New details on selectivity and sensitivity of fully integrated CMOS-based capacitive chemical microsensor systems are revealed. These microsystems have been developed to detect volatile organics in ambient air and rely on polymeric sensitive layers. The sensitivity and selectivity changes induced by thickness variation of the sensitive polymer layer allow for tuning of the layer parameters to achieve desired sensor features. Cross-sensitivity to interfering agents can be drastically reduced, as is shown for two important cases: (a). rendering the capacitive sensor insensitive to a low-dielectric-constant analyte (lower than that of the polymer) and (b). reducing the influence of a high-dielectric-constant analyte, such as water, on the sensor response. The second case is of vital importance for capacitive sensors, since water is omnipresent and evokes large capacitive sensor signals. The thickness-induced selectivity is explained as a combination of dielectric constant change and swelling and has been confirmed by measurements. Experimentally determined sensitivities qualitatively and quantitatively coincide with the calculated values implying understanding of the sensing mechanism.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1021/ac0352272 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Use of the FHTHWA Index as a Novel Approach for Predicting the Incidence of Diabetes in a Japanese Population Without Diabetes: Data Analysis Study.
JMIR Med Inform
January 2025
Department of Endocrinology and Metabolism, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China.
Background: Many tools have been developed to predict the risk of diabetes in a population without diabetes; however, these tools have shortcomings that include the omission of race, inclusion of variables that are not readily available to patients, and low sensitivity or specificity.
Objective: We aimed to develop and validate an easy, systematic index for predicting diabetes risk in the Asian population.
Methods: We collected the data from the NAGALA (NAfld [nonalcoholic fatty liver disease] in the Gifu Area, Longitudinal Analysis) database.
Optimisation of low and ultra-low dose scanning protocols for ultra-extended field of view PET in a real-world clinical setting.
Cancer Imaging
January 2025
Melbourne Theranostic Innovation Centre, Level 8, 14-20 Blackwood St, North Melbourne, VIC, 3051, Australia.
True total-body and extended axial field-of-view (AFOV) PET/CT with 1m or more of body coverage are now commercially available and dramatically increase system sensitivity over conventional AFOV PET/CT. The Siemens Biograph Vision Quadra (Quadra), with an AFOV of 106cm, potentially allows use of significantly lower administered radiopharmaceuticals as well as reduced scan times. The aim of this study was to optimise acquisition protocols for routine clinical imaging with FDG on the Quadra the prioritisation of reduced activity given physical infrastructure constraints in our facility.
View Article and Find Full Text PDFAI-based analysis of fetal growth restriction in a prospective obstetric cohort quantifies compound risks for perinatal morbidity and mortality and identifies previously unrecognized high risk clinical scenarios.
BMC Pregnancy Childbirth
January 2025
Department of Obstetrics and Gynecology, Division of Maternal-Fetal Medicine, University of Utah Health, 30 N. Mario Capecchi Dr., Level 5 South, Salt Lake City, UT, 84132, USA.
Background: Fetal growth restriction (FGR) is a leading risk factor for stillbirth, yet the diagnosis of FGR confers considerable prognostic uncertainty, as most infants with FGR do not experience any morbidity. Our objective was to use data from a large, deeply phenotyped observational obstetric cohort to develop a probabilistic graphical model (PGM), a type of "explainable artificial intelligence (AI)", as a potential framework to better understand how interrelated variables contribute to perinatal morbidity risk in FGR.
Methods: Using data from 9,558 pregnancies delivered at ≥ 20 weeks with available outcome data, we derived and validated a PGM using randomly selected sub-cohorts of 80% (n = 7645) and 20% (n = 1,912), respectively, to discriminate cases of FGR resulting in composite perinatal morbidity from those that did not.
Explore the factors related to the death of offspring under age five and appraise the hazard of child mortality using machine learning techniques in Bangladesh.
BMC Public Health
January 2025
Department of Statistics and Data Science, Jahangirnagar University, Dhaka, 1342, Bangladesh.
Background: Child mortality is a reliable and significant indicator of a nation's health. Although the child mortality rate in Bangladesh is declining over time, it still needs to drop even more in order to meet the Sustainable Development Goals (SDGs). Machine Learning models are one of the best tools for making more accurate and efficient forecasts and gaining in-depth knowledge.
View Article and Find Full Text PDFUltrasensitive and selective impedance paper-based analytical device through Dual-C imprinted sensor for determination of carcinoembryonic antigen and C-reactive protein.
Mikrochim Acta
January 2025
Department of Chemistry and Center of Excellence for Innovation in Chemistry, Faculty of Science, Ubon Ratchathani University, Ubon Ratchathani, 34190, Thailand.
Carcinoembryonic antigen (CEA) and C-reactive protein (CRP) are biomacromolecules known as cancer and inflammatory markers. Thus, they play a crucial role in early cancer diagnosis, post-treatment recurrence detection, and tumor risk assessment. This paper describes the development of an ultrasensitive and selective imprinted paper-based analytical device (PAD) as impedance sensor for determination of CEA and CRP in serum samples for point-of-care testing (POCT).
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!