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Aluminum

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[Migration of Metals Contained in Laminated Films for Food Packaging].

Shokuhin eiseigaku zasshi. Journal of the Food Hygienic Society of Japan
Multilayer laminated films are widely used as food packaging materials. The substances contained in these films have the potential to migrate into food in contact, but the actual situation is unknown. In this study, we first determined the contents o...

Quantifying disorder one atom at a time using an interpretable graph neural network paradigm.

Nature communications
Quantifying the level of atomic disorder within materials is critical to understanding how evolving local structural environments dictate performance and durability. Here, we leverage graph neural networks to define a physically interpretable metric ...

Machine learning-assisted fluorescence visualization for sequential quantitative detection of aluminum and fluoride ions.

Journal of environmental sciences (China)
The presence of aluminum (Al) and fluoride (F) ions in the environment can be harmful to ecosystems and human health, highlighting the need for accurate and efficient monitoring. In this paper, an innovative approach is presented that leverages the p...

Optimizing strength of directly recycled aluminum chip-based parts through a hybrid RSM-GA-ANN approach in sustainable hot forging.

PloS one
Direct recycling of aluminum waste is crucial in sustainable manufacturing to mitigate environmental impact and conserve resources. This work was carried out to study the application of hot press forging (HPF) in recycling AA6061 aluminum chip waste,...

Intelligent algorithms-aided modeling and optimization of the deturbidization of abattoir wastewater by electrocoagulation using aluminium electrodes.

Journal of environmental management
The removal of turbidity from abattoir wastewater (AWW) by electrocoagulation (EC) was modeled and optimized using Artificial Intelligence (AI) algorithms. Artificial neural networks (ANN), adaptive neuro-fuzzy inference systems (ANFIS), particle swa...

Classification of e-waste using machine learning-assisted laser-induced breakdown spectroscopy.

Waste management & research : the journal of the International Solid Wastes and Public Cleansing Association, ISWA
Waste management and the economy are intertwined in various ways. Adopting sustainable waste management techniques can contribute to economic growth and resource conservation. Artificial intelligence (AI)-based classification is very crucial for rapi...

Artificial Intelligence-Assisted Automatic Raman-Activated Cell Sorting (AI-RACS) System for Mining Specific Functional Microorganisms in the Microbiome.

Analytical chemistry
The microbiome represents the natural presence of microorganisms, and exploring, understanding, and leveraging its functions will bring about significant breakthroughs in life sciences and applications. Raman-activated cell sorting (RACS) enables the...

Supervised Machine Learning and Physics Machine Learning approach for prediction of peak temperature distribution in Additive Friction Stir Deposition of Aluminium Alloy.

PloS one
Additive friction stir deposition (AFSD) is a novel solid-state additive manufacturing technique that circumvents issues of porosity, cracking, and properties anisotropy that plague traditional powder bed fusion and directed energy deposition approac...

Rapid and sensitive detection of pharmaceutical pollutants in aquaculture by aluminum foil substrate based SERS method combined with deep learning algorithm.

Analytica chimica acta
BACKGROUND: Pharmaceutical residual such as antibiotics and disinfectants in aquaculture wastewater have significant potential risks for environment and human health. Surface enhanced Raman spectroscopy (SERS) has been widely used for the detection o...

Deep-Learning Potential Molecular Dynamics Study on Nanopolycrystalline Al-Er Alloys: Effects of Er Concentration, Grain Boundary Segregation, and Grain Size on Plastic Deformation.

Journal of chemical information and modeling
Understanding the tensile mechanical properties of Al-Er alloys at the atomic scale is essential, and molecular dynamics (MD) simulations offer valuable insights. However, these simulations are constrained by the unavailability of suitable interatomi...