The classes and forms of antibiotics directly determine their ecotoxicity and environmental chemical behavior, and developing a sensor array for simultaneous and in situ detection of antibiotics is highly anticipated. In this study, different morphologies of g-CN with different fluorescence properties and peroxidase activity were prepared by regulating the degree of interlayer stacking and planar connectivity. Subsequently, in order to enhance its enzyme activity and amplify the differences in response signals to different antibiotics, three morphologies of g-CN/MIL-101(Fe) were prepared by in situ growth of equivalent amounts of MIL-101(Fe) on g-CN, respectively. The sensor array constructed based on the cross-response signals between g-CN/MIL-101(Fe) and antibiotics not only realized the simultaneous detection of quinolones, furans, tetracyclines, and lincomamides but also could efficiently identify their seven different forms. In the range of 0.2-0.8 ppm, the minimum detection limit for antibiotics was 12 ppb. In addition, the recovery experiments of multicomponent-mixed antibiotics in environmental samples show that the recovery rate remained at 91.42-107.59%, confirming the reliability and practicality of the sensor array. This study not only revealed the influence of crystal morphology regulation on the optical properties and enzyme activities of nanozymes, but also provided support for tracing, ecological remediation, and in situ environmental chemical behavior research of antibiotics.
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http://dx.doi.org/10.1021/acs.analchem.3c02911 | DOI Listing |
Sensors (Basel)
December 2024
Department of Electrical and Computer Engineering, University of Manitoba, Winnipeg, MB R3T 5V6, Canada.
This paper presents a lens-free imaging approach utilizing an array of light sources, capable of measuring the dielectric properties of many particles simultaneously. This method employs coplanar electrodes to induce velocity changes in flowing particles through dielectrophoretic forces, allowing the inference of individual particle properties from differential velocity changes. Both positive and negative forces are detectable.
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December 2024
Center for Bioelectronics and Biosensors, Biodesign Institute, Arizona State University, 1001 S McAllister Ave, Tempe, AZ 85281, USA.
Alzheimer's disease (AD) and Alzheimer's Related Dementias (ADRD) are projected to affect 50 million people globally in the coming decades. Clinical research suggests that Mild Cognitive Impairment (MCI), a precursor to dementia, offers a critical window of opportunity for lifestyle interventions to delay or prevent the progression of AD/ADRD. Previous research indicates that lifestyle changes, including increased physical exercise, reduced caloric intake, and mentally stimulating activities, can reduce the risk of MCI.
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December 2024
Department of Electrical and Computer Engineering, Bucknell University, Lewisburg, PA 17837, USA.
Micropillar array electrodes offer several advantages, such as enhanced mass transport, lower detection limits, and the potential for miniaturization, making them instrumental in the design and fabrication of electrochemical biosensors. The performance of these biosensors is influenced by electrode geometry, including parameters like shape and height, which affect surface area and overall sensitivity. In this study, we designed a microfluidic electrochemical biosensor featuring micropillar array electrodes, modeled in COMSOL Multiphysics.
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December 2024
Electronics Technology Department, University of Madrid Carlos III, 28911 Leganes, Spain.
This paper explores the implementation of a VCO-based ADC, achieving an ENOB of 12 bits with 1 MHz of a sampling rate in the audio bandwidth. The solution exploits the scalability and PVT invariance of a novel digital-to-frequency converter to reduce the size and consumed power. The architecture has been validated in a 130 nm CMOS technology node displaying a power consumption of 105.
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December 2024
CommSensLab-UPC, Universitat Politècnica de Catalunya-BarcelonaTech, 08034 Barcelona, Spain.
Interferometric radiometers operating at L-band, such as ESA's SMOS mission, enable crucial Earth observations providing high-resolution measurements of soil moisture, ocean salinity, and other geophysical parameters. However, the increasing electromagnetic spectrum utilization has led to significant Radio Frequency Interference (RFI) challenges, particularly critical given the sensors' fine temperature resolution requirements of less than 1 K. This work presents the hardware implementation of an advanced RFI detection and mitigation algorithm specifically designed for interferometric radiometers, targeting future L-band missions.
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