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Record W4411029084 · doi:10.1063/5.0269800

Impulsive excitation of squeezed phonons in single crystal germanium by an x-ray laser

2025· article· en· W4411029084 on OpenAlexaff
Nan Wang, Haoyuan Li, Yanwen Sun, Dillon F. Hanlon, Yijing Huang, Peihao Sun, Baochen She, Chance Ornelas-Skarin, Samuel W. Teitelbaum, Mark Sutton, P. H. Fuoss, Jerome Hastings, Takahiro Sato, Sanghoon Song, Mariano Trigo, David A. Reis, Mike Dunne, Diling Zhu

Bibliographic record

VenueApplied Physics Letters · 2025
Typearticle
Languageen
FieldPhysics and Astronomy
TopicForce Microscopy Techniques and Applications
Canadian institutionsMcGill University
FundersChemical Sciences, Geosciences, and Biosciences DivisionBasic Energy Sciences
KeywordsGermaniumPhononGermanium compoundsLaserExcitationX-rayMaterials scienceSingle crystalCrystal (programming language)OpticsAtomic physicsOptoelectronicsCondensed matter physicsPhysicsSiliconNuclear magnetic resonance

Abstract

fetched live from OpenAlex

In this Letter, we present the experimental observation of squeezed phonon generation in semiconductor germanium (Ge) induced by x-ray excitation. Prior x-ray pump, x-ray probe studies reported coherent longitudinal acoustic phonon generation in insulating oxides like strontium titanate and potassium tantalate. In contrast, such signals were not observed in semiconductors likely due to limited signal-to-noise ratio. Now, with an improved experimental setup, we observe a phonon response in single-crystal germanium. Utilizing x-ray split-delay optics with enhanced stability, we extract the phonon dispersion relation, which shows strong agreement with the calculated transverse acoustic phonon mode. Our results reveal that responses to x-ray excitations in semiconductors are of a similar nature to optical excitations. This suggests that the initial response to x-ray core–hole excitations rapidly diffuses to a non-local excitation, similar to what is observed with optical laser valence excitation on a femtosecond timescale.

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 score0.148
Threshold uncertainty score0.678

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 head0.005
GPT teacher head0.243
Teacher spread0.238 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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