AIMC Topic: Electrons
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Artificial intelligence "sees" split electrons.
Science (New York, N.Y.)
Dec 9, 2021
Machine-learning creates a density functional that accounts for fractional charge and spin.
Few-fs resolution of a photoactive protein traversing a conical intersection.
Nature
Nov 3, 2021
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...
Machine Learning Approach to Calculate Electronic Couplings between Quasi-diabatic Molecular Orbitals: The Case of DNA.
The journal of physical chemistry letters
Oct 21, 2021
Diabatization of one-electron states in flexible molecular aggregates is a great challenge due to the presence of surface crossings between molecular orbital (MO) levels and the complex interaction between MOs of neighboring molecules. In this work, ...
Synaptic Weight Evolution and Charge Trapping Mechanisms in a Synaptic Pass-Transistor Operation With a Direct Potential Output.
IEEE transactions on neural networks and learning systems
Oct 5, 2021
We present an intensive study on the weight modulation and charge trapping mechanisms of the synaptic transistor based on a pass-transistor concept for the direct voltage output. In this article, the pass-transistor concept for a metal-oxide-semicond...
Using Neural Network Force Fields to Ascertain the Quality of Simulations of Liquid Water.
The journal of physical chemistry. B
Sep 20, 2021
Accurately simulating the properties of bulk water, despite the apparent simplicity of the molecule, is still a challenge. In order to fully understand and reproduce its complex phase diagram, it is necessary to perform simulations at the level, inc...
Neural network representation of electronic structure from ab initio molecular dynamics.
Science bulletin
Sep 17, 2021
Despite their rich information content, electronic structure data amassed at high volumes in ab initio molecular dynamics simulations are generally under-utilized. We introduce a transferable high-fidelity neural network representation of such data i...
Simulation and machine learning modelling based comparative study of InAlGaN and AlGaN high electron mobility transistors for the detection of HER-2.
Analytical methods : advancing methods and applications
Jul 29, 2021
The detection of the cancer biomarker human epidermal growth factor receptor 2 (HER-2) has always been challenging at the early stages of cancer due to its very small presence. A systematic study of biosensors to achieve optimum sensitivity is of par...
Automated and Autonomous Experiments in Electron and Scanning Probe Microscopy.
ACS nano
Jul 16, 2021
Machine learning and artificial intelligence (ML/AI) are rapidly becoming an indispensable part of physics research, with domain applications ranging from theory and materials prediction to high-throughput data analysis. In parallel, the recent succe...
DeepBeam: a machine learning framework for tuning the primary electron beam of the PRIMO Monte Carlo software.
Radiation oncology (London, England)
Jun 29, 2021
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 ...
Highly Sensitive Ultrastable Electrochemical Sensor Enabled by Proton-Coupled Electron Transfer.
Nano letters
Jun 14, 2021
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 ...
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