An Ultrasensitive and Universal Surface Plasmonic Biosensor for Detection of Micropollutants in Aquatic Environments.
Jisui TanZongren DaiKaiming ZhouLin ZhangMiao HeYidong TanXiaohong ZhouPublished in: Environmental science & technology (2023)
Simple yet ultrasensitive and accurate quantification of a variety of analytical targets by virtue of a universal sensing device holds promise to revolutionize environmental monitoring, medical diagnostics, and food safety. Here, we propose a novel optical surface plasmon resonance (SPR) system in which the frequency-shifted light of different polarizations returned the laser cavity to stimulate laser heterodyne feedback interferometry (LHFI), hence amplifying the reflectivity change caused by the refractive index (RI) variations on the gold-coated SPR chip surface. In addition, the s -polarized light was further used as the reference to compensate the noise of the LHFI-amplified SPR system, resulting in nearly 3 orders of magnitude enhancement of RI resolution (5.9 × 10 -8 RIU) over the original SPR system (2.0 × 10 -5 RIU). By exploiting nucleic acids, antibodies, and receptors as recognition materials, a variety of micropollutants were detected with ultralow detection limits, ranging from a toxic metal ion (Hg 2+ , 70 ng/L) to a group of commonly occurring biotoxin (microcystins, 3.9 ng microcystin-LR/L) and a class of environmental endocrine disruptors (estrogens, 0.7 ng 17β-estradiol/L). This sensing platform exhibits several distinct characteristics, including dual improvement of sensitivity and stability and common-path optical construction without needing optical alignment, demonstrating a promising avenue toward environmental monitoring.
Keyphrases
- label free
- high speed
- high resolution
- human health
- gold nanoparticles
- risk assessment
- quantum dots
- high throughput
- wastewater treatment
- healthcare
- life cycle
- loop mediated isothermal amplification
- real time pcr
- single molecule
- air pollution
- circulating tumor cells
- big data
- molecularly imprinted
- machine learning
- silver nanoparticles
- climate change
- single cell
- mass spectrometry
- liquid chromatography