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Record W4247844035 · doi:10.26434/chemrxiv.14719503

Modular Type III Porous Liquids based on Porous Organic Cage Microparticles

2021· preprint· en· W4247844035 on OpenAlex
Aiting Kai, Benjamin D. Egleston, Rob Clowes, Michael E. Briggs, Andrew I. Cooper, Rebecca L. Greenaway

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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueChemRxiv · 2021
Typepreprint
Languageen
FieldMaterials Science
TopicCovalent Organic Framework Applications
Canadian institutionsnot available
FundersEngineering and Physical Sciences Research CouncilChina Scholarship CouncilQueen's UniversityQueen's University BelfastRoyal Society
KeywordsIonic liquidPorosityMicroporous materialChemical engineeringDispersion (optics)Materials sciencePorous mediumThermal stabilityChemistryOrganic chemistryComposite materialCatalysis

Abstract

fetched live from OpenAlex

The dispersion of particulate porous solids in size-excluded liquids has emerged as a method to create Type III porous liquids, mostly using insoluble microporous materials such as metal-organic frameworks (MOFs) and zeolites. Here, we present the first examples of Type III porous liquids based on porous organic cages (POCs). By exploiting the solution processability of the POCs, racemic and quasiracemic cage microparticles were formed by chiral recognition. Dispersion of these porous microparticles in a range of size-excluded liquids, including oils and ionic liquids, formed stable POC-based Type III porous liquids. The flexible pairing between the solid POC particles and a carrier liquid allows the formation of a range of compositions, pore sizes, and other physicochemical properties to suit different applications and operating conditions. For example, we show that it is possible to produce porous liquids with relatively low viscosities (7-14 mpa∙s) or high thermal stability (325 °C). A 12.5 wt. % Type III porous liquid comprising racemic POC microparticles and an ionic liquid, [BPy][NTf<sub>2</sub>], shows a CO<sub>2</sub> working capacity (104.30 μmol/g<sub>L</sub>) that is significantly higher than the neat ionic liquid (37.27 μmol/g<sub>L</sub>) between 25 °C and 100 °C. This liquid is colloidally stable and can be recycled at least 10 times without loss of CO<sub>2</sub> capacity.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
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 score0.005
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.018
GPT teacher head0.252
Teacher spread0.234 · 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