An Asymmetric Iron‐Based Redox‐Active System for Electrochemical Separation of Ions in Aqueous Media
Bibliographic record
Abstract
Abstract Electrochemically mediated redox‐active processes are gaining momentum as a promising liquid‐phase separation technology. Compared to conventional systems, they offer potential benefits, such as smaller energy footprints, nondestructive operation, reversibility, and tunability for specific analyte removal, with clear applications to societal and industrial challenges like water treatment and chemical synthesis. An asymmetric Faradaic cell heterogeneously functionalized with a metallopolymer at the anode and a hexacyanoferrate material at the cathode is presented for the first time. The redox‐active species' iron centers enhance the electrosorption of heavy metal oxyanions with up to 98% removal in the ppb range, and offer tunable operating windows as low as ≈0.1 V at ≈1 A m−2. By avoiding water splitting, the hexacyanoferrate cathode imparts additional advantages, namely a four‐fold reduction in adsorption energy requirements, full suppression of solution pH increase, and the ability to capture redox‐active catalytic anions such as polyoxometalates without altering their bulk oxidation state. This hybrid framework of a polymeric ferrocene anode and crystalline hexacyanoferrate cathode allows for simultaneous and synergistic uptake of anions and cations, respectively, creating a new asymmetric scheme for water‐based separations, with foreseeable future extension to fields such as ion‐sensing, energy storage, and electrocatalysis.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".