Carbon Formation Mechanism of C<sub>2</sub>H<sub>2</sub> in Ni-Based Catalysts Revealed by in Situ Electron Microscopy and Molecular Dynamics Simulations
Bibliographic record
Abstract
Abstract Understanding the carbon formation mechanism is critical for designing catalysts in various applications. Here, we report the observation of the carbon formation mechanism on Ni-based catalysts by environmental transmission electron microscopy (ETEM) over a wide temperature range in combination with molecular dynamics simulations and density functional theory calculations. In situ TEM observation performed in a C2H2/H2 atmosphere provides real-time evidence that Ni3C is an intermediate phase that decomposes to graphitic carbon and metallic Ni, leading to carbon formation. Mechanisms of acetylene decomposition and evolution of carbon atom configuration are revealed by molecular dynamics simulations, which corroborate the experimental results. The modification of MgO on NiO can effectively decrease the formation of graphitic layers and thus enhance the catalytic performance of NiO. This finding may provide an insight into the origin of the carbon deposition and aid in developing effective approaches to mitigate it.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".