Template Effect and Ligand Substitution Methods for the Synthesis of Iron Catalysts: A Two-Part Experiment for Inorganic Chemistry
Bibliographic record
Abstract
Abstract Asymmetric transfer hydrogenation is an important transformation for the production of fine chemicals. Traditionally, platinum group metals are used to catalyze this reaction, but recent pressure for greener practices has driven the development of base-metal catalysts. Due to the growing interest in this area of research, the underlying concepts for this type of chemistry are suitable for an undergraduate laboratory. A two-part experiment was adapted from original research and tested for use in an upper-division undergraduate inorganic chemistry laboratory. The first part of the experiment explores the template synthesis of a trans-bis-acetonitrile iron complex with a tetradentate ligand. The product from the first laboratory period is used as the starting material in the second laboratory period that focuses on the synthesis of a green catalyst mimic. Students learn about multi-step synthesis, specifically the synthesis of a catalyst for green chemistry, and key inorganic chemistry concepts to help reinforce topics introduced during lectures.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".