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Record W2991418314 · doi:10.1002/ejic.201900981

Decorated Tetrathiafulvalene‐Based Ligands: Powerful Chemical Tools for the Design of Single‐Molecule Magnets

2019· article· en· W2991418314 on OpenAlexfundno aff
Olivier Cador, Boris Le Guennic, Lahcène Ouahab, Fabrice Pointillart

Bibliographic record

VenueEuropean Journal of Inorganic Chemistry · 2019
Typearticle
Languageen
FieldMaterials Science
TopicMagnetism in coordination complexes
Canadian institutionsnot available
FundersInstitute of Circulatory and Respiratory HealthEuropean Research CouncilÉcole Normale Supérieure de LyonRégion BretagneUniversité de Rennes 1Agence Nationale de la RechercheCentre National de la Recherche ScientifiqueEuropean Commission
KeywordsLanthanideSupramolecular chemistryMoleculeMagnetChemistrySingle-molecule magnetCoordination complexNanotechnologyIonMaterials scienceCombinatorial chemistryMetalMagnetizationMagnetic fieldOrganic chemistryPhysics

Abstract

fetched live from OpenAlex

This Minireview covers the design and characterization of coordination lanthanide complexes involving TTF‐based ligands. The specific design of TTF‐based ligands allowed the isolation of complexes with magnetic properties such as Single‐Molecule Magnets (SMMs) behavior and the studies of magnetic modulations due to supramolecular interaction, molecular engineering, magnetic dilution as well as isotopic enrichment. A careful design leads to TTF‐based ligands displaying several coordination sites in order to rationally elaborate polynuclear systems with multi‐SMM behavior or to auto‐assembly SMMs. Their redox activity allowed the investigation of coordination lanthanide complexes in several oxidation states and their consequences on optical and magnetic properties. The complete experimental and theoretical studies of such systems contributed to the understanding of the magnetic properties of lanthanide ions for futures applications in high density storage and quantum computing.

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)0.002
metaresearch head score (Gemma)0.001
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 score0.023
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.027
GPT teacher head0.231
Teacher spread0.204 · 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

Citations17
Published2019
Admission routes1
Has abstractyes

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