BACKGROUND: Any Monte Carlo simulation of dose delivery using medical accelerator-generated megavolt photon beams begins by simulating electrons of the primary electron beam interacting with a target. Because the electron beam characteristics of any ...
Electrochemical sensors are critical to artificial intelligence by virtue of capability of mimicking human skin to report sensing signals. But their practical applications are restricted by low sensitivity and limited cycling stability, which result ...
Journal of chemical information and modeling
May 19, 2021
Machine learning milestones in computational chemistry are overshadowed by their unaccountability and the overwhelming zoo of tools for each specific task. A promising path to tackle these problems is using machine learning to reproduce physical magn...
Techniques for training artificial neural networks (ANNs) and convolutional neural networks (CNNs) using simulated dynamical electron diffraction patterns are described. The premise is based on the following facts. First, given a suitable crystal str...
The journal of physical chemistry letters
Jan 8, 2021
Nonradiative electron-hole recombination constitutes a major route for charge and energy losses in copper zinc tin sulfide (CZTS) solar cells. Using a combination of nonadiabatic (NA) molecular dynamics and deep neural networks (DNN), we demonstrated...
Journal of chemical information and modeling
Dec 16, 2020
Atomic charges are critical quantities in molecular mechanics and molecular dynamics, but obtaining these quantities requires heuristic choices based on atom typing or relatively expensive quantum mechanical computations to generate a density to be p...
Journal of chemical information and modeling
Oct 8, 2020
Prediction of whether a compound is "aromatic" is at first glance a relatively simple task-does it obey Hückel's rule (planar cyclic π-system with 4n + 2 electrons) or not? However, aromaticity is far from a binary property, and there are distinct va...
We developed a machine learning framework in order to establish the correlation between dose and activity distributions in proton therapy. A recurrent neural network was used to predict dose distribution in three dimensions based on the information o...
PURPOSE: Imaging of the secondary electron bremsstrahlung (SEB) x rays emitted during particle-ion irradiation is a promising method for beam range estimation. However, the SEB x-ray images are not directly correlated to the dose images. In addition,...
Bioinspired electronics are rapidly promoting advances in artificial intelligence. Emerging AI applications, e.g., autopilot and robotics, increasingly spur the development of power devices with new forms. Here, we present a strain-controlled power d...
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