Accurate determination of polyethylene (PE) and polypropylene (PP) content in polyolefin blends using machine learning-assisted differential scanning calorimetry (DSC) analysis

Polymer Testing, Год журнала: 2024, Номер 131, С. 108353 - 108353

Опубликована: Янв. 26, 2024

Polyethylene (PE) and polypropylene (PP) are among the most recycled polymers. However, these polymers present similar physicochemical characteristics cross-contamination between them is commonly observed, affecting quality of recyclates. With increasing demand for plastics, understanding composition materials crucial. Numerous techniques have been introduced in literature to determine plastics. An ideal technique should be accessible, cost-efficient, fast, accurate. Differential Scanning Calorimetry (DSC) emerges as a suitable since it analyzes thermal behavior compounds under controlled time temperature conditions, entitling quantitative determination each component, e.g., PE/PP blends. Nevertheless, existing predictive methods lack accuracy estimating blends from DSC analysis this blend affects its overall crystallinity. This study advances state-of-the-art regarding quantification using by implementing non-linear calibration curve correlating evolutions crystallinity with composition. Additionally, machine-learned (ML) model validated, achieving high determination, presenting an mean absolute error low 1.0 wt%. Notably, ML-assisted approach can also quantify content subcategory polymers, enhancing utility.

Язык: Английский

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Occurrence, transport, and toxicity of microplastics in tropical food chains: perspectives view and way forward

Environmental Geochemistry and Health, Год журнала: 2024, Номер 46(3)

Опубликована: Фев. 23, 2024

Язык: Английский

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Environmental resilience through artificial intelligence: innovations in monitoring and management

Environmental Science and Pollution Research, Год журнала: 2024, Номер 31(12), С. 18379 - 18395

Опубликована: Фев. 15, 2024

Язык: Английский

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Recent Developments in Technology for Sorting Plastic for Recycling: The Emergence of Artificial Intelligence and the Rise of the Robots

Recycling, Год журнала: 2024, Номер 9(4), С. 59 - 59

Опубликована: Июль 15, 2024

Plastics recycling is an important component of the circular economy. In mechanical recycling, recovery high-quality plastics for subsequent reprocessing requires plastic waste to be first sorted by type, color, and size. chemical certain types should removed as they negatively affect process. Such sortation objects at Materials Recovery Facilities (MRFs) relies increasingly on automated technology. Critical any sorting proper identification type. Spectroscopy used this end, augmented machine learning (ML) artificial intelligence (AI). Recent developments in application ML/AI are highlighted here, state art presented. Commercial equipment recyclables identified from a survey publicly available information. Automated equipment, ML/AI-based sorters, robotic sorters currently market evaluated regarding their sensors, capability sort plastics, primary application, throughput, accuracy. This information reflects rapid progress achieved plastics. However, film, dark comprising multiple polymers remains challenging. Improvements and/or new solutions forthcoming.

Язык: Английский

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Photocatalytic degradation of drugs and dyes using a maching learning approach

RSC Advances, Год журнала: 2024, Номер 14(13), С. 9003 - 9019

Опубликована: Янв. 1, 2024

The waste management industry uses an increasing number of mathematical prediction models to accurately forecast the behavior organic pollutants during catalytic degradation.

Язык: Английский

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Revolutionizing Urban Solid Waste Management with AI and IoT: A review of smart solutions for waste collection, sorting, and recycling

Results in Engineering, Год журнала: 2025, Номер 25, С. 104018 - 104018

Опубликована: Янв. 12, 2025

Язык: Английский

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Artificial Intelligence In Financial Services: Advancements In Fraud Detection, Risk Management, And Algorithmic Trading Optimization

Опубликована: Янв. 1, 2025

Fraud detection, risk management, and algorithmic trading optimization are being revolutionized by AI in financial services. reduces false positives speeds up fraud detection spotting trends anomalies real time using advanced machine learning techniques. Financial institutions can now fight sophisticated cyber attacks with AI-powered systems that analyze massive databases detect illicit conduct unparalleled accuracy. predictive analytics changing how organizations identify mitigate risks. Institutions predict credit defaults, market swings, operational weaknesses big data AI. Natural language processing (NLP) techniques extracting insights from unstructured sources including regulatory filings news to improve decision-making. Real-time monitoring enable proactive interventions reduce losses assure compliance. is transforming trading, another breakthrough. Advanced models historical live price movements, find arbitrage opportunities, execute trades milliseconds. Reinforcement helping design adaptable algorithms respond changes, increasing profitability reducing risk. also promotes ethical transparent tactics, solving manipulation problems. This study analyses the newest applications services their disruptive influence. Generative AI, federated learning, quantum computing will further transform sector. adoption has many benefits, but privacy, bias, legal complexity must be addressed sustain progress. efficiency, resilience, creativity, creating a future where technology drives trust strategic advantage.

Язык: Английский

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Artificial Intelligence-Driven Customer Service: Enhancing Personalization, Loyalty, And Customer Satisfaction

Опубликована: Янв. 1, 2025

AI-driven customer service is revolutionizing how businesses interact with customers by improving personalization, loyalty, and satisfaction through data-driven insights responsive interactions. AI technologies like machine learning (ML), natural language processing (NLP), generative models allow companies to scale experiences that match individual preferences, behaviors, needs. tools in service, such as chatbots virtual assistants, are response times issue resolution, increasing loyalty. Companies can analyze massive datasets real time using improve profiles predict future systems boost brand loyalty personalizing interactions making feel valued. Additionally, ChatGPT engagement reducing friction providing human-like responses conversational experiences. sentiment analysis help anticipate dissatisfaction assessing emotions feedback. Along AI-based solutions programs them more dynamic engaging. Businesses identify high-value customers, personalize offers, encourage repeat business predictive analytics. Despite these advances, ethical issues data privacy interaction must be addressed. As evolves, balancing automation personalized human crucial. This paper examines current trends, case studies, developments demonstrate transform environments into customer-centric, responsive, adaptable ones foster long-term satisfaction.

Язык: Английский

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Artificial Intelligence In Retail And E-Commerce: Enhancing Customer Experience Through Personalization, Predictive Analytics, And Real-Time Engagement

Опубликована: Янв. 1, 2025

AI is transforming retail and e-commerce with unprecedented personalization, predictive analytics, real-time customer involvement. AI-powered recommendation engines, chatbots, sentiment analysis tools enable customer-centric tactics as consumers want more personalized experiences. AI's capacity to analyze massive volumes of data allows merchants develop shopping experiences that boost pleasure loyalty. For instance, deep learning-based systems accurately predict client preferences, increasing conversion rates average order values. analytics changing inventory management, demand forecasting, pricing in retail. Stock levels, waste, profitability are optimized by machine learning algorithms examine historical sales data, market trends, behavior. Real-time insights dynamic models adjust instantaneously supply changes, maintaining competitiveness fast-paced e-commerce. AI-enabled engagement business-customer interactions. Conversational can answer questions instantly personally smart chatbots voice assistants, improving user experience lowering operational expenses. Visual technologies like image identification augmented reality virtual try-ons visual search, online purchasing. The use has highlighted ethical issues such privacy algorithmic fairness. Growing sustainably requires balancing consumer personalization trust. This paper examines how might improve experience, supported recent breakthroughs industry trends. It shows may purchasing while tackling implementation a digital economy.

Язык: Английский

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Harnessing AI for sustainable higher education: ethical considerations, operational efficiency, and future directions

Discover Sustainability, Год журнала: 2025, Номер 6(1)

Опубликована: Янв. 13, 2025

As higher education faces technological advancement and environmental imperatives, AI becomes a key instrument for revolutionizing instructional methods institutional operations. can improve educational outcomes, resource management, long-term sustainability in education, according to this study. The research uses case studies best practices show how AI-driven innovations minimize impact, enhance energy efficiency, customize learning, creating more sustainable inclusive academic environment. document discusses ethics, including data privacy, algorithmic prejudice, the digital divide. It emphasizes need strong ethical frameworks use ethically make decisions with transparency fairness. study also robust rules infrastructure promote integration, protecting student privacy supporting fair access technologies. shows curriculum-building tools educate students future concerns stimulate innovation. prospects difficulties of are critically examined, its potential change traditional roles, performance, maintain profitability. Actionable recommendations educators, politicians, leaders contribute conversation. Focusing on creates framework where technology stewardship intimately connected, ensuring that institutions prosper fast-changing world.

Язык: Английский

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