Modeling and simulation details.The time-domain thermoreflectance (TDTR) experiments measure the transient thermoreflectance response of metallic heaters in the short time domain (0~6 ns), with subpicosecond temporal resolution. Since the change in thermoreflectance is linearly proportional to the change in temperature, measuring thermoreflectance is equivalent to measuring the temperature of the metallic heaters [1]. To gain insight into the thermal transport in the experiments, we numerically solve the full spectral Boltzmann transport equation (BTE) under the relaxation time approximation and compare the BTE solution to the Fourier prediction to obtain the effective thermal conductivities across a wide range of length scales [2]. The simulation geometry consists of a periodic heater array sitting on top of the underlying substrate, mimicking the experimental sample configurations. Since the structure is periodic, the system can be studied by looking at the thermal transport in one single pitch of the repeated structure by applying periodic boundary conditions. Both the BTE and Fourier simulations are performed under transient heating conditions.To solve the BTE, we used the recently developed variance-reduced Monte Carlo (VRMC) simulation technique [3][4] which substantially improves the computational efficiency and accuracy through the introduction of a reference state. In the VRMC model, only the deviation from the reference state is simulated. The deviational BTE is shown in Eq. (S1):

The human major histocompatibility complex (MHC) region has been shown to be associated with numerous diseases. However, it remains a challenge to pinpoint the causal variants for these associations because of the extreme complexity of the region. We thus sequenced the entire 5-Mb MHC region in 20,635 individuals of Han Chinese ancestry (10,689 controls and 9,946 patients with psoriasis) and constructed a Han-MHC database that includes both variants and HLA gene typing results of high accuracy. We further identified multiple independent new susceptibility loci in HLA-C, HLA-B, HLA-DPB1 and BTNL2 and an intergenic variant, rs118179173, associated with psoriasis and confirmed the well-established risk allele HLA-C*06:02. We anticipate that our Han-MHC reference panel built by deep sequencing of a large number of samples will serve as a useful tool for investigating the role of the MHC region in a variety of diseases and thus advance understanding of the pathogenesis of these disorders.

Improvements in thermoelectric material performance over the past two decades have largely been based on decreasing the phonon thermal conductivity. Enhancing the power factor has been less successful in comparison. In this work, a peak power factor of ∼106 μW·cm −1 ·K −2 is achieved by increasing the hot pressing temperature up to 1,373 K in the p-type half-Heusler Nb 0.95 Ti 0.05 FeSb. The high power factor subsequently yields a record output power density of ∼22 W·cm −2 based on a single-leg device operating at between 293 K and 868 K. Such a high-output power density can be beneficial for large-scale power generation applications.half-Heusler | thermoelectric | power factor | carrier mobility | output power density T he majority of industrial energy input is lost as waste heat. Converting some of the waste heat into useful electrical power will lead to the reduction of fossil fuel consumption and CO 2 emission. Thermoelectric (TE) technologies are unique in converting heat into electricity due to their solid-state nature. The ideal device conversion efficiency of TE materials is usually characterized by (1)where ZT is the average thermoelectric figure of merit (ZT) between the hot side temperature (T H ) and the cold side temperature (T C ) of a TE material and is defined aswhere PF, T, κ tot , S, σ, κ L , κ e , and κ bip are the power factor, absolute temperature, total thermal conductivity, Seebeck coefficient, electrical conductivity, lattice thermal conductivity, electronic thermal conductivity, and bipolar thermal conductivity, respectively. Higher ZT corresponds to higher conversion efficiency. One effective approach to enhance ZT is through nanostructuring that can significantly enhance phonon scattering and consequently result in a much lower lattice thermal conductivity compared with that of the unmodified bulk counterpart (2). This approach works well for many inorganic TE materials, such as Bi 2 Te 3 (2), IV-VI semiconductor compounds (3, 4), lead-antimony-silver-tellurium (LAST) (5), skutterudites (6), clathrates (7), CuSe 2 (8), Zintl phases (9), half-Heuslers (10-12), MgAgSb (13, 14), Mg 2 (Si, Ge, Sn) (15, 16), and others.However, nanostructuring is effective only when the grain size is comparable to or smaller than the phonon mean free path (MFP). In compounds with a phonon MFP shorter than the nanosized grain diameters, nanostructuring might impair the electron transport more than the phonon transport, thus potentially decreasing the power factor and ZT. In contrast, improving ZT by boosting the power factor has not yet been widely studied (17)(18)(19)(20). To the best of our knowledge, there is no theoretical upper limit applied to the power factor. Additionally, the output power density ω of a device with hot side at T H and cold side at T C is directly related to the power factor by (21)where L is the leg length of the TE material and PF is the averaged power factor over the leg. As contact resistance limits the reduction of length L, higher power factor favors higher power density when h...

The Chinese horseshoe bat (Rhinolophus sinicus), reservoir host of severe acute respiratory syndrome coronavirus (SARS-CoV), carries many bat SARS-related CoVs (SARSr-CoVs) with high genetic diversity, particularly in the spike gene. Despite these variations, some bat SARSr-CoVs can utilize the orthologs of human SARS-CoV receptor, angiotensin-converting enzyme 2 (ACE2), for entry. It is speculated that the interaction between bat ACE2 and SARSr-CoV spike proteins drives diversity. Here, we have identified a series of R. sinicus ACE2 variants with some polymorphic sites involved in the interaction with the SARS-CoV spike protein. Pseudoviruses or SARSr-CoVs carrying different spike proteins showed different infection efficiency in cells transiently expressing bat ACE2 variants. Consistent results were observed by binding affinity assays between SARS- and SARSr-CoV spike proteins and receptor molecules from bats and humans. All tested bat SARSr-CoV spike proteins had a higher binding affinity to human ACE2 than to bat ACE2, although they showed a 10-fold lower binding affinity to human ACE2 compared with their SARS-CoV counterpart. Structure modeling revealed that the difference in binding affinity between spike and ACE2 might be caused by the alteration of some key residues in the interface of these two molecules. Molecular evolution analysis indicates that some key residues were under positive selection. These results suggest that the SARSr-CoV spike protein and R. sinicus ACE2 may have coevolved over time and experienced selection pressure from each other, triggering the evolutionary arms race dynamics. Importance Evolutionary arms race dynamics shape the diversity of viruses and their receptors. Identification of key residues which are involved in interspecies transmission is important to predict potential pathogen spillover from wildlife to humans. Previously, we have identified genetically diverse SARSr-CoV in Chinese horseshoe bats. Here, we show the highly polymorphic ACE2 in Chinese horseshoe bat populations. These ACE2 variants support SARS- and SARSr-CoV infection but with different binding affinity to different spike proteins. The higher binding affinity of SARSr-CoV spike to human ACE2 suggests that these viruses have the capacity of spillover to humans. The positive selection of residues at the interface between ACE2 and SARSr-CoV spike protein suggests a long-term and ongoing coevolutionary dynamics between them. Continued surveillance of this group of viruses in bats is necessary for the prevention of the next SARS-like disease.

Heat conduction in semiconductors and dielectrics depends upon their phonon mean free paths that describe the average travelling distance between two consecutive phonon scattering events. Nondiffusive phonon transport is being exploited to extract phonon mean free path distributions. Here, we describe an implementation of a nanoscale thermal conductivity spectroscopy technique that allows for the study of mean free path distributions in optically absorbing materials with relatively simple fabrication and a straightforward analysis scheme. We pattern 1D metallic grating of various line widths but fixed gap size on sample surfaces. The metal lines serve as both heaters and thermometers in time-domain thermoreflectance measurements and simultaneously act as wire-grid polarizers that protect the underlying substrate from direct optical excitation and heating. We demonstrate the viability of this technique by studying length-dependent thermal conductivities of silicon at various temperatures. The thermal conductivities measured with different metal line widths are analyzed using suppression functions calculated from the Boltzmann transport equation to extract the phonon mean free path distributions with no calibration required. This table-top ultrafast thermal transport spectroscopy technique enables the study of mean free path spectra in a wide range of technologically important materials.