Advancements and challenges in molecular/hybrid perovskites for piezoelectric nanogenerator application: A comprehensive review
Bibliographic record
Abstract
Molecular perovskites are a class of materials that have attracted considerable attention in recent years due to their unique physical characteristics, structural properties, and diverse applications. These materials are also known as Hybrid Organic-Inorganic Perovskite (HOIP) and are denoted by the general formula ABX3. HOIP materials feature an organic or inorganic molecular cation (A), a metal or molecular cation (B), and a molecular anionic bridging ligand (X). The perovskite structure comprises BX6 octahedra that share corners, forming a three-dimensional network. The remarkable properties of molecular perovskites arise from their intrinsic polarization, resulting from the presence of polar organic cations in hybrid perovskites that possess a constant electric dipole moment. The alignment of these dipoles plays a crucial role in the properties of molecular perovskites. Consequently, this polarization can be harnessed to capture ambient mechanical energy and convert it into electrical energy. This review paper provides a comprehensive overview of molecular perovskites, focusing on their physical characteristics, synthesis methods, and multifunctional applications, particularly in piezoelectric nanogenerators. Furthermore, it addresses the challenges and opportunities associated with boosting their piezoelectric performance and integrating them with nanogenerator technology and flexible devices. Recent advances and breakthroughs in molecular perovskite-based nanogenerators are highlighted, including lead-free, metal-free, double perovskite materials, etc. Finally, the paper proposes future directions and perspectives for further research and innovation in this dynamic field.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".