Design Guidelines for Membrane-separated Organic Electrosynthesis: The Case of Adiponitrile Production
Bibliographic record
Abstract
The on-going efforts to transition from thermal to electricity-driven processes can enable the easy integration of renewable energy sources and sustainable practices in chemical manufacturing. Organic electrosynthetic processes are key players in this transition, but face important challenges regarding selectivity and energy efficiency. Although membrane-separated flow reactors can help address these issues, a deeper understanding of membrane behavior in organic electrosynthesis electrolytes is required. In this study, we evaluate the effect of organic reactants on the conductivity and permeability of one cation exchange membrane (Nafion 117) and two anion exchange membranes (Sustainion and Fumasep FAB), and later assess the advantages of their implementation in flow reactors for organic electrosynthesis. This is done in the context of the electrohydrodimerization of acrylonitrile to adiponitrile, the largest organic electrosynthesis in industry. The presence of organic molecules led to important losses in membrane conductivity, however no significant contribution to reactor overpotential was observed from their implementation in membrane-separated reactors. Furthermore, permeabilities between 0.4 – 1.2 x 10-6 cm2 s-1 towards organic molecules led to low crossover of organics and improved reactor selectivity. Undivided reactors yielded selectivities as high as 48% (40 mA cm-2 and 4 V), while selectivities of 77% (20 mA cm-2 and 2.7 V) and 81% (40 mA cm-2 and 3 V) were obtained with Nafion and Sustainion-separated reactors, respectively. The demonstrated improvement in energy efficiency for continuous organic electrosynthesis processes makes the insights from this work a significant step in the development of sustainable electrochemical manufacturing processes.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.005 |
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".