Negative Thermal Expansion Metamaterials: A Review of Design, Fabrication, and Applications
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
Most materials conventionally found in nature expand with an increase in temperature. In actual systems and assemblies like precision instruments, this can cause thermal distortions which can be difficult to handle. Materials with a tendency to shrink with an increase in temperature can be used alongside conventional materials to restrict the overall dimensional change of structures. Such structures, also called negative-thermal-expansion materials, could be crucial in applications like electronics, biomedicine, aerospace components, etc., which undergo high changes in temperature. This can be achieved using mechanically engineered materials, also called negative thermal expansion (NTE) mechanical metamaterials. Mechanical metamaterials are mechanically architected materials with novel properties that are rare in naturally occurring materials. NTE metamaterials utilize their artificially engineered architecture to attain the rare property of negative thermal expansion. The emergence of additive manufacturing has enabled the feasible production of their intricate architectures. Industrial processes such as laser powder bed fusion and direct energy deposition, both utilized in metal additive manufacturing, have proven successful in creating complex structures like lattice formations and multimaterial components in the industrial sector, rendering them suitable for manufacturing NTE structures. Nevertheless, this review examines a range of fabrication methods, encompassing both additive and traditional techniques, and explores the diverse materials used in the process. Despite NTE metamaterials being a prominent field of research, a comprehensive review of these architected materials is missing in the literature. This article aims to bridge this gap by providing a state-of-the-art review of these metamaterials, encompassing their design, fabrication, and cutting-edge applications.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 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