A Closer Look: Magnetic Behavior of a Three‐Dimensional Cyanometalate Coordination Polymer Dominated by a Trace Amount of Nanoparticle Impurity
Bibliographic record
Abstract
The structure and properties of the K{Ni[Au(CN)(2)](3)} coordination polymer, prepared as a powder at room temperature and recrystallized hydrothermally, are reported. The structure of K{Ni[Au(CN)(2)](3)} contains triply-interpenetrated Prussian Blue type pseudo-cubic arrays assembled from the alternation of octahedral Ni(II) centers and [Au(CN)(2)](-) bridging units. SQUID magnetometry studies have shown that K{Ni[Au(CN)(2)](3)} displays typical paramagnetic behavior for isolated Ni(II) centers down to 1.8 K. However, the magnetic behavior of the samples prepared under hydrothermal conditions suggests a superparamagnetic signature superimposed onto a paramagnetic background. After investigating the samples by transmission electron microscopy, it was determined that, in addition to K{Ni[Au(CN)(2)](3)}, the high-temperature (125, 135, and 165 degrees C) aqueous reaction of Ni(NO(3))(2)6 H(2)O with KAu(CN)(2) also led to the formation of nanoparticles of NiO and Au as minor side products, and that these dominated the magnetic behavior. Nanoparticles of various sizes and shapes were observed, depending on the reaction conditions. Samples containing nanoparticles were found to be superparamagnetic, exhibiting blocking temperatures of approximately 17-22 K, consistent with the behavior expected for NiO nanoparticles. These results illustrate the extreme care that must be taken when examining the physical properties of apparently analytically pure materials prepared by hydrothermal methods.
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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".