Resistance Response and Heating Profiles of Electro-deposited ZnO Nanostructures for E-Nose Acetone Sensing
| Field | Value | Language |
| dc.contributor.author | Garay-Rairan, Fabian | |
| dc.contributor.author | Wang, Qi | |
| dc.contributor.author | Tricoli, Antonio | |
| dc.contributor.author | Qian, Jing | |
| dc.contributor.author | Lensky, Artem | |
| dc.contributor.author | Murugappan, Krishnan | |
| dc.contributor.author | Suominen, Hanna | |
| dc.date.accessioned | 2026-04-10T04:42:20Z | |
| dc.date.available | 2026-04-10T04:42:20Z | |
| dc.date.issued | 2026-04-10 | |
| dc.identifier.uri | https://hdl.handle.net/2123/35095 | |
| dc.description.abstract | This dataset contains the experimental performance records of two high-performing zinc oxide (ZnO) nanostructured sensors developed for electronic nose (E-Nose) applications. The data includes resistance measurements over time during exposure to varying concentrations of acetone, as well as the thermal characterization (heating process) of the samples. The sensors were fabricated using electrodeposition with different molarities (0.1M and 0.2M ZnCl2) and current densities (250uA and 3mA). The records show how the system responds to changes, how it recovers, and how stable the signal-to-noise ratio (SNR) is. This information is important for machine learning-based gas identification and sensitivity optimization in nanomanufacturing. | en |
| dc.language.iso | en | en |
| dc.rights | Creative Commons Attribution-NonCommercial 4.0 | en |
| dc.subject | Zinc Oxide | en |
| dc.subject | Biosensors | en |
| dc.subject | E-Nose | en |
| dc.subject | Nanotechnology | en |
| dc.subject | Acetone Sensing | en |
| dc.subject | Resistive Sensors | en |
| dc.title | Resistance Response and Heating Profiles of Electro-deposited ZnO Nanostructures for E-Nose Acetone Sensing | en |
| dc.type | Dataset | en |
| dc.subject.asrc | ANZSRC FoR code::40 ENGINEERING::4018 Nanotechnology::401807 Nanomaterials | en |
| dc.subject.asrc | ANZSRC FoR code::46 INFORMATION AND COMPUTING SCIENCES::4611 Machine learning | en |
| dc.identifier.doi | 10.25910/b72c-mj11 | |
| dc.relation.arc | DP190101864 | |
| dc.description.method | Synthesis and Fabrication: ZnO sensing layers were synthesized via electrochemical deposition onto Micrux platinum interdigitated electrodes (IDEs). The electrolyte consisted of ZnCl2 (0.01M to 0.2M) and a constant 0.1M KCl support. Deposition was performed using chronopotentiometry at constant currents (-100 uA to -5 mA) for durations of 10s to 60s at 70°C. Post-deposition, samples were calcined at 400°C for 2 hours to enhance crystallinity. Gas Sensing Measurements: The performance was evaluated in a Linkam gas-sensing chamber at an operating temperature of 300°C. Sensors were exposed to acetone concentrations (0.1–1 ppm) diluted in synthetic air (0.1 L/min O2 and 0.4 L/min N2) with a constant total flow rate of 0.5 L/min. Data Acquisition: Resistance dynamics were recorded using a Keithley 2700 digital multimeter controlled by a custom LabVIEW program. The provided datasets include the raw resistance response over time, baseline stabilization under synthetic air, and heating profiles used to characterize the thermal behavior of the 0.1M and 0.2M ZnCl2 samples. | en |
| dc.relation.other | NS210100083 | |
| dc.relation.other | FT200100939 | |
| dc.relation.other | AS008 | |
| usyd.faculty | SeS faculties schools::Faculty of Engineering::School of Biomedical Engineering | en |
| usyd.department | Nanotechnology Research Laboratory | en |
| workflow.metadata.only | No | en |
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