Femtosecond Laser Assisted Chemical Ionization Mass Spectrometry: Toward Sub-ppq Detection Limits for Organic Molecules
Bibliographic record
Abstract
Ultrasensitive analysis of organic molecules is crucial for various fundamental research and applications. State-of-the-art techniques for this purpose can achieve detection limits of several hundred ppq (parts-per-quadrillion), while a higher sensitivity is pursued constantly. To achieve this goal, we develop femtosecond laser assisted chemical ionization for mass spectrometry. This technique combines the advantages of femtosecond laser ionization and chemical ionization, either of which enables subppt (parts-per-trillion) mass spectrometry analysis of organic molecules. The results demonstrate that the developed ionization technique, when employed in mass spectrometry, can surpass femtosecond laser ionization by more than 3 orders of magnitude in sensitivity, while still maintaining good versatility and the ability to work under ambient conditions. This work paves the way for subppq analysis of organic molecules in gas phase and even in ambient environments, which can open up new research fields for trace substance analysis in atmospheric environment, clinical diagnosis, biomedical studies, etc.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".