BibTeX
@ARTICLE{
         Marepalli2020Ada,
       title = "Automatic differentiation approach for property computations in nanoscale thermal
         transport",
       journal = "Computer Physics Communications",
       volume = "252",
       pages = "107138",
       year = "2020",
       issn = "0010-4655",
       doi = "10.1016/j.cpc.2020.107138",
       url = "http://www.sciencedirect.com/science/article/pii/S0010465520300011",
       author = "Prabhakar Marepalli and Sanjay R. Mathur and Jayathi Y. Murthy",
       keywords = "Nanoscale thermal transport, Property computations, Sensitivity analysis, Force
         constants, Gruneisen parameter, Automatic differentiation",
       abstract = "We present the automatic code differentiation technique to perform derivative
         computations in nanoscale phonon transport simulations. This method exploits the concepts of
         templating and operator overloading in C++ and other similar programming languages to unintrusively
         convert existing codes into those yielding derivatives of arbitrary order. The idea is demonstrated
         through the computation of phonon properties such as second and third order force constants, the
         Gruneisen parameter, group velocities, and the temperature variation of specific heat for materials
         like graphene and graphene nanoribbons. Derivative values so computed are compared with those
         obtained using finite difference approaches or with analytical values. The method is found to yield
         derivative values to machine accuracy, with none of the round-off issues associated with finite
         difference approaches.",
       ad_area = "Heat Transport"
}