4 years ago

A novel enzyme based biosensor for catechol detection in water samples using artificial neural network

A novel enzyme based biosensor for catechol detection in water samples using artificial neural network
Biosensors could be used as digital devices to measure the sample infield. Consequently, computational programming along with experimental achievements are required. In this study, a novel biosensor/artificial neural network (ANN) integrated system was developed. Poly (3,4-ethylenedioxy-thiophene)(PEDOT), graphene oxide nano-sheets (GONs) and laccase (Lac) were used to construct a biosensor. The simple and one-pot process was accomplished by electropolymerizing 3,4-ethylenedioxy-thiophene (EDOT) along with GONs and Lac as dopants on glassy carbon electrode. Scanning electron microscopy (SEM) and electrochemical characterization were conducted to confirm successful enzyme entrapment. The modified electrode was employed to detect and measure catechol. The reaction of catechol and the prepared electrode was controlled by adsorption. Linear responses of the biosensor were over two ranges, 0.036–0.35μM and 0.35–2.5μM, with a detection limit of 0.032μM. The proposed biosensor was tested in real water samples successfully. The experimental test results were applied to train ANNs by the back-propagation algorithm. The input and output parameters were current and catechol concentration, respectively. Results from ANN modeling complied well with the experiments, signifying its useful application in biosensor technology.

Publisher URL: www.sciencedirect.com/science

DOI: S1369703X17302255

You might also like
Discover & Discuss Important Research

Keeping up-to-date with research can feel impossible, with papers being published faster than you'll ever be able to read them. That's where Researcher comes in: we're simplifying discovery and making important discussions happen. With over 19,000 sources, including peer-reviewed journals, preprints, blogs, universities, podcasts and Live events across 10 research areas, you'll never miss what's important to you. It's like social media, but better. Oh, and we should mention - it's free.

  • Download from Google Play
  • Download from App Store
  • Download from AppInChina

Researcher displays publicly available abstracts and doesn’t host any full article content. If the content is open access, we will direct clicks from the abstracts to the publisher website and display the PDF copy on our platform. Clicks to view the full text will be directed to the publisher website, where only users with subscriptions or access through their institution are able to view the full article.