Advances in computational intelligence of polymer composite materials: machine learning assisted modeling, analysis and design
The superior multi-functional properties of polymer composites have made them an ideal
choice for aerospace, automobile, marine, civil, and many other technologically demanding …
choice for aerospace, automobile, marine, civil, and many other technologically demanding …
[PDF][PDF] Multifarious applications of halloysite nanotubes: a review
D Rawtani, YK Agrawal - Rev. Adv. Mater. Sci, 2012 - researchgate.net
Natural tubules Halloysite are unique and versatile material formed by surface weathering of
aluminosilicate minerals and comprises of different proportion of aluminum, silicon …
aluminosilicate minerals and comprises of different proportion of aluminum, silicon …
Effects of size and aggregation/agglomeration of nanoparticles on the interfacial/interphase properties and tensile strength of polymer nanocomposites
In this study, several simple equations are suggested to investigate the effects of size and
density on the number, surface area, stiffening efficiency, and specific surface area of …
density on the number, surface area, stiffening efficiency, and specific surface area of …
[HTML][HTML] Optimization of mechanical properties of multiscale hybrid polymer nanocomposites: A combination of experimental and machine learning techniques
E Champa-Bujaico, AM Díez-Pascual… - Composites Part B …, 2024 - Elsevier
Abstract Machine learning (ML) models provide fast and accurate predictions of material
properties at a low computational cost. Herein, the mechanical properties of multiscale poly …
properties at a low computational cost. Herein, the mechanical properties of multiscale poly …
Modifying engineered nanomaterials to produce next generation agents for environmental remediation
The application of pristine nanomaterials (PNMs) for environment remediation remains
challenging due to inherently high potential for aggregation, low stability, sub-optimum …
challenging due to inherently high potential for aggregation, low stability, sub-optimum …
Reviewing the novel machine learning tools for materials design
Computational materials design is a rapidly evolving field of challenges and opportunities
aiming at development and application of multi-scale methods to simulate, predict and select …
aiming at development and application of multi-scale methods to simulate, predict and select …
Drone navigation using region and edge exploitation-based deep CNN
Drones are unmanned aerial vehicles (UAV) utilized for a broad range of functions,
including delivery, aerial surveillance, traffic monitoring, architecture monitoring, and even …
including delivery, aerial surveillance, traffic monitoring, architecture monitoring, and even …
[HTML][HTML] Chemical treatment of sisal fiber using alkali and clay method
TP Mohan, K Kanny - Composites Part A: Applied Science and …, 2012 - Elsevier
In this study the chemical treatment of sisal fiber using the combined alkali (NaOH) and clay
is discussed. The purpose of this fiber treatment is to improve the fiber–matrix compatibility …
is discussed. The purpose of this fiber treatment is to improve the fiber–matrix compatibility …
Influence of nano-TiO2 particles on the microstructure, mechanical and wear behaviour of AA7178 alloy matrix fabricated by stir casting technique
The current study focuses on the influence of varying wt% of nano-TiO2 particles (1%, 2%
and 3%) on the microstructure, mechanical and tribological properties of AA7178 alloy …
and 3%) on the microstructure, mechanical and tribological properties of AA7178 alloy …
Machine learning in chemical product engineering: The state of the art and a guide for newcomers
Chemical Product Engineering (CPE) is marked by numerous challenges, such as the
complexity of the properties–structure–ingredients–process relationship of the different …
complexity of the properties–structure–ingredients–process relationship of the different …