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DOE OSTI2021

Density functional theory calculations of the thermodynamic and kinetic properties of point defects in β -U

Density functional theory (DFT) calculations of the thermodynamic and kinetic properties of point defects in the β phase of uranium are reported. Defect energies and entropies were calculated using 2 x 2 x 2 supercells and the Generalized Gradient Approximation (GGA) of Perdew-Burke-Ernzerhof (PBE) for the exchange-correlation potential. Due to computational cost, calculations of the vibrational properties governing entropies were performed by only displacing atoms within (roughly) the 3rd or 4th nearest neighbor shell of the defect, which implicitly assumes that atoms beyond this distance are unaffected by the defect. Migration barriers were estimated by nudged elastic band (NEB) calculations. The low symmetry of the β-U phase (the unit cell is tetragonal and contains 30 atoms) results in many point defect configurations and even more migration pathways. A connectivity map, starting from the most stable point defects, was developed in order to identify the rate-limiting step controlling the net diffusion rate in each crystallographic direction. The uranium self-diffusivity tensor was calculated by combining the defect formation energies, entropies, migration barriers and attempt frequencies. The fastest diffusion rate was determined to be a vacancy mechanism in the z crystallographic direction. The predicted uranium self-diffusivity for this mechanism agrees well with available experimental data. Finally, the diffusion mechanisms and rates identified in this study will inform fuel performance models of swelling and gas evolution.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2026

A score-based diffusion model approach for adaptive learning of stochastic partial differential equation solutions

In this paper, we propose a novel framework for adaptively learning the time-evolving solutions of stochastic partial differential equations (SPDEs) using score-based diffusion models within a recursive Bayesian inference setting. SPDEs play a central role in modeling complex physical systems under uncertainty, but their numerical solutions often suffer from model errors and reduced accuracy due to incomplete physical knowledge and environmental variability. To address these challenges, we encode the governing physics into the score function of a diffusion model using simulation data and incorporate observational information via a likelihood-based correction in a reverse-time stochastic differential equation. This enables adaptive learning through iterative refinement of the solution as new data becomes available. To improve computational efficiency in high-dimensional settings, we introduce the ensemble score filter, a training-free approximation of the score function designed for real-time inference. Numerical experiments on benchmark SPDEs demonstrate the accuracy and robustness of the proposed method under sparse and noisy observations.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

A quantum encryption design featuring confusion, diffusion, and mode of operation

Abstract Quantum cryptography—the application of quantum information processing and quantum computing techniques to cryptography has been extensively investigated. Two major directions of quantum cryptography are quantum key distribution (QKD) and quantum encryption, with the former focusing on secure key distribution and the latter focusing on encryption using quantum algorithms. In contrast to the success of the QKD, the development of quantum encryption algorithms is limited to designs of mostly one-time pads (OTP) that are unsuitable for most communication needs. In this work we propose a non-OTP quantum encryption design utilizing a quantum state creation process to encrypt messages. As essentially a non-OTP quantum block cipher the method stands out against existing methods with the following features: 1. complex key-ciphertext relation (i.e. confusion) and complex plaintext-ciphertext relation (i.e. diffusion); 2. mode of operation design for practical encryption on multiple blocks. These features provide key reusability and protection against eavesdropping and standard cryptanalytic attacks.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Diffuse Reflectance Spectroscopy and Principal Component Analysis to Retrospectively Determine Production History of Plutonium Dioxide

Diffuse reflectance spectroscopy measurements in the shortwave infrared (930–1600 nm) spectral region were acquired for Pu 2 (C 2 O 4 ) 3 •9H 2 O and its thermal decomposition product, PuO 2 . We analyzed a total of eight PuO 2 samples that were produced at different calcination temperatures (300, 350, 450, 525, 600, 675, 750, and 900 °C). Our goal was to identify spectroscopic fingerprints that could be used to gain retrospective information regarding the production parameters of these important nuclear compounds. The diffuse reflectance spectrum of Pu 2 (C 2 O 4 ) 3 •9H 2 O features several broad bands that currently preclude detailed analysis. However, all PuO 2 samples produced relatively sharp spectral features that got sharper and more intense for samples that were produced at higher calcination temperatures. The electronic band observed at 1433 nm in the diffuse reflectance spectra of PuO 2 was found to be a sensitive indicator of crystallinity; a result that is corroborated by ancillary Raman spectroscopy measurements. Principal component analysis of diffuse reflectance spectra was able to clearly rank and categorize PuO 2 samples based on the calcination temperature that was employed during their production. Thus, we show herein that important retrospective information pertaining to the process history of PuO 2 can be gained through the relatively simplistic combination of diffuse reflectance spectroscopy and principal component analysis. This discovery presents a new method for determining the provenance and process history of PuO 2 and should have an impact in the fields of nuclear forensics and nuclear nonproliferation.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2020

Selective One-Dimensional 13 C– 13 C Spin-Diffusion Solid-State Nuclear Magnetic Resonance Methods to Probe Spatial Arrangements in Biopolymers Including Plant Cell Walls, Peptides, and Spider Silk

Two-dimensional (2D) and 3D through-space 13 C– 13 C homonuclear spin-diffusion techniques are powerful solid-state nuclear magnetic resonance (NMR) tools for extracting structural information from 13 C-enriched biomolecules, but necessarily long acquisition times restrict their applications. In this work, we explore the broad utility and underutilized power of a chemical shift-selective one-dimensional (1D) version of a 2D 13 C– 13 C spin-diffusion solid-state NMR technique. The method, which is called 1D dipolar-assisted rotational resonance (DARR) difference, is applied to a variety of biomaterials including lignocellulosic plant cell walls, microcrystalline peptide fMLF, and black widow dragline spider silk. 1D 13 C– 13 C spin-diffusion methods described here apply in select cases in which the 1D 13 C solid-state NMR spectrum displays chemical shift-resolved moieties. Furthermore, this is analogous to the selective 1D nuclear Overhauser effect spectroscopy (NOESY) experiment utilized in liquid-state NMR as a faster (1D instead of 2D) and often less ambiguous (direct sampling of the time domain data, coupled with increased signal averaging) alternative to 2D NOESY. Selective 1D 13 C– 13 C spin-diffusion methods are more time-efficient than their 2D counterparts such as proton-driven spin diffusion (PDSD) and dipolar-assisted rotational resonance. The additional time gained enables measurements of 13 C– 13 C spin-diffusion buildup curves and extraction of spin-diffusion time constants TSD, yielding detailed structural information. Specifically, selective 1D DARR difference buildup curves applied to 13 C-enriched hybrid poplar woody stems confirm strong spatial interaction between lignin and acetylated xylan polymers within poplar plant secondary cell walls, and an interpolymer distance of ~0.45–0.5 nm was estimated. Additionally, Tyr/Gly long-range correlations were observed on isotopically enriched black widow spider dragline silks.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Colloidal State Machines as Smart Tracers for Chemical Reactor Analysis

A widely utilized tool in reactor analysis is passive tracers that report the residence time distribution, allowing estimation of the conversion and other properties of the system. Recently, advances in microrobotics have introduced powered and functional entities with sizes comparable to some traditional tracers. This has motivated the concept of Smart Tracers that could record the local chemical concentrations, temperature, or other conditions as they progress through reactors. Herein, the design constraints and advantages of Smart Tracers by simulating their operation in a laminar flow reactor model conducting chemical reactions of various orders are analyzed. It is noted that far fewer particles are necessary to completely map even the most complex concentration gradients compared with their conventional counterparts. Design criteria explored herein include sampling frequency, memory storage capacity, and ensemble number necessary to achieve the required accuracy to inform a reactor model. Cases of severe particle diffusion and sensor noise appear to bind the functional upper limit of such probes and require consideration for future design. The results of the study provide a starting framework for applying the new technology of microrobotics to the broad and impactful set of problems classified as chemical reactor analysis.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Distinct Mechanisms of Triplet Pair Decay in Amorphous and Crystalline Heteroacene Thin Films

Triplet pairs (TT) in crystalline molecular semiconductors have unique spin properties of interest for quantum information or enhancing solar photoconversion. The population and diffusion dynamics of TT have been the subject of recent studies, both in covalent dimers and in crystalline systems. Here, in this study, we monitor the triplet population in neat polycrystalline and amorphous films of a heteroacene with known TT spectral properties and tunable spin polarization depending on the intermolecular geometry. Transient measurements reveal an anomalous power dependence in polycrystalline films that we attribute to the fast diffusion and interaction of dissociated triplet pairs confined to one-dimensional stacks of strongly coupled molecules. The nongeminate triplet interaction after dephasing facilitates conversion to the triplet 3 TT and eventually T 1 +S 0 . Amorphous films have no power dependence and proceed directly from 1 TT to 3 TT and subsequently T 1 +S 0 via state mixing facilitated by nonparallel geometries and weak exchange coupling.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

In situ synchrotron investigation of degenerate graphite nodule evolution in ductile cast iron

Ductile cast irons (DCIs) are of increasing importance in the renewable energy and transportation sectors. The distribution and morphology of the graphite nodules, in particular the formation of degenerate features during solidification, dictate the mechanical performance of DCIs. In situ high-speed synchrotron X-ray tomography was used to capture the evolution of graphite nodules during solidification of DCI, including degenerate features and the effect of the carbon concentration field. The degeneration of nodules is observed to increase with re-melting cycles, which is attributed to Mg-loss. The dendritic primary austenite and carbon concentration gradients in the surrounding liquid phase were found to control nodule morphology by locally restricting and promoting growth. A coupled diffusion-mechanical model was developed, confirming the experimentally informed hypothesis that protrusions form through liquation cracking of the austenite shell and subsequent localised growth. In conclusion, these results provide valuable insights into the solidification kinetics of cast irons, supporting the design of advanced alloys.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Mechanistic nuclear fuel performance modeling of uranium nitride

Uranium mononitride (UN) is a nuclear fuel candidate for advanced reactor designs and an alternative being considered for light water reactors due to its higher thermal conductivity and uranium density than UO 2 . As with any nuclear fuel, swelling and fission gas release are important factors for safety, while also being some of the hardest phenomena to predict with a high degree of confidence. Getting a grasp on the gas swelling behavior and release is crucial to lower the barrier for UN utilization. An accelerated swelling rate at high temperatures observed experimentally, sometimes referred to as “breakaway swelling,” further complicates the prediction of fuel performance of UN. A mechanistic model has been developed using a multiscale approach to describe the intragranular and intergranular fission gas behavior. Lower-length-scale calculations have been employed to inform models of the gas and self-diffusion behavior, resolution rate, and bubble shape. Leveraging previous work on high burnup UO 2 , two populations of intragranular bubbles are considered; small bulk bubbles and larger bubbles located along dislocations. The dislocation bubbles were found to be crucial to the overall swelling behavior, and the breakaway swelling transition was associated with the transition in the gas atom diffusion mechanism from an irradiation-induced athermal diffusion regime at lower temperatures to an intrinsic thermal equilibrium regime at higher temperatures, accelerating the growth of the dislocation bubbles. Similarly, the threshold for fission gas release was associated with the grain boundary vacancy diffusivity surpassing the gas atom diffusivity at sufficiently high temperatures, allowing the over-pressurized grain boundary bubble to grow in size and interconnect. Using thermo-mechanical models with the fission gas model, two integral fuel pin assessment cases were simulated. Finally, this work demonstrates the ability of a multiscale approach to accelerate the understanding of advanced fuel forms when experimental data is limited.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2025

Laser-Induced Spectral Diffusion of T Centers in Silicon Nanophotonic Devices

Color centers in silicon are emerging as spin-photon interfaces operating at telecommunication wavelengths. The nanophotonic device integration of silicon color centers via ion implantation leads to significant optical-linewidth broadening, which makes indistinguishable photon generation challenging. Here, we study the optical spectral diffusion of T centers in a silicon photonic crystal cavity. We investigate the linewidth-broadening timescales and origins by measuring the temporal correlations of the resonance frequency under different conditions. Spectral hole-burning measurements reveal no spectral broadening at short timescales from 102 ns to 725 ns. We probe broadening at longer timescales using a check pulse to herald the T-center frequency and a probe pulse to measure the frequency after a wait time. The optical resonance frequency is stable up to 3 ms in the dark. Laser pulses below the silicon band gap applied during the wait time lead to linewidth broadening. Our observations establish laser-induced processes as the dominant spectral-diffusion mechanism for T centers in devices and inform materials and feedback strategies for indistinguishable photon generation.

Zhang, Xueyue↗

DOE OSTI2020

Multi-Physics Simulations of Molten Chloride Fast Reactor using Nek5000 and PROTEUS-NODAL

This report documents the FY20 work to demonstrate a specific multi-physics capability within NEAMS tools to model molten chloride fast reactors (MCFR). Specifically, the CFD code Nek5000 and the neutronics code PROTEUS-NODAL were coupled off-line to calculate the delayed neutron precursor distribution within the flowing fuel salts in an MCFR core. An MCFR benchmark problem and a 3D test problem based on a conceptual MSR design were successfully solved through the coupled simulation of Nek5000 and PROTEUS-NODAL. In the coupled simulations for these test problems, Nek5000 provided high-quality flow field information, and PROTEUS-NODAL performed the neutron diffusion calculation along with the precursor drift model. The impact of precursor drift on the core status was also investigated. Additionally, the precursor drift model implemented in PROTEUS-NODAL was verified by making use of the reference precursor distribution generated from Nek5000. Results of these test problems suggest that the multi-physics capability of Nek5000 and PROTEUS-NODAL was properly developed for tracking delayed neutron precursor drift.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2025

Data-Driven Method for Groundwater-Level Mapping and Monitoring-Well Network Optimization at Hanford

This report summarizes the initial results and outcomes of a physics-informed, data-driven groundwater level (GWL) mapping capability for the Hanford Site. GWL mapping at Hanford is typically conducted annually and requires a significant amount of computational and expert resources, and it does not allow assessment of the informational value of specific monitoring wells. The proposed method produces spatially and temporally resolved fields consistent with sparse, irregularly sampled, and nonuniformly distributed well measurements. Implemented successfully, this capability will allow rapid mapping of groundwater levels and provide an opportunity to optimize monitoring activities (both location and sampling frequency) based on data information value evaluation. The approach integrates a diffusion-based generative model – trained on MODFLOW simulation data from the Plateau-to-River (P2R) model – with score-based data assimilation (SDA), allowing observation-conditioned mapping without retraining for each monitoring-network layout.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Singularities in nearly uniform one-dimensional condensates due to quantum diffusion

Dissipative systems often exhibit wavelength-dependent loss rates. One prominent example is Rydberg polaritons formed by electromagnetically induced transparency, which have long been a leading candidate for studying the physics of interacting photons and also hold promise as a platform for quantum information. In this system, dissipation is in the form of quantum diffusion, i.e., proportional to k 2 (k being the wavevector) and vanishing at long wavelengths as k→0. Here, we show that one-dimensional condensates subject to this type of loss are unstable to long-wavelength density fluctuations in an unusual manner: after a prolonged period in which the condensate appears to relax to a uniform state, local depleted regions quickly form and spread ballistically throughout the system. We connect this behavior to the leading-order equation for the nearly uniform condensate—a dispersive analog to the Kardar-Parisi-Zhang equation—which develops singularities in finite time. Furthermore, we show that the wavefronts of the depleted regions are described by purely dissipative solitons within a pair of hydrodynamic equations, with no counterpart in lossless condensates. We close by discussing conditions under which such singularities and the resulting solitons can be physically realized.

74 ATOMIC AND MOLECULAR PHYSICS↗

DOE OSTI2020

Localization of fluorescent targets in deep tissue with expanded beam illumination for studies of cancer and the brain

Imaging fluorescence through millimeters or centimeters of tissue has important in vivo applications, such as guiding surgery and studying the brain. Often, the important information is the location of one of more optical reporters, rather than the specifics of the local geometry, motivating the need for a localization method that provides this information. We present an optimization approach based on a diffusion model for the fast localization of fluorescent inhomogeneities in deep tissue with expanded beam illumination that simplifies the experiment and the reconstruction. We show that the position of a fluorescent inhomogeneity can be estimated while assuming homogeneous tissue parameters and without having to model the excitation profile, reducing the computational burden and improving the utility of the method. We perform two experiments as a demonstration. First, a tumor in a mouse is localized using a near infrared folate-targeted fluorescent agent (OTL38). This result shows that localization can quickly provide tumor depth information, which could reduce damage to healthy tissue during fluorescence-guided surgery. Second, another near infrared fluorescent agent (ATTO647N) is injected into the brain of a rat, and localized through the intact skull and surface tissue. This result will enable studies of protein aggregation and neuron signaling.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2020

Relating Geometric Nanoconfinement and Local Molecular Environment to Diffusion in Ionic Polymer Membranes

Understanding structure-diffusion relationships in ionic polymer membranes not only illuminates fundamental mechanisms for membrane transport, but also informs further membrane development. In this study, we employ NMR diffusometry and molecular dynamics (MD) simulations to investigate diffusion coefficients and activation energies of diffusion (Ea) for both a lithium-form perfluorosulfonic acid membrane and aqueous solutions of lithium triflate. NMR shows that, at high water/ion molar ratio (?), Ea for water diffusion is slightly lower in the membrane than in solution. Conversely, membrane transport exhibits much higher Ea at low hydration as compared to solutions. MD simulations of a model system consisting of carbon nanotubes with varying diameter reveal that Ea of diffusion clearly relates to both the geometric nanoconfinement of the hydrophilic pathways in the membrane as well as the local molecular environment. These results demonstrate that Ea of diffusion can serve as a revelatory tool for the study of molecular transport processes and the coupling of morphology with transport at the nanoscale. This study thus provides new insights and new experimental and computational models for understanding transport in a wide range of polymer membranes, such as those used in molecular separations applications.

Zhang, Rui↗

DOE OSTI2021

Measurement of the longitudinal diffusion of ionization electrons in the MicroBooNE detector

Accurate knowledge of electron transport properties is vital to understanding the information provided by liquid argon time projection chambers (LArTPCs). Ionization electron drift-lifetime, local electric field distortions caused by positive ion accumulation, and electron diffusion can all significantly impact the measured signal waveforms. This paper presents a measurement of the effective longitudinal electron diffusion coefficient, D L , in MicroBooNE at the nominal electric field strength of 273.9 V/cm. Historically, this measurement has been made in LArTPC prototype detectors. This represents the first measurement in a large-scale (85 tonne active volume) LArTPC operating in a neutrino beam. This is the largest dataset ever used for this measurement. Using a sample of ~70,000 through-going cosmic ray muon tracks tagged with MicroBooNE's cosmic ray tagger system, we measure D L = 3.74 +0.28 -0.29 cm 2 /s.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2024

A Frequency Domain Methodology for Quantitative Evaluation of Diffuse Wavefield With Applications to Seismic Imaging

Abstract Ambient Noise Imaging (ANI) of subsurface structures relies on seismic interferometry of diffuse seismic wavefields. However, the lack of effective methods to quantify and identify highly diffuse waves hampers applications of ANI, particularly in evaluating seismic attenuation and monitoring structural changes with high temporal resolution. Conventional ANI approaches require data normalization, which effectively suppresses the non‐diffuse component with large amplitude but also results in significant loss of amplitude and phase information in the continuous seismic records. In this study, we propose a frequency domain method to quantitatively evaluate the degree of diffuseness of seismic wavefields by analyzing their statistical characteristics of modal amplitudes for stationarity and randomness. Tests on synthetic waveform and field nodal records show that the proposed method can effectively distinguish between diffuse and non‐diffuse waveforms for either single‐ or three‐component data. As an application, we identify a 60‐s‐long diffuse coda of a local M 2.2 earthquake recorded by a dense nodal array on the San Jacinto Fault Zone, and successfully extract high‐quality dispersion curve andQ‐value without performing data normalization. These results are consistent with those obtained by conventional methods that assess the correlation between coherency and the Green's function, and by modeling ballistic waves generated by road traffic. Our proposed method can advance the imaging of subsurface velocity and attenuation structures as well as monitoring temporal changes for scientific studies and engineering applications.

Geochemistry & Geophysics↗

DOE OSTI2020

Fission gas diffusion and release for Cr 2 O 3 -doped UO 2 : From the atomic to the engineering scale

Here, the anticipated benefits of large grains in Cr 2 O 3 -doped UO 2 pellets include improved mechanical and fission gas retention properties. To support the assessment of fission gas release (FGR) from doped pellets, the impact of doping on fission gas diffusivity for in-reactor conditions must be understood. In this work, we tackle this issue by informing the fission gas model within the BISON fuel performance code using material models developed at the atomic scale. The investigation of intra-granular fission gas diffusivity in Cr 2 O 3 -doped UO 2 is carried out by adapting a cluster dynamics model that, accounting for UO 2 thermochemistry, is capable of describing Xe diffusion under irradiation in undoped UO 2 as the starting point. Using a thermodynamic analysis, it is shown that in stoichiometric UO 2 with additions of Cr 2 O 3 the oxygen potential is defined by the Cr-Cr 2 O 3 two-phase equilibrium. Using the cluster dynamics model, the predicted Xe diffusivity in doped UO 2 was significantly increased in both the intrinsic and irradiation-enhanced regimes compared to undoped UO 2 as a result of higher concentrations of uranium and oxygen vacancies, respectively. This is a consequence of the more oxidizing conditions at high temperature, and more reducing conditions at low temperature, as a result of doping. Arrhenius functions have been fitted to the cluster dynamics results to enable implementation of the new diffusivities in the BISON fission gas behavior model. BISON simulations were carried out, showing the competing effects of the enlarged grains and the new fission gas diffusivity model, which act to suppress and enhance fission gas release, respectively. The new physics-informed model was validated against in-reactor experimental measurements under normal operation. Additionally, benchmarking was carried out for power ramp conditions. The predicted fission gas release agreed well with the experimental data, showing noticeable improvements over the standard UO 2 model.

36 MATERIALS SCIENCE↗