AIMC Topic: Aluminum

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

PloS one Apr 4, 2025
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...
Friction Temperature Aluminum Supervised Machine Learning Alloys Machine Learning Algorithms Neural Networks, Computer
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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 Mar 14, 2025
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...
Aluminum Nanostructures Particle Size Alloys Density Functional Theory Deep Learning Molecular Dynamics Simulation
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Artificial Intelligence-Assisted Automatic Raman-Activated Cell Sorting (AI-RACS) System for Mining Specific Functional Microorganisms in the Microbiome.

Analytical chemistry Nov 11, 2024
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...
Single-Cell Analysis Bacteria Artificial Intelligence Aluminum Microbiota Spectrum Analysis, Raman Soil Microbiology Optical Tweezers
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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 May 9, 2024
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...
Electronic Waste Spectrum Analysis Lasers Waste Management Alloys Aluminum Principal Component Analysis Machine Learning
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Optimizing strength of directly recycled aluminum chip-based parts through a hybrid RSM-GA-ANN approach in sustainable hot forging.

PloS one Mar 14, 2024
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,...
Neural Networks, Computer Aluminum Software Cold Temperature Temperature
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Machine learning-assisted fluorescence visualization for sequential quantitative detection of aluminum and fluoride ions.

Journal of environmental sciences (China) Jan 30, 2024
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...
Fluorides Water Pollutants, Chemical Environmental Monitoring Aluminum Machine Learning Fluorescence
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Intelligent algorithms-aided modeling and optimization of the deturbidization of abattoir wastewater by electrocoagulation using aluminium electrodes.

Journal of environmental management Jan 29, 2024
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...
Fuzzy Logic Electrodes Abattoirs Electrocoagulation Algorithms Aluminum Artificial Intelligence Wastewater
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Quantifying disorder one atom at a time using an interpretable graph neural network paradigm.

Nature communications Jul 7, 2023
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 ...
Aluminum Time Neural Networks, Computer
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Laser ultrasonic imaging of complex defects with full-matrix capture and deep-learning extraction.

Ultrasonics Dec 20, 2022
Phased array-based full-matrix ultrasonic imaging has been the golden standard for the non-destructive evaluation of critical components. However, the piezoelectric phased array cannot be applied in hazardous environments and online monitoring due to...
Proof of Concept Study Deep Learning Lasers Aluminum Ultrasonics
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Effect of dual-convolutional neural network model fusion for Aluminum profile surface defects classification and recognition.

Mathematical biosciences and engineering : MBE Nov 25, 2021
Classifying and identifying surface defects is essential during the production and use of aluminum profiles. Recently, the dual-convolutional neural network(CNN) model fusion framework has shown promising performance for defects classification and re...
Aluminum Neural Networks, Computer Wavelet Analysis
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