首页|Findings from TecNM Institute of Technology Broaden Understanding of Nanomateria ls (Machine-learning Driven Stm Images Prediction of Doped/defective Graphene: T owards Optimized Tools for 2d Nanomaterials Characterization)
Findings from TecNM Institute of Technology Broaden Understanding of Nanomateria ls (Machine-learning Driven Stm Images Prediction of Doped/defective Graphene: T owards Optimized Tools for 2d Nanomaterials Characterization)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – New research on Nanotechnology - Nanomaterials is the subject of a report. According to news reporting originating in Durango, Me xico, by NewsRx journalists, research stated, “Scanning tunneling microscopy (ST M) is a key characterization technique that allows for visualization of specific features at nanostructures, given its ability to reveal changes in local charge densities in doping or defective sites. Besides the experimental acquisition of STM data from real samples, there is the theoretical route, which allows for ST M images simulation from ab-initio calculations on defined nanostructures.” Financial support for this research came from National Council of Science and Te chnology (CONAHCYT, Mexico).
DurangoMexicoNorth and Central Ameri caCyborgsEmerging TechnologiesMachine LearningNanomaterialsNanostructu ralNanostructuresNanotechnologyScanning Tunneling MicroscopyTecNM Instit ute of Technology
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