<p>This study meticulously and rigorously investigates the stability of the melting temperature curve of C<sub>60</sub> under extreme pressures. Our analysis of four key parameters, bulk modulus at zero pressure, its first pressure derivative, the Gruneisen parameter, and the melting temperature at zero pressure, is conducted with utmost care for traceability. A model is developed using multiple state equations, including Brennan–Stacey, Srivastava–Pandey, Dixit–Srivastava, and Kholiya. The accuracy of these models is validated against experimental data. Results reveal that compression, bulk modulus, and melting temperature increase with pressure while the first-order pressure derivative decreases. Among the equations, the Srivastava–Pandey equation of state aligns most closely with experimental data, providing reliable predictions due to its gradual consideration of property changes under pressure. This method proves invaluable for accurately estimating the melting temperature of nanomaterials, especially considering the complexities and high costs associated with experimental studies.</p>

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Studying the Melting Behaviour of Fullerene by Utilising the Equation of State and Lindemann’s Law

  • Abhay P. Srivastava,
  • Brijesh K. Pandey

摘要

This study meticulously and rigorously investigates the stability of the melting temperature curve of C60 under extreme pressures. Our analysis of four key parameters, bulk modulus at zero pressure, its first pressure derivative, the Gruneisen parameter, and the melting temperature at zero pressure, is conducted with utmost care for traceability. A model is developed using multiple state equations, including Brennan–Stacey, Srivastava–Pandey, Dixit–Srivastava, and Kholiya. The accuracy of these models is validated against experimental data. Results reveal that compression, bulk modulus, and melting temperature increase with pressure while the first-order pressure derivative decreases. Among the equations, the Srivastava–Pandey equation of state aligns most closely with experimental data, providing reliable predictions due to its gradual consideration of property changes under pressure. This method proves invaluable for accurately estimating the melting temperature of nanomaterials, especially considering the complexities and high costs associated with experimental studies.