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responsible for the spread of antibiotic resistance determinants following the introduction of new antibiotics, and the genes conferring antimicrobial resistance are increasingly common on mobile genetic
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capable of interpreting this information and integrating data from other “-omic” platforms such as genomics, transcriptomics, and proteomics. Leveraging artificial neural networks is the linchpin
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biological systems. Our laboratory contains two continuous wave/pulsed spectrometer systems equipped with components that improve resolution, signal to noise, and decrease sampling time (Band et al. Journal
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are also of interest. A short-term goal of this project is to validate the performance of electric-acoustic spectroscopy, which is a new method for the measurement of intermolecular interactions that is
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of sound is a property that yields very powerful data for developing fluid equations of state (EOS), and we have two such instruments for liquid and vapor-phase measurements covering a combined temperature
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. Currently, near ambient pressure electron spectroscopy is conducted using dexterously designed electron energy analyzers coupled with differentially pumped electron lenses, which made possible measurements
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variability that is due to experimental conditions in metabolomics experiments. The aim of this project is to establish a standard protocol to evaluate the analytical variability associated with liquid
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include near-infrared (IR) and mid-IR semiconductor laser-based absorption spectroscopy systems, ultraviolet (UV) to near-IR gas laser-based Raman spectroscopy systems, Fourier-transform IR spectrometers
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of emerging devices. The ultimate goal is to explore the landscape of emerging hardware-based artificial intelligence systems to better understand the role played by measurement and metrology in these complex
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modeling is the parametrization of the force field. There are a large number of force fields in existence and significant efforts are spent on their development and improvement. However, to-date, development