Molecular dynamics simulation of water-based nanofluids viscosity
The shear viscosity coefficients of water and water-based nanofluids with copper particles are calculated by the molecular dynamics method. Copper nanoparticles with a diameter of 2, 4 and 10 nm were used in the simulation. The volume fraction of nanoparticles was varied from 1 to 5%. The interactio...
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Veröffentlicht in: | Journal of thermal analysis and calorimetry 2021-09, Vol.145 (6), p.2983-2990 |
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description | The shear viscosity coefficients of water and water-based nanofluids with copper particles are calculated by the molecular dynamics method. Copper nanoparticles with a diameter of 2, 4 and 10 nm were used in the simulation. The volume fraction of nanoparticles was varied from 1 to 5%. The interaction of water molecules with each other was modeled using the Lennard–Jones potential. The Rudyak–Krasnolutskii and Rudyak–Krasnolutskii–Ivanov potentials were used as nanoparticle–molecule and nanoparticles interaction potentials, respectively. The viscosity coefficient was calculated using the fluctuation–dissipation theorem by the Green–Kubo formula. It is shown that the viscosity of the nanofluid significantly exceeds the viscosity of the coarse-grained suspension and increases with a decrease in the nanoparticles size at their fixed volume fraction. The correlation functions determining the viscosity coefficient of the nanofluid were analyzed in detail. The radial distribution functions of pure water and nanofluids are also presented in the paper. It is shown that the liquid near the nanoparticle is structured much more strongly than in the bulk. This greater ordering of the nanofluid is one of the main factors determining the increase in nanofluids viscosity. |
doi_str_mv | 10.1007/s10973-020-09873-8 |
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Copper nanoparticles with a diameter of 2, 4 and 10 nm were used in the simulation. The volume fraction of nanoparticles was varied from 1 to 5%. The interaction of water molecules with each other was modeled using the Lennard–Jones potential. The Rudyak–Krasnolutskii and Rudyak–Krasnolutskii–Ivanov potentials were used as nanoparticle–molecule and nanoparticles interaction potentials, respectively. The viscosity coefficient was calculated using the fluctuation–dissipation theorem by the Green–Kubo formula. It is shown that the viscosity of the nanofluid significantly exceeds the viscosity of the coarse-grained suspension and increases with a decrease in the nanoparticles size at their fixed volume fraction. The correlation functions determining the viscosity coefficient of the nanofluid were analyzed in detail. The radial distribution functions of pure water and nanofluids are also presented in the paper. It is shown that the liquid near the nanoparticle is structured much more strongly than in the bulk. This greater ordering of the nanofluid is one of the main factors determining the increase in nanofluids viscosity.</description><identifier>ISSN: 1388-6150</identifier><identifier>EISSN: 1588-2926</identifier><identifier>DOI: 10.1007/s10973-020-09873-8</identifier><language>eng</language><publisher>Cham: Springer International Publishing</publisher><subject>Analysis ; Analytical Chemistry ; Chemistry ; Chemistry and Materials Science ; Coefficients ; Copper ; Distribution (Probability theory) ; Distribution functions ; Inorganic Chemistry ; Measurement Science and Instrumentation ; Molecular dynamics ; Nanofluids ; Nanoparticles ; Physical Chemistry ; Polymer Sciences ; Radial distribution ; Shear viscosity ; Viscosity ; Water chemistry</subject><ispartof>Journal of thermal analysis and calorimetry, 2021-09, Vol.145 (6), p.2983-2990</ispartof><rights>Akadémiai Kiadó, Budapest, Hungary 2020</rights><rights>COPYRIGHT 2021 Springer</rights><rights>Akadémiai Kiadó, Budapest, Hungary 2020.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c392t-972113070eaa7891f595dc7c78ceaa146d4a097f66c5840e2486ffb4b7a15c333</citedby><cites>FETCH-LOGICAL-c392t-972113070eaa7891f595dc7c78ceaa146d4a097f66c5840e2486ffb4b7a15c333</cites><orcidid>0000-0003-1335-4548 ; 0000-0001-5440-6362</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s10973-020-09873-8$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s10973-020-09873-8$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,780,784,27924,27925,41488,42557,51319</link.rule.ids></links><search><creatorcontrib>Rudyak, V.</creatorcontrib><creatorcontrib>Krasnolutskii, S.</creatorcontrib><creatorcontrib>Belkin, A.</creatorcontrib><creatorcontrib>Lezhnev, E.</creatorcontrib><title>Molecular dynamics simulation of water-based nanofluids viscosity</title><title>Journal of thermal analysis and calorimetry</title><addtitle>J Therm Anal Calorim</addtitle><description>The shear viscosity coefficients of water and water-based nanofluids with copper particles are calculated by the molecular dynamics method. Copper nanoparticles with a diameter of 2, 4 and 10 nm were used in the simulation. The volume fraction of nanoparticles was varied from 1 to 5%. The interaction of water molecules with each other was modeled using the Lennard–Jones potential. The Rudyak–Krasnolutskii and Rudyak–Krasnolutskii–Ivanov potentials were used as nanoparticle–molecule and nanoparticles interaction potentials, respectively. The viscosity coefficient was calculated using the fluctuation–dissipation theorem by the Green–Kubo formula. It is shown that the viscosity of the nanofluid significantly exceeds the viscosity of the coarse-grained suspension and increases with a decrease in the nanoparticles size at their fixed volume fraction. The correlation functions determining the viscosity coefficient of the nanofluid were analyzed in detail. The radial distribution functions of pure water and nanofluids are also presented in the paper. It is shown that the liquid near the nanoparticle is structured much more strongly than in the bulk. This greater ordering of the nanofluid is one of the main factors determining the increase in nanofluids viscosity.</description><subject>Analysis</subject><subject>Analytical Chemistry</subject><subject>Chemistry</subject><subject>Chemistry and Materials Science</subject><subject>Coefficients</subject><subject>Copper</subject><subject>Distribution (Probability theory)</subject><subject>Distribution functions</subject><subject>Inorganic Chemistry</subject><subject>Measurement Science and Instrumentation</subject><subject>Molecular dynamics</subject><subject>Nanofluids</subject><subject>Nanoparticles</subject><subject>Physical Chemistry</subject><subject>Polymer Sciences</subject><subject>Radial distribution</subject><subject>Shear viscosity</subject><subject>Viscosity</subject><subject>Water chemistry</subject><issn>1388-6150</issn><issn>1588-2926</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><recordid>eNp9kUtLxDAUhYso-PwDrgquXFRv0ua1HMTHgCL4WIdMmgwZOo0mrTr_3qsVxI1kkcPhO8m9nKI4JnBGAMR5JqBEXQGFCpREJbeKPcKkrKiifBt1jZoTBrvFfs4rAFAKyF4xu4uds2NnUtluerMONpc5rNEYQuzL6Mt3M7hULUx2bdmbPvpuDG0u30K2MYdhc1jseNNld_RzHxTPV5dPFzfV7f31_GJ2W9la0aFSghJSgwBnjJCKeKZYa4UV0qJDGt42BnfwnFsmG3C0kdz7RbMQhjBb1_VBcTK9-5Li6-jyoFdxTD1-qSnjhLJGNgSps4lams7p0Ps4JGPxtA53i73zAf0Zx2mYoMAxcPongMzgPoalGXPW88eHvyydWJtizsl5_ZLC2qSNJqC_etBTDxp70N89aImhegplhPulS79z_5P6BK3miX4</recordid><startdate>20210901</startdate><enddate>20210901</enddate><creator>Rudyak, V.</creator><creator>Krasnolutskii, S.</creator><creator>Belkin, A.</creator><creator>Lezhnev, E.</creator><general>Springer International Publishing</general><general>Springer</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope><scope>ISR</scope><orcidid>https://orcid.org/0000-0003-1335-4548</orcidid><orcidid>https://orcid.org/0000-0001-5440-6362</orcidid></search><sort><creationdate>20210901</creationdate><title>Molecular dynamics simulation of water-based nanofluids viscosity</title><author>Rudyak, V. ; Krasnolutskii, S. ; Belkin, A. ; Lezhnev, E.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c392t-972113070eaa7891f595dc7c78ceaa146d4a097f66c5840e2486ffb4b7a15c333</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Analysis</topic><topic>Analytical Chemistry</topic><topic>Chemistry</topic><topic>Chemistry and Materials Science</topic><topic>Coefficients</topic><topic>Copper</topic><topic>Distribution (Probability theory)</topic><topic>Distribution functions</topic><topic>Inorganic Chemistry</topic><topic>Measurement Science and Instrumentation</topic><topic>Molecular dynamics</topic><topic>Nanofluids</topic><topic>Nanoparticles</topic><topic>Physical Chemistry</topic><topic>Polymer Sciences</topic><topic>Radial distribution</topic><topic>Shear viscosity</topic><topic>Viscosity</topic><topic>Water chemistry</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Rudyak, V.</creatorcontrib><creatorcontrib>Krasnolutskii, S.</creatorcontrib><creatorcontrib>Belkin, A.</creatorcontrib><creatorcontrib>Lezhnev, E.</creatorcontrib><collection>CrossRef</collection><collection>Gale In Context: Science</collection><jtitle>Journal of thermal analysis and calorimetry</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Rudyak, V.</au><au>Krasnolutskii, S.</au><au>Belkin, A.</au><au>Lezhnev, E.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Molecular dynamics simulation of water-based nanofluids viscosity</atitle><jtitle>Journal of thermal analysis and calorimetry</jtitle><stitle>J Therm Anal Calorim</stitle><date>2021-09-01</date><risdate>2021</risdate><volume>145</volume><issue>6</issue><spage>2983</spage><epage>2990</epage><pages>2983-2990</pages><issn>1388-6150</issn><eissn>1588-2926</eissn><abstract>The shear viscosity coefficients of water and water-based nanofluids with copper particles are calculated by the molecular dynamics method. Copper nanoparticles with a diameter of 2, 4 and 10 nm were used in the simulation. The volume fraction of nanoparticles was varied from 1 to 5%. The interaction of water molecules with each other was modeled using the Lennard–Jones potential. The Rudyak–Krasnolutskii and Rudyak–Krasnolutskii–Ivanov potentials were used as nanoparticle–molecule and nanoparticles interaction potentials, respectively. The viscosity coefficient was calculated using the fluctuation–dissipation theorem by the Green–Kubo formula. It is shown that the viscosity of the nanofluid significantly exceeds the viscosity of the coarse-grained suspension and increases with a decrease in the nanoparticles size at their fixed volume fraction. The correlation functions determining the viscosity coefficient of the nanofluid were analyzed in detail. The radial distribution functions of pure water and nanofluids are also presented in the paper. It is shown that the liquid near the nanoparticle is structured much more strongly than in the bulk. This greater ordering of the nanofluid is one of the main factors determining the increase in nanofluids viscosity.</abstract><cop>Cham</cop><pub>Springer International Publishing</pub><doi>10.1007/s10973-020-09873-8</doi><tpages>8</tpages><orcidid>https://orcid.org/0000-0003-1335-4548</orcidid><orcidid>https://orcid.org/0000-0001-5440-6362</orcidid></addata></record> |
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subjects | Analysis Analytical Chemistry Chemistry Chemistry and Materials Science Coefficients Copper Distribution (Probability theory) Distribution functions Inorganic Chemistry Measurement Science and Instrumentation Molecular dynamics Nanofluids Nanoparticles Physical Chemistry Polymer Sciences Radial distribution Shear viscosity Viscosity Water chemistry |
title | Molecular dynamics simulation of water-based nanofluids viscosity |
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