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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.

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72 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Multiamorphous Phases in Diketopyrrolopyrrole-Based Conjugated Polymers: From Bulk to Ultrathin Films

The glass transition temperature (T g ) of conjugated polymers is a crucial physical parameter that governs their mechanical and electrical properties for applications from sensor technology to skin-like electronics. Despite some well-developed methods that exist for detecting T g of conjugated polymers, there is still a need for the combination of advanced calorimetric methodologies to characterize T g in a broad range of temperatures and scales from bulk to nanometer-thin films. In this work, alternating current (ac) chip calorimetry and flash differential scanning calorimetry (flash DSC) are applied to successfully identify the Tgs and segmental relaxations of conjugated polymers. The detected relaxations were interpreted, in agreement with existing observations in similar systems, as a side-chain relaxation (low temperature), mobile amorphous fractions (MAF), and rigid amorphous fractions (RAF). T g s of MAF and RAF increase and decrease with increasing size of fused thiophene units in the backbone, respectively. The T g s of diketopyrrolopyrrole-based conjugated polymer thin films are also identified by the same method, with both T g s showing a decreased value compared to those of bulk samples. Furthermore, the weight fractions of MAF and RAF with various film thicknesses are qualitatively analyzed based on the heat capacity step of each amorphous fraction during the glass transition. This facile method gives insights into the physical nature of amorphous phases in conjugated polymers for better revealing their structure-property relationships, which will guide the designs of new materials with optimized electrical and mechanical properties in the future.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Machine learning bridges local static structure with multiple properties in metallic glasses

A long-standing challenge in the metallic glass (MG) community has been how to quantitatively gauge the influence of the intricate local packing environment on the response (such as the propensity for atomic rearrangement) of the atomic configuration to external stimuli. Here we establish this structure–property relation by representing the complex amorphous structure using a single, flexibility-orientated structural quantity. This structural flexibility (SF) couples to a bona fide structural representation, the pair distribution function (PDF) of individual atoms, through a weighting function that reflects what matters in the static atomic configuration to dynamic responses. Machine learning is used, employing microscopic flexibility volume as the supervisory signal, to establish via direct regression an optimized weighting vector, which is proven robust for all quenching rates, deformation conditions, and different compositions in a given (e.g., Cu x Zr 100-x ) alloy system. Additionally, the SF is evaluated solely from the particle positions (PDF), for any structure variation, from the atomic scale up to sample average. Strong correlations are demonstrated between SF and a broad range of properties, including vibrational, diffusional, as well as elastic and plastic relaxation responses.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Photoluminescence Dynamics Defined by Exciton Trapping Potential of Coupled Defect States in DNA-Functionalized Carbon Nanotubes

Chemical reactions between semiconducting single-wall carbon nanotubes (SWCNTs) and single-stranded DNA (ssDNA) achieve spatially patterned covalent functionalization sites and create coupled fluorescent quantum defects on the nanotube surface, tailoring SWCNT photophysics for applications such as single-photon emitters in quantum information technologies. The evaluation of relaxation dynamics of photoluminescence (PL) from those coupled quantum defects is essential for understanding the nanotube electronic structure and beneficial to the design of quantum light emitters. Here, we measured the PL decay for ssDNA-functionalized SWCNTs as a function of the guanine content of the ssDNA oligo that dictates the red-shifting of their PL emission peaks relative to the band-edge exciton. We then correlate the observed dependence of PL decay dynamics on energy red-shifts to the exciton potential energy landscape, which is modeled using first-principles approaches based upon the morphology of ssDNA-altered SWCNTs obtained by atomic force microscopy (AFM) imaging. In this work, our simulations illustrate that the multiple guanine defects introduced within a single ssDNA strand strongly interact to create a deep exciton trapping well, acting as a single hybrid trap. The emission decay from the distinctive trapping potential landscape is found to be biexponential for ssDNA-modified SWCNTs. We attributed the fast time component of the biexponential PL decay to the redistribution of exciton population among the lowest energy bright states and a manifold of dark states emerging from the coupling of multiple guanine defects. The long lifetime component in the biexponential decay, on the other hand, is attributed to the redistribution of exciton population among different exciton trapping sites that arise from the binding of multiple ssDNA strands along the nanotube axis. AFM measurements indicate that those trapping sites are separated on average by ~8 nm along the nanotube axis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Adsorption of Rare Earth Elements onto DNA-Functionalized Mesoporous Carbon

The recovery and separation of rare earth elements (REEs) are of national importance owing to the specific usages, high demand, and low supply of these elements. In this research, we have investigated the adsorption of rare earth elements onto DNA-functionalized mesoporous carbons with a BET surface area of 605 m2/g and a median mesopore width of 48 Å. Additionally, three types of single-stranded DNA, one with 100 base units of thymine, another with 20 units of thymine, and the third, a 2000 unit long DNA from salmon milt were grafted on the carboxylated mesoporous carbon surface. All of the DNA-functionalized mesoporous carbons demonstrated higher adsorption of REEs compared to pristine mesoporous carbon and DNA grafted with 100 units of thymine demonstrated slightly higher adsorbed amounts compared to others. Pure neodymium (Nd(III)) adsorption in the aqueous phase demonstrated an adsorbed amount of 110.4 mg/g with respect to the initial concentration of 500 mg/g. A pH variation study with pure Nd(III) demonstrated that the adsorbed amount is higher at elevated pH compared to that at lower pH, thereby suggesting possible recovery at lower pH. Adsorption of a mixture of 16 REEs, including Sc, Lu, Tm, Yb, Er, Ho, Tb, Dy, Y, Eu, Gd, Sm, Ce, Nd, Pr, and La revealed that the adsorbed amount increased with an increase in the atomic weight and metallic radii of elements within the lanthanides. The calculation of the distribution coefficients for all of the equilibrium adsorption amounts suggested that adsorption is more effective in the lower concentration region. The Nd L3-edge X-ray absorption near edge structure (XANES) confirmed a 3+ oxidation state of Nd in the adsorbed phase. The extended X-ray absorption fine structure (EXAFS) confirmed the local atomic structure relaxation of Nd complexes in the adsorbed phase and shortening of the Nd–O bond distance by about 0.03–0.04 Å, which may be associated with their local complexation at the carbon surface.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Dynamics of High Molecular Weight Cylindrical and Lamellar Block Copolymers with X‐ray Photon Correlation Spectroscopy

Here, the structure and dynamics of polystyrene (PS)-b-poly(ethylene oxide) block copolymers (BCPs) are studied. The BCPs exhibit microphase-separated cylindrical and lamellar morphologies. Structural dynamics are measured with X-ray photon correlation spectroscopy in the small-angle regime. Morphologies and domain sizes are evaluated using small-angle X-ray scattering (SAXS), scanning electron microscopy, and atomic force microscopy. Different solvent processing conditions are investigated. Grain sizes evaluated using SAXS are found to depend on processing only for the rubbery majority BCP. The structural relaxation times are examined as a function of PS volume fraction, temperature, morphology, and structural sizes. Well above the glass transition temperature (T g ) of PS, all samples exhibit stretched autocorrelation decays and diffusive dynamics. Near T g of PS, the dynamics of all samples are anomalous with compressed autocorrelation decays and hyperdiffusive dynamics. This transition occurs at 153 °C or 1.13 T g of PS. In the diffusive regime (at high temperature), structural relaxation times are dependent on the processing method. Near PS T g (at low temperature), structural relaxation times scale with the PS volume fraction. Structural relaxation times do not correlate with grain size, indicating that the out-of-equilibrium state of PS dominates the structural dynamics of these strongly phase-segregated BCPs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Cost-efficiency enhancement of X- and Ku-band split waveguides for industrial accelerators

Compact microwave electron linear accelerators must operate at high frequencies in order to maintain tight SWaP (size, weight, and power) requirements, set by modern applications. Currently, the frequencies are practically limited to X- and Ku-bands because of the availability of MW-class magnetrons, required to achieve beam energies of several MeV, and tight fabrication tolerances. The latter is associated with micron-level accuracy and further waveguide frequency tuning process, both increasing its costs dramatically. By implying a novel split structure fabrication approach, it is possible to relax these tolerances to the values of 10–20 μm and eliminate the tuning step, greatly reducing their total costs. Finally, this paper presents the results of microwave measurements of split X- and Ku-band accelerating structures of different types and discusses the benefits of our fabrication approach.

43 PARTICLE ACCELERATORS↗
DOE OSTI2021

27 Al NMR diffusometry of Al 13 Keggin nanoclusters

Although nanometer-sized aluminum hydroxide clusters (i.e., ϵ-Al 13 , [Al 13 O 4 (OH) 24 (H 2 O) 12 ] 7+ ) command a central role in aluminum ion speciation and transformations between minerals, measurement of their translational diffusion is often limited to indirect methods. Here, in this work, 27 Al pulsed field gradient stimulated echo nuclear magnetic resonance (PFGSTE NMR) spectroscopy has been applied to the AlO 4 core of the ϵ-Al 13 cluster with complementary theoretical simulations of the diffusion coefficient and corresponding hydrodynamic radii from a boundary element-based calculation. The tetrahedral AlO 4 center of the ϵ-Al 13 cluster is symmetric and exhibits only weak quadrupolar coupling, which results in favorable T 1 and T 2 27 Al NMR relaxation coefficients for 27 Al PFGSTE NMR studies. Stokes–Einstein relationship was used to relate the 27 Al diffusion coefficient of the ϵ-Al 13 cluster to the hydrodynamic radius for comparison with theoretical simulations, dynamic light scattering from literature, and previously published 1 H PFGSTE NMR studies of chelated Keggin clusters. This first-of-its-kind observation proves that 27 Al PFGSTE NMR diffusometry can probe symmetric Al environments in polynuclear clusters of greater molecular weight than previously considered.

27Al↗
DOE OSTI2025

Constraints on neutrino physics from DESI DR2 BAO and DR1 full shape

The Dark Energy Spectroscopic Instrument (DESI) Collaboration has obtained robust measurements of baryon acoustic oscillations in the redshift range 0.1 < 𝑧 < 4.2, based on the Lyman-𝛼 forest and galaxies from data release 2. We combine these measurements with cosmic microwave background (CMB) data from Planck and the Atacama Cosmology Telescope to place our tightest constraints yet on the sum of neutrino masses. Assuming the cosmological Λ⁢ CDM model and three degenerate neutrino states, we find ∑𝑚 𝜈 < 0.0642 eV (95%) with a marginalized error of 𝜎⁡(∑𝑚 𝜈 ) = 0.020 eV. We also constrain the effective number of neutrino species, finding 𝑁 eff = 3.2⁢3$^{+0.35}_{−0.34}$ (95%), in line with the Standard Model prediction. When accounting for neutrino oscillation constraints, we find a preference for the normal mass ordering and an upper limit on the lightest neutrino mass of 𝑚 𝑙 < 0.023 eV (95%). However, we determine using frequentist and Bayesian methods that our constraints are in tension with the lower limits derived from neutrino oscillations. Correcting for the physical boundary at zero mass, we report a 95% Feldman-Cousins upper limit of ∑𝑚 𝜈 < 0.053 eV, breaching the lower limit from neutrino oscillations. Considering a more general Bayesian analysis with an effective cosmological neutrino mass parameter, ∑𝑚 𝜈,eff , that allows for negative energy densities and removes unsatisfactory prior weight effects, we derive constraints that are in 3⁢𝜎 tension with the same oscillation limit, while the error rises to 𝜎⁡(∑𝑚 𝜈,eff ) = 0.053 eV. In the absence of unknown systematics, this finding could be interpreted as a hint of new physics not necessarily related to neutrinos. The preference of DESI and CMB data for an evolving dark energy model offers one possible solution. In the 𝑤 0 ⁢𝑤 𝑎 ⁢CDM model, we find ∑𝑚 𝜈 < 0.163 eV (95%), relaxing the neutrino tension. These constraints all rely on the effects of neutrinos on the cosmic expansion history. Using full-shape power spectrum measurements of data release 1 galaxies, we place complementary constraints that rely on neutrino free streaming. Our strongest such limit in Λ ⁢CDM, using selected CMB priors, is ∑𝑚 𝜈 < 0.193 eV (95%).

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Linear Viscoelastic Properties of Putative Cyclic Polymers Synthesized by Reversible Radical Recombination Polymerization (R3P)

Linear viscoelastic properties in both melt and solution states are reported for a series of poly(3,6-dioxa-1,8-octanedithiol) (polyDODT) made by reversible radical recombination polymerization (R 3 P) under conditions designed to produce linear (LDODT), cyclic (RDODT) and linear-cyclic mixtures (LRDODT). PolyDODT is amorphous (T g < -50 °C) and highly flexible (entanglement molecular weight M e,lin ≈ 1850 g/mol for LDODT). PolyDODT’s low T g and low M e,lin enable characterization over a wide dynamic range and a wide range of dimensionless weight-average molecular weight Z w = M w /M e,lin . Measurements at temperatures from -57 °C to 100 °C provide up to 18 deades of reduced frequency, which is necessary to characterize RDODT melts with Z w from 23 to 300. The two highest molecular weight polymers in the present RDODT series have such high M w (406k and 556k g/mol) that mass spectrometry, NMR spectroscopy, and even chemical assays for chain ends are unable to rule out up to 2 mol% linear contaminant. By studying the samples in solution (using dilution to reduce Z w ) we could compare their dynamics with those of previously established high-purity polystyrene (PS) rings (limited to Z w ≤ 13.6). RDODT solutions with Z w < 15 (concentrations <5wt% for RDODT-406k and 556k) have dynamic moduli G^* that accord with LCCC-purified PS rings in terms of the frequency dependence (including the absence of a plateau), the progression of shapes of G* as a function of Z w , and the linear scaling of their zero-shear viscosity η0 with M w . The shape of G* as a function of Z w for solutions of RDODT-406k and -556k also accord with lower M w RDODT melts (which have ≤ 1.3mol% linear contaminant). Thus, measurement of the linear viscoelastic properties of appropriate concentrations of high M w (>200k g/mol) putative cyclic polymers, in which linear chains evade spectroscopic detection, may provide an alternative means (though not fully proven) of validation of sample purity. When Z w > 15 (including all seven RDODT melts and eight of their solutions), G* has a rubbery plateau. This suggests that the onset of entanglement-like behavior in rings requires 4-5-fold greater Z w than is required for linear chains. Further, the plateau moduli of RDODT samples are indistinguishable from G N o of the corresponding LDODT (melt or matched-concentration solutions). In entangled linear polymers, the observation that G N o is independent of Z w follows from limitations on lateral fluctuations due to neighboring chains becoming independent of position along a given chain. The present results for RDODT suggest that this holds for sufficiently long endless chains, too. While the RDODT have the same G N o as entangled LDODT, when Z w > 60 the terminal relaxation, if reached at all, of RDODT extends to orders of magnitude lower frequency than an entangled linear polymer of the same Z w . Consequently, the viscosity of RDODT with Z w > 60 increases with Z w much more strongly than the 3.4-power observed for entangled linear polymers. Lastly, these novel polymers, with disulfide-linked backbone and broad relaxation time distribution may prove important in relation to biodegradable elastomers and materials with exceptional low-frequency dissipation, extending at least 12 decades below the onset of the rubbery plateau.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Scattering phase shift in quantum mechanics on quantum computers

Here, we investigate the feasibility of extracting infinite volume scattering phase shift on quantum computers in a simple one-dimensional quantum mechanical model, using the formalism established in the work by Guo and Gasparian [Phys. Rev. D 108, 074504 (2023)] that relates the integrated correlation functions for a trapped system to the infinite volume scattering phase shifts through a weighted integral. The system is first discretized in a finite box with periodic boundary conditions, and the formalism in real time is verified by employing a contact interaction potential with exact solutions. Quantum circuits are then designed and constructed to implement the formalism on current quantum computing architectures. To overcome the fast oscillatory behavior of the integrated correlation functions in real-time simulation, different methods of postdata analysis are proposed and discussed. Test results on IBM hardware show that good agreement can be achieved with two qubits, but complete failure ensues with three qubits due to two-qubit gate operation errors and thermal relaxation errors.

Guo, Peng [Dakota State Univ., Madison, SD (United↗
DOE OSTI2024

Synthesis of Bio-Based Repairable Polyimines with Tailored Properties by Lignin Fractionation

Developing sustainable polymers with low-value lignin remains a challenge. Herein, lignin-containing repairable polyimines were synthesized with tailored properties using lignin fractionation. First, softwood Kraft lignin is fractionated into a more homogeneous fraction with a lower molecular weight and a higher OH content. Next, Kraft lignin and its fraction are esterified by levulinic acid to introduce active ketone groups and subsequently condensed with oleylamine (OAm) and bis(3-aminopropyl)-terminated polydimethylsiloxane (PDMS) via a catalyst-free Schiff-base reaction to form grafted lignin-OAm copolymers and cross-linked lignin-PDMS polymer networks (MKL-P and MFL-P), respectively. Results show that lignin-OAm polyimines can be self-repaired and hot reprocessed under pressure, while lignin-PDMS polyimines can be repaired with the assistance of a healing agent, heat, and pressure. Dynamic mechanical analyses demonstrate that the stress–relaxation behaviors of the polyimines follow the Arrhenius law under thermal-stress activation, indicating the occurrence of transimination. Moreover, compared with Kraft lignin, the lignin fraction ameliorates the grafting density of ketones and enhances the cross-linking density of lignin-PDMS polyimine networks. The higher cross-linking density of MFL-P leads to superior stress–relaxation activation energy, thermal stability, hydrophobicity, and light-shielding ability but inferior repairability and translucency. Finally, this work provides insights into the polymerization of lignin-based polymer networks and the potential application of lignin-PDMS polyimines for repairable, translucent, anti-UV, and hydrophobic coatings.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Solid-State, Single-Ion Conducting, Polymer Blend Electrolytes with Enhanced Li + Conduction, Electrochemical Stability, and Limiting Current Density

The development of solid-state polymer electrolytes with high lithium conductivity is crucial to improve lithium-ion battery performance and ameliorate the safety challenges associated with current solvent-based electrolytes. Unfortunately, sluggish polymer segmental dynamics are known to constrain conductivity enhancements in solid-state polymer electrolyte systems, limiting overall performance. In this work, a glassy single-ion-conducting polymer, poly[lithium sulfonyl(trifluoromethane sulfonyl)imide methacrylate] (PLiMTFSI), was blended with a flexible polymer, poly(oligo-oxyethylene methyl ether methacrylate) (POEM), and the impact of PLiMTFSI molecular weight and ion concentration on the thermal and ion-conducting behavior of blend electrolytes was investigated. High ionic conductivities approaching 1 × 10 -2 S/cm at 150 °C were realized in this polymer blend electrolyte system as a result of decoupling Li + transport from polymer segmental dynamics. The decoupled ion transport was attributed to the packing frustration of the glassy PLiMTFSI – sufficient percolating free volume was generated to produce effective ion diffusion pathways. This decoupling was tunable as the ion transport could be altered from being closely coupled to the polymer segmental dynamics (Vogel–Tammann–Fulcher-like) to hopping (Arrhenius-like) by increasing the PLiMTFSI molecular weight and ion concentration. Moreover, the immobilized TFSI anion resulted in high Li + selectivity (Li + transference number = 0.9), high electrochemical stability (up to 4.7 V against Li + / Li), and limiting current density of 1.8 mA/cm 2 (electrolyte thickness = 0.05 cm). These features suggest that this single-ion-conducting, polymer blend electrolyte might be a promising alternative to a benchmark system – salt-doped polyethylene oxide. Moreover, the above characteristics can support the battery operation at higher voltages using energy-dense Li metal anodes, with faster charging rates and enhanced energy/power densities. Altogether, the results suggest that polymer chain packing frustration can be exploited to overcome the constraints of slow polymer segmental relaxations to achieve rapid and highly selective ion transport and enhanced performance in solid-state polymer electrolytes.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Dynamics of superconducting qubit relaxation times

Superconducting qubits are a leading candidate for quantum computing but display temporal fluctuations in their energy relaxation times T 1 . This introduces instabilities in multi-qubit device performance. Furthermore, autocorrelation in these time fluctuations introduces challenges for obtaining representative measures of T 1 for process optimization and device screening. These T 1 fluctuations are often attributed to time varying coupling of the qubit to defects, putative two level systems (TLSs). In this work, we develop a technique to probe the spectral and temporal dynamics of T 1 in single junction transmons by repeated T 1 measurements in the frequency vicinity of the bare qubit transition, via the AC-Stark effect. Across 10 qubits, we observe strong correlations between the mean T 1 averaged over approximately nine months and a snapshot of an equally weighted T 1 average over the Stark shifted frequency range. These observations are suggestive of an ergodic-like spectral diffusion of TLSs dominating T 1 , and offer a promising path to more rapid T 1 characterization for device screening and process optimization.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Application of a Density Law via Python for Aqueous Plutonium Nitrate

A predictive density tool has been developed in Python to reduce bias and uncertainty in nuclear criticality safety calculations for plutonium nitrate systems. The Pitzer Method and an empirical method were implemented into the tool, allowing for plutonium nitrate density calculations. Additionally, the Python tool can generate atom densities for a MCNP6.2 material card using the density from the selected method and directly the densities into a prepared MCNP6 input text file. The material card and density are calculated based on customizable user inputs of plutonium content, nitric acid content, temperature, plutonium isotope weight percentages and impurity concentrations. The Python tool has been validated and verified against the International Handbook of Evaluated Criticality Safety Benchmark Experiments to predict densities within a root mean square error of 1.0% for the Pitzer method and 1.8% for the empirical method. These errors in density were shown to lead to a ±0.5% error in MCNP6.2 calculated k effective for the Pitzer method and a ±1.7% error for the Empirical method. Simultaneous work is also being done at the University of New Mexico and Los Alamos National Laboratory to create a similar tool for plutonium chloride solutions, which aims to provide the accreditation of the chlorine absorption. These capabilities will not only provide more accurate models but also lead the way towards a better understanding of solution systems and potential relaxation in the conservatism of the current aqueous plutonium processing limits.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Stress-constrained topology optimization of lattice-like structures using component-wise reduced order models

We report lattice-like structures can provide a combination of high stiffness with light weight that is useful in many applications, but a resolved finite element mesh of such structures results in a computationally expensive discretization. This computational expense may be particularly burdensome in many-query applications, such as optimization. We develop a stress-constrained topology optimization method for lattice-like structures that uses component-wise reduced order models as a cheap surrogate, providing accurate computation of stress fields while greatly reducing run time relative to a full order model. We demonstrate the ability of our method to produce large reductions in mass while respecting a constraint on the maximum stress in a pair of test problems. The ROM methodology provides a speedup of about 150x in forward solves compared to full order static condensation and provides a relative error of less than 5% in the relaxed stress.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

A Python Tool for Aqueous Plutonium Nitrate Density Law Input Preprocessing in MCNP6

Here, this work develops a predictive density tool in Python, named Plutonium Nitrate Solutions (PuNS), to reduce bias and uncertainty in nuclear criticality safety calculations for plutonium nitrate systems. The Pitzer method and an empirical method were implemented into the PuNS tool to generate atom densities for use in MCNP6 material cards. These material cards are directly prepared into an MCNP6 input text file and are calculated based on customizable user inputs of plutonium content, nitric acid content, temperature, and plutonium isotope weight percentages. The PuNS tool is validated and verified against the International Criticality Safety Benchmark Evaluation Project Handbook experiments and is observed to predict densities within a root mean square error of 0.89% for the Pitzer method and 1.82% for the empirical method. These errors in density lead to up to 1569 pcm difference in MCNP6 calculated k eff for the Pitzer method and up to a 1751 pcm difference for the empirical method when compared to experimental benchmarks. Simultaneous work is also being performed at Los Alamos National Laboratory and the University of New Mexico to create a similar tool for plutonium chloride solutions, named Plutonium Chloride Solution, which aims to provide the accreditation of the chlorine absorption. These capabilities will not only provide more accurate models but also facilitate an improved understanding of solution systems and a potential relaxation in the conservatism of current aqueous plutonium processing criticality safety limits.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2026

Gradient-informed Hamiltonian Monte Carlo for multicomponent CALPHAD model optimization and uncertainty quantification

CALPHAD model parameter optimization is inherently challenging due to non-smooth objective functions, high-dimensional parameter spaces, and the need for uncertainty quantification (UQ). Traditional weighted nonlinear least squares approaches are computationally efficient but local, whereas black-box global optimizers and ensemble Markov Chain Monte Carlo (MCMC) methods provide broader exploration at substantial computational cost. The objective of this work is to combine the global exploration capability of gradient-informed Hamiltonian Monte Carlo – specifically the No-U-Turn Sampler (NUTS) – with local deterministic refinement using BFGS to efficiently optimize multicomponent CALPHAD models with minimal manual intervention. Analytic gradients are computed via the Jansson derivative framework. The methodology is demonstrated on the Cr—Fe binary system and extended to the Cr—Fe—Ni ternary system with 32 degrees of freedom. For Cr—Fe, NUTS achieves comparable or superior optimality relative to ensemble MCMC while requiring over an order-of-magnitude fewer likelihood evaluations. Parameter uncertainties are quantified through NUTS sampling and propagated to thermodynamic observables using local expansion, demonstrating a novel modular approach that combines binary and ternary parameter subsets without requiring global relaxation. These results establish gradient-informed exploration as a scalable strategy for multicomponent CALPHAD optimization and provide a practical route towards efficient higher-order database development with quantified uncertainty.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Development and validation of a 30-day mortality index based on pre-existing medical administrative data from 13,323 COVID-19 patients: The Veterans Health Administration COVID-19 (VACO) Index

Background Available COVID-19 mortality indices are limited to acute inpatient data. Using nationwide medical administrative data available prior to SARS-CoV-2 infection from the US Veterans Health Administration (VA), we developed the VA COVID-19 (VACO) 30-day mortality index and validated the index in two independent, prospective samples. Methods and findings We reviewed SARS-CoV-2 testing results within the VA between February 8 and August 18, 2020. The sample was split into a development cohort (test positive between March 2 and April 15, 2020), an early validation cohort (test positive between April 16 and May 18, 2020), and a late validation cohort (test positive between May 19 and July 19, 2020). Our logistic regression model in the development cohort considered demographics (age, sex, race/ethnicity), and pre-existing medical conditions and the Charlson Comorbidity Index (CCI) derived from ICD-10 diagnosis codes. Weights were fixed to create the VACO Index that was then validated by comparing area under receiver operating characteristic curves (AUC) in the early and late validation cohorts and among important validation cohort subgroups defined by sex, race/ethnicity, and geographic region. We also evaluated calibration curves and the range of predictions generated within age categories. 13,323 individuals tested positive for SARS-CoV-2 (median age: 63 years; 91% male; 42% non-Hispanic Black). We observed 480/3,681 (13%) deaths in development, 253/2,151 (12%) deaths in the early validation cohort, and 403/7,491 (5%) deaths in the late validation cohort. Age, multimorbidity described with CCI, and a history of myocardial infarction or peripheral vascular disease were independently associated with mortality–no other individual comorbid diagnosis provided additional information. The VACO Index discriminated mortality in development (AUC = 0.79, 95% CI: 0.77–0.81), and in early (AUC = 0.81 95% CI: 0.78–0.83) and late (AUC = 0.84, 95% CI: 0.78–0.86) validation. The VACO Index allows personalized estimates of 30-day mortality after COVID-19 infection. For example, among those aged 60–64 years, overall mortality was estimated at 9% (95% CI: 6–11%). The Index further discriminated risk in this age stratum from 4% (95% CI: 3–7%) to 21% (95% CI: 12–31%), depending on sex and comorbid disease. Conclusion Prior to infection, demographics and comorbid conditions can discriminate COVID-19 mortality risk overall and within age strata. The VACO Index reproducibly identified individuals at substantial risk of COVID-19 mortality who might consider continuing social distancing, despite relaxed state and local guidelines.

60 APPLIED LIFE SCIENCES↗