Fe–N<sub>4</sub>@Graphene Single-Atom Catalyst-Based Nanozyme against Influenza A Virus
Bibliographic record
Abstract
Recent COVID-19 pandemic has raised an urgent need for effective strategies to combat viruses that can pose serious health threats to the entire human race. Incorporating antipathogenic functions into everyday objects and personal protective equipment has become increasingly important, motivating the development of general-purpose antiviral materials. Single-atom catalysts, known for superior catalytic performance and maximized atomic utilization, have been explored in various research fields, including artificial nanozymes for bioapplications. We present reduced graphene oxide (rGO)-supported Fe–N 4 single-atom catalyst-based nanozyme (Fe–N-rGO) capable of achieving 99.99% viral deactivation against influenza A virus, outperforming bulk and nanoscale counterparts. The antiviral mechanism is attributed to the strong adsorption of hemagglutinin on the viral surface, leading to protein denaturation along with the potential generation of reactive oxygen species. Additionally, Fe–N-rGO with 1 wt % Fe can be uniformly coated onto arbitrary substrates, well-maintaining the strong antiviral performance.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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".