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Fluids
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Fluid Flows at the Nanoscale
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Fluid Flows at the Nanoscale

A special issue of Fluids (ISSN 2311-5521). This special issue belongs to the section "Mathematical and Computational Fluid Mechanics".

Deadline for manuscript submissions: closed (28 February 2022) | Viewed by 16244

Special Issue Editor

Dr. Filippos Sofos

E-Mail Website
Guest Editor
Department of Physics, School of Science, University of Thessaly, 35100 Lamia, Greece
Interests: machine learning; symbolic regression; computational hydraulics; molecular dynamics; smoothed-particle hydrodynamics; multiscale modeling
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue of Fluids, “Fluid Flows at the Nanoscale”, is dedicated to recent advances in the computational modeling of nanoscale fluid flows, encouraging the adoption of new methods, tools, and programming techniques and the introduction of novel materials to be investigated over various simulation conditions. Linking molecular simulations to macroscale phenomena strengthens our understanding of the functionality of atomically precise nanochannels and their assembly into larger, practical systems. We aim to increase our ability to employ scientific principles to guide the fabrication of nanodevices with specific functionalities, to be used in applications such as biosensors, clean water systems, fuel cells, drug delivery systems, porous systems, and micro heat exchangers.

Dr. Filippos Sofos
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Fluids is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • nano/meso/multi-scale modeling
  • computational and statistical physics
  • heat and mass transfer
  • transport properties
  • interfacial phenomena
  • novel materials
  • electric/magnetic-driven flows
  • blood flows
  • neural networks
  • machine learning

Published Papers (5 papers)

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Research

17 pages, 5274 KiB  
Article
CFD Analysis of Convective Heat Transfer in a Vertical Square Sub-Channel for Laminar Flow Regime
by Efrizon Umar, Nathanael Panagung Tandian, Ahmad Ciptadi Syuryavin, Anwar Ilmar Ramadhan and Joko Hadi Prayitno
Fluids 2022, 7(6), 207; https://0-doi-org.brum.beds.ac.uk/10.3390/fluids7060207 - 17 Jun 2022
Cited by 5 | Viewed by 2156
Abstract
The development of new practices in nuclear research reactor safety aspects and optimization of recent nuclear reactors needs knowledge on forced convective heat transfer within sub-channels formed between several nuclear fuel rods or heat exchanger tubes, not only in the fully developed regime [...] Read more.
The development of new practices in nuclear research reactor safety aspects and optimization of recent nuclear reactors needs knowledge on forced convective heat transfer within sub-channels formed between several nuclear fuel rods or heat exchanger tubes, not only in the fully developed regime but also in the developing regime or laminar flow regime. The main objective of this research was to find a new correlation equation for calculating the convective heat transfer coefficient in the vertical square sub-channels. Recently, a simulation study was conducted to find a new heat transfer correlation equation for calculating the convective heat transfer coefficient within a vertical square sub-channel in the developing regime or laminar flow regime for Reynolds number range 400 ≤ Re ≤ 1700. Simulations were carried out using a computational fluid dynamics (CFD) code and modeling already defined in the software. The novelty of the research lies in the analysis of the entrance effect for the sub-channel by proposing a new empirical correlation that can then be inserted into the STAT computer code. The surface temperature distribution around the tangential direction of the active cylinders shows that the implementation of active and dummy cylinders in the current study can simulate sub-channels that exist in a real nuclear reactor core. The current study shows that the flow simulated in this study is in its developing condition (entrance region). A new forced convective heat transfer correlation for the developing region in the form of Nu = 2.094(Gz)0.329 for the Graetz number range 161 ≤ Gz ≤ 2429 was obtained from the current study. Full article
(This article belongs to the Special Issue Fluid Flows at the Nanoscale)
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14 pages, 1687 KiB  
Article
Investigation of Machining Performance of MQL and MQCL Hard Turning Using Nano Cutting Fluids
by Ngo Minh Tuan, Tran Minh Duc, Tran The Long, Vu Lai Hoang and Tran Bao Ngoc
Fluids 2022, 7(5), 143; https://0-doi-org.brum.beds.ac.uk/10.3390/fluids7050143 - 19 Apr 2022
Cited by 12 | Viewed by 2538
Abstract
Cutting fluids used in the metal machining industry have exerted serious impacts on the environment and human health. In addition, the very high cutting heat and forces in machining-hardened steels have been a growing concern in the metal cutting field. Hence, new, eco-friendly [...] Read more.
Cutting fluids used in the metal machining industry have exerted serious impacts on the environment and human health. In addition, the very high cutting heat and forces in machining-hardened steels have been a growing concern in the metal cutting field. Hence, new, eco-friendly cooling and lubricating techniques are necessary to study and develop. Minimum quantity lubrication (MQL) and minimum quantity cooling lubrication (MQCL) using nano cutting fluids have been proven as alternative solutions for machining difficult-to cut materials while retaining an environmentally friendly characteristic. Accordingly, this paper aims to analyze and evaluate the hard turning efficiency of 90CrSi (60 ÷ 62 HRC) steel using MQL and MQCL conditions, using Al2O3 and MoS2 nano cutting fluids. The 2k-p experimental design and analysis of variance (ANOVA) were used to study the influence of input parameters including fluid type, lubrication method, nanoparticle type, nanoparticle concentration, cutting speed and feed rate on surface roughness. The obtained results showed that the machinability of CNMG120404 TM T9125 carbide tools was improved and the highest machinable hardness was increased from 35 HRC to 60 ÷ 62 HRC (rising by approximately 71.4 ÷ 77.1%) by using the nanofluid MQL and MQCL methods. Furthermore, MQCL gives better performance than MQL, and the Al2O3 nanofluid exhibits the better result in terms of surface roughness values than the MoS2 nanofluid. Feed rate displays the strongest influence on surface roughness, while fluid type, nanoparticle concentration and cutting speed show low impacts. From these results, technical guidance will be provided for further studies using Al2O3 and MoS2 nano cutting fluids for MQL and MQCL methods, as well as their application in machining practice. Full article
(This article belongs to the Special Issue Fluid Flows at the Nanoscale)
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24 pages, 4736 KiB  
Article
Microfluidics for Multiphase Mixing and Liposomal Encapsulation of Nanobioconjugates: Passive vs. Acoustic Systems
by Kevin A. Giraldo, Juan Sebastian Bermudez, Carlos E. Torres, Luis H. Reyes, Johann F. Osma and Juan C. Cruz
Fluids 2021, 6(9), 309; https://0-doi-org.brum.beds.ac.uk/10.3390/fluids6090309 - 31 Aug 2021
Cited by 7 | Viewed by 5089
Abstract
One of the main routes to ensure that biomolecules or bioactive agents remain active as they are incorporated into products with applications in different industries is by their encapsulation. Liposomes are attractive platforms for encapsulation due to their ease of synthesis and manipulation [...] Read more.
One of the main routes to ensure that biomolecules or bioactive agents remain active as they are incorporated into products with applications in different industries is by their encapsulation. Liposomes are attractive platforms for encapsulation due to their ease of synthesis and manipulation and the potential to fuse with cell membranes when they are intended for drug delivery applications. We propose encapsulating our recently developed cell-penetrating nanobioconjugates based on magnetite interfaced with translocating proteins and peptides with the purpose of potentiating their cell internalization capabilities even further. To prepare the encapsulates (also known as magnetoliposomes (MLPs)), we introduced a low-cost microfluidic device equipped with a serpentine microchannel to favor the interaction between the liposomes and the nanobioconjugates. The encapsulation performance of the device, operated either passively or in the presence of ultrasound, was evaluated both in silico and experimentally. The in silico analysis was implemented through multiphysics simulations with the software COMSOL Multiphysics 5.5® (COMSOL Inc., Stockholm, Sweden) via both a Eulerian model and a transport of diluted species model. The encapsulation efficiency was determined experimentally, aided by spectrofluorimetry. Encapsulation efficiencies obtained experimentally and in silico approached 80% for the highest flow rate ratios (FRRs). Compared with the passive mixer, the in silico results of the device under acoustic waves led to higher discrepancies with respect to those obtained experimentally. This was attributed to the complexity of the process in such a situation. The obtained MLPs demonstrated successful encapsulation of the nanobioconjugates by both methods with a 36% reduction in size for the ones obtained in the presence of ultrasound. These findings suggest that the proposed serpentine micromixers are well suited to produce MLPs very efficiently and with homogeneous key physichochemical properties. Full article
(This article belongs to the Special Issue Fluid Flows at the Nanoscale)
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17 pages, 5174 KiB  
Article
Magneto-Bioconvection Flow of Williamson Nanofluid over an Inclined Plate with Gyrotactic Microorganisms and Entropy Generation
by Tunde A. Yusuf, Fazle Mabood, B. C. Prasannakumara and Ioannis E. Sarris
Fluids 2021, 6(3), 109; https://0-doi-org.brum.beds.ac.uk/10.3390/fluids6030109 - 08 Mar 2021
Cited by 88 | Viewed by 2946
Abstract
The fluid flow through inclined plates has several applications in magneto-aerodynamics, materials processing and magnetohydrodynamic propulsion thermo-fluid dynamics. Inspired by these applications, the rate of entropy production in a bio-convective flow of a magnetohydrodynamic Williamson nanoliquid over an inclined convectively heated stretchy plate [...] Read more.
The fluid flow through inclined plates has several applications in magneto-aerodynamics, materials processing and magnetohydrodynamic propulsion thermo-fluid dynamics. Inspired by these applications, the rate of entropy production in a bio-convective flow of a magnetohydrodynamic Williamson nanoliquid over an inclined convectively heated stretchy plate with the influence of thermal radiation, porous materials and chemical reaction has been deliberated in this paper. The presence of microorganisms aids in stabilizing the suspended nanoparticles through a bioconvection process. Also, the thermal radiation assumed an optically thick limit approximation. With the help of similarity transformations, the coupled partial differential equations are converted to nonlinear ordinary differential equations and the resulting model is numerically tackled using the shooting method. The influences of the determining thermo-physical parameters on the flow field are incorporated and extensively discussed. The major relevant outcomes of the present analysis are that the upsurge in values of Schmidt number decays the mass transfer characteristics, but the converse trend is depicted for boost up values of the thermophoresis parameter. Enhancement in bioconvection Peclet and Schmidt numbers deteriorates the microorganism density characteristics. Further, the upsurge in the Williamson parameter declines the Bejan number and irreversibility ratio. Full article
(This article belongs to the Special Issue Fluid Flows at the Nanoscale)
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16 pages, 4249 KiB  
Article
Machine Learning Techniques for Fluid Flows at the Nanoscale
by Filippos Sofos and Theodoros E. Karakasidis
Fluids 2021, 6(3), 96; https://0-doi-org.brum.beds.ac.uk/10.3390/fluids6030096 - 01 Mar 2021
Cited by 10 | Viewed by 2421
Abstract
Simulations of fluid flows at the nanoscale feature massive data production and machine learning (ML) techniques have been developed during recent years to leverage them, presenting unique results. This work facilitates ML tools to provide an insight on properties among molecular dynamics (MD) [...] Read more.
Simulations of fluid flows at the nanoscale feature massive data production and machine learning (ML) techniques have been developed during recent years to leverage them, presenting unique results. This work facilitates ML tools to provide an insight on properties among molecular dynamics (MD) simulations, covering missing data points and predicting states not previously located by the simulation. Taking the fluid flow of a simple Lennard-Jones liquid in nanoscale slits as a basis, ML regression-based algorithms are exploited to provide an alternative for the calculation of transport properties of fluids, e.g., the diffusion coefficient, shear viscosity and thermal conductivity and the average velocity across the nanochannels. Through appropriate training and testing, ML-predicted values can be extracted for various input variables, such as the geometrical characteristics of the slits, the interaction parameters between particles and the flow driving force. The proposed technique could act in parallel to simulation as a means of enriching the database of material properties, assisting in coupling between scales, and accelerating data-based scientific computations. Full article
(This article belongs to the Special Issue Fluid Flows at the Nanoscale)
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