Tunneling Nanoelectromechanical Switches Based on Compressible Molecular Thin Films
Bibliographic record
Abstract
Abrupt switching behavior and near-zero leakage current of nanoelectromechanical (NEM) switches are advantageous properties through which NEMs can outperform conventional semiconductor electrical switches. To date, however, typical NEMs structures require high actuation voltages and can prematurely fail through permanent adhesion (defined as stiction) of device components. To overcome these challenges, in the present work we propose a NEM switch, termed a "squitch," which is designed to electromechanically modulate the tunneling current through a nanometer-scale gap defined by an organic molecular film sandwiched between two electrodes. When voltage is applied across the electrodes, the generated electrostatic force compresses the sandwiched molecular layer, thereby reducing the tunneling gap and causing an exponential increase in the current through the device. The presence of the molecular layer avoids direct contact of the electrodes during the switching process. Furthermore, as the layer is compressed, the increasing surface adhesion forces are balanced by the elastic restoring force of the deformed molecules which can promote zero net stiction and recoverable switching. Through numerical analysis, we demonstrate the potential of optimizing squitch design to enable large on-off ratios beyond 6 orders of magnitude with operation in the sub-1 V regime and with nanoseconds switching times. Our preliminary experimental results based on metal-molecule-graphene devices suggest the feasibility of the proposed tunneling switching mechanism. With optimization of device design and material engineering, squitches can give rise to a broad range of low-power electronic applications.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".