State-of-the-art review on various applications of machine learning techniques in materials science and engineering DOI
Bing Yu, Lai‐Chang Zhang, Xiaoxia Ye

et al.

Chemical Engineering Science, Journal Year: 2024, Volume and Issue: unknown, P. 121147 - 121147

Published: Dec. 1, 2024

Language: Английский

SDUST2023BCO: a global seafloor model determined from a multi-layer perceptron neural network using multi-source differential marine geodetic data DOI Creative Commons
Shuai Zhou, Jinyun Guo, Huiying Zhang

et al.

Earth system science data, Journal Year: 2025, Volume and Issue: 17(1), P. 165 - 179

Published: Jan. 20, 2025

Abstract. Seafloor topography, as a fundamental marine spatial geographic information, plays vital role in observation and science research. With the growing demand for high-precision bathymetric models, multi-layer perceptron (MLP) neural network is used to integrate multi-source geodetic data this paper. A new model of global ocean, spanning 180° E–180° W 80° S–80° N, known Shandong University Science Technology 2023 Bathymetric Chart Oceans (SDUST2023BCO), has been constructed, with grid size 1′ × 1′. The include gravity anomaly released by Technology, vertical gradient deflection Scripps Institution Oceanography (SIO), mean dynamic topography Centre National d'Etudes Spatiales (CNES). First, input output are organized from train MLP model. Second, at interesting points fed into obtain prediction bathymetry. Finally, resolution constructed area. validity reliability SDUST2023BCO evaluated comparing shipborne single-beam GEBCO_2023 topo_25.1 models. results demonstrate that accurate reliable, effectively capturing reflecting information. available https://doi.org/10.5281/zenodo.13341896 (Zhou et al., 2024).

Language: Английский

Citations

2

Artificial intelligence in microplastic detection and pollution control DOI
Jin Hui,

Fanhao Kong,

Xiangyu Li

et al.

Environmental Research, Journal Year: 2024, Volume and Issue: 262, P. 119812 - 119812

Published: Aug. 16, 2024

Language: Английский

Citations

13

Research on the Migration and Adsorption Mechanism Applied to Microplastics in Porous Media: A Review DOI Creative Commons

Lin Zeng,

Yuan Cong,

Taoyu Xiang

et al.

Nanomaterials, Journal Year: 2024, Volume and Issue: 14(12), P. 1060 - 1060

Published: June 20, 2024

In recent years, microplastics (MPs) have emerged as a significant environmental pollutant, garnering substantial attention for their migration and transformation behaviors in natural environments. MPs frequently infiltrate porous media such soil, sediment, rock through various pathways, posing potential threats to ecological systems human health. Consequently, the adsorption mechanisms applied been extensively studied. This paper aims elucidate of influencing factors systematic review. The review encompasses characteristics MPs, physical properties media, hydrodynamic factors. Additionally, further clarifies provide theoretical support understanding behavior fate. Furthermore, current mainstream detection techniques are reviewed, with an analysis advantages, disadvantages, applications each technique. Finally, identifies limitations shortcomings research envisions future directions.

Language: Английский

Citations

6

Analysis of microplastics in the estuary lying along the coastal belt of the Arabian Sea DOI Creative Commons

Megha Sunil,

N Mithun,

Guruprasad Kalthur

et al.

Case Studies in Chemical and Environmental Engineering, Journal Year: 2024, Volume and Issue: 10, P. 100804 - 100804

Published: June 24, 2024

The significant impact of microplastics in the marine environment has sparked global concern. These tiny plastic particles travel from land to estuary through rivers, where they become intricately distributed within estuarine dynamics. spatial distribution debris and sedimentation is mainly influenced by dynamics estuary, posing a scientific challenge that demands immediate attention. main objective this study analyse microplastic contamination water samples collected Azhikkal Kannur, India, subsequent establishment seaport region, using home assembled micro-Raman spectrometer. This research sheds light on extensive prevalence detected vicinity estuary's entrance, with specific focus consequences construction surrounding region. Within surveyed considerable quantity 1260 1480 anthropogenic were identified. predominant varieties observed particular area consist polystyrene (38%), polysulfone (5%), polypropylene (1%), polyethylene terephthalate (1%). discovered region consisted fragments (82%) fibers (15%), varying sizes 10 100 μm (36%), resulting higher surface volume ratio. existence red blue pigments, such as copper phthalocyanine indigo blue, pollution causing alarm over potential harmful organisms rely these ecosystems. identification pigments aquatic environments across entire nation not been adequately pursued. Additionally, delves into spread murky setting, considering sea wind alterations buoyancy following formation biofilm their surface. leads acquiring hydrophilic characteristics turbid environment.

Language: Английский

Citations

6

SDUST2023BCO: a global seafloor model determined from multi-layer perceptron neural network using multi-source differential marine geodetic data DOI Creative Commons
Shuai Zhou, Jinyun Guo, Huiying Zhang

et al.

Published: Aug. 28, 2024

Abstract. Seafloor topography, as a fundamental marine spatial geographic information, plays vital role in observation and science research. With the growing demand for high-precision bathymetric models, Multi-layer Perceptron (MLP) neural network is used to integrate multi-source geodetic data this paper. A new model of global ocean, spanning 0°–360° E 80° S–80° N, has been constructed, known Shandong University Science Technology 2023 Bathymetric Chart Oceans (SDUST2023BCO), with grid size 1′×1′. The differential include gravity anomaly released by Technology, vertical gradient deflection Scripps Institution Oceanography, well mean dynamic topography Centre National d’Etudes Spatiales. First, input output are organized from train MLP model. Second, at interesting points fed into obtain prediction bathymetry points. Finally, resolution 1′×1′ constructed area. accuracy evaluated comparing single-beam shipborne data, GEBCO_2023 topo_25.1 models. results demonstrate that SDUST2023BCO accurate reliable, effectively capturing reflecting ocean information. available https://doi.org/10.5281/zenodo.13341896 (Zhou et al., 2024).

Language: Английский

Citations

4

Predictive modeling of microplastic adsorption in aquatic environments using advanced machine learning models DOI
Seyed Hamed Godasiaei

The Science of The Total Environment, Journal Year: 2024, Volume and Issue: 958, P. 178015 - 178015

Published: Dec. 14, 2024

Language: Английский

Citations

4

Raman spectroscopy integrated with machine learning techniques to improve industrial sorting of Waste Electric and Electronic Equipment (WEEE) plastics DOI Creative Commons
Ainara Pocheville, Iratxe Uria,

Paule España

et al.

Journal of Environmental Management, Journal Year: 2025, Volume and Issue: 373, P. 123897 - 123897

Published: Jan. 1, 2025

Current industrial separation and sorting technologies struggle to efficiently identify classify a large part of Waste Electric Electronic Equipment (WEEE) plastics due their high content certain additives. In this study, Raman spectroscopy in combination with machine learning methods was assessed develop classification models that could improve the identification Polystyrene (PS), Acrylonitrile Butadiene Styrene (ABS), Polycarbonate (PC) blend PC/ABS contained WEEE streams, including black plastics, increase recycling rate, enhance circularity. spectral analysis carried out two lasers different excitation wavelengths (785 nm 1064 nm) varying setting parameters (laser power, integration time, focus distance) aim at reducing fluorescence. data were used train test Discriminant Analysis (DA) Support Vector Machine (SVM) algorithms an iterative procedure assess performance identifying classifying real plastics. settings optimized considering industry requirements, such as process productivity (classification short measuring time for fast identification) product quality (purity sorted polymers). Classification trained, first approach, only on target plastics; second all polymers expected stream, leading realistic overview potential scalability advanced limitations. The best models, based DA obtained laser 500 mW 1.0 s, led PS ABS purity up 80 %.

Language: Английский

Citations

0

Community-based adaptation strategies for marine microplastic management DOI
Nova Ulhasanah, Mega Mutiara Sari, Ariyanti Sarwono

et al.

Regional Studies in Marine Science, Journal Year: 2025, Volume and Issue: unknown, P. 104015 - 104015

Published: Jan. 1, 2025

Language: Английский

Citations

0

Integrating Microplastic Research in Sustainable Agriculture: Challenges and Future Directions for Food Production DOI Creative Commons
Marcelo Illanes, María Toro, Mauricio Schoebitz

et al.

Current Plant Biology, Journal Year: 2025, Volume and Issue: 42, P. 100458 - 100458

Published: Feb. 5, 2025

Language: Английский

Citations

0

Automatic microplastic classification using dual-modality spectral and image data for enhanced accuracy DOI
Arsanchai Sukkuea,

Jakkaphong Inpun,

Phaothep Cherdsukjai

et al.

Marine Pollution Bulletin, Journal Year: 2025, Volume and Issue: 213, P. 117665 - 117665

Published: Feb. 17, 2025

Language: Английский

Citations

0