Application of artificial intelligence to improve the efficiency and stability of prosthetic hands via nanoparticle reinforcement

NEMS (Nano-Electro-Mechanical Systems) devices play a significant role in the advancement of prosthetic hands due to their unique properties at the nanoscale. Their integration enhances the functionality, sensitivity, and performance of prosthetic limbs. Understanding the electro-thermal buckling behavior of such structures is crucial since they may be subjected to extreme heat. So, in this paper, the two-dimensional hyperbolic differential quadrature method (2D-HDQM) integrated with a four-variable refined quasi-3D tangential shear deformation theory (RQ-3DTSDT) in view of the trace of thickness stretching is extended to study electro-thermal buckling response of three-directional poroelastic FG (3D-PFG) circular sector nanoplate patched with piezoelectric layer. Aimed at discovering the real governing equations, coupled equations with the aid of compatibility conditions are employed. Regarding modeling the size-impacts, nonlocal refined logarithmic strain gradient theory (NRLSGT) with two variables called nonlocal and length scale factors is examined. Numerical experimentation and comparison are used to indicate the precision and proficiency related to the created procedure. After obtaining the outputs of the mathematics, an appropriate dataset is used for testing, training and validating of the artificial intelligence. In the results section will be discussed the trace associated with multiple geometrical and physical factors on the electro-thermal buckling performance of the current nanostructure. These findings are essential for the design and optimization of NEMS applications in various fields, including sensing, actuation, and electronics, where thermal stability is paramount. The study's insights contribute to the development of more reliable and efficient NEMS devices, ensuring their robust performance under varying thermal conditions.