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dc.rights.licenseIn Copyrighten_US
dc.creatorSchwen, Eric M.
dc.date.accessioned2015-07-29T20:03:36Z
dc.date.available2015-07-29T20:03:36Z
dc.date.created2015
dc.date.issued2015
dc.identifier.urihttp://hdl.handle.net/11021/32173
dc.descriptionThesis; [FULL-TEXT FREELY AVAILABLE ONLINE]en_US
dc.descriptionEric M. Schwen is a member of the Class of 2015 of Washington and Lee University.en_US
dc.description.abstractWe introduce three stochastic cooperative models for particle deposition and evaporation relevant to ionic self-assembly of nanoparticles with applications in surface fabrication and nanomedicine. We present a method for mapping a stochastic model onto the Ising model, which allows us to use the established results for the Ising model to describe the properties of the system. After completing the mapping process, we investigate the time dependence of particle density using the mean _eld approximation. We complement this theoretical analysis with Monte Carlo simulations that support our models. These techniques, which can be used separately or in combination, are useful as pedagogical tools because they are tractable mathematically and they apply equally well to many other physical systems with nearest-neighbor interactions including voter and epidemic models.en_US
dc.description.statementofresponsibilityE. M. Schwen
dc.format.extent34 pagesen_US
dc.language.isoen_USen_US
dc.rightsThis material is made available for use in research, teaching, and private study, pursuant to U.S. Copyright law. The user assumes full responsibility for any use of the materials, including but not limited to, infringement of copyright and publication rights of reproduced materials. Any materials used should be fully credited with the source.en_US
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en_US
dc.subject.otherWashington and Lee University -- Honors in Physicsen_US
dc.titleAn introduction to stochastic self-assembly: theory, simulation and experimental applications (thesis)en_US
dc.typeTexten_US
dc.rights.holderSchwen, Eric M.
dc.subject.fastNanoparticlesen_US
dc.subject.fastStochastic processesen_US
dc.subject.fastStochastic modelsen_US
dc.subject.fastIsing modelen_US


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