{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/113096"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/113096","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Study of mechanical effects of microfluidic channels in microneedles","abstract":"Modern neural probes integrate microfluidic chemical sampling to measure spatio-temporal neurochemical transients in the brain while also pursuing miniaturization to minimize tissue damage. This brings into question the effect of the integrated microfluidic channels on the mechanical integrity of these probes. We have developed a set of tools to help us answer this question. We built an analytical model to predict the mechanical strength of a probe and used that backbone to answer the inverse question of what range of geometries are available to us for a target brain. We then bench marked this model against more complex simulations which were in turn validated with literature sources. This helped us obtain more insights into the effect or lack thereof of microfluidic channels on a neural probe’s mechanical integrity. Finally, we fabricated samples to test and built a setup to experimentally measure the mechanical strength of our probes. The experimental measurements unfortunately do not agree with our simulations or analytical model for several reasons we have outlined. We need to build a more robust and precisely controlled setup in order to take better measurements and completely leverage the predictive powers of our models.","abstract_html":"Modern neural probes integrate microfluidic chemical sampling to measure spatio-temporal neurochemical transients in the brain while also pursuing miniaturization to minimize tissue damage. This brings into question the effect of the integrated microfluidic channels on the mechanical integrity of these probes. We have developed a set of tools to help us answer this question. We built an analytical model to predict the mechanical strength of a probe and used that backbone to answer the inverse question of what range of geometries are available to us for a target brain. We then bench marked this model against more complex simulations which were in turn validated with literature sources. This helped us obtain more insights into the effect or lack thereof of microfluidic channels on a neural probe’s mechanical integrity. Finally, we fabricated samples to test and built a setup to experimentally measure the mechanical strength of our probes. The experimental measurements unfortunately do not agree with our simulations or analytical model for several reasons we have outlined. We need to build a more robust and precisely controlled setup in order to take better measurements and completely leverage the predictive powers of our models.","abstract_has_math":false,"creators":["Iyer, Hrishikesh"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"M.S.","degree_level":"Thesis","degree_discipline":"Electrical & Computer Engr","degree_department":null,"school":null,"contributors":["Vlasov, Yurii"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2022,"date_issued":"2022-01-12T21:47:01Z","date_published":"2022-01-12T21:47:01Z","updated_at":"2026-07-22T22:24:53Z","subjects":["neural probe","microfluidic channel","buckling"],"languages":["en"],"rights":["Copyright 2021 Hrishikesh Iyer"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/2142/113096","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Vlasov, Yurii"]},{"key":"dc:creator","label":"Author","values":["Iyer, Hrishikesh"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2022-01-12T21:47:01Z","2021-07-22","2021-08"]},{"key":"dc:type","label":"Dc Type","values":["text","Thesis"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Electrical & Computer Engr"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["M.S."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["neural probe","microfluidic channel","buckling"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2021 Hrishikesh Iyer"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/2142/113096"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Modern neural probes integrate microfluidic chemical sampling to measure spatio-temporal neurochemical transients in the brain while also pursuing miniaturization to minimize tissue damage. This brings into question the effect of the integrated microfluidic channels on the mechanical integrity of these probes. We have developed a set of tools to help us answer this question. We built an analytical model to predict the mechanical strength of a probe and used that backbone to answer the inverse question of what range of geometries are available to us for a target brain. We then bench marked this model against more complex simulations which were in turn validated with literature sources. This helped us obtain more insights into the effect or lack thereof of microfluidic channels on a neural probe’s mechanical integrity. Finally, we fabricated samples to test and built a setup to experimentally measure the mechanical strength of our probes. The experimental measurements unfortunately do not agree with our simulations or analytical model for several reasons we have outlined. We need to build a more robust and precisely controlled setup in order to take better measurements and completely leverage the predictive powers of our models.","Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2022-01-12 without embargo terms","The student, Hrishikesh Iyer, accepted the attached license on 2021-07-22 at 11:56.","The student, Hrishikesh Iyer, submitted this Thesis for approval on 2021-07-22 at 12:06.","This Thesis was approved for publication on 2021-07-22 at 14:20.","DSpace SAF Submission Ingestion Package generated from Vireo submission #17063 on 2022-01-12 at 12:46:49","Made available in DSpace on 2022-01-12T21:47:01Z (GMT). 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We built an analytical model to predict the mechanical strength of a probe and used that backbone to answer the inverse question of what range of geometries are available to us for a target brain. We then bench marked this model against more complex simulations which were in turn validated with literature sources. This helped us obtain more insights into the effect or lack thereof of microfluidic channels on a neural probe’s mechanical integrity. Finally, we fabricated samples to test and built a setup to experimentally measure the mechanical strength of our probes. The experimental measurements unfortunately do not agree with our simulations or analytical model for several reasons we have outlined. We need to build a more robust and precisely controlled setup in order to take better measurements and completely leverage the predictive powers of our models.","Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2022-01-12 without embargo terms","The student, Hrishikesh Iyer, accepted the attached license on 2021-07-22 at 11:56.","The student, Hrishikesh Iyer, submitted this Thesis for approval on 2021-07-22 at 12:06.","This Thesis was approved for publication on 2021-07-22 at 14:20.","DSpace SAF Submission Ingestion Package generated from Vireo submission #17063 on 2022-01-12 at 12:46:49","Made available in DSpace on 2022-01-12T21:47:01Z (GMT). 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