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Metal nanoparticle has been a promising option for fillers in thermal interface materials due to its low cost and ease of fabrication. However, nanoparticle aggregation effect is not well understood because of its complexity. Theoretical models, like effective medium approximation model, barely cover aggregation effect. In this work, we have fabricated nickel–epoxy nanocomposites and observed higher thermal conductivity than effective medium theory predicts. Smaller particles are also found to show higher thermal conductivity, contrary to classical models indicate. A two-level effective medium approximation (EMA) model is developed to account for aggregation effect and to explain the size-dependent enhancement of thermal conductivity by introducing local concentration in aggregation structures.

First-principles calculations are performed to study the absorption spectra and electron-vibration coupling of titanium-doped sapphire (Ti:Al2O3). Geometry optimization shows a local structure relaxation after the doping of Ti. Electronic band structure calculation shows that five additional dopant energy bands are observed around the band gap of Al2O3, and are attributed to the five localized d orbitals of the Ti dopant. The optical absorption spectra are then predicted by averaging the oscillator strength during a 4 ps first-principles molecular dynamics (MD) trajectory, and the spectra agree well with the experimental results. Electron-vibration coupling is further investigated by studying the response of the ground and excited states to the Eg vibrational mode, for which a configuration coordinate diagram is obtained. Stokes shift effect is observed, which confirms the red shift of emission spectra of Ti:sapphire. This work offers a quantitative understanding of the optical properties and crystal-field theory of Ti-doped sapphire. The first-principles calculation framework developed here can also be followed to predict the optical properties and study the electron-vibration coupling in other doped materials.

We review the progress on laser cooling of solids. Laser cooling of ion-doped solids and semiconductors is based on the anti-Stokes fluorescence, where the emitted photons have a mean energy higher than that of the absorbed photons. The thermodynamic analysis shows that this cooling process does not violate the second law, and that the achieved efficiency is much lower than the theoretical limit. Laser cooling has experienced rapid progress in rare-earth-ion doped solids in the last decade, with the temperature difference increasing from 0.3to92K. Further improvements can be explored from the perspectives of materials and structures. Also, theories need to be developed, to provide guidance for searching enhanced cooling performance. Theoretical predictions show that semiconductors may be cooled more than ion-doped solids, but no success in bulk cooling has been achieved yet after a few attempts (due to the fluorescence trapping and nonradiative recombination). Possible solutions are discussed, and net cooling is expected to be realized in the near future.

In recent years, there has been interest in employing atomistic computations to inform macroscale thermal transport analyses. In heat conduction simulations in semiconductors and dielectrics, for example, classical molecular dynamics (MD) is used to compute phonon relaxation times, from which material thermal conductivity may be inferred and used at the macroscale. A drawback of this method is the noise associated with MD simulation (here after referred to as MD noise), which is generated due to the possibility of multiple initial configurations corresponding to the same system temperature. When MD is used to compute phonon relaxation times, the spread may be as high as 20%. In this work, we propose a method to quantify the uncertainty in thermal conductivity computations due to MD noise, and its effect on the computation of the temperature distribution in heat conduction simulations. Bayesian inference is used to construct a probabilistic surrogate model for thermal conductivity as a function of temperature, accounting for the statistical spread in MD relaxation times. The surrogate model is used in probabilistic computations of the temperature field in macroscale Fourier conduction simulations. These simulations yield probability density functions (PDFs) of the spatial temperature distribution resulting from the PDFs of thermal conductivity. To allay the cost of probabilistic computations, a stochastic collocation technique based on generalized polynomial chaos (gPC) is used to construct a response surface for the variation of temperature (at each physical location in the domain) as a function of the random variables in the thermal conductivity model. Results are presented for the spatial variation of the probability density function of temperature as a function of spatial location in a typical heat conduction problem to establish the viability of the method.

Recent advances in nanofabrication technology have facilitated the development of arrays of nanostructures in the classical or quantum confinement regime, e.g., single-walled carbon nanotube (SWCNT) arrays with long-range order across macroscopic dimensions. So far, an accurate generalized method of modeling radiative properties of these systems has yet to be realized. In this work, a multiscale computational approach combining first-principles methods based on density functional theory (DFT) and classical electrodynamics simulations based on the finite element method (FEM) is described and applied to the calculations of optical properties of macroscopic SWCNT arrays. The first-principles approach includes the use of the GW approximation and Bethe–Salpeter methods to account for excited electron states, and the accuracy of these approximations is assessed through evaluation of the absorption spectra of individual SWCNTs. The fundamental mechanisms for the unique characteristics of extremely low reflectance and high absorptance in the near-IR are delineated. Furthermore, opportunities to tune the optical properties of the macroscopic array are explored.

Thermal properties and transport control are important for many applications, for example, low thermal conductivity is desirable for thermoelectrics. Knowledge of mode-wise phonon properties is crucial to identify dominant phonon modes for thermal transport and to design effective phonon barriers for thermal transport control. In this paper, we adopt time-domain (TD) and frequency-domain (FD) normal-mode analyses to investigate mode-wise phonon properties and to calculate phonon dispersion relations and phonon relaxation times in bismuth telluride. Our simulation results agree with the previously reported data obtained from ultrafast time-resolved measurements. By combining frequency-dependent anharmonic phonon group velocities and lifetimes, mode-wise thermal conductivities are predicted to reveal the contributions of heat carriers with different wavelengths and polarizations.