AIMC Topic: Ceramics

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Optimal structural characteristics of osteoinductivity in bioceramics derived from a novel high-throughput screening plus machine learning approach.

Biomaterials
Osteoinduction is an important feature of the next generation of bone repair materials. But the key structural factors and parameters of osteoinductive scaffolds are not yet clarified. This study leverages the efficiency of high-throughput screening ...

Machine learning predicting sintering temperature for ceramsite production from multiple solid wastes.

Waste management (New York, N.Y.)
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 ...

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
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

[Evaluation of drinking-water treatment by Lifestraw® and Ceramic-pot filters].

Revista de salud publica (Bogota, Colombia)
Objective To evaluate under laboratory conditions, the removal efficiency of turbidity and E. coli of two household water filters: LifeStraw® family (MF) and ceramic pot filter (CPF). Methods The two systems were operated over 6 months using two iden...