首页|Aalto University Reports Findings in Machine Learning (Automated Structure Disco very for Scanning Tunneling Microscopy)
Aalto University Reports Findings in Machine Learning (Automated Structure Disco very for Scanning Tunneling Microscopy)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Machine Learning is th e subject of a report. According to news reporting from Espoo, Finland, by NewsR x journalists, research stated, “Scanning tunneling microscopy (STM) with a func tionalized tip apex reveals the geometric and electronic structures of a sample within the same experiment. However, the complex nature of the signal makes imag es difficult to interpret and has so far limited most research to planar samples with a known chemical composition.” The news correspondents obtained a quote from the research from Aalto University , “Here, we present automated structure discovery for STM (ASD-STM), a machine l earning tool for predicting the atomic structure directly from an STM image, by building upon successful methods for structure discovery in noncontact atomic fo rce microscopy (nc-AFM). We apply the method on various organic molecules and ac hieve good accuracy on structure predictions and chemical identification on a qu alitative level while highlighting future development requirements for ASD-STM. This method is directly applicable to experimental STM images of organic molecul es, making structure discovery available for a wider scanning probe microscopy a udience outside of nc-AFM.”
EspooFinlandEuropeCyborgsEmergin g TechnologiesMachine Learning
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