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dc.creatorVega, Jorge Rubén
dc.creatorClementi, Luis Alberto
dc.creatorMeira, Gregorio
dc.date.accessioned2018-09-11T20:06:33Z
dc.date.available2018-09-11T20:06:33Z
dc.date.issued2013
dc.identifier.citationMacromolecular Theory And Simulations, 23(2), pp. 90-100 (2013)es_ES
dc.identifier.urihttp://hdl.handle.net/20.500.12272/3108
dc.description.abstractThis article theoretically evaluates the biases introduced into the distributions of molar masses (MMD) and the number of long chain branches per molecule (LCBD), when randomly-branched polymers are analyzed by size exclusion chromatography (SEC) with molar mass-sensitive detectors. The MMD of a polymer with tetrafunctional branch units has been calculated with the Stockmayer equation (1943); and an ideal SEC analysis has been simulated that assumes u-solvent, perfect measurements, and perfect fractionation by hydrodynamic volume except for a minor mixing in the detector cells. In ideal SEC, a negligible bias is introduced into the MMD, with the local dispersity exhibiting a maximum of 1.0035 at the high molar masses. This result is consistent with previous theoretical investigations, but differs qualitatively from experimental observationsofpolymerscontainingshort-andlong-chain branches. When including band broadening in the columns while still assuming perfect measurements, the MMDremainsessentiallyunbiased.Incontrast,poorMMD estimates are obtained when the chromatograms are contaminated with additive noise. Only qualitative estimates of the LCBD are possible, due to theoretical limitations combined with propagation of errors in a highly nonlinear calculation procedure.es_ES
dc.formatapplication/pdf
dc.language.isoenges_ES
dc.rightsinfo:eu-repo/semantics/openAccesses_ES
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/*
dc.subjectRandomly-Branched Polymerses_ES
dc.subjectDistribution of 5 Molar Masses_ES
dc.subjectBranching Degreeaes_ES
dc.titleRandomly-branched polymers by size exclusion chromatography with triple detection : computer simulation study for estimating errors in the distribution of molar mass and branching degreees_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.description.affiliationFil: Vega, Jorge Rubén. Universidad Tecnológica Nacional. Facultad Regional Santa Fe, Argentina.es_ES
dc.description.affiliationFil: Clementi, Luis Alberto. Universidad Tecnológica Nacional. Facultad Regional Santa Fe, Argentina.es_ES
dc.description.affiliationFil: Meira, Gregorio. CONICET-Universidad Nacional del Litoral. INTEC; Argentina.es_ES
dc.description.affiliationFil: Vega, Jorge Rubén. CONICET-Universidad Nacional del Litoral. INTEC; Argentina.es_ES
dc.description.affiliationFil: Clementi, Luis Alberto. CONICET-Universidad Nacional del Litoral. INTEC; Argentina.es_ES
dc.description.peerreviewedPeer Reviewedes_ES
dc.relation.projectidTecnicas numéricas de estimación y optimización: aplicaciones en problemas de nanotecnología y de energía eléctrica - Código: 25/0147es_ES
dc.type.versioninfo:eu-repo/semantics/acceptedVersiones_ES
dc.type.snrdinfo:ar-repo/semantics/artículoes_ES
dc.rights.useCondiciones de Uso desde su aprobaciónes_ES
dc.rights.useAtribución-NoComercial-CompartirIgual 4.0 Internacional*


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