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Record W4394596466 · doi:10.1021/acs.jpclett.4c00318

Cations and Anions Affect the Speed of Sound in Water Oppositely

2024· article· en· W4394596466 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

VenueThe Journal of Physical Chemistry Letters · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicChemical and Physical Studies
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsAffect (linguistics)Speed of soundSound (geography)AcousticsEnvironmental scienceChemistryCommunicationPhysicsPsychology

Abstract

fetched live from OpenAlex

Identifying the composition of a solution using acoustics remains a challenge. It is known that for low salt concentrations the speed of sound in water increases linearly with the concentration of the electrolyte, but the contribution of individual cations and anions is unknown. We introduce the concept of intrinsic sound speed A i to quantify the contribution of ions to the speed of sound. We found that cations increase the speed of sound in water whereas anions decrease the speed of sound. Hydration layers around the ions play a major role. Because cations have a hydration layer thicker than that of anions, their contribution to the speed of sound is larger than that of anions. Experimental data on salts not used to determine the contribution of individual ions are in quantitative agreement with the predicted values. Our method can be applied to various systems containing small quantities of ions, molecules, or particles. With the knowledge that cations increase the speed of sound, we were able to explain previously unexplained data in the literature.

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: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.147

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 head0.009
GPT teacher head0.248
Teacher spread0.239 · 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