Source abstract
Abstract
High Resolution Image Download MS PowerPoint Slide Developing electrochemical sensors capable of detecting multiple analytes at distinct potentials is vital for applications in environmental, biomedical, and quality monitoring. Here, we explore nanostructured, nonenzymatic α-Ni(OH) 2 as a versatile sensing material for the selective detection of phenol, catechol, and p -nitrophenol using two platforms: a standard three-electrode system and a portable strip sensor. α-Ni(OH) 2 was synthesized via a wet-chemical method and coated onto glassy carbon and screen-printed carbon electrodes for the respective configurations. Electron microscopy confirmed semicrystalline nanoscale morphology (nanoparticulate films), and cyclic voltammetry revealed clear redox signatures for each analyte, enabling selective detection with distinct peak positions across both systems. The three-electrode setup reached limits of detection of 0.003 μM (phenol), 0.1 μM (catechol), and 1 μM ( p -nitrophenol), whereas the portable sensor achieved 0.3, 1, and 2 μM, respectively. Amperometric measurements confirmed sensor performance at target potentials. Additionally, machine learning algorithms were applied to model signal behavior and support analyte classification. This combined approach demonstrates a robust strategy for sensitive, selective, and portable detection of multiple phenolic compounds.
Source: openalex_inverted_index · Quality: baseline
Affiliations
Department of Chemistry
Pandit Deendayal Energy University
Department of Chemical and Energy Engineering, London South Bank University, 103 Borough Road, London SE1 0AA, U.K.
Centre for Cooperative Research in Biomaterials (CIC biomaGUNE)
Basque Research and Technology Alliance (BRTA)
Chemistry and Forensic Science, School of Natural Sciences, University of Kent, Park Wood Rd, Canterbury CT2 7NH, U.K.
Department of Computer Science and Engineering
Funding
Royal Society · Department of Science and Technology, Ministry of Science and Technology, India