Ceramic coatings for extreme environments and energy systems: A review
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This paper provides a comprehensive review of wear-resistant ceramic coatings used in extreme environments, such as oil and gas operations, thermal barrier coatings, energy, and industrial applications. It explores various material classes, including oxides, carbides, nitrides, and borides, focusing on their thermal stability, mechanical strength, and resistance to oxidation and wear. The study discusses different deposition techniques, including chemical vapor deposition (CVD), physical vapor deposition (PVD), and plasma spraying, highlighting their advantages and challenges. Key challenges, including brittleness, adhesion issues, and high-temperature oxidation, were explained in detail, along with emerging solutions like high-entropy ceramics, self-healing materials, and computational modeling. The integration of smart monitoring systems and advanced fabrication methods is demonstrated as a promising way for optimizing the durability and performance of ceramic coatings. This review also aims to bridge the existing knowledge gaps, offering insights into the latest advancements and future directions in the development of high-performance ceramic coatings for extreme environments.
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.
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 | 0.000 | 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) | 0.000 | 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 it