AIMC Topic: Hydrogen

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Ultrafast Hydrogen Detection System Using Vertical Thermal Conduction Structure and Neural Network Prediction Algorithm Based on Sensor Response Process.

ACS sensors Mar 11, 2025
Hydrogen detection plays a crucial role in various scenes of hydrogen energy such as hydrogen vehicles, hydrogen transportation and hydrogen storage. It is essential to develop a hydrogen detection system with ultrafast response times (<1 s) for the ...
Neural Networks, Computer Thermal Conductivity Prediction Algorithms Algorithms Hydrogen
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PathInHydro, a Set of Machine Learning Models to Identify Unbinding Pathways of Gas Molecules in [NiFe] Hydrogenases.

Journal of chemical information and modeling Jan 7, 2025
Machine learning (ML) is a powerful tool for the automated data analysis of molecular dynamics (MD) simulations. Recent studies showed that ML models can be used to identify protein-ligand unbinding pathways and understand the underlying mechanism. T...
Machine Learning Carbon Monoxide Desulfovibrio Molecular Dynamics Simulation Oxygen Hydrogen Hydrogenase
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Accelerating Plasmonic Hydrogen Sensors for Inert Gas Environments by Transformer-Based Deep Learning.

ACS sensors Jan 7, 2025
Rapidly detecting hydrogen leaks is critical for the safe large-scale implementation of hydrogen technologies. However, to date, no technically viable sensor solution exists that meets the corresponding response time targets under technically relevan...
Noble Gases Deep Learning Surface Plasmon Resonance Hydrogen
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MGT: Machine Learning Accelerates Performance Prediction of Alloy Catalytic Materials.

Journal of chemical information and modeling Dec 19, 2024
The application of deep learning technology in the field of materials science provides a new method for predicting the adsorption energy of high-performance alloy catalysts in hydrogen evolution reactions and material discovery. The activity and sele...
Catalysis Hydrogen Alloys Machine Learning Adsorption
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Recent advances in dark fermentative hydrogen production from vegetable waste: role of inoculum, consolidated bioprocessing, and machine learning.

Environmental science and pollution research international Dec 6, 2024
Waste-centred-bioenergy generation have been garnering interest over the years due to environmental impact presented by fossil fuels. Waste generation is an unavoidable consequence of urbanization and population growth. Sustainable waste management t...
Fermentation Vegetables Biomass Hydrogen Biofuels Waste Management Machine Learning
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Production of high calorific value hydrogen-rich combustible gas by supercritical water gasification of straw assisted by machine learning.

Bioresource technology Aug 14, 2024
This article reveals the basic laws of straw supercritical water gasification (SCWG) and provides basic experimental data for the effective utilization of straw. The paper studied the impact of three operational conditions on the production of high-c...
Hydrogen Biomass Water Machine Learning Carbon Dioxide Gases
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Prediction of Individual Gas Yields of Supercritical Water Gasification of Lignocellulosic Biomass by Machine Learning Models.

Molecules (Basel, Switzerland) May 16, 2024
Supercritical water gasification (SCWG) of lignocellulosic biomass is a promising pathway for the production of hydrogen. However, SCWG is a complex thermochemical process, the modeling of which is challenging via conventional methodologies. Therefor...
Neural Networks, Computer Biomass Lignin Water Machine Learning Hydrogen Methane Support Vector Machine Gases Algorithms Carbon Dioxide
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Unlocking Predictive Capability and Enhancing Sensing Performances of Plasmonic Hydrogen Sensors via Phase Space Reconstruction and Convolutional Neural Networks.

ACS sensors May 13, 2024
This study innovates plasmonic hydrogen sensors (PHSs) by applying phase space reconstruction (PSR) and convolutional neural networks (CNNs), overcoming previous predictive and sensing limitations. Utilizing a low-cost and efficient colloidal lithogr...
Neural Networks, Computer Hydrogen Metal Nanoparticles Palladium
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Modeling and optimization of photo-fermentation biohydrogen production from co-substrates basing on response surface methodology and artificial neural network integrated genetic algorithm.

Bioresource technology Feb 24, 2023
The main aim of the present study was to establish a relationship model between bio-hydrogen yield and the key operating parameters affecting photo-fermentation hydrogen production (PFHP) from co-substrates. Central composite design-response surface ...
Hydrogen Fermentation Neural Networks, Computer Temperature
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Machine learning in fermentative biohydrogen production: Advantages, challenges, and applications.

Bioresource technology Dec 17, 2022
Hydrogen can be produced in an environmentally friendly manner through biological processes using a variety of organic waste and biomass as feedstock. However, the complexity of biological processes limits their predictability and reliability, which ...
Fermentation Reproducibility of Results Machine Learning Hydrogen Biomass
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