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For over three decades, scanning probe microscopy (SPM) has been a key method for exploring material structures and functionalities at nanometer and often atomic scales in ambient, liquid, and vacuum environments. Historically, SPM…
The rapid development of computation power and machine learning algorithms has paved the way for automating scientific discovery with a scanning probe microscope (SPM). The key elements towards operationalization of automated SPM are the…
Scanning Probe Microscopy (SPM) techniques have shown great potential in fabricating nanoscale structures endowed with exotic quantum properties achieved through various manipulations of atoms and molecules. However, precise control…
We present the development of an automated scanning probe microscopy (SPM) measurement system using an advanced large-scale language model (LLM). This SPM system can receive instructions via social networking services (SNS), and the…
Microscopy techniques have played vital roles in materials science, biology, and nanotechnology, offering high-resolution imaging and detailed insights into properties at nanoscale and atomic level. The automation of microscopy experiments,…
We present an advanced scanning probe microscopy system enhanced with artificial intelligence (AI-SPM) designed for self-driving atomic-scale measurements. This system expertly identifies and manipulates atomic positions with high…
Since the dawn of scanning probe microscopy (SPM), tapping or intermittent contact mode has been one of the most widely used imaging modes. Manual optimization of tapping mode not only takes a lot of instrument and operator time, but also…
Recent progress in machine learning methods, and the emerging availability of programmable interfaces for scanning probe microscopes (SPMs), have propelled automated and autonomous microscopies to the forefront of attention of the…
The Probe-Particle Model combine theories designed for the simulation of scanning probe microscopy experiments, employing non-reactive, flexible tip apices to achieve sub-molecular resolution. In the article we present the latest version of…
Time resolution is one of the most severe limitations of scanning probe microscopies (SPMs), since the typical image acquisition times are in the order of several seconds or even few minutes. As a consequence, the characterization of…
Though quite challenging, leveraging large-scale unlabeled or partially labeled images in a cost-effective way has increasingly attracted interests for its great importance to computer vision. To tackle this problem, many Active Learning…
We demonstrate a cryogenic scanned probe microscope (SPM) that has been modified to be controlled with a haptic device, such that the operator can `feel' the surface of a sample under investigation. This system allows for direct tactile…
We report our design, development, installation and troubleshooting of an open source Gnome X Scanning Microscopy (GXSM) software package for controlling and processing of modern Scanning Probe Microscopy (SPM) system as a development tool…
Scanning tunnelling microscopy (STM) is a powerful technique for imaging surfaces with atomic resolution, providing insight into physical and chemical processes at the level of single atoms and molecules. A regular task of STM image…
The Segment Anything Model (SAM) has demonstrated strong performance in image segmentation of natural scene images. However, its effectiveness diminishes markedly when applied to specific scientific domains, such as Scanning Probe…
Understanding the complex properties of electronic and spintronic devices at the micro- and nano-scale is a topic of intense current interest as it becomes increasingly important for scientific progress and technological applications.…
Microscopy, in particular scanning probe and electron microscopy, has been pivotal in improving our understanding of structure-function relationships at the nanoscale and is by now ubiquitous in most research characterization labs and…
Atomic force microscopy (AFM or SPM) imaging is one of the best matches with machine learning (ML) analysis among microscopy techniques. The digital format of AFM images allows for direct utilization in ML algorithms without the need for…
The rapid development of nanoscience and nanotechnology in the last two decades was stimulated by the emergence of scanning probe microscopy (SPM) techniques capable of accessing local material properties, including transport, mechanical,…
Scanning Tunneling Microscopy (STM) enables fabrication of atomically precise structures with unique properties and growing technological potential. However, reproducible manipulation of covalently bonded atoms requires control over the…