{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/132802"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/132802","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"From purification, spectroscopy, and microscopy of carbon dots to synthesis modeling and AI-assisted spectral data extraction","abstract":"Carbon dots (CDs) occupy a unique niche among nano-sized fluorescent materials. This dissertation integrates purification-first experiments, single-particle multimodal characterization, physical modeling, and AI-assisted data curation. Part A develops and applies rigorous purification and fractionation to disentangle bottom-up products of CD synthesis from confounding small molecules; it then combines ensemble spectroscopy with single-particle fluorescence (Eric Gomez) and scanning tunneling microscopy to quantify intrinsic absorption, bandgaps, blinking behavior, and structure–emission correlations. Building on this foundation, I engineer an impurity-free CD–dye hybrid that converts blue–green emissive CDs to red emission via near-ideal spectral overlap and short donor–acceptor separation, demonstrating a scalable path to color-tunable emitters. To enable electronic and optical probing, I fabricate ultrathin, atomically flat, and semi-transparent template-stripped Au films that simultaneously support scanning tunneling microscopy and single-particle photoluminescence, unlocking direct structure–property mapping at the single-dot level simultaneously. Part B advances a mechanistic view of bottom-up CD synthesis by formulating a Monte-Carlo–based dynamics framework for CD assembly. It then addresses the data bottleneck that limits ML for spectroscopy by creating an LLM-assisted, high-throughput pipeline that collect machine-readable structure–solvent–spectrum data at scale. Overall, the dissertation (i) establishes purification and single-particle standards that separate CD signals from artifacts, (ii) delivers practical routes to color-tunable CD emitters, STM/PL characterization of single CDs, and assembly process modelling, and (iii) bridges experiments and AI by converting the spectroscopy literature into large, usable datasets. These advances provide a reproducible foundation and scalable data infrastructure for CD photophysics and, more broadly, AI materials discovery.","abstract_html":"Carbon dots (CDs) occupy a unique niche among nano-sized fluorescent materials. This dissertation integrates purification-first experiments, single-particle multimodal characterization, physical modeling, and AI-assisted data curation. Part A develops and applies rigorous purification and fractionation to disentangle bottom-up products of CD synthesis from confounding small molecules; it then combines ensemble spectroscopy with single-particle fluorescence (Eric Gomez) and scanning tunneling microscopy to quantify intrinsic absorption, bandgaps, blinking behavior, and structure–emission correlations. Building on this foundation, I engineer an impurity-free CD–dye hybrid that converts blue–green emissive CDs to red emission via near-ideal spectral overlap and short donor–acceptor separation, demonstrating a scalable path to color-tunable emitters. To enable electronic and optical probing, I fabricate ultrathin, atomically flat, and semi-transparent template-stripped Au films that simultaneously support scanning tunneling microscopy and single-particle photoluminescence, unlocking direct structure–property mapping at the single-dot level simultaneously. Part B advances a mechanistic view of bottom-up CD synthesis by formulating a Monte-Carlo–based dynamics framework for CD assembly. It then addresses the data bottleneck that limits ML for spectroscopy by creating an LLM-assisted, high-throughput pipeline that collect machine-readable structure–solvent–spectrum data at scale. Overall, the dissertation (i) establishes purification and single-particle standards that separate CD signals from artifacts, (ii) delivers practical routes to color-tunable CD emitters, STM/PL characterization of single CDs, and assembly process modelling, and (iii) bridges experiments and AI by converting the spectroscopy literature into large, usable datasets. These advances provide a reproducible foundation and scalable data infrastructure for CD photophysics and, more broadly, AI materials discovery.","abstract_has_math":false,"creators":["Bian, Zhengyi"],"institution":"University of Illinois Urbana-Champaign","degree_name":"Ph.D.","degree_level":"Dissertation","degree_discipline":"Chemistry","degree_department":null,"school":null,"contributors":["Gruebele, Martin","Nie, Shuming","Link, Stephan","Landes, Christy F."],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2025,"date_issued":"2025-12","date_published":"2025-12","updated_at":"2026-07-22T22:25:07Z","subjects":["Carbon dots","STM","Data Collection"],"languages":["en"],"rights":["Copyright 2025 Zhengyi Bian"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/2142/132802","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Gruebele, Martin","Nie, Shuming","Link, Stephan","Landes, Christy F."]},{"key":"dc:creator","label":"Author","values":["Bian, Zhengyi"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2025-12","2025-12-05"]},{"key":"dc:type","label":"Dc Type","values":["text","Thesis"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Chemistry"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Ph.D."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Carbon dots","STM","Data Collection"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2025 Zhengyi Bian"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://hdl.handle.net/2142/132802"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Carbon dots (CDs) occupy a unique niche among nano-sized fluorescent materials. This dissertation integrates purification-first experiments, single-particle multimodal characterization, physical modeling, and AI-assisted data curation. Part A develops and applies rigorous purification and fractionation to disentangle bottom-up products of CD synthesis from confounding small molecules; it then combines ensemble spectroscopy with single-particle fluorescence (Eric Gomez) and scanning tunneling microscopy to quantify intrinsic absorption, bandgaps, blinking behavior, and structure–emission correlations. Building on this foundation, I engineer an impurity-free CD–dye hybrid that converts blue–green emissive CDs to red emission via near-ideal spectral overlap and short donor–acceptor separation, demonstrating a scalable path to color-tunable emitters. To enable electronic and optical probing, I fabricate ultrathin, atomically flat, and semi-transparent template-stripped Au films that simultaneously support scanning tunneling microscopy and single-particle photoluminescence, unlocking direct structure–property mapping at the single-dot level simultaneously. Part B advances a mechanistic view of bottom-up CD synthesis by formulating a Monte-Carlo–based dynamics framework for CD assembly. It then addresses the data bottleneck that limits ML for spectroscopy by creating an LLM-assisted, high-throughput pipeline that collect machine-readable structure–solvent–spectrum data at scale. Overall, the dissertation (i) establishes purification and single-particle standards that separate CD signals from artifacts, (ii) delivers practical routes to color-tunable CD emitters, STM/PL characterization of single CDs, and assembly process modelling, and (iii) bridges experiments and AI by converting the spectroscopy literature into large, usable datasets. These advances provide a reproducible foundation and scalable data infrastructure for CD photophysics and, more broadly, AI materials discovery.","Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2027-12-01","The student, Zhengyi Bian, accepted the attached license on 2025-12-05 at 08:20.","The student, Zhengyi Bian, submitted this Dissertation for approval on 2025-12-05 at 08:23.","This Dissertation was approved for publication on 2025-12-05 at 16:42.","DSpace SAF Submission Ingestion Package generated from Vireo submission #23075 on 2026-02-19 at 20:10:03"]},{"key":"dc:format","label":"Dc Format","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["From purification, spectroscopy, and microscopy of carbon dots to synthesis modeling and AI-assisted spectral data extraction"]}]}],"canonical_facts":{"dc:contributor":["Gruebele, Martin","Nie, Shuming","Link, Stephan","Landes, Christy F."],"dc:creator":["Bian, Zhengyi"],"dc:date":["2025-12","2025-12-05"],"dc:description":["Carbon dots (CDs) occupy a unique niche among nano-sized fluorescent materials. This dissertation integrates purification-first experiments, single-particle multimodal characterization, physical modeling, and AI-assisted data curation. Part A develops and applies rigorous purification and fractionation to disentangle bottom-up products of CD synthesis from confounding small molecules; it then combines ensemble spectroscopy with single-particle fluorescence (Eric Gomez) and scanning tunneling microscopy to quantify intrinsic absorption, bandgaps, blinking behavior, and structure–emission correlations. Building on this foundation, I engineer an impurity-free CD–dye hybrid that converts blue–green emissive CDs to red emission via near-ideal spectral overlap and short donor–acceptor separation, demonstrating a scalable path to color-tunable emitters. To enable electronic and optical probing, I fabricate ultrathin, atomically flat, and semi-transparent template-stripped Au films that simultaneously support scanning tunneling microscopy and single-particle photoluminescence, unlocking direct structure–property mapping at the single-dot level simultaneously. Part B advances a mechanistic view of bottom-up CD synthesis by formulating a Monte-Carlo–based dynamics framework for CD assembly. It then addresses the data bottleneck that limits ML for spectroscopy by creating an LLM-assisted, high-throughput pipeline that collect machine-readable structure–solvent–spectrum data at scale. Overall, the dissertation (i) establishes purification and single-particle standards that separate CD signals from artifacts, (ii) delivers practical routes to color-tunable CD emitters, STM/PL characterization of single CDs, and assembly process modelling, and (iii) bridges experiments and AI by converting the spectroscopy literature into large, usable datasets. These advances provide a reproducible foundation and scalable data infrastructure for CD photophysics and, more broadly, AI materials discovery.","Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2027-12-01","The student, Zhengyi Bian, accepted the attached license on 2025-12-05 at 08:20.","The student, Zhengyi Bian, submitted this Dissertation for approval on 2025-12-05 at 08:23.","This Dissertation was approved for publication on 2025-12-05 at 16:42.","DSpace SAF Submission Ingestion Package generated from Vireo submission #23075 on 2026-02-19 at 20:10:03"],"dc:format":["application/pdf"],"dc:identifier":["https://hdl.handle.net/2142/132802"],"dc:language":["en"],"dc:rights":["Copyright 2025 Zhengyi Bian"],"dc:subject":["Carbon dots","STM","Data Collection"],"dc:title":["From purification, spectroscopy, and microscopy of carbon dots to synthesis modeling and AI-assisted spectral data extraction"],"dc:type":["text","Thesis"],"thesis:degree_discipline":["Chemistry"],"thesis:degree_level":["Dissertation"],"thesis:degree_name":["Ph.D."],"thesis:institution_name":["University of Illinois Urbana-Champaign"]},"updated_at":"2026-07-22T22:25:07Z"}