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Record W4416781443 · doi:10.1107/s1600576725009823

Room-temperature structure determination of vacuum-sensitive organic compounds by formvar encapsulation and serial electron diffraction

2025· article· en· W4416781443 on OpenAlexafffund
Sreelaja Pulleri Vadhyar, Ehsan Nikbin, Hazem Daoud, Jane Y. Howe, R. J. Dwayne Miller

Bibliographic record

VenueJournal of Applied Crystallography · 2025
Typearticle
Languageen
FieldEngineering
TopicSurface Chemistry and Catalysis
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSublimation (psychology)Electron diffractionTransmission electron microscopyMoleculeDiffractionElectron microscopeReflection high-energy electron diffractionAnthracene

Abstract

fetched live from OpenAlex

Samples used in electron microscopy are traditionally required to be stable under vacuum. However, many organic compounds with high vapor pressures readily sublime at room temperature, a process that is further accelerated under the high-vacuum conditions of an electron microscope. Here, we demonstrate for the first time the structure determination of vacuum-sensitive organic compounds in their solid state at room temperature using electron crystallography. Serial electron diffraction was employed to obtain sub-Å-resolution structures of anthracene and pyrene, two representative organic molecules which sublimate under the high-vacuum conditions of a transmission electron microscope. This was made possible by a simple sample preparation technique in which ultrathin crystals are encapsulated with a formvar layer to prevent sublimation under vacuum. By combining serial electron diffraction with formvar encapsulation, we demonstrate high-resolution structure determination of vacuum-sensitive samples at room temperature rather than cryogenic conditions. Moreover, by avoiding low-temperature phase transitions that can alter material properties, this method expands the accessible temperature range for studying the structural characteristics of vacuum-sensitive materials.

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 score0.003
Threshold uncertainty score0.536

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 head0.001
GPT teacher head0.176
Teacher spread0.175 · 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

Citations1
Published2025
Admission routes2
Has abstractyes

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