Magnetic Frustration and Spin Disorder in Isostructural M(μ-OH<sub>2</sub>)<sub>2</sub>[Au(CN)<sub>2</sub>]<sub>2</sub> (M = Mn, Fe, Co) Coordination Polymers Containing Double Aqua-Bridged Chains: SQUID and μSR Studies
Bibliographic record
Abstract
A series of isostructural M(mu-OH(2))(2)[Au(CN)(2)](2) (M = Co, Fe, and Mn) coordination polymers was synthesized from the reaction of M(II) with [(n)Bu(4)N][Au(CN)(2)]. The basic structural motif for these polymers is analogous to that of previously reported Cu(II)- and Ni(II)-containing polymers and contains repeating double aqua bridges between metal centers that yield a chain structure with pendant [Au(CN)(2)](-) units. The aqueous reaction with Fe(III) yields Fe(mu-OH(2))(mu-OH)[Au(CN)(2)](2), which has a similar structure. The magnetic properties of these polymers were investigated by a combination of SQUID magnetometry and zero-field muon spin relaxation. The double aqua bridges were found to mediate ferromagnetic interactions along the chains in the Co(II)-containing polymer, whereas intrachain antiferromagnetic interactions are present in the Fe(II)-, Fe(III)-, and Mn(II)-containing polymers. Weak magnetic interchain interactions mediated through hydrogen bonds, involving the bridging water molecules and the pendant cyanide groups, are also present. In zero field, the interchain interactions yield a phase transition to a disordered spin-frozen magnetic state below 2-5 K for every polymer. However, the degree of spin disorder varies considerably, depending on the metal center.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".