Scanning Probe Lithography: State-of-the-Art and Future Perspectives

Anisotropic Effects in Local Anodic Oxidation Nanolithography on Silicon Surfaces: Insights from ReaxFF Molecular Dynamics

Fully understanding the anisotropic effect of silicon surface orientations in local anodic oxidation (LAO) nanolithography processes is critical to the precise control of oxide quality and rate. This study used ReaxFF MD simulations to reveal the surface anisotropic effects in the LAO through the analysis of adsorbed species, atomic charge, and oxide growth. Our results show that the LAO behaves differently on silicon (100), (110), and (111) surfaces. Specifically, the application of an electric field significantly increases the quantity of surface-adsorbed -OH2 while reducing -OH on the (111) surface, and results in a higher charge on a greater number of Si atoms on the (100) surface. Moreover, the quantity of surface-adsorbed -OH plays a pivotal role in influencing the oxidation rate, as it directly correlates with an increased formation rate of Si-O-Si bonds. During bias-induced oxidation, the (111) surface appears with a high initial oxidation rate among three surfaces, while the (110) surface underwent increased oxidation at higher electric field strengths. This conclusion is based on the analysis of the evolution of Si-O-Si bond number, surface elevation, and oxide thickness. Our findings align well with prior theoretical and experimental studies, providing deeper insights and clear guidance for the fabrication of high-performance nanoinsulator gates using LAO nanolithography.

How scanning probe microscopy can be supported by artificial intelligence and quantum computing?

The impact of Artificial Intelligence (AI) is rapidly expanding, revolutionizing both science and society. It is applied to practically all areas of life, science, and technology, including materials science, which continuously requires novel tools for effective materials characterization. One of the widely used techniques is scanning probe microscopy (SPM). SPM has fundamentally changed materials engineering, biology, and chemistry by providing tools for atomic-precision surface mapping. Despite its many advantages, it also has some drawbacks, such as long scanning times or the possibility of damaging soft-surface materials. In this paper, we focus on the potential for supporting SPM-based measurements, with an emphasis on the application of AI-based algorithms, especially Machine Learning-based algorithms, as well as quantum computing (QC). It has been found that AI can be helpful in automating experimental processes in routine operations, algorithmically searching for optimal sample regions, and elucidating structure-property relationships. Thus, it contributes to increasing the efficiency and accuracy of optical nanoscopy scanning probes. Moreover, the combination of AI-based algorithms and QC may have enormous potential to enhance the practical application of SPM. The limitations of the AI-QC-based approach were also discussed. Finally, we outline a research path for improving AI-QC-powered SPM. RESEARCH HIGHLIGHTS: Artificial intelligence and quantum computing as support for scanning probe microscopy. The analysis indicates a research gap in the field of scanning probe microscopy. The research aims to shed light into ai-qc-powered scanning probe microscopy.

Advances in lithographic techniques for precision nanostructure fabrication in biomedical applications

Nano-fabrication techniques have demonstrated their vital importance in technological innovation. However, low-throughput, high-cost and intrinsic resolution limits pose significant restrictions, it is, therefore, paramount to continue improving existing methods as well as developing new techniques to overcome these challenges. This is particularly applicable within the area of biomedical research, which focuses on sensing, increasingly at the point-of-care, as a way to improve patient outcomes. Within this context, this review focuses on the latest advances in the main emerging patterning methods including the two-photon, stereo, electrohydrodynamic, near-field electrospinning-assisted, magneto, magnetorheological drawing, nanoimprint, capillary force, nanosphere, edge, nano transfer printing and block copolymer lithographic technologies for micro- and nanofabrication. Emerging methods enabling structural and chemical nano fabrication are categorised along with prospective chemical and physical patterning techniques. Established lithographic techniques are briefly outlined and the novel lithographic technologies are compared to these, summarising the specific advantages and shortfalls alongside the current lateral resolution limits and the amenability to mass production, evaluated in terms of process scalability and cost. Particular attention is drawn to the potential breakthrough application areas, predominantly within biomedical studies, laying the platform for the tangible paths towards the adoption of alternative developing lithographic technologies or their combination with the established patterning techniques, which depends on the needs of the end-user including, for instance, tolerance of inherent limits, fidelity and reproducibility.

Thermal Scanning-Probe Lithography for Broad-Band On-Demand Plasmonic Nanostructures on Transparent Substrates

Thermal scanning-probe lithography (t-SPL) is a high-resolution nanolithography technique that enables the nanopatterning of thermosensitive materials by means of a heated silicon tip. It does not require alignment markers and gives the possibility to assess the morphology of the sample in a noninvasive way before, during, and after the patterning. In order to exploit t-SPL at its peak performances, the writing process requires applying an electric bias between the scanning hot tip and the sample, thereby restricting its application to conductive, optically opaque, substrates. In this work, we show a t-SPL-based method, enabling the noninvasive high-resolution nanolithography of photonic nanostructures onto optically transparent substrates across a broad-band visible and near-infrared spectral range. This was possible by intercalating an ultrathin transparent conductive oxide film between the dielectric substrate and the sacrificial patterning layer. This way, nanolithography performances comparable with those typically observed on conventional semiconductor substrates are achieved without significant changes of the optical response of the final sample. We validated this innovative nanolithography approach by engineering periodic arrays of plasmonic nanoantennas and showing the capability to tune their plasmonic response over a broad-band visible and near-infrared spectral range. The optical properties of the obtained systems make them promising candidates for the fabrication of hybrid plasmonic metasurfaces supported onto fragile low-dimensional materials, thus enabling a variety of applications in nanophotonics, sensing, and thermoplasmonics.

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.

Spatial modulation of scalable nanostructures by combining maskless plasmonic lithography and grayscale-patterned strategy

Nanolithography techniques providing good scalability and feature size controllability are of great importance for the fabrication of integrated circuits (IC), MEMS/NEMS, optical devices, nanophotonics, etc. Herein, a cost-effective, easy access, and high-fidelity patterning strategy that combines the high-resolution capability of maskless plasmonic lithography with the spatial morphology controllability of grayscale lithography is proposed to generate the customized pattern profile from microscale to nanoscale. Notably, the scaling effect of gap size in plasmonic lithography with a contact bowtie-shaped nanoaperture (BNA) is found to be essential to the rapid decay characteristics of an evanescent field, which leads to a wide energy bandwidth of the required optimal dose to record pattern in per unit volume, and hence, achieves the volumetrically scalable control of the photon energy deposition in the space more precisely. Based on the proper calibration and cooperation of pattern width and depth, a grayscale-patterned map is designed to compensate for the dose difference caused by the loss of the high spatial frequency component of the evanescent field. A Lena nanostructure with varying feature sizes by spatially modulating the exposure dose distribution was successfully demonstrated, and besides, we also successfully generated a microlens array (MLA) with high uniformity. The practical patterning method makes plasmonic lithography significant in the fabrication of functional nanostructures with high performance, including metasurfaces, plasmonics, and optical imaging systems.

Measurement and Control System for Atomic Force Microscope Based on Quartz Tuning Fork Self-Induction Probe

In this paper, we introduce a low-cost, expansible, and compatible measurement and control system for atomic force microscopes (AFM) based on a quartz tuning fork (QTF) self-sensing probe and frequency modulation, which is mainly composed of an embedded control system and a probe system. The embedded control system is based on a dual-core OMAPL138 microprocessor (DSP + ARM) equipped with 16 channels of a 16-bit high-precision general analog-to-digital converter (ADC) and a 16-bit high-precision general digital-to-analog converter (DAC), six channels of an analog-to-digital converter with a second-order anti-aliasing filter, four channels of a direct digital frequency synthesizer (DDS), a digital input and output (DIO) interface, and other peripherals. The uniqueness of the system hardware lies in the design of a high-precision and low-noise digital-analog hybrid lock-in amplifier (LIA), which is used to detect and track the frequency and phase of the QTF probe response signal. In terms of the system software, a software difference frequency detection method based on a digital signal processor (DSP) is implemented to detect the frequency change caused by the force gradient between the tip and the sample, and the relative error of frequency measurement is less than 3%. For the probe system, a self-sensing probe controller, including an automatic gain control (AGC) self-excitation circuit, is designed for a homemade balanced QTF self-sensing probe with a high quality factor (Q value) in an atmospheric environment. We measured the quality factor (Q value) of the balanced QTF self-sensing probes with different lengths of tungsten tips and successfully realized AFM topography imaging with a tungsten-tip QTF probe 3 mm in length. The results show that the QTF-based self-sensing probe and the developed AFM measurement and control system can obtain high quality surface topography scanning images in an atmospheric environment.

Review: Advanced Atomic Force Microscopy Modes for Biomedical Research

Visualization of biomedical samples in their native environments at the microscopic scale is crucial for studying fundamental principles and discovering biomedical systems with complex interaction. The study of dynamic biological processes requires a microscope system with multiple modalities, high spatial/temporal resolution, large imaging ranges, versatile imaging environments and ideally in-situ manipulation capabilities. Recent development of new Atomic Force Microscopy (AFM) capabilities has made it such a powerful tool for biological and biomedical research. This review introduces novel AFM functionalities including high-speed imaging for dynamic process visualization, mechanobiology with force spectroscopy, molecular species characterization, and AFM nano-manipulation. These capabilities enable many new possibilities for novel scientific research and allow scientists to observe and explore processes at the nanoscale like never before. Selected application examples from recent studies are provided to demonstrate the effectiveness of these AFM techniques.

Editorial for the Special Issue on Ultra Precision Technologies for Micromachining, Volume II

With the increasing demand for ultra-high-precision products and micro-products in fields such as aerospace, national defense, military, transportation, and people's livelihoods, it has become an important development trend in the field of machining to realize ultra-high-precision machining and miniaturization with a higher level and higher quality [...].

The Dislocation- and Cracking-Mediated Deformation of Single Asperity GaAs during Plowing Using Molecular Dynamics Simulation

This work simulates the plowing process of a single asperity GaAs by diamond indenter using molecular dynamics simulations. The deformation mechanism of asperity GaAs is revealed by examining the topography evolution and stress state during the plowing. This work also investigates the origin of the influence of asperity size, indenter radius and plow depth on the deformation of the asperity GaAs. We observed the initiation and propagation of cracks up to the onset of fracture and the plastic activity near the indenter, obtaining more information usually not available from planar GaAs in normal velocity plowing compared to just plastic activity. The simulations demonstrated the direct evidence of cracking in GaAs induced by plowing at an atomic level and probed the origin and extension of cracking in asperity GaAs. This finding suggests that cracking appears to be a new deformation pattern of GaAs in plowing, together with dislocation-dominated plasticity modes dominating the plowing deformation process. This work offers new insights into understanding the deformation mechanism of an asperity GaAs. It aims to find scientific clues for understanding plastic removal performed in the presence of cracking.