Fabrication methods and applications of microstructured gallium based liquid metal alloys
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 review contains a comparative study of reported fabrication techniques of gallium based liquid metal alloys embedded in elastomers such as polydimethylsiloxane or other rubbers as well as the primary challenges associated with their use. The eutectic gallium–indium binary alloy (EGaIn) and gallium–indium–tin ternary alloy (galinstan) are the most common non-toxic liquid metals in use today. Due to their deformability, non-toxicity and superior electrical conductivity, these alloys have become very popular among researchers for flexible and reconfigurable electronics applications. All the available manufacturing techniques have been grouped into four major classes. Among them, casting by needle injection is the most widely used technique as it is capable of producing features as small as 150 nm width by high-pressure infiltration. One particular fabrication challenge with gallium based liquid metals is that an oxide skin is rapidly formed on the entire exposed surface. This oxide skin increases wettability on many surfaces, which is excellent for keeping patterned metal in position, but is a drawback in applications like reconfigurable circuits, where the position of liquid metal needs to be altered and controlled accurately. The major challenges involved in many applications of liquid metal alloys have also been discussed thoroughly in this article.
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