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Thermodynamics

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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...
Neural Networks, Computer Thermodynamics Convection Algorithms Computer Simulation
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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 ...
Halogens Sulfur Thermodynamics Deep Learning Density Functional Theory Molecular Dynamics Simulation
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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...
Machine Learning Transition Temperature Thermodynamics Models, Chemical Pharmaceutical Preparations Solubility Calorimetry, Differential Scanning Freezing Computer Simulation Quantitative Structure-Activity Relationship Software Water Algorithms Models, Molecular
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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...
Neural Networks, Computer Kinetics Thermodynamics Electric Conductivity Electrodes Silicon Alloys
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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 ...
Machine Learning Thermodynamics Algorithms Protein Structure, Tertiary Drug Design Protein Binding Epoxide Hydrolases Humans Molecular Dynamics Simulation Ligands
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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...
Protein Conformation, alpha-Helical Protein Conformation, beta-Strand Protein Interaction Domains and Motifs Structural Homology, Protein Humans Ligands Software Binding Sites Research Design Thermodynamics Peptides Proteins Computer Graphics Molecular Docking Simulation Deep Learning Benchmarking Protein Interaction Mapping Amino Acid Sequence Protein Binding Protein Multimerization
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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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A deep learning approach for the blind logP prediction in SAMPL6 challenge.

Journal of computer-aided molecular design Jan 30, 2020
Water octanol partition coefficient serves as a measure for the lipophilicity of a molecule and is important in the field of drug discovery. A novel method for computational prediction of logarithm of partition coefficient (logP) has been developed u...
Machine Learning Drug Discovery Deep Learning Solubility Thermodynamics Octanols Water Molecular Structure Models, Chemical
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Quantification of interfacial energies associated with membrane fouling in a membrane bioreactor by using BP and GRNN artificial neural networks.

Journal of colloid and interface science Jan 7, 2020
Interfacial energy between sludge foulants and rough membrane surface critically determines adhesive fouling in membrane bioreactors (MBRs). As a current available method, the advanced extensive Derjaguin-Landau-Verwey-Overbeek (XDLVO) approach canno...
Thermodynamics Bioreactors Surface Properties Membranes, Artificial Neural Networks, Computer Particle Size
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Robust Prediction of Single and Multiple Point Protein Mutations Stability Changes.

Biomolecules Dec 31, 2019
Accurate prediction of protein stability changes resulting from amino acid substitutions is of utmost importance in medicine to better understand which mutations are deleterious, leading to diseases, and which are neutral. Since conducting wet lab ex...
Protein Stability Thermodynamics Proteins Point Mutation Neural Networks, Computer Databases, Protein Machine Learning Amino Acids
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