Laser-induced graphene with nickel oxide nanoparticles electrochemical immunosensor for rapid and label-free detection of Salmonella enterica Typhimurium.

Authors

Daniela A Oliveira, Cicero C Pola, Zachary T Johnson, Jingzhe Li, Emily A Smith, Eric S McLamore, Diana C Vanegas, Jonathan C Claussen, Carmen L Gomes

Published in

Mikrochimica acta. Volume 192. Issue 6. Pages 359. May 17, 2025. Epub May 17, 2025.

Abstract

Cost-effectiveness, high-throughput capability, and scalable manufacturing are key features required for the fabrication of in-field electrochemical sensors applicable to food safety analysis. In this work, a two-step method is described to create laser-induced graphene electrodes decorated with nickel oxide nanoparticles (LIG-NiO). Fabrication of the LIG-NiO electrodes is performed via direct writing under ambient conditions using a polyimide sheet and nickel acetate solution as substrates, which is then converted into a label-free immunosensor for the detection of Salmonella enterica serovar Typhimurium by functionalizing the working surface with an anti-Salmonella antibody. The resulting electrochemical immunosensor exhibits a sensitivity of 3.93 ± 0.25 Ω (log (CFU mL^-1)^-1), a limit of detection (LOD) of 8 ± 3 CFU mL^-1 and rapid response time (17 min) with a wide Salmonella Typhimurium linear sensing range, from 10¹ to 10⁶ CFU mL^-1 in buffer, covering relevant levels for food safety analysis without being affected by the presence of interferent bacteria Escherichia coli spp. Additionally, this LIG-NiO-based immunosensor presented a sensitivity of 1.92 ± 0.71 Ω (log (CFU mL^-1)^-1) when tested in chicken broth. The immunosensor developed in this study provides a simple fabrication method followed by functionalization and rapid Salmonella Typhimurium sensing that does not require sample pretreatment such as pre-enrichment or addition of external reagents, constituting a promising new sensing platform for pathogen detection in food safety monitoring and in general to other electrochemical immunosensing applications.

PMID:
40381040
Bibliographic data and abstract were imported from PubMed on 18 May 2025.

Read full publication at:
Please sign in to see all details.

Stats

1-terrible, 9-excellent. How would you rate this publication? Sign in in to submit your rating.

Post a comment

You need to be signed in to post comments. You can sign in here.

Comments

There are no comments yet.