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Electrons

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Few-fs resolution of a photoactive protein traversing a conical intersection.

Nature
The structural dynamics of a molecule are determined by the underlying potential energy landscape. Conical intersections are funnels connecting otherwise separate potential energy surfaces. Posited almost a century ago, conical intersections remain t...

Site-Specific Regulated Memristors via Electron-Beam-Induced Functionalization of HfO.

Small (Weinheim an der Bergstrasse, Germany)
Emerging nonvolatile resistive switching, also known as the memristor, works with a distinct concept that relies mainly on the change in the composition of the active materials, rather than to store the charge. Particularly for oxide-based memristors...

Artificial intelligence "sees" split electrons.

Science (New York, N.Y.)
Machine-learning creates a density functional that accounts for fractional charge and spin.

Automatic quantification and classification of microplastics in scanning electron micrographs via deep learning.

The Science of the total environment
Microplastics quantification and classification are demanding jobs to monitor microplastic pollution and evaluate the potential health risks. In this paper, microplastics from daily supplies in diverse chemical compositions and shapes are imaged by s...

Fast Improvement of TEM Images with Low-Dose Electrons by Deep Learning.

Microscopy and microanalysis : the official journal of Microscopy Society of America, Microbeam Analysis Society, Microscopical Society of Canada
Low electron dose observation is indispensable for observing various samples using a transmission electron microscope; consequently, image processing has been used to improve transmission electron microscopy (TEM) images. To apply such image processi...

Observing Noncovalent Interactions in Experimental Electron Density for Macromolecular Systems: A Novel Perspective for Protein-Ligand Interaction Research.

Journal of chemical information and modeling
We report for the first time the use of experimental electron density (ED) in the Protein Data Bank for modeling of noncovalent interactions (NCIs) for protein-ligand complexes. Our methodology is based on reduced electron density gradient (RDG) theo...

Deep learning-based in vivo dose verification from proton-induced secondary-electron-bremsstrahlung images with various count level.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
PURPOSE: Proton-induced secondary-electron-bremsstrahlung (SEB) imaging is a promising method for estimating the ranges of particle beam. However, SEB images do not directly represent dose distributions of particle beams. In addition, the ranges esti...

MemBrain: A deep learning-aided pipeline for detection of membrane proteins in Cryo-electron tomograms.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Cryo-electron tomography (cryo-ET) is an imaging technique that enables 3D visualization of the native cellular environment at sub-nanometer resolution, providing unpreceded insights into the molecular organization of cells....

Rapidly predicting Kohn-Sham total energy using data-centric AI.

Scientific reports
Predicting material properties by solving the Kohn-Sham (KS) equation, which is the basis of modern computational approaches to electronic structures, has provided significant improvements in materials sciences. Despite its contributions, both DFT an...

Direct mapping from PET coincidence data to proton-dose and positron activity using a deep learning approach.

Physics in medicine and biology
. Obtaining the intrinsic dose distributions in particle therapy is a challenging problem that needs to be addressed by imaging algorithms to take advantage of secondary particle detectors. In this work, we investigate the utility of deep learning me...