Journal of chemical information and modeling
Oct 14, 2020
We develop a convolutional neural network capable of directly parsing the 3D electronic structure of a molecule described by spatial point data for charge density and electrostatic potential represented as a 4D tensor. This method effectively bypasse...
Neural networks : the official journal of the International Neural Network Society
Oct 8, 2020
Estimating the importance of each atom in a molecule is one of the most appealing and challenging problems in chemistry, physics, and materials science. The most common way to estimate the atomic importance is to compute the electronic structure usin...
Advanced materials (Deerfield Beach, Fla.)
Oct 1, 2020
Memristors have recently attracted significant interest due to their applicability as promising building blocks of neuromorphic computing and electronic systems. The dynamic reconfiguration of memristors, which is based on the history of applied elec...
A rapid method for screening pathogens can revolutionize health care by enabling infection control through medication before symptom. Here we report on label-free single-cell identifications of clinically-important pathogenic bacteria by using a poly...
Charge transport in deoxyribonucleic acid (DNA) is of immense interest in biology and molecular electronics. Electronic coupling between the DNA bases is an important parameter describing the efficiency of charge transport in DNA. A reasonable estima...
Machine learning has revolutionized the high-dimensional representations for molecular properties such as potential energy. However, there are scarce machine learning models targeting tensorial properties, which are rotationally covariant. Here, we p...
Electronic skin (e-skin), which is an electronic surrogate of human skin, aims to recreate the multifunctionality of skin by using sensing units to detect multiple stimuli, while keeping key features of skin such as low thickness, stretchability, fle...
Neural networks : the official journal of the International Neural Network Society
Mar 3, 2020
The design of neuromorphic chips aims to develop electronic circuits dedicated to executing artificial neural networks, mainly by exploring parallel processing. Unsupervised learning models, such as Self-organizing Maps (SOM), may benefit from massiv...
Memristive and nanoionic devices have recently emerged as leading candidates for neuromorphic computing architectures. While top-down fabrication based on conventional bulk materials has enabled many early neuromorphic devices and circuits, bottom-up...
Mental fatigue, characterized by subjective feelings of "tiredness" and "lack of energy", can degrade individual performance in a variety of situations, for example, in motor vehicle driving or while performing surgery. Thus, a method for nonintrusiv...
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