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In the present work, we demonstrate the ability of a technique based on Monte Carlo resolution of the Boltzmann transport equation associated to the Green–Kubo autocorrelation of the phonon heat flux to predict, at thermal equilibrium, the thermal conductivity tensor of nanoporous structures. This methodology, which is derived from a former work [D. Lacroix, M. Isaiev, G. Pernot, Phys. Rev. B 104, 165 202 (2021)] developed in the case of bulk systems, is used to predict thermal transport properties of Si porous matrices and Si phononic membranes at room temperature. A broad range of porosities and different pore network organizations are considered. Our results are compared to available experimental data and former modeling techniques. In addition, analytical models based on the phonon mean free path are detailed and compared to numerical simulations. [ABSTRACT FROM AUTHOR]

In this study, we conducted calculations to determine the thermal conductivity of silicon nanowires with various shapes and cross-sectional designs using the Monte Carlo method combined with Green–Kubo heat flow autocorrelation. This computational approach is known for its reliability in predicting thermal properties of complex nanostructured devices. We specifically examined nanowires with circular or rectangular sections combined to complex serpentine and fishbone modulations. Our findings indicate that the nanowire's geometry significantly impacts the phonon mean free path and thermal transport. More specifically, patterns with serpentine modulations exhibit a pronounced reduction in thermal conductivity attributable to enhanced phonon boundary scatterings. Our simulation results are compared with the available experimental data, highlighting the potential of our method for structural optimization in thermal management applications, particularly in devices like thermoelectric converters. [ABSTRACT FROM AUTHOR]

Scanning Thermal Microscopy (SThM) has become an important measurement technique for characterizing the thermal properties of materials at the nanometer scale. This technique requires a SThM probe that combines an Atomic Force Microscopy (AFM) probe and a very sensitive resistive thermometer; the thermometer being located at the apex of the probe tip allows for the mapping of temperature or thermal properties of nanostructured materials with very high spatial resolution. The high interest of the SThM technique in the field of thermal nanoscience currently suffers from a low temperature sensitivity despite its high spatial resolution. To address this challenge, we developed a high vacuum-based AFM system hosting a highly sensitive niobium nitride (NbN) SThM probe to demonstrate its unique performance. As a proof of concept, we utilized this custom-built system to carry out thermal measurements using the 3ω method. By measuring the V3ω voltage on the NbN resistive thermometer under vacuum conditions, we were able to determine the SThM probe's thermal conductance and thermal time constant. The performance of the probe is demonstrated by performing thermal measurements in-contact with a sapphire sample. [ABSTRACT FROM AUTHOR]

Carbon nanotube (CNT) networks embedded in a polymer matrix have been extensively studied as a flexible thermoelectric transport medium over the recent years. However, their power factor has been largely limited by the relatively inefficient tunneling transport at junctions between CNTs and the low-density conducting channels throughout the networks. This work demonstrates that significant power factor enhancements can be achieved by adding electrically insulating microscale particles in three-dimensional CNT networks embedded in the polymer matrix. When silica particles of a few μm diameters were co-embedded in single-walled CNT (SWCNT)-polydimethylsiloxane (PDMS) composites, both the electrical conductivity and the Seebeck coefficient were simultaneously enhanced, thereby boosting the power factor by more than a factor of six. We found that the silica microparticles excluded a large volume of the composite from the access of CNTs and caused CNT networks to form around them with the polymer as a binder, resulting in improved network connectivity and alignment of CNTs. Our theoretical calculations based on junction tunneling transport for three-dimensional CNT networks show that the significant power factor enhancement can be attributed to the enhanced tunneling with reduced junction distance between CNTs. Additional power factor enhancement by a factor of three was achieved by sample compression, which further reduced the mean junction distance to enhance tunneling but also reduced the geometric factor at the same time, limiting the enhancement of electrical conductivity.