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Record W2395571735 · doi:10.1021/acs.accounts.6b00100

An Organolanthanide Building Block Approach to Single-Molecule Magnets

2016· article· en· W2395571735 on OpenAlexafffund
Katie L. M. Harriman, Muralee Murugesu

Bibliographic record

VenueAccounts of Chemical Research · 2016
Typearticle
Languageen
FieldMaterials Science
TopicMagnetism in coordination complexes
Canadian institutionsUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Ottawa
KeywordsAtomic orbitalSpintronicsMagnetizationLanthanideChemistryChemical physicsAnisotropyMagnetic anisotropyMagnetRelaxation (psychology)MoleculeIonFerromagnetismCondensed matter physicsPhysicsMagnetic fieldElectron

Abstract

fetched live from OpenAlex

Single-molecule magnets (SMMs) are highly sought after for their potential application in high-density information storage, spintronics, and quantum computing. SMMs exhibit slow relaxation of the magnetization of purely molecular origin, thus making them excellent candidates towards the aforementioned applications. In recent years, significant focus has been placed on the rare earth elements due to their large intrinsic magnetic anisotropy arising from the near degeneracy of the 4f orbitals. Traditionally, coordination chemistry has been utilized to fabricate lanthanide-based SMMs; however, heteroatomic donor atoms such as oxygen and nitrogen have limited orbital overlap with the shielded 4f orbitals. Thus, control over the anisotropic axis and induction of f-f interactions are limited, meaning that the performance of these systems can only extend so far. To this end, we have placed considerable attention on the development of novel SMMs whose donor atoms are conjugated hydrocarbons, thereby allowing us to perturb the crystal field of lanthanide ions through the use of an electronic π-cloud. This approach allows for fine tuning of the anisotropic axis of the molecule, allowing this method the potential to elicit SMMs capable of reaching much larger values for the two vital performance measurements of an SMM, the energy barrier to spin reversal (Ueff), and the blocking temperature of the magnetization (TB). In this Account, we describe our efforts to exploit the inherent anisotropy of the late 4f elements; namely, Dy(III) and Er(III), through the use of cyclooctatetraenyl (COT) metallocenes. With respect to the Er(III) derivatives, we have seen record breaking success, reaching blocking temperatures as high as 14 K with frozen solution magnetometry. These results represent the first example of such a high TB being observed for a system with only a single spin center, formally known as a single-ion magnet (SIM). Our continued interrelationship between theoretical and experimental chemistry allows us to shed light on the mechanisms and electronic properties that govern the slow relaxation dynamics inherent to this unique set of SMMs, thus providing insight into the role by which both symmetry and crystal field effects contribute to the magnetic properties. As we look to the future success of such materials in practical devices, we must gain an understanding of how the 4f elements communicate magnetically, a subject upon which there is still limited knowledge. As such, we have described our work on coupling mononuclear metallocenes to generate new dinuclear SMMs. Through a building block approach, we have been able to gain access to new double,- triple- and quadruple-decker complexes that possess remarkable properties; exhibiting TB of 12 K and Ueff above 300 K. Our goal is to develop a fundamental platform from which to study 4f coupling, while maintaining and enhancing the strict axiality of the anisotropy of the 4f ions. This Account will present a successful strategy employed in the production of novel and high-performing SMMs, as well as a clear overview of the lessons learned throughout.

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 score0.003
Threshold uncertainty score0.009

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.070
GPT teacher head0.365
Teacher spread0.296 · 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

Citations156
Published2016
Admission routes2
Has abstractyes

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