Limits of identification using VUV spectroscopy applied to C8H18 isomers isolated by GC×GC

The vacuum ultraviolet detector for gas chromatography can be used to identify structural differences between isomers with similar chromatographic elution times, which adds detail to characterization, valuable for prescreening of sustainable aviation fuel candidates. Although this capability has been introduced elsewhere, vacuum ultraviolet spectroscopy for saturated hydrocarbons has been examined minimally, as the similarities between their spectra are much less significant than their aromatic counterparts. The fidelity with which structural differences can be identified has been unclear. In this work, all possible structural isomers of C₈H₁₈ are measured and determined to have unambiguously unique vacuum ultraviolet spectra. Using a statistically based residual comparison approach, the concentration limits at which the spectral differences are interpretable are tested in both a controlled study and a real fuel application. The concentration limit at which the spectral differences between C₈H₁₈ isomers are unambiguous is below 0.40% by mass and less than 0.20% with human discretion in our experimental configuration.

A Data Set Comparison Method Using Noise Statistics Applied to VUV Spectrum Match Determinations

It has been demonstrated that a pair of spectra exhibiting a coefficient of determination (R²) as low as 0.976 can originate from the same chemical species in one example, while a different pair of spectra exhibiting an R² up to 0.9997 can originate from different chemical species. The R² between spectra overlays depends on the signal-to-noise ratio, while the residual between any two spectra should look like noise only when the two spectra originate from the same chemical species. Numerical characteristics of the residual between two high-resolution spectra are invaluable toward the definitive elimination of many plausible matches of reference spectra to the sample spectra of analytes eluted from two-dimensional gas chromatography. Additionally, numerical characteristics beyond R² facilitate a logical ranking of all plausible matches, making positive identification of a single-component analyte possible provided a reference spectrum exists for all plausible matches. Specifically, the experimental background noise is shown to follow a Gaussian distribution at all wavelengths, and a method is described to normalize the data such that the numerically adjusted noise distributions are independent of wavelength. The differences between matching spectra are further shown to exhibit numerical characteristics consistent with the background noise's Gaussian distribution, common to all wavelengths. Seven criteria are described for judging the similarity between spectra: R² between the two spectra, R² of a Q-Q plot with one axis being ideal Gaussian quantiles and the other axis being the distribution of the numerically adjusted residual quantiles, the maximum count of consecutive (by wavelength) signs in the residual, and the first four moments of the residuals. One exemplar application of the methodology is a definitive match of n-undecane, n-dodecane, and n-tridecane sample spectra to their corresponding reference spectrum, which is among the most challenging set of species within the volatility range of jet fuel to differentiate by spectral methods. While this example is a significant stress test of the approach, the utility of the methodology generally is in the subtle math and transparent criteria that unambiguously identify mismatches because the distributions of residuals between mismatching spectra are very clearly not Gaussian and have a high consecutive sign count, even in cases where the R² between the compared spectra is ambiguous.

Strategies for integrating clinical preventive medicine into family medicine clerkships

The value of integrating preventive medicine into primary care is widely accepted, although practical teaching methods to model this integration into medical student clerkships are not well developed. This paper reports on a competency-based clinical preventive medicine curriculum developed within an existing family medicine clinical clerkship. Evaluation of the curriculum during its first full year of implementation shows that students can significantly improve their perceived levels of competence in discussing specific healthy behaviors and risk factors as well as their fund of knowledge in preventive medicine content areas. However, the greatest effect of the curriculum was on increasing students' knowledge of basic health promotion concepts. Results from this clerkship suggest that collaborative efforts to integrate clinical preventive medicine into primary care education and to support the teaching of health promotion and disease prevention in clinical clerkships can be successful.