Ultra-Wideline Solid-State NMR Spectroscopy
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Although solid-state NMR (SSNMR) provides rich information about molecular structure and dynamics, the small spin population differences between pairs of spin states that give rise to NMR transitions make it an inherently insensitive spectroscopic technique in terms of signal acquisition. Scientists have continuously addressed this issue via improvements in NMR hardware and probes, increases in the strength of the magnetic field, and the development of innovative pulse sequences and acquisition methodologies. As a result, researchers can now study NMR-active nuclides previously thought to be unobservable or too unreceptive for routine examination via SSNMR. Several factors can make it extremely challenging to detect signal or acquire spectra using SSNMR: (i) low gyromagnetic ratios (i.e., low Larmor frequencies), (ii) low natural abundances or dilution of the nuclide of interest (e.g., metal nuclides in proteins or in organometallic catalysts supported on silica), (iii) inconvenient relaxation characteristics (e.g., very long longitudinal or very short transverse relaxation times), and/or (iv) extremely broad powder patterns arising from large anisotropic NMR interactions. Our research group has been particularly interested in efficient acquisition of broad NMR powder patterns for a variety of spin-1/2 and quadrupolar (spin > 1/2) nuclides. Traditionally, researchers have used the term "wideline" NMR to refer to experiments yielding broad (1)H and (2)H SSNMR spectra ranging from tens of kHz to ∼250 kHz in breadth. With modern FT NMR hardware, uniform excitation in these spectral ranges is relatively easy, allowing for the acquisition of high quality spectra. However, spectra that range in breadth from ca. 250 kHz to tens of MHz cannot be uniformly excited with conventional, high-power rectangular pulses. Rather, researchers must apply special methodologies to acquire such spectra, which have inherently low S/N because the signal intensity is spread across such large spectral breadths. We have suggested the term ultra-wideline NMR (UWNMR) spectroscopy to describe this set of methodologies. This Account describes recent developments in pulse sequences and strategies for the efficient acquisition of UWNMR spectra. After an introduction to anisotropically broadened NMR patterns, we give a brief history of methods used to acquire UWNMR spectra. We then discuss new acquisition methodologies, including the acquisition of CPMG echo trains and the application of pulses capable of broadband excitation and refocusing. Finally, we present several applications of UWNMR methods that use these broadband pulses.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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 it