Special Issue "Nanofluid for Heat Transfer Enhancement: Current and Future Perspective"
A special issue of Machines (ISSN 2075-1702). This special issue belongs to the section "Electromechanical Energy Conversion Systems".
Deadline for manuscript submissions: closed (31 May 2023) | Viewed by 1598
Special Issue Editors
Interests: fire safety in hydrogen energy development and utilization; CFD; clean energy
Special Issues, Collections and Topics in MDPI journals
Interests: heat transfer; CFD; machine learning
Special Issue Information
Dear Colleagues,
I want to extend a warm invitation to you all to submit your research papers to the Special Issue of Machines on "Nanofluid for Heat Transfer Enhancement: Current and Future Perspective".
A mixture of nanoparticles and base fluids, known as nanofluids, can provide a higher heat transfer rate than conventional coolants. The higher thermal conductivity of nanofluids is beneficial for abundant applications with the aim of cooling and heating, such as solar collectors, photovoltaic thermal systems, thermal management, electronic devices, radiators, refrigerators, boilers, lubrication, oil recovery, etc. New advancements in nanotechnology have propelled researcher interest in offering effective working fluids with the minimum costs.
However, despite considerable experimental and numerical research in this field, nanofluids require more fundamental studies. Major challenges in the application of nanofluids are:
- The stability and preservation of nanoparticles without sedimentation and aggregation;
- Higher pressure drop penalty and pumping power associated with nanofluid heat transfer enhancement;
- Corrosion and erosion of components by nanofluids.
A concerted global research effort is required to overcome the remaining technical challenges and provide new insights that benefit the research community. A primary focus of this Special Issue is to bring together papers that particularly present recent advances in the fields above to mitigate many of these technical challenges and indicate future trends of nanofluids. All research approaches (experimental, theoretical, and computational) are welcomed, emphasizing fundamental or applied nature aspects.
Dr. Javad Mohammadpour
Dr. Shahid Husain
Guest Editors
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. Machines 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 2400 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
- thermophysical properties of nanofluids
- nanofluid stability
- solar collectors and photovoltaic thermal systems
- electronic cooling systems and MCHS advancements
- hybrid combinations of passive and active cooling techniques
- applications of mono- and hybrid nanofluids in different energy systems
- data-driven models to predict nanofluid performance
- machine learning and multi-objective optimization
- investigation of nanoparticle shapes and influential forces acting on particles
- challenges in industrial adoption