{"id":{"repo_id":"houston","oai_identifier":"oai:uh-ir.tdl.org:10657/20862"},"canonical_url":"https://search.dev.ndltd.org/etd/houston/oai:uh-ir.tdl.org:10657/20862","repository":{"repo_id":"houston","name":"University of Houston","base_url":"https://uh-ir.tdl.org/server/oai/request"},"display":{"title":"Characterizing and Real-Time Monitoring of Various Types of Waters and Wastewaters Contaminated With Algae, Recycled Plastic Powders, and Clay Using the New Electrical Methods With Vipulanandan Models","abstract":"This study presents an advanced framework for real-time monitoring of contaminated water systems using Electrochemical Impedance Spectroscopy (EIS) integrated with the Vipulanandan Case-2 Smart Cement Model. The research bridges environmental water-quality assessment and impedance-based material characterization by developing a quantitative, model-driven method to evaluate the behavior of biological, chemical, and particulate contaminants under dynamic conditions. Six representative samples of algae, acidic algae, nitric acid (0.1 M), sodium hydroxide (0.1 M), polylactic acid (PLA), and bentonite clay were prepared in four concentrations and monitored over ten days, generating seventy-two datasets. Physicochemical parameters, including pH, EC, TDS, resistivity, DO, CO₂, NO₃⁻, and Cl,⁻ were measured alongside impedance spectra obtained between 20 Hz and 300 kHz using LCR meter configured in a two-probe, four-wire setup. The Vipulanandan Case-2 model accurately represented impedance responses (R² > 0.95, RMSE < 200) and extracted key parameters, resistance (Rc), capacitance (Cc), and relaxation time (τ = Rc × Cc). Distinct electrical signatures were observed for each contaminant: algal samples exhibited dielectric variation; nitric acid and NaOH showed dominant ionic conduction; PLA and bentonite displayed interfacial polarization effects. Strong correlations were identified between Rc, Cc, and EC/TDS, confirming τ as a reliable diagnostic indicator of contamination severity. Overall, this research validates EIS combined with the Vipulanandan Case-2 model as a reliable, reagent-free, and scalable technique for real-time water-quality monitoring, supporting future development of AI-enabled smart sensing networks for sustainable environmental and infrastructure management.","abstract_html":"This study presents an advanced framework for real-time monitoring of contaminated water systems using Electrochemical Impedance Spectroscopy (EIS) integrated with the Vipulanandan Case-2 Smart Cement Model. The research bridges environmental water-quality assessment and impedance-based material characterization by developing a quantitative, model-driven method to evaluate the behavior of biological, chemical, and particulate contaminants under dynamic conditions. Six representative samples of algae, acidic algae, nitric acid (0.1 M), sodium hydroxide (0.1 M), polylactic acid (PLA), and bentonite clay were prepared in four concentrations and monitored over ten days, generating seventy-two datasets. Physicochemical parameters, including pH, EC, TDS, resistivity, DO, CO₂, NO₃⁻, and Cl,⁻ were measured alongside impedance spectra obtained between 20 Hz and 300 kHz using LCR meter configured in a two-probe, four-wire setup. The Vipulanandan Case-2 model accurately represented impedance responses (R² > 0.95, RMSE < 200) and extracted key parameters, resistance (Rc), capacitance (Cc), and relaxation time (τ = Rc × Cc). Distinct electrical signatures were observed for each contaminant: algal samples exhibited dielectric variation; nitric acid and NaOH showed dominant ionic conduction; PLA and bentonite displayed interfacial polarization effects. Strong correlations were identified between Rc, Cc, and EC/TDS, confirming τ as a reliable diagnostic indicator of contamination severity. Overall, this research validates EIS combined with the Vipulanandan Case-2 model as a reliable, reagent-free, and scalable technique for real-time water-quality monitoring, supporting future development of AI-enabled smart sensing networks for sustainable environmental and infrastructure management.","abstract_has_math":false,"creators":["Radhakrishnan, Shanmathi 2001-"],"institution":"University of Houston","degree_name":"Master of Science","degree_level":null,"degree_discipline":"Construction Management","degree_department":null,"school":null,"contributors":[],"advisors":["Gao, Lu","Vipulanandan, Cumaraswamy"],"committee_chairs":[],"committee_members":["Shaffer, Devin L.","Din, Zia Ud"],"year":2025,"date_issued":"2025-12","date_published":"2025-12","updated_at":"2026-07-24T02:33:01Z","subjects":["Vipulanandan Model","Impedance Descriptors","Water Quality Monitoring","Bentonite Clay","Microplastics (PLA)","Algae"],"languages":["English"],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/10657/20862","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Gao, Lu","Vipulanandan, Cumaraswamy"]},{"key":"dc:contributor.committeemember","label":"Committee Member","values":["Shaffer, Devin L.","Din, Zia Ud"]},{"key":"dc:creator","label":"Author","values":["Radhakrishnan, Shanmathi 2001-"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2026-02-05T21:25:43Z"]},{"key":"dc:date.issued","label":"Date","values":["2025-12"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Construction Management"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Master of Science"]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Houston"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Vipulanandan Model","Impedance Descriptors","Water Quality Monitoring","Bentonite Clay","Microplastics (PLA)","Algae"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["English"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://hdl.handle.net/10657/20862"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["This study presents an advanced framework for real-time monitoring of contaminated water systems using Electrochemical Impedance Spectroscopy (EIS) integrated with the Vipulanandan Case-2 Smart Cement Model. The research bridges environmental water-quality assessment and impedance-based material characterization by developing a quantitative, model-driven method to evaluate the behavior of biological, chemical, and particulate contaminants under dynamic conditions. Six representative samples of algae, acidic algae, nitric acid (0.1 M), sodium hydroxide (0.1 M), polylactic acid (PLA), and bentonite clay were prepared in four concentrations and monitored over ten days, generating seventy-two datasets. Physicochemical parameters, including pH, EC, TDS, resistivity, DO, CO₂, NO₃⁻, and Cl,⁻ were measured alongside impedance spectra obtained between 20 Hz and 300 kHz using LCR meter configured in a two-probe, four-wire setup. The Vipulanandan Case-2 model accurately represented impedance responses (R² > 0.95, RMSE < 200) and extracted key parameters, resistance (Rc), capacitance (Cc), and relaxation time (τ = Rc × Cc). Distinct electrical signatures were observed for each contaminant: algal samples exhibited dielectric variation; nitric acid and NaOH showed dominant ionic conduction; PLA and bentonite displayed interfacial polarization effects. Strong correlations were identified between Rc, Cc, and EC/TDS, confirming τ as a reliable diagnostic indicator of contamination severity. Overall, this research validates EIS combined with the Vipulanandan Case-2 model as a reliable, reagent-free, and scalable technique for real-time water-quality monitoring, supporting future development of AI-enabled smart sensing networks for sustainable environmental and infrastructure management."]},{"key":"dc:format.mimetype","label":"Dc Format Mimetype","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Characterizing and Real-Time Monitoring of Various Types of Waters and Wastewaters Contaminated With Algae, Recycled Plastic Powders, and Clay Using the New Electrical Methods With Vipulanandan Models"]}]}],"canonical_facts":{"dc:contributor.advisor":["Gao, Lu","Vipulanandan, Cumaraswamy"],"dc:contributor.committeemember":["Shaffer, Devin L.","Din, Zia Ud"],"dc:creator":["Radhakrishnan, Shanmathi 2001-"],"dc:date.accessioned":["2026-02-05T21:25:43Z"],"dc:date.issued":["2025-12"],"dc:description.abstract":["This study presents an advanced framework for real-time monitoring of contaminated water systems using Electrochemical Impedance Spectroscopy (EIS) integrated with the Vipulanandan Case-2 Smart Cement Model. The research bridges environmental water-quality assessment and impedance-based material characterization by developing a quantitative, model-driven method to evaluate the behavior of biological, chemical, and particulate contaminants under dynamic conditions. Six representative samples of algae, acidic algae, nitric acid (0.1 M), sodium hydroxide (0.1 M), polylactic acid (PLA), and bentonite clay were prepared in four concentrations and monitored over ten days, generating seventy-two datasets. Physicochemical parameters, including pH, EC, TDS, resistivity, DO, CO₂, NO₃⁻, and Cl,⁻ were measured alongside impedance spectra obtained between 20 Hz and 300 kHz using LCR meter configured in a two-probe, four-wire setup. The Vipulanandan Case-2 model accurately represented impedance responses (R² > 0.95, RMSE < 200) and extracted key parameters, resistance (Rc), capacitance (Cc), and relaxation time (τ = Rc × Cc). Distinct electrical signatures were observed for each contaminant: algal samples exhibited dielectric variation; nitric acid and NaOH showed dominant ionic conduction; PLA and bentonite displayed interfacial polarization effects. Strong correlations were identified between Rc, Cc, and EC/TDS, confirming τ as a reliable diagnostic indicator of contamination severity. Overall, this research validates EIS combined with the Vipulanandan Case-2 model as a reliable, reagent-free, and scalable technique for real-time water-quality monitoring, supporting future development of AI-enabled smart sensing networks for sustainable environmental and infrastructure management."],"dc:format.mimetype":["application/pdf"],"dc:identifier.uri":["https://hdl.handle.net/10657/20862"],"dc:language.iso":["English"],"dc:subject":["Vipulanandan Model","Impedance Descriptors","Water Quality Monitoring","Bentonite Clay","Microplastics (PLA)","Algae"],"dc:title":["Characterizing and Real-Time Monitoring of Various Types of Waters and Wastewaters Contaminated With Algae, Recycled Plastic Powders, and Clay Using the New Electrical Methods With Vipulanandan Models"],"dc:type":["Thesis"],"thesis:degree_discipline":["Construction Management"],"thesis:degree_name":["Master of Science"],"thesis:institution_name":["University of Houston"]},"updated_at":"2026-07-24T02:33:01Z"}