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dc.contributor.authorZhang, Ge
dc.contributor.authorYang, Jing Fan
dc.contributor.authorYang, Sungyun
dc.contributor.authorBrooks, Allan M
dc.contributor.authorKoman, Volodymyr B
dc.contributor.authorGong, Xun
dc.contributor.authorStrano, Michael S
dc.date.accessioned2026-01-23T21:53:17Z
dc.date.available2026-01-23T21:53:17Z
dc.date.issued2023-06-29
dc.identifier.urihttps://hdl.handle.net/1721.1/164629
dc.description.abstractA widely utilized tool in reactor analysis is passive tracers that report the residence time distribution, allowing estimation of the conversion and other properties of the system. Recently, advances in microrobotics have introduced powered and functional entities with sizes comparable to some traditional tracers. This has motivated the concept of Smart Tracers that could record the local chemical concentrations, temperature, or other conditions as they progress through reactors. Herein, the design constraints and advantages of Smart Tracers by simulating their operation in a laminar flow reactor model conducting chemical reactions of various orders are analyzed. It is noted that far fewer particles are necessary to completely map even the most complex concentration gradients compared with their conventional counterparts. Design criteria explored herein include sampling frequency, memory storage capacity, and ensemble number necessary to achieve the required accuracy to inform a reactor model. Cases of severe particle diffusion and sensor noise appear to bind the functional upper limit of such probes and require consideration for future design. The results of the study provide a starting framework for applying the new technology of microrobotics to the broad and impactful set of problems classified as chemical reactor analysis.en_US
dc.language.isoen
dc.publisherWileyen_US
dc.relation.isversionof10.1002/aisy.202300130en_US
dc.rightsCreative Commons Attributionen_US
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en_US
dc.sourceWileyen_US
dc.titleColloidal State Machines as Smart Tracers for Chemical Reactor Analysisen_US
dc.typeArticleen_US
dc.identifier.citationZhang, Ge, Yang, Jing Fan, Yang, Sungyun, Brooks, Allan M, Koman, Volodymyr B et al. 2023. "Colloidal State Machines as Smart Tracers for Chemical Reactor Analysis." Advanced Intelligent Systems, 5 (9).
dc.contributor.departmentMassachusetts Institute of Technology. Department of Chemical Engineeringen_US
dc.relation.journalAdvanced Intelligent Systemsen_US
dc.eprint.versionFinal published versionen_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dc.date.updated2026-01-23T21:49:22Z
dspace.orderedauthorsZhang, G; Yang, JF; Yang, S; Brooks, AM; Koman, VB; Gong, X; Strano, MSen_US
dspace.date.submission2026-01-23T21:49:26Z
mit.journal.volume5en_US
mit.journal.issue9en_US
mit.licensePUBLISHER_CC
mit.metadata.statusAuthority Work and Publication Information Neededen_US


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