MétaCan
Menu
Back to cohort
Record W2086718153 · doi:10.1134/s2070050414010024

A new gas-phase method for formic acid production: Tests on a pilot plant

2014· article· en· W2086718153 on OpenAlexaff
Т. В. Андрушкевич, G. Ya. Popova, Е. В. Данилевич, I.A. Zolotarskii, В. Б. Накрохин, Т. А. Никоро, С. И. Стомпель, Valentin N. Parmon

Bibliographic record

VenueCatalysis in Industry · 2014
Typearticle
Languageen
FieldChemical Engineering
TopicCatalysis and Oxidation Reactions
Canadian institutionsSafe Engineering Services & Technologies (Canada)
Fundersnot available
KeywordsFormaldehydeFormic acidMethanolCatalysisChemistryMethyl formatePartial oxidationYield (engineering)FormateCatalytic oxidationInorganic chemistryOrganic chemistryMaterials science

Abstract

fetched live from OpenAlex

Formic acid is industrially produced from methyl formate by multi-stage liquid-phase methods characterized by high capital intensity and high energy costs. The gas-phase synthesis of formic acid by catalytic oxidation of formaldehyde with atmospheric oxygen is developed at the Boreskov Institute of Catalysis. A pilot plant with productivity of up to 3 kg of formic acid per hour is constructed; its flow sheet and the apparatus constructions fully reproduce the future industrial process. It includes two catalytic stages: the oxidation of methanol to formaldehyde and the oxidation of formaldehyde to formic acid. Methanol is oxidized over a commercial iron-molybdenum catalyst oxide under conventional conditions. The oxidation of formaldehyde to acid is performed over titania-vanadia catalyst at temperatures of 120–140°C. Because of the narrow temperature range, a two-reactor flow sheet and the partial dilution of a bed with inert filling in the first of two reactors are used at the second stage. The tests are performed at a methanol concentration in the initial mixture of 6–7 vol % and the temperature is varied in the formaldehyde oxidation reactors. Under optimum conditions, the acid yield is 87–88% relative to the converted formaldehyde and 79–81% based on the converted methanol. This is achieved at the complete conversion of methanol and 96.5–98.5% conversion of formaldehyde. The technology meets the requirements of “green” chemistry.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.036
GPT teacher head0.322
Teacher spread0.285 · 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

Citations19
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueCatalysis in IndustrySame topicCatalysis and Oxidation ReactionsFrench-language works237,207