pH is one of the important parameters of a biological microenvironment, which is closely related to cell growth, development, vitality, division, and differentiation. Monitoring the pH of a microenvironment is helpful to monitor the cell metabolism as well as to understand the cellular life cycle. The sensitivity of liquid metals (LMs) to hydrogen ions has aroused our interest. Here, we propose a novel but facile pH sensor using liquid gallium (LM for short) droplet morphological change as the readout. The pH sensing characteristics of the LM droplet were examined, especially the shape response. LM can form solid native oxide skin rapidly in oxygenated solution, and the oxide layer will be removed in acidic or alkaline solutions, which will cause a great change in surface tension. The phenomenon is the change of LM morphology from macroscopic observation. We explored the electrochemical characteristics of LM at different pH values, explained the mechanism of surface change, and calibrated the relationship curve between LM morphology and pH and the interference of impurity ions on the sensor. Finally, we proposed a detection algorithm for the LM pH morphology sensor and tried to automatically detect pH with a mobile app, which was applied to the pH detection of cell culture solution. We believe that the response characteristics of LM to hydrogen ions have great potential in microenvironment detection.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1021/acs.analchem.2c04357 | DOI Listing |
Anal Chem
January 2025
Center of Advanced Analysis and Gene Sequencing, Key Laboratory of Molecular Sensing and Harmful Substances Detection Technology, Zhengzhou University, Kexue Avenue 100, Zhengzhou, Henan 450001, P. R. China.
A novel sensing platform was constructed for the recognition and identification of dihydroxybenzene isomers based on the MOF-0.02TEA fluorescence sensor with the morphology of nanosheet microspheres through coordination modulation. Based on the sensing principle that the amino group on the MOF-0.
View Article and Find Full Text PDFSensors (Basel)
January 2025
School of Mechanical and Electrical Engineering, China Jiliang University, Hangzhou 310018, China.
Breast cancer (BC) is one of the most lethal cancers worldwide, and its early diagnosis is critical for improving patient survival rates. However, the extraction of key information from complex medical images and the attainment of high-precision classification present a significant challenge. In the field of signal processing, texture-rich images typically exhibit periodic patterns and structures, which are manifested as significant energy concentrations at specific frequencies in the frequency domain.
View Article and Find Full Text PDFSensors (Basel)
December 2024
CNR-IPCF, Institute for Chemical-Physical Processes Messina, 98158 Messina, Italy.
Zinc oxide nanoparticles (ZnO NPs) with varying levels of nitrogen (N) doping were synthesized using a straightforward sol-gel approach. The morphology and microstructure of the N-doped ZnO NPs were examined through techniques such as SEM, XRD, photoluminescence, and Raman spectroscopy. The characterization revealed visible changes in the morphology and microstructure resulting from the incorporation of nitrogen into the ZnO lattice.
View Article and Find Full Text PDFSensors (Basel)
December 2024
Pediatric Neurology, ERN-RND, Euro-NMD, Vall d'Hebron Institut de Recerca (VHIR), Hospital Universitari Vall d'Hebron, Vall d'Hebron Barcelona Hospital Campus, Passeig Vall d'Hebron 119-129, 08035 Barcelona, Spain.
We investigate the application of deep learning in comparing gait cycle time series from two groups of healthy children, each assessed in different gait laboratories. Both laboratories used similar gait analysis protocols with minimal differences in data collection. Utilizing a ResNet-based deep learning model, we successfully identified the source laboratory of each dataset, achieving a high classification accuracy across multiple gait parameters.
View Article and Find Full Text PDFSensors (Basel)
December 2024
State Grid Tianjin Electric Power Research Institute, Tianjin 300180, China.
Large oil-immersed transformers have metal-enclosed shells, making it difficult to visually inspect the internal insulation condition. Visual inspection of internal defects is carried out using a self-developed micro-robot in this work. Carbon trace is the main visual characteristic of internal insulation defects.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!