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Record W2008106236 · doi:10.1134/s2070050413010108

Catalytic hydrodechlorination of chlorinated hydrocarbons in a medium of sodium hydroxide solutions. I: Conversion of carbon tetrachloride

2013· article· en· W2008106236 on OpenAlexaboutno aff
А. В. Терехов, Л. Н. Занавескин, К. Л. Занавескин, О. А. Конорев

Bibliographic record

VenueCatalysis in Industry · 2013
Typearticle
Languageen
FieldEngineering
TopicEnvironmental remediation with nanomaterials
Canadian institutionsnot available
Fundersnot available
KeywordsCatalysisChemistryAutoclaveCarbon tetrachlorideSodium hydroxideInorganic chemistryCarbon monoxideOrganic chemistryNuclear chemistry

Abstract

fetched live from OpenAlex

Carbon tetrachloride, classified as an ozone-depleting substance in the Montreal Protocol, is formed as a byproduct in the production of chlorinated hydrocarbons (chloromethanes, perchloroethylene, etc.). To develop a rational method of CCl 4 utilization (an alternative to burning), in this work we study the liquid-phase catalytic hydrodechlorination of CCl 4 with the formation of useful products such as sodium formiate, hexachloroethane, and perchloroethylene in the presence of aqueous sodium hydroxide solutions. Experiments are performed in a 300-mL autoclave at pressures of up to 1.5 MPa within a temperature range of 80–120°C on a Pd catalyst on sibunite (5 fractions, 0.1 to 1.6 mm). The dependences of the CCl 4 conversion and the selectivities with respect to the principal reaction products on the initial concentrations of CCl 4 and NaOH, the temperature, the partial pressure of hydrogen, the size of catalyst particles, and the palladium content in a catalyst are studied. Using the obtained data as a basis, we propose a process flowsheet, make some recommendations on the process conditions (depending on the specified composition of products), and determine the optimum catalyst characteristics: 1.5 wt % Pd on sibunite with a grain size of 0.315–0.63 mm. The proposed process allows us not only to solve the problem of recycling CCl 4 -containing wastes, but also to provide the production of three marketable products.

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 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 score0.029
Threshold uncertainty score0.937

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
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 head0.011
GPT teacher head0.200
Teacher spread0.189 · 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

Citations3
Published2013
Admission routes1
Has abstractyes

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