Search

Model predictive control (MPC) algorithms can be sensitive to model mismatch when used in challenging nonlinear control tasks. In particular, the performance of MPC for vehicle control at the limits of handling suffers when the underlying model overestimates the vehicle's capabilities. In this work, we propose a risk-averse MPC framework that explicitly accounts for uncertainty over friction limits and tire parameters. Our approach leverages a sample-based approximation of an optimal control problem with a conditional value at risk (CVaR) constraint. This sample-based formulation enables planning with a set of expressive vehicle dynamics models using different tire parameters. Moreover, this formulation enables efficient numerical resolution via sequential quadratic programming and GPU parallelization. Experiments on a Lexus LC 500 show that risk-averse MPC unlocks reliable performance, while a deterministic baseline that plans using a single dynamics model may lose control of the vehicle in adverse road conditions.

Entropy or randomness represents a foundational security property in security-related operations, such as key generation. Key generation in turn is central to security protocols such as authentication and encryption. Physical unclonable functions (PUF) are hardware-based primitives that can serve as key generation engines in modern microelectronic devices and applications. PUFs derive entropy from manufacturing variations that exist naturally within and across otherwise identical copies of a device. However, the levels of random variations that represent entropy, which are strongly correlated to the quality of the PUF-generated bitstrings, vary from one manufacturer to another. In this paper, we evaluate entropy across a set of devices manufactured by three mainstream FPGA vendors, Xilinx, Altera and Microsemi. The devices selected for evaluation are considered low-end commercial devices to make the analysis relevant to IoT applications. The SiRF PUF is used in the evaluation, and is constructed nearly identically across the three vendor devices, setting aside minor differences that exist in certain logic element primitives used within the PUF architecture, and which have only a minor impact on our comparative analysis. The SiRF PUF uses a high-resolution time-to-digital converter (TDC) crafted from high-speed carry-chain logic embedded within each device to measure path delays in an engineered netlist of logic gates as a source of entropy. Therefore, our analysis includes an evaluation of actual path delay variation as it exists across the three device classes, as well as a statistical evaluation of the PUF-generated bitstrings. A reliablity analysis is also provided using data collected in industrial-standard temperature experiments to round out the evaluation of important statistical properties of the PUF., Comment: 15 pages, 22 figures, IEEE journal

In this study, we investigate in situ etching of \b{eta}-Ga2O3 in a metal-organic chemical vapor deposition (MOCVD) system using tert-Butyl chloride (TBCl). We report the successful etching of both heteroepitaxial (-201)-oriented and homoepitaxial (010)-oriented \b{eta}-Ga2O3 films over a wide range of substrate temperature, TBCl molar flows, and reactor pressures. We identify that the likely etchant is HCl (g) formed by the pyrolysis of TBCl in the hydrodynamic boundary layer above the substrate. The temperature dependence of the etch rate reveals two distinct regimes characterized by markedly different apparent activation energies. The extracted apparent activation energies suggest that at temperatures below ~800 {\deg}C the etch rate is likely limited by desorption of etch products, while at higher substrate temperatures chemisorption of HCl limits the etch rate. The relative etch rates of heteroepitaxial (-201) and homoepitaxial (010) \b{eta}-Ga2O3 were observed to scale by the ratio of the surface energies indicating an anisotropic etch. For (010) homoepitaxial films, relatively smooth post-etch surface morphology was achieved by tuning the etching parameters., Comment: 12 pages, 8 figures

Here we report that the source of Si impurities commonly observed on (010) $\beta-Ga_2O_3$ is from exposure of the surface to air. Moreover, we find that a 15 minute HF (49%) treatment reduces the Si density by approximately 1 order of magnitude on (010) $\beta-Ga_2O_3$ surfaces. This reduction in Si is critical for the elimination of the often observed parasitic conducting channel, which negatively affects transport properties and lateral transistor performance. After the HF treatment the sample must be immediately put under vacuum, for the Si fully returns within 10 minutes of additional air exposure. Lastly, we demonstrate that performing a 30 minute HF (49%) treatment on the substrate before growth has no deleterious effect on the structure or on the epitaxy surface after subsequent $Ga_2O_3$ growth.

Fabrication of superconducting nanomechanical resonators for quantum research, detectors and devices traditionally relies on a lithographic process, resulting in oscillators with sharp edges and a suspended length limited to a few 100 micrometres. We report a low-investment top-down approach to fabricating NbTi nanowire resonators with suspended lengths up to several millimetres and diameters down to 100 nanometres. The nanowires possess high critical currents and fields, making them a natural choice for magnetomotive actuation and sensing. This fabrication technique is independent of the substrate material, dimensions and layout and can readily be adapted to fabricate nanowire resonators from any metal or alloy with suitable ductility and yield strength. Our work thus opens access to a new class of nanomechanical devices with applications including microscopic and mesoscopic investigations of quantum fluids, detecting dark matter and fundamental materials research in one-dimensional superconductors in vacuum., Comment: 19 pages, 4 figures

X-ray diffraction (XRD) is an essential technique to determine a material's crystal structure in high-throughput experimentation, and has recently been incorporated in artificially intelligent agents in autonomous scientific discovery processes. However, rapid, automated and reliable analysis method of XRD data matching the incoming data rate remains a major challenge. To address these issues, we present CrystalShift, an efficient algorithm for probabilistic XRD phase labeling that employs symmetry-constrained pseudo-refinement optimization, best-first tree search, and Bayesian model comparison to estimate probabilities for phase combinations without requiring phase space information or training. We demonstrate that CrystalShift provides robust probability estimates, outperforming existing methods on synthetic and experimental datasets, and can be readily integrated into high-throughput experimental workflows. In addition to efficient phase-mapping, CrystalShift offers quantitative insights into materials' structural parameters, which facilitate both expert evaluation and AI-based modeling of the phase space, ultimately accelerating materials identification and discovery., Comment: 13 pages, 6 figures

Intermetallic Nb3Sn alloys have long been believed to form through Sn diffusion into Nb. However, our observations of significant oxygen content in Nb3Sn prompted an investigation of alternative formation mechanisms. Through experiments involving different oxide interfaces (clean HF-treated, native oxidized, and anodized), we demonstrate a thermodynamic route that fundamentally challenges the conventional Sn diffusion mechanism for Nb3Sn nucleation. Our results highlight the critical involvement of a SnOx intermediate phase. This new nucleation mechanism identifies the principles for growth optimization and new synthesis of high-quality Nb3Sn superconductors.

Surface structures on radio-frequency (RF) superconductors are crucially important in determining their interaction with the RF field. Here we investigate the surface compositions, structural profiles, and valence distributions of oxides, carbides, and impurities on niobium (Nb) and niobium-tin (Nb3Sn) in situ under different processing conditions. We establish the underlying mechanisms of vacuum baking and nitrogen processing in Nb and demonstrate that carbide formation induced during high-temperature baking, regardless of gas environment, determines subsequent oxide formation upon air exposure or low-temperature baking, leading to modifications of the electron population profile. Our findings support the combined contribution of surface oxides and second-phase formation to the outcome of ultra-high vacuum baking (oxygen processing) and nitrogen processing. Also, we observe that vapor-diffused Nb3Sn contains thick metastable oxides, while electrochemically synthesized Nb3Sn only has a thin oxide layer. Our findings reveal fundamental mechanisms of baking and processing Nb and Nb3Sn surface structures for high-performance superconducting RF and quantum applications

The ability to reliably maximize tire force usage would improve the safety of autonomous vehicles, especially in challenging edge cases. However, vehicle control near the limits of handling has many challenges, including robustly contending with tire force saturation, balancing model fidelity and computational efficiency, and coordinating inputs with the lower level chassis control system. This work studies Nonlinear Model Predictive Control for limit handling, specifically adapting to changing tire-road conditions and maximally allocating tire force utilization. We present a novel hierarchical framework that combines a single-track model with longitudinal weight transfer dynamics in the predictive control layer, with lateral brake distribution occurring at the chassis control layer. This vehicle model is simultaneously used in an Unscented Kalman Filter for online friction estimation. Comparative experiments on a full-scale vehicle operating on a race track at up to 95% of maximum tire force usage demonstrate the overall practical effectiveness of this approach., Comment: Preprint of accepted paper in Field Robotics

The safe deployment of autonomous vehicles relies on their ability to effectively react to environmental changes. This can require maneuvering on varying surfaces which is still a difficult problem, especially for slippery terrains. To address this issue we propose a new approach that learns a surface-aware dynamics model by conditioning it on a latent variable vector storing surface information about the current location. A latent mapper is trained to update these latent variables during inference from multiple modalities on every traversal of the corresponding locations and stores them in a map. By training everything end-to-end with the loss of the dynamics model, we enforce the latent mapper to learn an update rule for the latent map that is useful for the subsequent dynamics model. We implement and evaluate our approach on a real miniature electric car. The results show that the latent map is updated to allow more accurate predictions of the dynamics model compared to a model without this information. We further show that by using this model, the driving performance can be improved on varying and challenging surfaces.

Superconducting radio-frequency (SRF) resonators are critical components for particle accelerator applications, such as free-electron lasers, and for emerging technologies in quantum computing. Developing advanced materials and their deposition processes to produce RF superconductors that yield nanoohms surface resistances is a key metric for the wider adoption of SRF technology. Here we report ZrNb(CO) RF superconducting films with high critical temperatures (Tc) achieved for the first time under ambient pressure. The attainment of a Tc near the theoretical limit for this material without applied pressure is promising for its use in practical applications. A range of Tc, likely arising from Zr doping variation, may allow a tunable superconducting coherence length that lowers the sensitivity to material defects when an ultra-low surface resistance is required. Our ZrNb(CO) films are synthesized using a low-temperature (100 - 200 C) electrochemical recipe combined with thermal annealing. The phase transformation as a function of annealing temperature and time is optimized by the evaporated Zr-Nb diffusion couples. Through phase control, we avoid hexagonal Zr phases that are equilibrium-stable but degrade Tc. X-ray and electron diffraction combined with photoelectron spectroscopy reveal a system containing cubic ZrNb mixed with rocksalt NbC and low-dielectric-loss ZrO2. We demonstrate proof-of-concept RF performance of ZrNb(CO) on an SRF sample test system. BCS resistance trends lower than reference Nb, while quench fields occur at approximately 35 mT. Our results demonstrate the potential of ZrNb(CO) thin films for particle accelerator and other SRF applications.

Workbench-size particle accelerators, enabled by Nb3Sn-based superconducting radio-frequency (SRF) cavities, hold the potential of driving scientific discovery by offering a widely accessible and affordable source of high-energy electrons and X-rays. Thin-film Nb3Sn RF superconductors with high quality factors, high operation temperatures, and high-field potentials are critical for these devices. However, surface roughness, non-stoichiometry, and impurities in Nb3Sn deposited by conventional Sn-vapor diffusion prevent them from reaching their theoretical capabilities. Here we demonstrate a seed-free electrochemical synthesis that pushes the limit of chemical and physical properties in Nb3Sn. Utilization of electrochemical Sn pre-deposits reduces the roughness of converted Nb3Sn by five times compared to typical vapor-diffused Nb3Sn. Quantitative mappings using chemical and atomic probes confirm improved stoichiometry and minimized impurity concentrations in electrochemically synthesized Nb3Sn. We have successfully applied this Nb3Sn to the large-scale 1.3 GHz SRF cavity and demonstrated ultra-low BCS surface resistances at multiple operation temperatures, notably lower than vapor-diffused cavities. Our smooth, homogeneous, high-purity Nb3Sn provides the route toward high efficiency and high fields for SRF applications under helium-free cryogenic operations.

Bridging functionalities in periodic mesoporous organosilicas (PMOs) enable new functionalities for a wide range of applications. Bridge cleavage is frequently observed during anneals required to form porous structures, yet the mechanism of these bridge cleavages has not been completely resolved. Here, we reveal these chemical transformations and their kinetic pathways on sub-millisecond timescales induced by laser heating. By varying anneal times and temperatures, the transformation dynamics of bridge cleavage and structural transformations, and their activation energies, are determined. The structural relaxation time for individual reactions and their effective local heating time are determined and compared, and results directly demonstrate the manipulation of different molecules through kinetic control of the sequence of reactions. By isolating and understanding the earliest stage of structural transformations, this study identifies the kinetic principles for new synthesis and post-processing routes to control individual molecules and reactions in PMOs and other material systems with multi-functionalities.

We report the use of suboxide molecular-beam epitaxy (S-MBE) to grow $\beta$-Ga$_2$O$_3$ at a growth rate of ~1 ${\mu}$m/h with control of the silicon doping concentration from 5x10$^{16}$ to 10$^{19}$ cm$^{-3}$. In S-MBE, pre-oxidized gallium in the form of a molecular beam that is 99.98\% Ga$_2$O, i.e., gallium suboxide, is supplied. Directly supplying Ga2O to the growth surface bypasses the rate-limiting first step of the two-step reaction mechanism involved in the growth of $\beta$-Ga$_2$O$_3$ by conventional MBE. As a result, a growth rate of ~1 ${\mu}$m/h is readily achieved at a relatively low growth temperature (T$_{sub}$ = 525 $^\circ$C), resulting in films with high structural perfection and smooth surfaces (rms roughness of < 2 nm on ~1 ${\mu}$m thick films). Silicon-containing oxide sources (SiO and SiO$_2$) producing an SiO suboxide molecular beam are used to dope the $\beta$-Ga$_2$O$_3$ layers. Temperature-dependent Hall effect measurements on a 1 ${\mu}$m thick film with a mobile carrier concentration of 2.7x10$^{17}$ cm$^{-3}$ reveal a room-temperature mobility of 124 cm$^2$ V$^{-1}$ s$^{-1}$ that increases to 627 cm$^2$ V$^{-1}$ s$^{-1}$ at 76 K; the silicon dopants are found to exhibit an activation energy of 27 meV. We also demonstrate working MESFETs made from these silicon-doped $\beta$-Ga$_2$O$_3$ films grown by S-MBE at growth rates of ~1 ${\mu}$m/h., Comment: 19 pages, 7 figures, 2 tables, 2 pages supplementary materials

Coronavirus can be transmitted through the air by close proximity to infected persons. Commercial aircraft are a likely way to both transmit the virus among passengers and move the virus between locations. The importance of learning about where and how coronavirus has entered the United States will help further our understanding of the disease. Air travelers can come from countries or areas with a high rate of infection and may very well be at risk of being exposed to the virus. Therefore, as they reach the United States, the virus could easily spread. On our analysis, we utilized machine learning to determine if the number of flights into the Washington DC Metro Area had an effect on the number of cases and deaths reported in the city and surrounding area.