Imidazole‐Modified Lignin as a Suitable Substrate for Synthesis of N and S Co‐Doped Carbon Supported Cobalt Sulfide Dual‐Functional Electrocatalyst for Overall Water Splitting
Bibliographic record
Abstract
Abstract The hydrogen production by water electrolysis has attracted great research interest as a sustainable approach for clean energy production. However, such process is plagued by the use of high‐cost precious metal‐based catalysts (such as Pt, RuO2). Hereby, the use of a low‐cost Nitrogen and Sulfur co‐doped carbon‐supported cobalt sulfide dual‐functional electrocatalyst derived from imidazole modified lignin for overall water splitting is presented. To introduce nitrogen and sulfur heteroatoms in the carbon structure, lignin is modified by imidazolation through thiol‐alkynes click reaction. Imidazole‐lignin shows a strong chelation tendancy with cobalt salt, and N and the S co‐doped cobalt sulfide catalyst (IL‐Co@GC‐PO) is obtained by pyrolysis. The IL‐Co@GC‐PO has an oxygen evolution potential of 1.57 V and a hydrogen evolution overpotential of 204 mV at a current density of 10 mA cm−2. During the overall water splitting process, the IL‐Co@GC‐PO catalysts require only 1.58 V to reach a current density of 10 mA cm−2, which is equivalent to the performance of the system composed of the noble metal Pt/C||RuO2. This work not only provides a strategy for the preparation of N and S co‐doped cobalt sulfide catalysts, but also provides guidance for using lignin as a carbon source to design and develop cheap electrocatalysts.
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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".