MEMS-Based Micro-Electro-Discharge Machining (M$^{3}$ EDM) by Electrostatic Actuation of Machining Electrodes on the Workpiece
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Bibliographic record
Abstract
<para xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> This paper reports a micro-electro-discharge machining technique that is enabled by electrostatic microactuators. The 18-<formula formulatype="inline"><tex Notation="TeX">$\mu\hbox{m}$</tex></formula>-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 <formula formulatype="inline"><tex Notation="TeX">$\sim\!\! 30\ \mu\hbox{m}$</tex></formula> is measured at the machining/actuation voltage of 100 V. Micromachining of stainless steel is implemented using the planar electrode with <formula formulatype="inline"><tex Notation="TeX">$1.6 \times 1.03\hbox{-mm}^{2}$</tex></formula> area, achieving the removal depth of 20 <formula formulatype="inline"><tex Notation="TeX">$\mu\hbox{m}$</tex></formula>. 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.<formula formulatype="inline"><tex Notation="TeX">$\hfill$</tex></formula> [2008-0299] </para>
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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