Computational analysis of factors influencing thermal conductivity of nanofluids
Numerical investigations are conducted to study the effect of factors such as particle clustering and interfacial layer thickness on thermal conductivity of nanofluids. Based on this, parameters including Kapitza radius and fractal and chemical dimension which have received little attention by previ...
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| Veröffentlicht in: | Journal of nanoparticle research : an interdisciplinary forum for nanoscale science and technology 2011-12, Vol.13 (12), p.6365-6375 |
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| creator | Okeke, G. Witharana, S. Antony, S. J. Ding, Y. |
| description | Numerical investigations are conducted to study the effect of factors such as particle clustering and interfacial layer thickness on thermal conductivity of nanofluids. Based on this, parameters including Kapitza radius and fractal and chemical dimension which have received little attention by previous research are rigorously investigated. The degree of thermal enhancement is analyzed for increasing aggregate size, particle concentration, interfacial thermal resistance, and fractal and chemical dimensions. This analysis is conducted for water-based nanofluids of Alumina (Al
2
O
3
), CuO, and Titania (TiO
2
) nanoparticles where the particle concentrations are varied up to 4 vol%. Results from the numerical work are validated using available experimental data. For the case of aggregate size, particle concentration, and interfacial thermal resistance, the aspect ratio (ratio of radius of gyration of aggregate to radius of primary particle,
R
g
/
a
) is varied from 2 to 60. It was found that the enhancement decreases with interfacial layer thickness. Also the rate of decrease is more significant after a given aggregate size. For a given interfacial resistance, the enhancement is mostly sensitive to
R
g
/
a
|
| doi_str_mv | 10.1007/s11051-011-0389-9 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_1439751461</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>1439751461</sourcerecordid><originalsourceid>FETCH-LOGICAL-c349t-a2e075360b8f695b3ea31b89436dc3c39a53f085e327b4fd6ea77cc217dd89a23</originalsourceid><addsrcrecordid>eNp10MtKxDAYBeAgCo6jD-Cu4MZNNZc2l6UM3kDQhYK7kKbJmKFNxiQV5u3NUBciGMhl8Z0fcgA4R_AKQciuE0KwRTVEZRMuanEAFqhluOaCvh-WN-G8how2x-AkpQ2EiGKBF-BlFcbtlFV2wauhUuXYJZeqYCurdA4xVc7bYTJeO7-u8oeJY3E6-H7S2X25vNtbr3woyvXpFBxZNSRz9nMvwdvd7evqoX56vn9c3TzVmjQi1wobyFpCYcctFW1HjCKo46IhtNdEE6FaYiFvDcGsa2xPjWJMa4xY33OhMFmCy3nuNobPyaQsR5e0GQblTZiSRA0RrEUNRYVe_KGbMMXy06LK4i0mkBaFZqVjSCkaK7fRjSruJIJy37GcO5alY7nvWIqSwXMmFevXJv6a_G_oG06zf20</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1111852306</pqid></control><display><type>article</type><title>Computational analysis of factors influencing thermal conductivity of nanofluids</title><source>SpringerLink Journals - AutoHoldings</source><creator>Okeke, G. ; Witharana, S. ; Antony, S. J. ; Ding, Y.</creator><creatorcontrib>Okeke, G. ; Witharana, S. ; Antony, S. J. ; Ding, Y.</creatorcontrib><description>Numerical investigations are conducted to study the effect of factors such as particle clustering and interfacial layer thickness on thermal conductivity of nanofluids. Based on this, parameters including Kapitza radius and fractal and chemical dimension which have received little attention by previous research are rigorously investigated. The degree of thermal enhancement is analyzed for increasing aggregate size, particle concentration, interfacial thermal resistance, and fractal and chemical dimensions. This analysis is conducted for water-based nanofluids of Alumina (Al
2
O
3
), CuO, and Titania (TiO
2
) nanoparticles where the particle concentrations are varied up to 4 vol%. Results from the numerical work are validated using available experimental data. For the case of aggregate size, particle concentration, and interfacial thermal resistance, the aspect ratio (ratio of radius of gyration of aggregate to radius of primary particle,
R
g
/
a
) is varied from 2 to 60. It was found that the enhancement decreases with interfacial layer thickness. Also the rate of decrease is more significant after a given aggregate size. For a given interfacial resistance, the enhancement is mostly sensitive to
R
g
/
a
< 20 indicated by the steep gradients of data plots. Predicted and experimental data for thermal conductivity enhancement are in good agreement. On the influence of fractal and chemical dimensions (
d
l
and d
f
) of Alumina–water nanofluid, the
R
g
/
a
was varied from 2 to 8,
d
l
from 1.2 to 1.8, and
d
f
from 1.75 to 2.5. For a given concentration, the enhancement increased with the reduction of
d
l
or
d
f
. It appears a distinctive sensitivity of the enhancement to
d
f
, in particular, in the range 2–2.25, for all values of
R
g
/
a
. However, the sensitivity of
d
l
was largely depended on the value of
R
g
/
a
. The information gathered from this study on the sensitivity of thermal conductivity enhancement to aggregate size, particle concentration, interfacial resistance, and fractal and chemical dimensions will be useful in manufacturing highly thermally conductive nanofluids. Further research on the refine cluster evolution dynamics as a function of particle-scale properties is underway.</description><identifier>ISSN: 1388-0764</identifier><identifier>EISSN: 1572-896X</identifier><identifier>DOI: 10.1007/s11051-011-0389-9</identifier><language>eng</language><publisher>Dordrecht: Springer Netherlands</publisher><subject>Aggregates ; Characterization and Evaluation of Materials ; Chemistry and Materials Science ; COMPOSITES ; COPPER OXIDE ; CUPRIC OXIDE ; ELECTRICAL CONDUCTIVITY ; Experimental data ; FLUID FLOW ; Fractal analysis ; Heat transfer ; Inorganic Chemistry ; Lasers ; Materials Science ; MICROSTRUCTURES ; Nanocomposites ; Nanofluids ; Nanomaterials ; Nanoparticles ; Nanostructure ; Nanotechnology ; Optical Devices ; Optics ; Photonics ; Physical Chemistry ; Research Paper ; Thermal conductivity ; TITANIUM DIOXIDE</subject><ispartof>Journal of nanoparticle research : an interdisciplinary forum for nanoscale science and technology, 2011-12, Vol.13 (12), p.6365-6375</ispartof><rights>Springer Science+Business Media B.V. 2011</rights><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c349t-a2e075360b8f695b3ea31b89436dc3c39a53f085e327b4fd6ea77cc217dd89a23</citedby><cites>FETCH-LOGICAL-c349t-a2e075360b8f695b3ea31b89436dc3c39a53f085e327b4fd6ea77cc217dd89a23</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s11051-011-0389-9$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s11051-011-0389-9$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,780,784,27924,27925,41488,42557,51319</link.rule.ids></links><search><creatorcontrib>Okeke, G.</creatorcontrib><creatorcontrib>Witharana, S.</creatorcontrib><creatorcontrib>Antony, S. J.</creatorcontrib><creatorcontrib>Ding, Y.</creatorcontrib><title>Computational analysis of factors influencing thermal conductivity of nanofluids</title><title>Journal of nanoparticle research : an interdisciplinary forum for nanoscale science and technology</title><addtitle>J Nanopart Res</addtitle><description>Numerical investigations are conducted to study the effect of factors such as particle clustering and interfacial layer thickness on thermal conductivity of nanofluids. Based on this, parameters including Kapitza radius and fractal and chemical dimension which have received little attention by previous research are rigorously investigated. The degree of thermal enhancement is analyzed for increasing aggregate size, particle concentration, interfacial thermal resistance, and fractal and chemical dimensions. This analysis is conducted for water-based nanofluids of Alumina (Al
2
O
3
), CuO, and Titania (TiO
2
) nanoparticles where the particle concentrations are varied up to 4 vol%. Results from the numerical work are validated using available experimental data. For the case of aggregate size, particle concentration, and interfacial thermal resistance, the aspect ratio (ratio of radius of gyration of aggregate to radius of primary particle,
R
g
/
a
) is varied from 2 to 60. It was found that the enhancement decreases with interfacial layer thickness. Also the rate of decrease is more significant after a given aggregate size. For a given interfacial resistance, the enhancement is mostly sensitive to
R
g
/
a
< 20 indicated by the steep gradients of data plots. Predicted and experimental data for thermal conductivity enhancement are in good agreement. On the influence of fractal and chemical dimensions (
d
l
and d
f
) of Alumina–water nanofluid, the
R
g
/
a
was varied from 2 to 8,
d
l
from 1.2 to 1.8, and
d
f
from 1.75 to 2.5. For a given concentration, the enhancement increased with the reduction of
d
l
or
d
f
. It appears a distinctive sensitivity of the enhancement to
d
f
, in particular, in the range 2–2.25, for all values of
R
g
/
a
. However, the sensitivity of
d
l
was largely depended on the value of
R
g
/
a
. The information gathered from this study on the sensitivity of thermal conductivity enhancement to aggregate size, particle concentration, interfacial resistance, and fractal and chemical dimensions will be useful in manufacturing highly thermally conductive nanofluids. Further research on the refine cluster evolution dynamics as a function of particle-scale properties is underway.</description><subject>Aggregates</subject><subject>Characterization and Evaluation of Materials</subject><subject>Chemistry and Materials Science</subject><subject>COMPOSITES</subject><subject>COPPER OXIDE</subject><subject>CUPRIC OXIDE</subject><subject>ELECTRICAL CONDUCTIVITY</subject><subject>Experimental data</subject><subject>FLUID FLOW</subject><subject>Fractal analysis</subject><subject>Heat transfer</subject><subject>Inorganic Chemistry</subject><subject>Lasers</subject><subject>Materials Science</subject><subject>MICROSTRUCTURES</subject><subject>Nanocomposites</subject><subject>Nanofluids</subject><subject>Nanomaterials</subject><subject>Nanoparticles</subject><subject>Nanostructure</subject><subject>Nanotechnology</subject><subject>Optical Devices</subject><subject>Optics</subject><subject>Photonics</subject><subject>Physical Chemistry</subject><subject>Research Paper</subject><subject>Thermal conductivity</subject><subject>TITANIUM DIOXIDE</subject><issn>1388-0764</issn><issn>1572-896X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2011</creationdate><recordtype>article</recordtype><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNp10MtKxDAYBeAgCo6jD-Cu4MZNNZc2l6UM3kDQhYK7kKbJmKFNxiQV5u3NUBciGMhl8Z0fcgA4R_AKQciuE0KwRTVEZRMuanEAFqhluOaCvh-WN-G8how2x-AkpQ2EiGKBF-BlFcbtlFV2wauhUuXYJZeqYCurdA4xVc7bYTJeO7-u8oeJY3E6-H7S2X25vNtbr3woyvXpFBxZNSRz9nMvwdvd7evqoX56vn9c3TzVmjQi1wobyFpCYcctFW1HjCKo46IhtNdEE6FaYiFvDcGsa2xPjWJMa4xY33OhMFmCy3nuNobPyaQsR5e0GQblTZiSRA0RrEUNRYVe_KGbMMXy06LK4i0mkBaFZqVjSCkaK7fRjSruJIJy37GcO5alY7nvWIqSwXMmFevXJv6a_G_oG06zf20</recordid><startdate>20111201</startdate><enddate>20111201</enddate><creator>Okeke, G.</creator><creator>Witharana, S.</creator><creator>Antony, S. J.</creator><creator>Ding, Y.</creator><general>Springer Netherlands</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7QO</scope><scope>7SR</scope><scope>7TB</scope><scope>7U5</scope><scope>7U7</scope><scope>7X7</scope><scope>7XB</scope><scope>8AO</scope><scope>8BQ</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>C1K</scope><scope>CCPQU</scope><scope>D1I</scope><scope>DWQXO</scope><scope>F28</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>JG9</scope><scope>K9.</scope><scope>KB.</scope><scope>L6V</scope><scope>L7M</scope><scope>LK8</scope><scope>M0S</scope><scope>M7P</scope><scope>M7S</scope><scope>P5Z</scope><scope>P62</scope><scope>P64</scope><scope>PDBOC</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PTHSS</scope><scope>H8G</scope></search><sort><creationdate>20111201</creationdate><title>Computational analysis of factors influencing thermal conductivity of nanofluids</title><author>Okeke, G. ; Witharana, S. ; Antony, S. J. ; Ding, Y.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c349t-a2e075360b8f695b3ea31b89436dc3c39a53f085e327b4fd6ea77cc217dd89a23</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2011</creationdate><topic>Aggregates</topic><topic>Characterization and Evaluation of Materials</topic><topic>Chemistry and Materials Science</topic><topic>COMPOSITES</topic><topic>COPPER OXIDE</topic><topic>CUPRIC OXIDE</topic><topic>ELECTRICAL CONDUCTIVITY</topic><topic>Experimental data</topic><topic>FLUID FLOW</topic><topic>Fractal analysis</topic><topic>Heat transfer</topic><topic>Inorganic Chemistry</topic><topic>Lasers</topic><topic>Materials Science</topic><topic>MICROSTRUCTURES</topic><topic>Nanocomposites</topic><topic>Nanofluids</topic><topic>Nanomaterials</topic><topic>Nanoparticles</topic><topic>Nanostructure</topic><topic>Nanotechnology</topic><topic>Optical Devices</topic><topic>Optics</topic><topic>Photonics</topic><topic>Physical Chemistry</topic><topic>Research Paper</topic><topic>Thermal conductivity</topic><topic>TITANIUM DIOXIDE</topic><toplevel>online_resources</toplevel><creatorcontrib>Okeke, G.</creatorcontrib><creatorcontrib>Witharana, S.</creatorcontrib><creatorcontrib>Antony, S. J.</creatorcontrib><creatorcontrib>Ding, Y.</creatorcontrib><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Biotechnology Research Abstracts</collection><collection>Engineered Materials Abstracts</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Solid State and Superconductivity Abstracts</collection><collection>Toxicology Abstracts</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>ProQuest Pharma Collection</collection><collection>METADEX</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest One Sustainability</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>Natural Science Collection</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>ProQuest Materials Science Collection</collection><collection>ProQuest Central Korea</collection><collection>ANTE: Abstracts in New Technology & Engineering</collection><collection>Engineering Research Database</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>Materials Research Database</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Materials Science Database</collection><collection>ProQuest Engineering Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>ProQuest Biological Science Collection</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Biological Science Database</collection><collection>Engineering Database</collection><collection>Advanced Technologies & Aerospace Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Materials Science Collection</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>Engineering Collection</collection><collection>Copper Technical Reference Library</collection><jtitle>Journal of nanoparticle research : an interdisciplinary forum for nanoscale science and technology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Okeke, G.</au><au>Witharana, S.</au><au>Antony, S. J.</au><au>Ding, Y.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Computational analysis of factors influencing thermal conductivity of nanofluids</atitle><jtitle>Journal of nanoparticle research : an interdisciplinary forum for nanoscale science and technology</jtitle><stitle>J Nanopart Res</stitle><date>2011-12-01</date><risdate>2011</risdate><volume>13</volume><issue>12</issue><spage>6365</spage><epage>6375</epage><pages>6365-6375</pages><issn>1388-0764</issn><eissn>1572-896X</eissn><abstract>Numerical investigations are conducted to study the effect of factors such as particle clustering and interfacial layer thickness on thermal conductivity of nanofluids. Based on this, parameters including Kapitza radius and fractal and chemical dimension which have received little attention by previous research are rigorously investigated. The degree of thermal enhancement is analyzed for increasing aggregate size, particle concentration, interfacial thermal resistance, and fractal and chemical dimensions. This analysis is conducted for water-based nanofluids of Alumina (Al
2
O
3
), CuO, and Titania (TiO
2
) nanoparticles where the particle concentrations are varied up to 4 vol%. Results from the numerical work are validated using available experimental data. For the case of aggregate size, particle concentration, and interfacial thermal resistance, the aspect ratio (ratio of radius of gyration of aggregate to radius of primary particle,
R
g
/
a
) is varied from 2 to 60. It was found that the enhancement decreases with interfacial layer thickness. Also the rate of decrease is more significant after a given aggregate size. For a given interfacial resistance, the enhancement is mostly sensitive to
R
g
/
a
< 20 indicated by the steep gradients of data plots. Predicted and experimental data for thermal conductivity enhancement are in good agreement. On the influence of fractal and chemical dimensions (
d
l
and d
f
) of Alumina–water nanofluid, the
R
g
/
a
was varied from 2 to 8,
d
l
from 1.2 to 1.8, and
d
f
from 1.75 to 2.5. For a given concentration, the enhancement increased with the reduction of
d
l
or
d
f
. It appears a distinctive sensitivity of the enhancement to
d
f
, in particular, in the range 2–2.25, for all values of
R
g
/
a
. However, the sensitivity of
d
l
was largely depended on the value of
R
g
/
a
. The information gathered from this study on the sensitivity of thermal conductivity enhancement to aggregate size, particle concentration, interfacial resistance, and fractal and chemical dimensions will be useful in manufacturing highly thermally conductive nanofluids. Further research on the refine cluster evolution dynamics as a function of particle-scale properties is underway.</abstract><cop>Dordrecht</cop><pub>Springer Netherlands</pub><doi>10.1007/s11051-011-0389-9</doi><tpages>11</tpages></addata></record> |
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| issn | 1388-0764 1572-896X |
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| subjects | Aggregates Characterization and Evaluation of Materials Chemistry and Materials Science COMPOSITES COPPER OXIDE CUPRIC OXIDE ELECTRICAL CONDUCTIVITY Experimental data FLUID FLOW Fractal analysis Heat transfer Inorganic Chemistry Lasers Materials Science MICROSTRUCTURES Nanocomposites Nanofluids Nanomaterials Nanoparticles Nanostructure Nanotechnology Optical Devices Optics Photonics Physical Chemistry Research Paper Thermal conductivity TITANIUM DIOXIDE |
| title | Computational analysis of factors influencing thermal conductivity of nanofluids |
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