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 ...
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...
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...
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...
Journal of chemical information and modeling
39698829
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...
Environmental science and pollution research international
39638894
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...
Journal of chemical information and modeling
39764769
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...
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...
We present a simplest-level electron nuclear dynamics/machine learning (SLEND/ML) approach to predict chemical properties in ion cancer therapy (ICT) reactions. SLEND is a time-dependent, variational, on-the-fly, and nonadiabatic method. In SLEND, nu...
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 ...