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Record W4407802824 · doi:10.1126/sciadv.adu1093

Exploring molecular superfluidity in hydrogen clusters

2025· article· en· W4407802824 on OpenAlexaff
Hatsuki Otani, Susumu Kuma, Shinichi Miura, Majd Mustafa, J.C. Lee, Pavle Djuricanin, Takamasa Momose

Bibliographic record

VenueScience Advances · 2025
Typearticle
Languageen
FieldPhysics and Astronomy
TopicQuantum, superfluid, helium dynamics
Canadian institutionsTRIUMFUniversity of British Columbia
Fundersnot available
KeywordsSuperfluidityHydrogen moleculeHydrogenPhysicsComputational biologyChemical physicsBiologyQuantum mechanics

Abstract

fetched live from OpenAlex

Molecular hydrogen (H 2 ) has long been predicted to exhibit superfluidity—a state of zero viscosity—at extremely low temperatures. However, its existence remains under debate despite several experimental reports. In this study, we investigated the infrared transitions of methane embedded in clusters of parahydrogen molecules at 0.4 K using high-resolution helium nanodroplet spectroscopy. Our results revealed fully quantized rotational states of methane with minimal interference from surrounding H 2 molecules, enabling precise determination of the rotational constant for each hydrogen cluster. The cluster-size dependence of the determined rotational constant aligns with behavior predicted by path-integral Monte Carlo simulations, indicating that more than 60% of the hydrogen molecules in the clusters participate in quantum bosonic exchanges, a characteristic feature of superfluidity. This work provides strong experimental evidence for the existence of a superfluid phase of molecular hydrogen at 0.4 K, representing a major step forward in understanding quantum behaviors in molecular systems.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.539
Threshold uncertainty score0.530

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0010.000
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 head0.022
GPT teacher head0.279
Teacher spread0.257 · 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

Citations2
Published2025
Admission routes1
Has abstractyes

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