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61,005 resultsShowing papers similar to Learning from Nature to Achieve Material Sustainability: Generative AI for Rigorous Bio-inspired Materials Design
ClearA Review on Replacing Food Packaging Plastics with Nature-Inspired Bio-Based Materials
Researchers reviewed bio-based materials inspired by nature as sustainable alternatives to petroleum-based food packaging plastics. The study highlights that while conventional plastic packaging is effective for food preservation, its environmental impact has driven research into biodegradable and compostable alternatives that could reduce plastic waste and microplastic generation.
Machine intelligence-accelerated discovery of all-natural plastic substitutes
Researchers combined robotics and machine learning to rapidly discover biodegradable plastic substitutes made entirely from natural ingredients, using an automated system to test 286 material combinations and build a predictive model that can design new materials to order. This approach dramatically speeds up the search for alternatives to petroleum-based plastics that contribute to microplastic pollution.
Impacto en la salud causado por los nanoplásticos contenidos en alimentos y su posible atenuación mediante un proceso de bioingeniería
This review examines the health impacts of nanoplastics found in food, tracing their origins to the indiscriminate disposal of synthetic, non-biodegradable materials into waterways and land. Researchers discuss how plastics containing toxic chemical additives break down into increasingly smaller particles that contaminate the food supply. The study explores potential bioengineering approaches that could help mitigate nanoplastic contamination in food products.
Using artificial intelligence to rapidly identify microplastics pollution and predict microplastics environmental behaviors
This review summarizes how artificial intelligence and machine learning are being used to identify, track, and predict the environmental behavior of microplastics in soil and water. AI methods can analyze the chemical composition, shape, and distribution of microplastics faster and more accurately than traditional techniques. The technology could help scientists better understand where microplastics accumulate and what risks they pose to ecosystems and human health.
Design of new biopolymers for biomedicine and food-packaging
Researchers review new biopolymer designs intended for biomedical and food packaging applications, aiming to replace fossil-fuel-based plastics with biodegradable alternatives from renewable sources. Widespread adoption of such materials could significantly reduce long-term microplastic pollution.
The Role of Artificial Intelligence in Microplastic Pollution Studies and Management
This review explores how artificial intelligence is transforming microplastic research, from automating detection in microscopy images and spectral analysis to predicting how plastics interact with pollutants and living organisms. AI-powered sensors and real-time monitoring systems are also being integrated into wastewater treatment to reduce microplastic release, making the technology a powerful tool for both understanding and managing plastic pollution.
Microplastics in ecosystems: ecotoxicological threats and strategies for mitigation and governance
This review provides a broad assessment of microplastic pollution across ecosystems, covering sources, detection methods, ecological impacts, and cleanup strategies. The study highlights recent advances including AI-enhanced detection tools and microbe-based degradation approaches, and proposes a roadmap for working toward microplastic-free environments through coordinated scientific and policy action.
Integrating artificial intelligence with microbial biotechnology for sustainable environmental remediation
This review examines how artificial intelligence is being combined with microbial biotechnology to improve the detection and breakdown of persistent environmental pollutants including microplastics. Researchers found that AI models achieve over 90 percent accuracy in classifying microplastics and have helped design enzymes that degrade PET plastic up to 46 times faster than conventional approaches. The integration of AI with biotechnology represents a significant advance in developing sustainable pollution remediation strategies.
Sustainable Materials and Technologies for Biomedical Applications
This review covers sustainable biomaterials for medical implants, including 3D-printed devices made from biopolymers, ceramics, and composites. While not directly about microplastics, it is relevant because developing biodegradable alternatives to traditional plastics in medical devices could reduce the amount of plastic waste that eventually breaks down into microplastics. The research highlights how sustainable manufacturing could help address plastic pollution at its source.
Leveraging Artificial Intelligence for Accelerated Polymer Synthesis and Design
This review examines AI-enabled advances in polymer informatics, focusing on machine learning and deep learning approaches for accelerating the design of application-specific polymeric materials across energy storage, production, and sustainable economy applications including recyclable and biodegradable polymers. The review highlights how AI-powered workflows are shortening the design-to-discovery cycle for next-generation polymer materials.
Polymer engineering at the nexus of additive manufacturing, artificial intelligence, and responsible innovation
This perspective piece is not primarily a microplastics research paper; it broadly discusses the intersection of 3D printing, artificial intelligence, and sustainable polymer engineering, mentioning microplastics only peripherally in the context of material design challenges.
Micro- and Nano-Plastics Contaminants in the Environment: Sources, Fate, Toxicity, Detection, Remediation, and Sustainable Perspectives
This review provides a broad overview of micro- and nanoplastic pollution, covering where these particles come from, how they spread through the environment, and the damage they cause to living things including humans. The authors also compare different methods for removing microplastics from the environment, including physical, chemical, and biological approaches. The paper calls for more research and global cooperation to develop better tools for measuring the health risks of plastic pollution.
Understanding microplastic pollution: Tracing the footprints and eco-friendly solutions
This review covers the sources, health impacts, detection methods, and biological removal strategies for microplastic pollution. Biological approaches using algae, bacteria, and fungi show promise for breaking down microplastics in wastewater treatment plants, which could help reduce the amount of these particles that ultimately reach humans through contaminated water and food.
Advances in microplastic mitigation: current progress and future directions
This review synthesizes recent advances in biotechnology-based approaches to microplastic remediation, including microbial degradation, engineered enzyme systems, and AI-driven monitoring. Researchers found that while promising enzymes and engineered biofilm systems have been demonstrated in the lab, translating these solutions to diverse polymer types and real-world field applications remains a major challenge. The study proposes a unified roadmap for scaling sustainable biotechnology solutions to address the global microplastic crisis.
Integrating Genomic and Proteomic Data Using Machine Learning for Plastic Biodegradation: A Systematic Review
This systematic review summarizes how machine learning and genomic data are being used to identify microbes and enzymes that can break down plastic waste. The research is significant for microplastic concerns because discovering more effective biological degradation pathways could provide a natural solution for reducing the microplastic pollution that accumulates in our environment and bodies.
Evaluating the Environmental and Health Impacts of Disposable Plastics: Toward Sustainable Material Alternatives
This review synthesized evidence on the environmental and health impacts of disposable plastics, drawing on environmental science, health studies, and sustainability literature. The paper examined how plastic waste drives ocean pollution and wildlife harm while exploring sustainable alternative materials and policies.
Alleviating Health Risks for Water Safety: A Systematic Review on Artificial Intelligence-Assisted Modelling of Proximity-Dependent Emerging Pollutants in Aquatic Systems
This systematic review summarizes how artificial intelligence can help track emerging pollutants, including microplastics, in water systems. It highlights that AI-driven models can predict contamination patterns more efficiently than traditional methods, which could help protect drinking water safety and public health.
An integrated chemical engineering approach to understanding microplastics
Researchers proposed an integrated chemical engineering approach combining artificial intelligence, theoretical methods, and experimental techniques to better understand microplastic properties and behavior. The study suggests that the broad scope of chemical engineering makes it well-suited for characterizing microplastics and addressing the complexity of their environmental and health effects.
Exploring microplastic pollution from origin to environmental impact and remediation approaches
This review provides a comprehensive assessment of microplastic pollution, covering their sources from synthetic textiles, cosmetics, and packaging to their fate in aquatic and terrestrial ecosystems. The study critically examines detection techniques, structural and chemical classification methods, and the health risks microplastics pose to organisms including humans.
Artificial intelligence in microplastics domain: Current progress, challenges, and sustainable prospects
This critical review assesses how artificial intelligence tools—including machine learning and image recognition—are being applied to detect, characterize, and predict the behavior of microplastics in the environment. AI approaches show promise for overcoming persistent bottlenecks in large-scale microplastic analysis, but the authors highlight challenges around data quality, model interpretability, and standardization that must be addressed for these tools to reach their potential.
Recent Advances in Microplastic Pollution for its Sustainable Management
This review covers the many sources of microplastic pollution -- from industrial waste and textiles to agricultural runoff -- and evaluates current strategies for managing the problem. The authors discuss both prevention approaches like biodegradable alternatives and cleanup technologies, emphasizing that microplastics pose health risks to humans through contaminated water, food, and air.
AI, Fashion, and Climate Conscious Consumers Promoting Sustainable Consumption Through Intelligent System
This research review explains how artificial intelligence (AI) could help reduce fashion's harmful impact on the environment, including cutting down on microplastic pollution that can affect human health. AI tools can help shoppers make better choices by showing which clothes are made sustainably and last longer, potentially reducing the tiny plastic fibers that shed from synthetic clothes into water and air. However, the authors warn that AI must be used responsibly to truly help the environment rather than just appearing to do so.
Recent innovations in the developments of biopolymer-based materials for the removal of micro- and nanoplastics: A review of performance, critical factors, practicability and knowledge gaps
A review of recent innovations in biopolymer-based materials for various applications assessed how bio-derived polymers are being developed to reduce reliance on fossil-fuel plastics. The transition to biopolymers is relevant to reducing the long-term sources of microplastic pollution.
From Harm to Hope: Tackling Microplastics’ Perils with Recycling Innovation
This review examines how plastics break down into microplastics, nanoplastics, and persistent organic pollutants that contaminate the environment and enter the human food chain. Researchers call for new biomarkers to track human exposure and improved methods for detecting these tiny particles in food and the environment. The study emphasizes the need for better recycling practices and adherence to reduce-reuse-recycle strategies to address the growing health and environmental risks of plastic pollution.