Investigation of Solvent-Free MALDI-TOFMS Sample Preparation Methods for the Analysis of Organometallic and Coordination Compounds
Bibliographic record
Abstract
An investigation of various solvent-free matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOFMS) sample preparation methods for the characterization of organometallic and coordination compounds is described. Such methods are desirable for insoluble materials, compounds that are only soluble in disadvantageous solvents, or complexes that dissociate in solution, all of which present a major "difficulty" to most mass spectrometry techniques. First-row transition metal acetylacetonate complexes, which have been characterized previously by solution preparation MALDI-TOFMS, were used to evaluate the various solvent-free procedures. These procedures comprise two distinct steps: the first being the efficient "solids mixing" (the mixing of sample and matrix), and the second being the effective transfer of the sample/matrix mixture to the MALDI target plate. This investigation shows that vortex mixing is the most efficient first step and that smearing using a microspatula is the most effective second step. In addition, the second step is shown to be much more critical than the first step in obtaining high-quality data. Case studies of truly insoluble materials highlight the importance of these techniques for the wider chemistry community.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".