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Record W2332529589 · doi:10.1021/ja200715h

Highly Covalent Ferric−Thiolate Bonds Exhibit Surprisingly Low Mechanical Stability

2011· article· en· W2332529589 on OpenAlexaff
Peng Zheng, Hongbin Li

Bibliographic record

VenueJournal of the American Chemical Society · 2011
Typearticle
Languageen
FieldMaterials Science
TopicCorrosion Behavior and Inhibition
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsChemistryCovalent bondFerricBondPolymer chemistryComputational chemistryInorganic chemistryOrganic chemistry

Abstract

fetched live from OpenAlex

Depending on their nature, different chemical bonds show vastly different stability with covalent bonds being the most stable ones that rupture at forces above nanonewton. Studies have revealed that ferric-thiolate bonds are highly covalent and are conceived to be of high mechanical stability. Here, we used single molecule force spectroscopy techniques to directly determine the mechanical strength of such highly covalent ferric-thiolate bonds in rubredoxin. We observed that the ferric-thiolate bond ruptures at surprisingly low forces of ∼200 pN, significantly lower than that of typical covalent bonds, such as C-Si, S-S, and Au-thiolate bonds, which typically ruptures at >1.5 nN. And the mechanical strength of Fe-thiolate bonds is observed to correlate with the covalency of the bonds. Our results indicated that highly covalent Fe-thiolate bonds are mechanically labile and display features that clearly distinguish themselves from typical covalent bonds. Our study not only opens new avenues to investigating this important class of chemical bonds, but may also shed new lights on our understanding of the chemical nature of these metal thiolate bonds.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

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)0.0010.000

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 head0.031
GPT teacher head0.255
Teacher spread0.224 · 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 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

Citations86
Published2011
Admission routes1
Has abstractyes

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