Peak Distortion Effects in Analytical Ion Chromatography
Bibliographic record
Abstract
The elution profile of chromatographic peaks provides fundamental understanding of the processes that occur in the mobile phase and the stationary phase. Major advances have been made in the column chemistry and suppressor technology in ion chromatography (IC) to handle a variety of sample matrices and ions. However, if the samples contain high concentrations of matrix ions, the overloaded peak elution profile is distorted. Consequently, the trace peaks shift their positions in the chromatogram in a manner that depends on the peak shape of the overloading analyte. In this work, the peak shapes in IC are examined from a fundamental perspective. Three commercial IC columns AS16, AS18, and AS23 were studied with borate, hydroxide and carbonate as suppressible eluents. Monovalent ions (chloride, bromide, and nitrate) are used as model analytes under analytical (0.1 mM) to overload conditions (10-500 mM). Both peak fronting and tailing are observed. On the basis of competitive Langmuir isotherms, if the eluent anion is more strongly retained than the analyte ion on an ion exchanger, the analyte peak is fronting. If the eluent is more weakly retained on the stationary phase, the analyte peak always tails under overload conditions regardless of the stationary phase capacity. If the charge of the analyte and eluent anions are different (e.g., Br(-) vs CO3(2-)), the analyte peak shapes depend on the eluent concentration in a more complex pattern. It was shown that there are interesting similarities with peak distortions due to strongly retained mobile phase components in other modes of liquid chromatography.
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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 | 0.007 | 0.022 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".