Pub Date : 2022-10-30DOI: 10.1109/SENSORS52175.2022.9967210
Yuan Cao, J. Floehr, D. Azarkh, U. Schnakenberg
Artificial fertilization depends on the oocyte quality, especially on the zona pellucida. This gelatinous outer layer becomes soft before and hardens after sperm penetration. Here, we propose a setup that characterizes the stiffness of the zona pellucida of mouse oocytes by electrical impedance spectroscopy. Single oocytes are hydrodynamically trapped at an aperture, which is located between two ring-shaped electrodes. By applying weak negative pressures to the cell trap, the electrical impedance correlates with the stiffness of the zona pellucida.
{"title":"Mouse Oocyte Characterization by Electrical Impedance Spectroscopy","authors":"Yuan Cao, J. Floehr, D. Azarkh, U. Schnakenberg","doi":"10.1109/SENSORS52175.2022.9967210","DOIUrl":"https://doi.org/10.1109/SENSORS52175.2022.9967210","url":null,"abstract":"Artificial fertilization depends on the oocyte quality, especially on the zona pellucida. This gelatinous outer layer becomes soft before and hardens after sperm penetration. Here, we propose a setup that characterizes the stiffness of the zona pellucida of mouse oocytes by electrical impedance spectroscopy. Single oocytes are hydrodynamically trapped at an aperture, which is located between two ring-shaped electrodes. By applying weak negative pressures to the cell trap, the electrical impedance correlates with the stiffness of the zona pellucida.","PeriodicalId":120357,"journal":{"name":"2022 IEEE Sensors","volume":"92 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115965007","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}
Pub Date : 2022-10-30DOI: 10.1109/SENSORS52175.2022.9967030
Zhibin Liu, N. Stevens, Miguel Heredia Conde
Visible Light Positioning (VLP) as a class of Optical Wireless Positioning (OWP) has been increasingly studied due to the massive installation of Light Emitting Diodes (LEDs) in recent years. A passive Time-of-Flight (ToF) camera can work as a receiver in VLP systems because it can demodulate the received modulated optical signals. In this work, we aim to combine VLP technology and ToF cameras to achieve unprece-dented positioning accuracy. To this end, a VLP experimental framework consisting of five LED modules modulated by a Field Programmable Gate Array (FPGA) and a passive ToF camera is constructed. A fusion algorithm is proposed and experimentally validated that combines the Angle Of Arrival (AOA) algorithm leveraging the knowledge of the lens normals of the ToF camera and the Time Difference Of Arrival (TDOA) algorithm based on the hybrid Chan/Taylor series expansion method. In the end, we demonstrate through extensive experiments that the positioning accuracy using the fusion algorithm is higher than that using a single positioning algorithm.
{"title":"Visible Light Positioning Using Arrays of Time-of- Flight Pixels","authors":"Zhibin Liu, N. Stevens, Miguel Heredia Conde","doi":"10.1109/SENSORS52175.2022.9967030","DOIUrl":"https://doi.org/10.1109/SENSORS52175.2022.9967030","url":null,"abstract":"Visible Light Positioning (VLP) as a class of Optical Wireless Positioning (OWP) has been increasingly studied due to the massive installation of Light Emitting Diodes (LEDs) in recent years. A passive Time-of-Flight (ToF) camera can work as a receiver in VLP systems because it can demodulate the received modulated optical signals. In this work, we aim to combine VLP technology and ToF cameras to achieve unprece-dented positioning accuracy. To this end, a VLP experimental framework consisting of five LED modules modulated by a Field Programmable Gate Array (FPGA) and a passive ToF camera is constructed. A fusion algorithm is proposed and experimentally validated that combines the Angle Of Arrival (AOA) algorithm leveraging the knowledge of the lens normals of the ToF camera and the Time Difference Of Arrival (TDOA) algorithm based on the hybrid Chan/Taylor series expansion method. In the end, we demonstrate through extensive experiments that the positioning accuracy using the fusion algorithm is higher than that using a single positioning algorithm.","PeriodicalId":120357,"journal":{"name":"2022 IEEE Sensors","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116872279","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}
Pub Date : 2022-10-30DOI: 10.1109/SENSORS52175.2022.9967249
S. Ahmadi, D. Maddipatla, V. Palaniappan, H. Emani, Sajjad Hajian, Q. Wu, M. Atashbar
Thick electrodes with condensed active materials have been employed to increase volumetric and gravimetric capacity/energy density of lithium ion batteries (LIBs) for electric vehicle (EV) applications. However, thick electrodes suffer from low ionic transportation at high current rates during charging process. Introduction of channels along the thickness of the electrode to make 3-dimensional (3D) architectures leads to better performance under fast charging conditions when compared to baseline electrodes without channels. This can be attributed to the fact that the main factor limiting capacity density at high rates of charging is the diffusion of lithium ions across the cell. 3D channel architectures facilitates a large pathway for ionic transportation that leads to an overall reduction in cell internal impedance, electrode tortuosity and increased active surface area, resulting in better electrochemical and cycling performance. In this paper, a laser patterning process was employed to create channels (in the z-direction) along the thickness of a 74 µm thick electrode made of Philips graphite with 26% porosity. The rate performance test results demonstrated an improvement of 47.6%/49.3% in gravimetric capacity density at extremely fast charging rates of 4C/6C when compared to the baseline electrode. The cycling performance test under 3C showed more than 3 times improvement in capacity retention after 200 cycles for the laser patterned electrode compared to the baseline electrode, indicating the superior performance of the laser-patterned electrodes.
{"title":"3D Architectures of a Thick Graphite Anode Enabled by Laser Patterning Process to Improve Capacity Density and Cycling Performance of LIBs","authors":"S. Ahmadi, D. Maddipatla, V. Palaniappan, H. Emani, Sajjad Hajian, Q. Wu, M. Atashbar","doi":"10.1109/SENSORS52175.2022.9967249","DOIUrl":"https://doi.org/10.1109/SENSORS52175.2022.9967249","url":null,"abstract":"Thick electrodes with condensed active materials have been employed to increase volumetric and gravimetric capacity/energy density of lithium ion batteries (LIBs) for electric vehicle (EV) applications. However, thick electrodes suffer from low ionic transportation at high current rates during charging process. Introduction of channels along the thickness of the electrode to make 3-dimensional (3D) architectures leads to better performance under fast charging conditions when compared to baseline electrodes without channels. This can be attributed to the fact that the main factor limiting capacity density at high rates of charging is the diffusion of lithium ions across the cell. 3D channel architectures facilitates a large pathway for ionic transportation that leads to an overall reduction in cell internal impedance, electrode tortuosity and increased active surface area, resulting in better electrochemical and cycling performance. In this paper, a laser patterning process was employed to create channels (in the z-direction) along the thickness of a 74 µm thick electrode made of Philips graphite with 26% porosity. The rate performance test results demonstrated an improvement of 47.6%/49.3% in gravimetric capacity density at extremely fast charging rates of 4C/6C when compared to the baseline electrode. The cycling performance test under 3C showed more than 3 times improvement in capacity retention after 200 cycles for the laser patterned electrode compared to the baseline electrode, indicating the superior performance of the laser-patterned electrodes.","PeriodicalId":120357,"journal":{"name":"2022 IEEE Sensors","volume":"162 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116056836","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}
Pub Date : 2022-10-30DOI: 10.1109/SENSORS52175.2022.9967194
Yuna Jung, Daniel W. Gulick, J. Christen
Hydrocephalus is an accumulation of excess pressure in the brain due to malfunction of the fluid drainage system, arachnoid granulations. Standard treatment uses a shunt to drain excess cerebrospinal fluid to the abdomen. Conventional shunts suffer high failure rates over time. To reduce failure, we propose replacing the shunt with a miniaturized valve placed in the intracranial space. Our current prototype uses a duckbill valve design with 1 mm outlet width. The valve leaflets are silicone (PDMS), with the fluid channel defined using photolithography. In bench top pressure vs. flow testing, the silicone duckbill valve achieved the target cracking pressure range of 5 to 15 cmH2O with no cycling degradation or reverse flow leakage. Upcoming studies will monitor long-term degradation and test valve performance in vivo.
{"title":"Miniaturized Passive Bio-mechanical Valve for Hydrocephalus Treatment","authors":"Yuna Jung, Daniel W. Gulick, J. Christen","doi":"10.1109/SENSORS52175.2022.9967194","DOIUrl":"https://doi.org/10.1109/SENSORS52175.2022.9967194","url":null,"abstract":"Hydrocephalus is an accumulation of excess pressure in the brain due to malfunction of the fluid drainage system, arachnoid granulations. Standard treatment uses a shunt to drain excess cerebrospinal fluid to the abdomen. Conventional shunts suffer high failure rates over time. To reduce failure, we propose replacing the shunt with a miniaturized valve placed in the intracranial space. Our current prototype uses a duckbill valve design with 1 mm outlet width. The valve leaflets are silicone (PDMS), with the fluid channel defined using photolithography. In bench top pressure vs. flow testing, the silicone duckbill valve achieved the target cracking pressure range of 5 to 15 cmH2O with no cycling degradation or reverse flow leakage. Upcoming studies will monitor long-term degradation and test valve performance in vivo.","PeriodicalId":120357,"journal":{"name":"2022 IEEE Sensors","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116348960","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}
Pub Date : 2022-10-30DOI: 10.1109/SENSORS52175.2022.9967277
M. Schneider, Júlia Santasusagna, Ingrid Anna Maria Magnet, U. Schmid
This exploratory work demonstrates the potential of plate-type piezoelectric MEMS resonators for measuring the dynamic viscosity of human blood. These micromachined silicon sensors are operated in roof-tile shaped vibrational modes, featuring high quality factors in liquids. The quality factor of the 17 vibrational mode is used in combination with a sensor calibration procedure which is based on viscosity standards to monitor this fluidic material parameter. We demonstrate, that the MEMS sensor can provide real-time viscosity data over extended periods of time, which may be of high interest in cardiovascular medicine and medical applications such as extracorporal membrane oxygenation (ECMO).
{"title":"Ex Vivo Blood Viscosity Monitoring with Piezoelectric MEMS Resonators","authors":"M. Schneider, Júlia Santasusagna, Ingrid Anna Maria Magnet, U. Schmid","doi":"10.1109/SENSORS52175.2022.9967277","DOIUrl":"https://doi.org/10.1109/SENSORS52175.2022.9967277","url":null,"abstract":"This exploratory work demonstrates the potential of plate-type piezoelectric MEMS resonators for measuring the dynamic viscosity of human blood. These micromachined silicon sensors are operated in roof-tile shaped vibrational modes, featuring high quality factors in liquids. The quality factor of the 17 vibrational mode is used in combination with a sensor calibration procedure which is based on viscosity standards to monitor this fluidic material parameter. We demonstrate, that the MEMS sensor can provide real-time viscosity data over extended periods of time, which may be of high interest in cardiovascular medicine and medical applications such as extracorporal membrane oxygenation (ECMO).","PeriodicalId":120357,"journal":{"name":"2022 IEEE Sensors","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121225253","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}
Pub Date : 2022-10-30DOI: 10.1109/SENSORS52175.2022.9967035
M. Ghahramani, Iman Hosseini, D. Herath
Postural sway in older people can be indicative of risk of falling. Common sway assessment methods are either subjective or require expensive and obtrusive measuring devices. In this study, the performance of a Balance Mat prototype in postural sway assessment is compared against an inertial measurement unit sensor. A total of 20 older participants con-ducted six standing tests while standing on the Balance Mat and equipped with the sensor. Several spatio-temporal and frequency domain sway measures were derived from the Balance Mat and the sensor data and the correlation between the corresponding measures of the two devices were tested. The results show strong to very strong correlation between common sway assessment metrics of sway range, RMS, path, distance, jerk, velocity, and total power. This suggests that this device is effective in postural sway assessment. The Balance Mat can offer unique advantages in postural sway assessment due to its light weight, portability, and ease of use.
{"title":"Performance Analysis of a Postural Balance Assessment Mat Prototype Using Inertial Sensor","authors":"M. Ghahramani, Iman Hosseini, D. Herath","doi":"10.1109/SENSORS52175.2022.9967035","DOIUrl":"https://doi.org/10.1109/SENSORS52175.2022.9967035","url":null,"abstract":"Postural sway in older people can be indicative of risk of falling. Common sway assessment methods are either subjective or require expensive and obtrusive measuring devices. In this study, the performance of a Balance Mat prototype in postural sway assessment is compared against an inertial measurement unit sensor. A total of 20 older participants con-ducted six standing tests while standing on the Balance Mat and equipped with the sensor. Several spatio-temporal and frequency domain sway measures were derived from the Balance Mat and the sensor data and the correlation between the corresponding measures of the two devices were tested. The results show strong to very strong correlation between common sway assessment metrics of sway range, RMS, path, distance, jerk, velocity, and total power. This suggests that this device is effective in postural sway assessment. The Balance Mat can offer unique advantages in postural sway assessment due to its light weight, portability, and ease of use.","PeriodicalId":120357,"journal":{"name":"2022 IEEE Sensors","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121601305","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}
Pub Date : 2022-10-30DOI: 10.1109/SENSORS52175.2022.9967244
Stefan Schulte, Gianni Allevato, Christoph Haugwitz, M. Kupnik
Air-coupled ultrasonic phased arrays are a complement to existing lidar-, camera- and radar-based sensors for object detection and spatial imaging. These in-air sonar systems typically use conventional beamforming (CBF) for high-frame rate image formation. Consequently, in real-world multi-target environments, the unique identification of reflectors is a challenging task due to the array-specific point spread function (PSF). Therefore, we present a neural auto-encoder network based on Xception for removing the PSF characteristics from CBF images and estimating the number of reflectors. Based on this information, the reflector coordinates are extracted by Gaussian mixture model clustering. We train and test the architecture on simulated and randomized multi-target CBF images. The performance is evaluated in terms of the localization precision, reflector count error and the angular resolution obtained. The preliminary results show a low mean error for the localization (-0.61°, -3 mm) and an accuracy of 83% for the reflector count estimation. The angular resolution of the given array can be improved from 14° to 2°. Overall, we highlight the potential of state-of-the-art auto-encoder networks, typically used for optical images, for CBF image enhancement and the combination with clustering for target localization.
{"title":"Deep-Learned Air-Coupled Ultrasonic Sonar Image Enhancement and Object Localization","authors":"Stefan Schulte, Gianni Allevato, Christoph Haugwitz, M. Kupnik","doi":"10.1109/SENSORS52175.2022.9967244","DOIUrl":"https://doi.org/10.1109/SENSORS52175.2022.9967244","url":null,"abstract":"Air-coupled ultrasonic phased arrays are a complement to existing lidar-, camera- and radar-based sensors for object detection and spatial imaging. These in-air sonar systems typically use conventional beamforming (CBF) for high-frame rate image formation. Consequently, in real-world multi-target environments, the unique identification of reflectors is a challenging task due to the array-specific point spread function (PSF). Therefore, we present a neural auto-encoder network based on Xception for removing the PSF characteristics from CBF images and estimating the number of reflectors. Based on this information, the reflector coordinates are extracted by Gaussian mixture model clustering. We train and test the architecture on simulated and randomized multi-target CBF images. The performance is evaluated in terms of the localization precision, reflector count error and the angular resolution obtained. The preliminary results show a low mean error for the localization (-0.61°, -3 mm) and an accuracy of 83% for the reflector count estimation. The angular resolution of the given array can be improved from 14° to 2°. Overall, we highlight the potential of state-of-the-art auto-encoder networks, typically used for optical images, for CBF image enhancement and the combination with clustering for target localization.","PeriodicalId":120357,"journal":{"name":"2022 IEEE Sensors","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121375287","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}
Pub Date : 2022-10-30DOI: 10.1109/SENSORS52175.2022.9967231
Abhishek Khoyani, Harshdeep Kaur, Marzieh Amini, H. Sadreazami
The brain-computer interface is a technology that allows a machine to connect with the human brain and work based on the commands released by thoughts and activities of the brain. Electrodes are placed on the scalp and the changes in electric waves released by the brain are recorded as Electroencephalography (EEG) signals. In this work, we propose the use of generative adversarial networks and musigma methods to augment the EEG signals. Some of the existing deep learning methods such as convolutional neural network and recurrent neural network for classification of the EEG signals are implemented and their classification performance is examined with and without data augmentation. It is shown that the use of data augmentation can improve the performance of the EEG signal classification with deep learning models to a considerable extend.
{"title":"Motor Imagery Brain Activity Recognition through Data Augmentation using DC-GANs and Mu-Sigma","authors":"Abhishek Khoyani, Harshdeep Kaur, Marzieh Amini, H. Sadreazami","doi":"10.1109/SENSORS52175.2022.9967231","DOIUrl":"https://doi.org/10.1109/SENSORS52175.2022.9967231","url":null,"abstract":"The brain-computer interface is a technology that allows a machine to connect with the human brain and work based on the commands released by thoughts and activities of the brain. Electrodes are placed on the scalp and the changes in electric waves released by the brain are recorded as Electroencephalography (EEG) signals. In this work, we propose the use of generative adversarial networks and musigma methods to augment the EEG signals. Some of the existing deep learning methods such as convolutional neural network and recurrent neural network for classification of the EEG signals are implemented and their classification performance is examined with and without data augmentation. It is shown that the use of data augmentation can improve the performance of the EEG signal classification with deep learning models to a considerable extend.","PeriodicalId":120357,"journal":{"name":"2022 IEEE Sensors","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122494003","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}
Pub Date : 2022-10-30DOI: 10.1109/SENSORS52175.2022.9967191
Jaime Aru, Erik Verreycken, D. Laurijssen, J. Steckel
In the last decades our never-ending desire for space exploration has grown exponentially. In this endeavour, one of the major points of interest is the red planet Mars. To autonomously navigate the Martian terrains a combination of optical sensors (LiDAR, Camera) are used in the latest NASA Perseverance Rover. However, the harsh Martian climate and dust storms can significantly impair the accuracy of these sensors due to their use of light as a medium. By utilising a 3D sonar sensor, which is not affected by bad visibility, we can attempt to reduce navigation issues. However, because of the many differences between the Earth and Mars (e.g. temperature, atmospheric pressure…), a degradation in performance can be expected for the 3D sonar sensor in comparison to its performance on Earth. We developed a simulation which can give us an estimate of the performance differences between a 3D sonar on Earth and one on Mars. This simulation is then used to asses performance in different realistic scenarios, like high winds and component failure. A Martian sonar would have reduced range compared to its terrestrial counterpart, but we believe it to be a worthwhile addition to current Mars rover's navigation methods.
{"title":"3D Sonar on Mars","authors":"Jaime Aru, Erik Verreycken, D. Laurijssen, J. Steckel","doi":"10.1109/SENSORS52175.2022.9967191","DOIUrl":"https://doi.org/10.1109/SENSORS52175.2022.9967191","url":null,"abstract":"In the last decades our never-ending desire for space exploration has grown exponentially. In this endeavour, one of the major points of interest is the red planet Mars. To autonomously navigate the Martian terrains a combination of optical sensors (LiDAR, Camera) are used in the latest NASA Perseverance Rover. However, the harsh Martian climate and dust storms can significantly impair the accuracy of these sensors due to their use of light as a medium. By utilising a 3D sonar sensor, which is not affected by bad visibility, we can attempt to reduce navigation issues. However, because of the many differences between the Earth and Mars (e.g. temperature, atmospheric pressure…), a degradation in performance can be expected for the 3D sonar sensor in comparison to its performance on Earth. We developed a simulation which can give us an estimate of the performance differences between a 3D sonar on Earth and one on Mars. This simulation is then used to asses performance in different realistic scenarios, like high winds and component failure. A Martian sonar would have reduced range compared to its terrestrial counterpart, but we believe it to be a worthwhile addition to current Mars rover's navigation methods.","PeriodicalId":120357,"journal":{"name":"2022 IEEE Sensors","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128526179","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}
Pub Date : 2022-10-30DOI: 10.1109/SENSORS52175.2022.9967274
Hamed Nikfarjam, S. Sheikhlari, S. Pourkamali
This work describes a simple low-cost method to prevent stiction in low-stiffness suspended microstructures via naphthalene sublimation. Different microstructure types with different lengths and therefore different stiffness were fabricated and released using this technique. The results show great improvement when compared to water release. The method uses naphthalene crystal sediments acting as temporary support underneath and between suspended microstructures during solvent evaporation. Results show a significant reduction of stiction compared to similar structures released and dried without this procedure.
{"title":"Stiction Reduction in MEMS Fabrication via Naphthalene Sublimation","authors":"Hamed Nikfarjam, S. Sheikhlari, S. Pourkamali","doi":"10.1109/SENSORS52175.2022.9967274","DOIUrl":"https://doi.org/10.1109/SENSORS52175.2022.9967274","url":null,"abstract":"This work describes a simple low-cost method to prevent stiction in low-stiffness suspended microstructures via naphthalene sublimation. Different microstructure types with different lengths and therefore different stiffness were fabricated and released using this technique. The results show great improvement when compared to water release. The method uses naphthalene crystal sediments acting as temporary support underneath and between suspended microstructures during solvent evaporation. Results show a significant reduction of stiction compared to similar structures released and dried without this procedure.","PeriodicalId":120357,"journal":{"name":"2022 IEEE Sensors","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129054583","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}
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