Interplay between Size, Composition, and Phase Transition of Nanocrystalline Cr<sup>3+</sup>-Doped BaTiO<sub>3</sub> as a Path to Multiferroism in Perovskite-Type Oxides
Bibliographic record
Abstract
Multiferroics, materials that exhibit coupling between spontaneous magnetic and electric dipole ordering, have significant potential for high-density memory storage and the design of complex multistate memory elements. In this work, we have demonstrated the solvent-controlled synthesis of Cr(3+)-doped BaTiO(3) nanocrystals and investigated the effects of size and doping concentration on their structure and phase transformation using X-ray diffraction and Raman spectroscopy. The magnetic properties of these nanocrystals were studied by magnetic susceptibility, magnetic circular dichroism (MCD), and X-ray magnetic circular dichroism (XMCD) measurements. We observed that a decrease in nanocrystal size and an increase in doping concentration favor the stabilization of the paraelectric cubic phase, although the ferroelectric tetragonal phase is partly retained even in ca. 7 nm nanocrystals having the doping concentration of ca. 5%. The chromium(III) doping was determined to be a dominant factor for destabilization of the tetragonal phase. A combination of magnetic and magneto-optical measurements revealed that nanocrystalline films prepared from as-synthesized paramagnetic Cr(3+)-doped BaTiO(3) nanocrystals exhibit robust ferromagnetic ordering (up to ca. 2 μ(B)/Cr(3+)), similarly to magnetically doped transparent conducting oxides. The observed ferromagnetism increases with decreasing constituent nanocrystal size because of an enhancement in the interfacial defect concentration with increasing surface-to-volume ratio. Element-specific XMCD spectra measured by scanning transmission X-ray microscopy (STXM) confirmed with high spatial resolution that magnetic ordering arises from Cr(3+) dopant exchange interactions. The results of this work suggest an approach to the design and preparation of multiferroic perovskite materials that retain the ferroelectric phase and exhibit long-range magnetic ordering by using doped colloidal nanocrystals with optimized composition and size as functional building blocks.
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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".