AIMC Topic: Thermodynamics

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Finite-time stabilization and energy consumption estimation for delayed neural networks with bounded activation function.

Neural networks : the official journal of the International Neural Network Society Aug 5, 2020
This paper concentrates on finite-time stabilization and energy consumption estimation for one type of delayed neural networks (DNNs) with bounded activation function. Under the bounded activation function condition and using the comparison theorem, ...
Neural Networks, Computer Thermodynamics Finite Element Analysis Time
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Hybrid Alchemical Free Energy/Machine-Learning Methodology for the Computation of Hydration Free Energies.

Journal of chemical information and modeling Aug 4, 2020
A methodology that combines alchemical free energy calculations (FEP) with machine learning (ML) has been developed to compute accurate absolute hydration free energies. The hybrid FEP/ML methodology was trained on a subset of the FreeSolv database a...
Retrospective Studies Thermodynamics Entropy Machine Learning Computer Simulation
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Modeling of Cu(II) Adsorption from an Aqueous Solution Using an Artificial Neural Network (ANN).

Molecules (Basel, Switzerland) Jul 17, 2020
This research optimized the adsorption performance of rice husk char (RHC4) for copper (Cu(II)) from an aqueous solution. Various physicochemical analyses such as Fourier transform infrared spectroscopy (FTIR), field-emission scanning electron micros...
Solutions Thermodynamics Adsorption Models, Molecular Neural Networks, Computer Algorithms Kinetics Copper Water Diffusion Water Pollutants, Chemical Sulfur
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Investigation of singular ordinary differential equations by a neuroevolutionary approach.

PloS one Jul 9, 2020
In this research, we have investigated doubly singular ordinary differential equations and a real application problem of studying the temperature profile in a porous fin model. We have suggested a novel soft computing strategy for the training of unk...
Computer Simulation Neural Networks, Computer Thermodynamics Convection Algorithms
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Extending the Applicability of the ANI Deep Learning Molecular Potential to Sulfur and Halogens.

Journal of chemical theory and computation Jun 29, 2020
Machine learning (ML) methods have become powerful, predictive tools in a wide range of applications, such as facial recognition and autonomous vehicles. In the sciences, computational chemists and physicists have been using ML for the prediction of ...
Deep Learning Density Functional Theory Molecular Dynamics Simulation Sulfur Halogens Thermodynamics
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Machine Estimation of Drug Melting Properties and Influence on Solubility Prediction.

Molecular pharmaceutics Jun 19, 2020
There has been much recent interest in machine learning (ML) and molecular quantitative structure property relationships (QSPR). The present research evaluated modern ML-based methods implemented in commercial software (COSMOquick and Molecular Model...
Transition Temperature Thermodynamics Models, Chemical Pharmaceutical Preparations Solubility Calorimetry, Differential Scanning Freezing Quantitative Structure-Activity Relationship Computer Simulation Water Models, Molecular Software Algorithms Machine Learning
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Alloying conducting channels for reliable neuromorphic computing.

Nature nanotechnology Jun 8, 2020
A memristor has been proposed as an artificial synapse for emerging neuromorphic computing applications. To train a neural network in memristor arrays, changes in weight values in the form of device conductance should be distinct and uniform. An elec...
Electrodes Silicon Neural Networks, Computer Alloys Kinetics Thermodynamics Electric Conductivity
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Combining Machine Learning and Enhanced Sampling Techniques for Efficient and Accurate Calculation of Absolute Binding Free Energies.

Journal of chemical theory and computation Jun 4, 2020
Calculating absolute binding free energies is challenging and important. In this paper, we test some recently developed metadynamics-based methods and develop a new combination with a Hamiltonian replica-exchange approach. The methods were tested on ...
Humans Machine Learning Algorithms Ligands Thermodynamics Protein Structure, Tertiary Drug Design Protein Binding Molecular Dynamics Simulation Epoxide Hydrolases
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Energy-based graph convolutional networks for scoring protein docking models.

Proteins Mar 16, 2020
Structural information about protein-protein interactions, often missing at the interactome scale, is important for mechanistic understanding of cells and rational discovery of therapeutics. Protein docking provides a computational alternative for su...
Proteins Benchmarking Amino Acid Sequence Deep Learning Protein Binding Computer Graphics Protein Conformation, alpha-Helical Protein Interaction Domains and Motifs Protein Interaction Mapping Protein Conformation, beta-Strand Humans Structural Homology, Protein Ligands Protein Multimerization Research Design Software Binding Sites Peptides Thermodynamics Molecular Docking Simulation
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Application of Symmetry Functions to Large Chemical Spaces Using a Convolutional Neural Network.

Journal of chemical information and modeling Mar 16, 2020
The use of machine learning in chemistry is on the rise for the prediction of chemical properties. The input feature representation or descriptor in these applications is an important factor that affects the accuracy as well as the extent of the expl...
Machine Learning Thermodynamics Physical Phenomena Neural Networks, Computer
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