AIMC Topic: Biofuels

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An integrated review on the role of different biocatalysts, process parameters, bioreactor technologies and data-driven predictive models for upgrading biogas.

Journal of environmental management
As energy consumption and waste generation from human activities continue to rise, the technology of anaerobic digestion (AD), which converts waste into bioenergy, has gained popularity. Biogas produced from AD commonly contains 60 % CH, 40 % CO and ...

Predicting anaerobic digestion stability in load-flexible operation using gas phase indicators and classification algorithms.

Bioresource technology
This study investigates early warning indicators for process instabilities in anaerobic digestion caused by shock-loadings in biogas plants, focussing on gas-phase parameters to avoid substrate analyses. With the increasing use of renewable energy so...

ML techniques increasing the power factor of a compression ignition engine that is powered by Annona biodiesel using SATACOM.

Scientific reports
The global production of biodiesel in 2023 amounted to 34 billion liters because compression ignition engines need environmentally friendly fuel alternatives. The research investigates Annona biodiesel in combination with machine learning (ML) and ST...

Development of artificial neural network model for anaerobic digestion-elutriated phase treatment.

Journal of environmental management
Nonlinear autoregressive exogenous (NARX) neural network models were used to forecast the time-series profiles of anaerobic digestion-elutriated phase treatment (ADEPT). Experimental data from the operation of the pilot plant and lab-scale reactor we...

A machine learning approach to feature selection and uncertainty analysis for biogas production in wastewater treatment plants.

Waste management (New York, N.Y.)
The growing demand for efficient waste management solutions and renewable energy sources has driven research into predicting biogas production at wastewater treatment plants. This study outlines a methodology starting with data collection from a full...

Graph-based deep learning for predictions on changes in microbiomes and biogas production in anaerobic digestion systems.

Water research
Anaerobic digestion (AD), which relies on a complex microbial consortium for efficient biogas generation, is a promising avenue for renewable energy production and organic waste treatment. However, understanding and optimising AD processes are challe...

Harnessing artificial neural networks to model caffeine degradation by High-Yield biodiesel algae Desmodesmus pannonicus.

Bioresource technology
In this study, Desmodesmus pannonicus IITISM-DIX2, outperforming Chlorella sorokiniana IITISM-DIX3 in caffeine degradation, was used to develop an artificial neural network (ANN) model for predicting caffeine removal efficiency under varying pH, phot...

Recent advances in dark fermentative hydrogen production from vegetable waste: role of inoculum, consolidated bioprocessing, and machine learning.

Environmental science and pollution research international
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...

Harnessing Artificial Intelligence for Sustainable Bioenergy: Revolutionizing Optimization, Waste Reduction, and Environmental Sustainability.

Bioresource technology
Assessing the mutual benefits of artificial intelligence (AI) and bioenergy systems, to promote efficient and sustainable energy production. By addressing issues with conventional bioenergy techniques, it highlights how AI is revolutionising optimisa...

Exploring interactive effects of environmental and microbial factors on food waste anaerobic digestion performance: Interpretable machine learning models.

Bioresource technology
Biogas yield in anaerobic digestion (AD) involves continuous and complex biological reactions. The traditional linear models failed to quantitatively assess the interactive effects of these factors on AD performance. To further explore the internal r...