AIMC Topic: Materials Testing

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Estimation of compressive strength of ultra-high performance lightweight concrete (UHPLC) using neural network.

PloS one Jul 7, 2025
High strength and lightweight are key trends in concrete development. Achieving a balance between these properties to produce high structural efficiency (strength-to-weight ratio) concrete is challenging due to the complex relationship between compre...
Coal Ash Materials Testing Neural Networks, Computer Sand Construction Materials Compressive Strength
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An enhanced UHMWPE wear particle detection approach based on YOLOv9.

Medical engineering & physics Jun 6, 2025
Ultra-high molecular weight polyethylene (UHMWPE) has been widely used in total joint arthroplasty for orthopedic and spinal implants. However, the biological response to UHMWPE wear particles has been identified as a major contributor to inflammator...
Image Processing, Computer-Assisted Materials Testing Polyethylenes Deep Learning
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Optimization of hemocompatibility metrics in ventricular assist device design using machine learning and CFD-based response surface analysis.

The International journal of artificial organs Jun 6, 2025
Ventricular assist devices (VADs) are essential for end-stage heart failure patients, but their design must balance hydraulic efficiency and hemocompatibility to minimize blood damage. This study presents a multi-objective optimization framework inte...
Materials Testing Heart-Assist Devices Stress, Mechanical Prosthesis Design Heart Failure Models, Cardiovascular Platelet Activation Hemolysis Hydrodynamics Humans Computer Simulation Bayes Theorem Machine Learning
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A machine learning model exploring creep performance of dental composites.

Dental materials : official publication of the Academy of Dental Materials Jun 3, 2025
OBJECTIVES: Viscoelastic creep behaviour of RBCs determines their dimensional stability and thus contributes to their clinical performance. However, due to complex material compositional variations and differing testing protocols, comparing and analy...
Machine Learning Elasticity Composite Resins Viscosity Materials Testing Dental Materials
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Predicting the tensile properties of heat treated and non-heat treated LPBFed AlSi10Mg alloy using machine learning regression algorithms.

PloS one Jun 2, 2025
In this study, the ability of machine learning algorithms to predict tensile properties of both heat-treated and non-heat treated LPBFed AlSi10Mg alloy is investigated. The data was analyzed using various Machine Learning Regression (MLR) models such...
Alloys Hot Temperature Tensile Strength Magnesium Materials Testing Machine Learning Algorithms
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Performance evaluation of machine learning techniques in surface morphology and corrosion prediction for A286 3D printed micro-lattice structures.

PloS one May 7, 2025
The development of lightweight, corrosion-resistant metallic lattice structures has gained significant attention in aerospace, defense, and structural applications, where material durability and weight optimization are critical. This study investigat...
Machine Learning Surface Properties Steel Corrosion Printing, Three-Dimensional Materials Testing
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Machine learning-assisted strategies to enhance the mechanical properties of PVA hydrogels.

Journal of the mechanical behavior of biomedical materials Apr 19, 2025
Polyvinyl alcohol (PVA) hydrogels have garnered increasing interest in the field of biomedical materials due to their excellent biocompatibility and controllable mechanical properties. Although various preparation strategies such as freeze-thaw cycle...
Hydrogels Polyvinyl Alcohol Mechanical Phenomena Machine Learning Materials Testing
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The influence of different factors on the bond strength of lithium disilicate-reinforced glass-ceramics to Resin: a machine learning analysis.

BMC oral health Feb 18, 2025
BACKGROUND: To assess the influence of various factors on the bond strength of glass-based ceramics and develop a model that can predict the bond strength values using machine learning (ML).
Dental Bonding Dental Porcelain Machine Learning Humans Resin Cements Materials Testing Ceramics
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Harnessing machine learning algorithms for the prediction and optimization of various properties of polylactic acid in biomedical use: a comprehensive review.

Biomedical materials (Bristol, England) Jan 22, 2025
Machine learning (ML) has emerged as a transformative tool in various industries, driving advancements in key tasks like classification, regression, and clustering. In the field of chemical engineering, particularly in the creation of biomedical devi...
Polymers Materials Testing Polyesters Tissue Engineering Biocompatible Materials Algorithms Drug Delivery Systems Humans Biomedical Engineering Machine Learning
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Development of hybrid bionanocomposites of poly(3-hydroxybutyrate-co-3-hydroxyvalerate) with zinc oxide and silicon-doped hydroxyapatite nanocrystals and machine learning for predicting dynamic mechanical properties.

International journal of biological macromolecules Dec 30, 2024
The development of hybrid materials that integrate bioactive and antimicrobial properties within a biodegradable and biocompatible polymer matrix is a key focus in current biomedical research and applications. A significant research gap exists in the...
Mechanical Phenomena Silicon Polyhydroxybutyrates Zinc Oxide Durapatite Nanoparticles Biocompatible Materials Materials Testing Humans Nanocomposites Cell Survival Polyesters Machine Learning
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