Oblique nanomachining of gallium arsenide explained using AFM experiments and MD simulations

Pengfei Fan, Nirmal Kumar Katiyar, Saurav Goel*, Yang He, Yanquan Geng, Yongda Yan, Hui Mao, Xichun Luo

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

11 Citations (Scopus)
28 Downloads (Pure)

Abstract

Gallium Arsenide (GaAs) continues to remain a material of significant importance due to being a preferred semiconductor substrate for the growth of quantum dots (QDs) and GaAs-based quantum devices used widely in fifth-generation (5G) wireless communication networks. In this paper, we explored aspects of oblique nanomachining to investigate the improvement in the machining quality as well as to understand plasticity and transport phenomena in GaAs using atomic scale machining experiments and simulations. We studied the influence of the direction vector of the cutting tip (e.g. tip alignment) during the surface generation process in GaAs. We noticed a novel observation that when the AFM tip's cutting edge presented two acute angles (i.e., 30° angles each) between the cutting face and the cutting direction (which can be regarded as an oblique cutting condition), the cutting configuration involved early avalanche of dislocations compared to other tip configurations (e.g., orthogonal cutting). Orthogonal cutting involved the least coefficient of friction but the highest specific cutting energy compared to oblique cutting. High-resolution transmission electron microscopy (HRTEM) examination revealed that the shuffle-set slip on the {1 1 1} slip system due to the 〈1 1 0〉 type dislocation paves the way for plasticity during nanometric cutting of GaAs. Overall, a particular condition of oblique cutting was inferred to be the best for nanofabrication of high-quality wafers using an AFM.

Original languageEnglish
Pages (from-to)125-138
Number of pages14
JournalJournal of Manufacturing Processes
Volume90
Early online date13 Feb 2023
DOIs
Publication statusPublished - 24 Mar 2023

Funding

XL gratefully acknowledge the financial support from the EPSRC (EP/K018345/1, EP/T024844/1 and EP/V055208/1), the International Cooperation Program of China (No. 2015DFA70630), Royal Society-NSFC International Exchange scheme (IEC\NSFC\181474) and Science and Technology Based for Equipment Design and Manufacturing for Introduction Talents of Discipline to Universities 2.0 of the 111 project (Project No. BP0719002) for this research. SG acknowledges the financial support provided by the UKRI via Grants No. EP/S036180/1, EP/T001100/1 and EP/T024607/1, feasibility study awards to LSBU from the UKRI National Interdisciplinary Circular Economy Hub (EP/V029746/1) and Transforming the Foundation Industries: a Network+ (EP/V026402/1), the Hubert Curien Partnership award 2022 from the British Council, Transforming the Partnership award from the Royal Academy of Engineering (TSP1332) and the Newton Fellowship award from the Royal Society (NIF\R1\191571). This work also accessed the Isambard Bristol, UK supercomputing service via Resource Allocation Panel (RAP) as well as ARCHER2 resources (Project e648). The authors also acknowledge the use of the EPSRC (EP/K000586/1) funded ARCHIE-WeSt High-Performance Computer at the University of Strathclyde. All data underpinning this publication are openly available from the University of Strathclyde Knowledge Base. SG acknowledges the financial support provided by the UKRI via Grants No. EP/S036180/1 , EP/T001100/1 and EP/T024607/1 , feasibility study awards to LSBU from the UKRI National Interdisciplinary Circular Economy Hub (EP/V029746/1) and Transforming the Foundation Industries: a Network+ (EP/V026402/1), the Hubert Curien Partnership award 2022 from the British Council, Transforming the Partnership award from the Royal Academy of Engineering (TSP1332) and the Newton Fellowship award from the Royal Society (NIF\R1\191571). This work also accessed the Isambard Bristol, UK supercomputing service via Resource Allocation Panel (RAP) as well as ARCHER2 resources (Project e648). The authors also acknowledge the use of the EPSRC ( EP/K000586/1 ) funded ARCHIE-WeSt High-Performance Computer at the University of Strathclyde. XL gratefully acknowledge the financial support from the EPSRC ( EP/K018345/1 , EP/T024844/1 and EP/V055208/1 ), the International Cooperation Program of China (No. 2015DFA70630 ), Royal Society-NSFC International Exchange scheme ( IEC\NSFC\181474 ) and Science and Technology Based for Equipment Design and Manufacturing for Introduction Talents of Discipline to Universities 2.0 of the 111 project (Project No. BP0719002 ) for this research.

Keywords

  • atomic force microscope
  • GaAs
  • MD simulation
  • plastic flow

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