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Record W4224324300 · doi:10.3390/ma15093031

Structure Determination, Mechanical Properties, Thermal Stability of Co2MoB4 and Fe2MoB4

2022· article· en· W4224324300 on OpenAlexaff
Shijing Zhao, Wenju Zhou, Xiaojun Xiang, Xuyan Cao, Ning Chen, Weifeng Chen, Xiaohui Yu, Bingmin Yan, Huiyang Gou

Bibliographic record

VenueMaterials · 2022
Typearticle
Languageen
FieldMaterials Science
TopicBoron and Carbon Nanomaterials Research
Canadian institutionsCanadian Light Source (Canada)
FundersNational Natural Science Foundation of China
KeywordsX-ray absorption fine structureMaterials scienceValence (chemistry)Density functional theoryCrystallographyThermal stabilityThermogravimetric analysisCrystal structureBoronDifferential thermal analysisDiffractionXANESAnalytical Chemistry (journal)Spectral lineSpectroscopyChemistryComputational chemistryOptics

Abstract

fetched live from OpenAlex

The precise determination of atomic position of materials is critical for understanding the relationship between structure and properties, especially for compounds with light elements of boron and single or multiple transition metals. In this work, the single crystal X-ray diffraction is employed to analyze the atomic positions of Co2MoB4 and Fe2MoB4 with a Ta3B4-type structure, and it is found that the lengths of B-B bonds connecting the two zig-zag boron chains are 1.86 Å and 1.87 Å, but previously unreported 1.4 Å. Co and Fe atoms occupy the same crystallographic position in lattice for the doped samples and the valence is close to the metal itself, and Co/Fe K-edge X-ray Absorption Fine Structure(XAFS) spectra of borides with different ratios of Co to Fe are collected to detect the local environment and chemical valence of Co and Fe. Vickers hardness and nano indentation measurements are performed, together with the Density Functional Theory (DFT) calculations. Finally, Co2MoB4 possess better thermal stability than Fe2MoB4 evaluated by Thermogravimetric Differential Thermal Analysis (TG-DTA) results.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.020
Threshold uncertainty score0.981

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0200.000

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 head0.025
GPT teacher head0.246
Teacher spread0.221 · 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.

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
Published2022
Admission routes1
Has abstractyes

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