AIMC Topic: Methane
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Electrohydrolysis pretreatment for enhanced methane production from lignocellulose waste pulp and paper mill sludge and its kinetics.
Bioresource technology
Dec 29, 2017
A novel electrohydrolysis pretreatment enhances methane production from lignocellulose material during anaerobic digestion. A biochemical methane potential assay was carried out to determine the effect of direct current and the efficacy of electrohyd...
Employing response surface methodology (RSM) to improve methane production from cotton stalk.
Environmental science and pollution research international
Dec 28, 2017
China is the largest cotton producer with the cotton output accounting for 25% of the total world's cotton production. A large quantity of cotton stalk (CS) waste is generated which is burned and causes environmental and ecological problems. This stu...
Improving methane production from anaerobic digestion of Pennisetum Hybrid by alkaline pretreatment.
Bioresource technology
Dec 6, 2017
Alkaline pretreatment with NaOH was used to improve methane yield from Pennisetum Hybrid. The pretreatments were carried out with different NaOH solutions (2-8% w/w) at three temperatures (35, 55 and 121 °C) for different periods of time (24, 24 and ...
Microbial community redundancy in anaerobic digestion drives process recovery after salinity exposure.
Water research
Dec 26, 2016
Anaerobic digestion of high-salinity wastewaters often results in process inhibition due to the susceptibility of the methanogenic archaea. The ability of the microbial community to deal with increased salinity levels is of high importance to ensure ...
Estimation of biogas and methane yields in an UASB treating potato starch processing wastewater with backpropagation artificial neural network.
Bioresource technology
Dec 16, 2016
Three-layered feedforward backpropagation (BP) artificial neural networks (ANN) and multiple nonlinear regression (MnLR) models were developed to estimate biogas and methane yield in an upflow anaerobic sludge blanket (UASB) reactor treating potato s...
Application of fuzzy neural networks for modeling of biodegradation and biogas production in a full-scale internal circulation anaerobic reactor.
Journal of environmental science and health. Part A, Toxic/hazardous substances & environmental engineering
Sep 9, 2016
This paper presents the development and evaluation of three fuzzy neural network (FNN) models for a full-scale anaerobic digestion system treating paper-mill wastewater. The aim was the investigation of feasibility of the approach-based control syste...
A fuzzy-logic-based controller for methane production in anaerobic fixed-film reactors.
Environmental technology
May 13, 2016
The main objective of this work was to develop a controller for biogas production in continuous anaerobic fixed-bed reactors, which used effluent total volatile fatty acids (VFA) concentration as control input in order to prevent process acidificatio...
Artificial neural network based modeling to evaluate methane yield from biogas in a laboratory-scale anaerobic bioreactor.
Bioresource technology
Mar 12, 2016
The performance of a laboratory-scale anaerobic bioreactor was investigated in the present study to determine methane (CH4) content in biogas yield from digestion of organic fraction of municipal solid waste (OFMSW). OFMSW consists of food waste, veg...
Enhanced methane production in an anaerobic digestion and microbial electrolysis cell coupled system with co-cultivation of Geobacter and Methanosarcina.
Journal of environmental sciences (China)
Oct 23, 2015
The anaerobic digestion (AD) and microbial electrolysis cell (MEC) coupled system has been proved to be a promising process for biomethane production. In this paper, it was found that by co-cultivating Geobacter with Methanosarcina in an AD-MEC coupl...
Meta-tuning and fast optimization of machine learning models for dynamic methane prediction in anaerobic digestion.
Bioresource technology
Sep 1, 2025
This study evaluates the performance of several optimization algorithms for tuning a data preparation and hyperparameter optimization pipeline applied to machine and deep learning models predicting methane production. Bayesian ridge regression and re...
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