Synthesis of α-Amino Acids via Electrochemical Fixation of CO<sub>2</sub> to Imines Using Different Metal Cathodes
Bibliographic record
Abstract
The electrochemical fixation of CO2 by imines has recently attracted an increased interest as sustainable strategy for the synthesis of α-amino acids and a green alternative to the traditional Strecker synthesis, which relies on highly toxic precursors. Despite the industrial prospects of the electrochemical approach, the catalyst material effects on the selectivity of the process are still purely understood, hindering rational catalyst design. Herein, we study the electrochemical fixation of CO2 by N-benzylideneaniline using a wide variety of cathode materials, including 10 polycrystalline metals (Ti, Zn, Au, Pd, Pt, Sn, Ag, Ni, Fe, Cu), glassy carbon, and Pd nanoparticles of different shapes. We found that among all studied bulk metals, Ti and Zn show the best results with above 93% faradaic efficiency of α-amino acid, while other materials show from good to low selectivity (12% for Sn). We also demonstrate that especially high current densities and nearly quantitative faradaic efficiency and selectivity of α-amino acids can be achieved by employing Pd nanoparticles.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".