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DOE OSTI2022

Resonant ultrasound spectroscopy for crystalline samples containing initial strain

Resonant ultrasound spectroscopy (RUS) is a mature and robust technique for the nondestructive characterization of the elastic properties of solids capable of providing the elastic constants of anisotropic crystalline solids. The traditional method is based on assuming that the solid is linear elastic and, therefore, obeys a linearized Hookean constitutive relationship (Hooke’s law). In this work, an alternative constitutive law is provided that allows for an initial strain or prestrain to be present stemming from residual stress. Then, the constitutive relationship is integrated into the RUS framework. The model is demonstrated using a realistic prestrain field obtained by simulating shot-peening processing of a polycrystalline Cu sample. The sensitivity of the resonances to the developed prestrain is established and discussed. This work allows researchers to consider the influence of initial strain or residual stress in their samples and the potential influence on accurate elastic constant estimates. The model also supports the potential of RUS for the nondestructive characterization of prestrain in materials.

42 ENGINEERING↗

DOE OSTI2020

Phenological responses of temperate and boreal trees to warming depend on ambient spring temperatures, leaf habit, and geographic range

Changes in plant phenology associated with climate change have been observed globally. What is poorly known is whether and how phenological responses to climate warming will differ from year to year, season to season, habitat to habitat, or species to species. Here, we present 5 y of phenological responses to experimental warming for 10 subboreal tree species. Research took place in the open-air B4WarmED experiment in Minnesota. The design is a two habitat (understory and open) × three warming treatments (ambient, +1.7 °C, +3.4 °C) factorial at two sites. Phenology was measured twice weekly during the growing seasons of 2009 through 2013. We found significant interannual variation in the effect of warming and differences among species in response to warming that relate to geographic origin and plant functional group. Moreover, responses to experimental temperature variation were similar to responses to natural temperature variation. Warming advanced the date of budburst more in early compared to late springs, suggesting that to simulate interannual variability in climate sensitivity of phenology, models should employ process-based or continuous development approaches. Differences among species in timing of budburst were also greater in early compared to late springs. Our results suggest that climate change—which will make most springs relatively “early”—could lead to a future with more variable phenology among years and among species, with consequences including greater risk of inappropriately early leafing and altered interactions among species.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2026

Search for Higgsinos in final states with low-momentum lepton-track pairs at 13 TeV

We present a search for the pair production of Higgsinos in final states with large missing transverse momentum and either two reconstructed muons or a reconstructed lepton (muon or electron) and an isolated track. The analyzed data correspond to proton-proton collisions with an integrated luminosity of 137 fb −1 , collected by the CMS experiment at $\sqrt{𝑠}$ =13 TeV in 2016, 2017, and 2018. The signal scenario assumes four nearly mass degenerate Higgsino mass eigenstates: two neutralino states $\tilde{𝜒}^0_2$ and $\tilde{𝜒}^0_1$ with a small mass difference in the range 1–10 GeV and two chargino states $\tilde{𝜒}^±_1$ with an intermediate mass. The analysis focuses on the decay of the heavier neutralino into the lighter one and a virtual 𝑍 boson, which decays into two same-flavor leptons. The leptons have small transverse momentum and/or a small opening angle between the identified muons. An isolated track is used to recover events in which only one of the two leptons is identified. Multivariate discriminants are used to enhance the sensitivity by efficiently rejecting backgrounds from SM processes or misreconstructed tracks and/or leptons. The search explores a unique phase space and probes a previously unexplored region of the signal model parameter space. Mass differences between the two neutralinos are probed down to 1.5 GeV, assuming a Higgsino mass of 100 GeV. The maximum excluded Higgsino mass is 115 GeV.

Hayrapetyan, A. [Yerevan Physics Institute]↗

DOE OSTI2026

Evaluation of an event-driven 3FI ASIC for spectroscopic X-ray detection with synchrotron radiation

The novel design and evaluation on the NSLS-II beamline of the 3FI application-specific integrated circuit (ASIC) bump-bonded to a simple, planar, 2D segmented silicon sensor are presented. The ASIC was developed for full-field fluorescence spectral X-ray imaging (3FI). It is a small-scale prototype that features a square array of 32 × 32 pixels, and the size of the pixels is 100 µm × 100 µm. The ASIC was implemented in a 65 nm CMOS integrated circuit fabrication process. Each pixel incorporates a charge-sensitive amplifier, a shaping filter, a discriminator, a peak detector and a sample-and-hold circuit, allowing detection of events and storage of signal amplitudes. The system operates in a frameless event-driven readout mode, outputting analog values for threshold-triggered events, allowing high-speed multi-element X-ray fluorescence data acquisition. The 3FI ASIC achieves per-channel spectrometric performance at a power consumption of only 200 µW per pixel, with nearly all dissipation confined to the analog front-end. An energy resolution is measured at the level of 308 eV full width at half-maximum (FWHM) at 8.04 keV (Cu Kα), and 138 eV FWHM at 3.69 keV (Ca Kα). This per-pixel capability makes the prototype suitable for in situ trace element microanalysis in biological and environmental studies. Moreover, the frameless architecture of the detector is designed to address limitations of conventional X-ray fluorescence microscopy, which typically requires mechanical scanning, by enabling continuous high-throughput data acquisition in future full-field implementations.

47 OTHER INSTRUMENTATION↗

DOE OSTI2022

Effect of Thermal Expansion Coefficient, Viscosity and Melting Range in Simulation of PCM Embedded Heat Exchangers With and Without Fins

Phase change material heat exchangers (PCMHX) have an important role in integrating renewable energy systems. PCMHX can offer high storage density at various temperatures of interest and can be used for grid load shifting purposes. Numerical models enable engineers to estimate PCMHX performance for different design parameters and operating conditions. Modeling phase change phenomena is challenging due to the complex time-dependent nature of the process. The accuracy of models is highly sensitive to PCM thermo-physical properties. Thermal expansion coefficient (β), viscosity (μ) and melting temperature range (MR) of a PCM are important properties, especially when natural convection is not negligible. In PCMHX modeling, using less than accurate values for these properties can have significant impact on the simulation outcomes. These properties and discussions thereof are not readily available in the literature. This paper presents a brief review of the literature and a numerical study investigating the model sensitivity to the above-mentioned properties for PCMHX with and without fins. CFD is used to evaluate the charging (melting) phenomena. The study quantifies the impact of uncertainty in these properties on the melting rate and temperature profile. Constant wall temperature was considered as heat source with no heat loss to ambient. Here, the results show that β and μ has significant effect on the melting rate and evolution of the melting front. For a non-finned domain when comparing results for different published values of β and μ, the deviation in melting time can be up to 12.9% and 57.6% respectively. For high wall temperatures, change in melting range did not impact melting time. But when the wall temperature is reduced, up to 9.8% deviation in melting time is observed.

CFD↗

DOE OSTI2024

Adaptive optical third-harmonic generation microscopy for in vivo imaging of tissues

Third-harmonic generation microscopy is a powerful label-free nonlinear imaging technique, providing essential information about structural characteristics of cells and tissues without requiring external labelling agents. In this work, we integrated a recently developed compact adaptive optics module into a third-harmonic generation microscope, to measure and correct for optical aberrations in complex tissues. Taking advantage of the high sensitivity of the third-harmonic generation process to material interfaces and thin membranes, along with the 1,300-nm excitation wavelength used here, our adaptive optical third-harmonic generation microscope enabled high-resolution in vivo imaging within highly scattering biological model systems. Examples include imaging of myelinated axons and vascular structures within the mouse spinal cord and deep cortical layers of the mouse brain, along with imaging of key anatomical features in the roots of the model plant Brachypodium distachyon. In all instances, aberration correction led to enhancements in image quality.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2021

Group-velocity-dispersion engineering of tantala integrated photonics

Designing integrated photonics, especially to leverage Kerr-nonlinear optics, requires accurate and precise knowledge of the refractive index across the visible to infrared spectral ranges. Tantala ( T a 2 O 5 ) is an emerging material platform for integrated photonics and nanophotonics that offers broadband ultralow loss, moderately high nonlinearity, and advantages for scalable and heterogeneous integration. We present refractive index measurements on a thin film of tantala, and we explore the efficacy of this data for group-velocity-dispersion (GVD) engineering with waveguide and ring-resonator devices. In particular, the observed spectral extent of supercontinuum generation in fabricated waveguides and the wavelength dependence of free spectral range (FSR) in optical resonators provide a sensitive test of our integrated photonics design process. Our work opens up new design possibilities with tantala, including with octave-spanning soliton microcombs.

Black, Jennifer A.↗

DOE OSTI2020

Ablating nanoscale pores in crystalline quartz using laser-induced micro-plasmas in tri-layer structures

We demonstrate a novel approach for achieving rapid, consistent, and controllable micro-pore fabrication in single-crystalline quartz. These micro-pores are essential for applications in biology, i.e., studying ion channels in general and mechano-sensitive channels (MSC) in particular. The fabrication process consists of direct material ablation using pulsed UV light from a 193 nm excimer laser. These pulses ablate single-crystalline quartz chips by burning a laser-induced plasma in a tri-layer structure. Controllable plasma confinement and thus pore size is achieved by sandwiching a thin layer of a selected organic solution between the quartz chip and different substrates. This solution causes the confined micro-plasma to generate special ablation conditions, to create uniformly sized and shaped nanopores.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Emerging magnetic materials for electric vehicle drive motors

Abstract Increasing demand for electric vehicles (EVs) is increasing demand for the permanent magnets that drive their motors, as approximately 80% of modern EV drivetrains rely on high-performance permanent magnets to convert electricity into torque. In turn, these high-performance permanent magnets rely on rare earth elements for their magnetic properties. These elements are “critical” (i.e., at risk of limiting the growth of renewable energy technologies such as EVs), which motivates an exploration for alternative materials. In this article, we overview the relevant fundamentals of permanent magnets, describe commercialized and emerging materials, and add perspective on future areas of research. Currently, the leading magnetic material for EV motors is Nd 2 Fe 14 B, with samarium-cobalt compounds (SmCo 5 and Sm 2 Co 17 ) providing the only high-performing commercialized alternative. Emerging materials that address criticality concerns include Sm 2 Fe 17 N 3 , Fe 16 N 2 , and the L1 0 structure of FeNi, which use lower cost elements that produce similar magnetic properties. However, these temperature-sensitive materials are incompatible with current metallurgical processing techniques. We provide perspective on how advances in low-temperature synthesis and processing science could unlock new classes of high-performing magnetic materials for a paradigm shift beyond rare earth-based magnets. In doing so, we explore the question: What magnetic materials will drive future EVs? Graphical abstract

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2020

Machine-Learning Enabled Evaluation of Probability of Piping Degradation In Secondary Systems of Nuclear Power Plants

The transition to condition-based, risk-informed automated maintenance will contribute to a significant reduction of operations and maintenance costs that account for the majority of nuclear power generation costs. Furthermore, of the operations and maintenance costs in U.S. plants, approximately 80% are labor costs. To address the issue of rising operating costs and economic viability, technologies used to perform online monitoring of piping and other secondary system structural components in commercial nuclear power plants (NPPs) are under evaluation. These online monitoring systems have the potential to identify when a more detailed inspection is needed using real time measurements, rather than at a pre-determined inspection interval thus reducing the maintenance cost. This paper describes distributed high-temperature stable fiber sensors fabricated in optical fibers through a roll-to-roll laser direct writing process using femtosecond lasers. Using phase-sensitive optical time domain reflectometry, distributed acoustic and vibration sensors can be developed and deployed to critical components and systems in NPPs to perform active measurements with spatial resolution down to 0.5-meter throughout the piping systems. Complex acoustic and vibration signatures harnessed by distributed sensors are registered and analyzed by artificial intelligence algorithms for degradation detection and flaw identification. Piping elbows with machined-in flaws were instrumented with fiber sensors. High-spatial-resolution data were used to develop and validate machine learning algorithms, including both linear and nonlinear regression, and classification. Additionally, classification and sensor analysis were also performed for data analysis. The paper concludes with recommendations and future work on applications of machine learning enabled high-resolution fiber sensors for piping degradation monitoring in current or future NPPs.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2020

BioGeoChemistry of Actinides (LLNL SFA OBER - SBR FY20 Program Management and Performance Report)

The focus of the BioGeoChemistry of Actinides SFA is to identify and quantify the biogeochemical processes and the underlying mechanisms that control actinide mobility in an effort to reliably predict and control the cycling and migration of actinides in the environment. The research approach includes: (1) Field Studies (Research Thrust 1) that capture actinide behavior on the timescale of decades and (2) Fundamental Laboratory Studies (Research Thrust 2) that isolate specific biogeochemical processes observed in the field. These research thrusts are underpinned by the unique capabilities and staff expertise at Lawrence Livermore National Laboratory (LLNL), allowing the BioGeoChemistry of Actinides SFA to advance our understanding of actinide migration behavior in the environment, and serve as an international resource for environmental radiochemistry research (Figure 1). Research Thrusts 1 and 2 are guided by broad central hypotheses: Thrust 1 Hypothesis: Biogeochemical processes occurring on the timescale of years to decades lead to greater actinide recalcitrance in sediments and limit their migration in surface and groundwater. Thrust 2 Hypothesis: Long-term biogeochemical processes include mineral and surface alteration, which leads to stabilization of actinide surface associations or incorporation into mineral precipitates. Our strategic goal is to use the knowledge gained from our Science Plan to advance our understanding of the behavior of actinides, providing DOE with the scientific basis for remediation and long-term stewardship of DOE’s legacy sites and, more broadly, increasing our understanding of transport phenomena in environmental systems sciences with a particular emphasis on environmentally relevant (long-term) timescales. Although our focus is on actinide biogeochemistry, the increased focus on biogeochemistry at unique Test Bed locations associated with this SFA is providing fundamental information on redox processes and associated microbiological processes that control the cycling of redox sensitive metals under dynamic and transient biogeochemical conditions.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

DOE OSTI2021

Improving GCM Representation of Convective Cloud Microphysics by Using ARM Raman Lidar and Cloud Radar Observations

The overall objective of this Department of Energy (DOE) Atmospheric System Research (ASR) funded project is to improve the representation of convective cloud microphysics in global climate models (GCMs) and check it by comparing the model simulations with observations. We have derived the cloud ice water content by synthesizing ARM Raman lidar (RL) and cloud radar observations at the Atmospheric Radiation Measurement (ARM) sites. Noting that the simulated anvil clouds in terms of their macro- and micro-physical properties are sensitive to the parameterization of convective microphysical processes, observed ice water content in anvil clouds provides a useful constraint on these parameterizations. We have improved the convective microphysics parameterization scheme by (1) considering sedimentation for cloud ice crystals that do not fall in the original scheme, (2) applying a new terminal velocity parameterization that depends on the environmental conditions for convective snow, (3) adding a new hydrometeor category, “rimed ice,” to the original four-class (cloud liquid, cloud ice, rain, and snow) scheme, and (4) allowing convective clouds to detrain snow particles into stratiform clouds. We have examined the impact of improved convective cloud microphysics parameterization on the simulated global climate from GCM simulations.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

ORNL Neutron Cross Section Measurements of 90 Zr NCSP ND-1 Task [Slides]

Luiz Leal's idea to integrate the experimental uncertainties, covariances, and sensitivities in this workflow and centralize the process at one location led to the creation of a cohesive tool for data testing. It has been practiced for more than two decades by the NCS and ND groups at ORNL. The development and use of the ORNL codes TSUNAMI and TSURFER within SCALE made it possible. Today, it has been extended to SAMINT which enables the coupling of differential and integral data evaluation in a continuous-energy framework.

43 PARTICLE ACCELERATORS↗

DOE OSTI2024

Emerging magnetic materials for electric vehicle drive motors [Slides]

Increasing demand for electric vehicles (EVs) is increasing demand for the permanent magnets that drive their motors, as approximately 80% of modern EV drivetrains rely on high-performance permanent magnets to convert electricity into torque. In turn, these high-performance permanent magnets rely on rare earth elements for their magnetic properties. These elements are "critical" (i.e., at risk of limiting the growth of renewable energy technologies such as EVs), which motivates an exploration for alternative materials. In this article, we overview the relevant fundamentals of permanent magnets, describe commercialized and emerging materials, and add perspective on future areas of research. Currently, the leading magnetic material for EV motors is Nd 2 Fe 14 B, with samarium-cobalt compounds (SmCo 5 and Sm 2 Co 17 ) providing the only high-performing commercialized alternative. Emerging materials that address criticality concerns include Sm 2 Fe 17 N 3 , Fe 16 N 2 , and the L10 structure of FeNi, which use lower cost elements that produce similar magnetic properties. However, these temperature-sensitive materials are incompatible with current metallurgical processing techniques. We provide perspective on how advances in low-temperature synthesis and processing science could unlock new classes of high-performing magnetic materials for a paradigm shift beyond rare earth-based magnets. In doing so, we explore the question: What magnetic materials will drive future EVs?

42 ENGINEERING↗

DOE OSTI2026

Advancing Detector R&D for High-Pressure Gaseous Argon TPCs in Precision Neutrino Physics

High-pressure gaseous argon time projection chambers (HPgTPCs) represent an emerging detector paradigm for neutrino physics, combining increased target density with the intrinsic tracking and low thresholds of gaseous detectors. This approach enables detailed reconstruction of exclusive final states, improved particle identification, and sensitivity to low-energy and rare processes — capabilities that are increasingly central to precision oscillation measurements and searches for beyond-the-Standard-Model signatures. This abstract presents an overview of ongoing detector R&D toward high-pressure gaseous argon TPC operation, with emphasis on micro-pattern gas detector (MPGD) charge amplification in argon-based mixtures. We report experimental characterization of triple-GEM structures at pressures relevant for neutrino applications, including studies of multiplication factor scaling, stability, and operational voltage envelopes across gas admixtures. Measurements performed at the TOAD and GORG test stands at Fermilab help define viable amplification and electronics noise regimes in conditions where higher density imposes stricter constraints on signal formation. These results provide essential input to the optimization of high-pressure gaseous argon detectors for future neutrino experiments, including near-detector concepts such as ND-GAr in DUNE Phase II near detector upgrade. More broadly, this program shows how dedicated detector R&D can expand the precision frontier in neutrino physics by enabling complementary reconstruction capabilities beyond conventional detectors.

McConnell, Brenna [Indiana U.] (ORCID:000900041138↗

DOE OSTI2024

Debiasing with Diffusion: Probabilistic Reconstruction of Dark Matter Fields from Galaxies with CAMELS

Abstract Galaxies are biased tracers of the underlying cosmic web, which is dominated by dark matter (DM) components that cannot be directly observed. Galaxy formation simulations can be used to study the relationship between DM density fields and galaxy distributions. However, this relationship can be sensitive to assumptions in cosmology and astrophysical processes embedded in galaxy formation models, which remain uncertain in many aspects. In this work, we develop a diffusion generative model to reconstruct DM fields from galaxies. The diffusion model is trained on the CAMELS simulation suite that contains thousands of state-of-the-art galaxy formation simulations with varying cosmological parameters and subgrid astrophysics. We demonstrate that the diffusion model can predict the unbiased posterior distribution of the underlying DM fields from the given stellar density fields while being able to marginalize over uncertainties in cosmological and astrophysical models. Interestingly, the model generalizes to simulation volumes ≈500 times larger than those it was trained on and across different galaxy formation models. The code for reproducing these results can be found athttps://github.com/victoriaono/variational-diffusion-cdm✎.

Astronomy & Astrophysics↗

DOE OSTI2022

Sensitivity Coefficients Calculated for the Prompt Neutron Decay Constant at or Near Delayed Critical [Abstract]

Experimenters at Los Alamos National Laboratory (LANL) measure the prompt neutron decay constant for many experiments at the National Criticality Experiments Research Center (NCERC) to infer reactivity and the effective neutron multiplication factor. These quantities are very important for nuclear criticality safety and validating nuclear data. Uncertainty in measures of criticality of an experimental configuration can be determined prior to physically performing the experiment by applying first order perturbation theory to Monte Carlo codes, such as MCNP®. The first order perturbation theory produces first derivatives of some nuclear parameter to nuclear data (e.g., cross section data). This first derivative is commonly referred to as a sensitivity coefficient. Currently, the MCNP® software has the capability of computing effective neutron multiplication factor sensitivity coefficients to cross section data. This work builds off of this MCNP® capability and the first order perturbation theory to provide a method of calculating sensitivity coefficients for the prompt neutron decay constant at or near delayed critical to cross section data. The prompt neutron decay constant sensitivity coefficient calculated in this work does not depend on any modification of the MCNP® source code. Prompt neutron decay constant sensitivity coefficient calculations can be used to infer reactivity and effective neutron multiplication factor sensitivity coefficient values as well. By investigating the trends of prompt neutron decay constant sensitivity coefficients for nuclide-reaction pairs across energy spectra, experiments can be designed to maximize or minimize the uncertainty in the prompt neutron decay constant in a particular energy region, which can lead to further optimization studies. Prompt neutron decay constant sensitivity coefficients will be calculated for the Jezebel benchmark. Subsequently, these sensitivity coefficients will be used in a data assimilation process to determine if there is or are optimal experiments that can be performed to provide insight into adjustments of uncertain/inaccurate cross section data. Specifically, the effect of the prompt neutron decay constant sensitivity coefficients on the nuclear data-induced uncertainty in the effective neutron multiplication factor will be examined

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2025

Implications of a weakening N = 126 shell closure away from stability for r -process astrophysical conditions

The formation of the third r-process abundance peak near A ∼ 195 is highly sensitive to both nuclear structure far from stability and the astrophysical conditions that produce the heaviest elements. In particular, the N = 126 shell closure plays a crucial role in shaping this peak. Experimental data hints that the shell weakens as proton number departs from Z = 82, a trend largely missed by global mass models. To investigate its impact on r-process nucleosynthesis, we employ both standard global models with strong closures and modified Duflo-Zuker (DZ) models that reproduce the weakening, combined with three sets of β − -decay rates. Strong shell closures generate sharply peaked abundances, whereas weakened closures consistent with the experimental trend produce broader, flatter patterns. Accurately reproducing the solar third peak under weakened shell strength requires sufficiently neutron-rich conditions that significant fission occurs, and slower decay rates. These results demonstrate that a weakening N = 126 shell closure away from stability imposes significant constraints on the astrophysical environments of the r-process and underscores the need for precise mass measurements and improved characterization of β − -decay properties in this region.

N = 126 closed shells↗