Theoretical And Computational Studies Of Heat Transport Processes In Molecular Systems

There has been growing research interest in the field of nanoscale thermal transport over the past two decades due its importance to a variety of fascinating applications, such as waste heat control, improved electronic functionality, and phononics building blocks. Much of this focus has been on solid-state systems for which advanced experimental characterizations and measurements are readily available. Molecule-based systems, which in principle exhibit no less structural richness than solid state systems and may show excellent energy transport capabilities, have been largely ignored until recently. This is mostly because of the difficulties associated with measuring heat transport on the molecular scale. However, a few recent experimental breakthroughs have brought molecular energy transport process into the spotlight, and at the same time established measurement techniques that can be tested, verified, and explained using theoretical tools. This dissertation examines and explores theoretical approaches for modeling heat transport in molecular systems. Specifically, we have developed a stochastic nonequilibrium molecular dynamics (MD) method which mimics the experimental setting of substrate-bridge-substrate structure, i.e., a molecular junction. We incorporate this approach, along with a quantum Landauer\u27s formalism, into the open-source molecular simulation package--GROMACS, so that it can be applied to molecular systems with different topologies and thermal environments. Our simulations of heat conduction in hydrocarbon-based single molecule junctions yield excellent agreement with the recent state-of-the-art experimental data. Within the capacities of the new method,we have also investigated phononic interference effects in the heat conduction characteristics of benzendithiol molecules. Using the methods developed in this dissertation, we have mapped, for the first time, thermal fluxes down to the atomistic level. In the context of phononic energy transport, we develop a simulation method that integrates quantum effects into classical MD. This hybrid method, once fully implemented, will compensate for the disadvantages of classical approaches at low temperatures and for the difficulty in treating anharmonicites in Landauer-type quantum transport calculations. This method will improve the predictive power of classical heat conduction simulations. The second part of this dissertation explores an intriguing energy transport channel that has been newly discovered termed electron-transfer-induced heat transport (ETIHT), which is distinct from traditional heat transfer mechanisms that rely purely onmolecular vibrations. We construct a theoretical model that combines the two energy transport channels (ETIHT and phononic) into one general model and then we show analytically under certain parametric thresholds (e.g. reorganization energies) that ETIHT dominates while other conditions may magnify the phononic contributions. Although the work in this part of the thesis is currently purely theoretical, it may provide useful insights into future organic molecular thermoelectric devices

Energy transport between heat baths with oscillating temperatures

Energy transport is a fundamental physical process that plays a prominent role in the function and performance of myriad systems and technologies. Recent experimental measurements have shown that subjecting a macroscale system to a time-periodic temperature gradient can increase thermal conductivity in comparison to a static temperature gradient. Here, we theoretically examine this mechanism in a nanoscale model by applying a stochastic Langevin framework to describe the energy transport properties of a particle connecting two heat baths with different temperatures, where the temperature difference between baths is oscillating in time. Analytical expressions for the energy flux of each heat bath and for the system itself are derived for the case of a free particle and a particle in a harmonic potential. We find that dynamical effects in the energy flux induced by temperature oscillations give rise to complex energy transport hysteresis effects. The presented results suggest that applying time-periodic temperature modulations is a potential route to control energy storage and release in molecular devices and nanosystems

Data-driven methods for diffusivity prediction in nuclear fuels

The growth rate of structural defects in nuclear fuels under irradiation is intrinsically related to the diffusion rates of the defects in the fuel lattice. The generation and growth of atomistic structural defects can significantly alter the performance characteristics of the fuel. This alteration of functionality must be accurately captured to qualify a nuclear fuel for use in reactors. Predicting the diffusion coefficients of defects and how they impact macroscale properties such as swelling, gas release, and creep is therefore of significant importance in both the design of new nuclear fuels and the assessment of current fuel types. In this article, we apply data-driven methods focusing on machine learning (ML) to determine various diffusion properties of two nuclear fuels, uranium oxide and uranium nitride. We show that using ML can increase, often significantly, the accuracy of predicting diffusivity in nuclear fuels in comparison to current analytical models. We also illustrate how ML can be used to quickly develop fuel models with parameter dependencies that are more complex and robust than what is currently available in the literature. These results suggest there is potential for ML to accelerate the design, qualification, and implementation of nuclear fuels

Theoretical and Computational Studies of Heat Transport Processes in Molecular Systems

There has been growing research interest in the field of nanoscale thermal transport over the past two decades due its importance to a variety of fascinating applications, such as waste heat control, improved electronic functionality, and phononics building blocks. Much of this focus has been on solid-state systems for which advanced experimental characterizations and measurements are readily available. Molecule-based systems, which in principle exhibit no less structural richness than solid state systems and may show excellent energy transport capabilities, have been largely ignored until recently. This is mostly because of the difficulties associated with measuring heat transport on the molecular scale. However, a few recent experimental breakthroughs have brought molecular energy transport process into the spotlight, and at the same time established measurement techniques that can be tested, verified, and explained using theoretical tools. This dissertation examines and explores theoretical approaches for modeling heat transport in molecular systems. Specifically, we have developed a stochastic nonequilibrium molecular dynamics (MD) method which mimics the experimental setting of substrate-bridge-substrate structure, i.e., a molecular junction. We incorporate this approach, along with a quantum Landauer\u27s formalism, into the open-source molecular simulation package--GROMACS, so that it can be applied to molecular systems with different topologies and thermal environments. Our simulations of heat conduction in hydrocarbon-based single molecule junctions yield excellent agreement with the recent state-of-the-art experimental data. Within the capacities of the new method, we have also investigated phononic interference effects in the heat conduction characteristics of benzendithiol molecules. Using the methods developed in this dissertation, we have mapped, for the first time, thermal fluxes down to the atomistic level. In the context of phononic energy transport, we develop a simulation method that integrates quantum effects into classical MD. This hybrid method, once fully implemented, will compensate for the disadvantages of classical approaches at low temperatures and for the difficulty in treating anharmonicites in Landauer-type quantum transport calculations. This method will improve the predictive power of classical heat conduction simulations. The second part of this dissertation explores an intriguing energy transport channel that has been newly discovered termed electron-transfer-induced heat transport (ETIHT), which is distinct from traditional heat transfer mechanisms that rely purely on molecular vibrations. We construct a theoretical model that combines the two energy transport channels (ETIHT and phononic) into one general model and then we show analytically under certain parametric thresholds (e.g. reorganization energies) that ETIHT dominates while other conditions may magnify the phononic contributions. Although the work in this part of the thesis is currently purely theoretical, it may provide useful insights into future organic molecular thermoelectric devices

Intrinsic Delocalization during the Decay of Excitons in Polymeric Solar Cells

In bulk heterojunction polymer solar cells, external photoexcitation results in localized excitons in the polymer chain. After hot exciton formation and subsequent relaxation, the dipole moment drives the electron to partially transfer to extended orbitals from the original localized ones, leading to self-delocalization. Based on the dynamic fluorescence spectra, the delocalization of excitons is revealed to be an intrinsic property dominated by exciton decay, acting as a bridge for the exciton to diffuse in the polymeric solar cell. The modification of the dipole moment enhances the efficiency of polymer solar cells

Comparison of the Effects of Dibutyl and Monobutyl Phthalates on the Steroidogenesis of Rat Immature Leydig Cells

Dibutyl phthalate (DBP) is a widely used synthetic phthalic diester and monobutyl phthalate (MBP) is its main metabolite. DBP can be released into the environment and potentially disrupting mammalian male reproductive endocrine system. However, the potencies of DBP and MBP to inhibit Leydig cell steroidogenesis and their possible mechanisms are not clear. Immature Leydig cells isolated from rats were cultured with 0.05–50 μM DBP or MBP for 3 h in combination with testosterone synthesis regulator or intermediate. The concentrations of 5α-androstanediol and testosterone in the media were measured, and the mRNA levels of the androgen biosynthetic genes were detected by qPCR. The direct actions of DBP or MBP on CYP11A1, CYP17A1, SRD5A1, and AKR1C14 activities were measured. MBP inhibited androgen production by the immature Leydig cell at as low as 50 nM, while 50 μM was required for DBP to suppress its androgen production. MBP mainly downregulated Cyp11a1 and Hsd3b1 expression levels at 50 nM. However, 50 μM DBP downregulated Star, Hsd3b1, and Hsd17b3 expression levels and directly inhibited CYP11A1 and CYP17A1 activities. In conclusion, DBP is metabolized to more potent inhibitor MBP that downregulated the expression levels of some androgen biosynthetic enzymes