A smartphone-based sensor for detection of iron and potassium in food and beverage samples.

A novel approach for simultaneous detection of iron and potassium via a smartphone-based potentiometric method is proposed in this study. The screen printed electrodes were modified with carbon black nanomaterial and ion selective membrane including zinc (II) phtalocyanine as the ionophore. The developed Fe3+-selective electrode and K+-selective electrode exhibited detection limits of 1.0 × 10-6 M and 1.0 × 10-5 M for Fe3+ and K+ ions, respectively. The electrodes were used to simultaneously detect Fe3+ and K+ ions in apple juice, skim milk, soybean and coconut water samples with recovery values between 90%-100.5%, and validated against inductively coupled plasma-optical emission spectrometry. Due to the advantageous characteristics of the sensors and the portability of Near Field Communication potentiometer supported with a smartphone application, the proposed method offers sensitive and selective detection of iron and potassium ions in food and beverage samples at the point of need.

Optical biosensors for diagnosis of COVID-19: nanomaterial-enabled particle strategies for post pandemic era.

The COVID-19 pandemic underlines the need for effective strategies for controlling virus spread and ensuring sensitive detection of SARS-CoV-2. This review presents the potential of nanomaterial-enabled optical biosensors for rapid and low-cost detection of SARS-CoV-2 biomarkers, demonstrating a comprehensive analysis including colorimetric, fluorescence, surface-enhanced Raman scattering, and surface plasmon resonance detection methods. Nanomaterials including metal-based nanomaterials, metal-organic frame-based nanoparticles, nanorods, nanoporous materials, nanoshell materials, and magnetic nanoparticles employed in the production of optical biosensors are presented in detail. This review also discusses the detection principles, fabrication methods, nanomaterial synthesis, and their applications for the detection of SARS-CoV-2 in four categories: antibody-based, antigen-based, nucleic acid-based, and aptamer-based biosensors. This critical review includes reports published in the literature between the years 2021 and 2024. In addition, the review offers critical insights into optical nanobiosensors for the diagnosis of COVID-19. The integration of artificial intelligence and machine learning technologies with optical nanomaterial-enabled biosensors is proposed to improve the efficiency of optical diagnostic systems for future pandemic scenarios.