AIMC Topic: Static Electricity

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Machine Learning in QM/MM Molecular Dynamics Simulations of Condensed-Phase Systems.

Journal of chemical theory and computation Apr 5, 2021
Quantum mechanics/molecular mechanics (QM/MM) molecular dynamics (MD) simulations have been developed to simulate molecular systems, where an explicit description of changes in the electronic structure is necessary. However, QM/MM MD simulations are ...
Molecular Dynamics Simulation Quantum Theory Static Electricity Machine Learning
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Uncertainty Quantification and Sensitivity Analysis of Partial Charges on Macroscopic Solvent Properties in Molecular Dynamics Simulations with a Machine Learning Model.

Journal of chemical information and modeling Mar 17, 2021
The molecular dynamics (MD) simulation technique is among the most broadly used computational methods to investigate atomistic phenomena in a variety of chemical and biological systems. One of the most common (and most uncertain) parametrization step...
Machine Learning Molecular Dynamics Simulation Solvents Static Electricity Uncertainty
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Electro-pneumatic pumps for soft robotics.

Science robotics Feb 17, 2021
Soft robotics has applications in myriad fields from assistive wearables to autonomous exploration. Now, the portability and the performance of many devices are limited by their associated pneumatic energy source, requiring either large, heavy pressu...
Muscles Smart Materials Robotics Equipment Design Humans Artificial Organs Wearable Electronic Devices Pressure Static Electricity
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HASEL Artificial Muscles for a New Generation of Lifelike Robots-Recent Progress and Future Opportunities.

Advanced materials (Deerfield Beach, Fla.) Nov 9, 2020
Future robots and intelligent systems will autonomously navigate in unstructured environments and closely collaborate with humans; integrated with our bodies and minds, they will allow us to surpass our physical limitations. Traditional robots are mo...
Equipment Design Biomimetics Artificial Organs Humans Animals Robotics Muscles Biomimetic Materials Static Electricity
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Modeling and Optimization of Electrostatic Film Actuators Based on the Method of Moments.

Soft robotics Oct 1, 2020
Electrostatic film actuators represent a promising new approach to drive a soft robot, but they lack a comprehensive model to link the design parameters and actuation performance, making actuator design and parameter optimization challenging. To solv...
Robotics Equipment Design Static Electricity Mechanical Phenomena Movement
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Miniaturized Circuitry for Capacitive Self-Sensing and Closed-Loop Control of Soft Electrostatic Transducers.

Soft robotics Oct 1, 2020
Soft robotics is a field of robotic system design characterized by materials and structures that exhibit large-scale deformation, high compliance, and rich multifunctionality. The incorporation of soft and deformable structures endows soft robotic sy...
Muscles Transducers Musculoskeletal System Robotics Static Electricity
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Characterizing Protein-Ligand Binding Using Atomistic Simulation and Machine Learning: Application to Drug Resistance in HIV-1 Protease.

Journal of chemical theory and computation Jan 16, 2020
Over the past several decades, atomistic simulations of biomolecules, whether carried out using molecular dynamics or Monte Carlo techniques, have provided detailed insights into their function. Comparing the results of such simulations for a few clo...
Hydrogen Bonding Static Electricity Monte Carlo Method HIV Protease HIV Protease Inhibitors Protein Binding Mutation Molecular Dynamics Simulation HIV-1 Ligands Drug Resistance, Viral Humans Machine Learning
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Steroid identification via deep learning retention time predictions and two-dimensional gas chromatography-high resolution mass spectrometry.

Journal of chromatography. A Oct 28, 2019
Untargeted steroid identification represents a great analytical challenge even when using sophisticated technology such as two-dimensional gas chromatography coupled to high resolution mass spectrometry (GC × GCHRMS) due to the chemical similarity of...
Neural Networks, Computer Steroids Deep Learning Support Vector Machine Static Electricity Least-Squares Analysis Gas Chromatography-Mass Spectrometry
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Practical High-Quality Electrostatic Potential Surfaces for Drug Discovery Using a Graph-Convolutional Deep Neural Network.

Journal of medicinal chemistry Sep 25, 2019
Inspecting protein and ligand electrostatic potential (ESP) surfaces in order to optimize electrostatic complementarity is a key activity in drug design. These ESP surfaces need to reflect the true electrostatic nature of the molecules, which typical...
X-Linked Inhibitor of Apoptosis Protein Ligands Protein Binding Factor Xa Datasets as Topic Drug Discovery Organic Chemicals Hydrogen Bonding Deep Learning Quantum Theory Static Electricity
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A Machine Learning-Based QSAR Model for Benzimidazole Derivatives as Corrosion Inhibitors by Incorporating Comprehensive Feature Selection.

Interdisciplinary sciences, computational life sciences Sep 4, 2019
BACKGROUND: Computational prediction of inhibition efficiency (IE) for inhibitor molecules is a crucial supplementary way to design novel molecules that can efficiently inhibit corrosion onto metallic surfaces.
Algorithms Metals Corrosion Imaging, Three-Dimensional Static Electricity Conservation of Natural Resources Machine Learning Predictive Value of Tests Benzimidazoles Computational Biology Quantitative Structure-Activity Relationship Hydrazines Chemistry Support Vector Machine Linear Models Cluster Analysis
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