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61,005 resultsShowing papers similar to Machine Learning-EmpoweredPlastic-Derived PorousCarbons for High-Performance CO2 Capture
ClearMachine Learning-Empowered Plastic-Derived Porous Carbons for High-Performance CO 2 Capture
Machine learning was used to design porous carbon materials derived from waste plastics for use in energy storage and environmental remediation applications. Repurposing plastic waste as functional carbon materials is a promising circular economy strategy that could reduce the volume of plastics entering the environment.
Hydrogen production from plastic waste: A comprehensive simulation and machine learning study
Researchers used computer simulations and machine learning to optimize hydrogen production from polystyrene and polypropylene plastic waste through gasification. They found that increasing the gasification temperature up to 900 degrees Celsius significantly boosted hydrogen output, while higher pressures reduced production. The study demonstrates that converting plastic waste into hydrogen fuel could be an efficient way to address both energy needs and plastic pollution.
Low-cost activated carbon from the pyrolysis of post-consumer plastic waste and the application in CO2 capture
Researchers prepared low-cost activated carbon from char residue generated during the pyrolysis of post-consumer plastic waste and tested its application for CO2 capture. The study demonstrates that plastic waste pyrolysis byproducts can be repurposed into useful porous materials, offering a dual benefit of chemical recycling and carbon capture.
Transforming a mixture of real post-consumer plastic waste into activated carbon for biogas upgrading
Researchers explored converting mixed post-consumer plastic waste into activated carbon through pyrolysis and chemical activation for use in biogas purification. The resulting activated carbon demonstrated effective carbon dioxide adsorption capacity comparable to commercial alternatives. The study suggests that transforming hard-to-recycle plastic waste into useful carbon materials could offer a circular economy solution for both plastic pollution and renewable energy production.
Machine Learning to Predict the Adsorption Capacity of Microplastics
Researchers developed machine learning models to predict the adsorption capacity of microplastics for chemical pollutants, providing a computational tool to better understand how microplastics act as vectors for contaminant dispersal in aquatic environments.
Sustainable Adsorption of Polystyrene Microplastics in Aqueous Media Using PET-C Synthesized from Plastic Waste: DFT and Experimental Studies
Researchers converted PET plastic waste into activated carbon (PET-C) via direct carbonisation and KOH activation, then tested it for adsorbing polystyrene microplastics. PET-C achieved a maximum adsorption capacity of 139.57 mg/g via monolayer chemical adsorption, demonstrating a circular approach to using plastic waste to remove plastic pollution.
The state-of-the-art review on biochar as green additives in cementitious composites: performance, applications, machine learning predictions, and environmental and economic implications
Researchers reviewed how biochar — a carbon-rich material made by heating biomass — can be added to cement to reduce carbon emissions and improve building material performance, while also examining how machine learning models can predict composite properties and support more sustainable construction practices.
Recent Advances in Polymeric Systems for CO2 Capture: A Small Catalogue
This review surveys advances in polymer-based materials for capturing carbon dioxide as part of climate change mitigation. Polymer science advances relevant to CO2 capture are also applicable to developing materials that can remove microplastics from water and air.
Versatile in silico modelling of microplastics adsorption capacity in aqueous environment based on molecular descriptor and machine learning
Researchers developed machine learning models using molecular descriptors to predict the adsorption capacity of microplastics for organic pollutants in aqueous environments, achieving high accuracy across multiple polymer types and enabling faster environmental risk assessment.
Pollutants to Products: A Tailored Multicomponent Photocatalyst for Simultaneous CO 2 and Plastic Waste Conversion
Researchers developed a photocatalyst that simultaneously converts CO2 and PET plastic waste into useful chemicals (CO, methane, ethylene glycol) using only light, with CO2 reduced at over 95% selectivity. The dual-use design eliminates the need for chemical sacrificial agents by using plastic as the electron donor for CO2 reduction. Beyond plastic recycling, the system also suggests a pathway for degrading microplastics, offering a single solar-driven process that tackles two major pollution problems at once.
Rapidly Predicting Aqueous Adsorption Constants of Organic Pollutants onto Polyethylene Microplastics by Combining Molecular Dynamics Simulations and Machine Learning
Researchers developed a computational method combining molecular simulations with machine learning to rapidly predict how organic pollutants adsorb onto polyethylene microplastics in water. The approach accurately predicted adsorption behavior across different conditions including particle size, water salinity, and pH without requiring time-consuming laboratory experiments. The tool could help environmental scientists more quickly assess how microplastics interact with and transport chemical contaminants in aquatic environments.
Elucidating the impacts of microplastics on soil greenhouse gas emissions through automatic machine learning frameworks
Researchers used machine learning frameworks to model how microplastics in soil affect greenhouse gas emissions, including carbon dioxide, methane, and nitrous oxide. They found that the type of microplastic significantly influenced CO2 emissions, with biodegradable plastics like polyamide leading to higher levels that worsened with environmental aging. The study suggests that microplastic contamination in agricultural soils could have meaningful implications for climate-related greenhouse gas output.
Application of machine learning and statistical approaches for optimization of heavy metals (Cd2+, Pb2+, Cu2+, and Zn2+) adsorption onto carbonized char prepared from PET plastic bottle waste
This is not directly about microplastic pollution risks — it is a materials and environmental engineering study using carbonized char made from PET plastic bottle waste as an adsorbent to remove heavy metals (cadmium, lead, copper, zinc) from water, focusing on optimizing adsorption performance.
Addressing plastic pollution: A 3D-printed porous PAC scaffold for effective nanoplastic removal
Researchers used 3D printing to fabricate porous activated carbon scaffolds and demonstrated they effectively adsorb multiple types of nanoplastics — including polystyrene, PET, polypropylene, and PVC — from freshwater samples through a combination of pore-filling and chemical interactions, with stable performance across varied environmental conditions.
Predictive modeling of microplastic adsorption in aquatic environments using advanced machine learning models
Scientists used advanced machine learning models to predict how microplastics interact with and absorb organic pollutants in water. The results showed that microplastics with certain chemical properties attract more toxic compounds, which matters because contaminated microplastics in waterways can concentrate harmful chemicals that may eventually reach humans through drinking water and seafood.
Upcycling of polyethylene to gasoline through a self-supplied hydrogen strategy in a layered self-pillared zeolite
Researchers developed a special zeolite material (a porous mineral catalyst) that converts polyethylene plastic waste into high-quality gasoline with over 80% yield, without needing expensive metals or added hydrogen. This breakthrough offers a practical pathway for recycling one of the most common plastics into usable fuel, potentially reducing plastic waste and reliance on fossil fuel extraction.
Developing Bioderived CO2-Responsive Polymers as Alternatives to Petroleum-derived Polymers
Researchers examined the development of bioderived, CO2-responsive polymers as sustainable alternatives to petroleum-derived plastics, using life cycle assessment principles and green chemistry frameworks to guide material design. The work addresses the environmental harms of petroleum-based plastic production and low recycling rates, proposing bio-based responsive polymers as a route toward materials with reduced environmental impact across their full lifecycle.
Plastic regulates its co-pyrolysis process with biomass: Influencing factors, model calculations, and mechanisms
Researchers investigated co-pyrolysis of plastics and biomass, finding that varying the hydrogen-to-carbon ratio of biomass feedstocks influences synergistic effects on bio-oil quality, offering a strategy to improve plastic waste valorization.
Adsorption of acid and basic dye from the simulated wastewater using carbonized microplastic particles synthesized from recycled polyethylene terephthalate plastic waste bottles: an integrated approach for experimental and practical applications
Researchers carbonized waste PET plastic bottles to create microplastic-like adsorbent particles and demonstrated their effectiveness in removing over 99% of methylene blue and methyl orange dyes from simulated wastewater, with adsorption optimized by response surface methodology and confirmed as exothermic, spontaneous, and applicable to real wastewater.
Recycling Carbon Resources from Waste PET to Reduce Carbon Dioxide Emission: Carbonization Technology Review and Perspective
This review summarized carbonization technologies for converting waste PET plastic into valuable carbon materials, offering a strategy to reduce carbon dioxide emissions while recycling plastic resources in alignment with carbon neutrality goals.
Hydrothermal carbonization of plastic waste: A review of its potential in alternative energy applications
Researchers reviewed how hydrothermal carbonization — a process that converts materials into a coal-like substance using heat and water under pressure — can transform plastic waste into useful products like solid fuels, catalysts, and materials for energy storage devices. While the technology is promising, challenges like variable plastic feedstock quality and scaling up production must be addressed before widespread commercial use.
Lightweight Carbon Foam obtained from post-use Polyehylene Terephthalate bottles and potential applications
Researchers developed a lightweight carbon foam from post-consumer PET bottles through carbonization, demonstrating a viable way to upcycle plastic waste into a valuable material with potential applications in filtration and thermal insulation.
Upcycling Plastic Waste into High Value‐Added Carbonaceous Materials
This review examines methods for converting plastic waste into high-value carbonaceous materials through upcycling techniques. Researchers surveyed approaches for transforming discarded plastics into products such as carbon fibres, water purification absorbents, and energy storage electrodes. The study suggests that upcycling plastic waste into carbon-based materials offers a practical alternative to conventional disposal methods like landfilling and incineration.
Insights into using plastic waste to produce activated carbons for wastewater treatment applications: A review
This review explores the potential of converting plastic waste into activated carbon, a material widely used to filter pollutants from water. Researchers found that various plastics including polyethylene, polystyrene, and PET can be transformed into effective adsorbents through controlled heating processes. The approach offers a promising way to simultaneously address plastic waste accumulation and water pollution challenges.