[HTML][HTML] Machine-learning-aided thermochemical treatment of biomass: a review

H Li, J Chen, W Zhang, H Zhan, C He… - Biofuel Research …, 2023 - biofueljournal.com
Thermochemical treatment is a promising technique for biomass disposal and valorization.
Recently, machine learning (ML) has been extensively used to predict yields, compositions …

Applications of machine learning in thermochemical conversion of biomass-A review

SR Naqvi, Z Ullah, SAA Taqvi, MNA Khan, W Farooq… - Fuel, 2023 - Elsevier
Thermochemical conversion of biomass has been considered a promising technique to
produce alternative renewable fuel sources for future energy supply. However, these …

Recent advances and future prospects of thermochemical biofuel conversion processes with machine learning

PR Jeon, JH Moon, NO Ogunsola, SH Lee… - Chemical Engineering …, 2023 - Elsevier
Biofuels have been widely recognized as potential solutions to addressing the climate crisis
and strengthening energy security and sustainability. However, techno-economic and …

Co-pyrolysis of lignocellulosic biomass with other carbonaceous materials: A review on advance technologies, synergistic effect, and future prospectus

WH Chen, C Naveen, PK Ghodke, AK Sharma… - Fuel, 2023 - Elsevier
Due to the continuous rise in population, modernization, and industrialization, the demand
for energy is increasing day by day, resulting in serious issues such as fossil fuel depletion …

Applications of artificial intelligence in anaerobic co-digestion: Recent advances and prospects

M Khan, W Chuenchart, KC Surendra, SK Khanal - Bioresource technology, 2023 - Elsevier
Anaerobic co-digestion (AcoD) offers several merits such as better digestibility and process
stability while enhancing methane yield due to synergistic effects. Operation of an efficient …

Comparative study of machine learning methods integrated with genetic algorithm and particle swarm optimization for bio-char yield prediction

ZU Haq, H Ullah, MNA Khan, SR Naqvi, A Ahad… - Bioresource …, 2022 - Elsevier
In this study, Machine learning (ML) models integrated with genetic algorithm (GA) and
particle swarm optimization (PSO) have been developed to predict, evaluate, and analyze …

Hydrogen production optimization from sewage sludge supercritical gasification process using machine learning methods integrated with genetic algorithm

ZU Haq, H Ullah, MNA Khan, SR Naqvi… - … Research and Design, 2022 - Elsevier
Hydrogen production from the supercritical water gasification (SCWG) of sewage sludge
(SS) is a sustainable and efficient process. However, the challenging and intricate task for …

Multi-variable assessment/optimization of a new two-source multigeneration system integrated with a solid oxide fuel cell

L Tian, Z Zhang, B Salah, M Marefati - Process Safety and Environmental …, 2023 - Elsevier
The integration of renewable energies can improve the thermodynamic performance and
increase the popularity and commercialization of the energy production system. Moreover …

Catalytic pyrolysis of rice husk over defect-rich beta zeolites for biofuel production

AA Zaidi, A Khan, H AlMohamadi, MW Anjum, I Ali… - Fuel, 2023 - Elsevier
Abstract The Coats-Redfern method was used to identify the catalytic and non-catalytic
pyrolysis of rice husk biomass kinetics by using thermogravimetric analysis. MTES-beta …

A renewable and sustainable framework for clean fuel towards circular economy for solid waste generation in leather tanneries

AM Ali, A Khan, M Shahbaz, MI Rashid, M Imran… - Fuel, 2023 - Elsevier
In today's economy, the leather industry is one of the most important manufacturing
industries in the world. Mismanaging solid waste in tanneries is the most significant …