An axial flow cyclone for removing nanoparticles was tested for collection efficiency. Data were validated numerically in vacuum conditions of several Torrs, with flow rates of 0.35-0.57 slpm. The experimental cutoff aerodynamic diameter of the cyclone ranged from 21.7 to 49.8 nm. A 3-D numerical simulation was conducted first to calculate detailed flow and pressure fields, then a Brownian Dynamics simulation was done to determine the collection efficiency of nanoparticles. Both centrifugal force and Brownian diffusion were taken into account. The simulated results for both pressure drop and cutoff aerodynamic diameter are in good agreement with the experimental data. In comparison, previous theories using simplified tangential flow field assumption are not able to predict collection efficiencies accurately. The numerical model developed in this study can facilitate cyclone design to classify valuable nanopowders below a certain diameter, or to remove toxic nanoparticles from the vacuum exhaust of process chambers commonly used in high-tech industries.
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http://dx.doi.org/10.1021/es060518o | DOI Listing |
Artif Organs
January 2025
BioCirc Research Laboratory, School of Biomedical Engineering, Science, and Health Systems, Drexel University, Philadelphia, Pennsylvania, USA.
Background: Safe and effective pediatric blood pumps continue to lag far behind those developed for adults. To address this growing unmet clinical need, we are developing a hybrid, continuous-flow, magnetically levitated, pediatric total artificial heart (TAH). Our hybrid TAH design, the Dragon Heart (DH), integrates both an axial flow and centrifugal flow blood pump within a single, compact housing.
View Article and Find Full Text PDFSensors (Basel)
December 2024
Department of Biomedical Engineering, Army Medical University, The Third Military Medical University, Chongqing 400038, China.
Magnetic induction phase shift is a promising technology for the detection of cerebral hemorrhage, owing to its nonradioactive, noninvasive, and real-time detection properties. To enhance the detection sensitivity and linearity, a zero-flow sensor was proposed. The uniform primary magnetic field and its counteraction were achieved.
View Article and Find Full Text PDFMaterials (Basel)
January 2025
School of Mining Engineering, Heilongjiang University of Science and Technology, Harbin 150022, China.
The cavitation water jet cleaning and coating removal technique represents an innovative sustainable method for cleaning and removing coatings, with the nozzle serving as a crucial component of this technology. Developing an artificially submerged nozzle with a reliable structure and excellent cavitation performance is essential for enhancing cavitation water jets' cleaning and coating removal efficacy in an atmosphere environment (non-submerged state). This study is based on the shear flow cavitation mechanism of an angular nozzle, the resonance principle of an organ pipe, and the jet pump principle.
View Article and Find Full Text PDFMaterials (Basel)
December 2024
Hubei Key Laboratory of Advanced Technology for Automotive Components, Wuhan University of Technology, Wuhan 430070, China.
Through the ferrite single-phase parameters of M50 bearing steel obtained based on nanoindentation experiments and the representative volume element (RVE) model established based on the real microstructure of M50, this paper established a multiscale finite element model for the cold ring rolling of M50 and verified its accuracy. The macroscale and mesoscale flow behaviors of the ring during the cold rolling deformation process were examined and explained. The macroscopic flow behavior demonstrated that the stress distribution was uniform following rolling.
View Article and Find Full Text PDFPhys Med Biol
January 2025
The Key Laboratory of Biomedical Information Engineering of Ministry of Education, Department of Biomedical Engineering, School of life Science and Technology, Xi'an Jiaotong University, Xi'an, People's Republic of China.
Estimating the high-resolution (HR) blood flow velocity and pressure fields for the diagnosis and treatment of vascular diseases remains challenging.. In this study, a physics-informed neural network (PINN) with a refined mapping capability was combined with ultrafast ultrasound image velocimetry (u-UIV) to predict HR hemodynamic parameters.
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