Expanding plastics recycling technologies: chemical aspects, technology status and challenges
Less than 10% of the plastics generated globally are recycled, while the rest are incinerated,
accumulated in landfills, or leak into the environment. New technologies are emerging to …
accumulated in landfills, or leak into the environment. New technologies are emerging to …
Toward autonomous laboratories: Convergence of artificial intelligence and experimental automation
The ever-increasing demand for novel materials with superior properties inspires retrofitting
traditional research paradigms in the era of artificial intelligence and automation. An …
traditional research paradigms in the era of artificial intelligence and automation. An …
Computational design and manufacturing of sustainable materials through first-principles and materiomics
Engineered materials are ubiquitous throughout society and are critical to the development
of modern technology, yet many current material systems are inexorably tied to widespread …
of modern technology, yet many current material systems are inexorably tied to widespread …
[HTML][HTML] Optical sensors and machine learning algorithms in sensor-based material flow characterization for mechanical recycling processes: A systematic literature …
Digital technologies hold enormous potential for improving the performance of future-
generation sorting and processing plants; however, this potential remains largely untapped …
generation sorting and processing plants; however, this potential remains largely untapped …
Artificial intelligence–coupled plasmonic infrared sensor for detection of structural protein biomarkers in neurodegenerative diseases
Diagnosis of neurodegenerative disorders (NDDs) including Parkinson's disease and
Alzheimer's disease is challenging owing to the lack of tools to detect preclinical biomarkers …
Alzheimer's disease is challenging owing to the lack of tools to detect preclinical biomarkers …
Machine-learning-based predictions of polymer and postconsumer recycled polymer properties: a comprehensive review
There has been a tremendous increase in demand for virgin and postconsumer recycled
(PCR) polymers due to their wide range of chemical and physical characteristics. Despite …
(PCR) polymers due to their wide range of chemical and physical characteristics. Despite …
[HTML][HTML] Applied machine learning for prediction of waste plastic pyrolysis towards valuable fuel and chemicals production
Pyrolysis is a suitable conversion technology to address the severe ecological and
environmental hurdles caused by waste plastics' ineffective pre-and/or post-user …
environmental hurdles caused by waste plastics' ineffective pre-and/or post-user …
[HTML][HTML] A waste separation system based on sensor technology and deep learning: A simple approach applied to a case study of plastic packaging waste
M Dokl, Y Van Fan, A Vujanović, ZN Pintarič… - Journal of Cleaner …, 2024 - Elsevier
Plastic waste pollution is a challenging and complex issue caused mainly by high
consumption of single-use plastics and the linear economy of “extract-make-use-throw” …
consumption of single-use plastics and the linear economy of “extract-make-use-throw” …
Infrared Spectral Analysis for Prediction of Functional Groups Based on Feature-Aggregated Deep Learning
Infrared (IR) spectroscopy is a powerful and versatile tool for analyzing functional groups in
organic compounds. A complex and time-consuming interpretation of massive unknown …
organic compounds. A complex and time-consuming interpretation of massive unknown …
Combining spectroscopy and machine learning for rapid identification of plastic waste: recent developments and future prospects
J Yang, YP Xu, P Chen, JY Li, D Liu, XL Chu - Journal of Cleaner …, 2023 - Elsevier
Recycling and utilization of plastic waste are receiving more and more attention, and the
combination of spectroscopic techniques and machine learning is expected to solve the …
combination of spectroscopic techniques and machine learning is expected to solve the …