AIMC Topic: Surface Properties
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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.
Taylor-Gorilla troops optimized deep learning network for surface roughness estimation.
Network (Bristol, England)
Aug 22, 2023
In order to guarantee the desired quality of machined products, a reliable surface roughness assessment is essential. Using a surface profile metre with a contact stylus, which can produce accurate measurements of surface profiles, is the most popula...
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.
Application of unsupervised and supervised learning to a material attribute database of tablets produced at two different granulation scales.
International journal of pharmaceutics
May 20, 2023
The purpose of this study is to demonstrate the usefulness of machine learning (ML) for analyzing a material attribute database from tablets produced at different granulation scales. High shear wet granulators (scale 30 g and 1000 g) were used and da...
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 the Lotus Effect on Solid Surfaces by Machine Learning.
Small (Weinheim an der Bergstrasse, Germany)
Sep 7, 2022
Superhydrophobic surfaces with the "lotus effect" have wide applications in daily life and industry, such as self-cleaning, anti-freezing, and anti-corrosion. However, it is difficult to reliably predict whether a designed superhydrophobic surface ha...
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...
Generation of Interconnected Neural Clusters in Multiscale Scaffolds from Human-Induced Pluripotent Stem Cells.
ACS applied materials & interfaces
Nov 17, 2021
The development of in vitro neural networks depends to a large extent on the scaffold properties, including the scaffold stiffness, porosity, and dimensionality. Herein, we developed a method to generate interconnected neural clusters in a multiscale...
A deep learning approach to identify and segment alpha-smooth muscle actin stress fiber positive cells.
Scientific reports
Nov 8, 2021
Cardiac fibrosis is a pathological process characterized by excessive tissue deposition, matrix remodeling, and tissue stiffening, which eventually leads to organ failure. On a cellular level, the development of fibrosis is associated with the activa...
Optimization of running-in surface morphology parameters based on the AutoML model.
PloS one
Oct 4, 2021
Running-in is an important and relatively complicated process. The surface morphology prior to running-in affects the surface morphology following the running-in process, which in turn influences the friction and wear characteristics of the workpiece...
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