Lynette Cegelski (source code)

= Lynette Cegelski
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\b[Lynette Cegelski] is a Stanford chemist who develops and applies <solid-state nuclear magnetic resonance> to determine composition and structure in complex materials. Her work connects the measured spectrum with the quantities that can be inferred from it.<Lynette Cegelski profile at Stanford University>[Official Stanford profile, appointment and research/publications]{ref}

\Image[https://biox.stanford.edu/files/styles/profile_thumbnail/public/lynette_cegelski_for_seminar_0.webp?orig=png]
{title=Lynette Cegelski, from her labeled Stanford institutional portrait}
{height=200}
{source=https://biox.stanford.edu/people/lynette-cegelski}

In a coauthored 2019 materials study, <carbon-13> <cross-polarization magic-angle spinning> spectra of individual <polymer> components were compared with spectra of intact polymer materials. The comparison yielded approximate carbon contributions from major components. Measuring the material itself provides information different from estimating its composition only from unused starting components.<Carbon compositional analysis of hydrogel contact lenses by solid-state NMR spectroscopy (2019)>[Author-hosted original abstract: individual-component spectra, intact materials and approximate carbon contributions]{ref}

An original calibration example explains why spectral response matters. Suppose two separately resolved contributions have intensities $I_A=60$ and $I_B=40$, with known <spectroscopic response factors> $k_A=2$ and $k_B=1$ in a model $I_i=k_i n_i$. The inferred carbon counts are proportional to 30 and 40, so the A fraction is $30/70=3/7$, rather than the raw-intensity fraction $60/100$.

These invented coefficients are not results from the paper. They illustrate the distinction between observing a spectral feature and calibrating its contribution to composition. Cegelski's materials measurements exemplify how <solid-state nuclear magnetic resonance> can make insoluble samples accessible to direct compositional analysis while retaining explicit limits on quantification.