Enhanced Reaction Kinetics of Highly Selective Oxidation of 5-Hydroxymethylfurfural to 2,5-Furandicarboxylic Acid over NiCo<sub>2</sub>S<sub>4</sub>
Bibliographic record
Abstract
Selective valorization of biomass feedstocks and their derivatives, using renewable electricity to produce value-added chemicals, is a promising route to decarbonize the chemical industry. Herein, we demonstrate the selective production of 2,5-furandicarboxylic acid (FDCA) from the electrocatalytic oxidation of 5-hydroxymethylfurfural (HMF). NiCo 2 S 4 as an anode electrode exhibits almost 100% yield of FDCA with >90% Faradaic efficiency (FE) and high stability at optimized conditions, which outperforms pure NiS x and CoS x . Theoretical calculations reveal that the enhanced reaction kinetics for HMF conversion to FDCA on NiCo 2 S 4 arises from an optimal OH coverage and a more exergonic rate-limiting step compared with its monometallic counterparts. A techno-economic analysis (TEA) for a 100-ton/day FDCA industrial scale production facility reveals that the NiCo 2 S 4 catalyst could drive economic feasibility of the process. This work provides an economically feasible approach to sustainably produce FDCA from HMF oxidation by electrocatalysis.
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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".