Artificial intelligence and machine learning in the design and additive manufacturing of responsive composites
In recent years, the development of artificial intelligence (AI) and machine learning (ML)
techniques has revolutionized composite design. Researchers have investigated intricate …
techniques has revolutionized composite design. Researchers have investigated intricate …
Characterize traction–separation relation and interfacial imperfections by data-driven machine learning models
Interfacial mechanical properties are important in composite materials and their applications,
including vehicle structures, soft robotics, and aerospace. Determination of traction …
including vehicle structures, soft robotics, and aerospace. Determination of traction …
Influence of grain boundary density on the surface energy of nanocrystalline metal thin films
Owing to the proliferation of nanomaterials, the precise measurement of surface energy (SE)
has gained importance because of their large specific surface area. Grain boundary (GB) …
has gained importance because of their large specific surface area. Grain boundary (GB) …
A Crystal Plasticity Finite Element—Machine Learning Combined Approach for Phase Transformation Prediction in High Entropy Alloy
The mechanical properties of an alloy depend on its microstructure. The strength-ductility
trade-off is a paradigm that existed for a long time. Advanced alloys, such as high entropy …
trade-off is a paradigm that existed for a long time. Advanced alloys, such as high entropy …
PeakForce Quantitative Nanomechanical Imaging for Characterization of the Surface Energy of Nano-Patterned Au Strip
Precise measurement of the surface energy of nanoscale metal thin films is crucial for the
fabrication of reliable miniaturized electronic devices consisting of multi-stacked thin film …
fabrication of reliable miniaturized electronic devices consisting of multi-stacked thin film …