Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Faculty Publications Article Faculty Publications -Articles Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Seema; Singhal, Abhinav Title A name given to the resource Rayleigh-Type Surface Waves in Piezo-Thermoelastic Materials: A Comparative Study Using GreenNaghdi III and Three-Phase-Lag Models with Machine-Learning Surrogates Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2025 Source A related resource from which the described resource is derived Mechanics of Solids;Volume;60;Issue;8;pp.6860-6887 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1134/S0025654425604811" target="_blank" rel="noreferrer noopener">https://doi.org/10.1134/S0025654425604811</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105036522806?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105036522806?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Seema, Christ University, Bengaluru, 560029, India; Singhal A., Christ University, Bengaluru, 560029, India Description An account of the resource Abstract: In this work, the GreenNaghdi type III (GN-III) and Three-Phase-Lag (TPL) thermoelastic theories are used to investigate Rayleigh-type surface wave propagation in a transversely isotropic piezo-thermoelastic half-space. Phase velocity, attenuation, and specific loss may be thoroughly evaluated thanks to the derivation of secular equations for electrically open/shorted and thermally insulated/isothermal boundary conditions. The findings indicate that attenuation and loss show a substantial dependency on boundary restrictions and the chosen thermoelastic model, but phase velocity increases with inclination angle and stabilises for high wave numbers. The TPL framework predicts somewhat greater velocities and damping because of thermal relaxation effects, while electrically shorted isothermal surfaces produce the lowest dissipation. By explicitly incorporating governing equations into its loss function, a Physics-Informed Neural Network (PINN) is utilised to overcome the computational burden of solving difficult transcendental equations. The PINN provides an effective stand-in for optimisation and real-time diagnostics in SAW sensors, ultrasonic devices, and smart piezoelectric materials by precisely reconstructing dispersion trends from sparse analytical data. Pleiades Publishing, Ltd. 2025. Subject The topic of the resource GreenNaghdi III; Machine learning; Piezoelectric thermoelasticity; Rayleigh-type waves; Three-phase-lag model Publisher An entity responsible for making the resource available Pleiades Publishing Relation A related resource ISSN: 256544; Language A language of the resource English Type The nature or genre of the resource Article Rights Information about rights held in and over the resource Restricted Access; Hardcopy may be available in the library Format The file format, physical medium, or dimensions of the resource online