We report a p24(HIV disease biomarker)detection assay using an MgO-based magnetic tunnel junction(MTJ)sensor and 20-nm magnetic nanoparticles.The MTJ array sensor with sensing area of 890×890μ2 possessing a sens...We report a p24(HIV disease biomarker)detection assay using an MgO-based magnetic tunnel junction(MTJ)sensor and 20-nm magnetic nanoparticles.The MTJ array sensor with sensing area of 890×890μ2 possessing a sensitivity of 1.39%/Oe was used to detect p24 antigens.It is demonstrated that the p24 antigens could be detected at a concentration of 0.01μg/ml.The development of bio-detection systems based on magnetic tunnel junction sensors with high-sensitivity will greatly benefit the early diagnosis of HIV.展开更多
The electrical tunneling sensors have excellent potential in the next generation of single-molecule measurement and sequencing technologies due to their high sensitivity and spatial resolution capabilities.Electrical ...The electrical tunneling sensors have excellent potential in the next generation of single-molecule measurement and sequencing technologies due to their high sensitivity and spatial resolution capabilities.Electrical tunneling signals that have been measured at a high sampling rate may provide detailed molecular information.Despite the extraordinarily large amount of data that has been gathered,it is still difficult to correlate signal transformations with molecular processes,which creates great obstacles for signal analysis.Machine learning is an effective tool for data analysis that is currently gaining more significance.It has demonstrated promising results when used to analyze data from single-molecule electrical measurements.In order to extract meaningful information from raw measurement data,we have combined intelligent machine learning with tunneling electrical signals.For the purpose of analyzing tunneling electrical signals,we investigated the clustering approach,which is a classic algorithm in machine learning.A clustering model was built that combines the advantages of hierarchical clustering and Gaussian mixture model clustering.Additionally,customized statistical algorithms were designed.It has been proven to efficiently gather molecular information and enhance the effectiveness of data analysis.展开更多
Magnetic sensors based on tunneling magnetoresistance(TMR)effect exhibit high sensitivity,small size,and low power consumption.They have gained a lot of attention and have potential applications in various domains.Thi...Magnetic sensors based on tunneling magnetoresistance(TMR)effect exhibit high sensitivity,small size,and low power consumption.They have gained a lot of attention and have potential applications in various domains.This study first introduces the development history and basic principles of TMR sensors.Then,a comprehensive description of TMR sensors linearization and Wheatstone bridge configuration is presented.Two key performance parameters,the field sensitivity and noise mechanisms,are considered.Finally,the emerging applications of TMR sensors are discussed.展开更多
基金President’s Fund of CUHKSZ,Longgang Key Laboratory of Applied Spintronics,at The Chinese University of Hong Kong,the National Natural Science Foundation of China(Grant Nos.11974298 and 61961136006)the Shenzhen Fundamental Research Fund,China(Grant No.JCYJ20170410171958839)Shenzhen Peacock Group Plan,China(Grant No.KQTD20180413181702403).
文摘We report a p24(HIV disease biomarker)detection assay using an MgO-based magnetic tunnel junction(MTJ)sensor and 20-nm magnetic nanoparticles.The MTJ array sensor with sensing area of 890×890μ2 possessing a sensitivity of 1.39%/Oe was used to detect p24 antigens.It is demonstrated that the p24 antigens could be detected at a concentration of 0.01μg/ml.The development of bio-detection systems based on magnetic tunnel junction sensors with high-sensitivity will greatly benefit the early diagnosis of HIV.
基金the National Natural Science Foundation of China(grant nos.62127818)Natural Science Foundation of Zhejiang Province(grant no.LR22F050003)Fundamental Research Funds for Central Universities。
文摘The electrical tunneling sensors have excellent potential in the next generation of single-molecule measurement and sequencing technologies due to their high sensitivity and spatial resolution capabilities.Electrical tunneling signals that have been measured at a high sampling rate may provide detailed molecular information.Despite the extraordinarily large amount of data that has been gathered,it is still difficult to correlate signal transformations with molecular processes,which creates great obstacles for signal analysis.Machine learning is an effective tool for data analysis that is currently gaining more significance.It has demonstrated promising results when used to analyze data from single-molecule electrical measurements.In order to extract meaningful information from raw measurement data,we have combined intelligent machine learning with tunneling electrical signals.For the purpose of analyzing tunneling electrical signals,we investigated the clustering approach,which is a classic algorithm in machine learning.A clustering model was built that combines the advantages of hierarchical clustering and Gaussian mixture model clustering.Additionally,customized statistical algorithms were designed.It has been proven to efficiently gather molecular information and enhance the effectiveness of data analysis.
基金financially supported by Beijing Municipal Science and Technology Project(No.Z201100004220002)the International Collaboration Project B16001+1 种基金the Key Research and Development Program of Shandong Province of China(No.2020S020201-01621)the Magnetic Sensor Innovation Platform from Laoshan District。
文摘Magnetic sensors based on tunneling magnetoresistance(TMR)effect exhibit high sensitivity,small size,and low power consumption.They have gained a lot of attention and have potential applications in various domains.This study first introduces the development history and basic principles of TMR sensors.Then,a comprehensive description of TMR sensors linearization and Wheatstone bridge configuration is presented.Two key performance parameters,the field sensitivity and noise mechanisms,are considered.Finally,the emerging applications of TMR sensors are discussed.