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Record W2128395199 · doi:10.1021/la204580y

Three-Dimensional Structure and Defects in Colloidal Photonic Crystals Revealed by Tomographic Scanning Transmission X-ray Microscopy

2012· article· en· W2128395199 on OpenAlexaff
Jan Hilhorst, Matti M. van Schooneveld, Jian Wang, Emiel de Smit, Tolek Tyliszczak, Jörg Raabe, Adam P. Hitchcock, Martin Obst, Frank M. F. de Groot, Andrei V. Petukhov

Bibliographic record

VenueLangmuir · 2012
Typearticle
Languageen
FieldPhysics and Astronomy
TopicPhotonic Crystals and Applications
Canadian institutionsCanadian Light Source (Canada)University of Saskatchewan
Fundersnot available
KeywordsMicroscopyPhotonic crystalColloidal crystalMaterials scienceTransmission electron microscopyOpticsResolution (logic)PhotonicsStackingScanning confocal electron microscopyScatteringScanning electron microscopeScanning transmission electron microscopyColloidNanotechnologyOptoelectronicsChemistryPhysicsNuclear magnetic resonance

Abstract

fetched live from OpenAlex

Self-assembled colloidal crystals have attracted major attention because of their potential as low-cost three-dimensional (3D) photonic crystals. Although a high degree of perfection is crucial for the properties of these materials, little is known about their exact structure and internal defects. In this study, we use tomographic scanning transmission X-ray microscopy (STXM) to access the internal structure of self-assembled colloidal photonic crystals with high spatial resolution in three dimensions for the first time. The positions of individual particles of 236 nm in diameter are identified in three dimensions, and the local crystal structure is revealed. Through image analysis, structural defects, such as vacancies and stacking faults, are identified. Tomographic STXM is shown to be an attractive and complementary imaging tool for photonic materials and other strongly absorbing or scattering materials that cannot be characterized by either transmission or scanning electron microscopy or optical nanoscopy.

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 score0.590
Threshold uncertainty score0.559

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 head0.006
GPT teacher head0.240
Teacher spread0.234 · 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

Citations30
Published2012
Admission routes1
Has abstractyes

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