Investigating Unexpected Magnetism of Mesoporous Silica-Supported Pd and PdO Nanoparticles
Bibliographic record
Abstract
The synthesis and magnetic behavior of matrix-supported Pd and PdO nanoparticles (NPs) are described. Mesoporous silica with hexagonal columnal packing is selected as a template, and the impregnation method with thermal annealing is used to obtain supported Pd and PdO NPs. The heating rate and the annealing conditions determine the particle size and the phase of the NPs, with a fast heating rate of 30 °C/min producing the largest supported Pd NPs. Unusual magnetic behaviors are observed. (1) Contrary to the general belief that smaller Pd NPs or cluster size particles have higher magnetization, matrix-supported Pd NPs in this study maintain the highest magnetization with room temperature ferromagnetism when the size is the largest. (2) Twin boundaries along with stacking faults are more pronounced in these large Pd NPs and are believed to be the reason for this high magnetization. Similarly, supported PdO NPs were prepared under air conditions with different heating rates. Their phase is tetragonal (P4 2 /mmc) with cell parameters of a = 3.050 Å and c = 5.344 Å, which are slightly larger than in the bulk phase ( a = 3.03 Å, c = 5.33 Å). Faster heating rate of 30 °C/min also produces larger particles and larger magnetic hysteresis loop, although magnetization is smaller and few twin boundaries are observed compared to the supported metallic Pd NPs.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.003 | 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 teacher head, 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".