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Record W7116071585 · doi:10.82417/gj4e-n361

Precision machining of glass in the submillimeter scale using thermochemically-assisted grinding

2025· other· en· W7116071585 on OpenAlexaff

Bibliographic record

VenueEspace ÉTS (ETS) · 2025
Typeother
Languageen
Field
Topic
Canadian institutionsÉcole de Technologie Supérieure
Fundersnot available
KeywordsMachiningGrindingAbrasiveSurface micromachiningIsotropic etchingThermalGrindPotassium hydroxideAbrasive machining

Abstract

fetched live from OpenAlex

The mechanical, optical, and thermal properties of glass make it well-adapted for use in Micro-Electromechanical Systems, optics, and microfluidics. However, micromachining glass and other SiO2-based materials poses significant challenges due to their hardness and brittleness. Mechanical, thermal, and chemical machining processes face constraints related to processing speed, feature precision, and high costs. Additionally, the demand for glass microsystems is growing, and there is a lack of processes adapted to small-batch production and rapid prototyping of sub-millimeter scale glass parts.Spark-Assisted Chemical Engraving (SACE), or Electro-Chemical Discharge Machining, is a hybrid machining process combining chemical and thermal effects to remove material. A tool-electrode applies electrochemical discharges near a nonconductive workpiece submerged in an electrolytic solution, accelerating the chemical etching through localized heating. This process removes material with minimal damage.In the past years it was proposed to use abrasive tool-electrodes for simultaneous material removal through electrochemical discharges and mechanical grinding, improving material removal rates, while conserving the advantages of SACE, such as the absence of material redeposition and good surface quality. While some studies demonstrate the synergy between grinding and thermochemical etching, understanding the underlying mechanism of this hybrid machining process remains limited. This work aims to better characterize the interactions of the two material removal mechanisms and thus define a range of operating parameters to improve processing speed, reliability and cutting quality.Borosilicate glass workpieces were submerged in 27% (wt.) potassium hydroxide (KOH). The tool-electrode, a 0.8 mm diameter diamond-coated grinding bit with cobalt binder, was used to grind and apply electrochemical discharges to create 0.8-mm wide channels in the workpiece. The effects of varying machining voltage, tool rotation speed, feed rate and depth of cut were studied. The measured response parameters were machining force, surface roughness and frequency of chipping of the material. Different cutting regimes were identified based on the relative intensity of the mechanical and chemical attacks.It was found that the proposed thermochemically-assisted grinding process produces better surface quality with less chipping than grinding alone. In conventional machining, machining forces on the tool increase linearly with material removal rate (MRR). When electrochemical attack is combined with mechanical grinding, this relation is no longer linear; machining forces do not intervene at all for lower MRR and are greatly reduced at higher MRR.It was shown that thermochemically-assisted grinding offers higher processing speed than SACE, improving potential for economically viable manufacturing of millimeter-scale glass parts in small batches.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.556
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.021
GPT teacher head0.287
Teacher spread0.266 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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