Machine learning is supposed to help us do everything these days, so why not electron microscopy? A team from Ireland has done just that and published their results using machine learning to enhance ...

Before and after: example of image denoising as applied to atomic resolution imaging of a gold nanoparticle. On the left is the original experimental data as captured. On the right is the same image ...

Finding defects in electron microscopy images takes months. Now, there’s a faster way. It’s called MENNDL, the Multinode Evolutionary Neural Networks for Deep Learning. It creates artificial neural ...

Beams of accelerated electrons power electron microscopes, X-ray lasers, medical accelerators and other devices. To optimize the performance of these applications, operators must be able to analyze ...

Researchers in Korea have developed an artificial intelligence (AI) technology that predicts molecular properties by learning electron-level information without requiring costly quantum mechanical ...

Achieving state-of-the-art accuracy in molecular property prediction using self-supervised AI, enabling cost-effective modeling based on electron-level information without quantum calculations ...