Chemical Ionization Mass Spectrometry: Fundamental Principles, Diverse Applications, and the Latest Technological Frontiers
Bibliographic record
Abstract
The review examines the evolution of chemical ionization mass spectrometry (CI-MS), a technique developed in 1966 by Field and Munson. CI is a soft-ionization method that produces more intense molecular ions with less fragmentation than electron ionization (EI). CI-MS is widely utilized across various fields, including atmospheric chemistry, environmental science, and biomedical research. The article highlights different CI-MS types, such as proton transfer reaction mass spectrometry (PTR-MS), which is renowned for its ability to analyze volatile organic compounds in real-time; negative ion CI-MS, which provides insights into anions; selected ion flow tube mass spectrometry (SIFT-MS), and ion-drift chemical ionization mass spectrometry (ID-CIMS), techniques that allow for the direct analysis of trace gases with high sensitivity and specificity. The article discusses advancements in chromatography with CI-MS, particularly atmospheric pressure chemical ionization (APCI) and liquid electron ionization (LEI) interface. The ongoing exchange of data between fundamental ion/molecule studies and specific applications has significantly boosted the growth of CI-MS in recent decades. In recent years, no extensive review has been published on CI-MS. This article provides an overview of CI-MS technique, its applications, and its evolution over the years, highlighting its importance in advancing scientific research and understanding the chemistry of various environments.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".