Hot electron relaxation in Type-II quantum wells.

A photovoltaic device fabricated with conventional zincblende materials can use the Type-II quantum well structure, which spatially separates electrons and holes, to reduce their recombination rate. In order to obtain higher power conversion efficiency, it is desirable to preserve more energetic carriers by engineering a phonon "bottleneck," a mismatch between the gaps in the well and barrier phonon structure. Such a mismatch leads to poor phonon transport and therefore prevents energy from leaving the system in the form of heat. In this paper, we perform a superlattice phonon calculation to verify the "bottleneck" effect and build on this a model to predict the steady state of the hot electrons under photoexcitation. We describe the electrons and phonons with a coupled Boltzmann equation system and numerically integrate it to get the steady state. We find that inhibited phonon relaxation does lead to a more out-of-equilibrium electron distribution and discuss how this might be enhanced. We examine the different behaviors obtained for various combinations of recombination and relaxation rates and their experimental signatures.

Quantum-electrodynamical time-dependent density functional theory within Gaussian atomic basis.

Inspired by the formulation of quantum-electrodynamical time-dependent density functional theory (QED-TDDFT) by Rubio and co-workers [Flick et al., ACS Photonics 6, 2757-2778 (2019)], we propose an implementation that uses dimensionless amplitudes for describing the photonic contributions to QED-TDDFT electron-photon eigenstates. This leads to a Hermitian QED-TDDFT coupling matrix that is expected to facilitate the future development of analytic derivatives. Through a Gaussian atomic basis implementation of the QED-TDDFT method, we examined the effect of dipole self-energy, rotating-wave approximation, and the Tamm-Dancoff approximation on the QED-TDDFT eigenstates of model compounds (ethene, formaldehyde, and benzaldehyde) in an optical cavity. We highlight, in the strong coupling regime, the role of higher-energy and off-resonance excited states with large transition dipole moments in the direction of the photonic field, which are automatically accounted for in our QED-TDDFT calculations and might substantially affect the energies and compositions of polaritons associated with lower-energy electronic states.

Automatic learning of topological phase boundaries.

Topological phase transitions, which do not adhere to Landau's phenomenological model (i.e., a spontaneous symmetry breaking process and vanishing local order parameters), have been actively researched in condensed matter physics. Machine learning of topological phase transitions has generally proved difficult due to the global nature of the topological indices. Only recently has the method of diffusion maps been shown to be effective at identifying changes in topological order. However, previous diffusion map results required adjustments of two hyperparameters: a data length scale and the number of phase boundaries. In this article we introduce a heuristic that requires no such tuning. This heuristic allows computer programs to locate appropriate hyperparameters without user input. We demonstrate this method's efficacy by drawing remarkably accurate phase diagrams in three physical models: the Haldane model of graphene, a generalization of the Su-Schreiffer-Haeger model, and a model for a quantum ring with tunnel junctions. These diagrams are drawn, without human intervention, from a supplied range of model parameters.

Line of Dirac Nodes in Hyperhoneycomb Lattices.

We propose a family of structures that have "Dirac loops," closed lines of Dirac nodes in momentum space, on which the density of states vanishes linearly with energy. Those lattices all possess the planar trigonal connectivity present in graphene, but are three dimensional. We show that their highly anisotropic and multiply connected Fermi surface leads to quantized Hall conductivities in three dimensions for magnetic fields with toroidal geometry. In the presence of spin-orbit coupling, we show that those structures have topological surface states. We discuss the feasibility of realizing the structures as new allotropes of carbon.

Using normal modes to calculate and optimize thermal conductivity in functionalized macromolecules.

The quest for high thermal conductivity materials has led to nanocomposites incorporating macromolecular materials with excellent thermal conductivity, such as carbon nanotubes and graphene nanoribbons, in a matrix of poorer thermal conductivity. To minimize the interface thermal resistance the stiff, incorporated materials can be chemically functionalized with various side chains. We report here an efficient theoretical method using normal modes to calculate the thermal conductivity of such systems and show how the participation ratio of these modes can be used to evaluate different choices for functionalization. We use this method to examine how effective different alkane chains improve the heat flux through a graphene nanosheet.

Computational modeling of the thermal conductivity of single-walled carbon nanotube-polymer composites.

A computational model was developed to study the thermal conductivity of single-walled carbon nanotube (SWNT)-polymer composites. A random walk simulation was used to model the effect of interfacial resistance on the heat flow in different orientations of SWNTs dispersed in the polymers. The simulation is a modification of a previous model taking into account the numerically determined thermal equilibrium factor between the SWNTs and the composite matrix material. The simulation results agreed well with reported experimental data for epoxy and polymethyl methacrylate (PMMA) composites. The effects of the SWNT orientation, weight fraction and thermal boundary resistance on the effective conductivity of composites were quantified. The present model is a useful tool for the prediction of the thermal conductivity within a wide range of volume fractions of the SWNTs, so long as the SWNTs are not in contact with each other. The developed model can be applied to other polymers and solid materials, possibly even metals.

Atomic-scale observation of temperature and pressure driven preroughening and roughening.

Preroughening and roughening transitions are observed on the GaAs(001) surface using scanning tunneling microscopy. By tuning the substrate temperature or As4 pressure the surface morphology can be made free of islands, covered with one monolayer high islands or covered with islands on top of islands forming a wedding-cake-type structure. These three distinct surface morphologies are classified as ordered flat (OF), disordered flat (DOF), and rough within the restricted solid-on-solid model. Here, the DOF phase is macroscopically flat; however, an up-down-up-down step pattern persists across the entire surface. Using this model we have determined the next-nearest-neighbor interaction energy to be about 0.05 eV.