Keyword search (4,163 papers available)

"Nerguizian V" Authored Publications:

Title Authors PubMed ID
1 Synthesis and Characterization of CNC/CNF/rGO Composite Films for Advanced Functional Applications Ramezani G; Stiharu I; van de Ven TGM; Ramezani H; Nerguizian V; 41900273
ENCS
2 Lasso Model-Based Optimization of CNC/CNF/rGO Nanocomposites Ramezani G; Silva IO; Stiharu I; Ven TGMV; Nerguizian V; 40283268
ENCS
3 A synthetic model of bioinspired liposomes to study cancer-cell derived extracellular vesicles and their uptake by recipient cells López RR; Ben El Khyat CZ; Chen Y; Tsering T; Dickinson K; Bustamante P; Erzingatzian A; Bartolomucci A; Ferrier ST; Douanne N; Mounier C; Stiharu I; Nerguizian V; Burnier JV; 40069225
ENCS
4 Advancements in Hybrid Cellulose-Based Films: Innovations and Applications in 2D Nano-Delivery Systems Ramezani G; Stiharu I; van de Ven TGM; Nerguizian V; 38667550
ENCS
5 Advancement in Biosensor Technologies of 2D MaterialIntegrated with Cellulose-Physical Properties Ramezani G; Stiharu I; van de Ven TGM; Nerguizian V; 38258201
ENCS
6 A review on microfluidic-assisted nanoparticle synthesis, and their applications using multiscale simulation methods Agha A; Waheed W; Stiharu I; Nerguizian V; Destgeer G; Abu-Nada E; Alazzam A; 36800044
CONCORDIA
7 Comparative Evaluation of Artificial Neural Networks and Data Analysis in Predicting Liposome Size in a Periodic Disturbance Micromixer Ocampo I; López RR; Camacho-León S; Nerguizian V; Stiharu I; 34683215
ENCS
8 Numerical and Experimental Validation of Mixing Efficiency in Periodic Disturbance Mixers López RR; Sánchez LM; Alazzam A; Burnier JV; Stiharu I; Nerguizian V; 34577745
ENCS
9 Surface Response Based Modeling of Liposome Characteristics in a Periodic Disturbance Mixer. López RR, Ocampo I, Sánchez LM, Alazzam A, Bergeron KF, Camacho-León S, Mounier C, Stiharu I, Nerguizian V 32106424
ENCS
10 Dielectrophoresis Multipath Focusing of Microparticles through Perforated Electrodes in Microfluidic Channels. Alazzam A, Al-Khaleel M, Riahi MK, Mathew B, Gawanmeh A, Nerguizian V 31394810
ENCS
11 Fabrication of Porous Gold Film Using Graphene Oxide as a Sacrificial Layer. Alazzam A, Alamoodi N, Abutayeh M, Stiharu I, Nerguizian V 31323903
ENCS
12 The effect of dielectrophoresis on living cells: crossover frequencies and deregulation in gene expression. Nerguizian V, Stiharu I, Al-Azzam N, Yassine-Diab B, Alazzam A 31099354
ENCS

 

Title:Numerical and Experimental Validation of Mixing Efficiency in Periodic Disturbance Mixers
Authors:López RRSánchez LMAlazzam ABurnier JVStiharu INerguizian V
Link:https://pubmed.ncbi.nlm.nih.gov/34577745/
DOI:10.3390/mi12091102
Publication:Micromachines
Keywords:image processingmicrofluidicsmicromixersmixing efficiencynumerical model
PMID:34577745 Category: Date Added:2021-09-28
Dept Affiliation: ENCS
1 Department of Electrical Engineering, École de Technologie Supérieure, 1100 Notre Dame West, Montreal, QC H3C 1K3, Canada.
2 Cancer Research Program, RI-MUHC, McGill University, 1001 Decarie Boulevard, Montreal, QC H4A 3J1, Canada.
3 Department of Engineering, Universidad Autónoma de Querétaro, Cerro de las Campanas, Santiago de Querétaro 76010, Querétaro, Mexico.
4 Department of Mechanical Engineering, Khalifa University, Abu Dhabi 127788, United Arab Emirates.
5 Department of Mechanical and Industrial Engineering, Concordia University, 1515 Saint Catherine West, Montreal, QC H3G 1M8, Canada.

Description:

The shape and dimensions of a micromixer are key elements in the mixing process. Accurately quantifying the mixing efficiency enables the evaluation of the performance of a micromixer and the selection of the most suitable one for specific applications. In this paper, two methods are investigated to evaluate the mixing efficiency: a numerical model and an experimental model with a software image processing technique. Using two methods to calculate the mixing efficiency, in addition to corroborating the results and increasing their reliability, creates various possible approaches that can be selected depending on the circumstances, resources, amount of data to be processed and processing time. Image processing is an easy-to-implement tool, is applicable to different programming languages, is flexible, and provides a quick response that allows the calculation of the mixing efficiency using a process of filtering of images and quantifying the intensity of the color, which is associated with the percentage of mixing. The results showed high similarity between the two methods, with a difference ranging between 0 and 6% in all the evaluated points.





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