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Ultrafast Electron Scattering: Femtosecond Electron Pulses in Materials Research

2021· article· en· W3217686825 on OpenAlexaff
Laurent P. René de Cotret, Martin Otto, Jan‐Hendrik Pöhls, Tristan L. Britt, Mark J. Stern, Mark Sutton, Bradley J. Siwick

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced Electron Microscopy Techniques and Applications
Canadian institutionsMcGill University
Fundersnot available
KeywordsFemtosecondUltrashort pulseBrillouin zoneElectronLaserUltrafast electron diffractionRelaxation (psychology)PhononScatteringMaterials scienceOpticsNanotechnologyPhysicsOptoelectronicsCondensed matter physicsQuantum mechanics

Abstract

fetched live from OpenAlex

Combining ultrafast lasers and electron microscopes in novel ways makes it possible to directly ‘watch’ the time-evolving structure of condensed matter on the fastest timescales open to atomic motion. By combining such measurements with complementary (and more conventional) spectroscopic probes one can develop structure-property relationships for materials under even very far from equilibrium conditions and explore how light can be used to control material properties. Several examples of the remarkable new kinds of information that can be gleaned from ultrafast electron scattering will be given. For example, it is possible to make ‘molecular movies’ of atomic-level structural dynamics. It is also possible to directly probe the strength of the coupling between electrons and phonons in materials across the entire Brillouin zone and to probe nonequilibrium phonon dynamics (or relaxation) in exquisite detail. Femtosecond electron pulses are having broad impacts in materials research.

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 score0.040
Threshold uncertainty score0.558

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 head0.019
GPT teacher head0.390
Teacher spread0.371 · 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
Published2021
Admission routes1
Has abstractyes

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