Optimization of energy storage and electrocaloric performance in Pb(Zr,Ti)O<sub>3</sub> via A-Site La and Bi Co-doping
Bibliographic record
Abstract
Abstract Lead-based ferroelectrics are one of the most fascinating candidates in the field of state-of-the-art electronic technology. Their intriguing properties are further enriched via the realization of morphotropic phase boundaries. Moreover, the A-site chemical substitution provides insight into the emergence of various exotic phases. Here, we employ co-doping of La3+ and Bi3+ at the A-site of Pb(Zr,Ti)O3 (PZT) ferroelectric to broaden the practical perspective of relaxor systems. Here, we emphasize that the A-site co-doping approach introduces technologically appealing amendments in the well-established temperature composition phase diagram of the PZT system. La3+ and Bi3+ doping favors the evolution of a novel response to thermal and field fluctuations. The maximum values of − Δ S are found to be ∼0.157, 0.118 and 0.176 J (kg·K)−1 for x = 0.01 , 0.02 and 0.03 , respectively. We employ the electrocaloric characteristics and Arrott plot as probing tools. The observation of a negative electrocaloric effect and the systematic reversal of Arrott lines, followed by a poling effect on the dielectric constant, reveals the emergence of ergodic phase as a novel phase. This further reveals that the Bi doping approach leads to the emergence of exotic characteristics in the chemically modified PZT system. The maximum observed recoverable energy for the composition for x = 0.01 is 0.0479 J cm−3 at a temperature of 388 K.
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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 | 0.001 | 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".