In the last few years, electron microscopy has experienced a new methodological paradigm
aimed to fix the bottlenecks and overcome the challenges of its analytical workflow. Machine …

Halide perovskite materials serve as excellent candidates for solar cell and optoelectronic
devices. Recently, the design of the halide perovskite materials is greatly facilitated by …

RNA flexibility is reflected in its heterogeneous conformation. Through direct visualization
using atomic force microscopy (AFM) and the adenosylcobalamin riboswitch aptamer …

Scanning probe microscopies allow investigating surfaces at the nanoscale, in real space
and with unparalleled signal-to-noise ratio. However, these microscopies are not used as …

Surface topography, or height profile, is a critical property for various micro-and
nanostructured materials and devices, as well as biological systems. At the nanoscale …

Progress in computing capabilities has enhanced science in many ways. In recent years,
various branches of machine learning have been the key facilitators in forging new paths …

The dynamics of complex ordering systems with active rotational degrees of freedom
exemplified by protein self-assembly is explored using a machine learning workflow that …

State-of-the-art contact angle measurements usually involve image analysis of sessile
drops. The drops are symmetric and images can be taken at high resolution. The analysis of …

Glass science, like other materials domains, has been advancing at a rapid pace during the
last few decades thanks to sophisticated experimental techniques, simulation methods, and …

In this paper, we present a new machine learning (ML) workflow with unsupervised learning
techniques to identify domains within atomic force microscopy (AFM) images obtained from …