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Record W4396871589 · doi:10.26434/chemrxiv-2024-6xq70

An Investigation into Transition States of CyclicTetra-Atomic Silicon and Germanium InterstellarDust Compounds: Si(x)C(4−x), Ge(x)C(4−x), andGe(x)Si(4−x) (x ∈ {1, 2, 3})

2024· preprint· en· W4396871589 on OpenAlexaff
Adam Mackenzie Flowers, Alex Brown, Mariusz Kłobukowski

Bibliographic record

VenueChemRxiv · 2024
Typepreprint
Languageen
FieldMaterials Science
TopicSilicon Nanostructures and Photoluminescence
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsGermaniumTetraSiliconGermanium compoundsCrystallographyChemistryMaterials scienceMetallurgy

Abstract

fetched live from OpenAlex

Presented in this work is a thorough determination of the transition states between the different isomers of cyclic tetra-atomic silicon-carbide, germanium-carbide, and germanium-silicide clusters. Through use of density functional theory (B3LYP-D3BJ, M06-2X, ωB97X-D4, and B2GP-PLYP) in conjunction with the aug-cc-pVTZ basis set, transition state structures and their barrier heights are determined for the interconversions between the various isomers for the family of tetra-atomic SiC, GeC, and GeSi compounds. SiC dust grains are known to be prevalent in interstellar dust, and among this group, so far only diamond-shaped (d-)SiC(3) has been detected in the interstellar medium (ISM). Determining which other structures might be detectable not only depends on their intrinsic spectroscopic features, but whether or not they are likely to exist as isomers in interstellar environments. By examining the energy barrier heights for transitions between isomers, we determined that many of these structures are unlikely to exhibit interconversion in the ISM, outside of hotter circumstellar environments. Although Boltzmann population ratios at approximate circumstellar temperatures suggest the presence of higher energy minima, it is likely that once interconversion happens, as molecules travel away from a star and cool, they will get kinetically trapped in the potential energy well they inhabit, making how the ratios freeze out dependent on the time and pathways the molecules take to cool down. As such, many of these higher energy minima may still be good candidates for detection including (rhomboidal) r-SiC(3), r-GeC(3), r-GeSi(3), (trapezoidal) t-Si(2)C(2), r-Ge(2)C(2), and d-Si(3)C.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

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)0.0020.000

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 head0.012
GPT teacher head0.249
Teacher spread0.237 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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
Published2024
Admission routes1
Has abstractyes

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