Bibliographic record
Abstract
The goal of this study is to examine the theoretical capability of bimaterial lattices as thermally driven actuators. The lattices are composed of planar non-identical cells. Each cell consists of a skewed hexagon surrounding an irregular triangle; the skew angles of the hexagon and the ratio of the coefficients of thermal expansion (CTEs) of the two component materials determine the overall performance of the actuator. Such a cell has three tailorable CTEs along the lines connecting the points where adjoining cells are connected. Each individual cell and a lattice consisting of such cells can be strongly anisotropic in terms of thermal expansion. While these lattice cells have been used as stress-free connectors for components with differing CTEs, they have not been explored for their actuation capacity. This paper develops models for bimaterial lattices that can be used as mechanical actuators for valves, switches and differential motion. A general procedure for lattice design includes drawing of its skeleton, which identifies the points at which a lattice cell is connected to other cells or substrates; calculation of three CTEs in each cell depending upon the functionality desired; choosing lattice materials; and finding of the skew angles for each cell as solutions of three nonlinear algebraic equations. By changing materials and geometry, we can determine the change of their configuration when the temperature changes. This paper illustrates the concepts with several examples: a two-cell lattice that is connected to a substrate that functions as a lever in a switch; a three-cell lattice that serves as a valve; and a lattice that controls the maximum total deflection of two adjoining parts of a structure.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".