Resonant Acoustic Mixing of Dense Pastes: Role of Adhesion and Viscosity
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Materials science↗
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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
Design and Modeling of the Charge Readout of a SiMOS Quantum Dot with a Single Electron Transistor and CryoCMOS
Single electron spin qubits trapped in SiMOS quantum dots are a promising technology for scaling to thousand- or million-qubit systems due to their compatibility with mature CMOS manufacturing processes. A readout system that combines a single electron transistor with a custom cryogenic CMOS amplification and digitization chain offers key advantages by avoiding the use of bulky RF components or room-temperature interconnects. We present design techniques and simulation results for an optimized qubit-SET cryoCMOS interface, culminating in the design of the QNDR1 ASIC, the first cryogenic readout ASIC designed under the Quandarum project, which targets the development of a many-channel spin qubit based detector for use in high energy physics.
Quinn, Adam [Fermilab] (ORCID:0009000605056371)↗
A Unified Tracer Analysis of DESI DR2 Baryon Acoustic Oscillations
We improve upon previous efforts to optimally combine overlapping galaxy samples in the DESI baryon acoustic oscillation analysis. By weighting each galaxy by its linear bias, overlapping galaxies are combined into a single, unified catalog, naturally avoiding double counting of cosmic volume and including all auto- and cross- information at the catalog level. Improvements over the previous effort include the addition of QSO out to $z=1.6$ to account for all overlapping DR2 tracers and redshift-dependent bias treatment to improve reconstruction. We report distance measurements using this unified tracer, and find them to be highly consistent with the baseline DR2 BAO analysis. We also test for tracer-dependent systematics within the DESI data, and find no evidence of tracer-dependent systematics within $0.8
Sanders, N. [Ohio U., Athens] (ORCID:0009000800202↗
Measurement of the t-channel single top quark cross section in proton-proton collisions at $\sqrt{s}=5.02$ TeV
The single top quark t-channel production cross section is measured in proton-proton collisions at the CERN LHC at $\sqrt{s}=5.02$ TeV, using data recorded with the CMS detector in 2017, corresponding to an integrated luminosity of 302 pb −1 , and resulting in the first CMS measurement of the process at that energy. Events with one electron or muon and two or more jets, among which at least one is identified as originating from a b quark fragmentation, are analyzed. The combined cross section of single top quark (tq) and single top antiquark ($\overline{\mathrm{t}}\mathrm{q}$) production is $\sigma \left(\mathrm{tq}+\overline{\mathrm{t}}\mathrm{q}\right)={25.5}_{-3.5}^{+3.6}{\left(\mathrm{stat}\right)}_{-3.9}^{+4.2}\left(\mathrm{syst}\right)\pm 0.5\left(\mathrm{lumi}\right)$ pb. The individual cross sections are measured to be $\sigma \left(\mathrm{tq}\right)={17.7}_{-2.7}^{+2.9}{\left(\mathrm{stat}\right)}_{-2.4}^{+2.6}\left(\mathrm{syst}\right)\pm 0.3\left(\mathrm{lumi}\right)$ pb and $\sigma \left(\overline{\mathrm{t}}\mathrm{q}\right)={6.7}_{-1.6}^{+2.4}{\left(\mathrm{stat}\right)}_{-2.5}^{+2.1}\left(\mathrm{syst}\right)\pm 0.1\left(\mathrm{lumi}\right)$ pb. Their ratio is measured to be ${\mathcal{R}}_{\mathrm{t}-\mathrm{ch}}={2.7}_{-0.8}^{+1.5}{\left(\mathrm{stat}\right)}_{-0.3}^{+1.2}\left(\mathrm{syst}\right)$. The absolute value of the Cabibbo-Kobayashi-Maskawa matrix element is found to be |f LV V tb | = 0.92 ± 0.09(exp) ± 0.01(theo). The measurements are in good agreement with the standard model predictions at next-to-next-to-leading order accuracy in quantum chromodynamics.
Hadron-Hadron Scattering↗
Elucidating the impact of stress states on grain boundary passivation in Ni-5Cr using the Rhines pack method
The oxidation behavior of a Ni–5Cr (at.%) alloy was evaluated at 420 ° C using the Rhines pack method and simultaneous tensile and compressive stress states via a miniature four-point bending fixture. At this moderate temperature, grain boundaries dominate mass transport and the resulting oxidation response. Oxidation produced approximately 1μm-wide protective Cr 2 O 3 films capping some grain boundaries and penetrative, intergranular Cr-rich oxides at other grain boundaries. Externally applied tensile and compressive stress during oxidation increased the prevalence of Cr 2 O 3 cap formation compared to no applied stress, with tensile stress resulting in more Cr 2 O 3 caps than compressive stress. The observed oxide cap morphology was similar across all test conditions. Regions under compressive stress showed an order of magnitude greater Cr depletion depth along the grain boundary. Chromium nitrides (CrN), likely from N contamination of the Rhines pack cell, were observed both at the oxide–metal interface and intergranularly within the alloy. Collectively these results demonstrate that applied stress promotes localized protective oxide cap formation over grain boundaries, with compressive stress additionally promoting deeper Cr depletion. Furthermore the experimental approach helped separate out the effects of stress on local oxide formation and grain boundary passivation.
4 point bend↗
Spectrophotometric study of erbium (III) speciation in chloride solutions from 25 to 75 °C
In this study, UV-Vis spectrophotometric experiments were conducted from 25 to 75 °C using Er-HClO4-bearing solutions with varying NaCl concentrations. The molar absorbance coefficient of Er3+ decreases with temperature, and the absorbance intensity gradually decreases with increasing mCl/mEr ratios. The number of absorbing species include Er3+ and ErCl2+ even at the highest mCl/mEr ratio. The formation constant (β 1 ) for the ErCl 2+ species was derived and fitted between 50 and 250 °C with existing literature values, yielding the following equation: logβ 1 0 = −22.4315 + 0.0345T + 3.9379·10 3 /T, where T is temperature in Kevin.
58 GEOSCIENCES↗
Ultrafast Proton-Coupled Electron Transfer Reactions at Unit Quantum Yield
Proton-coupled electron transfer (PCET) reactions mediate essential biological energy-conversion processes, yet dynamical experiments that distinguish concerted electron/proton motion from sequential electron-transfer/proton-transfer pathways are unprecedented on ultrafast time scales. Here we report a tightly coupled donor–spacer–acceptor assembly, NDI-Sp-PhOH/BI, that enables direct interrogation of light-triggered and ultrafast PCET dynamics. Photoexcitation of the naphthalene diimide chromophore drives charge separation forming NDI radical anion and benzimidazolium phenoxy radical (PhO●/BIH+) products with a 440 fs time constant, followed by thermal charge recombination on a 5 ps time scale. Transient visible/near-infrared and mid-infrared spectroscopies independently track electron and proton motion and reveal coincident formation and decay of the charge-separated PCET products, excluding detectable phenol radical cation or phenoxide intermediates expected for sequential electron transfer-proton transfer (ET-PT) pathways. Surface-hopping quasiclassical trajectory simulations demonstrate rapid proton relocation coupled to evolution from locally excited to charge-transfer states, congruent with a concerted mechanism. These combined spectroscopic and computational results establish NDI-Sp-PhOH/BI as an archetype for ultrafast, concerted PCET occurring with unit quantum yield; further, because this platform provides distinct electronic and vibrational spectroscopic handles in its ground, electronically excited, and charge-separated states, it provides new opportunities to characterize mechanistic crossover in biomimetic PCET systems.
10 SYNTHETIC FUELS↗
Resolving root causes of experiment discrepancies guided by machine learning
Abstract Scientists rely on accurate experimental data to explain nature and then harness this knowledge for applications addressing human needs. However, discrepancies between experiments of the same observable can impede scientific progress if one does not understand the underlying causes. Here, we developed a process that unravels data discrepancies by first using Bayesian machine learning to relate discrepancies to few of many, potentially biasing metadata features that encode experiment procedures. This machine learning output guides human experts to study discrepancy causes by simulating suspicious aspects of historical experiments or designing modern ones to address open questions. The study findings then lead to rejecting or correcting historical data on firm scientific bases. This process is demonstrated for the energy spectrum of neutrons emitted promptly (<1 ns) after fission of 252 Cf, a trusted nuclear physics Standard. It reduces the spread in experimental 252 Cf spectra by up to a factor of 6.
Neudecker, D. (ORCID:0000000339200627)↗
Automated scanning probe microscopy of combinatorial ferroelectric libraries: Gaussian-process-guided exploration and noise-aware experiment planning
Combinatorial materials libraries provide an efficient route for mapping composition–property relationships, but their broader impact depends on rapid, quantitative, and functionally relevant characterization. Scanning Probe Microscopy (SPM), including piezoresponse force microscopy (PFM), offers significant potential for quantitative, functionally relevant combi-library readouts. Here, we implement a fully automated SPM workflow for ferroelectric combinatorial libraries and benchmark Gaussian-process-based Bayesian optimization strategies for autonomous experiment planning. The workflow integrates automated probe motion, contact optimization, imaging, and dual amplitude resonance tracking-PFM spectroscopy, and uses scalarized spectroscopic observables to guide subsequent measurements. Stage motion, probe engagement, in-contact tuning, imaging, spectroscopy, and the choice of the next measurement location all proceed without human input. We demonstrate the approach on Sm-doped BiFeO 3 and Zn x Mg 1−x O libraries. By comparing vanilla Bayesian optimization with a measured-noise variant, we show that explicit treatment of local reproducibility can improve modeling of composition-dependent response when the measured variance is physically meaningful, but can also reduce robustness when variability is dominated by outliers or topographic artifacts. Furthermore, these results establish automated SPM as a bridge between combinatorial synthesis and quantitative functional characterization.
Liu, Yu [University of Tennessee, Knoxville, TN (U↗
The Role of Nuclear Data Sensitivities in Prompt α-Eigenvalue Predictions of Delayed Critical Benchmarks
Alpha (α) eigenvalues, which describe the logarithmic time derivative of the neutron population in a multiplying system, are integral to time-dependent behavior and diagnostic applications. However, uncertainties in the evaluated nuclear data can significantly impact the accuracy of transport simulations for such quantities. This work explores the use of machine learning models to predict two key outputs, α-eigenvalues and keff bias, using input features derived from α-eigenvalue sensitivities to nuclear data. The criticality safety benchmark models used in this study come from the International Handbook of Evaluated Criticality Safety Benchmark Experiments. Three models, random forest, XGBoost, and NGBoost, are trained on both energy-resolved and energy-summed α sensitivities. For the α-eigenvalue bias prediction, NGBoost achieved the highest R 2 (0.9476) using energy-resolved features, while XGBoost performed best using summed sensitivities. In contrast, when predicting the keff bias, all the models showed moderate predictive capability (best R 2 ≈ 0.72), as the mapping from the static α-sensitivities to the static keff bias was less direct. SHAP (SHapley Additive exPlanations) analysis was used to interpret the model predictions. Across both prediction tasks, the features associated with neutron capture [H-1 (n, γ)], uranium scattering reactions (such as 235 U elastic/inelastic), and actinide capture/fission reactions (such as 239 Pu and 234 U) were consistently identified as the most impactful. This highlights the key role of specific nuclear reactions and energy ranges in shaping both time-dependent and steady-state criticality behavior. These results demonstrated that α-sensitivities, despite being computed for time-dependent metrics, can provide valuable insights for predicting both α-eigenvalues and the keff bias. Moreover, machine learning models offer a promising pathway for uncovering important nuclear data dependencies and guiding future data evaluation efforts.
Nuclear data↗
Systematic Construction of Time-Dependent Hamiltonians for Microwave-Driven Josephson Circuits
Time-dependent electromagnetic drives are fundamental for controlling complex quantum systems, including superconducting Josephson circuits. In these devices, accurate time-dependent Hamiltonian models are imperative for predicting their dynamics and designing high-fidelity quantum operations. Existing numerical methods, such as black-box quantization (BBQ) and energy-participation ratio (EPR), excel at modeling the static Hamiltonians of Josephson circuits. However, these techniques do not fully capture the behavior of driven circuits stimulated by external microwave drives, nor do they include a generalized approach to account for the inevitable noise and dissipation that enter through microwave ports. Here, we introduce numerical techniques that leverage classical microwave simulations, efficiently executable in finite-element solvers, to obtain the time-dependent Hamiltonian of microwave-driven superconducting circuits with arbitrary geometries under charge, flux, or mixed electromagnetic modulation. Importantly, our techniques do not rely on a lumped-element description of the superconducting circuit, in contrast to previous approaches to tackling this problem. We demonstrate the versatility of our approach by characterizing the driven properties of realistic circuit devices in complex electromagnetic environments, including coherent dynamics due to charge and flux modulation, as well as drive-induced relaxation and dephasing. Our techniques offer a powerful toolbox for optimizing circuit designs and advancing practical applications in superconducting quantum computing.
Lu, Yao [Yale U.; Yale U. (main); Fermilab] (ORCID↗
Evidence of Z Z γ Production and Observation of 4 ℓ γ in Proton-Proton Collisions at s = 13 TeV
Evidence of the production of two Z bosons and a photon in proton-proton collisions is reported for the first time in CMS. The analysis uses data collected by the CMS experiment between 2016 and 2018 at a center-of-mass energy of 13 TeV, corresponding to an integrated luminosity of 138 fb - 1 . Evidence for the process p p → Z Z γ → 4 ℓ γ ( ℓ = e , μ ), with an observed (expected) significance of 3.7 (3.1) standard deviations in a fiducial region defined by p T γ > 20 GeV , | η γ | < 2.4 , Δ R ( ℓ , γ ) > 0.5 , m Z between 60 and 120 GeV, and the invariant mass of either of the two Z bosons combined with the photon ( m Z γ ) larger than 100 GeV, is reported. The measured (predicted) fiducial cross section is 60 - 22 + 27 ab ( 47.56 ± 0.04 ab ). Additionally, the inclusive production of p p → 4 ℓ γ is studied by removing the m Z γ requirement to include final state radiation where one Z boson decays to 2 ℓ γ , yielding an observed (expected) significance of 5.0 (4.2) standard deviations and a measured (predicted) fiducial cross section of 156 - 35 + 39 ab ( 99.97 ± 0.09 ab ).
Hayrapetyan, Aram [Yerevan Phys. Inst.]↗
Monte Carlo Event Generation with Continuous Normalizing Flows
We apply continuous normalizing flows trained with the flow matching method to the problem of phase-space sampling in Monte Carlo event generation for high-energy collider physics. Focusing on lepton-pair and top-quark pair production with multiple jets, the two computationally most expensive processes at the Large Hadron Collider, we train helicity-conditioned continuous normalizing flows to remap the random numbers used in matrix element evaluation. Compared to standard methods, we achieve unweighting efficiency improvements by factors of up to 184 and 25 for the two processes at their respective highest jet number, at the cost of an increased evaluation time. When combining the advantages of continuous normalizing flows with the fast evaluation times of coupling-layer-based flows, using the RegFlow approach, we find parton-level unweighted event generation walltime gains of about a factor of 10 at the highest jet numbers. These substantial gains highlight the promise of samplers based on machine learning for next-generation collider experiments.
Bothmann, Enrico [CERN; Gottingen U.] (ORCID:00000↗
Optical cycling on thorium monoxide for an improved test of fundamental symmetries
Optical cycling refers to repeated excitation and spontaneous emission on an electronic transition in an atom or molecule. Optical cycling in molecules can enable a wide range of quantum control and readout techniques, but unfortunately it has only been demonstrated on a small class of alkalilike or alkaline-earth-like molecules. Thorium monoxide (ThO), a molecule used in one of the most precise permanent electron electric dipole moment (eEDM) searches (ACME†) [Andreev et al., Nature (London) 562, 355 (2018)], does not fall into this category. In this work, we demonstrate the first optical cycling on this nonconventional class over a range of experimental parameter space, including laser intensity, polarization switching rate, and interaction time. We show that both the 𝐽 = 1 and 𝐽 = 2 rotational levels of ThO molecule are capable of cycling an average of 11(2) photons with a single laser, at scattering rates of 1.9(6) × 10 6 and 2.3(7) × 10 6 s −1 , respectively, before population is lost to other vibronic levels. We outline a scheme to apply this demonstrated optical cycling in an ACME-style eEDM measurement, improving the detection efficiency by over fourfold compared to noncycling fluorescence detection. This would lead to over a twofold enhancement in the statistical sensitivity of the eEDM search. This optical-cycling scheme can be further extended to scatter ∼100 photons, which would enable a wider range of quantum control and sensing using ThO molecules.
Atomic & molecular processes in external fields↗
Improving Process Level Understanding of Boundary Layer Winds over the Northeast U.S. Shelf: The Third Wind Forecast Improvement Project (WFIP3)
The third Wind Forecast Improvement Project (WFIP3), a U.S. Department of Energy and National Oceanic and Atmospheric Administration sponsored investigation, sought to improve understanding of the physical phenomena in the atmosphere and ocean that dictate the structure and variability of wind and thermodynamic fields within the marine atmospheric boundary layer. WFIP3 focused on mesoscale and submesoscale flows -- including sea breezes, low-level jets, low-level clouds, and coastal storms -- and the ability of advanced numerical model parameterizations to represent them within fully coupled oceanic and atmospheric modeling systems and foundational weather forecast models. WFIP3 conducted a comprehensive 18-month observational study over the Northeast U.S. outer continental shelf, a high-use coastal zone, using a 3D multiscale sensor array to highly resolve the temporal, vertical, and horizontal structure of the coupled atmospheric and oceanic boundary layers. Multiple land-based study sites adjacent to the coastal ocean observed surface meteorology and vertical profiles of atmospheric properties via passive infrared and microwave radiometers, active lidars and radars, and radiosondes. At sea, an array of surface flux buoys and two vertical profiling lidar buoys observed both atmospheric and oceanic properties, augmented by land-based oceanographic radar systems and routine ship-based surveys. Intensive observations of the marine atmospheric boundary layer over the ocean was done from an air-sea interaction flux tower and extended deployments of a large autonomous barge platform. Numerous critical forecasting phenomena were observed that are being evaluated within regional coupled and uncoupled modeling systems, including the National Oceanic and Atmospheric Administration's foundational High-Resolution Rapid Refresh forecast model.
Kirincich, Anthony↗
Neutron scattering for NiPS3
Inelastic magnetic spectra for NiPS3 as published in Phys. Rev. B 108, 104402, 2023; https://doi.org/10.1103/PhysRevB.108.104402 . Analysis scripts and SpinW code also included.
36 MATERIALS SCIENCE↗
COOPERATIVE RESEARCH AND DEVELOPMENT AGREEMENT (CRADA NO. TC02404) FINAL REPORT
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Materials science↗
3D Shock Breakout from a Red Supergiant
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Astronomy and AstroPhysics↗