arXiv subjects

S. Aria Hosseini

Publications and source records attributed to S. Aria Hosseini.

8 recordsLinked to original sources

arXiv2024

Super-suppression of long wavelength phonons in constricted nanoporous geometries

In a typical semiconductor material, the majority of heat is carried by long wavelength, long mean-free-path phonons. Nanostructuring strategies to reduce thermal conductivity, a promising direction in the field of thermoelectrics, place scattering centers of size and spatial separation comparable to the mean-free-paths of the dominant phonons to selectively scatter them. The resultant thermal conductivity is in most cases well predicted using Matthiessens rule. In general, however, long wavelength phonons are not as effectively scattered as the rest of the phonon spectrum. In this work, using large-scale Molecular Dynamics simulations, Non-Equilibrium Greens Function simulations, and Monte Carlo simulations, we show that specific nanoporous geometries, which create narrow constrictions in the passage of phonons, lead to anticorrelated heat currents in the phonon spectrum. This results in super-suppression of long-wavelength phonons due to heat trapping, and reductions in the thermal conductivity well below what is predicted by Matthiessens rule.

cond-mat.mes-hall↗

arXiv2023

Reduced-Order Model to Predict Thermal Conductivity of Dimensionally-Confined Materials

Predicting nanoscale thermal transport in dielectrics requires models, such as the Boltzmann transport equation (BTE), that account for phonon boundary scattering in structures with complex geometries. Although the BTE has been validated against several key experiments, its computational expense limits its applicability. Here, we demonstrate the use of an analytic reduced-order model for predicting the thermal conductivity in dimensionally confined materials, i.e., monolithic and porous thin films, and rectangular and cylindrical nanowires. The approach uses the recently developed "Ballistic Correction Model" (BCM) which accounts for materials' full distribution of phonon mean-free-paths. The model is validated against BTE simulations for a selection of base materials, obtaining excellent agreement. By furnishing a precise yet easy-to-use prediction of thermal transport in nanostructures, our work strives to accelerate the identification of materials for energy-conversion and thermal-management applications.

cond-mat.mtrl-sci↗

arXiv2022

Super-Suppression of Long Phonon Mean-Free-Paths in Nano-engineered Si due to Heat Current Anticorrelations

The ability to minimize the thermal conductivity of dielectrics with minimal structural intervention that could affect electrical properties is an important capability for engineering thermoelectric efficiency in low-cost materials such as Si. We recently reported the discovery of special arrangements for nanoscale pores in Si that produce a particularly large reduction in thermal conductivity accompanied by strongly anticorrelated heat current fluctuations, a phenomenon that is missed by the diffuse adiabatic boundary conditions conventionally used in numerical Boltzmann transport models. This manuscript presents the results of molecular dynamics simulations and a Monte Carlo ray tracing model that teases apart this phenomenon to reveal that special pore layouts elastically backscatter long-wavelength heat-carrying phonons. This means that heat carriage by a phonon before scattering is undone by the scattered phonon, resulting in an effective mean-free-path that is significantly shorter than the geometric line-of-sight to the pores. This effect is particularly noticeable for the long-wavelength, long mean-free-path phonons whose transport is impeded drastically more than is expected purely from the usual considerations of scattering defined by the distance between defects. This super-suppression of the mean-free-path below the characteristic length scale of the nanostructuring offers a route for minimizing thermal conductivity with minimal structural impact, while the stronger impact on long wavelengths offers possibilities for the design of band-pass phonon filtering. Moreover, the ray tracing model developed in this paper shows that different forms of correlated scattering imprint a unique signature in the heat current autocorrelation function that could be used as a diagnostic in other nanostructured systems.

cond-mat.mtrl-sci↗

arXiv2022

Mode- and Space- Resolved Thermal Transport of Alloy Nanostructures

Nanostructured semiconducting alloys obtain ultra-low thermal conductivity as a result of the scattering of phonons with a wide range of mean-free-paths (MFPs). In these materials, long-MFP phonons are scattered at the nanoscale boundaries whereas short-MFP high-frequency phonons are impeded by disordered point defects introduced by alloying. While this trend has been validated by simplified analytical and numerical methods, an ab-initio space-resolved approach remains elusive. To fill this gap, we calculate the thermal conductivity reduction in porous alloys by solving the mode-resolved Boltzmann transport equation for phonons using the finite-volume approach. We analyze different alloys, length-scales, concentrations, and temperatures, obtaining a very large reduction in the thermal conductivity over the entire configuration space. For example, a ~97% reduction is found for Al$_{0.8}$In$_{0.2}$As with 25% porosity. Furthermore, we employ these simulations to validate our recently introduced "Ballistic Correction Model" (BCM), an approach that estimates the effective thermal conductivity using the characteristic MFP of the bulk alloy and the length-scale of the material. The BCM is then used to provide guiding principles in designing alloy-based nanostructures. Notably, it elucidates how porous alloys such as Si$_{x}$Ge$_{1-x}$ obtain larger thermal conductivity reduction compared to porous Si or Ge, while also explaining why we should not expect similar behavior in alloys such as Al$_{x}$In$_{1-x}$As. By taking into account the synergy from scattering at different scales, we provide a route for the design of materials with ultra-low thermal conductivity.

cond-mat.mtrl-sci↗

arXiv2021

Enhanced Thermoelectric ZT in the Tails of the Fermi Distribution via Electron Filtering by Nanoinclusions -- Model Electron Transport in Nanocomposites

Silicon carbide nanoparticles with diameters around 8 nm and with narrow size distribution have been finely mixed with doped silicon nanopowders and sintered into bulk samples to investigate the influence of nanoinclusions on electrical and thermal transport properties. We have compared the thermoelectric properties of samples ranging from 0-5% volume fraction of silicon carbide. The silicon carbide nanoinclusions lead to a significant improvement in the thermoelectric figure of merit, ZT, largely due to an enhancement of the Seebeck coefficient. A semiclassical Boltzmann transport equation is used to model the electrical transport properties of the Seebeck coefficient and electrical conductivity. The theoretical analysis confirms that the enhancements in the thermoelectric properties are consistent with the energy selective scattering of electrons induced by the offset between the silicon Fermi level and the carbide conduction band edge. This study proves that careful engineering of the energy-dependent electron scattering rate can provide a route towards relaxing long-standing constraints in the design of thermoelectric materials.

cond-mat.mtrl-sci↗

arXiv2021

Universal Effective Medium Theory to Predict the Thermal Conductivity in Nanostructured Materials

Nanostructured materials enable high thermal transport tunability, holding promises for thermal management and heat harvesting applications. Predicting the effect that nanostructuring has on thermal conductivity requires models, such as the Boltzmann transport equation (BTE), that capture the non-diffusive transport of phonons. Although the BTE has been well validated against several key experiments, notably those on nanoporous materials, its applicability is computationally expensive. Several effective model theories have been put forward to estimate the effective thermal conductivity; however, most of them are either based on simple geometries, e.g., thin films, or simplified material descriptions such as the gray-model approximation. To fill this gap, we propose a model that takes into account the whole mean-free-path (MFP) distribution as well as the complexity of the material's boundaries in infinitely thick films with extruded porosity using uniparameter logistic regression. We validate our approach, which is called the "Ballistic Correction Model" (BCM), against full BTE simulations of a selection of three base materials (GaAs, InAs, and Si) with nanoscale porosity, obtaining excellent agreement. While the key parameters of our method, associated with the geometry of the bulk material, are obtained from the BTE, they can be decoupled and used in arbitrary combinations and scales. We tabulated these parameters for a few cases, enabling the exploration of systems that are beyond those considered in this work. Providing a simple yet accurate estimation of thermal transport in nanostructures, our work sets out to accelerate the discovery of materials for thermal-related applications.

cond-mat.mtrl-sci↗

arXiv2021

Mitigating the Effect of Nanoscale Porosity on Thermoelectric Power Factor of Si

The addition of porosity to thermoelectric materials can significantly increase the figure of merit, ZT, by reducing the thermal conductivity. Unfortunately, porosity is also detrimental to the thermoelectric power factor in the numerator of the figure of merit ZT. In this manuscript we derive strategies to recoup electrical performance in nanoporous Si by fine tuning the carrier concentration and through judicious design of the pore size and shape so as to provide energy selective electron filtering. In this study, we considered phosphorus doped silicon containing discrete pores that are either spheres, cylinders, cubes, or triangular prisms. The effects from these pores are compared with those from extended pores with circular, square and triangular cross sectional shape, and infinite length perpendicular to the electrical current. A semiclassical Boltzmann transport equation is used to model Si thermoelectric power factor. This model reveals three key results: The largest enhancement in Seebeck coefficient occurs with cubic pores. The fractional improvement is about 15% at low carrier concentration ($< 10^{20}\ \mathrm{1/cm^3}$) up to 60% at high carrier population with characteristic length around $\sim 1\ \mathrm{nm}$. To obtain the best energy filtering effect at room temperature, nanoporous Si needs to be doped to higher carrier concentration than is optimal for bulk Si. Finally, in $n$-type Si thermoelectrics the electron filtering effect that can be generated with nanoscale porosity is significantly lower than the ideal filtering effect; nevertheless, the enhancement in the Seebeck coefficient that can be obtained is large enough to offset the reduction in electrical conductivity caused by porosity.

cond-mat.mes-hall↗

arXiv2020

Heat current anticorrelation effects leading to thermal conductivity reduction in nanoporous Si

Prevailing nanostructuring strategies focus on increasing phonon scattering and reducing the mean-free-path of phonons across the spectrum. In nanoporous Si materials, for example, boundary scattering reduces thermal conductivity drastically. In this work, we identify an unusual anticorrelated specular phonon scattering effect which can result in additional reductions in thermal conductivity of up to ~ 80% for specific nanoporous geometries. We further find evidence that this effect has its origin in heat trapping between large pores with narrow necks. As the heat becomes trapped between the pores, phonons undergo multiple specular reflections such that their contribution to the thermal conductivity is partly undone. We find this effect to be wave-vector dependent at low temperatures. We use large-scale molecular dynamics simulations, wave packet analysis, as well as an analytical model to illustrate the anticorrelation effect, evaluate its impact on thermal conductivity, and detail how it can be controlled to manipulate phonon transport in nanoporous materials.

cond-mat.mes-hall↗