Mechanochemical Synthesis and Magnetic Properties of the Mixed-Valent Binary Silver(I,II) Fluorides, Ag<sup>I</sup><sub>2</sub>Ag<sup>II</sup>F<sub>4</sub> and Ag<sup>I</sup>Ag<sup>II</sup>F<sub>3</sub>
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide Fluoridoargentates(II) represent a fascinating class of silver(II) compounds with structural and magnetic similarities to cuprate superconductors. However, their synthesis is challenging, leaving their properties largely underexplored and hindering the discovery of new phases. This study introduces mechanochemistry as a novel approach for the synthesis of fluoridoargentates(II), avoiding the use of anhydrous HF or elemental fluorine and employing readily available equipment. Notably, ball milling of commercially available precursors successfully produced the long-sought-after first two examples of binary mixed-valent silver(I,II) phases, Ag I 2 Ag II F 4 (Ag 3 F 4 ) and Ag I Ag II F 3 (Ag 2 F 3 ). While the Ag I 2 Ag II F 4 phase was obtained at room temperature, the Ag I Ag II F 3 phase is metastable and required milling under cryogenic conditions. Characterization by synchrotron powder X-ray and neutron diffraction revealed that Ag I 2 Ag II F 4 crystallizes in the P 2 1 / c space group and is isostructural to β-K 2 AgF 4 . In this crystal structure, [Ag II F 2 F 4/2 ] 2– distorted octahedral units with 4 + 2 coordination, extend parallel to a -crystallographic axis giving a quasi-one-dimensional canted antiferromagnetic character, as shown by magnetic susceptibility. The triclinic perovskite Ag I Ag II F 3 phase adopts the P 1̅ space group, is isostructural to AgCuF 3 and also shows features of a one-dimensional antiferromagnet. This mechanochemical approach, also successfully applied to synthesize β-K 2 AgF 4, is expected to expand the field of silver(II) chemistry, accelerating the search for silver analogs to cuprate superconductors and potentially extending to other cations in unusual oxidation states.
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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".