Systems of Zhejiang Zhejiang University Zhejiang Hangzhou310027 China Zhejiang Lab Zhejiang Hangzhou311121 China College of Electronic Information and Engineering Hangzhou Dianzi University Zhejiang Hangzhou310018 China School of Optoelectronic Science and Engineering University of Electronic Science and Technology of China Sichuan Chengdu610054 China

Fabrication of flexible piezoelectric polymers is essential for the development of wearable biosensors. Nevertheless, the piezoelectric coefficient of polymers is usually an order of magnitude lower than the inorganic piezoelectric materials, which limits the miniature of the devices. Herein, a simple and cost-effective technique is proposed by applying an electrostatic field to in-situ regulate the recrystallization behavior of the poly(vinylidene fluoride-trifluorethylene) (P(VDF-TrFE)) film during the thermal annealing and recrystallization stage. Significantly enhanced properties are obtained, including a large piezoelectric coefficient (d 33 ~30.7 pC/N) and a high voltage sensitivity of 167.12 mV/kPa. The outstanding performance is mainly attributed to the applied electrostatic field maintained during the film growth stage, which promotes the generation of nucleation sites for the polar β lamellae crystals. A wireless sensor system is further established with the obtained P(VDF-TrFE) film, demonstrating great potential applications in movement monitoring. The proposed facile approach could potentially be applied to the large-scale production of polymer films with excellent piezoelectric properties for flexible wireless biosensing device applications. © 2022, The Authors. All rights reserved.

关键词： Piezoelectricity

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Micropatterned piezoelectric films induced by modulated corona field for weak signal detection

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Chemical Engineering Journal 2025年 517卷

作者： Fu Lv Chenghang Yu Bing Liu Jiamin Lin Zijian Hong Yongjun Wu Zhaohui Ren Qilong Zhang Shurong Dong Jikui Luo Juan Li Yuhui Huang School of Materials Science and Engineering Cyrus Tang Center for Sensor Materials and Applications Innovation Center of Yangtze Delta Institute of Fundamental and Transdisciplinary Research Zhejiang University Hangzhou Zhejiang 310058 China Nanhu Brain-computer Interface Institute Hangzhou Zhejiang 311100 China School of Engineering Hangzhou City University Hangzhou Zhejiang 310015 China College of Electronic Information and Engineering Hangzhou Dianzi University Hangzhou Zhejiang 310018 China Zhejiang Key Laboratory of Advanced Solid State Energy Storage Technology and Applications Taizhou Institute of Zhejiang University Taizhou Zhejiang 318000 China College of Information Science and Electronic Engineering Key Lab of Advanced Micro/Nano Electronic Devices & Smart Systems of Zhejiang Zhejiang University Hangzhou Zhejiang 310027 China College of Materials and Science Engineering Zhejiang University of Technology Hangzhou Zhejiang 310014 China

Enhancing the inherent piezoelectricity and introducing innovative structural designs are the two fundamental strategies for enhancing the pressure sensitivity of P(VDF-TrFE)-based sensors. In this study, we propose a scalable and cost-effective manufacturing approach that utilizes a modulated corona field to create micropatterns on the surface of P(VDF-TrFE) films, and enhance their piezoelectric properties during the annealing and recrystallization process. The micropatterned P(VDF-TrFE) films exhibit a distinctive “wavy” microstructure and possess ultrahigh piezoelectric properties (d 33 ∼ 35.6 pC/N), resulting in excellent sensitivity (∼477.94 mV/kPa). To unravel the underlying mechanism responsible for this superior performance, we employ finite element modeling and phase-field simulations. Our findings reveal that the modulated corona field generates an equipotential surface with a characteristic “wavy” distribution and promotes the creation of nucleation sites for the polar β phase in P(VDF-TrFE) films. A real-time monitoring system is further exploited with the obtained micropatterned P(VDF-TrFE) films for detecting radial artery pulse signals. The results obtained from this work hold great promise for the development of highly sensitive sensors, with wide-ranging applications in healthcare and environmental monitoring.

关键词： Flexible wireless biosensors Micropatterned structure Phase-field simulations Piezoelectric polymer

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