We mathematically derived a sensitivity-based method that identifies the thermal transport physics and parameters suitable for multivariate nonlinear fits in a frequency-domain thermoreflectance (FDTR) experiment. Modern electronic devices often consist of heterogeneous nanolayers with multiple unknown thermal transport properties. However, simultaneous fitting in a single experiment for these unknown parameters will produce unreliable results if they are correlated. Current methods to identify such correlations are unreliable. This unreliability has impeded the accuracy and speed of characterizing the unknown thermal properties of such multilayer stacks. Our proposed logarithmic sensitivity ratio (LSR) analysis can evaluate the feasibility of fitting a pair of unknown parameters and clarify the governing thermal transport physics. The effectiveness and convenience of this analysis were studied using Monte Carlo simulations and actual FDTR experiments for fitting up to three unknown parameters. The principle behind this method can be extended to other techniques where multivariate fits are needed.
Bibliographical noteKAUST Repository Item: Exported on 2023-05-09
Acknowledged KAUST grant number(s): OSR-CRG2018-3737
Acknowledgements: W.-L. O. was the principal supervisor supported by the Natural Science Foundation of Zhejiang Province (LZ19E060002), National Natural Science Foundation of China (52150410417 and 51876186), the Fundamental Research Funds for the Central Universities, the Zhejiang-Saudi EMC2 Laboratory, and the ZJU-UIUC Institute. D.B. acknowledge the support by the King Abdullah University of Science and Technology (KAUST) Office of Sponsored Research (OSR) under Award No. OSR-CRG2018-3737.