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Record W2588613540 · doi:10.1002/chem.201605980

Enhancing Photocatalytic Hydrogen Generation: the Impact of the Peripheral Ligands in Ru/Pd and Ru/Pt Complexes

2017· article· en· W2588613540 on OpenAlexaff
Nivedita Das, Gurmeet Singh Bindra, Avishek Paul, Johannes G. Vos, Martin Schulz, Mary T. Pryce

Bibliographic record

VenueChemistry - A European Journal · 2017
Typearticle
Languageen
FieldEnergy
TopicElectrocatalysts for Energy Conversion
Canadian institutionsRTDS Technologies (Canada)
FundersScience Foundation IrelandEnvironmental Protection Agency
KeywordsPhotocatalysisCatalysisLigand (biochemistry)ChemistryBipyridineHydrogenPlatinumSupramolecular chemistryMedicinal chemistryRutheniumPhotochemistry2,2'-BipyridineCrystallographyOrganic chemistryCrystal structureReceptor

Abstract

fetched live from OpenAlex

Abstract The synthesis, photophysical properties and photocatalytic efficiency of a range of novel supramolecular assemblies of the type [Ru(dceb)2(μ‐bisbpy)MCl2][PF6]2 and [Ru(bpy)2(μ‐bisbpy)MCl2][PF6]2 (M=Pd or Pt, dceb=diethyl 2,2’‐bipyridine‐4,4’‐dicarboxylate, bpy=2,2’‐bipyridine and bisbpy=2,2’:5’,3’’:6’’,2’’’‐quaterpyridine) are reported. Photocatalytic hydrogen generation was dependent on the nature of the peripheral ligand, on the catalytic centre and on the amount of water present in the photocatalytic mixture. The best catalytic conditions were obtained with the dceb peripheral ligand (turnover numbers up to 513 after 18 h). The experimental data and DFT calculations on both the bpy‐ and dceb‐based compounds indicated that the peripheral dceb ligands participated in the photocatalytic process.

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)0.000
metaresearch head score (Gemma)0.000
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: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.016
GPT teacher head0.245
Teacher spread0.229 · 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

Citations18
Published2017
Admission routes1
Has abstractyes

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