Qr code
DALIAN UNIVERSITY OF TECHNOLOGY Login 中文
闫英

Associate Professor
Supervisor of Doctorate Candidates
Supervisor of Master's Candidates


Title : 高性能制造研究所 副所长 机械学院招生宣传组成员(武汉)
Gender:Female
Alma Mater:清华大学
Degree:Doctoral Degree
School/Department:机械工程学院
Discipline:Mechanical Manufacture and Automation
Business Address:大连理工大学 机械学院 知方楼5005
Contact Information:yanying@dlut.edu.cn
E-Mail:yanying@dlut.edu.cn
Click: times

Open time:..

The Last Update Time:..

Current position: Home >> Scientific Research >> Paper Publications

Near-field microscopy inspection of nano scratch defects on the monocrystalline silicon surface

Hits : Praise

Indexed by:期刊论文

Date of Publication:2019-03-01

Journal:PRECISION ENGINEERING-JOURNAL OF THE INTERNATIONAL SOCIETIES FOR PRECISION ENGINEERING AND NANOTECHNOLOGY

Included Journals:EI、SCIE

Volume:56

Page Number:506-512

ISSN No.:0141-6359

Key Words:s-SNOM; Surface defects; Micro crack

Abstract:Knowledge about the removal mechanism at the nanometer scale is essential for eliminating the negative effects of surface defects and subsurface damages of silicon finishing with the ultra-precision machine. It is always studied by the scratching tests and how to distinguish the characteristics of scratch is of great importance to further analysis of material removal mechanism. In this study, the scattering-type scanning near-field optical microscopy (s-SNOM) was employed as a direct and non-destructive method to characterize the scratch generated by single-point diamond scratching. The near-field amplitude obtained by s-SNOM was in direct proportion to the free-carrier concentration that represents the subsurface dislocation of silicon, and the plastic regime of the scratch could be distinguished. Furthermore, s-SNOM could tell the difference between plastic pile-ups and burrs, and the microstructures at the subsurface of the scratch can be detected as well. These characteristics are critical to investigate the material removal mechanisms in ultra-precision machining but the AFM and SEM could just observe the surface morphology instead of telling the difference between various regimes. s-SNOM provided possibilities for nanoscale material characterization and could become a tool for subsurface damages observation of ultra-precision machined materials.