Doping Effects on Magnetic and Electronic Transport Properties in (Ba1−xRbx)(Zn1−yMny)2As2 (0.1 ≤ x, y ≤ 0.25)
Bibliographic record
Abstract
Diluted magnetic semiconductors (DMSs) represent a significant area of interest for research and applications in spintronics. Recently, DMSs derived from BaZn2As2 have garnered significant interest due to the record Curie temperature (TC) of 260 K. However, the influence of doping on their magnetic evolution and transport characteristics has not been thoroughly investigated. This study aims to fill this gap through susceptibility and magnetization measurements, electric transport analysis, and muon spin relaxation and rotation (µSR) measurements on (Ba1−xRbx)(Zn1−yMny)2As2 (0.1 ≤ x, y ≤ 0.25, BRZMA). Key findings include the following: (1) BRZMA showed a maximum TC of 138 K, much lower than (Ba,K)(Zn,Mn)2As, because of a reduced carrier concentration. (2) A substantial electromagnetic coupling is evidenced by a negative magnetoresistance of up to 34% observed in optimally doped BRZMA. (3) A 100% static magnetic ordered volume fraction is achieved in the low-temperature region, indicating a homogeneous magnet. (4) Furthermore, a systematic and innovative methodology has been initially proposed, characterized by clear step-by-step instructions aimed at enhancing TC, grounded in robust experimental findings. The findings presented provide valuable insights into the spin–charge interplay concerning magnetic and electronic transport properties. Furthermore, they offer clear direction for the investigation of higher TC DMSs.
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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".