AIMC Topic: Ceramics

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Review on Piezoelectric Actuators Based on High-Performance Piezoelectric Materials.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control Nov 2, 2022
The piezoelectric actuator is a kind of actuation device that acts through the inverse piezoelectric effect. Due to advantages of high precision, low power consumption, compact size, and flexible structure design, they have a wide range of applicatio...
Robotics Ceramics Micro-Electrical-Mechanical Systems
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Inspecting Decorative Ceramic Defects by Fusing Convolutional Neural Network and Image Recognition.

Computational intelligence and neuroscience Aug 21, 2022
The intelligent inspection of ceramic decorative defects is one of the hot research at present. This work aims to improve the defect inspection automation of finished decorative ceramic workpieces. First, it introduces the multi-target detection algo...
Neural Networks, Computer Algorithms Automation Ceramics
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Color Design Decisions for Ceramic Products Based on Quantification of Perceptual Characteristics.

Sensors (Basel, Switzerland) Jul 20, 2022
The appearance characteristics of ceramic color are an important factor in determining the user's aesthetic perception of the product. Given the problem that ceramic color varies and the user's visual sensory evaluation of color is highly subjective ...
Semantics Ceramics Neural Networks, Computer Color
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Feedforward Control of Piezoelectric Ceramic Actuators Based on PEA-RNN.

Sensors (Basel, Switzerland) Jul 19, 2022
Multilayer perceptron (MLP) has been demonstrated to implement feedforward control of the piezoelectric actuator (PEA). To further improve the control accuracy of the neural network, reduce the training time, and explore the possibility of online mod...
Neural Networks, Computer Pisum sativum Ceramics Transducers
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Protocol to predict mechanical properties of multi-element ceramics using machine learning.

STAR protocols Jul 18, 2022
Identifying and designing high-performance multi-element ceramics based on trial-and-error approaches are ineffective and expensive. Here, we present a machine-learning-accelerated method for prediction of mechanical properties of multi-element ceram...
Ceramics Machine Learning
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Composition analysis of ceramic raw materials using laser-induced breakdown spectroscopy and autoencoder neural network.

Analytical methods : advancing methods and applications Mar 31, 2022
In the ceramic production process, the content of Si, Al, Mg, Fe, Ti and other elements in the ceramic raw materials has an important impact on the quality of the ceramic products. Exploring a method that can quickly and accurately analyze the conten...
Lasers Ceramics Neural Networks, Computer Spectrum Analysis
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Biomarkers for Pulmonary Inflammation and Fibrosis and Lung Ventilation Function in Chinese Occupational Refractory Ceramic Fibers-Exposed Workers.

International journal of environmental research and public health Dec 27, 2017
Refractory ceramic fibers (RCFs) can cause adverse health effects on workers' respiratory system, yet no proper biomarkers have been used to detect early pulmonary injury of RCFs-exposed workers. This study assessed the levels of two biomarkers that ...
Ceramics Vital Capacity Pulmonary Fibrosis Pulmonary Ventilation Lung Adult Dust China Male Forced Expiratory Volume Humans Occupational Exposure Biomarkers
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Complete rehabilitation of compromised full dentitions with adhesively bonded all-ceramic single-tooth restorations: Long-term outcome in patients with and without amelogenesis imperfecta.

Journal of dentistry Dec 21, 2017
OBJECTIVES: This clinical follow-up evaluated the long-term outcome of full-mouth rehabilitations with adhesively bonded all-ceramic restorations in patients suffering from amelogenesis imperfecta (AI) or affected by extensive tooth wear including a ...
Incisor Periodontal Index Tooth Fractures Tooth Wear Dental Veneers Dental Materials Dentition Amelogenesis Imperfecta Survival Rate Dental Porcelain Treatment Outcome Male Dental Bonding Dental Restoration Failure Oral Health Middle Aged Dental Cements Time Factors Young Adult Bruxism Dental Marginal Adaptation Humans Adult Ceramics Female
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Machine learning predicting sintering temperature for ceramsite production from multiple solid wastes.

Waste management (New York, N.Y.) Jul 15, 2025
An efficient machine learning model was developed to accurately predict the sintering temperature of ceramsite synthesized from various solid waste materials. Based on experimental data from 236 samples, eight key chemical components were defined as ...
Hot Temperature Solid Waste Ceramics Machine Learning Temperature
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Simulation and prediction of the attenuation behaviour of the KNN-LMN-based lead-free ceramics by FLUKA code and artificial neural network (ANN)-based algorithm.

Environmental technology Apr 1, 2023
The significance and novelty of the present work are the preparation of the non-lead ceramic by the general formula of (1-x) KNa.NbO-xLa MnNiO (KNN-LMN) with different x (0
Ceramics Neutrons Neural Networks, Computer Computer Simulation
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