AIMC Topic: Hydrogen

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Capturing the potential energy landscape of large size molecular clusters from atomic interactions up to a 4-body system using deep learning.

Physical chemistry chemical physics : PCCP Nov 18, 2022
Exploring the structure and properties of molecular clusters with accuracy using the methods is a resource intensive task due to the increasing cost of the methods and the number of distinct conformers as the size increases. The energy landscape of...
Deep Learning Methanol Hydrogen
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Machine Learning for Predicting Chemical Potentials of Multifunctional Organic Compounds in Atmospherically Relevant Solutions.

The journal of physical chemistry letters Oct 19, 2022
We have trained the Extreme Minimum Learning Machine (EMLM) machine learning model to predict chemical potentials of individual conformers of multifunctional organic compounds containing carbon, hydrogen, and oxygen. The model is able to predict chem...
Organic Chemicals Carbon Oxygen Machine Learning Hydrogen Thermodynamics
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Machine-learning-assisted molecular design of phenylnaphthylamine-type antioxidants.

Physical chemistry chemical physics : PCCP Jun 1, 2022
In this study, a total of 302 molecular structures of phenylnaphthylamine antioxidants based on -phenyl-1-naphthylamine and -phenyl-2-naphthylamine skeletons with various substituents were modeled by exhaustive methods. Antioxidant parameters, includ...
Hydrogen Machine Learning Antioxidants Neural Networks, Computer
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Efficient Machine-Learning-Aided Screening of Hydrogen Adsorption on Bimetallic Nanoclusters.

ACS combinatorial science Nov 4, 2020
Nanoclusters add an additional dimension in which to look for promising catalyst candidates, since catalytic activity of materials often changes at the nanoscale. However, the large search space of relevant atomic sites exacerbates the challenge for ...
Machine Learning Nanoparticles Hydrogen Thermodynamics Copper Cobalt Adsorption Density Functional Theory
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Effective modelling of hydrogen and energy recovery in microbial electrolysis cell by artificial neural network and adaptive network-based fuzzy inference system.

Bioresource technology Aug 5, 2020
This study aims to analyze and model cathodic H recovery (r), coulombic efficiency (CE) with inputs of voltage, electrical conductivity (EC) and anode potential, and H production rate and total energy recovery with inputs of r and CE in a microbial e...
Neural Networks, Computer Fuzzy Logic Physical Phenomena Hydrogen Electrolysis
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Powerful, transferable representations for molecules through intelligent task selection in deep multitask networks.

Physical chemistry chemical physics : PCCP Jun 1, 2020
Chemical representations derived from deep learning are emerging as a powerful tool in areas such as drug discovery and materials innovation. Currently, this methodology has three major limitations - the cost of representation generation, risk of inh...
Fluorine Bromine Deep Learning Nitrogen Carbon Hydrogen Phosphorus Oxygen Sulfur Chlorine Iodine Metals
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Untethered Soft Robotics with Fully Integrated Wireless Sensing and Actuating Systems for Somatosensory and Respiratory Functions.

Soft robotics Jan 23, 2020
There has been a great deal of interest in designing soft robots that can mimic a human system with haptic and proprioceptive functions. There is now a strong demand for soft robots that can sense their surroundings and functions in harsh environment...
Robotics Hand Hydrogen Elastomers Humans Hand Strength
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Machine Learning Prediction of H Adsorption Energies on Ag Alloys.

Journal of chemical information and modeling Apr 2, 2019
Adsorption energies on surfaces are excellent descriptors of their chemical properties, including their catalytic performance. High-throughput adsorption energy predictions can therefore help accelerate first-principles catalyst design. To this end, ...
Machine Learning Adsorption Silver Molecular Conformation Models, Molecular Thermodynamics Hydrogen Alloys
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3D Fabrication of Fully Iron Magnetic Microrobots.

Small (Weinheim an der Bergstrasse, Germany) Mar 4, 2019
Biocompatibility and high responsiveness to magnetic fields are fundamental requisites to translate magnetic small-scale robots into clinical applications. The magnetic element iron exhibits the highest saturation magnetization and magnetic susceptib...
Humans Iron Hydrogen Microfluidics Electroplating HCT116 Cells Magnets Surface Properties Printing, Three-Dimensional Magnetic Fields Electrochemistry Robotics Biocompatible Materials Microtechnology
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Improving the environmental impact of palm kernel shell through maximizing its production of hydrogen and syngas using advanced artificial intelligence.

The Science of the total environment Dec 19, 2018
Fossil fuel depletion and the environmental concerns have been under discussion for energy production for many years and finding new and renewable energy sources became a must. Biomass is considered as a net zero CO energy source. Gasification of bio...
Conservation of Energy Resources Gases Arecaceae Pyrolysis Fuzzy Logic Biofuels Nuts Hydrogen
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