MétaCan
Menu
Back to cohort

Sulfur–Nitrogen Compounds

2005· other· en· W1859355651 on OpenAlexaff
T. Chivers

Bibliographic record

VenueEncyclopedia of Inorganic and Bioinorganic Chemistry · 2005
Typeother
Languageen
FieldChemistry
TopicChemical Reactions and Mechanisms
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsChemistrySulfurMoleculeBenzeneReactivity (psychology)NitrogenCrystallographyComputational chemistryOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract The quintessential sulfur–nitrogen compound, tetrasulfur tetranitride, S4N4, was first detected in 1835, just 10 years after the discovery of benzene. Its unusual structure, like that of benzene, was not elucidated for over 100 years. The application of diffraction techniques revealed the unusual cage arrangement with two weak cross‐ring sulfur–sulfur interactions. The details of the electronic structure of this fascinating molecule are still a matter for debate today. The polymer, (SN)x, was first obtained in 1910 and its metallic character was noted. However, it was the discovery in 1973 that a polymer comprising only nonmetallic elements behaves as a superconductor at 0.26 K that sparked widespread interest in sulfur–nitrogen (SN) chemistry. A year later it was proposed that planar SN heterocycles belong to a class of ‘electron‐rich aromatics’ that conform to the well‐known Hückel (4n + 2)π‐electron rule of organic chemistry. This suggestion, which was based on simple electron‐counting concepts, provided an additional impetus for both experimental and theoretical investigations of SN systems. In the past thirty years, the combination of structural studies, primarily through X‐ray crystallography, spectroscopic information, and molecular orbital calculations has provided reasonable rationalizations of the structure–reactivity relationships of these fascinating compounds. Interfaces with other areas of chemistry, for example, materials chemistry, organic synthesis, coordination chemistry, and biochemistry have been established and are under active investigation. For example, in the area of solid‐state chemistry, materials with unique magnetic and conducting properties that depend on intermolecular sulfur–nitrogen interactions between radical species have been designed. These new materials have potential applications in the construction of organic data recording devices. At the other end of the chemical spectrum,S‐nitrosothiols (RSNO) have been shown to be important species in the storage and transport of nitric oxide. As NO donors, these SN compounds have potential medical applications in the treatment of blood circulation problems. This contribution begins with a short discussion of structure and bonding in cyclic SN species. This is followed by an overview of the various physical methods that are used to characterize SN compounds. The subsequent sections deal with specific classes of SN compounds starting with binary species, which include cations and anions as well as neutral molecules. The next sections are concerned with two important classes of reagents, SN halides and SN oxides. Heterocyclothiazenes, in which a sulfur atom in an SN ring is replaced by another atom, most commonly carbon, phosphorus, or a transition metal, constitute a continually expanding area of investigation as reflected in the relatively large section on this topic. Sulfanuric ring systems, which involve sulfur in the +VI oxidation state, have been known for many years and recent interest has revolved around polymers involving the NS(O)R repeating unit, which are isoelectronic with the well‐known polyphosphazenes. The next section describes the chemistry of cyclic sulfur imides, that are structurally related to the cyclic sulfur allotropes by the replacement of one or more sulfur atoms by an imido (NR) group. In the final sections, the unusual properties of SN chains, including the unique polymer (SN)xare discussed.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.017
Threshold uncertainty score0.055

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0170.003

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 head0.005
GPT teacher head0.202
Teacher spread0.198 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations6
Published2005
Admission routes1
Has abstractyes

Explore more

Same venueEncyclopedia of Inorganic and Bioinorganic ChemistrySame topicChemical Reactions and MechanismsFrench-language works237,207