2024-03-02 18:20:54
Artificial intelligence is revolutionizing microscopy: a giant step towards nanometric precision.
Atomic force microscopy (AFM) has long represented an essential tool for researchers in the analysis of material surfaces. However, the size of the microscope probe has always limited the precision of the images produced. Today, a significant breakthrough is announced by the University of Illinois Urbana-Champaign: a new artificial intelligence (AI) technique promises to overcome this fundamental limitation, providing unprecedented insight at the nanoscale.
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A historical limitation exceeded
For decades, AFM has allowed scientists to accurately map the surfaces of materials in three dimensions. But when surface features approach the size of the probe tip, around 10 nanometers, their resolution becomes problematic. New AI technique developed by University of Illinois researchers manages to “decode” microscope images, eliminating unwanted effects of probe width and thus allowing lower resolution than this .
The deep learning revolution
The research team, led by Professor Yingjie Zhang and doctoral student Lalith Bonagiri, developed an innovative deep learning algorithm. This algorithm uses an encoder-decoder framework to transform raw AFM images by identifying and removing distortions introduced by the probe. This process produces three-dimensional surface profiles with unparalleled precision.
Algorithm training and validation
To train this algorithm, the researchers created artificial images of three-dimensional structures and simulated their AFM readings. The big challenge was to maintain the absolute brightness and contrast of the images, essential elements to maintain the significance of the data. Tests performed on gold and palladium nanoparticles proved the effectiveness of the algorithm in suppressing the effects of the probe tip and accurately revealing the three-dimensional characteristics of the nanoparticles.
Implications et perspectives futures
This advancement not only represents a significant improvement for AFM images, but it also opens the door to new possibilities in the development of nanotechnology and the study of biological systems and materials. The researchers point out that, although promising, the technique can still be improved by training on more and better data.
Impact on research and industry
Improving the resolution of AFM images using AI might revolutionize many areas of research and industrial application. This might lead to significant discoveries in advanced materials, biology, and nanotechnology, making possible the exploration of previously inaccessible territories.
This article explores the recent breakthrough in microscopy, where an artificial intelligence technique overcomes a fundamental limitation of AFM, providing unprecedented precision at the nanoscale. This advancement promises to open new avenues in scientific research and technology development, enabling more detailed and precise analysis of material surfaces.
Source : https://pubs.acs.org/doi/10.1021/acs.nanolett.3c04712
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