Solid-state NMR spectra of amino acid enantiomers and their relative intensities
Bibliographic record
Abstract
Under normal experimental conditions in an achiral environment, NMR spectra of enantiomers have chemical shifts and J couplings which are not differentiable. In this work, the reproducibility of spectral intensities for pairs of amino acid enantiomers, as well as factors influencing these intensities, is assessed using 13C and 15N cross-polarization magic-angle spinning (CP/MAS) NMR spectroscopy. Prompted by a recent literature debate over a possible influence of the chirality-induced spin selectivity (CISS) effect on spectral intensities obtained in CP/MAS NMR experiments carried out on enantiomers, a number of control experiments were performed with recycle delays of at least 5T1. These included the analysis of proton-decoupled Bloch decay solid-state NMR spectra as well as solution NMR spectra where the cross polarization process is absent. Bloch decay and CP/MAS NMR spectra yield the same relative intensities for pairs of enantiomers while solution NMR spectra provide relative intensities closest to unity. Differences of plus-or-minus a few percent in the D/L spectral intensity ratios observed in all solid-state NMR experiments are due to sample preparation (i.e., grinding, particle size, partial amorphization) and limitations on sample purity. As previously described in the literature, more drastic intensity differences on the order of 50% are easily created by ball milling the samples. Finally, apodization is shown to invert the apparent D/L ratio in low signal-to-noise 15N CP/MAS NMR spectra of aspartic acid enantiomers. In summary, no spectral intensity differences attributable to enantiomerism are identified.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".