Elastic recovery of monocrystalline silicon during ultra-fine rotational grinding

Date

2020-05-21

Supervisor/s

Journal Title

Journal ISSN

Volume Title

Publisher

Elsevier

Department

Type

Article

ISSN

0141-6359

Format

Free to read from

2021-05-22

Citation

Huang N, Yan Y, Zhou P, et al., (2020) Elastic recovery of monocrystalline silicon during ultra-fine rotational grinding. Precision Engineering, Volume 65, September 2020, pp. 64-71

Abstract

Micromachining of brittle materials like monocrystalline silicon to obtain deterministic surface topography is a 21st Century challenge. As the scale of machining has shrunk down to sub-micrometre dimensions, the undulations in the machined topography start to overlap with the extent of elastic recovery (spring back) of the workpiece, posing challenges in the accurate estimation of the material's elastic recovery effect. The quantification of elastic recovery is rather complex in the grinding operation due to (i) randomness in the engagement of various grit sizes with the workpiece as well as (ii) the high strain rate employed during grinding as opposed to single grit scratch tests employed in the past at low strain rates. Here in this work, a method employing inclination of workpiece surface was proposed to quantify elastic recovery of silicon in ultra-fine rotational grinding. The method uniquely enables experimental extraction of the elastic recovery and tip radius of the grits actively engaged with the workpiece at the end of the ultra-fine grinding operation. The proposed experimental method paves the way to enable a number of experimental and simulation endeavours to develop more accurate material constitutive models and grinding models targeted towards precision processing of materials. It can also be shown that using this method if the tip radius distribution of active grits is measured at different time instances, then this data can be used to assess the state of the grinding wheel to monitor its wear rate which will be a useful testbed to create a digital twin in the general framework of digital manufacturing processes.

Description

Software Description

Software Language

Github

Keywords

Brittle materials, Rotational grinding, Silicon, Elastic recovery, Grit tip radius

DOI

Rights

Attribution-NonCommercial-NoDerivatives 4.0 International

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