{"id":{"repo_id":"cork","oai_identifier":"oai:cora.ucc.ie:10468/18412"},"canonical_url":"https://search.dev.ndltd.org/etd/cork/oai:cora.ucc.ie:10468/18412","repository":{"repo_id":"cork","name":"University College Cork","base_url":"https://cora.ucc.ie/server/oai/request"},"display":{"title":"The design of sensor interface circuits for electrochemical impedance spectroscopy","abstract":"Electrochemical Impedance Spectroscopy (EIS) has gained attention in biomedical applications—such as DNA, antigen–antibody, and virus detection—due to its label-free nature and high sensitivity. The development of EIS circuits with low power consumption, reduced complexity, and faster measurement times has been a particularly active area of research. However, the lengthy measurement times and the complexity of traditional EIS systems limit their adoption in real-time, portable, and low-cost point-of-care (PoC) applications. In addition, conventional RC-based equivalent AC impedance electrochemical sensor models, namely, models consisting of a resistor and a capacitor in parallel structure, cannot accurately reflect realistic sensor behavior; therefore, they do not support essential simulation analyses (e.g., transient, DC sweep, or DC operating point) and fail to facilitate accurate EIS sensor interface design. To address these challenges, this research introduces a dynamic model of an Ultra-Microband (UMB) sensor, implemented in Verilog-A, and proposes a fast, high-accuracy methodology for conducting EIS based on the Fast Fourier Transform (FFT). This approach aims to fulfill the requirements of portable, real-time, label-free EIS biomedical detection. The work begins by reviewing fundamental electrochemical principles and examining the electrode–electrolyte interface, represented by the Randles model. A static three-electrode small-signal impedance model of the UMB sensor is then analyzed to illustrate its application in small-signal scenarios such as EIS, thereby bridging the gap between electrochemists and electronic engineers. Subsequently, a dynamic model of the UMB sensor is developed and implemented in Verilog-A, enabling comprehensive simulations—such as AC stability, AC sweep, transient, and DC sweep—within Electronic Design Automation (EDA) tools like Cadence Spectre. This model thus captures more realistic sensor behavior and enhances design accuracy and robustness. Finally, a square-wave-based EIS approach is proposed by identifying the conditions under which the UMB sensor behaves as a Linear Time-Invariant (LTI) system. A circuit comprising a control amplifier and a Trans-Impedance Amplifier (TIA) is designed and fabricated in a 65 nm CMOS process to validate its feasibility for on-chip integration. The proposed square-wave EIS shortens the measurement time by 91.7% across frequencies ranging from 0.5 Hz to 500 Hz, with only a 2.73% average Mean Absolute Percentage Error (MAPE) compared to a commercial instrument (AutoLab). Tests using five premodified electrodes with four different concentrations of Ferrocene Carboxylic Acid (FcCOOH) demonstrate that this method is suitable for portable, real-time EIS biomedical detection and related applications.","abstract_html":"Electrochemical Impedance Spectroscopy (EIS) has gained attention in biomedical applications—such as DNA, antigen–antibody, and virus detection—due to its label-free nature and high sensitivity. The development of EIS circuits with low power consumption, reduced complexity, and faster measurement times has been a particularly active area of research. However, the lengthy measurement times and the complexity of traditional EIS systems limit their adoption in real-time, portable, and low-cost point-of-care (PoC) applications. In addition, conventional RC-based equivalent AC impedance electrochemical sensor models, namely, models consisting of a resistor and a capacitor in parallel structure, cannot accurately reflect realistic sensor behavior; therefore, they do not support essential simulation analyses (e.g., transient, DC sweep, or DC operating point) and fail to facilitate accurate EIS sensor interface design. To address these challenges, this research introduces a dynamic model of an Ultra-Microband (UMB) sensor, implemented in Verilog-A, and proposes a fast, high-accuracy methodology for conducting EIS based on the Fast Fourier Transform (FFT). This approach aims to fulfill the requirements of portable, real-time, label-free EIS biomedical detection. The work begins by reviewing fundamental electrochemical principles and examining the electrode–electrolyte interface, represented by the Randles model. A static three-electrode small-signal impedance model of the UMB sensor is then analyzed to illustrate its application in small-signal scenarios such as EIS, thereby bridging the gap between electrochemists and electronic engineers. Subsequently, a dynamic model of the UMB sensor is developed and implemented in Verilog-A, enabling comprehensive simulations—such as AC stability, AC sweep, transient, and DC sweep—within Electronic Design Automation (EDA) tools like Cadence Spectre. This model thus captures more realistic sensor behavior and enhances design accuracy and robustness. Finally, a square-wave-based EIS approach is proposed by identifying the conditions under which the UMB sensor behaves as a Linear Time-Invariant (LTI) system. A circuit comprising a control amplifier and a Trans-Impedance Amplifier (TIA) is designed and fabricated in a 65 nm CMOS process to validate its feasibility for on-chip integration. The proposed square-wave EIS shortens the measurement time by 91.7% across frequencies ranging from 0.5 Hz to 500 Hz, with only a 2.73% average Mean Absolute Percentage Error (MAPE) compared to a commercial instrument (AutoLab). Tests using five premodified electrodes with four different concentrations of Ferrocene Carboxylic Acid (FcCOOH) demonstrate that this method is suitable for portable, real-time EIS biomedical detection and related applications.","abstract_has_math":false,"creators":["Wang, Zhongzheng"],"institution":"University College Cork","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":["O'Hare, Daniel","O'Connell, Ivan","O'Riordan, Alan"],"committee_chairs":[],"committee_members":[],"year":2025,"date_issued":"2025","date_published":"2025","updated_at":"2026-07-24T01:46:44Z","subjects":["UMB","CV","EIS","FFT","Verilog-A","Sensor modelling"],"languages":["en"],"rights":["© 2025, Zhongzheng Wang."],"rights_urls":["https://creativecommons.org/licenses/by-nc/4.0/"],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/10468/18412","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["O'Hare, Daniel","O'Connell, Ivan","O'Riordan, Alan"]},{"key":"dc:creator","label":"Author","values":["Wang, Zhongzheng"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2026-01-20T10:33:44Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2026-01-20T10:33:44Z"]},{"key":"dc:date.issued","label":"Date","values":["2025"]},{"key":"dc:publisher","label":"Institution","values":["University College Cork"]},{"key":"dc:type","label":"Dc Type","values":["Doctoral thesis"]},{"key":"dc:type.qualificationlevel","label":"Dc Type Qualificationlevel","values":["Doctoral"]},{"key":"dc:type.qualificationname","label":"Dc Type Qualificationname","values":["PhD - Doctor of Philosophy"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["UMB","CV","EIS","FFT","Verilog-A","Sensor modelling"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["© 2025, Zhongzheng Wang."]},{"key":"dc:rights.uri","label":"Rights URI","values":["https://creativecommons.org/licenses/by-nc/4.0/"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://hdl.handle.net/10468/18412"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Electrochemical Impedance Spectroscopy (EIS) has gained attention in biomedical applications—such as DNA, antigen–antibody, and virus detection—due to its label-free nature and high sensitivity. The development of EIS circuits with low power consumption, reduced complexity, and faster measurement times has been a particularly active area of research. However, the lengthy measurement times and the complexity of traditional EIS systems limit their adoption in real-time, portable, and low-cost point-of-care (PoC) applications. In addition, conventional RC-based equivalent AC impedance electrochemical sensor models, namely, models consisting of a resistor and a capacitor in parallel structure, cannot accurately reflect realistic sensor behavior; therefore, they do not support essential simulation analyses (e.g., transient, DC sweep, or DC operating point) and fail to facilitate accurate EIS sensor interface design. To address these challenges, this research introduces a dynamic model of an Ultra-Microband (UMB) sensor, implemented in Verilog-A, and proposes a fast, high-accuracy methodology for conducting EIS based on the Fast Fourier Transform (FFT). This approach aims to fulfill the requirements of portable, real-time, label-free EIS biomedical detection. The work begins by reviewing fundamental electrochemical principles and examining the electrode–electrolyte interface, represented by the Randles model. A static three-electrode small-signal impedance model of the UMB sensor is then analyzed to illustrate its application in small-signal scenarios such as EIS, thereby bridging the gap between electrochemists and electronic engineers. Subsequently, a dynamic model of the UMB sensor is developed and implemented in Verilog-A, enabling comprehensive simulations—such as AC stability, AC sweep, transient, and DC sweep—within Electronic Design Automation (EDA) tools like Cadence Spectre. This model thus captures more realistic sensor behavior and enhances design accuracy and robustness. Finally, a square-wave-based EIS approach is proposed by identifying the conditions under which the UMB sensor behaves as a Linear Time-Invariant (LTI) system. A circuit comprising a control amplifier and a Trans-Impedance Amplifier (TIA) is designed and fabricated in a 65 nm CMOS process to validate its feasibility for on-chip integration. The proposed square-wave EIS shortens the measurement time by 91.7% across frequencies ranging from 0.5 Hz to 500 Hz, with only a 2.73% average Mean Absolute Percentage Error (MAPE) compared to a commercial instrument (AutoLab). Tests using five premodified electrodes with four different concentrations of Ferrocene Carboxylic Acid (FcCOOH) demonstrate that this method is suitable for portable, real-time EIS biomedical detection and related applications."]},{"key":"dc:format.mimetype","label":"Dc Format Mimetype","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["The design of sensor interface circuits for electrochemical impedance spectroscopy"]}]}],"canonical_facts":{"dc:contributor.advisor":["O'Hare, Daniel","O'Connell, Ivan","O'Riordan, Alan"],"dc:creator":["Wang, Zhongzheng"],"dc:date.accessioned":["2026-01-20T10:33:44Z"],"dc:date.available":["2026-01-20T10:33:44Z"],"dc:date.issued":["2025"],"dc:description.abstract":["Electrochemical Impedance Spectroscopy (EIS) has gained attention in biomedical applications—such as DNA, antigen–antibody, and virus detection—due to its label-free nature and high sensitivity. The development of EIS circuits with low power consumption, reduced complexity, and faster measurement times has been a particularly active area of research. However, the lengthy measurement times and the complexity of traditional EIS systems limit their adoption in real-time, portable, and low-cost point-of-care (PoC) applications. In addition, conventional RC-based equivalent AC impedance electrochemical sensor models, namely, models consisting of a resistor and a capacitor in parallel structure, cannot accurately reflect realistic sensor behavior; therefore, they do not support essential simulation analyses (e.g., transient, DC sweep, or DC operating point) and fail to facilitate accurate EIS sensor interface design. To address these challenges, this research introduces a dynamic model of an Ultra-Microband (UMB) sensor, implemented in Verilog-A, and proposes a fast, high-accuracy methodology for conducting EIS based on the Fast Fourier Transform (FFT). This approach aims to fulfill the requirements of portable, real-time, label-free EIS biomedical detection. The work begins by reviewing fundamental electrochemical principles and examining the electrode–electrolyte interface, represented by the Randles model. A static three-electrode small-signal impedance model of the UMB sensor is then analyzed to illustrate its application in small-signal scenarios such as EIS, thereby bridging the gap between electrochemists and electronic engineers. Subsequently, a dynamic model of the UMB sensor is developed and implemented in Verilog-A, enabling comprehensive simulations—such as AC stability, AC sweep, transient, and DC sweep—within Electronic Design Automation (EDA) tools like Cadence Spectre. This model thus captures more realistic sensor behavior and enhances design accuracy and robustness. Finally, a square-wave-based EIS approach is proposed by identifying the conditions under which the UMB sensor behaves as a Linear Time-Invariant (LTI) system. A circuit comprising a control amplifier and a Trans-Impedance Amplifier (TIA) is designed and fabricated in a 65 nm CMOS process to validate its feasibility for on-chip integration. The proposed square-wave EIS shortens the measurement time by 91.7% across frequencies ranging from 0.5 Hz to 500 Hz, with only a 2.73% average Mean Absolute Percentage Error (MAPE) compared to a commercial instrument (AutoLab). Tests using five premodified electrodes with four different concentrations of Ferrocene Carboxylic Acid (FcCOOH) demonstrate that this method is suitable for portable, real-time EIS biomedical detection and related applications."],"dc:format.mimetype":["application/pdf"],"dc:identifier.uri":["https://hdl.handle.net/10468/18412"],"dc:language.iso":["en"],"dc:publisher":["University College Cork"],"dc:rights":["© 2025, Zhongzheng Wang."],"dc:rights.uri":["https://creativecommons.org/licenses/by-nc/4.0/"],"dc:subject":["UMB","CV","EIS","FFT","Verilog-A","Sensor modelling"],"dc:title":["The design of sensor interface circuits for electrochemical impedance spectroscopy"],"dc:type":["Doctoral thesis"],"dc:type.qualificationlevel":["Doctoral"],"dc:type.qualificationname":["PhD - Doctor of Philosophy"]},"updated_at":"2026-07-24T01:46:44Z"}