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Record W4408308385 · doi:10.1002/solr.202400804

Lighting the Path to Practical Applications of Single‐Atom Catalysts in Photocatalysis: The Role of Platinum Group Single Atoms in Enhancing Catalytic Activity

2025· article· en· W4408308385 on OpenAlexaff
Zi Qi Chen, Aldrich Ngan, Christopher T. Chan, Jaeha Lee, David Dwi Sanjaya, Frank Gu

Bibliographic record

VenueSolar RRL · 2025
Typearticle
Languageen
FieldEnergy
TopicAdvanced Photocatalysis Techniques
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPhotocatalysisCatalysisPlatinumPlatinum groupGroup (periodic table)Atom (system on chip)Path (computing)Materials scienceChemistryNanotechnologyPhotochemistryComputer scienceOrganic chemistryEmbedded systemComputer network

Abstract

fetched live from OpenAlex

Single‐atom catalysts (SACs) show promise because of their efficient use of precious metals, unique coordination and electronic structures, and excellent tunability. Photocatalysis can harvest solar energy to drive energetically unfavorable reactions under mild conditions, offering a sustainable alternative to energy‐intensive reactions. However, the efficiency of solar photocatalysis is limited by poor solar spectrum utilization and rapid charge recombination. Integrating single atoms into semiconductor photocatalysts is a promising route to address these limitations. Mechanistic understanding of single‐atom photocatalysis is crucial for developing efficient catalysts as they guide effective material design. This work provides an overview of the current knowledge on platinum group SACs applied to photocatalytic applications with a focus on the role of single atoms in photocatalytic reactions. The review begins with a summary of the unique advantages of platinum group metal SACs as well as their common structures. A concise summary of synthesis methods is then provided, followed by a comprehensive review of characterization methods for SAC structure, photoelectronic properties, and mechanisms of action. Next, the role of single atoms in improving general photocatalytic processes as well as specific reactions are discussed. Finally, future outlooks for SAC development are included to guide further advancements in the field.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0020.003
Open science0.0010.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0030.002

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.

Opus teacher head0.009
GPT teacher head0.278
Teacher spread0.268 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations6
Published2025
Admission routes1
Has abstractyes

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