Bibliographic record
Abstract
This research is focused on development of routes towards the rational design of nanoparticle catalysts. Primarily, it is focused on two main projects; (1) the use of imidazolium-based ionic liquids (ILs) as greener media for the design of quasi-homogeneous nanoparticle catalysts and (2) the rational design of heterogeneous-supported nanoparticle catalysts from structured nanoparticle precursors. Each project has different studies associated with the main objective of the design of nanoparticle catalysts. In the first project, imidazolium-based ionic liquids have been used for the synthesis of nanoparticle catalysts. In particular, studies on recyclability, reuse, mode-of-stability, and long-term stability of these ionic-liquid supported nanoparticle catalysts have been done; all of which are important factors in determining the overall “greenness” of such synthetic routes. Three papers have been published/submitted for this project. In the first publication, highly stable polymer-stabilized Au, Pd and bimetallic Au-Pd nanoparticle catalysts have been synthesized in imidazolium-based 1-butyl-3-methylimidazolium hexafluorophosphate ([BMIM]PF6) ionic liquid (Journal of Molecular Catalysis A: Chemical, 2008, 286, 114). The resulting nanoparticles were found to be effective and selective quasi-homogeneous catalysts towards a wide-range of hydrogenation reactions and the catalyst solution was reused for further catalytic reactions with minimal loss in activity. The synthesis of very pure and clean ILs has allowed a platform to study the effects of impurities in the imidazolium ILs on nanoparticle stability. In a later study, a new mode of stabilization was postulated where the presence of low amounts of 1-methylimidazole has substantial effects on the resulting stability of Au and Pd-Au nanoparticles in these ILs (Chemical Communications, 2009, 812). In further continuation of this study, a comparative study involving four stabilization protocols for nanoparticle stabilization in BMIMPF6 IL is described, and have shown that nanoparticle stability and catalytic activity of nanoparticles is dependent on the overall stability of the nanoparticles towards aggregation (manuscript submitted). The second major project is focused on synthesizing structurally well-defined supported catalysts by incorporating the nanoparticle precursors (both alloy and core shell) into oxide frameworks (TiO2 and Al2O3), and examining their structure-property relationships and catalytic activity. a full article has been published on this project (Journal of Physical Chemistry C, 2009, 113, 12719) in which a route to rationally design supported catalysts from structured nanoparticle precursors with precise control over size, composition, and internal structure of the nanoparticles has been shown. In a continuation of this methodology for the synthesis of heterogeneous catalysts, efforts were carried out to apply the same methodology in imidazolium-based ILs as a one-pot media for the synthesis of supported-nanoparticle heterogeneous catalysts via the trapping of pre-synthesized nanoparticles into porous inorganic oxide materials. Nanoparticle catalysts in highly porous titania supports were synthesized using this methodology (manuscript to be submitted).
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".