Sustainable Nanomaterials Combined with Raman Spectroscopy-based Techniques to Advance Environmental Sensing

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Virginia Tech


The propagation of contaminants in the environment continues to threaten public health and safety. Conventional analytical techniques for environmental detection require centralized facilities and intensive resources for operation. An effective implementation of a wide network of field deployable point-of-use (POU) sensors can potentially enable real-time monitoring of water quality parameters and inform decision making on public health outbreaks. The use of nanotechnology and field-deployable analytical tools can potentially advance the development of POU sensors for future field application. In this dissertation, we developed environmental sensing techniques that utilize nanocomposites made of low-cost, biocompatible, and sustainable nanomaterials combined with Raman spectroscopy. First, a technology pre-assessment was performed that included a comprehensive evaluation of cellulose-derived nanocomposites and nanobiotechnology enabled techniques for their sustainable long-term environmental application. Furthermore, to contribute to the better understanding of the potential environmental implications of nanomaterial production and application, life cycle assessment (LCA) was used to evaluate the environmental impacts of six iron precursors and seven iron oxide nanoparticle synthesis methods. Secondly, in the technology development step, gold (Au) and iron oxide (Fe3O4) nanoparticles were incorporated onto bacterial cellulose nanocrystals and nanoscale magnetite were synthesized. As proof-of-concept environmental applications, the Au@Fe3O4@BCNCs were applied for the magnetic separation and surface-enhanced Raman scattering (SERS) detection of malachite green isothiocyanate (MGITC), and nanoscale magnetite were applied for phosphate (PO43-) removal and recovery from synthetic urine matrices. Finally, in the technological application step, three environmental sensing applications are presented that use nanomaterial-based sensor platforms and/or Raman spectroscopic techniques. The first application involved using Lectin-modified BCNCs coupled SERS and machine learning for discrimination of bacterial strains. The second application presents a simple Raman-stable isotope labeling approach for the study of viral infection of bacteria. The third application involved use of SERS pH nanoprobes for measuring pH in droplets of complex matrices (e.g., DMEM cell culture media, human saliva).



Nanomaterials, environmental sensing, surface enhanced Raman spectroscopy (SERS), machine learning, environmental contaminants, virus, bacteria, point-of-use (POU) sensors