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DOE OSTI2023

Investigation of process history and underlying phenomena associated with the synthesis of plutonium oxides using Vector Quantizing Variational Autoencoder

Accurate, high throughput, and unbiased analysis of plutonium oxide particles is needed for analysis of the phenomenology associated with process parameters in their synthesis. Compared to qualitative and taxonomic descriptors, quantitative descriptors of particle morphology through scanning electron microscopy (SEM) have shown success in analyzing process parameters of uranium oxides. Among other candidates, a neural network called a Vector Quantizing Variational Autoencoder (VQ-VAE) has shown the ability to quantitatively describe particle morphology to attain >85% accuracy in identifying uranium oxide processing routes. We utilize a VQ-VAE to quantitatively describe plutonium dioxide (PuO 2 ) particles created in a designed experiment and investigate their phenomenology and prediction of their process parameters. PuO 2 was calcined from Pu(III) oxalates that were precipitated under varying synthetic conditions that related to concentrations, temperature, addition and digestion times, precipitant feed, and strike order; the surface morphology of the resulting PuO 2 powders were analyzed by SEM. A pipeline was developed to extract and quantify useful image representations for individual particles with the VQ-VAE, then further reduce the dimensionality of the feature space using a bottlenecking neural network fit to perform multiple classification tasks simultaneously. The reduced feature space could predict process parameters with greater than 80% accuracies for some parameters with a single particle. They also showed utility for grouping particles with similar surface morphology characteristics together. Both the clustering and classification results reveal valuable information regarding which chemical process parameters chiefly influence the PuO 2 particle morphologies: strike order and oxalic acid feedstock. Doing the same analysis with multiple particles was shown to improve the classification accuracy on each process parameter over the use of a single particle, with statistically significant results generally seen with as few as four particles in a sample.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2016

Quantitative Analysis of {sup 18}F-Fluorodeoxyglucose Positron Emission Tomography Identifies Novel Prognostic Imaging Biomarkers in Locally Advanced Pancreatic Cancer Patients Treated With Stereotactic Body Radiation Therapy

Purpose: To identify prognostic biomarkers in pancreatic cancer using high-throughput quantitative image analysis. Methods and Materials: In this institutional review board–approved study, we retrospectively analyzed images and outcomes for 139 locally advanced pancreatic cancer patients treated with stereotactic body radiation therapy (SBRT). The overall population was split into a training cohort (n=90) and a validation cohort (n=49) according to the time of treatment. We extracted quantitative imaging characteristics from pre-SBRT {sup 18}F-fluorodeoxyglucose positron emission tomography, including statistical, morphologic, and texture features. A Cox proportional hazard regression model was built to predict overall survival (OS) in the training cohort using 162 robust image features. To avoid over-fitting, we applied the elastic net to obtain a sparse set of image features, whose linear combination constitutes a prognostic imaging signature. Univariate and multivariate Cox regression analyses were used to evaluate the association with OS, and concordance index (CI) was used to evaluate the survival prediction accuracy. Results: The prognostic imaging signature included 7 features characterizing different tumor phenotypes, including shape, intensity, and texture. On the validation cohort, univariate analysis showed that this prognostic signature was significantly associated with OS (P=.002, hazard ratio 2.74), which improved upon conventional imaging predictors including tumor volume, maximum standardized uptake value, and total legion glycolysis (P=.018-.028, hazard ratio 1.51-1.57). On multivariate analysis, the proposed signature was the only significant prognostic index (P=.037, hazard ratio 3.72) when adjusted for conventional imaging and clinical factors (P=.123-.870, hazard ratio 0.53-1.30). In terms of CI, the proposed signature scored 0.66 and was significantly better than competing prognostic indices (CI 0.48-0.64, Wilcoxon rank sum test P<1e-6). Conclusion: Quantitative analysis identified novel {sup 18}F-fluorodeoxyglucose positron emission tomography image features that showed improved prognostic value over conventional imaging metrics. If validated in large, prospective cohorts, the new prognostic signature might be used to identify patients for individualized risk-adaptive therapy.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2025

Geochemical Phosphorus Sequestration in Tundra Soils Impedes Delivery of Bioavailable Phosphorus to the Kuparuk River, Alaska, USA: Implications for the Broader Arctic Region

Long-term river monitoring of the Kuparuk River (North Slope, Alaska, USA) confirms significant increases in solutes that are indicative of active layer thickening due to thawing permafrost. However, there is no evidence of an increase in total dissolved phosphorus (TDP) or soluble reactive phosphorus (SRP), the nutrient that limits primary production in this and similar rivers in the region. Here, we show that Mehlich-3 extractable iron (Fe) and aluminum (Al) in active layer soils impart high P geochemical sorption capacities across a range of landscape features that we would expect to promote lateral movement of water and solutes to headwater streams in our study watershed. Reanalysis of a recently published pan-Arctic soils database that includes active layer and permafrost soil samples suggests that this high P sorption capacity could be common in other parts of the Arctic region. We conclude that soil minerals enhance P retention on hillslopes and propose pedogenic secondary Fe and Al minerals may continue to retain P in these soils and limit biological productivity in the adjacent river even as active layer thickening increases potential P mobility in the watershed. We suggest that similar interactions may occur in other areas of the Arctic where comparable geochemical conditions prevail.

Sutor, Frederick W. [Univ. of Vermont, Burlington,↗

DOE OSTI2016

Isotopomer-selective spectra of a single intact H 2 O molecule in the Cs + (D 2 O) 5 H 2 O isotopologue: Going beyond pattern recognition to harvest the structural information encoded in vibrational spectra

We report the vibrational signatures of a single H 2 O water molecule occupying distinct sites of the hydration network in the Cs + (H 2 O) 6 cluster. This is accomplished using isotopomer selective IR-IR hole-burning on the Cs + (D 2 O) 5 (H 2 O) clusters formed by gas-phase exchange of a single, intact H 2 O molecule for D 2 O in the Cs + (D 2 O) 6 ion. The OH stretching pattern of the Cs + (H 2 O) 6 isotopologue is accurately recovered by superposition of the isotopomer spectra, thus establishing that the H 2 O incorporation is random and that the OH stretching manifold is largely due to contributions from decoupled water molecules. This behavior enables a powerful new way to extract structural information from vibrational spectra of size-selected clusters by explicitly identifying the local environments responsible for specific infrared features. The Cs + (H 2 O) 6 structure was unambiguously assigned to the 4.1.1 isomer (a homodromic water tetramer with two additional flanking water molecules) from the fact that its computed IR spectrum matches the observed overall pattern and recovers the embedded correlations in the two OH stretching bands of the water molecule in the Cs + (D 2 O) 5 (H 2 O) isotopomers. The 4.1.1 isomer is the lowest in energy among other candidate networks at advanced (e.g., CCSD(T)) levels of theoretical treatment after corrections for (anharmonic) zero-point energy (ZPE). With the structure in hand, we then explore the mechanical origin of the various band locations using a local electric field formalism. Furthermore, this approach promises to provide a transferrable scheme for the prediction of the OH stretching fundamentals displayed by water networks in close proximity to solute ions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Tracking the topology of neural manifolds across populations

Neural manifolds summarize the intrinsic structure of the information encoded by a population of neurons. Advances in experimental techniques have made simultaneous recordings from multiple brain regions increasingly commonplace, raising the possibility of studying how these manifolds relate across populations. However, when the manifolds are nonlinear and possibly code for multiple unknown variables, it is challenging to extract robust and falsifiable information about their relationships. We introduce a framework, called the method of analogous cycles, for matching topological features of neural manifolds using only observed dissimilarity matrices within and between neural populations. We demonstrate via analysis of simulations and in vivo experimental data that this method can be used to correctly identify multiple shared circular coordinate systems across both stimuli and inferred neural manifolds. Conversely, the method rejects matching features that are not intrinsic to one of the systems. Further, as this method is deterministic and does not rely on dimensionality reduction or optimization methods, it is amenable to direct mathematical investigation and interpretation in terms of the underlying neural activity. We thus propose the method of analogous cycles as a suitable foundation for a theory of cross-population analysis via neural manifolds.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2015

On reaching the adiabatic limit in multi-field inflation

We calculate the scalar spectral index n{sub s} and the tensor-to-scalar ratio r in a class of recently proposed two-field no-scale inflationary models in supergravity. We show that, in order to obtain correct predictions, it is crucial to take into account the coupling between the curvature and the isocurvature perturbations induced by the noncanonical form of the kinetic terms. This coupling enhances the curvature perturbation and suppresses the resulting tensor-to-scalar ratio to the per mille level even for values of the slow-roll parameter ε ∼ 0.01. Beyond these particular models, we emphasise that multifield models of inflation are a priori not predictive, unless one supplies a prescription for the post-inflationary era, or an adiabatic limit is reached before the end of inflation. We examine the conditions that enabled us to actually derive predictions in the models under study, by analysing the various contributions to the effective isocurvature mass in general two-field inflationary models. In particular, we point out a universal geometrical contribution that is important at the end of inflation, and which can be directly extracted from the inflationary Lagrangian, independently of a specific trajectory. Eventually, we point out that spectator fields can lead to oscillatory features in the time-dependent power spectra at the end of inflation. We demonstrate how these features can be model semi-analytically as well as the theoretical uncertainties they can entail.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2022

Non-linearities in the Lyman-α forest and in its cross-correlation with dark matter halos

Here three-dimensional correlations of the Lyman-α (Lyα) forest and cross correlations between the Lyα forest and quasars have been measured on large scales, allowing a precise measurement of the baryon acoustic oscillation (BAO) feature at redshifts z > 2. These 3D correlations are often modelled using linear perturbation theory, but full-shape analyses to extract cosmological information beyond BAO will require more realistic models capable of describing non-linearities present at smaller scales. We present a measurement of the Lyα forest flux power spectrum from large hydrodynamic simulations — the Sherwood simulations — and compare it to different models describing the small-scale deviations from linear theory. We confirm that the model presented in Arinyo-i-Prats et al. (2015) fits the measured 3D power up to k = 10 h Mpc -1 with an accuracy better than 5%, and show that the same model can also describe the 1D correlations with similar precision. We also present, for the first time, an equivalent study for the cross-power spectrum of halos with the Lyα forest, and we discuss different challenges we face when modelling the cross-power spectrum beyond linear scales. We make all our measured power spectra public in https://github.com/andreufont/sherwoo_p3d. This study is a step towards joint analyses of 1D and 3D flux correlations, and towards using the quasar-Lyα cross-correlation beyond BAO analyses.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2016

An a 0 resonance in strongly coupled π η , K K ¯ scattering from lattice QCD

Here, we present the first calculation of coupled-channel meson-meson scattering in the isospin $=1$, $G$-parity negative sector, with channels $\pi \eta$, $K\overline{K}$ and $\pi \eta'$, in a first-principles approach to QCD. From the discrete spectrum of eigenstates in three volumes extracted from lattice QCD correlation functions we determine the energy dependence of the $S$-matrix, and find that the $S$-wave features a prominent cusp-like structure in $\pi \eta \to \pi \eta$ close to $K\overline{K}$ threshold coupled with a rapid turn on of amplitudes leading to the $K\overline{K}$ final-state. This behavior is traced to an $a_0(980)$-like resonance, strongly coupled to both $\pi \eta$ and $K\overline{K}$, which is identified with a pole in the complex energy plane, appearing on only a single unphysical Riemann sheet. Consideration of $D$-wave scattering suggests a narrow tensor resonance at higher energy.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2019

Wobbly Dark Matter Signals at Cherenkov Telescopes from Long-Lived Mediator Decays

Imaging Atmospheric Cherenkov telescope (IACT) searches for dark matter often perform observations in “wobble mode,” i.e., simultaneously collecting data from the signal region and from a corresponding background control region. This observation strategy is possibly compromised in scenarios where dark matter annihilates to long-lived mediators that can traverse astrophysical distances before decaying to produce the gamma rays observed by the IACTs. In this Letter, we show that this challenge comes with several interesting features and opportunities: in addition to signal contamination in the background control region, the gamma-ray spectrum changes with the observing direction angle and typically exhibits a hard excess at high energies. Furthermore, such features represent a significant departure from the canonical picture and offer novel handles to identify a dark matter signal and to extract underlying dark matter parameters.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2019

Adversarial Training for Privacy-Preserving Deep Learning Model Distribution

Collaboration among cancer registries is essential to develop accurate, robust, and generalizable deep learning models for automated information extraction from cancer pathology reports. Sharing data presents a serious privacy issue, especially in biomedical research and healthcare delivery domains. Distributing pretrained deep learning (DL) models has been proposed to avoid critical data sharing. However, there is growing recognition that collaboration among clinical institutes through DL model distribution exposes new security and privacy vulnerabilities. These vulnerabilities increase in natural language processing (NLP) applications, in which the dataset vocabulary with word vector representations needs to be associated with the other model parameters. In this paper, we propose a novel privacy-preserving DL model distribution across cancer registries for information extraction from cancer pathology reports with privacy and confidentiality considerations. The proposed approach exploits the adversarial training framework to distinguish private features from shared features among different datasets. It only shares registry-invariant model parameters, without sharing raw data nor registry-specific model parameters among cancer registries. Thus, it protects both the data and the trained model simultaneously. We compare our proposed approach to single-registry models, and a model trained on centrally hosted data from different cancer registries. The results show that the proposed approach significantly outperforms the single-registry models and achieves statistically indistinguishable micro and macro F1-score as compared to the centralized model.

Alawad, Mohammed↗

DOE OSTI2019

Scalable Performance Awareness for In Situ Scientific Applications

Part of the promise of exascale computing and the next generation of scientific simulation codes is the ability to bring together time and spatial scales that have traditionally been treated separately. This enables creating complex coupled simulations and in situ analysis pipelines, encompassing such things as "whole device" fusion models or the simulation of cities from sewers to rooftops. Unfortunately, the HPC analysis tools that have been built up over the preceding decades are ill suited to the debugging and performance analysis of such computational ensembles. In this paper, we present a new vision for performance measurement and understanding of HPC codes, MonitoringAnalytics (MONA). MONA is designed to be a flexible, high performance monitoring infrastructure that can perform monitoring analysis in place or in transit by embedding analytics and characterization directly into the data stream, without relying upon delivering all monitoring information to a central database for post-processing. It addresses the trade-offs between the prohibitively expensive capture of all performance characteristics and not capturing enough to detect the features of interest. We demonstrate several uses of MONA; capturing and indexing multi-executable performance profiles to enable later processing, extraction of performance primitives to enable the generation of customizable benchmarks and performance skeletons, and extracting communication and application behaviors to enable better control and placement for the current and future runs of the science ensemble. Relevant performance information based on a system for MONA built from ADIOS and SOSflow technologies is provided for DOE science applications and leadership machines.

Wolf, Matthew D.↗

DOE OSTI2020

Adaptive thermal stabilization of an integrated photonic spectrometer using parasitic interference fringes

Parasitic fringe drift from unwanted scatterings limits the long-term stability of waveguide-based optical spectrometers. Yet their spectral features provide relevant information that can be used to improve performance of the spectrometer. We show that fringe drift can be extracted and utilized to perform accurate thermal stabilization, especially in the case of integrated waveguide sensors. In this Letter, effective stabilization of a methane silicon photonic sensor is demonstrated, and significant reduction in fringe noise is clearly observed.

Teng, Chu C.↗

DOE OSTI2021

OpenSesame tutorial

OpenSesame is a program for generating tabular equations of state (EOS), with capabilities for multiphase EOS construction. In this tutorial, we provide an overview of how to run OpenSesame to construct a multiphase EOS. We discuss some general features of OpenSesame, followed by a description of sample input files required for multiphase EOS construction. We also discuss how to extract data from EOS tables in order to compare to experimental data, with an example using the OpenSesame GUI. Lastly, we provide a description of how to generate ASCII-formatted EOS tables most often used by hydro code users.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2017

Challenges to Constraining Exoplanet Masses via Transmission Spectroscopy

MassSpec , a method for determining the mass of a transiting exoplanet from its transmission spectrum alone, was proposed by de Wit and Seager. The premise of this method relies on the planet’s surface gravity being extracted from the transmission spectrum via its effect on the atmospheric scale height, which in turn determines the strength of absorption features. Here, we further explore the applicability of MassSpec to low-mass exoplanets—specifically those in the super-Earth size range for which radial velocity determinations of the planetary mass can be extremely challenging and resource intensive. Determining the masses of these planets is of the utmost importance because their nature is otherwise highly unconstrained. Without knowledge of the mass, these planets could be rocky, icy, or gas-dominated. To investigate the effects of planetary mass on transmission spectra, we present simulated observations of super-Earths with atmospheres made up of mixtures of H{sub 2}O and H{sub 2}, both with and without clouds. We model their transmission spectra and run simulations of each planet as it would be observed with James Webb Space Telescope using the NIRISS, NIRSpec, and MIRI instruments. We find that significant degeneracies exist between transmission spectra of planets with different masses and compositions, making it impossible to unambiguously determine the planet’s mass in many cases.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2025

Non-Hermitian quantum mechanics approach for extracting and emulating continuum physics based on bound-state-like calculations: Detailed description

Here, this work applies a reduced basis method to study the continuum physics of a finite quantum system—either few or many-body. Specifically, I develop reduced-order models, or emulators, for the underlying inhomogeneous Schrödinger equation and train the emulators against the equation's bound-state-like solutions at complex energies. The emulators rapidly and accurately interpolate and extrapolate the matrix elements of the Hamiltonian resolvent operator (Green's function) across a parameter space that includes both complex energy and other real-valued physical inputs in the Schrödinger equation. The spectra, discretized and compressed as the result of emulation, and the associated resolvent matrix elements (or amplitudes), have the defining characteristics of non-Hermitian quantum mechanics calculations, featuring complex eigenenergies with negative imaginary parts and branch cuts moved below the real axis in the complex energy plane. Therefore, one now has a method that extracts continuum physics from bound-state-like calculations and emulates those extractions in the input parameter space. Building on a prior Letter [Zhang, Phys. Rev. Lett. 135, 242501 (2025)], this article provides the full theoretical details, a comprehensive analysis of the method's performance, and a brief discussion of how it can be coupled with existing continuum approaches to perform emulations in their input parameter spaces.

ab initio calculations↗

DOE OSTI2014

Realizing one-dimensional quantum and high-frequency transport features in aligned single-walled carbon nanotube ropes

The superiority of the electronic transport properties of single-walled carbon nanotube (SWNT) ropes over SWNT mats is verified from low temperature and frequency-dependent transport. The overall change of resistance versus in nanotube mats shows that 3D variable range hopping is the dominant conduction mechanism within the 2–300 K range. The magneto-resistance (MR) is found to be predominantly negative with a parabolic nature, which can also be described by the hopping model. Although the positive upturn of the MR at low temperatures establishes the contribution from quantum interference, the inherent quantum transport in individual tubes is suppressed at elevated temperatures. Therefore, to minimize multi-channel effects from inter-tube interactions and other defects, two-terminal devices were fabricated from aligned SWNT (extracted from a mat) for low temperature transport as well as high-frequency measurements. In contrast to the mat, the aligned ropes exhibit step-like features in the differential conductance within the 80–300 K temperature range. The effects of plasmon propagation, unique to one dimension, were identified in electronic transport as a non-universal power-law dependence of the differential conductance on temperature and source-drain voltage. The complex impedance showed high power transmission capabilities up to 65 GHz as well as oscillations in the frequency range up to 30 GHz. The measurements suggest that aligned SWNT ropes have a realistic potential for high-speed device applications.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2015

Real-time ultrasound-tagging to track the 2D motion of the common carotid artery wall in vivo

Purpose: Tracking the motion of biological tissues represents an important issue in the field of medical ultrasound imaging. However, the longitudinal component of the motion (i.e., perpendicular to the beam axis) remains more challenging to extract due to the rather coarse resolution cell of ultrasound scanners along this direction. The aim of this study is to introduce a real-time beamforming strategy dedicated to acquire tagged images featuring a distinct pattern in the objective to ease the tracking. Methods: Under the conditions of the Fraunhofer approximation, a specific apodization function was applied to the received raw channel data, in real-time during image acquisition, in order to introduce a periodic oscillations pattern along the longitudinal direction of the radio frequency signal. Analytic signals were then extracted from the tagged images, and subpixel motion tracking of the intima–media complex was subsequently performed offline, by means of a previously introduced bidimensional analytic phase-based estimator. Results: The authors’ framework was applied in vivo on the common carotid artery from 20 young healthy volunteers and 6 elderly patients with high atherosclerosis risk. Cine-loops of tagged images were acquired during three cardiac cycles. Evaluated against reference trajectories manually generated by three experienced analysts, the mean absolute tracking error was 98 ± 84 μm and 55 ± 44 μm in the longitudinal and axial directions, respectively. These errors corresponded to 28% ± 23% and 13% ± 9% of the longitudinal and axial amplitude of the assessed motion, respectively. Conclusions: The proposed framework enables tagged ultrasound images of in vivo tissues to be acquired in real-time. Such unconventional beamforming strategy contributes to improve tracking accuracy and could potentially benefit to the interpretation and diagnosis of biomedical images.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2026

Multiscale modeling of packed-bed microwave reactors and estimation of intrinsic materials' permittivity

Modeling of packed-bed microwave reactors relies on an accurate representation of particle size, shape, and distribution within the bed, as well as the particles' dielectric properties. The measured permittivity of microwave susceptors (powders or structured materials) depends on the geometric features of the particles and the porosity of the bed, as well as the specific form factor of a structured material. These are effective properties and cannot be used to analyze other reactor configurations unless the geometric effects are removed. Therefore, we introduce a methodology for extracting the intrinsic particle permittivity from experimentally measured effective permittivity by combining cavity-based measurements with multiscale simulations and machine learning. Further, we develop the first multiscale model of packed-bed microwave reactors that incorporate particle effects (geometric features, random packing, and particle contact). This approach bridges macroscopic observables with mesoscopic physics, enabling analysis of local hotspots, arcing, and contact effects that control reactor performance. Using polymer-based spherical activated carbon (PBSAC) and silicon carbide (SiC) as examples, we demonstrate that the inferred particle permittivity is consistent with independent experimental heating profiles we collect from microwave reactors without adjustable parameters. Finally, this methodology establishes a foundation for predictive, multiscale design of microwave packed-bed reactors that explicitly accounts for particle-scale effects, enabling the estimation of intrinsic permittivity for the first time.

97 MATHEMATICS AND COMPUTING↗