Structural Optimization of Si Nanowires for Ultimate Efficiency Improvement via Tuning Optical Properties

• Published in: Transactions on electrical and electronic materials Vol. 24; no. 6; pp. 489 - 501
• Main Authors: Muduli, Sakti Prasanna, Khan, Md Asif, Kale, Paresh
• Format: Journal Article
• Language: English
• Published: Seoul The Korean Institute of Electrical and Electronic Material Engineers (KIEEME) 01.12.2023; 한국전기전자재료학회
• Subjects: Chemistry and Materials Science; Electronics and Microelectronics; Instrumentation; Materials Science; Optical and Electronic Materials; Regular Paper; 전기공학; Vertical etching; Correlation; Porosity; Horizontal Etching; Aspect ratio; MACE
• ISSN: 1229-7607; 2092-7592
• DOI: 10.1007/s42341-023-00474-4

Si nanostructures are preferred for optoelectronic applications over bulk Si owing to their enhanced optical and electrical characteristics. Si nanowires (SiNWs) and porous SiNWs (PSiNWs) are the widely studied structures for photovoltaics. The optical and electrical characteristics depend on the structural attributes of the nanowires- length, diameter, and porosity of PSiNWs. Tailoring the structural attributes is possible with metal-assisted chemical etching (MACE), a cost-effective method for fabricating the SiNWs and PSiNWs. However, the process involves multiple parameters. The paper optimizes the MACE parameters such as wafer resistivity, HF concentration, MACE duration, temperature, and H 2 O 2 concentration for the maximum length, minimum diameter, undistorted nanowires, and minimum tip agglomeration. Wafer resistivity optimization eliminates the expensive options with inferior nanowire diameters, whereas the other MACE parameters control the nanowire length and the diameter by limiting the vertical and horizontal etching. The work optimizes MACE parameters to investigate the influence on reflectance, band gap, and ultimate efficiency through changes in the structural attributes. The investigation establishes a correlation between the aspect ratio and the ultimate efficiency to optimize the MACE parameters.