In this work, we report a two-member fluorescence array sensor for the effective discrimination of five classes of explosives. This smallest array sensor is composed of tricarbazole-based nanofibers (sensor member 1) and nanoribbons (sensor member 2) deposited as two film bands in a quartz tube. On the basis of a simple comparison of the resulting fluorescence quenching ratios between two sensor members and the response reversibility upon exposure to vaporized explosives, five classes of explosives can be sensitively detected and easily discriminated. This array sensor that has only two sensor members and no complex data analysis represents a new design way for discrimination of a broad class of explosives.
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http://dx.doi.org/10.1021/acs.analchem.7b04083 | DOI Listing |
Nat Commun
January 2025
Toyota Central R&D Labs. Inc.; 41-1, Yokomichi, Nagakute, Aichi, Japan.
We propose a network architecture for electronic skin with an extensive sensor array-crucial for enabling robots to perceive their environment and interact effectively with humans. Fault tolerance is essential for electronic skins on robot exteriors. Although self-healing electronic skins targeting minor damages are studied using material-based approaches, substantial damages such as severe cuts necessitate re-establishing communication pathways, traditionally performed with high-functionality microprocessor sensor nodes.
View Article and Find Full Text PDFBiosens Bioelectron
January 2025
Department of Analytical Chemistry, College of Chemistry, Jilin University, Changchun, 130012, China. Electronic address:
As an emerging class of extended crystalline organic materials, covalent organic framework (COF)-based aggregation-induced emission luminogen (AIE-gen) exhibited encouraging emissive properties. In this work, 4',4'',4‴,4‴'-(1,1,2,2-Ethenetetrayl)tetra(4-biphenylcarbaldehyde) (ETBC) as AIEgen was used to prepare AIE-COF (ET-COF-COOH) luminescent nanoprobe. ETBC and 1,3,5-Tris(4-aminophenyl)benzene (TAPB) had an extended π electronic system that allowed electron delocalization and overlapping transport.
View Article and Find Full Text PDFAnal Chem
January 2025
Department of Chemistry, College of Sciences, Nanjing Agricultural University, Nanjing, Jiangsu 210095, People's Republic of China.
Accurate discrimination of complicated glycosaminoglycans is a challenging but meaningful task for ensuring their safe use in clinics. With the purpose of reducing the production cost of sensor arrays for glycosaminoglycans, three fluorescence turn-on sensors named , , and were readily synthesized by simple alkylation of the pyridyl units of the π-extended AIEgen, namely, tetra-(4-pyridylphenyl) ethylene. The designed sensors are cross-reactive toward tested glycosaminoglycans including heparin, chondroitin sulfate, hyaluronic acid, and dextran sulfate, whose mechanism could be ascribed to the multivalent electrostatic, CH···π, and hydrophobic interactions between the sensors and different glycosaminoglycans to form corresponding fluorescent aggregates.
View Article and Find Full Text PDFACS Nano
January 2025
CAS Key Laboratory of Magnetic Materials and Devices & Zhejiang Province Key Laboratory of Magnetic Materials and Application Technology, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo 315201, P. R. China.
Flexible magnetic sensors, which have advantages such as deformability, vector field sensing, and noncontact detection, are an important branch of flexible electronics and have significant applications in fields such as magnetosensitive electronic skin. Human skin surfaces have complicated deformations, which pose a demand for magnetic sensors that can withstand omnidirectional strain while maintaining stable performance. However, existing flexible magnetic sensor arrays can only withstand stretching along specific directions and are prone to failure under complicated deformations.
View Article and Find Full Text PDFData Brief
February 2025
Faculty of Civil and Environmental Engineering, Technion, Haifa 320003, Israel.
Effective spatio-temporal measurements of water surface elevation (water waves) in laboratory experiments are essential for scientific and engineering research. Existing techniques are often cumbersome, computationally heavy and generally suffer from limited wavenumber/frequency response. To address these challenges a novel method was developed, using polarization filter equipped camera as the main sensor and Machine Learning (ML) algorithms for data processing [1,2].
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