Chitosan-encapsulated ZnS : M (M: Fe3+ or Mn2+) quantum dots for fluorescent labelling of sulphate-reducing bacteria
Source abstract
Abstract
Chitosan-encapsulated Mn2+ and Fe3+-doped ZnS colloidal quantum dots (QDs) were synthesized using chemical precipitation method. Though there are many reports on bio-imaging applications of ZnS QDs, the present study focussed on the new type of microbial-induced corrosive bacteria known as sulphate-reducing bacteria, Thiobacillus novellus. Sulphate-reducing bacteria can obtain energy by oxidizing organic compounds while reducing sulphates to hydrogen sulphide. This can create a problem in engineering industries. When metals are exposed to sulphate containing water, water and metal interacts and creates a layer of molecular hydrogen on the metal surface. Sulphate-reducing bacteria then oxidize the hydrogen while creating hydrogen sulphide, which contributes to corrosion for instance, in pipelines of oil and gas industries. In this study, detection and labelling of sulphate-reducing bacteria is demonstrated using fluorescent QDs. Chitosan capped ZnS QDs were synthesized using dopants at different doping concentrations. UV–Vis spectroscopy, XRD and FTIR characterizations were done to identify the optical band gap energy, crystal planes and determine the presence of capping agent, respectively. The morphology and the average particle size of 3.5 ± 0.2 nm were analysed using TEM which substantiated UV–Vis and XRD results. Photoluminescence spectroscopy detected the bacteria attachment to the QDs by showing significant blue shift in bacteria conjugated ZnS QDs. Fluorescence microscopy confirmed the fluorescent labelling of QDs to Thiobacillus novellus bacteria cells making them ideal for bio-labelling applications.
Source: openaire · Quality: candidate unverified · Source record ↗
Research context
OpenAlex topics: Advanced biosensing and bioanalysis techniques · Quantum Dots Synthesis And Properties · Biosensors and Analytical Detection
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
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