An overview of the enhanced biomass gasification for hydrogen production
Hydrogen (H 2) production from biomass gasification offers exceptional benefits regarding
renewable energy sources, zero-carbon emission, cost-effective processes, and high …
renewable energy sources, zero-carbon emission, cost-effective processes, and high …
Production of hydrogen from fossil fuel: A review
Production of hydrogen, one of the most promising alternative clean fuels, through catalytic
conversion from fossil fuel is the most technically and economically feasible technology …
conversion from fossil fuel is the most technically and economically feasible technology …
100 years of scaling up fluidized bed and circulating fluidized bed reactors
JW Chew, WCQ LaMarche, RA Cocco - Powder Technology, 2022 - Elsevier
This year, 2022, we celebrate the 100-year anniversary of the commercialization of the
fluidized bed reactor. In those years, many new processes have been developed, with many …
fluidized bed reactor. In those years, many new processes have been developed, with many …
Development of machine learning-based models for describing processes in a continuous solar-driven biomass gasifier
The synergy of two renewable and efficient sources in producing clean fuels, ie, solar
energy and biomass, can result in high efficiency. In this regard, developing syngas …
energy and biomass, can result in high efficiency. In this regard, developing syngas …
Scaling up dry methane reforming: Integrating computational fluid dynamics and machine learning for enhanced hydrogen production in industrial-scale fluidized bed …
This research investigates the optimization and simulation of dry methane reforming (DMR)
in fluidized and fixed bed reactors at an industrial scale. By utilizing Computational Fluid …
in fluidized and fixed bed reactors at an industrial scale. By utilizing Computational Fluid …
[HTML][HTML] The rise of the machines: A state-of-the-art technical review on process modelling and machine learning within hydrogen production with carbon capture
WG Davies, S Babamohammadi, Y Yang… - Gas Science and …, 2023 - Elsevier
This study aims to present a compendious yet technical scrutiny of the current trends in
process modelling as well as the implementation of machine learning within combined …
process modelling as well as the implementation of machine learning within combined …
Advancing light olefin production: Exploring pathways, catalyst development, and future prospects
The utilization of light olefins (C 2-C 4) as fundamental building blocks in chemical industries
has been a subject of extensive research, particularly in exploring their production through a …
has been a subject of extensive research, particularly in exploring their production through a …
Fluidized Bed Scale-Up for Sustainability Challenges. 1. Tomorrow's Tools
RA Cocco, JW Chew - Industrial & Engineering Chemistry …, 2024 - ACS Publications
The scaling up of fluidized beds has been purposefully pursued for more than 100 years.
Yet, over that time, scale-up tools have not significantly changed. Data analysis is typically a …
Yet, over that time, scale-up tools have not significantly changed. Data analysis is typically a …
A review on thermochemical based biorefinery catalyst development progress
M Gholizadeh, C Castro, SM Fabrega… - Sustainable Energy & …, 2023 - pubs.rsc.org
The depletion of fossil fuel resources highlighted the need for renewable energy. Between
different sources of the renewable energy, biorefinery, which is based on thermochemical …
different sources of the renewable energy, biorefinery, which is based on thermochemical …
Smart investigation of artificial intelligence in renewable energy system technologies by natural language processing: Insightful pattern for decision-makers
K Niroomand, NMC Saady, C Bazan… - … Applications of Artificial …, 2023 - Elsevier
This study aims to provide a framework which enables decision-makers and researchers to
identify AI technology patterns in renewable energy systems from a massive data set of …
identify AI technology patterns in renewable energy systems from a massive data set of …