Split-Pool Method for Synthesis of Solid-State Material Combinatorial Libraries
Bibliographic record
Abstract
The synthesis and analysis of inorganic material combinatorial libraries by the split-pool bead method were demonstrated at the proof-of-concept level. Millimeter-size spherical beads of porous gamma-alumina, a commonly used support material for heterogeneous catalysts, were modified with Al(13)O(4)(OH)(24)(H(2)O)(12)(7+) cations in order to promote irreversible adsorption of the anionic fluorescent dyes Cascade Blue, Lucifer Yellow, and Sulforhodamine 101. The compositions of individual beads were easily determined through three split-pool cycles using a conventional fluorescence plate reader. Small split-pool material libraries were made by adsorbing noble metal salts (H(2)PtCl(6), H(2)IrCl(6), and RhCl(3)) into the beads. Analysis of these beads by micro-X-ray fluorescence showed that quantitative adsorption of metal salts without cross-contamination of beads could be achieved at levels (0.3 wt % metal loading) relevant to heterogeneous catalysis. The method offers the potential for synthesis of rather large libraries of inorganic materials through relatively simple benchtop split-pool chemistry.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.004 |
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".