[HTML][HTML] 3D printing of biodegradable polymers and their composites–Current state-of-the-art, properties, applications, and machine learning for potential future …
This review paper comprehensively examines the dynamic landscape of 3D printing and
Machine Learning utilizing biodegradable polymers and their composites, presenting a …
Machine Learning utilizing biodegradable polymers and their composites, presenting a …
[HTML][HTML] Advances in machine learning-aided design of reinforced polymer composite and hybrid material systems
Reinforced composite is a preferred choice of material for the design of industrial lightweight
structures. As of late, composite materials analysis and development utilizing machine …
structures. As of late, composite materials analysis and development utilizing machine …
Thermal properties of surface-modified nano-Al2O3/kevlar fiber/epoxy composites
The mechanical and thermal properties of Kevlar fiber reinforced polymer composites are
favorable. Researchers have extensively studied to improve these composites' mechanical …
favorable. Researchers have extensively studied to improve these composites' mechanical …
Evaluation of artificial intelligence methods to estimate the compressive strength of geopolymers
The depletion of natural resources and greenhouse gas emissions related to the
manufacture and use of ordinary Portland cement (OPC) pose serious concerns to the …
manufacture and use of ordinary Portland cement (OPC) pose serious concerns to the …
[HTML][HTML] Ensemble Machine Learning approach for evaluating the material characterization of carbon nanotube-reinforced cementitious composites
Time and cost-efficient techniques are essential to avoid extra conventional experimental
studies with large data-set for material characterization of composite materials. This study is …
studies with large data-set for material characterization of composite materials. This study is …
Buckling response of CNT based hybrid FG plates using finite element method and machine learning method
In this study, a C 0 finite element model (FEM) based on modified third-order shear
deformation (MTSDT) theory in conjunction with a deep neural network (DNN), extreme …
deformation (MTSDT) theory in conjunction with a deep neural network (DNN), extreme …
Metabolism of the predominant human milk oligosaccharide fucosyllactose by an infant gut commensal
K James, F Bottacini, JIS Contreras, M Vigoureux… - Scientific reports, 2019 - nature.com
A number of bifidobacterial species are found at a particularly high prevalence and
abundance in faecal samples of healthy breastfed infants, a phenomenon that is believed to …
abundance in faecal samples of healthy breastfed infants, a phenomenon that is believed to …
[HTML][HTML] Using machine learning to predict the long-term performance of fibre-reinforced polymer structures: A state-of-the-art review
When exposed to environmental conditions, fibre-reinforced polymer (FRP) composites are
prone to material degradation. The environmental reduction factor in different structural …
prone to material degradation. The environmental reduction factor in different structural …
Properties prediction of composites based on machine learning models: A focus on statistical index approaches
Composites have a wide range of applications across various industries due to their high
strength-to-weight ratio, corrosion resistance, durability, versatility, and lightweight …
strength-to-weight ratio, corrosion resistance, durability, versatility, and lightweight …
Prediction of fracture toughness of concrete using the machine learning approach
AB Shemirani - Theoretical and Applied Fracture Mechanics, 2024 - Elsevier
In the process of structural design, it is useful to estimate the fracture toughness of concrete
samples. This research showcases the effectiveness of utilizing machine learning methods …
samples. This research showcases the effectiveness of utilizing machine learning methods …