MEMS-Based Micro-Electro-Discharge Machining (M$^{3}$ EDM) by Electrostatic Actuation of Machining Electrodes on the Workpiece
Bibliographic record
Abstract
This paper reports a micro-electro-discharge machining technique that is enabled by electrostatic microactuators. The 18-$\mu\hbox{m}$-thick movable copper electrodes that serve as machining tools are microfabricated directly on the surfaces of the workpiece and operated in dielectric machining fluid. A dc voltage of 80–140 V applied between the electrode and the workpiece through a resistance–capacitance pulse generation circuit is leveraged to electrostatically pull in the electrodes toward the workpiece, inducing a breakdown and spark discharge. The discharge lowers the gap voltage and releases the electrode, which is pulled in again as the capacitor is recharged through the resistor. This pull-in and discharge cycle is self-sustained to perform the removal of the workpiece material. The electrode's displacement of$\sim\!\! 30\ \mu\hbox{m}$is measured at the machining/actuation voltage of 100 V. Micromachining of stainless steel is implemented using the planar electrode with$1.6 \times 1.03\hbox{-mm}^{2}$area, achieving the removal depth of 20$\mu\hbox{m}$. The double-layer electrodes that have electroplated microstructures with high-contrast patterns on the backside of the electrodes are developed to demonstrate custom micromachining. A dynamic characteristic of the built-in capacitance of the devices, which is used to form the pulse generation circuit, as well as their mechanical response during the machining process, is theoretically analyzed with the experimental results.$\hfill$[2008-0299]
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 | 0.000 |
| 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) | 0.003 | 0.001 |
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".