AIMC Topic: Carbon
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Machine learning-assisted prediction of engineered carbon systems' capacity to treat textile dyeing wastewater via adsorption technology.
Environmental monitoring and assessment
Feb 1, 2025
Dyes are widely used in industries like printing, cosmetics, paper, leather processing, textiles, and manufacturing to add color to products. However, improper disposal of dyes into wastewater has raised major concerns due to their harmful effects on...
Machine Learning-Assisted Biomass-Derived Carbon Dots as Fluorescent Sensor Array for Discrimination of Warfarin and Its Metabolites.
Langmuir : the ACS journal of surfaces and colloids
Jan 11, 2025
Warfarin (WAR), an effective oral anticoagulant, is of utmost importance in treating many diseases. Despite its significance, rapid and precise discrimination of WAR remains a formidable challenge, especially facing its structural analogs of metaboli...
Exploring spatio-temporal heterogeneity of rural settlement patterns on carbon emission across more than 2800 Chinese counties using multiple supervised machine learning models.
Journal of environmental management
Jan 4, 2025
China, the world's largest carbon emitter, plays a pivotal role in achieving carbon neutrality. This study systematically analyzes the impact of landscape indices on carbon emissions from rural settlements across more than 2800 counties using eight s...
Optimization of carbon footprint management model of electric power enterprises based on artificial intelligence.
PloS one
Jan 3, 2025
This study intends to optimize the carbon footprint management model of power enterprises through artificial intelligence (AI) technology to help the scientific formulation of carbon emission reduction strategies. Firstly, a carbon footprint calculat...
An explainable machine learning system for efficient use of waste glasses in durable concrete to maximise carbon credits towards net zero emissions.
Waste management (New York, N.Y.)
Dec 31, 2024
Recycling waste glass (WG) can be time-consuming, costly, and impractical. However, its incorporation into concrete significantly reduces environmental impact and carbon emissions. This paper introduces machine learning (ML) to civil engineering to o...
Achieving pollution abatement and carbon reduction synergistically: How can industrial robots play a role?
Journal of environmental management
Dec 24, 2024
Intelligent manufacturing and green development are pivotal issues in China's pursuit of high-quality economic growth. As the core carrier of artificial intelligence-driven production transformations, industrial robots' role in synergizing enterprise...
Preparation, characterization, and protective effects of carbon dots against oxidative damage induced by LPS in IPEC-J2 cells.
Frontiers in cellular and infection microbiology
Dec 18, 2024
This study aimed to prepare carbon dots (GF-CDs) and examine their efficacy in mitigating oxidative stress and apoptosis in intestinal porcine epithelial cells from the jejunum (IPEC-J2 cells) induced by lipopolysaccharide (LPS). The GF-CDs were syn...
Optimizing carbon source addition to control surplus sludge yield via machine learning-based interpretable ensemble model.
Environmental research
Dec 17, 2024
Appropriate carbon source addition can save operational costs and reduce surplus sludge yield in the wastewater treatment plant (WWTP). However, the link between carbon source and surplus sludge yield remains neglected although machine learning (ML) ...
Technological innovations fuel carbon prices and transform environmental management across Europe.
Journal of environmental management
Dec 17, 2024
This study investigates the impact of recent Artificial Intelligence (AI)-driven technological innovations on carbon prices across different quantiles, assessing the influence of AI stock prices on energy prices based on European carbon allowances wh...
Public health perspectives on green efficiency through smart cities, artificial intelligence for healthcare and low carbon building materials.
Frontiers in public health
Dec 16, 2024
INTRODUCTION: Smart cities, artificial intelligence (AI) in healthcare, and low-carbon building materials are pivotal to public health, environmental sustainability, and green efficiency. Despite their critical importance, understanding public percep...
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