Heat dissipation remains a key challenge to be addressed, determining the performance
and durability of smart electronic devices. Graphene reinforced metal matrix composites …

Metal matrix nanocomposites (MMNCs) are gaining more and more interest because
matrices and nanophases with heterogeneous characteristics could combine to provide …

Abstract In this study, Mg-Ti-SiC composite powders with varied micron and nano silicon
carbide (SiC) particle sizes were fabricated utilizing the ball milling technology at various …

This work focused on develo** an analytical fast and reliable model to predict the
morphological changes in nanocomposite powders during mechanical alloying. A …

In this paper, we present a newly modified machine learning model that employs a long
short-term memory (LSTM) neural network model with the golden jackal optimization (GJO) …

Due to the lack of analytical solutions for the wear rates prediction of nanocomposites, we
present a modified machine learning method named Dendritic Neural (DN) to predict the …

Owing to the absence of scientific methods for predicting nanocomposites' wear rates, a
freshly updated machine learning method that uses an Artificial Protozoa Optimizer (APO) to …

A novel catalyst composed of Ag 3 PO 4 bridged by Ni/Ti LDH-graphene heterojunction
structure was successfully prepared by a simple in-situ deposition method, which has …

Electro-less deposition synthesized Al2O3 nanoparticles coated Ag with different weight
percent (0, 2.5, 5, 7.5 and 10) were mixed with pure Cu powder to manufacture Cu–Al 2 O 3 …

Abstract Three-dimensional (3D) printing of complex metallic parts with a micrometer
resolution can extend the application of additive manufacturing to various fields wherein the …