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To our knowledge, a novel experimental method is proposed to remotely measure the droplet concentration in a water spray using a short-range elastic backscatter lidar. A specific calibration technique is proposed to determine the lidar radiometric constant, enabling the conversion of lidar signals into attenuated backscatter signals and, ultimately, into aerosol properties, including average volume concentration. To our knowledge, a new formulation for the lidar constant is proposed, using the total spray transmittance and the particle size distribution of the water droplets, measured using the established laser diffraction technique. The lidar constant value is then compared and discussed in relation to an alternative method based on a Lambertian surface. Ultimately, the attenuated backscatter signals, calculated using the calibration constant, enable the estimation of the average volume concentrations of droplets in the spray under various injection conditions of a full-cone pneumatic atomizer. The retrieved concentrations range between 10 and 10 droplets per cubic meter, which are comparable to those obtained from laser diffraction measurements, especially for sprays with large droplets, , with a Sauter mean diameter greater than 50 µm.
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http://dx.doi.org/10.1364/OE.563691 | DOI Listing |
J Chem Phys
September 2025
Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA.
We study how protein condensates respond to a site of active RNA transcription (i.e., a gene promoter) due to electrostatic protein-RNA interactions.
View Article and Find Full Text PDFLangmuir
September 2025
Process Engineering in Life Science Engineering, HTW Berlin, Wilhelminenhofstraße 75 A, 12459 Berlin, Germany.
Pickering emulsions (PEs), where water-in-oil (w/o) droplets are stabilized by nanoparticles (NPs), offer a promising platform for biocatalysis by providing a large interfacial area crucial for efficient substrate conversion. While several lipase catalyzed reactions in PEs have been demonstrated, the exact interfacial structure is unknown. This study focuses on the interfacial network formed by NPs and lipase (CRL) at the octanol/water-interface by varying pH and NP charge.
View Article and Find Full Text PDFLangmuir
September 2025
ThAMeS Multiphase, Department of Chemical Engineering, University College London, Torrington Place, London WC1E 7JE, U.K.
The evaporation of surfactant-laden sessile droplets has widespread applications in both natural and technological contexts. This study explores the evaporation of droplets containing a nonionic surfactant (tristyrylphenol ethoxylates (EOT)), an anionic surfactant (sodium benzenesulfonate with alkyl chain lengths of C-C (NaDDBS)), and their mixtures at / mole ratios of 0.01, 0.
View Article and Find Full Text PDFOpen Life Sci
August 2025
Botany and Microbiology Department, Faculty of Science, Al-Azhar University, Nasr City, Cairo, 11884, Egypt.
Although citrus essential oils, including lemongrass essential oil, have antibacterial, anti-biofilm, and antioxidant properties, their biological instability and poor water solubility render them unsuitable for industrial usage. Thus, this study aimed to prepare both lemongrass essential oil emulsion (LEO-E) and lemongrass essential oil nanoemulsion (LEO-NE), and evaluate their different bioactivities. Characterization by gas chromatography-mass spectroscopy (GC-MS) and evaluation of antimicrobial, antibiofilm, antioxidant, and anticancer activities were carried out.
View Article and Find Full Text PDFAn integrated approach is proposed to rapidly evaluate the effects of anticancer treatments in 3D models, combining a droplet-based microfluidic platform for spheroid formation and single-spheroid chemotherapy application, label-free morphological analysis, and machine learning to assess treatment response. Morphological features of spheroids, such as size and color intensity, are extracted and selected using the multivariate information-based inductive causation algorithm, and used to train a neural network for spheroid classification into viability classes, derived from metabolic assays performed within the same platform as a benchmark. The model is tested on Ewing sarcoma cell lines and patient-derived xenograft (PDX) cells, demonstrating robust performance across datasets.
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