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Record W4389554440 · doi:10.1021/acs.iecr.3c03013

Constructing a Coupling Layer of an Inorganic Catalyst and a Conjugate Polymer for Efficient Electron Transport at the Biotic/Abiotic Interface

2023· article· en· W4389554440 on OpenAlexaff
Shuting Huang, Dongyun Chen, Najun Li, Qingfeng Xu, Hua Li, Hongbo Zeng, Jianmei Lu

Bibliographic record

VenueIndustrial & Engineering Chemistry Research · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicMicrobial Fuel Cells and Bioremediation
Canadian institutionsUniversity of Alberta
FundersNational Key Research and Development Program of ChinaPriority Academic Program Development of Jiangsu Higher Education InstitutionsNational Natural Science Foundation of China
KeywordsShewanella oneidensisCatalysisChemical engineeringPolymerChemistryElectron transport chainPhotocatalysisSulfideMaterials scienceOrganic chemistryBacteria

Abstract

fetched live from OpenAlex

A comodified strategy was developed to connect inorganic catalysts with conjugated polymers and outer-membrane proteins, where an in situ growth method was used to stimulate synergistic interactions fully and thus enhance photocatalytic performance of the biocatalysts. The biocatalyst bCdS/PA@MR-1 decolored low-concentration dyestuff wastewater continuously, with decoloring completed within 15 min. Under visible-light irradiation, the photoelectrons from cadmium sulfide and bioelectrons in bCdS/PA@MR-1 formed a fast electron flow, and electron transport occurred in the comodified structure. Moreover, the separation of photoholes can effectively promote the properties of bioelectrons produced by the bacteria Shewanella oneidensis MR-1 that were used to clean the photoholes to prevent damage or corrosion, thereby ensuring efficient decolorization of anthraquinone and azo dyes. After decolorization in dyes, the activity of bCdS/PA@MR-1 was rejuvenated, with the OD 600 value reaching 92.7% of that of the initial, illustrating advantages such as long shelf life and sustained renewable catalytic activity of the bCdS/PA@MR-1 biocatalyst.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.025
Threshold uncertainty score0.355

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.038
GPT teacher head0.288
Teacher spread0.251 · 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.

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

Citations1
Published2023
Admission routes1
Has abstractyes

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