Research Frontiers in Numerical Simulation and Mechanical Modeling of Ceramic Matrix Composites: Bibliometric Analysis and Hotspot Trends from 2000 to 2025. [PDF]
Wang S +5 more
europepmc +1 more source
This review comprehensively summarizes the atomic defects in TMDs for their applications in sustainable energy storage devices, along with the latest progress in ML methodologies for high‐throughput TEM data analysis, offering insights on how ML‐empowered microscopy facilitates bridging structure–property correlation and inspires knowledge for precise ...
Zheng Luo +6 more
wiley +1 more source
Synergetic properties of advanced materials for high-power and high-temperature applications. [PDF]
Mengesha WG, Nagessar K.
europepmc +1 more source
Inherently Disordered Auxetic Metamaterials
Inherently disordered auxetic metamaterials based on random chiral Delaunay triangulations are designed and investigated using numerical simulations and experimental tests. These disordered frameworks exhibit orthotropic behavior and a large negative Poisson's ratio (ca.
Matteo Montanari +3 more
wiley +1 more source
Recent Advances in the Synthesis and Processing of Carbon Nanotubes and Carbon Nanocomposites for Energy Storage, Biomedical, and Environmental Applications. [PDF]
Altaf NU +9 more
europepmc +1 more source
Unveiling a Bulk WTaV Multicomponent Alloy With Superior Thermal Properties and Manufacturability
ABSTRACT Many tungsten (W)‐based medium and high entropy alloys (HEA) demonstrate superior microstructural stability and enhanced mechanical properties as compared to pure W, effectively rendering them as viable candidate materials for extreme environments such as nuclear fusion, aerospace applications, and so on.
Ishtiaque K. Robin +11 more
wiley +1 more source
Experimental Testing, Manufacturing and Numerical Modelling of Composite and Sandwich Structures (Second Edition). [PDF]
Campilho RDSG.
europepmc +1 more source
Physics‐Embedded Neural Network: A Novel Approach to Design Polymeric Materials
Traditional black‐box models for polymer mechanics rely solely on data and lack physical interpretability. This work presents a physics‐embedded neural network (PENN) that integrates constitutive equations into machine learning. The approach ensures reliable stress predictions, provides interpretable parameters, and enables performance‐driven, inverse ...
Siqi Zhan +8 more
wiley +1 more source
Dynamic mechanical thermal analysis (DMTA) of the hybrid epoxy/carbon-fibers nanocomposites for satellite structures. [PDF]
Gamil M +6 more
europepmc +1 more source

