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Computational simulation of artificial nanoparticles paths
dc.contributor.author | Nieto-Chaupis, Huber | |
dc.date.accessioned | 2021-10-01T00:12:22Z | |
dc.date.available | 2021-10-01T00:12:22Z | |
dc.date.issued | 2021-02-28 | |
dc.identifier.citation | Nieto, H. (2021). Computational simulation of artificial nanoparticles paths. IEEE Third International Conference on Artificial Intelligence and Knowledge Engineering (AIKE), 193-197. https://doi.org/10.1109/AIKE48582.2020.00045 | es_PE |
dc.identifier.uri | https://hdl.handle.net/11537/28011 | |
dc.description | El texto completo de este trabajo no está disponible en el Repositorio Académico UPN por restricciones de la casa editorial donde ha sido publicado. | es_PE |
dc.description.abstract | ABSTRACT In this paper the action to deliver nanoparticles in prospective Nanomedicine is computationally simulated. For this end, the usage of quantum mechanics has as end to describe the different paths that nanoparticles travel from a generator to a concrete target. The presence of ions might be against the purpose of the technique of Drug Delivery Targeted by which assumes that not any noise might coexist together to the nanoparticles. This paper presents simulations by which the Brownian dynamics would alter the nanoparticles paths. From the results one finds that depending on the energy interactions it would be a cause for errors and deviation of nanoparticles along their path to the desired target. | es_PE |
dc.format | application/pdf | es_PE |
dc.language.iso | eng | es_PE |
dc.publisher | IEEE | es_PE |
dc.rights | info:eu-repo/semantics/closedAccess | es_PE |
dc.source | Universidad Privada del Norte | es_PE |
dc.source | Repositorio Institucional - UPN | es_PE |
dc.subject | Farmacología | es_PE |
dc.subject | Medicamentos | es_PE |
dc.subject | Simulación por computadora | es_PE |
dc.title | Computational simulation of artificial nanoparticles paths | es_PE |
dc.type | info:eu-repo/semantics/conferenceObject | es_PE |
dc.publisher.country | US | es_PE |
dc.identifier.journal | IEEE Third International Conference on Artificial Intelligence and Knowledge Engineering (AIKE) | es_PE |
dc.description.peer-review | Revisión por pares | es_PE |
dc.subject.ocde | https://purl.org/pe-repo/ocde/ford#3.03.03 | es_PE |
dc.description.sede | Los Olivos | es_PE |
dc.identifier.doi | https://doi.org/10.1109/AIKE48582.2020.00045 |
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