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Record W4410486325 · doi:10.1016/j.gee.2025.05.007

Advancements in catalytic hydrogenation of nitrocyclohexane to cyclohexanone oxime

2025· article· en· W4410486325 on OpenAlex
Jinzhi Lu, Tongxin Song, Weiping Ding, Yan Zhu

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

VenueGreen Energy & Environment · 2025
Typearticle
Languageen
FieldChemistry
TopicNanomaterials for catalytic reactions
Canadian institutionsMinistry of Education and Child Care
FundersNatural Science Foundation of Jiangsu ProvinceNational Natural Science Foundation of China
KeywordsCyclohexanone oximeCyclohexanoneCatalysisOximeChemistryOrganic chemistryCatalytic hydrogenationCombinatorial chemistry

Abstract

fetched live from OpenAlex

Cyclohexanone oxime serves as a crucial intermediate in the synthesis of caprolactam, which is an essential precursor for manufacturing nylon fibers, high-performance engineering plastics, and specialized plastic films. Catalytic hydrogenation of nitrocyclohexane to cyclohexanone oxime has been documented to be an atom-economical, green and environmentally friendly process. In this review, we first introduce the current design rules of catalysts for catalytic hydrogenation of nitrocyclohexane in terms of both active metals and supports. Secondly, we discuss the influence of solvent effects on the cyclohexanone oxime from the nitrocyclohexane conversion. In addition, we concisely discuss typically proposed reaction pathways for the hydrogenation of nitrocyclohexane to produce cyclohexanone oxime. Finally, we provide our perspectives on some issues for catalytic conversion of nitrocyclohexane to cyclohexanone oxime in the future.

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)0.000
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 score0.042
Threshold uncertainty score0.897

Codex and Gemma teacher scores by category

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 head0.005
GPT teacher head0.209
Teacher spread0.204 · 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