Sensitive multichannel zero-to ultralow-field NMR with atomic magnetometer arrays
Bibliographic record
Abstract
Abstract Despite its versatility and high chemical specificity, conventional nuclear magnetic resonance (NMR) spectroscopy is limited in measurement throughput due to the need for high-homogeneity magnetic fields, necessitating sequential sample analysis, and expensive devices. Here, we propose a multichannel NMR device that addresses these limitations by leveraging the zero-to ultralow-field (ZULF) regime, where simultaneous detection of multiple samples is carried out via an array of compact optically pumped magnetometers (OPMs). A magnetic field is used only for prepolarization, permitting the use of large-bore, high-field, inhomogeneous magnets that can accommodate multiple samples concurrently. Through systematic improvements, we demonstrate sensitive, high-resolution ZULF NMR spectroscopy with sensitivity comparable to benchtop 13C NMR systems. The spectroscopy remains robust without the need for field shimming for periods on the order of weeks. We show the detection of ZULF NMR signals from organic molecules without isotopic enrichment, and demonstrate the parallelized detection of three distinct samples simultaneously as a proof-of-concept, with the ability to scale further to over 100 channels at a cost comparable to traditional liquid state NMR systems. This work sets the stage for using multichannel “NMR camera” devices for inline reaction monitoring, robotic chemistry, quality control, and high-throughput assays.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".