Diagnostics for Sandia's Hypersonic Shock Tunnel
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Phase transformations are widely invoked as a source of rheological weakening during subduction, continental collision, mantle convection and various other geodynamic phenomena. However, despite more than half a century of research, the likelihood and magnitude of such weakening in nature remain poorly constrained. Here we use experiments performed on a synchrotron beamline to reveal transient weakening of up to three orders of magnitude during the polymorphic quartz to coesite (SiO 2 ) and olivine to ringwoodite (Fe 2 SiO 4 ) phase transitions. Weakening becomes increasingly prominent as the transformation outpaces deformation. We suggest that this behaviour is broadly applicable among silicate minerals undergoing first-order phase transitions and examine the likelihood of weakening due to the olivine-spinel, (Mg,Fe) 2 SiO 4 , transformation during subduction. Modelling suggests that cold, wet slabs are most susceptible to transformational weakening, consistent with geophysical observations of slab stagnation in the mantle transition zone beneath the western Pacific. In conclusion, our study highlights the importance of incorporating transformational weakening into geodynamic simulations and provides a quantitative basis for doing so.
We report a search for neutrino oscillations to sterile neutrinos under a model with three active and one sterile neutrinos (3+1 model). This analysis uses the NOvA detectors exposed to the NuMI beam, running in neutrino mode. The data exposure, 13.6 × 10 20 protons on target, doubles that previously analyzed by NOvA, and the analysis is the first to use 𝜈 𝜇 charged-current interactions in conjunction with neutral-current interactions. Neutrino samples in the near and far detectors are fitted simultaneously, enabling the search to be carried out over a Δ𝑚$^{2}_{41}$ range extending 2 (3) orders of magnitude above (below) 1 eV 2 . NOvA finds no evidence for active-to-sterile neutrino oscillations under the 3+1 model at 90% confidence level. New limits are reported in multiple regions of parameter space, excluding some regions currently allowed by IceCube at 90% confidence level. We additionally set the most stringent limits for anomalous 𝜈 𝜏 appearance for Δ𝑚$^{2}_{41}$ ≤ 3 eV 2 .
Double- and single-differential cross sections for inclusive charged-current 𝜈 𝜇 -nucleus scattering are reported for the kinematic domain 0 to 2 GeV/𝑐 in three-momentum transfer and 0 to 2 GeV in available energy, at a mean 𝜈 𝜇 energy of 1.86 GeV. The measurements are based on an estimated 995,760 𝜈 𝜇 charged-current (CC) interactions in the scintillator medium of the NOvA Near Detector. The subdomain populated by 2-particle-2-hole (2p2h) reactions is identified by the cross section excess relative to predictions for 𝜈 𝜇 -nucleus scattering that are constrained by a data control sample. Models for 2-particle-2-hole processes are rated by 𝜒 2 comparisons of the predicted-versus-measured 𝜈 𝜇 CC inclusive cross section over the full phase space and in the restricted subdomain. Shortfalls are observed in neutrino generator predictions obtained using the theory-based València and SuSAv2 2p2h models.
Ultrafast light-matter interactions inspire potential functionalities in picosecond optoelectronic applications. However, achieving directional carrier dynamics in metals remains challenging due to strong carrier scattering within a multiband environment, typically expected for isotropic carrier relaxation. In this study, we demonstrate epitaxial RuO 2 /TiO 2 (110) heterostructures grown by hybrid molecular beam epitaxy to engineer polarization selectivity of ultrafast light-matter interactions via anisotropic strain engineering. Combining spectroscopic ellipsometry, x-ray absorption spectroscopy, and optical pump-probe spectroscopy, we revealed the strong anisotropic transient optoelectronic response at an excitation energy of 1.58 eV in strain-engineered RuO 2 /TiO 2 (110) heterostructures along both in-plane [001] and [1$\bar1$0] crystallographic directions. Theoretical analysis identifies strain-induced modifications in band nesting as the underlying mechanism for enhanced anisotropic carrier relaxation observed at this excitation energy. These findings establish epitaxial strain engineering as a powerful tool for tuning anisotropic optoelectronic responses with near-infrared excitations in metallic systems, paving the way for next-generation polarization-sensitive ultrafast optoelectronic devices.
Neutrino-nucleus cross section measurements are critical for future neutrino oscillation analyses. However, our models to describe them require further refinement, and a deeper understanding of the underlying physics is essential for future neutrino oscillation experiments to realize their ambitious physics goals. Current neutrino cross section measurements provide clear deficiencies in neutrino interaction modeling, but almost all are reported averaged over broad neutrino fluxes, rendering their interpretation challenging. Using the concept of deep underground neutrino experiment-precision reaction independent spectrum measurement (DUNE-PRISM)—a movable near detector that samples multiple off axis positions—neutrino interaction measurements can be used to construct narrow virtual fluxes (less than 100 MeV wide). These fluxes can be used to extract charged-current neutrino-nucleus cross sections as functions of outgoing lepton kinematics within specific neutrino energy ranges. Based on a dedicated simulation with realistic event statistics and flux-related systematic uncertainties, but assuming an almost-perfect detector, we run a feasibility study demonstrating how DUNE-PRISM data can be used to measure muon neutrino charged-current integrated and differential cross sections over narrow fluxes. We find that this approach enables a largely model-independent reconstruction of powerful observables, including energy transfer, typically accessible only in electron scattering measurements, but that large exposures may be required for differential cross section measurements with few-percentage statistical uncertainties.
This paper reports on the capabilities in reconstructing and identifying atmospheric neutrino interactions in one of the Deep Underground Neutrino Experiment’s (DUNE) far detector modules, a liquid argon time projection chamber (LArTPC) with horizontal drift (FD-HD) of ionization electrons. The reconstruction is based upon the workflow developed for DUNE’s long-baseline oscillation analysis, with some necessary machine-learning models’ retraining and the addition of features relevant only to atmospheric neutrinos such as the neutrino direction reconstruction. Where relevant, the impact of the detection of the charged particles of the hadronic system is emphasized, and comparisons are carried out between the case when lepton-only information is considered in the reconstruction (as is the case for many neutrino oscillation experiments), versus when all particles identified in the LArTPC were included. Three neutrino direction reconstruction methods have been developed and studied for the atmospheric analyses: using lepton-only information, using all reconstructed particles, and using only correlations from reconstructed hits. The results indicate that incorporating more than just lepton information significantly improves the resolution of both neutrino direction and energy reconstruction. The angle reconstruction algorithms developed in this work result in no strong dependence on particle direction for reconstruction efficiencies or neutrino flavor identification. This comprehensive review of the reconstruction of atmospheric neutrinos in DUNE’s FD-HD LArTPC is the first step towards developing a first neutrino oscillation sensitivity analysis, which will ready DUNE for its first measurements.
We present the measurement of 𝜋 + -argon inelastic cross sections using the ProtoDUNE single-phase liquid argon time projection chamber in the incident 𝜋 + kinetic energy range of 500–800 MeV in multiple exclusive channels (absorption, charge exchange, and the remaining inelastic interactions). The results of this analysis are important inputs to simulations of liquid argon neutrino experiments such as the Deep Underground Neutrino Experiment and the Short Baseline Neutrino program at Fermi National Accelerator Laboratory. They will be employed to improve the modeling of final state interactions within neutrino event generators used by these experiments, as well as the modeling of 𝜋 + -argon secondary interactions within the liquid argon. This is the first measurement of 𝜋 + -argon absorption at this kinetic energy range as well as the first ever measurement of 𝜋 + -argon charge exchange.
DUNE (Deep Underground Neutrino Experiment) is a long-baseline neutrino oscillation experiment currently under construction, whose far detectors will be the largest liquid argon time projection chambers ever built. This detector design calls for custom-built cryogenic front-end electronics to meet its performance requirements. This paper describes the charge readout electronics that will be used in the DUNE horizontal drift (HD) far detector and presents performance results using data from the ProtoDUNE-HD detector, a 770 ton liquid argon time projection chamber operated at the CERN Neutrino Platform in 2024 that served as the final prototype of the DUNE HD design.
The 2x2 Demonstrator, a prototype for the Deep Underground Neutrino Experiment (DUNE) liquid argon (LAr) Near Detector, was exposed to the Neutrinos from the Main Injector (NuMI) neutrino beam at Fermi National Accelerator Laboratory (Fermilab). This detector is a prototype of a new modular design for a liquid argon time-projection chamber (LArTPC), comprising a two-by-two array of four modules, each further segmented into two optically isolated LArTPCs. The 2x2 Demonstrator features a number of pioneering technologies, including a low-profile resistive field shell to establish drift fields, native 3D ionization pixelated imaging, and a high-coverage dielectric light readout system. The 2.4-tonne active mass detector is flanked upstream and downstream by supplemental solid-scintillator tracking planes, repurposed from the MINERvA experiment, which track ionizing particles exiting the argon volume. The antineutrino beam data collected by the detector over a 4.5 day period in 2024 include over 30,000 neutrino interactions in the LAr active volume—the first neutrino interactions reported by a DUNE detector prototype. During its physics-quality run, the 2x2 Demonstrator operated at a nominal drift field of 500 V/cm and maintained good LAr purity, with a stable electron lifetime of approximately 1.25 ms. This paper describes the detector and supporting systems, summarizes the installation and commissioning, and presents the initial validation of collected NuMI beam and off-beam self-triggers. In addition, it highlights observed interactions in the detector volume, including candidate muon antineutrino events.
We present a high-statistics measurement of muon antineutrino-induced charged-current neutral pion production on a hydrocarbon target using the NOvA near detector. The differential cross sections as functions of the momenta and angles of the outgoing pion and muon, the squared four-momentum transfer, and the invariant mass of the hadronic system at an average neutrino energy of 2 GeV are measured and compared with predictions from various neutrino interaction models. The results agree with the GENIE prediction but suggest that other models underestimate the cross section in the Δ(1232) resonance region. These results represent the most precise measurement of antineutrino-induced neutral pion production to date.
Advancements in synthesis science are revolutionizing the way we create atomically precise materials. Techniques like molecular beam epitaxy (MBE) have set the benchmark for addressing long-standing questions in materials science by leveraging improved control over the composition and structure of existing materials and enabling materials discovery. In this review, we discuss recent innovations in MBE that are redefining its capabilities, enabling the fabrication of ultra-pure, defect-engineered films and the stabilization of metastable phases that were previously unattainable. These advancements are unlocking new opportunities in electronic, magnetic, and quantum technologies, where the precise tuning of material properties is essential for advancing device functionality and performance.
Eddy covariance data are critical for inferring ecosystem water use strategies. Yet, such inferences are sensitive to a range of assumptions applied across studies, hindering our understanding of water use strategies within and across eddy covariance sites. A recent analysis across 151 FLUXNET2015 and AmeriFlux-FLUXNET datasets found that poor model performance was the key driver of non-robust inferences of ecosystem water use strategies. Here, we leverage this previous analysis to (i) identify the specific assumptions that improve inference model performance across most sites, (ii) explain the mechanisms behind the performance improvements, and (iii) check whether better performance improves water use inference. We find that the common practice of fitting a model to canopy conductance (G c ) derived from the evapotranspiration (ET) observations, rather than to observed ET itself, artificially amplifies data errors and degrades the model performance. Next, accounting for vegetation dynamics by applying a growing season filter or incorporating satellite LAI data improves performance, but the former practice may remove soil water stress periods. Lastly, using the leaf-to-air vapor pressure deficit (VPD l ) derived from ET observations as a model input may artificially inflate performance. Based on these results, we recommend selecting observed ET (rather than derived G c ) as the response variable, carefully accounting for vegetation dynamics, and avoiding derived VPD l as a model input; these best practices improve model performance by c. 20% and robustness by c. 80% across all eddy covariance sites. Nevertheless, the performance improvements do not always correspond to more robust inference of water use strategies, as model parameter selection and surface energy budget closure corrections still strongly influence the ecosystem water use parameter estimation in a site-specific manner.
Overall reactions in interconnected networks exhibit net, forward, and reverse rates that are governed by both constitutive elementary steps in the pathway of interest and branching elementary steps that lead to alternative products. Accordingly, steps in branching pathways exhibit negative net, forward, and reverse degrees of rate control, as they reduce reaction flux to the desired product. We here contextualize the forward and reverse degrees of rate control in terms of kinetic resistances (inverse of rates) and leverage the additive nature of kinetic resistance to decouple kinetic driving forces contributed by constitutive elementary steps and branching points (nodal species) in interconnected networks. Regardless of the network connectivity, forward and reverse degrees of rate control are shown to converge at equilibrium. Away from equilibrium, we identify two critical features of interconnected networks: stoichiometric regularity─condition where all stoichiometric numbers are unity─and pathway symmetry around nodal species─condition where branching pathways share the same rate constants, stoichiometry, and species concentrations/activities─that result in (i) equal forward, reverse, and consequently net degrees of rate control and (ii) forward and reverse degrees of rate control that exhibit constant offsets, respectively, across all extents of reaction. Furthermore, our discourse further provides a mathematical description for the influence of stoichiometric irregularity and pathway asymmetry on forward and reverse degrees of rate control. Altogether, the presented work details the effects of network (inter)connectivity and stoichiometry on reaction kinetics and, in doing so, establishes general protocols for capturing these effects as additive terms in the formulation of forward and reverse degrees of rate control.
Spin glasses are inherently dynamical. Taken properly, measurements of these materials can capture their dynamics and provide a wealth of insight into the physics of the spin glass state. In this methods review, two magnetometry methods are directly compared–ac and dc. Because these measurements are taken differently, the resulting data of each method will contain different information about spin glass behavior. This review will specifically focus on how the out-of-equilibrium effects of aging, rejuvenation, and memory manifest in each of these techniques, and how to construct protocols to measure these effects. We then describe the physical significance of each type of measurement and how to interpret their results. Finally, we explicitly detail which applications are most appropriate for which method. This will help the reader select the most helpful technique to carry out their own future experiments.
Here, we recommend that stomatal slope parameters (g 1 ) be inferred by inversion so that variations in g 1 may be attributed to variations physiological and environmental conditions. Understanding g1 will advance predictions of plant gas exchange and performance under global climate.
Pre-chamber combustion is an advanced ignition strategy that has been shown to enhance spark ignition (SI) combustion stability in natural gas (NG) engines by providing distributed ignition sites from turbulent jets and enhancing main-chamber turbulence. Pre-chamber combustion has been proven especially advantageous compared to SI in ultra-lean and dilute operating conditions. This work involves experimental investigation of the effects of varying passive pre-chamber nozzle configuration on pre-chamber and main chamber combustion under simulated exhaust gas recirculation (EGR) dilution (0 and 20%) conditions in a heavy-duty, single-cylinder, optically accessible NG engine at stoichiometric fuel-air ratio. Pre-chamber nozzle configurations include four pre-chambers with constant nozzle area to pre-chamber volume ratio (A/V) with different nozzle sizes and orientations and one configuration with larger nozzles. The optical engine is operated in a skip-fire sequence consisting of 18 motored cycles followed by two consecutive fired cycles to elucidate the effect of combustion residuals (internal EGR) on combustion evolution. Pressure-based diagnostics are used to monitor pre-chamber and subsequent main chamber combustion, and optical diagnostics include high-speed OH* chemiluminescence to visualize the development of pre-chamber jets and the resulting ignition of the main chamber charge. Heat release analysis of the in-cylinder pressure data indicates that a faster pre-chamber pressure rise does not always translate into faster main-chamber combustion. The pre-chamber with the smallest nozzle diameter produced the highest pre-chamber pressure rise and fastest combustion under non-diluted conditions. However, dilution delays the main chamber ignition for smaller nozzles despite a comparable rise in pre-chamber pressure compared to configurations with larger nozzles. This effect is more pronounced for cycles with in-cylinder combustion residuals in addition to external dilution. Additionally, it was observed that pre-chambers with swirling nozzles have a faster pressure rise in the pre-chamber and main chamber under dilute conditions. Optical diagnostics suggest that the main reason for the delay between the pre-chamber pressure rise and main-chamber combustion lies in jet quenching and delayed re-ignition, which can even lead to misfire if jets emitted from small nozzles combined with dilution fail to re-ignite.
With the increasing number of electric vehicles (EV), the smart transportation system is becoming more closely related to the smart energy system in a smart city. However, because of the high complexity, dynamics, and large-scale of these two systems, it is challenging to study their operation problems systematically, especially in severe conditions, e.g., the 2021 winter Texas power traffic crisis. With artificial intelligence, federated learning, edge computing, and automatic control, a digital twin based smart city is proposed in this paper and it focuses on two applications: smart transportation and smart energy grid. Both systems are presented in a structured design manner with several components in the digital twin system, which also contains many real-implementations of different scenarios. The proposed digital twin of a smart city provides a potential clue for the problems mentioned above.