Percolation of rigid fractal carbon black aggregates

dc.bibliographicCitation.firstPage124902
dc.bibliographicCitation.issue12
dc.bibliographicCitation.journalTitleThe Journal of Chemical Physicseng
dc.bibliographicCitation.volume155
dc.contributor.authorCoupette, Fabian
dc.contributor.authorZhang, Long
dc.contributor.authorKuttich, Björn
dc.contributor.authorChumakov, Andrei
dc.contributor.authorRoth, Stephan V.
dc.contributor.authorGonzález-García, Lola
dc.contributor.authorKraus, Tobias
dc.contributor.authorSchilling, Tanja
dc.date.accessioned2022-03-10T12:41:26Z
dc.date.available2022-03-10T12:41:26Z
dc.date.issued2021
dc.description.abstractWe examine network formation and percolation of carbon black by means of Monte Carlo simulations and experiments. In the simulation, we model carbon black by rigid aggregates of impenetrable spheres, which we obtain by diffusion-limited aggregation. To determine the input parameters for the simulation, we experimentally characterize the micro-structure and size distribution of carbon black aggregates. We then simulate suspensions of aggregates and determine the percolation threshold as a function of the aggregate size distribution. We observe a quasi-universal relation between the percolation threshold and a weighted average radius of gyration of the aggregate ensemble. Higher order moments of the size distribution do not have an effect on the percolation threshold. We conclude further that the concentration of large carbon black aggregates has a stronger influence on the percolation threshold than the concentration of small aggregates. In the experiment, we disperse the carbon black in a polymer matrix and measure the conductivity of the composite. We successfully test the hypotheses drawn from simulation by comparing composites prepared with the same type of carbon black before and after ball milling, i.e., on changing only the distribution of aggregate sizes in the composites.eng
dc.description.versionpublishedVersioneng
dc.identifier.urihttps://oa.tib.eu/renate/handle/123456789/8208
dc.identifier.urihttps://doi.org/10.34657/7246
dc.language.isoengeng
dc.publisherMelville, NY : American Institute of Physics
dc.relation.doihttps://doi.org/10.1063/5.0058503
dc.relation.essn1089-7690
dc.rights.licenseCC BY 4.0 Unported
dc.rights.urihttps://creativecommons.org/licenses/by/4.0
dc.subject.ddc540
dc.subject.ddc530
dc.subject.otherAggregateseng
dc.subject.otherBall millingeng
dc.subject.otherIntelligent systemseng
dc.subject.otherMonte Carlo methodseng
dc.subject.otherPercolation (computer storage)eng
dc.subject.otherPercolation (fluids)eng
dc.subject.otherPolymer matrix compositeseng
dc.subject.otherSize distributioneng
dc.subject.otherSolventseng
dc.subject.otherBlack aggregateseng
dc.subject.otherDiffusion limited aggregationeng
dc.subject.otherDiffusion limited aggregation]eng
dc.subject.otherInput parametereng
dc.subject.otherMonte Carlo experimentseng
dc.subject.otherMonte Carlo's simulationeng
dc.subject.otherNetwork formationeng
dc.subject.otherNetwork percolationeng
dc.subject.otherPercolation thresholdseng
dc.subject.otherSize-distributioneng
dc.subject.otherCarbon blackeng
dc.titlePercolation of rigid fractal carbon black aggregateseng
dc.typeArticleeng
dc.typeTexteng
tib.accessRightsopenAccesseng
wgl.contributorINMger
wgl.subjectPhysikger
wgl.subjectChemieger
wgl.typeZeitschriftenartikelger
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