Exploiting rotational asymmetry for sub-50 nm mechanical nanocalligraphy

Tip-based Lithography with a Sacrificial Layer

The fabrication of a highly controlled gold (Au) nanohole (NH) array via tip-based lithography is improved by incorporating a sacrificial layer-a tip-crash buffer layer. This inclusion mitigates scratches during the nano-indentation process by employing a 300 nm thick poly(methyl methacrylate) layer as a sacrificial layer on top of the Au film. Such a precaution ensures minimal scratches on the Au film, facilitating the creation of sub-50 nm Au NHs with a 15 nm gap between the Au NHs. The precision of this method exceeds that of fabricating Au NHs without a sacrificial layer. Demonstrating its versatility, this Au NH array is utilized in two distinct applications: as a dry etching mask to form a molybdenum disulfide hole array and as a catalyst in metal-assisted chemical etching, resulting in conical-shaped silicon nanostructures. Additionally, a significant electric field is generated when Au nanoparticles (NPs) are placed within the Au NHs. This effect arises from coupling electromagnetic waves, concentrated by the Au NHs and amplified by the Au NPs. A notable result of this configuration is the enhancement factor of surface-enhanced Raman scattering, which is an order of magnitude greater than that observed with just Au NHs and Au NPs alone.

Towards smart scanning probe lithography: a framework accelerating nano-fabrication process with in-situ characterization via machine learning

Scanning probe lithography (SPL) is a promising technology to fabricate high-resolution, customized and cost-effective features at the nanoscale. However, the quality of nano-fabrication, particularly the critical dimension, is significantly influenced by various SPL fabrication techniques and their corresponding process parameters. Meanwhile, the identification and measurement of nano-fabrication features are very time-consuming and subjective. To tackle these challenges, we propose a novel framework for process parameter optimization and feature segmentation of SPL via machine learning (ML). Different from traditional SPL techniques that rely on manual labeling-based experimental methods, the proposed framework intelligently extracts reliable and global information for statistical analysis to fine-tune and optimize process parameters. Based on the proposed framework, we realized the processing of smaller critical dimensions through the optimization of process parameters, and performed direct-write nano-lithography on a large scale. Furthermore, data-driven feature extraction and analysis could potentially provide guidance for other characterization methods and fabrication quality optimization.

Conductive Materials with Elaborate Micro/Nanostructures for Bioelectronics

Bioelectronics, an emerging field with the mutual penetration of biological systems and electronic sciences, allows the quantitative analysis of complicated biosignals together with the dynamic regulation of fateful biological functions. In this area, the development of conductive materials with elaborate micro/nanostructures has been of great significance to the improvement of high-performance bioelectronic devices. Thus, here, a comprehensive and up-to-date summary of relevant research studies on the fabrication and properties of conductive materials with micro/nanostructures and their promising applications and future opportunities in bioelectronic applications is presented. In addition, a critical analysis of the current opportunities and challenges regarding the future developments of conductive materials with elaborate micro/nanostructures for bioelectronic applications is also presented.