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Raman-Based Diagnostics of Plant Diseases

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Plant diseases are one of the leading contributors to hunger in the world. Over 14% of crop losses can be directly attributed to disease, suggesting that if we could detect and subsequently prevent plant disease, the world would produce 14% more food. This is necessary as we will need to produce enough food to feed an estimated 9 billion people by 2050. Disease detection is significant because identifying the cause (be it biotic or abiotic) of plant issues can guide treatment and quarantine. Polymerase chain reaction (PCR) is the mainstay method of disease detection in plant pathology. While extremely accurate, it is reagent-hungry, slow, and has limited portability. Our lab uses Raman spectroscopy to detect structural changes within plant tissues associated with the disease. We analyze our spectra using Multivariate statistical methods to predict the presence of disease. Our objective is to build platforms for Raman disease and stress detection in the field.

 

 

Nanoscale Structural Characterization of Biological Systems Using AFM-IR

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A waxy cuticle acts as the first barrier between many plants and the outside world. Composed of primarily long chain aliphatic molecules, plant epicuticular wax has two critical, highly relevant properties. First, as a barrier, it is typically the first obstacle encountered by a pathogen or herbivore attempting to exploit the plant. Additionally, due to its highly organized nature, epicuticular wax is a compelling target for bioengineering of unique polymers. These characteristics make the characterization of intact wax critical; however, most extraction methods involve harsh solvents and fractionation, eliminating the organizational component of wax analysis. Using AFM-IR, our group is probing the chemical organization of the intact wax surface. We hope to characterize not only the wax surface itself, but also the interactions between the host cuticle and pathogens during an infection event.

 

 

Plasmonic Catalysis at the Nanoscale

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In the past decade, noble metal nanomaterials have been widely investigated to improve the efficiency and/or the selectively of catalytic processes. Recently, detailed research has shown that the catalytic properties of these nanomaterials are sensitive not only to the size but also to the shape of them due to their well-defined facets, i.e. facet-dependent catalysis. An obstacle in facet-dependent catalysis is how to determine the catalytic activity of specific groups of facets. Tip-enhanced Raman spectroscopy (TERS), a scanning probe microscope (SPM) based near-field super-resolution technology, has been proven capable of monitoring catalysis processes at the nanometer scale. In a recent study, we found that the chemical information from different facets of Au microplates (AuMPs) can be clearly distinguished and imaged with TERS. By taking advantage of the tip-broadening effect (TBE), typically thought of as a major weakness of atomic force microscope (AFM) based techniques, we found the TERS signals of catalyzed reduction products (N=N) are highly located at the top (corresponds to {111} facets) of AuMPs, while the sides (correspond to {100} or {110} facets) are dominated by the raw species (-NO2), indicating {111} has higher catalytic activity than {110} and {100} facets. Expanding upon these results, we use TERS to investigate dynamics of various photocatalytic and electrochemical processes at the nanoscale.

 

 

Forensic Analysis of Artificial Hair Dyes

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Hair is one of the most common types of physical evidence found at a crime scene. Forensic examination can suggest connections between a suspect and a crime scene or victim, or demonstrate an absence of such associations. Therefore, forensic analysis of hair evidence is invaluable to criminal investigations. Current hair forensic examinations are primarily based on a subjective microscopic comparison of hair found at the crime scene with a sample of suspect’s hair. Since this is often inconclusive, development of alternative and more accurate hair analysis techniques is critical. We develop surface-enhanced Raman spectroscopy (SERS) for confirmatory identification of dyes on hair. Using SERS, we can (1) identify whether hair was artificially dyed or not, (2) determine if permanent or semi-permanent colorants were used, and (3) distinguish the commercial brands that are utilized to dye hair. Expanding upon these results, we continue developing SERS-based dye diagnostics that can be used to solve many important problems in criminalistics and cosmetics.

 

 

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