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Record W3115240221 · doi:10.1016/j.fuel.2020.119977

Interaction force between coal and Na-, K- and Ca- montmorillonite 001 surfaces in aqueous solutions

2020· article· en· W3115240221 on OpenAlexaff
Hongliang Li, Hua Han, Yue Wang, Xianshu Dong, Hongli Yang, Minqiang Fan, Yang Hu, Zeyu Feng

Bibliographic record

VenueFuel · 2020
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCoal and Its By-products
Canadian institutionsUniversity of Alberta
FundersTaiyuan University of TechnologyChina Scholarship CouncilNational Natural Science Foundation of China
KeywordsMontmorilloniteChaotropic agentCoalChemical engineeringChemistryContact angleAdsorptionAqueous solutionMaterials scienceOrganic chemistryComposite material

Abstract

fetched live from OpenAlex

In coal beneficiation, the clean coal would be easily contaminated with the super fine montmorillonite particles coating on it. This interaction between coal (hydrophobic) and montmorillonite (hydrophilic) surfaces is the interactions between the asymmetric systems. Previous studies detected the force between the montmorillonite and graphite or between the montmorillonite mounted tip and coal substrate to represent the interactions between 001 surface and coal. However, there is still lack of experimental direct measurement on the interaction between montmorillonite 001 surface and coal macerals. In this study, proposes methods for determinine the interactions between coal macerals and 001 surface of Na-, K- and Ca- montmorillonite directly by using an atomic force microscope (AFM). The results indicate that the 001 surface of Na- and Ca- montmorillonite served as the chaotropic and kosmotropic surface when it is adjacent to coal surfaces, with an attractive force and repulsive force occurring between them, respectively. The 001 surface of K-montmorillonite served as the chaotropic surface and kosmotropic surface while it is close to liptinite and inertinite, respectively. This chaotropic or kosmotropic property of the surface is determined by the coordination number of the cations and wettability of the hydrophobic surface simultaneously.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.038
Threshold uncertainty score0.721

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 head0.035
GPT teacher head0.219
Teacher spread0.184 · 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 designObservational
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

Citations12
Published2020
Admission routes1
Has abstractyes

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