Near-infrared–driven decomposition of metal precursors yields amorphous electrocatalytic films
Bibliographic record
Abstract
Amorphous metal-based films lacking long-range atomic order have found utility in applications ranging from electronics applications to heterogeneous catalysis. Notwithstanding, there is a limited set of fabrication methods available for making amorphous films, particularly in the absence of a conducting substrate. We introduce herein a scalable preparative method for accessing oxidized and reduced phases of amorphous films that involves the efficient decomposition of molecular precursors, including simple metal salts, by exposure to near-infrared (NIR) radiation. The NIR-driven decomposition process provides sufficient localized heating to trigger the liberation of the ligand from solution-deposited precursors on substrates, but insufficient thermal energy to form crystalline phases. This method provides access to state-of-the-art electrocatalyst films, as demonstrated herein for the electrolysis of water, and extends the scope of usable substrates to include nonconducting and temperature-sensitive platforms.
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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 | 0.001 |
| 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".