Application of machine learning in anaerobic digestion: Perspectives and challenges
Anaerobic digestion (AD) is widely adopted for remediating diverse organic wastes with
simultaneous production of renewable energy and nutrient-rich digestate. AD process …
simultaneous production of renewable energy and nutrient-rich digestate. AD process …
Innovation designs of industry 4.0 based solid waste management: Machinery and digital circular economy
Abstract The Industrial Revolution 4.0 (IR 4.0) holds the opportunity to improve the efficiency
of managing solid waste through digital and machinery applications, effectively eliminating …
of managing solid waste through digital and machinery applications, effectively eliminating …
Machine learning and circular bioeconomy: Building new resource efficiency from diverse waste streams
Biorefinery systems are playing pivotal roles in the technological support of resource
efficiency for circular bioeconomy. Meanwhile, artificial intelligence presents great potential …
efficiency for circular bioeconomy. Meanwhile, artificial intelligence presents great potential …
The role of electrochemical properties of biochar to promote methane production in anaerobic digestion
The electrochemical properties of biochar may be the key factor to promote anaerobic
digestion, which has attracted extensive attention. However, the mechanism and the role of …
digestion, which has attracted extensive attention. However, the mechanism and the role of …
Predicting the performance of anaerobic digestion using machine learning algorithms and genomic data
Modeling of anaerobic digestion (AD) is crucial to better understand the process dynamics
and to improve the digester performance. This is an essential yet difficult task due to the …
and to improve the digester performance. This is an essential yet difficult task due to the …
Review of explainable machine learning for anaerobic digestion
Anaerobic digestion (AD) is a promising technology for recovering value-added resources
from organic waste, thus achieving sustainable waste management. The performance of AD …
from organic waste, thus achieving sustainable waste management. The performance of AD …
Insights into the mechanism of ozone activation and singlet oxygen generation on N-doped defective nanocarbons: A DFT and machine learning study
N-doped defective nanocarbon (N-DNC) catalysts have been widely studied due to their
exceptional catalytic activity in many applications, but the O3 activation mechanism in …
exceptional catalytic activity in many applications, but the O3 activation mechanism in …
Prediction of biogas production in anaerobic co-digestion of organic wastes using deep learning models
Interest in anaerobic co-digestion (AcoD) has increased significantly in recent decades
owing to enhanced biogas productivity due to the utilization of different organic wastes, such …
owing to enhanced biogas productivity due to the utilization of different organic wastes, such …
Data-Driven Based In-Depth Interpretation and Inverse Design of Anaerobic Digestion for CH4-Rich Biogas Production
Anaerobic digestion (AD) is one of the most widely used bioconversion technologies for
renewable energy production from wet biowaste. However, such an AD system is so …
renewable energy production from wet biowaste. However, such an AD system is so …
Interpretable machine-learning model with a collaborative game approach to predict yields and higher heating value of torrefied biomass
Torrefaction is a treatment process for converting biomass to high-quality solid fuels. The
investigation and interpretation of this process on highly dimensional, non-linear …
investigation and interpretation of this process on highly dimensional, non-linear …