High-Temperature Polyimide Composites—A Review on Polyimide Types, Manufacturing, and Mechanical and Thermal Behavior
Bibliographic record
Abstract
Polyimide composites represent a class of advanced materials with remarkable mechanical robustness and thermal stability, making them highly suitable for applications in extreme environments. Their unique ability to maintain performance under high temperatures and corrosive conditions, combined with a favorable strength-to-weight ratio, positions them as critical components in aerospace, electronics, and automotive systems. Several leading aerospace and electronics corporations have made significant investments in incorporating polyimide composites into their products, indicating the material’s transformative potential. This review paper provides an overview of mechanical and thermal behaviors of polyimide composites, summarizing recent developments and research trends. It examines the influence of various reinforcements, processing techniques, and composite architectures on material performance under mechanical loading and thermal stress. The paper synthesizes findings from experimental studies and modeling efforts to highlight the critical factors affecting strength, durability, and thermal stability. Discussion and recommendations regarding applications in aerospace, electronics, and other high-temperature environments are provided, emphasizing the challenges and opportunities presented by these advanced materials. This review adopts a broad scope to reflect the interdisciplinary nature of polyimide research. Due to gaps in literature, this work aims to provide a foundational overview that supports future, more specialized investigations.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".