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DOE OSTI2023

An effective field theory for non-maximal quantum chaos

In non-maximally quantum chaotic systems, the exponential behavior of out-of-time-ordered correlators (OTOCs) results from summing over exchanges of an infinite tower of higher “spin” operators. We construct an effective field theory (EFT) to capture these exchanges in (0 + 1) dimensions. The EFT generalizes the one for maximally chaotic systems, and reduces to it in the limit of maximal chaos. The theory predicts the general structure of OTOCs both at leading order in the 1/N expansion (N is the number of degrees of freedom), and after resuming over an infinite number of higher order 1/N corrections. These general results agree with those previously explicitly obtained in specific models. We also show that the general structure of the EFT can be extracted from the large q SYK model.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2022

Electric fields and substrates dramatically accelerate spin relaxation in graphene

Electrons in graphene are theoretically expected to retain spin states much longer than most materials, making graphene a promising platform for spintronics and quantum information technologies. Here, in this work, we use first-principles density-matrix (FPDM) dynamics simulations to show that interaction with electric fields and substrates strongly enhances spin relaxation through scattering with phonons. Consequently, the relaxation time at room temperature reduces from microseconds in free-standing graphene to nanoseconds in graphene on the hexagonal boron nitride (hBN) substrate, which is the order of magnitude typically measured in experiments. Further, inversion symmetry breaking by hBN introduces a stronger asymmetry in electron and hole spin lifetimes than predicted by the conventional D'yakonov-Perel' (DP) model for spin relaxation. Deviations from the conventional DP model are stronger for in-plane spin relaxation, resulting in out-of-plane to in-plane lifetime ratios much greater than 1/2 with a maximum close to the Dirac point. These FPDM results, independent of symmetry-specific assumptions or material-dependent parameters, also validate recent modifications of the DP model to explain such deviations. Overall, our results indicate that spin-phonon relaxation in the presence of substrates may be more important in graphene than typically assumed, requiring consideration for graphene-based spin technologies at room temperature.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2022

Progress Report on Model Development for the Transport of Aerosol through Microchannels

This report summarizes the current progress in the development of a phenomenological model of aerosol transport, deposition, and plugging through microchannels. The purpose is to introduce a generic, reliable numerical model for the prediction of aerosol transport, deposition, and plugging in leak paths while accounting for potential plugging formation, to a user community involving researchers, regulators, and industry. In that regard, a Graphical User Interface (GUI) was generated by integrating the individual MATLAB scripts that make up the model and adding additional features to aid the general understanding of the problem to a user. This report focuses on the model development and features included. Further, predictions from the GUI are compared with experimental data for validation. The strength of the GUI is the ability of a user to plug in basic parameters such as the initial pressure conditions and canister model specifications in order to obtain a first principal approximation of vital information such as the blowdown pressure differential, aerosol penetration, and deposition as a function of time. The user can obtain this without the know-how of the underlying MATLAB scripts and thus enables the model to be readily applied by regulators, industry, and shareholders to reduce the uncertainty in the off-site radiological consequences. The report also lists future tasks under this work scope. This includes ongoing efforts to include additional crack geometries (divergent and divergent-convergent slots) to the model; GUI development and improvement based on feedback from users, and integration of aerosol source term data from Sibling Pin tests into the model as we approach realistic canister stress corrosion cracking–induced aerosol release scenarios.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

Thermal and electromechanical response of ultra-thin carbon-strip polarimeter targets in relativistic bunched beams

Thin carbon-strip targets provide fast relative hadron beam polarimetry, but their response in intense relativistic bunched beams is not governed by local stopping-power heating alone. We develop a coupled response model that combines beam-target overlap, secondary-electron escape, retained heat, target motion, transient heat transport, RF-induced strip-end heating, beam-induced forces, resistance changes, and slack-strip deformation. RHIC target observations constrain the relevant motion, force, and nonlocal-heating scales and show that target survival depends on both beam-center heating and electromagnetic boundary conditions near the strip ends. Applying the model to Booster, AGS, RHIC, and EIC proton and 3 He cases shows that the RHIC proton lifetime scale is reproduced at the order-of-magnitude level, while the RHIC target-holder fin results require the additional RF/end-heating mechanism. For EIC proton flattop operation, carbon-strip polarimetry may remain viable only with reduced dwell time, sufficient detector acceptance, and suppression of RF-induced end heating. For cooled-emittance 3 He, the calculated sublimation-loss scale is far beyond a straightforward RHIC-like carbon-strip extrapolation. Conventional carbon strips are therefore unlikely to remain viable for the most demanding EIC light-ion cases without major changes in target motion, target technology, or diagnostic concept.

43 PARTICLE ACCELERATORS↗

DOE OSTI2022

Novel fractal-textured solar absorber surfaces for concentrated solar power

The solar absorptance of a thermal receiver surface significantly affects the photothermal conversion efficiency of concentrated solar power (CSP) plants. The development of low-cost Gen3 CSP systems calls for increasing the solar absorptance of the thermal receivers at operating temperatures above 750 °C. This study presents an innovative approach to the fractal, multiscale texturing of absorber surfaces to significantly enhance solar energy absorption for Gen3 CSP applications. The absorber surface is described in terms of its fractal parameters that are uniquely determined from surface profile measurements. The interaction of solar radiation with the fractal surface is numerically simulated by solving the governing Maxwell’s equations for electromagnetic wave propagation to investigate the effect of texturing on the absorptance of the surfaces. It is shown that absorption of the solar spectrum increases with an increase in the fractal dimension and the multiscale asperity height of the surface texturing. Here, the theoretical model is demonstrated to be in close agreement with experimental measurements of spectral absorptance of electrodeposited copper (Cu), copper mono-oxide (CuO), and copper-manganese oxide (CuMnO) surfaces that are textured to produce a range of fractal parameters by tailoring the deposition parameters. Fractal surface texturing is shown to reduce reflectance by over one order of magnitude, yielding an absorptance of greater than 0.985 for CuMnO. For the first time, the study presents a significant effective means of increasing solar absorptance and a fundamental theoretical description of the underlying physics.

14 SOLAR ENERGY↗

DOE OSTI2025

Physics-informed transformation toward improving the machine-learned NLTE models of ICF simulations

The integration of machine-learning techniques into inertial confinement fusion (ICF) simulations has emerged as a powerful approach for enhancing computational efficiency. By replacing the costly nonlocal thermodynamic equilibrium (NLTE) model with machine-learning models, significant reductions in calculation time have been achieved. However, determining how to optimize machine-learning-based NLTE models in order to match ICF simulation dynamics remains challenging, underscoring the need for physically relevant error metrics and strategies to enhance model accuracy with respect to these metrics. Thus, we propose novel physics-informed transformations designed to emphasize energy transport, use these transformations to establish new error metrics, and demonstrate that they yield smaller errors within reduced principal-component spaces compared to conventional transformations. Published by the American Physical Society 2025

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2022

High-density binding to Plasmodium falciparum circumsporozoite protein repeats by inhibitory antibody elicited in mouse with human immunoglobulin repertoire

Antibodies targeting the human malaria parasite Plasmodium falciparum circumsporozoite protein (PfCSP) can prevent infection and disease. PfCSP contains multiple central repeating NANP motifs; some of the most potent anti-infective antibodies against malaria bind to these repeats. Multiple antibodies can bind the repeating epitopes concurrently by engaging into homotypic Fab-Fab interactions, which results in the ordering of the otherwise largely disordered central repeat into a spiral. Here, we characterize IGHV3-33/IGKV1-5-encoded monoclonal antibody (mAb) 850 elicited by immunization of transgenic mice with human immunoglobulin loci. mAb 850 binds repeating NANP motifs with picomolar affinity, potently inhibits Plasmodium falciparum (Pf) in vitro and, when passively administered in a mouse challenge model, reduces liver burden to a similar extent as some of the most potent anti-PfCSP mAbs yet described. Like other IGHV3-33/IGKV1-5-encoded anti-NANP antibodies, mAb 850 primarily utilizes its HCDR3 and germline-encoded aromatic residues to recognize its core NANP motif. Biophysical and cryo-electron microscopy analyses reveal that up to 19 copies of Fab 850 can bind the PfCSP repeat simultaneously, and extensive homotypic interactions are observed between densely-packed PfCSP-bound Fabs to indirectly improve affinity to the antigen. Together, our study expands on the molecular understanding of repeat-induced homotypic interactions in the B cell response against PfCSP for potently protective mAbs against Pf infection.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

Advancing Additive Manufacturing Through Artificial Intelligence–Powered, High-Throughput, Nondestructive Characterization and Process Optimization

This Cooperative Research and Development Agreement (CRADA) between Oak Ridge National Laboratory (ORNL) and ZEISS Industrial Metrology has demonstrated the transformative potential of artificial intelligence (AI)-enabled x-ray computed tomography (XCT) to accelerate the qualification and certification of additively manufactured (AM) parts. At the core of this effort is Simurgh, an AI-powered XCT reconstruction framework jointly advanced by ORNL and ZEISS that integrates computer-aided design (CAD) models, physics-based simulations, and deep learning to overcome the long-standing challenges of metal artifact correction, long scan durations, and limited flaw detectability in dense and geometrically complex components. Simurgh enables high-throughput, high-quality 3D reconstruction from sparse and fast scans, which reduces XCT acquisition times by more than an order of magnitude and simultaneously improves defect detection limits by up to fourfold compared with industry-standard approaches. This capability reduces scan costs by more than 50%, lowers labor overhead, and makes XCT characterization economically viable for routine industrial use. By enabling reliable flaw detection in minutes rather than hours, Simurgh facilitates real-time feedback loops for process parameter optimization, which was highlighted in a recent npj Computational Materials (a Nature journal) issue. In the published study, more than 100 alloy coupons were characterized within a single day. This work represents a tenfold acceleration in the development of novel AM alloys and processes compared with conventional workflows. The ZEISS collaboration has also demonstrated the scalability of Simurgh to diverse application domains, including aerospace, nuclear, automotive, and biomedical components; in these applications, ensuring structural integrity is paramount. By drastically reducing barriers to XCT adoption, this partnership has laid the foundation for digital twins and data-driven certification pipelines and directly addressed bottlenecks in qualifying new materials and designs. Together, ORNL and ZEISS have shown that Simurgh advances the state of the art in nondestructive evaluation and aligns with the broader mission of enabling Industry 4.0 manufacturing ecosystems, in which intelligent, cost-effective, rapid quality assurance is integral to accelerating innovation and ensuring safety in critical applications.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Advancing Additive Manufacturing Through Artificial Intelligence–Powered, High-Throughput, Nondestructive Characterization and Process Optimization

36 MATERIALS SCIENCE↗

DOE OSTI2022

Thermodynamic Constraints on Electromicrobial Protein Production

Global consumption of protein is projected to double by the middle of the 21st century. However, protein production is one of the most energy intensive and environmentally damaging parts of the food supply system today. Electromicrobial production technologies that combine renewable electricity and CO 2 -fixing microbial metabolism could dramatically increase the energy efficiency of commodity chemical production. Here we present a molecular-scale model that sets an upper limit on the performance of any organism performing electromicrobial protein production. We show that engineered microbes that fix CO 2 and N 2 using reducing equivalents produced by H 2 -oxidation or extracellular electron uptake could produce amino acids with energy inputs as low as 64 MJ kg −1 , approximately one order of magnitude higher than any previous estimate of the efficiency of electromicrobial protein production. This work provides a roadmap for development of engineered microbes that could significantly expand access to proteins produced with a low environmental footprint.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2024

Hydrological controls of a riparian wetland based on stable isotope data and model simulations

Isotopic evidence of groundwater and stream water is frequently used to investigate water exchanges with groundwater. Monthly sampling of rain, stream water, and groundwater was conducted at Tims Branch watershed in South Carolina for the oxygen and hydrogen stable isotope (δ 2 H and δ 18 O) measurement, as well as pH and oxidation–reduction potential (ORP). Together with a mass balance perspective, it was determined that it takes a few weeks to one month for groundwater in the hyporheic zone to fully exchange with stream water. From hydrodynamic modelling, we show that substantial (up to 70 %) groundwater exchange occurs at gaining and losing sites. Groundwater exfiltration, i.e. inflow into stream water, contributes up to 4 % to stream water, with the remainder from upstream exfiltration. A 2–4 % per day renewal rate of adjacent groundwater would indirectly indicate a groundwater residence time in the order of half a month to a full month (assuming either a well-mixed case or large dispersion rate in pulse flow case), in agreement with a greatly reduced variability of δ 2 H and δ 18 O of groundwater compared to stream water and rain. This reduced variability of stable isotope signal from groundwater confirms our hypothesis that riparian groundwater mixing at Tims Branch is more of a mixed type rather than a pulse flow type. As a result, a monthly time scale is sufficient for groundwater to become anoxic at exit points into stream water resulting in the episodic production of natural organic matter- and iron-rich flocs upon oxidation.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Modifying Interface Solvation and Oxygen Reduction Electrocatalysis with Hydrophobic Species

Ionic liquid interlayers improve the oxygen reduction reaction (ORR) kinetics on bulk and nanostructured catalysts for both Pt and alloyed-Pt materials. Despite the demonstrated performance enhancement at the half-cell and membrane electrode assembly level, the mechanism of the improvement is not fully understood. In this work, we combine single-crystal experiments with microkinetic modeling to uncover the origin of the ORR kinetic improvement on Pt(111) in the presence of ionic liquids and hydrophobic cations. With the incorporation of a modified Frumkin isotherm, our model accurately simulates the disorder–order transition observed in hydroxyl and bisulfate adsorption on Pt(111) under acidic conditions. Voltametric analysis shows that ionic liquids impact solvation to break so-called scaling relations between the adsorption strength of OH ad and O ad , but these effects have little impact on ORR activity. Instead, destabilized OH ad reduces the overall hydroxyl (spectator) coverage, resulting in higher availability of active sites.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Simple Approximation for the Ideal Reference State of Gases Adsorbed on Solid-State Surfaces

Reference states are useful as models for facilitating calculations of equilibrium constants, and they may also serve as standard states that are convenient for organizing and tabulating thermodynamic data; however, standard state conventions and appropriate reference states for adsorbed species have received less attention than those for pure substances and solutes. Here, we compare seven choices of reference states for calculations of equilibrium constants and transition state theory rate constants for flat surfaces, in particular (1) an ideal 2D harmonic oscillator, (2) an ideal rigid-molecule harmonic oscillator, (3) an ideal 2D harmonic oscillator with separable surface modes, (4) a 2D ideal gas, (5) an ideal 2D hindered translator, (6) an ideal 2D hindered translator with lowest-order barriers, and (7) a simple ideal 2D hindered translator proposed in this work. The advantage of models 5–7 is that they can treat both mobile and localized adsorbates in a consistent way, whereas models 1–3 are only appropriate for localized adsorbates, and model 4 is only appropriate for a freely translating adsorbate. Furthermore, models 6 and 7 reduce the computational cost without the user having to calculate barrier heights for diffusion. An advantage of the simple ideal 2D hindered translator is that it has a physical high-temperature limit. We also propose a reference state for nonflat surfaces. Here, the user is encouraged to choose a reference state based on the appropriateness of the model and the practicality of the calculations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Turbulent flow characteristics in an 84-pin rod bundle for typical and damaged spacer grids

Hexagonal rod bundles arranged in a tightly packed triangular lattice are extensively used for heat transfer and energy generation applications. Staggered spacer grids are used to maintain the structural integrity of gas-cooled fast reactor (GFR) fuel assemblies, while inducing localized turbulence in flow. Damage to these spacer grids results in a disruption of flow fields within these hexagonal fuel bundles. Experimental flow visualizations are critical to identify the differences in local flow properties that the structural damage may cause. This experimental research investigates the flow-field characteristics at a near-wall and center plane in a prototypical 84-pin GFR fuel assembly. Newly installed typical spacers and spacers subject to naturally occurring damage due to material degradation over prolonged experimentation were investigated. Velocity fields were acquired by utilizing the matched-index-of-refraction method to obtain time-resolved particle image velocimetry measurements for a Reynolds number of 12 000. Reynolds decomposition statistical results divulged differences in the time-averaged velocity, velocity fluctuations, flow anisotropy, and Reynolds stress distributions. Galilean decomposition demarcated the influence of spacer grid damage on the velocity fields. To extract turbulent structures and elucidate mechanisms of flow instabilities, proper orthogonal decomposition analysis was employed. Reduced order flow reconstructions enabled the application of vortex identification algorithms to determine the spatial and statistical characteristics of vortices generated. This research work provides unique experimental data on the spacer grid condition-dependent flow. The results offer a deeper understanding of fluid dynamics behavior to support GFR rod bundle design efforts and computational fluid dynamics model validation.

36 MATERIALS SCIENCE↗

DOE OSTI2022

The benefits of CMB delensing

The effects of gravitational lensing of the cosmic microwave background (CMB) have been measured at high significance with existing data and will be measured even more precisely in future surveys. Reversing the effects of lensing on the observed CMB temperature and polarization maps provides a variety of benefits. Delensed CMB spectra have sharper acoustic peaks and more prominent damping tails, allowing for improved inferences of cosmological parameters that impact those features. Delensing reduces B-mode power, aiding the search for primordial gravitational waves and allowing for lower variance reconstruction of lensing and other sources of secondary CMB anisotropies. Lensing-induced power spectrum covariances are reduced by delensing, simplifying analyses and improving constraints on primordial non-Gaussianities. Biases that result from incorrectly modeling nonlinear and baryonic feedback effects on the lensing power spectrum are mitigated by delensing. All of these benefits are possible without any changes to experimental or survey design. Here, we develop a self-consistent, iterative, all-orders treatment of CMB delensing on the curved sky and demonstrate the impact that delensing will have with future surveys.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2021

Fire reduces riverine DOC concentration draining a watershed and alters post-fire DOC recovery patterns

Abstract The loading of dissolved organic carbon (DOC) from soils to inland waters and ultimate transport to the ocean is a critical flux pathway in the terrestrial biosphere carbon cycle. Fires can significantly affect this flux through biogeochemical processes related to oxidation and mobilization of DOC in the soil. Therefore, in order to accurately estimate and model terrestrial carbon storage and export to the marine environment, we need to better understand the effects of fire on DOC flux. In this analysis, we compiled available observational data sets from seven watersheds across the conterminous United States generally spanning the years 1999–2019. We used these data sets to examine the effects of fire on riverine DOC concentration draining a watershed to study both the immediate impacts and the post-fire recovery patterns. Our results suggest that these fires result in an immediate decrease in riverine DOC concentration draining the watershed by 26 ± 15%, and the time required for DOC concentrations to recover to pre-fire levels was estimated to be, on average, approximately 9 months. During recovery, DOC concentration was 24 ± 11% lower than the long-term average for the watershed. In addition, the larger the proportion of the watershed that burned, the greater the concentration decrease and the longer the time period for post-fire recovery.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Physical Parameters of the Multiplanet Systems HD 106315 and GJ 9827

HD 106315 and GJ 9827 are two bright, nearby stars that host multiple super-Earths and sub-Neptunes discovered by K2 that are well suited for atmospheric characterization. We refined the planets’ ephemerides through Spitzer transits, enabling accurate transit prediction required for future atmospheric characterization through transmission spectroscopy. Through a multiyear high-cadence observing campaign with Keck/High Resolution Echelle Spectrometer and Magellan/Planet Finder Spectrograph, we improved the planets’ mass measurements in anticipation of Hubble Space Telescope transmission spectroscopy. For GJ 9827, we modeled activity-induced radial velocity signals with a Gaussian process informed by the Calcium II H&K lines in order to more accurately model the effect of stellar noise on our data. We measured planet masses of M {sub b} = 4.87 ± 0.37 M {sub ⊕}, M {sub c} = 1.92 ± 0.49 M {sub ⊕}, and M {sub d} = 3.42 ± 0.62 M {sub ⊕}. For HD 106315, we found that such activity radial velocity decorrelation was not effective due to the reduced presence of spots and speculate that this may extend to other hot stars as well (T {sub eff} > 6200 K). We measured planet masses of M {sub b} = 10.5 ± 3.1 M {sub ⊕} and M {sub c} = 12.0 ± 3.8 M {sub ⊕}. We investigated all of the planets’ compositions through comparison of their masses and radii to a range of interior models. GJ 9827 b and GJ 9827 c are both consistent with a 50/50 rock-iron composition, GJ 9827 d and HD 106315 b both require additional volatiles and are consistent with moderate amounts of water or hydrogen/helium, and HD 106315 c is consistent with a ∼10% hydrogen/helium envelope surrounding an Earth-like rock and iron core.

47 OTHER INSTRUMENTATION↗

DOE OSTI2021

Dilute Combustion Control Using Spiking Neural Networks

Dilute combustion with exhaust gas recirculation (EGR) in spark-ignition engines presents a cost-effective method for achieving higher levels of engine efficiency. At high levels of EGR, however, cycle-to-cycle variability (CCV) of the combustion process is exacerbated by sporadic occurrences of misfires and partial burns. Previous studies have shown that temporal deterministic patterns emerge at such conditions and certain combustion cycles have a significant influence over future events. Due to the complexity of the combustion process and the nature of CCV, harnessing all the deterministic information for control purposes has remained challenging even with physics based 0-D, 1-D, and high-fidelity computational fluid dynamics (CFD) models. In this study, we present a data-driven approach to optimize the combustion process by controlling CCV adjusting the cycle-to-cycle fuel injection quantity. Readily available data from in-cylinder pressure was used to train a spiking neural network (SNN) which learns the optimal way to manage fuel injection in order to reduce CCV while maintaining acceptable levels of fuel consumption. SNNs are particularly well suited for powertrain control applications due to their ability to be deployed on FPGA-based neuromorphic hardware which are small, inexpensive, and have a low power demand. The high-performance computing (HPC) resources of Oak Ridge National Laboratory were used to run an evolutionary-based training approach for choosing the best SNN configuration that minimizes the size of the network while achieving the desired goal. The neuromorphic hardware with the optimized SNN deployed was connected to the rapid prototyping engine control system for real-time control implementation and tested on a single cylinder version of a GM LNF 4-cylinder engine. The results show a significant reduction of CCV with a small percentage of additional fuel used to stabilize the charge.

33 ADVANCED PROPULSION SYSTEMS↗