Humidity sensing has been offering a noticeable contribution in different industrial, medical, and agricultural activities. Here, graphene quantum dots doped with polyaniline (PANI) and MnO were successfully prepared. The synthesized system is exposed to a set of structural, morphological, and optical investigations. The apparent crystallite size is less than 30 nm, reflecting the nanoscale of the structure, and thus validating the preparation route as evident on XRD pattern. SEM images show a fibrous structure where polyaniline dominates and covers most of the structure's surface. The evident bands of the FTIR spectrum are designated to the component used in synthesis confirming the chemical structure of the fabricated system. The humidity sensing study of the synthesized structure is carried out through a wide range of relative humidity (RH) levels range of 11-97%. The response and recovery times of the fabricated structure are found to be around 120 and 220s, respectively.
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http://dx.doi.org/10.1038/s41598-023-48928-2 | DOI Listing |
Phys Chem Chem Phys
January 2025
Temperature and Humidity Metrology, CSIR-National Physical Laboratory, Dr K. S. Krishnan Marg, New Delhi, 110012, India.
In this study, we have proposed an advanced humidity sensor based on a composite of chitosan (CS) and graphene oxide (GO), prepared by the drop casting method. Graphene oxide-chitosan (GO-CS) films with varying volumetric ratios, along with pure GO and CS films, were prepared and extensively characterized using XRD, Raman, FTIR, SEM, XPS, and water contact angle to study their structural and morphological properties. Comparative analysis of humidity sensing parameters of all prepared films revealed that the film with a volumetric ratio of 4 : 1 (GOCS-2) performs best among all of them, which is attributed to the synergistic interaction between GO and CS.
View Article and Find Full Text PDFNanoscale Adv
January 2025
College of BioNano Technology, Gachon University Gyeonggi 13120 Republic of Korea
Sensing of hazardous gases has an important role in ensuring safety in a variety of industries as well as environments. Mainly produced by the combustion of fossil fuels and other organic matter, ethanol is a dangerous gas that endangers human health and the environment. Stability and sensing sensitivity are major considerations when designing gas sensors.
View Article and Find Full Text PDFSci Data
January 2025
Key Laboratory of Humid Subtropical Eco-Geographical Process of Ministry of Education, School of Geographical Sciences, Fujian Normal University, Fuzhou, 350117, China.
Deforestation-induced forest loss largely affects both the carbon budget and ecosystem services. Subsequent forest regrowth plays a crucial role in ecosystem restoration and carbon replenishment. However, there is an absence of comprehensive datasets explicitly delineating the forest regrowth following deforestation.
View Article and Find Full Text PDFSensors (Basel)
January 2025
Department of Biomedical Engineering, Yonsei University, Wonju 26493, Republic of Korea.
This study presents the fabrication of a sustainable flexible humidity sensor utilizing chitosan derived from mealworm biomass as the primary sensing material. The chitosan-based humidity sensor was fabricated by casting chitosan and polyvinyl alcohol (PVA) films with interdigitated copper electrodes, forming a laminate composite suitable for real-time, resistive-type humidity detection. Comprehensive characterization of the chitosan film was performed using Fourier-transform infrared (FTIR) spectroscopy, contact angle measurements, and tensile testing, which confirmed its chemical structure, wettability, and mechanical stability.
View Article and Find Full Text PDFSensors (Basel)
January 2025
Department of Optical Engineering, Utsunomiya University, 7-2-1 Yoto, Utsunomiya 321-8585, Japan.
We describe the various steps of a gas imaging algorithm developed for detecting, identifying, and quantifying gas leaks using data from a snapshot infrared spectral imager. The spectral video stream delivered by the hardware allows the system to combine spatial, spectral, and temporal correlations into the gas detection algorithm, which significantly improves its measurement sensitivity in comparison to non-spectral video, and also in comparison to scanning spectral imaging. After describing the special calibration needs of the hardware, we show how to regularize the gas detection/identification for optimal performance, provide example SNR spectral images, and discuss the effects of humidity and absorption nonlinearity on detection and quantification.
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