Monte Carlo simulations for phonon transport in silicon nanomaterials

In nanostructures phonon transport behaviour is distinctly different to transport in bulk materials such that materials with ultra low thermal conductivities and enhanced thermoelectric performance can be realized. Low thermal conductivities have been achieved in nanocrystalline materials that include hierarchical sizes of inclusions and pores. Nanoporous structures present a promising set of material properties and structures which allow for ultra-low thermal conductivity, even below the amorphous limit. In this paper we outline a semiclassical Monte Carlo code for the study of phonon transport and present an investigation of the thermal conductivity in nanoporous and nanocrystalline silicon. Different disordered geometry configurations are incorporated to investigate the effects of pores and grain boundaries on the phonon flux and the thermal conductivity, including the effects of boundary roughness, pore position and pore diameter. At constant porosity, thermal conductivity reduction is maximized by having a large number of smaller diameter pores as compared to a small number of larger diameter pores. Furthermore, we show that porosity has a greater impact on thermal conductivity than the degree of boundary roughness. Our simulator is validated across multiple simulation and experimental works for both pristine silicon channels and nanoporous structures.Comment: 10 pages, 8 figure

Monte Carlo phonon transport simulations in hierarchically disordered silicon nanostructures

Hierarchical material nanostructuring is considered to be a very promising direction for high performance thermoelectric materials. In this work we investigate thermal transport in hierarchically nanostructured silicon. We consider the combined presence of nanocrystallinity and nanopores, arranged under both ordered and randomized positions and sizes, by solving the Boltzmann transport equation using the Monte Carlo method. We show that nanocrystalline boundaries degrade the thermal conductivity more drastically when the average grain size becomes smaller than the average phonon mean-free path. The introduction of pores degrades the thermal conductivity even further. Its effect, however, is significantly more severe when the pore sizes and positions are randomized, as randomization results in regions of higher porosity along the phonon transport direction, which introduce significant thermal resistance. We show that randomization acts as a large increase in the overall effective porosity. Using our simulations, we show that existing compact nanocrystalline and nanoporous theoretical models describe thermal conductivity accurately under uniform nanostructured conditions, but overestimate it in randomized geometries. We propose extensions to these models that accurately predict the thermal conductivity of randomized nanoporous materials based solely on a few geometrical features. Finally, we show that the new compact models introduced can be used within Matthiessen's rule to combine scattering from different geometrical features withi

Phonon transport simulations in hierarchical and highly disordered nanostructures

Nanostructuring is considered a very promising direction for high performance thermoelectric materials, which can convert waste heat into useful energy. These materials can reduce dependence on fossil fuels and enhance thermal energy harvesting, with huge environmental and societal benefits. In this work we investigate thermal transport in nanostructures and study methods to reduce the thermal conductivity (which enhances thermoelectric efficiency). Using silicon as an example, we consider the combined presence of nanocrystallinity and nanopores, arranged under both ordered and disordered (randomized) positions and sizes by using a phonon transport simulator constructed as a part of this work. We show that nanocrystalline boundaries degrade the thermal conductivity more drastically when the average grain size becomes smaller than the material average phonon mean-free-path. Introduction of pores in a hierarchical fashion degrades the thermal conductivity even further. Its effect, however, is significantly more severe when the pore sizes and positions are randomized, as randomization results in regions of higher porosity along the phonon transport direction, which introduce significant thermal resistance. We show that this randomization, or disorder, acts as a large increase in the overall effective porosity. Using our simulations, we show that existing compact nanocrystalline and nanoporous theoretical models describe thermal conductivity accurately under uniform nanostructured conditions but overestimate it in disordered geometries. We propose extensions to these models that accurately predict the thermal conductivity of disordered nanoporous materials based solely on a few geometrical features. Additionally, we show that the new compact models introduced can be used within Matthiessen’s rule to combine scattering from different geometrical features within ~10% accuracy. Looking at high temperature regimes, we show that the relative reduction in thermal conductivity is stronger at high temperatures in the presence of nanocrystallinity, a consequence of the wavevector-dependent nature of phonon scattering on the nanocrystalline grain domain boundaries. We next consider asymmetric nanoporous structures, and investigate the combined effects of porosity, inter-pore distance, and pore position on thermal rectification in nanoporous silicon. We define thermal rectification in terms of system mean-free-paths rather than non-linearity in temperature – as conventionally done. We show that systems: i) with denser, compressed pore arrangements (i.e. with smaller inter-pore distances), ii) with pores positioned closer to the device edge/contact, and iii) with pores in a triangular arrangement, can achieve rectification of over 55%. Introducing hierarchically smaller pores into existing porous geometries increases rectification even further. Importantly, for the structures we simulate, we show that sharp rectifying junctions, separating regions of long from short phonon mean-free-paths are more beneficial than spreading the asymmetry throughout the material along the heat direction in a graded fashion. Lastly, comparing a full wave-based quantum mechanical Non-Equilibrium Green's Function (NEGF) method, and a particle-based classical ray-tracing approach, we investigate the qualitative differences in the wave and particle-based phonon transport at the vicinity of nanoscale features, indicating when simplified particle based approaches fail, and when not. Insight extracted from this work can be used to provide better and more complete understanding of phonon transport in nanomaterials

Thermal rectification optimization in nanoporous Si using Monte Carlo simulations

We investigate thermal rectification in nanoporous silicon using a semiclassical Monte Carlo simulation method. We consider geometrically asymmetric nanoporous structures and investigate the combined effects of porosity, interpore distance, and pore position relative to the device boundaries. Two basis geometries are considered, one in which the pores are arranged in rectangular arrays and ones in which they form triangular arrangements. We show that systems (i) with denser, compressed pore arrangements (i.e., with smaller interpore distances), (ii) with the pores positioned closer to the device edge/contact, and (iii) with the pores in a triangular arrangement can achieve rectification of over 55%. Introducing smaller pores into existing porous geometries in a hierarchical fashion increases rectification even further to over 60%. Importantly, for the structures we simulate, we show that sharp rectifying junctions, separating regions of long from short phonon mean-free-paths, are more beneficial for rectification than spreading the asymmetry throughout the material along the heat direction in a graded fashion

Batteries Safety: Recent Progress and Current Challenges

https://www.frontiersin.org/articles/10.3389/fenrg.2019.00071/fullIn this growing age of clean energy and the use of power storage to circumvent the use of traditional fossil fuel technologies, batteries of greater capacity, storage, and power are increasingly becoming indispensable. New chemistries are being developed to increase the capacity of traditional lithium ion batteries and to develop batteries beyond Lithium ion. Promising high capacity cathodes and anodes are developed however their large-scale deployment is hindered due to safety concerns. In this review, we summarize recent progress of lithium ion batteries safety, highlight current challenges, and outline the most advanced safety features that may be incorporated to improve battery safety for both lithium ion and batteries beyond lithium ion. Of particular interest is the issue of thermal runaway mitigation by incorporation of novel nano-materials and advanced technologies

Effect of wave versus particle phonon nature in thermal transport through nanostructures

Comprehensive understanding of thermal transport in nanostructured materials needs large scale simulations bridging length scales dictated by different physics related to the wave versus particle nature of phonons. Yet, available computational approaches implicitly treat phonons as either just waves or as particles. In this work, using a full wave-based Non-Equilibrium Green's Function (NEGF) method, and a particle-based ray-tracing Monte Carlo (MC) approach, we investigate the qualitative differences in the wave and particle-based phonon transport at the vicinity of nanoscale features. For the simple example of a nanoporous geometry, we show that phonon transmission agrees very well for both methods with an error margin of ±15%, across phonon wavelengths even for features with sizes down to 3–4 nm. For cases where phonons need to squeeze in smaller regions to propagate, we find that MC underestimates the transmission of long wavelength phonons whereas wave treatment within NEGF indicates that those long wavelength phonons can propagate more easily. We also find that particle-based simulation methods are somewhat more sensitive to structural variations compared to the wave-based NEGF method. The insight extracted from comparing wave and particle methods can be used to provide a better and more complete understanding of phonon transport in nanomaterials

Network analysis reveals common host protein/s modulating pathogenesis of neurotropic viruses

Network analysis through graph theory provides a quantitative approach to characterize specific proteins and their constituent assemblies that underlie host-pathogen interactions. In the present study, graph theory was used to analyze the interactome designed out of 50 differentially expressing proteins from proteomic analysis of Chandipura Virus (CHPV, Family: Rhabdoviridae) infected mouse brain tissue to identify the primary candidates for intervention. Using the measure of degree centrality, that quantifies the connectedness of a single protein within a milieu of several other interacting proteins, DJ-1 was selected for further molecular validation. To elucidate the generality of DJ-1’s role in propagating infection its role was also monitored in another RNA virus, Japanese Encephalitis Virus (JEV, Family: Flaviviridae) infection. Concurrently, DJ-1 got over-expressed in response to reactive oxygen species (ROS) generation following viral infection which in the early phase of infection migrated to mitochondria to remove dysfunctional mitochondria through the process of mitophagy. DJ-1 was also observed to modulate the viral replication and interferon responses along with low-density lipoprotein (LDL) receptor expression in neurons. Collectively these evidences reveal a comprehensive role for DJ-1 in neurotropic virus infection in the brain

Enhanced phonon boundary scattering at high temperatures in hierarchically disordered nanostructures

Boundary scattering in hierarchically disordered nanomaterials is an effective way to reduce the thermal conductivity of thermoelectric materials and increase their performance. In this work, we investigate thermal transport in silicon-based nanostructured materials in the presence of nanocrystallinity and nanopores at the range of 300–900 K using a Monte Carlo simulation approach. The thermal conductivity in the presence of nanocrystallinity follows the same reduction trend as in the pristine material. We show, however, that the relative reduction is stronger with temperature in the presence of nanocrystallinity, a consequence of the wavevector-dependent (q-dependent) nature of phonon scattering on the domain boundaries. In particular, as the temperature is raised, the proportion of large wavevector phonons increases. Since these phonons are more susceptible to boundary scattering, we show that this q-dependent surface scattering could account for as much as a ∼ 40% reduction in the thermal conductivity of nanocrystalline Si. The introduction of nanopores with randomized positions magnifies this effect, which suggests that hierarchical nanostructuring is actually more effective at high temperatures than previously thought