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Ultra-wide bandgap (UWBG) semiconductors are promising for many applications, such as power electronics and deep-ultraviolet photonics. In this research, UWBG β-phase magnesium gallium oxide (MgGaO) thin films with a bandgap of 5.1 eV were grown using low-temperature homo-buffer layers in a plasma-assisted molecular beam epitaxy system. The role of the growth temperature and thickness of low-temperature buffer layer on the quality of the active layer was studied using x-ray diffraction and transmission electron microscopy and by analyzing the properties of metal–semiconductor–metal photodetector devices based on these films. It is found that lower buffer growth temperature at 300 °C leads to higher crystal quality of active layer. For the same low buffer growth temperature, different crystal quality in the active layer is attained with different buffer layer thickness. A buffer layer thickness at 40 nm has the best active layer quality with the highest photo current under 265 nm illumination and long decay time as a result of reduced recombination of photo-generated carriers through fewer defects in the active layer.

To reach Earth’s surface, magma must ascend from the hot, ductile asthenosphere through cold and brittle rock in the lithosphere. It does so via fluid-filled fractures called dykes. While the continuum mechanics of ductile asthenosphere is well established, there has been little theoretical work on the cold and brittle regime where dyking and faulting occurs. Geodynamic models use plasticity to model fault-like behaviour; plasticity also shows promise for modelling dykes. Here we build on an existing model to develop a poro-viscoelastic–viscoplastic theory for two-phase flow across the lithosphere. Our theory addresses the deficiencies of previous work by incorporating (i) a hyperbolic yield surface, (ii) a plastic potential with control of dilatancy and (iii) a viscous regularization of plastic failure. We use analytical and numerical solutions to investigate the behaviour of this theory. Through idealized models and a comparison to linear elastic fracture mechanics, we demonstrate that this behaviour includes a continuum representation of dyking. Finally, we consider a model scenario reminiscent of continental rifting and demonstrate the consequences of dyke injection into the cold, upper lithosphere: a sharp reduction in the force required to rift.

When galaxies move through the intracluster medium (ICM) inside galaxy clusters, the ram pressure of the ICM can strip the gas from galaxies. The stripped gas forms tails on the trailing side. These galaxies are hence dubbed ‘jellyfish galaxies’. ESO 137-001 is a quintessential jellyfish galaxy located in the nearest rich cluster, the Norma cluster. Its spectacular multiphase tail has complex morphology and kinematics both from the imprinted galaxy’s interstellar medium (ISM) and as a result of the interactions between the stripped gas and the surrounding hot plasma, mediated by radiative cooling and magnetic fields. We study the kinematics of the multiphase tail using high-resolution observations of the ionized and the molecular gas in the entire structure. We calculate the velocity structure functions in moving frames along the tail and find that turbulence driven by Kelvin–Helmholtz (KH) instability quickly overwhelms the original ISM turbulence and saturates at ∼30 kpc. There is also a hint that the far end of the tail has possibly started to inherit pre-existing large-scale ICM turbulence likely caused by structure formation. Turbulence measured by the molecular gas is generally consistent with that measured by the ionized gas in the tail but has a slightly lower amplitude.more »Most of the measured turbulence is below the mean free path of the hot ICM (∼11 kpc). Using warm/cool gas as a tracer of the hot ICM, we find that the isotropic viscosity of the hot plasma must be suppressed below 0.01 per cent Spitzer level.

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Ram pressure stripping (RPS) is an important process to affect the evolution of cluster galaxies and their surrounding environment. We present a large MUSE mosaic for ESO 137-001 and its stripped tails, and study the detailed distributions and kinematics of the ionized gas and stars. The warm, ionized gas is detected to at least 87 kpc from the galaxy and splits into three tails. There is a clear velocity gradient roughly perpendicular to the stripping direction, which decreases along the tails and disappears beyond ∼45 kpc downstream. The velocity dispersion of the ionized gas increases to ∼80 km s−1 at ∼20 kpc downstream and stays flat beyond. The stars in the galaxy disc present a regular rotation motion, while the ionized gas is already disturbed by the ram pressure. Based on the observed velocity gradient, we construct the velocity model for the residual galactic rotation in the tails and discuss the origin and implication of its fading with distance. By comparing with theoretical studies, we interpreted the increased velocity dispersion as the result of the oscillations induced by the gas flows in the galaxy wake, which may imply an enhanced degree of turbulence there. We also compare the kinematic properties of the ionizedmore »gas and molecular gas from ALMA, which shows they are co-moving and kinematically mixed through the tails. Our study demonstrates the great potential of spatially resolved spectroscopy in probing the detailed kinematic properties of the stripped gas, which can provide important information for future simulations of RPS.

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Geophysical observations at some mid-ocean ridges document an across-axis asymmetry in indicators of magma production. Other observations are interpreted as showing non-monotonic variations in the depth of the lithosphere–asthenosphere boundary. These patterns are inconsistent with the classical models of mantle corner flow and half-space cooling. To investigate this discrepancy, we use models of coupled magma/mantle dynamics beneath mid-ocean ridges in which phase densities are determined by melt–residue partitioning of iron and magnesium, and bulk density is affected by residual porosity. Our models predict that emergent gradients in density drive ridge-local convection. In particular, we show that convective upwelling is enhanced by porous buoyancy and suppressed by compositional buoyancy. Despite this suppression, models that include both compositional and porous buoyancy are more sensitive to long-wavelength mantle heterogeneity than models with porous buoyancy alone. This sensitivity enables models to readily form across-axis asymmetry of upwelling. In some cases, it leads to lithospheric delamination and time-dependent, small-scale convection. We conclude that melting-induced buoyancy effects may explain the magmatic asymmetry and variations in lithospheric thickness that are inferred from observations.

In pursuit of higher inference accuracy, deep neural network (DNN) models have significantly increased in complexity and size. To overcome the consequent computational challenges, scalable chiplet-based accelerators have been proposed. However, data communication using metallic-based interconnects in these chiplet-based DNN accelerators is becoming a primary obstacle to performance, energy efficiency, and scalability. The photonic interconnects can provide adequate data communication support due to some superior properties like low latency, high bandwidth and energy efficiency, and ease of broadcast communication. In this paper, we propose SPACX: a Silicon Photonics-based Chiplet ACcelerator for DNN inference applications. Specifically, SPACX includes a photonic network design that enables seamless single-chiplet and cross-chiplet broadcast communications, and a tailored dataflow that promotes data broadcast and maximizes parallelism. Furthermore, we explore the broadcast granularities of the photonic network and implications on system performance and energy efficiency. A flexible bandwidth allocation scheme is also proposed to dynamically adjust communication bandwidths for different types of data. Simulation results using several DNN models show that SPACX can achieve 78% and 75% reduction in execution time and energy, respectively, as compared to other state-of-the-art chiplet-based DNN accelerators.

The security of manycore systems has become increasingly critical. In system-on-chips (SoCs), Hardware Trojans (HTs) manipulate the functionalities of the routing components to saturate the on-chip network, degrade performance, and result in the leakage of sensitive data. Existing HT detection techniques, including runtime monitoring and state-of-the-art learning-based methods, are unable to timely and accurately identify the implanted HTs, due to the increasingly dynamic and complex nature of on-chip communication behaviors. We propose AGAPE, a novel Generative Adversarial Network (GAN)-based anomaly detection and mitigation method against HTs for secured on-chip communication. AGAPE learns the distribution of the multivariate time series of a number of NoC attributes captured by on-chip sensors under both HT-free and HT-infected working conditions. The proposed GAN can learn the potential latent interactions among different runtime attributes concurrently, accurately distinguish abnormal attacked situations from normal SoC behaviors, and identify the type and location of the implanted HTs. Using the detection results, we apply the most suitable protection techniques to each type of detected HTs instead of simply isolating the entire HT-infected router, with the aim to mitigate security threats as well as reducing performance loss. Simulation results show that AGAPE enhances the HT detection accuracy by 19%, reducesmore »network latency and power consumption by 39% and 30%, respectively, as compared to state-of-the-art security designs.« less