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DOE OSTI2026

Classical-Quantum Algorithm for Solving Stochastic Programs

Stochastic programming provides a rigorous mathematical framework for making decisions under uncertainty in a risk-aware manner. Two-stage stochastic programming is, perhaps, the simplest form of this framework. Here the first-stage variables represent decisions that must be made "here and now" in the face of uncertainty, while the second-stage variables are decisions made after uncertain events. However, the broad adoption of stochastic programming has been hindered by computational challenges caused by the two-stage stochastic programming formulation which requires solving an ensemble of optimization problems. Using quantum amplitude estimation (QAE), quantum computers have shown the theoretic ability to compute expectations with Monte-Carlo methods with quadratically fewer samples than classical methods. In this work, we present a quantum algorithm for computing the expectation term using QAE for given first-stage decisions. Further, we detail methods of computing gradient information from the quantum calculation enabling the application of classical gradient-based optimization techniques. The result is a classical-quantum hybrid method of solving two-stage stochastic programs. These techniques are demonstrated with computational experiments based an engineering optimization problem.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2026

Techno-Economic Evaluation of Electrified Vehicle Options in Drayage Fleets

The electrification of drayage fleets offers potential economic and operational benefits, but the financial viability of electrified vehicles remains sensitive to battery cost, energy price, and fleet usage patterns. While total cost of ownership (TCO) is a useful benchmark, fleet operators and investors are equally concerned with investment performance metrics such as payback period (PB) and Internal Rate of Return (IRR), which better reflect financial risks and investment return timelines. This study develops a unified techno-economic framework that jointly evaluates TCO, PB, and IRR to determine when electrified trucks become cost-effective alternatives to diesel trucks. Building on a previously developed cost modeling tool and using real-world telematics data from a Class 8 drayage fleet at the Port of Savannah, the analysis incorporates projected battery cost trajectories, electricity and diesel price trends, vehicle efficiency improvements, and multiple battery capacities. Parameter ranges reflect widely cited projections and observed drayage-duty-cycle variability. A surrogate-modeling method approximates economic performance across thousands of battery cost–electricity price combinations, enabling high-resolution identification of conditions that achieve TCO parity, acceptable PB thresholds, and target IRR levels. Additionally, the study estimates the evolving share of the fleet that can feasibly electrify over time under multiple economic metrics. This integrated framework offers a novel, data-driven approach to inform risk-aware decision-making for fleet electrification and supports investment planning under evolving cost and operational conditions.

Sun, Ruixiao [ORNL] (ORCID:0000000341768676)↗

DOE OSTI2026

Shakeup and shakeoff spectra in the electron capture decay of atomic 7 Be

The most stringent laboratory-based experimental limits on the existence of submegaelectronvolt sterile neutrinos are currently set by decay spectroscopy of radioactive 7 Be embedded into superconducting sensors. The systematic uncertainties are dominated by the modeling of the electron shakeup and shakeoff spectra that are not based on state-of-the-art atomic theory and do not include electron correlations or relativistic effects. We have used the multiconfiguration Dirac-Fock formalism to obtain correlated wave functions ab initio and compute all single and double shake processes in the electron capture decay of atomic 7 Be . The simulations can explain some but not all of the observed spectral features, likely because the wave functions are modified by the Ta sensor material that the 7 Be is embedded into. The new models also show that the 𝐿/𝐾 electron capture ratio of 7 Be in Ta has previously been slightly underestimated revising the previous value of 0.070(7) to a new value of 0.0756(20).

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2026

Upper ocean mixing, surface heat fluxes, and heat content variability in the upper 150 m during Hurricane Laura (2020)

Observations (from thermistor sensors and a hurricane glider) and model-based temperature were used to answer questions including the following: 1) What physical and environmental conditions explain the rapid intensification of Hurricane Laura? 2) How did the pre-existing warm mixed layer at Stone mooring (StM) influence the degree of cooling in the mixed layer? 3) How did vertical mixing, surface heat fluxes, and advective processes collectively shape the mixed layer heat evolution at StM? Observations measured by thermistor sensors showed that Hurricane Laura induced a cooling of -1.2oC in the mixed layer when Hurricane Laura’s wind speed increased to 47 m/s on 26 August. This contrasts with the -1.04oC mixed layer temperature change estimated from model-based temperature. At StM, the presence of a 31oC warm mixed layer and elevated heat content (60-80kJ/cm2) effectively preconditioned the upper ocean ahead of Hurricane Laura’s passage. After Hurricane Laura passed, turbulent mixing associated with the storm transported the heat anomalies downward into subsurface layers. In addition, this study shows that a surface heat flux of 5.04 kJ/cm2 supported the intensity of Hurricane Laura as it traversed over the StM. Using a mixed layer heat balance model, this study shows that entrainment flux and surface flux mostly contributed to the observed change in the mixed layer temperature.

Tsai, Senam↗

DOE OSTI2024

Hamiltonian switching control of noisy bipartite qubit systems

Abstract We develop a Hamiltonian switching ansatz for bipartite control that is inspired by the quantum approximate optimization algorithm, to mitigate environmental noise on qubits. We demonstrate the control for a central spin coupled to bath spins via isotropic Heisenberg interactions, and then make physical applications to the protection of quantum gates performed on superconducting transmon qubits coupling to environmental two-level-systems (TLSs) through dipole-dipole interactions, as well as on such qubits coupled to both TLSs and a Lindblad bath. The control field is classical and acts only on the system qubits. We use reinforcement learning with policy gradient to optimize the Hamiltonian switching control protocols, using a fidelity objective for specific target quantum gates. We use this approach to demonstrate effective suppression of both coherent and dissipative noise, with numerical studies achieving target gate implementations with fidelities over 0.9999 (four nines) in the majority of our test cases and showing improvement beyond this to values of 0.999 999 999 (nine nines) upon a subsequent optimization by GRadient Ascent Pulse Engineering (GRAPE). We analyze how the control depth, total evolution time, number of environmental TLS, and choice of optimization method affect the fidelity achieved by the optimal protocols and reveal some critical behaviors of bipartite control of quantum gates.

Physics↗

DOE OSTI2026

Secondary-Side Active Rectifier Synchronization and Control in LCC-LC Compensated Inductive Power Transfer Systems

This paper proposes a communication-less synchronization and output power control strategy for LCC-LC compensated inductive power transfer systems with a secondaryside active rectifier. By replacing the passive rectifier with an active bridge, the proposed architecture eliminates the need for a separate secondary-side DC-DC converter and enables direct regulation of battery power. The key challenge in such a system is achieving robust synchronization of the secondary active bridge with the primary inverter without access to primary-side signals. To address this issue, the secondary-side variables are analyzed and the current through the secondary series inductor is identified as a load-independent synchronization variable with a fixed phase relationship to the primary excitation. A fixed-frequency second order generalized (SOGI)-based phase locked loop (PLL) is used to estimate the switching phase and frequency, and a phase-shift-based output power controller is developed using a phasor-transformer model of the active bridges. A modified control formulation is further introduced to remove phase-dependent loop-gain variation and simplify controller design. Simulation results validate the proposed method under both fixed and varying switching-frequency conditions, demonstrating successful frequency tracking from 82 kHz to 88 kHz and accurate output power regulation over a wide operating range. The proposed method offers a compact and effective solution for high-power IPT systems by enabling secondary-side synchronization and control without wireless communication or an additional DC-DC conversion stage.

Fernandes, Arnold Anthony [ORNL] (ORCID:0009000631↗

DOE OSTI2024

Simulating hindered grain boundary diffusion using the smoothed boundary method

Abstract Grain boundaries can greatly affect the transport properties of polycrystalline materials, particularly when the grain size approaches the nanoscale. While grain boundaries often enhance diffusion by providing a fast pathway for chemical transport, some material systems, such as those of solid oxide fuel cells and battery cathode particles, exhibit the opposite behavior, where grain boundaries act to hinder diffusion. To facilitate the study of systems with hindered grain boundary diffusion, we propose a model that utilizes the smoothed boundary method to simulate the dynamic concentration evolution in polycrystalline systems. The model employs domain parameters with diffuse interfaces to describe the grains, thereby enabling solutions with explicit consideration of their complex geometries. The intrinsic error arising from the diffuse interface approach employed in our proposed model is explored by comparing the results against a sharp interface model for a variety of parameter sets. Finally, two case studies are considered to demonstrate potential applications of the model. First, a nanocrystalline yttria-stabilized zirconia solid oxide fuel cell system is investigated, and the effective diffusivities are extracted from the simulation results and are compared to the values obtained through mean-field approximations. Second, the concentration evolution during lithiation of a polycrystalline battery cathode particle is simulated to demonstrate the method’s capability.

Materials Science↗

DOE OSTI2026

Achieving uniaxial magnetic anisotropy in Ce2⁢Fe17⁢N3 through Co- and Sm-substitution

Th2⁢Zn17−type structure-based permanent magnets, such as Sm2⁢Fe17⁢N3, offer strong potential as alternatives to neodymium magnets (NdFeB), but their practical use is limited by phase stability and the scarcity of Sm. Ce-based counterparts, particularly Ce2⁢Fe17⁢N3, are attractive low-cost candidates, yet their intrinsic planar magnetic anisotropy restricts permanent-magnet performance. Here, we induce uniaxial magnetic anisotropy in Ce2⁢Fe17⁢N3 through two approaches: (i) Co substitution on the Fe sublattice and (ii) partial substitution of Ce with Sm. Combined density functional theory and experimental results show that both strategies modify the 3⁢𝑑–4⁢𝑓 interactions and band filling, yielding magnetization values up to ∼1.2T and magnetocrystalline anisotropy energies exceeding 1MJ/m3 for Co-alloyed compositions, with significantly larger anisotropy achieved upon Sm substitution. In addition, the Sm-substituted Ce2⁢Fe17⁢N3 samples exhibit enhanced high-temperature stability compared to Sm2⁢Fe17⁢N3. These findings demonstrate that Ce2⁢Fe17⁢N3-based alloys can deliver magnetic performance suitable for permanent-magnet applications while reducing cost and reliance on critical rare-earth elements, and they provide practical design guidelines for rare-earth-lean magnets for energy and industrial applications.

Pokhrel, Nabaraj [ORNL] (ORCID:0000000328283076)↗

DOE OSTI2025

CASM Monte Carlo: Calculations of the thermodynamic and kinetic properties of complex multicomponent crystals

Monte Carlo techniques play a central role in statistical mechanics approaches that connect macroscopic thermodynamic and kinetic properties to the electronic structure of a material. This paper describes the implementation of Monte Carlo techniques for the study of multicomponent crystalline materials within the Clusters Approach to Statistical Mechanics (CASM) software suite, and demonstrates their use in model systems to calculate free energies and kinetic coefficients, study phase transitions, and construct phase diagrams from first principles. Many crystal structures are complex, with multiple sublattices occupied by differing sets of chemical species, along with the presence of vacancies or interstitial species. This imposes constraints on concentration variables, the form of thermodynamic potentials, and the values of kinetic transport coefficients. The framework used by CASM to formulate thermodynamic potentials and kinetic transport coefficients accounting for arbitrarily complex crystal structures is presented and demonstrated with examples of increasing complexity. Additionally, an overview of the capabilities of the CASM software specific to Monte Carlo methods is given, and a new CASM software package is introduced, casm-flow, which helps automate the setup, submission, management, and analysis of Monte Carlo simulations.

Cluster expansion↗

DOE OSTI2026

Evolution of the Antarctic Ice Sheet from 2000–2300 and beyond: model sensitivity and uncertainty analysis using MPAS-Albany Land Ice

We present a description of the Antarctic Ice Sheet model configuration submitted to the ISMIP6-Antarctica-2300 experiment using the MPAS-Albany Land Ice model, along with three new sets of simulations: (1) a set of extended simulations to 2500 for three forced experiments and to 2775 for the control experiment; (2) a sensitivity analysis of our model configuration to parameters controlling basal sliding and sub-shelf melt, and to model structural choices including the choice of the energy and stress balances; and (3) a 72-member ensemble run on graphics processing units (GPUs) and analysis of variance to determine the primary sources of uncertainty in our ice-sheet model projections. Our extended simulations predict rapid retreat beginning after 2300 for SSP1-2.6 forcing and after 2500 for present-day (control) forcing, primarily in the Amundsen Sea Embayment. We find that varying the sub-shelf melt parameter between the 5th to 95th percentile values for a mean-Antarctic calibration target results in an up to ∼ ± 40 % change in sea-level contribution relative to our baseline simulations that used the median value. Using a linear basal sliding law reduces sea-level contribution by 51 %–73 % relative to our baseline nonlinear sliding law with an exponent of 1/5. When using basal sliding law exponents of 1/3 and 1/10, the overall difference from our baseline simulations at 2300 is on the order of 10 %. The Amundsen Sea Embayment region displays a strongly non-linear dependence of mass loss on the sliding law exponent, with no discernible relationship between the sliding law exponent and the mass loss by 2300, while the sectors feeding the Ross and Filchner-Ronne ice shelves exhibit more mass loss with a more-plastic sliding law. Our model fidelity sensitivity experiments reveal a 9 %–31 % increase in sea-level contribution when using a depth-integrated stress balance approximation relative to our three-dimensional solver, while using a fixed-in-time temperature field increases sea-level contribution by 14 %–88 % relative to two thermomechanically coupled configurations. Our 72-member ensemble and analysis of variance show that the uncertainty in long-term projections is dominated by the choice of Earth system model forcing and the presence or absence of hydrofracture forcing, rather than uncertainty in sliding and sub-shelf melt parameters.

58 GEOSCIENCES↗

DOE OSTI2026

TRACE Input Modernization

This work presents a Tom’s Obvious Minimal Language (TOML)-based representation of input for the US Nuclear Regulatory Commission’s TRAC/RELAP Advanced Computational Engine (TRACE) thermal hydraulics code. Implemented using the Workbench Analysis Sequence Processor (WASP), the approach maps traditional TRACE input structures to a hierarchical format composed of named parameters, typed values, and native data collections. The resulting representation preserves TRACE’s existing modeling capabilities while providing a modern, structured interface for model development and management. WASP further extends TOML through a file import directive that supports modular model composition and reusable input organization. In addition, WASP provides extended array data entry convenience with various data repeat and interpolation capabilities. Examples of the new TOML syntax are provided for major TRACE input categories, including hydraulic components, heat structures, control systems, and trip logic. The TOML representation establishes a foundation for improved validation, tooling, automation, and model maintainability while remaining compatible with existing TRACE workflows. To facilitate migration to the TOML-based input format, the TRACE executable now supports conversion of native TRACE input into an intermediate JSON representation. A Python utility subsequently transforms the JSON data into an equivalent TOML model. Lastly, the TRACE executable now supports execution using TOML-formatted input.

Lefebvre, Robert A. [Oak Ridge National Laboratory↗

DOE OSTI2026

Nanoscale Observation and Control of Quasiparticle Induced Magnetic Noise in a Superconducting Resonator

Superconducting circuits are arguably taking a leading role in driving the ongoing quantum technological revolution. A detailed knowledge of the microscopic fluctuating electromagnetic properties plays an important role in advancing the circuitry design, testing, and material integration of cutting-edge superconducting quantum electronics. Here, in this work, we report scanning nitrogen-vacancy (NV) quantum sensing of local magnetic noise environment of an on-chip superconducting resonator. We find that quasiparticle-induced fluctuating magnetic fields can drive NV spin relaxation, which shows a peak value around the superconducting transition point of niobium at the thermal equilibrium state. External microwave driving at the resonator mode frequency significantly increases the quasiparticle density, leading to enhancement of magnetic noise. We further perform optically detected magnetic resonance measurements to demonstrate quasiparticle magnetic noise mediated off-resonant dipole coupling between the NV center and niobium resonator. Our Letter reports experimental observation of the Hebel-Slichter peak signature by an external sensor outside of a superconductor. The presented study also highlights the advantages of quantum sensors in investigating miniaturized superconducting devices, providing insights into their future performance improvements.

Li, Senlei [Georgia Institute of Technology]↗

DOE OSTI2026

Solar Heat for Industrial Processes: Integration with Chemical Reactors

The integration of solar thermal systems with chemical reactors has been proposed as part of a larger effort to develop and deploy solar heat for industrial processes (SHIP) technologies. A strong motivation for SHIP processes and technologies is the potential for high thermal efficiency coupled with low-cost thermal energy storage (TES) which can enable commercial deployment of such systems. While there are different ways to categorize SHIP technologies, one important such distinction is between directly irradiated systems and indirect off-sun process driven by a SHIP system. While directly irradiated systems can provide high thermal efficiencies and high fluxes, they usually require complex engineering solutions due to the need for redesigning the established processes and unit operations. In most cases, it is also more challenging to couple such a process to a TES system, losing some of the benefits of SHIP. On the other hand, using a SHIP system to drive an industrial process off-sun can allow better integration with existing process chains, easier TES capabilities, and potential for more applications fitting a specific SHIP technology. However, the integration of SHIP systems with the industrial processes is not fully explored in detail, especially in the case of high-temperature processes such as reforming, cracking, cement manufacturing, and iron/steelmaking. Many of these systems require heating fluxes of >50 kW/m^2, supplied via combustion of hydrocarbons in a fire box and benefitting from radiative heat transfer between the flue gases and the reaction zones. As such, using SHIP systems for such processes is more complex than providing the same thermal input in the form of a heat transfer medium (HTM) entering the reactor, kiln, or furnace. Moreover, in case convective heat transfer using SHIP is envisioned, for example using supercritical CO2 as the HTM from a particle receiver, the thermal integration might be more challenging than initially envisioned: lower heat transfer coefficients and limited approach temperature might require large flow rates, causing a mismatch between the process thermal requirements and the thermal capacity of the SHIP system. In addition, even if the heat exchange between SHIP and reactor is effective, there is still a cold leg HTM at the reaction temperature or slightly below it. Chemical plants usually include a set of heat exchangers, heat recovery steam generators, and even power generation units - in a tightly integrated design - to recover the flue gases which are eventually vented. With SHIP systems mostly operating on a closed HTM loop, bottoming the cold leg is crucial. In this talk, we will present different modeling results for a variety of syngas production reactions, using catalytic and chemical looping processes, and discuss some of the challenges and design considerations for off-sun chemical reactors using SHIP systems.

14 SOLAR ENERGY↗

DOE OSTI2026

Enzymatic Nylon Deconstruction: Enzyme Discovery, Engineering, and Opportunities

Nylons are widely used synthetic polyamides valued for their strength, versatility, and durability across diverse applications. However, their petrochemical origin and energy-intensive production underscore the need for efficient, circular solutions. Conventional recycling methods remain limited by incomplete recovery, material degradation, and costly sorting requirements. Enzymatic depolymerization offers a selective, low-energy alternative capable of processing mixed waste streams under mild conditions. While significant progress has been achieved for polyesters, enzymatic degradation of polyamides is still at an early stage. The discovery of nylon hydrolases demonstrated the potential of biological systems to evolve catalysts for synthetic polyamides, yet reported depolymerization yields remain low. These limitations reflect both the structural complexity of nylons and the need for improved enzyme discovery and engineering. In conclusion, this review highlights recent advances, key challenges, and future directions for enzymatic nylon recycling, outlining its potential role enabling mixed polymer waste to be used as a green feedstock for remanufacturing.

Amides↗

DOE OSTI2024

Estradiol associations with brain functional connectivity in postmenopausal women

Abstract Objective Previous studies have found that estrogens play a role in functional connectivity in the brain; however, little research has been done regarding how estradiol is associated with functional connectivity in postmenopausal women. The purpose of this study was to examine the relationship between estradiol and functional connectivity in postmenopausal women. Methods Structural and blood oxygenation level–dependent resting-state magnetic resonance imaging scans of 88 cognitively healthy postmenopausal individuals were obtained along with blood samples collected the same day as the magnetic resonance imaging to assess hormone levels. We generated connectivity values in CONN toolbox version 20.b, an SPM-based software. Results A regression analysis was run using estradiol level and regions of interest (ROI), including the hippocampus, parahippocampus, dorsolateral prefrontal cortex, and precuneus. Estradiol level was found to enhance parahippocampal gyrus anterior division left functional connectivity during ROI-to-ROI regression analysis. Estradiol enhanced functional connectivity between the parahippocampal gyrus anterior division left and the precuneus as well as the parahippocampal gyrus anterior division left and parahippocampal gyrus posterior division right. An exploratory analysis showed that years since the final menstrual period was related to enhanced connectivity between regions within the frontoparietal network. Conclusions These results illustrated the relationship between estradiol level and functional connectivity in postmenopausal women. They have implications for understanding how the functioning of the brain changes for individuals after menopause that may eventually lead to changes in cognition and behavior in older ages.

Obstetrics & Gynecology↗

DOE OSTI2026

Criteria for Retention of 3013 S1 Containers Based on Relative Risk and Expert Judgment

An evaluation was performed to assess the suitability of thirty-three 3013 containers proposed for retention. These containers have moisture levels greater than 0.08 wt.% – the S1 population. The remainder of the S1 population stored at SRS will be down blended and disposed of by the end of 2028. Based on field surveillance and shelf-life data available to date as well as informed technical judgment, no container is currently expected to fail in its 50-year storage period. However, corrosion risk varies across the S1 population. Relative risks were evaluated using predicted Consensus Scores and their 95% Upper Prediction Limits (UPLs). The predicted values are based on a statistical model of Consensus Score as a function of moisture, chloride, and whether the packaged material was electrorefining scrap packaged at Hanford. Consensus Score has been shown to be a useful indicator of corrosion potential, and the UPL captures uncertainty in the model predictions, providing a conservative indicator of corrosion potential. Using UPLs to determine relative risks, together with expert review, three containers were identified as not suitable for retention, and the remainder were determined to be suitable.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2021

Tritium Betavoltaic Powered Sensor Platforms: Power Augmentation with Scintillating Particles

Betavoltaics (BV) are long-life power sources that typically convert beta particle radiation into electricity. Largely, the radioactive decays within the source go unharvested by the device. This work seeks to augment the power generation of BV devices by integration of scintillating particles within the radiative getter to convert beta emission which would otherwise not leave the getter into usable light for power generation. Silica-covered barium fluoride scintillating particles were integrated into a tritiated water getter. Power generation was increased from 100s of nW to µW levels with the addition of 0.2 wt. % particles into the getter. Nanowatt-scale sensor platforms were demonstrated with the µW BV devices and the maximum possible lifetime of such platforms was estimated. As this technique enables higher power density BV devices from conventional Si semiconductors (compared to wider bandgap BVs), the further implementation may lower the barrier-to-deployment of these long-life power/sensor platforms.

42 ENGINEERING↗

DOE OSTI2024

Effect of Biomass Water Dynamics in Cosmic-Ray Neutron Sensor Observations: A Long-Term Analysis of Maize–Soybean Rotation in Nebraska

Precise soil water content (SWC) measurement is crucial for effective water resource management. This study utilizes the Cosmic-Ray Neutron Sensor (CRNS) for area-averaged SWC measurements, emphasizing the need to consider all hydrogen sources, including time-variable plant biomass and water content. Near Mead, Nebraska, three field sites (CSP1, CSP2, and CSP3) growing a maize–soybean rotation were monitored for 5 (CSP1 and CSP2) and 13 (CSP3) years. Data collection included destructive biomass water equivalent (BWE) biweekly sampling, epithermal neutron counts, atmospheric meteorological variables, and point-scale SWC from a sparse time domain reflectometry (TDR) network (four locations and five depths). In 2023, dense gravimetric SWC surveys were collected eight (CSP1 and CSP2) and nine (CSP3) times over the growing season (April to October). The N0 parameter exhibited a linear relationship with BWE, suggesting that a straightforward vegetation correction factor may be suitable (fb). Results from the 2023 gravimetric surveys and long-term TDR data indicated a neutron count rate reduction of about 1% for every 1 kg m−2 (or mm of water) increase in BWE. This reduction factor aligns with existing shorter-term row crop studies but nearly doubles the value previously reported for forests. This long-term study contributes insights into the vegetation correction factor for CRNS, helping resolve a long-standing issue within the CRNS community.

Chemistry↗