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Hollow NiP–ZnIn<sub>2</sub>S<sub>4</sub> Heterojunction for Simultaneous Hydrogen and Pyruvic Acid Production from Lactic Acid Photoreforming

2023· article· en· W4387901227 on OpenAlexafffund
Tayebeh Roostaei, Heng Zhao, Mehdi Eisapour, Jun Zhao, Ali Omidkar, Zhangxin Chen, Jinguang Hu

Bibliographic record

VenueEnergy & Fuels · 2023
Typearticle
Languageen
FieldEnergy
TopicAdvanced Photocatalysis Techniques
Canadian institutionsUniversity of Calgary
FundersCanada First Research Excellence Fund
KeywordsPhotocatalysisHydrogen productionBifunctionalHydrogenPyruvic acidLactic acidChemistryCatalysisMaterials scienceChemical engineeringOrganic chemistry

Abstract

fetched live from OpenAlex

Photocatalytic hydrogen production provides an alternative approach to sustainable energy storage and conversion. However, the nonselective oxidation of sacrificial agents greatly increases the cost of green hydrogen generation. Herein, we demonstrate the simultaneous production of hydrogen and value-added chemicals by rationally designing a bifunctional photocatalyst. This approach uses hollow ZnIn 2 S 4 spheres with NiP as a cocatalyst, which enables the photocatalyst with dual functionalities to produce sustainable hydrogen and selectively dehydrogenate lactic acid into pyruvic acid. As a result, 381 μmol/h of H 2 is produced on the optimized photocatalyst with an apparent quantum yield of 11.1% at 365 ± 20 nm monochromatic light. Meanwhile, pyruvic acid, with a selectivity of 97.8%, is simultaneously achieved from lactic acid oxidation. Techno-economic analysis reveals the profitability of the present system and provides a promising outlook for the sustainability and economic viability of the unit. The present work demonstrates a good example of sustainable hydrogen and valuable chemical coproduction with the rational design of bifunctional photocatalytic materials.

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.106
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.012
GPT teacher head0.238
Teacher spread0.226 · 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 teacher head, not a consensus.

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

Citations15
Published2023
Admission routes2
Has abstractyes

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