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DOE OSTI2026

Non-Markovian relaxation spectroscopy of fluxonium qubits

Recent studies have shown that parasitic two-level systems (TLS) in superconducting qubits, which are a leading source of decoherence, can have relaxation times longer than the qubits themselves. However, the standard techniques used to characterize qubit relaxation is only valid for measuring T 1 under the Born-Markov approximation and could mask environmental memory effects in practice. Here, we introduce two-timescale relaxometry, a technique to probe the qubit and environment relaxation simultaneously and efficiently. We apply it to high-coherence fluxonium qubits over a frequency range of 0.1-0.4 GHz, and reveal a discrete spectrum of TLS with millisecond lifetimes. Our analysis of the spectrum is consistent with a random distribution of TLS in the aluminum oxide tunnel barrier of the Josephson junction chain of the fluxonium, with a spectral and volumetric density and average electric dipole similar to previous TLS studies at much higher frequencies. Our study suggests that investigating and mitigating TLS in the junction chain is crucial to the development of various types of noise-protected qubits in circuit QED.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2025

Two transitions in complex eigenvalue statistics: Hermiticity and integrability breaking

Open quantum systems have complex energy eigenvalues which are expected to follow non-Hermitian random matrix statistics, when chaotic, or two-dimensional (2d) Poisson statistics, when integrable. We investigate the spectral properties of a many-body quantum spin chain, i.e., the Hermitian Heisenberg model with imaginary disorder. Its rich complex eigenvalue statistics is found to separately break both Hermiticity and integrability at different scales of the disorder strength. With no disorder, the system is integrable and Hermitian, with spectral statistics corresponding to the 1d Poisson point process. At very small disorder, we find a transition from 1d Poisson statistics to an effective D -dimensional Poisson point process, showing Hermiticity breaking. At intermediate disorder, we find integrability breaking, as inferred from the statistics matching that of non-Hermitian complex symmetric random matrices in class AI † . For large disorder, as the spins align, we recover the expected integrability (now in the non-Hermitian setup), indicated by 2d Poisson statistics. These conclusions are based on fitting the spin-chain data of numerically generated nearest- and next-to-nearest-neighbor spacing distributions to an effective 2d Coulomb gas description at inverse temperature β . We confirm that such an effective description of random matrices also applies in classes AI † and AII † up to next-to-nearest-neighbor spacings. Published by the American Physical Society 2025

Akemann, Gernot (ORCID:0000000217104258)↗

DOE OSTI2025

On symmetry-resolved generalized entropies

Symmetry-resolved entanglement, capturing the refined structure of quantum entanglement in systems with global symmetries, has attracted a lot of attention recently. In this manuscript, introducing the notion of symmetry-resolved generalized entropies, we aim to develop a computational framework suitable for the study of excited state symmetry-resolved entanglement as well as the dynamical evolution of symmetry-resolved entanglement in symmetry-preserving out-of-equilibrium settings. We illustrate our framework using the example of (1+1)-d free massless compact boson theory, and benchmark our results using lattice computation in the XX chain. As a byproduct, our computational framework also provides access to the probability distribution of the symmetry charge contained within a subsystem and the corresponding full counting statistics.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2024

Synthesis of Novel Hybrid Nanostructures Employing Advanced Structural Characterization Techniques

This proposal was for carrying out research on creating novel hybrid nanostructures with novel and interesting functional properties with the help of advanced structural on adding 0.001, 0.01 and 0.02 mg of Au nanoparticles. From the reflectivity measurements, and the intensities of the various order diffraction peaks from the multilayers, we were able to reconstruct the electron density profiles of the films normal to their surfaces. characterization techniques. There were 3 components to the research: (1) seeing if new hybrid nanostructures could be synthesized from Au nanoparticles and lipid multilayers (2) making artificial cells from Galactopyranose-Derived Single-Chain Amphiphiles and sponge phases of lipid/amphiphile mixtures, and (3) characterizing the pair distribution function for complex nanoparticles of melanin to understand/predict the structural colors seen in aggregates of such nanoparticles.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

DOE OSTI2022

Multiscale Shear Properties and Flow Performance of Milled Woody Biomass

One dominant challenge facing the development of biorefineries is achieving consistent system throughput with highly variant biomass feedstock quality and handling performance. Current handling unit operations are adapted from other sectors (primarily agriculture), where some simplifying assumptions about granular mechanics and flow performance do not translate well to a highly compressible and anisotropic material with nonlinear time- and stress-dependent properties. This work explores the shear and frictional properties of loblolly pine at multiple experimental test apparatus and particle scales to elucidate a property window that defines the shear behavior over a range of material attributes (particle size, size distribution, moisture content, etc.). In general, it was observed that the bulk internal friction and apparent cohesion depend strongly on both the stress state of the sample in granular shear testers and the overall particle size and distribution span. For equipment designed to characterize the quasi-static shear stress failure of bulk materials ranging from 50 to 1,000 ml in test volume, similar test results were observed for finely milled particles (50% passing size of 1.4 mm) with a narrow size distribution (span between 10 and 90% passing size of 0.9 mm), while stress chaining and over-torque issues persisted for the bench-scale test apparatus for larger particle sizes or widely dispersed sample sizes. Measurement of the anisotropic particle–particle friction ranged from coefficients of approximately 0.20 to 0.45 and resulted in significantly higher and more variable friction measurements for larger particle sizes and in perpendicular alignment orientations. To supplement these laboratory-scale properties, this work explores the flow of loblolly pine and Douglas fir through a pilot-scale wedge-shaped hopper and a screw feeder. For the gravity-driven hopper flow, the critical arching distance and mass discharge rate ranged from approximately 10 to 30 mm and 2 to 16 tons/hour, respectively, for both materials, where the arching distance depends strongly on the overall particle size and depends less on the hopper inclination angle. Comparatively, the auger feeder was found to be much more impacted by the size of the particles, where smaller particles had a more consistent and stable flow while consuming less power.

09 BIOMASS FUELS↗

NASA NTRS1976

Radical formation, chemical processing, and explosion of interstellar grains

The ultraviolet radiation in interstellar space is shown to create a sufficient steady-state density of free radicals in the grain mantle material consisting of oxygen, carbon, nitrogen, and hydrogen to satisfy the critical condition for initiation of chain reactions. The criterion for minimum critical particle size for maintaining the chain reaction is of the order of the larger grain sizes in a distribution satisfying the average extinction and polarization measures. The triggering of the explosion of interstellar grains leading to the ejection of complex interstellar molecules is shown to be most probable where the grains are largest and where radiation is suddenly introduced; i.e., in regions of new star formation. Similar conditions prevail at the boundaries between very dark clouds and H II regions. When the energy released by the chemical activity of the free radicals is inadequate to explode the grain, the resulting mantle material must consist of extremely large organic molecules which are much more resistant to the hostile environment of H II regions than the classical dirty-ice mantles made up of water, methane, and ammonia.

Greenberg, J. M.↗

NASA NTRS2016

Optical Modeling and Polarization Calibration for CMB Measurements with Actpol and Advanced Actpol

The Atacama Cosmology Telescope Polarimeter (ACTPol) is a polarization sensitive upgrade to the Atacama Cosmology Telescope, located at an elevation of 5190 m on Cerro Toco in Chile. ACTPol uses transition edge sensor bolometers coupled to orthomode transducers to measure both the temperature and polarization of the Cosmic Microwave Background (CMB). Calibration of the detector angles is a critical step in producing polarization maps of the CMB. Polarization angle offsets in the detector calibration can cause leakage in polarization from E to B modes and induce a spurious signal in the EB and TB cross correlations, which eliminates our ability to measure potential cosmological sources of EB and TB signals, such as cosmic birefringence. We calibrate the ACTPol detector angles by ray tracing the designed detector angle through the entire optical chain to determine the projection of each detector angle on the sky. The distribution of calibrated detector polarization angles are consistent with a global offset angle from zero when compared to the EB-nulling offset angle, the angle required to null the EB cross-correlation power spectrum. We present the optical modeling process. The detector angles can be cross checked through observations of known polarized sources, whether this be a galactic source or a laboratory reference standard. To cross check the ACTPol detector angles, we use a thin film polarization grid placed in front of the receiver of the telescope, between the receiver and the secondary reflector. Making use of a rapidly rotating half-wave plate (HWP) mount we spin the polarizing grid at a constant speed, polarizing and rotating the incoming atmospheric signal. The resulting sinusoidal signal is used to determine the detector angles. The optical modeling calibration was shown to be consistent with a global offset angle of zero when compared to EB nulling in the first ACTPol results and will continue to be a part of our calibration implementation. The first array of detectors for Advanced ACTPol, the next generation upgrade to ACTPol, will be deployed in 2016.We plan to continue using both techniques and compare them to astrophysical source measurements for the Advanced ACTPol polarization calibration.

Koopman, Brian↗

NASA NTRS2017

Planetary Crater Detection and Registration Using Marked Point Processes, Multiple Birth and Death Algorithms, and Region-Based Analysis

Because of the large variety of sensors and spacecraft collecting data, planetary science needs to integrate various multi-sensor and multi-temporal images. These multiple data represent a precious asset, as they allow the study of targets spectral responses and of changes in the surface structure; because of their variety, they also require accurate and robust registration. A new crater detection algorithm, used to extract features that will be integrated in an image registration framework, is presented. A marked point process-based method has been developed to model the spatial distribution of elliptical objects (i.e. the craters) and a birth-death Markov chain Monte Carlo method, coupled with a region-based scheme aiming at computational efficiency, is used to find the optimal configuration fitting the image. The extracted features are exploited, together with a newly defined fitness function based on a modified Hausdorff distance, by an image registration algorithm whose architecture has been designed to minimize the computational time.

Image Processing; Pattern Recognition↗

NASA NTRS2018

Planetary Crater Detection and Registration Using Marked Point Processes, Multiple Birth and Death Algorithms, and Region-Based Analysis

Image Processing:Pattern Recognition↗

DOE OSTI2026

Assessing Photovoltaic Capacity Factor Variability Using Long-Term Satellite Derived Solar Resource Data Under Brazilian Climate

Accurate estimation of photovoltaic (PV) energy yield and its variability is essential for reducing financial risk and supporting reliable system planning for rapidly expanding PV markets. In Brazil, high solar adoption and increasing levels of distributed energy resources are beginning to introduce operational challenges such as curtailment and evolving grid requirements. Understanding how natural variability in solar resource propagates into PV system performance is therefore increasingly important for both project design and grid integration. Modern PV yield assessments commonly rely on multi-year meteorological datasets and probabilistic exceedance metrics (e.g., P50/P90) to quantify energy yield uncertainty for project financing. However, the implications of long-term solar resource variability for PV system design choices and high-adoption grid conditions remain less well characterized for rapidly expanding markets such as Brazil. In particular, understanding how weather-driven variability propagates into PV production distributions and capacity factor expectations is important for evaluating curtailment exposure, deployment strategies, and storage requirements in regions experiencing rapid growth of distributed and utility-scale PV. Seasonal and interannual variability in atmospheric conditions can produce substantial fluctuations in monthly PV energy production, which propagate into uncertainty in annual energy yield and capacity factor expectations. Characterizing this variability using long-term meteorological datasets allows probabilistic estimation of PV system performance and provides improved insight into the range of expected PV energy outcomes. This study explores the use of long-term satellite-derived meteorological data from the National Solar Radiation Database (NSRDB) to evaluate the variability of photovoltaic system performance across multiple locations in Brazil. Using a 27-year dataset (1998-2024), PV system simulations are performed to characterize the distribution of annual and seasonal capacity factors and energy yield outcomes, while propagating key sources of meteorological variability and model uncertainty through the PV modeling chain. The analysis also investigates the sensitivity of PV performance outcomes to key system design assumptions within the PV modeling chain, including tracking configuration and system sizing parameters. The resulting probabilistic performance characterization provides insight into how weather-driven variability influences PV production expectations and capacity factor distributions. These results provide a foundation for evaluating how weather-driven variability interacts with high PV adoption and potential storage or curtailment mitigation strategies.

14 SOLAR ENERGY↗

DOE OSTI2020

Improving the picture of atomic structure in nonoriented polymer domains using the pair distribution function: A study of polyamide 6

Abstract Investigations of the atomic structures within polyamides started over 80 years ago and continue today. These weakly ordered materials diffract X‐rays poorly and typically require postprocessing to obtain idealized samples for structural studies. An important goal remains to develop techniques to study the local structure in its natural state, with atomic resolution, and with sensitivity to subtle changes due to synthesis conditions or other technologically relevant processing procedures. Here, we compare the structures of as‐produced, nonoriented polyamide 6 ([C 6 H 11 NO] n ) from both hydrolytic and anionic processes. A total scattering pair distribution function approach is used to elucidate information about the atomic bonding, molecular conformation, chain packing, crystallite size, and ratio of ordered to disordered domain content. The results are compared with those from standard analytical methods.

Terban, Maxwell W.↗

DOE OSTI2022

Dynamical Bond Formation in KNi 2 Se 2

Emphanisis, or the appearance out of nothing, has been used to describe the phenomena of spontaneous atom off-centering and dipole formation at elevated temperatures in lead chalcogenides. Here, we provide spectroscopic evidence of spontaneous formation of metal-metal bonds above T~50 K in the layered metal KNi 2 Se 2 . These bonds form zig-zag chains that lower the local symmetry from tetragonal to monoclinic. Energy-resolved pair distribution function measurements exclude a pure phonon origin of our observations, and instead imply the existence of extra, slowly fluctuating, Ni-Ni bonds above T=50 K. Density functional theory calculations support this lower symmetry configuration as an instability of tetragonal KNi 2 Se 2 . We thus demonstrate that the phenomena of emphansis is not limited to local electric dipole formation, but can also be driven by the formation of metal-metal bonds.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Forecasting Multi-Wave Epidemics Through Bayesian Inference

We present a simple, near-real-time Bayesian method to infer and forecast a multiwave outbreak, and demonstrate it on the COVID-19 pandemic. The approach uses timely epidemiological data that has been widely available for COVID-19. It provides short-term forecasts of the outbreak’s evolution, which can then be used for medical resource planning. The method postulates one- and multiwave infection models, which are convolved with the incubation-period distribution to yield competing disease models. The disease models’ parameters are estimated via Markov chain Monte Carlo sampling and information-theoretic criteria are used to select between them for use in forecasting. The method is demonstrated on two- and three-wave COVID-19 outbreaks in California, New Mexico and Florida, as observed during Summer-Winter 2020. We find that the method is robust to noise, provides useful forecasts (along with uncertainty bounds) and that it reliably detected when the initial single-wave COVID-19 outbreaks transformed into successive surges as containment efforts in these states failed by the end of Spring 2020.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

Reaction chemistry of ethanol oligomerization to distillate-range molecules using low loading Cu/Mg x AlO y catalysts

We study ethanol oligomerization to higher alcohols and other oxygenates with a 0.3 wt. %Cu/Mg 2.9 AlO catalyst. This reaction involves more than 130 products in a complicated reaction network. The selectivity towards diesel fuel precursor compounds (hereafter ‘DFPC’) increased with conversion until reaching a plateau at an ethanol conversion of ~70 %. Alcohol selectivity was found to follow Schultz-Flory distribution at all studied conversions. Larger sized alcohols then are formed mostly by chain-growth mechanisms via surface reactions of adsorbed oligomers with ethanol-based monomers. Higher esters are formed from alcohols and aldehydes in a series reaction mechanism. Moreover, C 6+ ester and C 4+ ketones selectivities increase as conversion increases. We also found that C 4+ alcohols most likely undergo Guerbet coupling with the studied catalyst to form even higher alcohols once, and that the oxygen of these alcohols is active as a nucleophile, resulting in the selective formation of esters if the starting alcohol is branched. Finally, we performed several cofeed studies varying ethanol-to-H 2 inlet partial pressures, and adding acetaldehyde and ethyl acetate as cofeeds to ethanol at different concentrations. Here, we conclude from these experiments that acetaldehyde concentration controls reaction chemistry, with conditions favoring larger concentrations of the molecule promoting both alcohol coupling and ester formation, and conditions leading to lower concentrations of acetaldehyde resulting in higher alcohol selectivity at the expense of esters and higher aldehydes.

10 SYNTHETIC FUELS↗

DOE OSTI2024

Role of Bottlebrush Additives on the Structure of Block Copolymers in the Bulk and Thin Films

Blending block copolymers (BCP) with additives is a useful approach for controlling BCP morphology and properties. In athermal systems, blends of BCPs with polymer additives having very high molecular (M n ) mass generally result in macrophase separation. Bottlebrush polymers, which consist of a linear backbone and grafted side chains, present an interesting alternative where the overall M n of the system can be very large but the low M n side chains may drive miscibility with the BCP. Here, in this study, a bottlebrush with a polynorbornene backbone and polystyrene (PS) side chains is blended with PS-b-poly(methyl methacrylate) (PS-b-PMMA) of varying M n , and the resulting morphologies are examined in both the bulk and thin films. Two different M n of PS-b-PMMA were used in the bulk study, and the analysis of small-angle X-ray scattering data shows that the blends were miscible and lamellar at all concentrations. This deviates from reference series of both low and high M n linear polymer additives, which either showed morphological transitions from lamellae to cylinders (low M n ) or were immiscible at all mass fractions studied (high M n ). The relative molecular mass of the side chain (N SC ) and the corresponding component in the BCP (N A ) dictate the distribution of the bottlebrush throughout the BCP, analogous to BCP/linear blends or grafted nanoparticles in a homopolymer matrix. The studies on thin films show a thickness dependence for bottlebrush mass fractions at or above 0.17, a behavior which may be driven by conformational changes of the bottlebrush upon confinement.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Centrality dependence of Lévy-stable two-pion Bose-Einstein correlations in $\sqrt{𝑠{𝑁⁢𝑁}}$ = 200 GeV Au + Au collisions

The PHENIX experiment measured the centrality dependence of two-pion Bose-Einstein correlation functions in $\sqrt{𝑠{𝑁⁢𝑁}}$ = 200 GeV Au + Au collisions at the Relativistic Heavy Ion Collider at Brookhaven National Laboratory. The data are well represented by Lévy-stable source distributions. The extracted source parameters are the correlation-strength parameter 𝜆, the Lévy index of stability 𝛼, and the Lévy-scale parameter 𝑅 as a function of transverse mass 𝑚 𝑇 and centrality. The 𝜆⁡(𝑚 𝑇 ) parameter is constant at larger values of 𝑚 𝑇 , but decreases as 𝑚 𝑇 decreases. The Lévy-scale parameter 𝑅⁡(𝑚 𝑇 ) decreases with 𝑚 𝑇 and exhibits proportionality to the length scale of the nuclear overlap region. The Lévy exponent 𝛼⁡(𝑚 𝑇 ) is independent of 𝑚 𝑇 within uncertainties in each investigated centrality bin, but shows a clear centrality dependence. At all centralities, the Lévy exponent 𝛼 is significantly different from that of Gaussian (𝛼 = 2) or Cauchy (𝛼 = 1) source distributions. Comparisons to the predictions of Monte-Carlo simulations of resonance-decay chains show that, in all but the most peripheral centrality class (50%–60%), the obtained results are inconsistent with the measurements, unless a significant reduction of the in-medium mass of the 𝜂′ meson is included. Finally, in each centrality class, the best value of the in-medium 𝜂′ mass is compared to the mass of the 𝜂 meson, as well as to several theoretical predictions that consider restoration of U 𝐴⁢ (1) symmetry in hot hadronic matter.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2022

Models to Incorporate Reaction Mechanisms into DG-OSPREY: Fixed-Bed Simulations for Organic Iodides Capture Using Ag 0 Z

As one of the most potent radioisotopes released during spent nuclear fuel reprocessing, 129 I is strictly regulated and must be removed before discharge. Organic iodides (primarily alkyl iodides with different chain lengths, i.e., CH 3 I, C 4 H 9 I, and C 12 H 25 I) comprise ~2% of the total iodine in the reprocessing off-gases and are primarily present in vessel off-gas (VOG). Reduced silver mordenite (Ag 0 Z) is predominantly considered for the removal of radioiodine; however, its capture performance and underlying interaction processes with long-chain organic iodides are not fully understood. Two major tasks were accomplished in this study. First, to improve upon the previous experimental studies where Ag 0 Z was used to capture CH 3 I, C 4 H 9 I, and C 12 H 25 I at different concentrations, we comprehensively investigated the corresponding capture mechanisms by characterizing fully loaded Ag 0 Z samples. Second, computational codes were implemented to perform fixed-bed simulations that account for transport and reaction mechanisms. Scanning electron microscopy with energy dispersive X-ray analysis (SEM-EDX), powder X-ray diffraction (PXRD), UV-visible diffuse reflectance spectroscopy (UV-vis DRS), and thermogravimetric analysis (TGA) were conducted on Ag 0 Z samples that are saturated with I 2 , CH 3 I, C 4 H 9 I, and C 12 H 25 I), respectively. Results indicate that AgI is the predominant adsorption product regardless of the adsorbed iodine species, yet alkyl iodides with different carbon chain lengths may have different compositions of α- and γ-AgI. Synchrotron pair distribution function (PDF) measurements and TGA coupled with a Fourier transformed infrared detector (TGA FTIR) have been performed, and experimental data are currently analyzed. Results are expected to provide further insights into the adsorption mechanisms. The fixed-bed capture performance for CH 3 I was successfully simulated by solving mathematical equations that describe the underlying transport processes and adsorption reactions. The computational framework, Catalytic After Treatment System (CATS), that was originated in our research group, was used to solve the governing equations. Kinetic parameters, including the pore diffusivity and reaction rate constant were obtained by optimization techniques using data from thin-bed experiments performed at Oak Ridge National Laboratory. The performance of a deep bed predicted using the optimized parameters showed promising agreement with the experimental data.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

NASA NTRS2006

An Ensemble-Based Smoother with Retrospectively Updated Weights for Highly Nonlinear Systems

Monte Carlo computational methods have been introduced into data assimilation for nonlinear systems in order to alleviate the computational burden of updating and propagating the full probability distribution. By propagating an ensemble of representative states, algorithms like the ensemble Kalman filter (EnKF) and the resampled particle filter (RPF) rely on the existing modeling infrastructure to approximate the distribution based on the evolution of this ensemble. This work presents an ensemble-based smoother that is applicable to the Monte Carlo filtering schemes like EnKF and RPF. At the minor cost of retrospectively updating a set of weights for ensemble members, this smoother has demonstrated superior capabilities in state tracking for two highly nonlinear problems: the double-well potential and trivariate Lorenz systems. The algorithm does not require retrospective adaptation of the ensemble members themselves, and it is thus suited to a streaming operational mode. The accuracy of the proposed backward-update scheme in estimating non-Gaussian distributions is evaluated by comparison to the more accurate estimates provided by a Markov chain Monte Carlo algorithm.

Monte Carlo↗