This paper reports a numerical and experimental study of acoustic streaming and micromixing in polydimethylsiloxane microchannels. The mixing between two fluids flowing in microchannels was evaluated through the following conditions: (1) using a 28 μm thick β-poly(vinylidene fluoride) (β-PVDF) as a piezoelectric transducer actuated with a 24 Vpp and 40 MHz sinusoidal voltage; (2) using different flow rates. The results suggest that the mixing length increases as the flow rate increases and that the acoustic streaming phenomenon leads to a reduction on the mixing length. The good qualitative agreement between numerical and experimental results is a valuable indicator to predict the mixing performance of microfluidic devices, for improving biological fluid analysis in diagnosis lab-on-a-chip devices.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1109/EMBC.2016.7592011 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Multiscale Numerical Study of Enhanced Ductility Ratios and Capacity in Carbon Fiber-Reinforced Polymer Concrete Beams for Safety Design.
Polymers (Basel)
January 2025
Department of Civil and Environmental Engineering, Ben-Gurion University of the Negev, Beer Sheva 8410501, Israel.
Rigid reinforced concrete (RC) frames are generally adopted as stiff elements to make the building structures resistant to seismic forces. However, a method has yet to be fully sought to provide earthquake resistance through optimizing beam and column performance in a rigid frame. Due to its high corrosion resistance, the integration of CFRP offers an opportunity to reduce frequent repairs and increase durability.
View Article and Find Full Text PDFVat photopolymerization (VPP) is an additive manufacturing method that requires the design of photocurable resins to act as feedstock and binder for the printing of parts, both monolithic and composite. The design of a suitable photoresin is costly and time-consuming. The development of one formulation requires the consumption of kilograms of costly materials, weeks of printing and performance testing, as well as the need to have developers with the expertise and knowledge of the materials used, making the development process cost thousands.
View Article and Find Full Text PDFAn Experimental Approach for Investigating Fatigue-Induced Debonding Propagation in Composite Stiffened Panels Using Thermographic Phase Mapping.
Polymers (Basel)
January 2025
Institute for Polymers Composites and Biomaterials, Italian National Research Council, Piazzale Enrico Fermi, 80055 Portici, NA, Italy.
This work introduces an experimental approach focused on investigating fatigue-driven debonding in a composite structure designed to simulate the complexity of a typical aeronautical panel. The debonding is placed between the skin and the stringer, and the structure has been tested under fatigue compression conditions. Using lock-in thermography, the damage evolution during fatigue cycles has been detailed monitored.
View Article and Find Full Text PDFNumerical Modelling of Hybrid Polymer Composite Frame for Selected Construction Parts and Experimental Validation of Mechanical Properties.
Polymers (Basel)
January 2025
Department of Material Science and Manufacturing Technology, Faculty of Engineering, Czech University of Life Sciences Prague, Kamycka 129, 16500 Prague, Czech Republic.
This article is a numerical and experimental study of the mechanical properties of different glass, flax and hybrid composites. By utilizing hybrid composites consisting of natural fibers, the aim is to eventually reduce the percentage usage of synthetic or man-made fibers in composites and obtain similar levels of mechanical properties that are offered by composites using synthetic fibers. This in turn would lead to greener composites being utilized.
View Article and Find Full Text PDFAn Embodied Intelligence System for Coal Mine Safety Assessment Based on Multi-Level Large Language Models.
Sensors (Basel)
January 2025
School of Communication and Information Engineering, Xi'an University of Science and Technology, Xi'an 710054, China.
Artificial intelligence (AI), particularly through advanced large language model (LLM) technologies, is reshaping coal mine safety assessment methods with its powerful cognitive capabilities. Given the dynamic, multi-source, and heterogeneous characteristics of data in typical mining scenarios, traditional manual assessment methods are limited in their information processing capacity and cost-effectiveness. This study addresses these challenges by proposing an embodied intelligent system for mine safety assessment based on multi-level large language models (LLMs) for multi-source sensor data.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!