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Record W3048799828 · doi:10.1126/science.abc3183

Using nature’s blueprint to expand catalysis with Earth-abundant metals

2020· review· en· W3048799828 on OpenAlex
R. Morris Bullock, Jingguang G. Chen, Laura Gagliardi, Paul J. Chirik, Omar K. Farha, Christopher H. Hendon, Christopher W. Jones, John A. Keith, Jerzy Klosin, Shelley D. Minteer, Robert H. Morris, Alexander T. Radosevich, Thomas B. Rauchfuss, Neil A. Strotman, Aleksandra Vojvodić, Thomas R. Ward, Jenny Y. Yang, Yogesh Surendranath

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueScience · 2020
Typereview
Languageen
FieldChemistry
TopicMetal-Catalyzed Oxygenation Mechanisms
Canadian institutionsUniversity of TorontoDow Chemical (Canada)
FundersBasic Energy SciencesNational Institute of General Medical SciencesOffice of ScienceNational Institutes of HealthU.S. Department of Energy
KeywordsRhodiumBlueprintCatalysisPalladiumChemistryPrecious metalPlatinumNanotechnologyMaterials scienceOrganic chemistryEngineering

Abstract

fetched live from OpenAlex

Numerous redox transformations that are essential to life are catalyzed by metalloenzymes that feature Earth-abundant metals. In contrast, platinum-group metals have been the cornerstone of many industrial catalytic reactions for decades, providing high activity, thermal stability, and tolerance to chemical poisons. We assert that nature's blueprint provides the fundamental principles for vastly expanding the use of abundant metals in catalysis. We highlight the key physical properties of abundant metals that distinguish them from precious metals, and we look to nature to understand how the inherent attributes of abundant metals can be embraced to produce highly efficient catalysts for reactions crucial to the sustainable production and transformation of fuels and chemicals.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.928
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.003
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.077
GPT teacher head0.367
Teacher spread0.290 · 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