ArticleNature communications2024
Machine learning aided design of single-atom alloy catalysts for methane cracking.
Article in Nature communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
14 citing papers in PubMed.
- Evaluating carbon affinity in catalytic methane decomposition using UBI-QEP energetics and DFT carbon-binding analysis.RSC advances · 2026Article
- Mapping Distinct Oxygen-Binding Regimes in Single-Atom Alloys.Small (Weinheim an der Bergstrasse, Germany) · 2026Article
- The Applications of Machine Learning in Micro-Nano Materials Research: From High-Throughput Screening to Intelligent Design.Small (Weinheim an der Bergstrasse, Germany) · 2026Review
- Hydrogen generation promoted by single-atom-based thermochemical catalysts.Nature reviews. Chemistry · 2026Review
- Generative intelligence explores the chemical space of ten million catalysts.Chemical science · 2026Article
- Sustainable Materials Design With Multi-Modal Artificial Intelligence.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Review
- Machine learning-guided design of energy-related catalysts from nanoparticles to single-atom sites.Communications chemistry · 2026Review
- High-Throughput Screening and Interpretable Machine Learning for Rational Design of Bimetallic Catalysts for Methane Activation.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Design strategies for dual-atom and multi-atom catalysts: Unlocking synergistic interactions in carbon-based electrocatalysis.Fundamental research · 2026Review
- Synergizing advanced materials and artificial intelligence for next-generation carbon capture, utilization, and storage (CCUS): a review.RSC advances · 2026Review
- Advancements in Single-Atom Catalysts: Synthesis, Characterization, and Applications in Sensing Technologies.Small science · 2025Review
- Knowledge Graph for Methane Selective Conversion: Revisiting and Predicting Product Selectivity and Methane Conversion.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Single Atom Engineering for Electrocatalysis: Fundamentals and Applications.ACS catalysis · 2025Review
- Machine learning and DFT database for C-H dissociation on single-atom alloy surfaces in methane decomposition.Scientific data · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
Abstract
The process of CH
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.