Energy-conservative CO2 electroreduction for efficient formate co-generation
Bibliographic record
Abstract
Developing energy-conservative and highly efficient electrochemical systems is an appealing approach to co-generating value-added chemicals while simultaneously reducing energy input. In this work, an integrated electrochemical system combining CO 2 electroreduction (CO 2 RR) and polyethylene terephthalate (PET) plastic upcycling is developed for the efficient co-generation of formate. The cathodic electrocatalyst, comprising BiOI nanoclusters confined within carbon nanospheres, demonstrates excellent selectivity and stability for formate formation. The strong electronic metal-support interaction between BiOI nanoclusters and carbon substrate not only enhances CO 2 adsorption and charge transfer capabilities but also effectively modulates the electronic structure to facilitate CO 2 RR. Coupled with a highly active anodic electrocatalyst, NiCo 2 O 4 nanosheets grown on Ni foam, this integrated system achieves a formate Faradaic efficiency (FE) of 90 % at the cathode and 85 % at the anode at 250 mA cm⁻² over 140 hours. Techno-economic analysis further underscores the system’s economic feasibility and underscores its significant potential for commercial applications. • High performance in formate formation is achieved at both the cathode and the anode. • Strong electronic metal-support interaction (ESMI) enhances electrocatalyst durability. • Polyethylene terephthalate (PET) plastic upcycling significantly increases anodic product value. • An energy-efficient electrochemical system demonstrating economic feasibility has been developed.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".