AIMC Topic: Materials Testing
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Mechanical strength recognition and classification of thermal protective fabric images after thermal aging based on deep learning.
International journal of occupational safety and ergonomics : JOSE
May 14, 2024
. Currently, numerous studies have focused on testing or modeling to evaluate the safe service life of thermal protective clothing after thermal aging, reducing the risk to occupational personnel. However, testing will render the garment unsuitable f...
Study on design optimization of GFRP tubular column composite structure based on machine learning method.
PloS one
Apr 26, 2024
Circular reinforced concrete wound glass fiber reinforced polymer (GFRP) columns and reinforced concrete filled GFRP columns are extensively utilized in civil engineering practice. Various factors influence the performance of these two types of GFRP ...
CAD-CAM resin composites: Effective components for further development.
Dental materials : official publication of the Academy of Dental Materials
Jan 15, 2024
OBJECTIVE: This paper summarizes the effective components of computer-aided design and computer-aided manufacturing (CAD-CAM) resin composites that contribute to achieving greater mechanical properties and further development.
Optimizing the selection of natural fibre reinforcement and polymer matrix for plastic composite using LS-SVM technique.
Chemosphere
Dec 18, 2023
The manufacturing sector is paying close attention to plastic matrix composites (PMCs) reinforced with natural fibres for improving their products. Due to the fact that PMC reinforced with naturally occurring fibres is more affordable and has superio...
Development of predictive algorithms for the wear resistance of denture teeth materials.
Journal of the mechanical behavior of biomedical materials
Jun 25, 2023
OBJECTIVES: To investigate the wear resistance of conventional, CAD-milled and 3D-printed denture teeth in vitro with simulated aging. To use the collected data to train single time series sample model LSTM and provide proof of concept.
Using artificial intelligence to predict the final color of leucite-reinforced ceramic restorations.
Journal of esthetic and restorative dentistry : official publication of the American Academy of Esthetic Dentistry ... [et al.]
Jan 2, 2023
OBJECTIVES: The aim of this study was to evaluate the accuracy of machine learning regression models in predicting the final color of leucite-reinforced glass CAD/CAM ceramic veneer restorations based on substrate shade, ceramic shade, thickness and ...
Prediction of abrasive wears behavior of dental composites using an artificial neural network.
Computer methods in biomechanics and biomedical engineering
Jun 8, 2022
Resin composites are widely used as dental restorative materials since dental parts are subjected to prolonged wear and ultimately need to be replaced. The objective of this study is to analyze the potential of the feed-forward back propagation artif...
Hepatic enzymes and immunoinflammatory response to Bio-C Temp bioceramic intracanal medication implanted into the subcutaneous tissue of rats.
Scientific reports
Feb 18, 2022
Our purpose was to evaluate the biocompatibility and hepatotoxicity of a new bioceramic intracanal medicament, Bio-C Temp (BIO). The biological properties of BIO were compared with calcium hydroxide-based intracanal medicament (Calen; CAL), used as g...
From Drug Molecules to Thermoset Shape Memory Polymers: A Machine Learning Approach.
ACS applied materials & interfaces
Dec 8, 2021
Ultraviolet (UV)-curable thermoset shape memory polymers (TSMPs) with high recovery stress but mild glass transition temperature () are highly desired for 3D/4D printing lightweight load-bearing structures and devices. However, a bottleneck is that h...
Activating Silent Synapses in Sulfurized Indium Selenide for Neuromorphic Computing.
ACS applied materials & interfaces
Dec 8, 2021
The transformation from silent to functional synapses is accompanied by the evolutionary process of human brain development and is essential to hardware implementation of the evolutionary artificial neural network but remains a challenge for mimickin...
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