Magnet-Based Mechanical Logic Gates With Programmability and Continuous Operation Capability in High-Radiation Environments
Bibliographic record
Abstract
Mechanical logic gates provide mechanical systems with the ability to process information, thereby promoting the evolution of mechanical computing. However, current mechanical logic gates rely on sustained energy to maintain their programmable logical functions, and they cannot achieve both programmability and the capability for continuous operation within a single framework. In this article, we propose a design strategy for mechanical logic gates that harnesses a magnetic bistable mechanism and a magnetic spring configuration, thereby overcoming the limitations of existing mechanical computing systems. Strategically adjusting parameters or reconfiguring kinematic pairs within magnetic interconnects achieves programmable logical functions that can be maintained without external energy. The continuous operation capability allows the output of logic gates to respond to varying inputs in real time, which enables mechanical computing systems to execute multiple computations continuously without resetting. Furthermore, we have experimentally validated the functioning of the mechanical logic gates under high-radiation environments, marking a significant stride for the application of mechanical computing in extreme conditions. This strategy paves the way for the development of mechanical computing systems that possess programmability and continuous operation capabilities concurrently, empowering them to execute complex operations in high-radiation environments.
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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) | 0.000 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".