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Record W3165752174 · doi:10.1016/j.ceja.2021.100122

An environmentally friendly method for efficient atmospheric oxidation of pyrrhotite in arsenopyrite/pyrite calcine

2021· article· en· W3165752174 on OpenAlex

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueChemical Engineering Journal Advances · 2021
Typearticle
Languageen
FieldEngineering
TopicMetal Extraction and Bioleaching
Canadian institutionsNational Research Council CanadaQueen's University
FundersMitacsQueen's University
KeywordsPyrrhotitePyriteArsenopyriteArsenicEnvironmentally friendlySulfurSulfideChemistryLeaching (pedology)Inorganic chemistryMetallurgyMaterials scienceMineralogyGeologyChalcopyriteOrganic chemistryCopper

Abstract

fetched live from OpenAlex

Pyrite and arsenopyrite are the most common hosts for invisible gold, but pyrite and arsenic are refractory during conventional sulfide oxidation, which significantly challenges subsequent gold extraction. One option is high-temperature pretreatment of arsenical materials to sequester > 90% of the arsenic as a gas, then convert it to a stable form. This process produces a calcine similar in composition to pyrrhotite (Fe1-xS) but with higher porosity. In this study, the calcine product is oxidized with an efficient, cost-effective atmospheric process using acidic and near-neutral solutions. A sulfur mass balance analysis method based on iron sulfide thermal transformation in nitrogen atmosphere was developed to quantify the oxidation efficiency of pyrrhotite leaching. The optimization confirmed that > 90% of the calcine was oxidized by Fe3+ (5 and 10 g/L) and O2 (0.5 L/min) at pH 1 after 48 h and at 95 °C even without ultrafine grinding. Elemental sulfur was the main oxidation product when the oxidation pH was 1,2. This study provides the foundation for the development of a low-cost and environmentally friendly process option for pretreatment of arsenical sulfide refractory gold 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.

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: none
Teacher disagreement score0.223
Threshold uncertainty score0.602

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)0.0000.000

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 head0.005
GPT teacher head0.245
Teacher spread0.241 · 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