AIMC Topic: Biofuels
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Machine learning-based optimization of biogas and methane yields in UASB reactors for treating domestic wastewater.
Biodegradation
Jun 26, 2025
This study aimed to optimize biogas and methane production from Up-flow anaerobic sludge blanket reactors for treating domestic wastewater using advanced machine learning models-namely, eXtreme Gradient Boosting (XGBoost) and its hybridized form, XGB...
Fully Wearable Devices for Real-Time Health Monitoring and Multimodal Sensing in Nanomedicine Using Multiplexed Green Biofuels.
Nano letters
Jun 9, 2025
Fully wearable devices are crucial for real-time health monitoring, but existing devices often lack stable power, on-site signal processing, and multimodal sensing. To overcome these limitations, we introduce the first self-powered and fully wearable...
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
May 5, 2025
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 ...
ML techniques increasing the power factor of a compression ignition engine that is powered by Annona biodiesel using SATACOM.
Scientific reports
Apr 5, 2025
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
Mar 5, 2025
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.)
Feb 21, 2025
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
Jan 13, 2025
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
Dec 10, 2024
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
Dec 6, 2024
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
Nov 27, 2024
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...
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