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Record W2016116755 · doi:10.1103/physrevb.72.184202

Helium adsorption in silica aerogel near the liquid-vapor critical point

2005· article· en· W2016116755 on OpenAlexaff
Tobias Herman, James Day, John Beamish

Bibliographic record

VenuePhysical Review B · 2005
Typearticle
Languageen
FieldChemistry
TopicAerogels and thermal insulation
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsAerogelCapillary condensationCritical point (mathematics)Vapor pressureHysteresisHeliumMaterials scienceDesorptionThermal conductivityBoiling pointLiquid heliumLambda pointCondensationCapillary actionAdsorptionThermodynamicsAnalytical Chemistry (journal)ChemistryCondensed matter physicsNanotechnologyComposite materialOrganic chemistry

Abstract

fetched live from OpenAlex

We have investigated the adsorption and desorption of helium near its liquid-vapor critical point in silica aerogels with porosities between 95% and 98%. We used a capacitive measurement technique which allowed us to probe the helium density inside the aerogel directly, even though the samples were surrounded by bulk helium. The aerogel's very low thermal conductivity resulted in long equilibration times so we monitored the pressure and the helium density, both inside the aerogel and in the surrounding bulk, and waited at each point until all had stabilized. Our measurements were made at temperatures far from the critical point, where a well-defined liquid-vapor interface exists, and at temperatures up to the bulk critical point. Hysteresis between adsorption and desorption isotherms persisted to temperatures close to the liquid-vapor critical point and there was no sign of an equilibrium liquid-vapor transition once the hysteresis disappeared. Many features of our isotherms can be described in terms of capillary condensation, although this picture becomes less applicable as the liquid-vapor critical point is approached and it is unclear how it can be applied to aerogels, whose tenuous structure includes a wide range of length scales.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.635
Threshold uncertainty score0.784

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)0.0010.001

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 head0.019
GPT teacher head0.319
Teacher spread0.300 · 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

Citations23
Published2005
Admission routes1
Has abstractyes

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