Artificial intelligence and machine learning in design of mechanical materials
Artificial intelligence, especially machine learning (ML) and deep learning (DL) algorithms,
is becoming an important tool in the fields of materials and mechanical engineering …
is becoming an important tool in the fields of materials and mechanical engineering …
A state-of-the-art review on machine learning-based multiscale modeling, simulation, homogenization and design of materials
Multiscale simulation and homogenization of materials have become the major
computational technology as well as engineering tools in material modeling and material …
computational technology as well as engineering tools in material modeling and material …
Machine learning‐driven biomaterials evolution
Biomaterials is an exciting and dynamic field, which uses a collection of diverse materials to
achieve desired biological responses. While there is constant evolution and innovation in …
achieve desired biological responses. While there is constant evolution and innovation in …
Glass-ceramics in dentistry: Fundamentals, technologies, experimental techniques, applications, and open issues
M Montazerian, F Baino, E Fiume, C Migneco… - Progress in Materials …, 2023 - Elsevier
Dental glass-ceramics (DGCs) are developed by controlled crystallization of oxide glasses
and form an important group of biomaterials used in modern dentistry. They are also of great …
and form an important group of biomaterials used in modern dentistry. They are also of great …
Using deep learning to predict fracture patterns in crystalline solids
Fracture is a catastrophic process whose understanding is critical for evaluating the integrity
and sustainability of engineering materials. Here, we present a machine-learning approach …
and sustainability of engineering materials. Here, we present a machine-learning approach …
A review on Machine learning aspect in physics and mechanics of glasses
The glass science and technology is a rapidly developing field which is focused on
development of new glasses with excellent properties. Glasses are the non-crystalline …
development of new glasses with excellent properties. Glasses are the non-crystalline …
Predicting densities and elastic moduli of SiO2-based glasses by machine learning
Chemical design of SiO2-based glasses with high elastic moduli and low weight is of great
interest. However, it is difficult to find a universal expression to predict the elastic moduli …
interest. However, it is difficult to find a universal expression to predict the elastic moduli …
Designing optical glasses by machine learning coupled with a genetic algorithm
Engineering new glass compositions have experienced a sturdy tendency to move forward
from (educated) trial-and-error to data-and simulation-driven strategies. In this work, we …
from (educated) trial-and-error to data-and simulation-driven strategies. In this work, we …
GlassNet: a multitask deep neural network for predicting many glass properties
DR Cassar - Ceramics International, 2023 - Elsevier
A multitask deep neural network model was trained on more than 218k different glass
compositions. This model, called GlassNet, can predict 85 different properties (such as …
compositions. This model, called GlassNet, can predict 85 different properties (such as …
ViscNet: Neural network for predicting the fragility index and the temperature-dependency of viscosity
DR Cassar - Acta materialia, 2021 - Elsevier
Viscosity is one of the most important properties of disordered matter. The temperature-
dependence of viscosity is used to adjust process variables for glass-making, from melting to …
dependence of viscosity is used to adjust process variables for glass-making, from melting to …