2021 IEEE International Conference on Sensors and Nanotechnology (SENNANO)最新文献

Electrochemical Detection of Tributyrin using Prussian Blue Functionalized Glassy Carbon Electrode 普鲁士蓝功能化玻碳电极对三丁酸酯的电化学检测

2021 IEEE International Conference on Sensors and Nanotechnology (SENNANO) Pub Date : 2021-09-22 DOI: 10.1109/sennano51750.2021.9642610

S. Sarah, S. R. Balakrishnan, C. W. Zanariah, W. W. Wan Ismail, M. Sahrim, I. Ismail, J. Jamaludin, M. Othman, K. N. Zainul Ariffin

{"title":"Electrochemical Detection of Tributyrin using Prussian Blue Functionalized Glassy Carbon Electrode","authors":"S. Sarah, S. R. Balakrishnan, C. W. Zanariah, W. W. Wan Ismail, M. Sahrim, I. Ismail, J. Jamaludin, M. Othman, K. N. Zainul Ariffin","doi":"10.1109/sennano51750.2021.9642610","DOIUrl":"https://doi.org/10.1109/sennano51750.2021.9642610","url":null,"abstract":"Electrochemical biosensor is a self-contained integrated device, which can provide specific quantitative or semiquantitative analytical information using a biological recognition element (biochemical receptor) which is retained in direct spatial contact with an electrochemical transduction element. In this work, surface functionalization is done on the glassy carbon electrode (GCE) as the electrochemical sensor for detection of tributyrin (TB) as fat content measurement tool. Tributyrin is a triglyceride present in butter and can be described as a liquid fat with an acrid taste. This paper described about the cyclic voltammetry (CV) measurements on the functionalized GCE with graphene oxide (GO) and Prussian Blue (PB) immobilized with lipase (denoted as GC/GO/PB/Lipase electrode) dipped into the phosphate buffer solution (PBS pH 7.4). The functionalized electrode then used to measure the current response of different concentration of tributyrin ranged from (10 mg/ml to 1000 mg/ml). The results shows that current GC/GO/PB/Lipase electrode response was proportional to the tributyrin concentration. The proposed GC/GO/PB/Lipase bioelectrode for TB analysis offers an efficient derivative in the field of bioelectronics devices.","PeriodicalId":325031,"journal":{"name":"2021 IEEE International Conference on Sensors and Nanotechnology (SENNANO)","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122903139","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Computational Study on Sensing Properties of Oxygen on Defected Graphene Nanoribbon 缺陷石墨烯纳米带对氧传感特性的计算研究

2021 IEEE International Conference on Sensors and Nanotechnology (SENNANO) Pub Date : 2021-09-22 DOI: 10.1109/sennano51750.2021.9642655

Zuriana Auzar, Z. Johari, N. Alias, Ainun Khairiyah Taib, M. F. Mohd Yusoff

引用次数: 0

Fabrication of Integrated Electrode for pH Sensor Application 用于pH传感器的集成电极的制备

2021 IEEE International Conference on Sensors and Nanotechnology (SENNANO) Pub Date : 2021-09-22 DOI: 10.1109/sennano51750.2021.9642499

Farehanim Syukhairiyah Mohd Akhir, Foo Kai Loong, T. S. Jin, U. Hashim, C. Voon, Mohamad Azman Abu Hassan

引用次数: 0

Mechanical Suite of Flexural Bending Method for Electronic Memory Packages 电子存储封装弯曲弯曲方法的机械套件

2021 IEEE International Conference on Sensors and Nanotechnology (SENNANO) Pub Date : 2021-09-22 DOI: 10.1109/sennano51750.2021.9642645

Vance Liu, S. Arifeen, Cassie Bassett, M. Chung, C. Gan, H. Takiar

{"title":"Mechanical Suite of Flexural Bending Method for Electronic Memory Packages","authors":"Vance Liu, S. Arifeen, Cassie Bassett, M. Chung, C. Gan, H. Takiar","doi":"10.1109/sennano51750.2021.9642645","DOIUrl":"https://doi.org/10.1109/sennano51750.2021.9642645","url":null,"abstract":"With the advance of memory packaging technology toward small and thin form factor, the die stacking structure and material design of memory packages are getting complex and challenging. In the package compliance perspective, layers inside the package or intrinsic material defects are all subjectable and sensitive to mechanical load effect. The study demonstrates the application of three-point bending (3PB) test onto overall four different types of electronic memory packages to evaluate the mechanical behavior. The test data were analyzed by Weibull-based probabilistic mechanics approach and determined the B10 (Breakage at 10%) value. Finite element method (FEA) was further applied to evaluate the strain gradient geometry between three-point and four-point bending. The result data show that four-point bending method will result in more ideal stress and strain gradient that is less sensitive to package asymmetry. At last, a region of span setting has been simulated to define metrologically as the optimized span region. Due to the confidentiality of the test results, the material properties and detailed package constructional information have not been presented here in the paper.","PeriodicalId":325031,"journal":{"name":"2021 IEEE International Conference on Sensors and Nanotechnology (SENNANO)","volume":"187 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126429338","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

The Application of IoT-based Water Pressure Monitoring System 基于物联网的水压监测系统的应用

2021 IEEE International Conference on Sensors and Nanotechnology (SENNANO) Pub Date : 2021-09-22 DOI: 10.1109/sennano51750.2021.9642624

Kim-Mey Chew, S. Yiiong, Nancy Bundan, Syvester Chiang-Wei Tan

{"title":"The Application of IoT-based Water Pressure Monitoring System","authors":"Kim-Mey Chew, S. Yiiong, Nancy Bundan, Syvester Chiang-Wei Tan","doi":"10.1109/sennano51750.2021.9642624","DOIUrl":"https://doi.org/10.1109/sennano51750.2021.9642624","url":null,"abstract":"The study was stimulated by local utilities to improve their reputation in the era of water supply in residential areas, particularly the issue of low water pressure. The current low water pressure situation is highly dependent on complaints from residents in the supply area. This resulted in an extended period of time to solve the problem. Therefore, an IoT-based water pressure measuremeter was proposed. The proposed measurement device was used to detect low water pressure at the residential area or internal area that is away from the water main. The proposed solution is developed based on the principle of IoT architecture which covers the perception layer, network layer and application layer. The perception layer is composed of Arduino as microcontroller, GSM and WiFi shield as communication and water pressure sensor as transducer. WiFi and GSM shield provide communication services within the network layer. For the application layer, an IoT platform was chosen for data analysis and visualisation. The water pressure variation taken at two different places in urban areas. Two datasets were collected at Location 1 and four datasets were collected at Location 2. Each dataset has a 24-hour time frame. Preliminary findings were obtained and presented in this paper. The results showed the water pressure pattern within 24 hours. The study shows that real-time monitoring of water pressure contributes to a better standard of living for residents, as well as helping authorities find efficiencies and increase profits.","PeriodicalId":325031,"journal":{"name":"2021 IEEE International Conference on Sensors and Nanotechnology (SENNANO)","volume":"192 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132862729","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Study of Electrical Conductivity of Pyrrole-Reduced Graphene Oxide Pellet 吡咯还原氧化石墨烯球团的电导率研究

2021 IEEE International Conference on Sensors and Nanotechnology (SENNANO) Pub Date : 2021-09-22 DOI: 10.1109/sennano51750.2021.9642498

Sara Maira Mohd Hizam, Nurul Izza Soaid, Mohamed Shuaib Mohamed Saheed, Norani Muti Mohamed, C. F. Kait

{"title":"Study of Electrical Conductivity of Pyrrole-Reduced Graphene Oxide Pellet","authors":"Sara Maira Mohd Hizam, Nurul Izza Soaid, Mohamed Shuaib Mohamed Saheed, Norani Muti Mohamed, C. F. Kait","doi":"10.1109/sennano51750.2021.9642498","DOIUrl":"https://doi.org/10.1109/sennano51750.2021.9642498","url":null,"abstract":"Pyrrole-reduced graphene oxide was synthesized by chemical reduction because of its outstanding advantages including large surface area, high effective permittivity and electron mobility, and high electrical conductivity. This work reports on the detailed electrical conductivity study of pyrrole-reduced graphene oxide (py-rGO) coated on fluorine-doped tin oxide (FTO) glass. The py-rGO pellet is compressed by a pair of (3 cm x 2 cm) FTO glasses electrode was characterized by electrochemical impedance spectroscopy (EIS). Py-rGO was characterized by Fourier transform infrared (FTIR), Raman, X-ray powder diffraction (XRD) and X-ray photoelectron spectroscopy (XPS). The symmetric supercapacitor cell was made by putting rGO pellet in between of a pair of FTO glasses that has been soldered to act as anode and cathode. The electrical conductivity depends on the water hardness. Every types of water have different hardness. The conductivity of each rGO pellet before the water sample drop namely tap, distilled and lake water, are 1.154, 2.256 and 15.057 S/cm, respectively. Meanwhile, the conductivity of each rGO pellet after dropping are 5.168, 102.11 and 4.938 S/cm, respectively, showing that treated water has higher conductivity than untreated water. The changes in conductivity of the rGO pellet show that the conductivity of rGO pellet could be tuned by changing the condition of the water sample.","PeriodicalId":325031,"journal":{"name":"2021 IEEE International Conference on Sensors and Nanotechnology (SENNANO)","volume":"340 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133159675","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Hybrid Energy Harvester from Wireless Charging and Body Heat to Power-up IoT Devices 从无线充电和身体热量到为物联网设备供电的混合能量采集器

2021 IEEE International Conference on Sensors and Nanotechnology (SENNANO) Pub Date : 2021-09-22 DOI: 10.1109/sennano51750.2021.9642692

W. N. Mohd Fairuz, M. R. Ahmad, S. M. Arabee

{"title":"Hybrid Energy Harvester from Wireless Charging and Body Heat to Power-up IoT Devices","authors":"W. N. Mohd Fairuz, M. R. Ahmad, S. M. Arabee","doi":"10.1109/sennano51750.2021.9642692","DOIUrl":"https://doi.org/10.1109/sennano51750.2021.9642692","url":null,"abstract":"As we move towards Industrial Revolution 4.0, the miniaturization of electronic devices has introduced a new type of challenge where the dependency on the battery as a sole power supply is no longer practical due to its limited capacity, costly replacement process, and recently, new regulations set forth to minimize the usage of chemicals in batteries. Hence, an alternative method explored to mitigate this issue is by using energy harvesting. In this paper, energy harvesting methods from human body heat and wireless charging are studied and developed as potential energy sources. The feasibility of two systems integration that will form a Hybrid Energy Harvester device which theoretically may increase the output power required for the application is explored. A mathematical model for thermal energy harvesting is first developed using MATLAB/Simulink and simulation of and the wireless charging analyzed using Multisim. Finally, the prototype of each module was constructed, analyzed, and integrated into a prototype hybrid energy harvester device. The maximum output power achieved for the thermal energy harvester and wireless charging are 22.4mV and 0.947mV respectively. The feasibility of the device is proven and thus opens an opportunity to further study the application.","PeriodicalId":325031,"journal":{"name":"2021 IEEE International Conference on Sensors and Nanotechnology (SENNANO)","volume":"84 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128902523","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Impedimetric Lectin Biosensor for Prostate Cancer Detection 用于前列腺癌检测的阻抗凝集素生物传感器

2021 IEEE International Conference on Sensors and Nanotechnology (SENNANO) Pub Date : 2021-09-22 DOI: 10.1109/sennano51750.2021.9642659

Siti Fatimah Abd Rahman, Mohd Khairuddin Md Arshad, S. Gopinath, Mohamad Faris Mohamad Fathil, F. Sarry, M. N. Md Nor

引用次数: 0

Fabrication of Graphene Electrode via Graphene Transfer Method for Bisphenol A (BPA) Detection 石墨烯转移法制备双酚A (BPA)检测电极

2021 IEEE International Conference on Sensors and Nanotechnology (SENNANO) Pub Date : 2021-09-22 DOI: 10.1109/sennano51750.2021.9642581

Nur Insyirah Ahmad Shukri, Norhayati Bt Sabani, Ruslinda Bt A. Rahim, M. Fathil, S. Sabki, N. H. Halim, Nur Syakimah Binti Ismail

引用次数: 0

Comparative analysis of optimization algorithm on DSAE model for bearing fault diagnosis 基于DSAE模型的轴承故障诊断优化算法对比分析

2021 IEEE International Conference on Sensors and Nanotechnology (SENNANO) Pub Date : 2021-09-22 DOI: 10.1109/sennano51750.2021.9642578

S. R. Saufi, Mat Hussin Ab Talib, Zair Asrar Bin Ahmad, Lim Meng Hee, M. Leong, Mohd Haffizzi Bin Md Idris

{"title":"Comparative analysis of optimization algorithm on DSAE model for bearing fault diagnosis","authors":"S. R. Saufi, Mat Hussin Ab Talib, Zair Asrar Bin Ahmad, Lim Meng Hee, M. Leong, Mohd Haffizzi Bin Md Idris","doi":"10.1109/sennano51750.2021.9642578","DOIUrl":"https://doi.org/10.1109/sennano51750.2021.9642578","url":null,"abstract":"A rolling-element bearing is one of the most vital components in machinery and maintaining the bearing health condition is very important. Intelligent fault detection and diagnosis based on deep sparse autoencoder (DSAE) is presented to improve the current maintenance strategy. The conventional maintenance strategy suffers from manual feature extraction and feature selection. In this project, the DSAE model made up of multiple layers of neural networks that can perform automated feature extraction and feature dimensional reduction is proposed. The DSAE model is used to extract the important features from the Fast Fourier Transform (FFT) images by learning the high-level feature from the unlabeled images. However, the DSAE model requires hyperparameter selection of which manual hand-tuning is time-intensive. The DSAE model contains four hidden layers and requires 12 hyperparameters selection. The hyperparameter is automatically selected using an optimization algorithm. The comparative study is conducted on three optimization algorithms, namely particle swarm optimization (PSO), grey wolf optimizer (GWO) and genetic algorithm (GA). The overall analysis result shows that the proposed model achieved 100% diagnosis accuracy. Furthermore, the proposed model is tested with a completely new dataset and the result indicated that the DSAE model achieved 93.5% accuracy for the new dataset. The grey-wolf optimizer optimized quicker compared to PSO and GA.","PeriodicalId":325031,"journal":{"name":"2021 IEEE International Conference on Sensors and Nanotechnology (SENNANO)","volume":"84 5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126082119","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0