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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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At least 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Analysis of heat transfer and AuNPs-mediated photo-thermal inactivation of E. coli at varying laser powers using single-phase CFD modeling

In the wake of the COVID-19 pandemics, the demand for innovative and effective methods of bacterial inactivation has become a critical area of research, providing the impetus for this study. The purpose of this research is to analyze the AuNPs-mediated photothermal inactivation of E. coli. Gold nanoparticles irradiated by laser represent a promising technique for combating bacterial infection that combines high-tech and scientific progress. The intermediate aim of the work was to present the calibration of the model with respect to the gold nanorods experiment. The purpose of this work is to study the effect of initial concentration of E. coli bacteria, the design of the chamber and the laser power on heat transfer and inactivation of E. coli bacteria. Using the CFD simulation, the work combines three main concepts. 1. The conversion of laser light to heat has been described by a combination of three distinctive approximations: a- Discrete particle integration to take into account every nanoparticle within the system, b- Rayleigh-Drude approximation to determine the scattering and extinction coefficients and c- Lambert–Beer–Bourger law to describe the decrease in laser intensity across the AuNPs. 2. The contribution of the presence of E. coli bacteria to the thermal and fluid-dynamic fields in the microdevice was modeled by single-phase approach by determining the effective thermophysical properties of the water-bacteria mixture. 3. An approach based on a temperature threshold attained at which bacteria will be inactivated, has been used to predict bacterial response to temperature increases. The comparison of the thermal fields and temporal temperature changes obtained by the CFD simulation with those obtained experimentally confirms the accuracy of the light-heat conversion model derived from the aforementioned approximations. The results show a linear relationship between maximum temperature and variation in laser power over the range studied, which is in line with previous experimental results. It was also found that the temperature inside the microchamber can exceed 55 °C only when a laser power higher than 0.8 W is used, so bacterial inactivation begins. The experimental data allows to determinate the concentration of nanoparticles. This parameter is introduced into the mathematical model obtaining the same number of AuNPs. However, this assumption introduces a certain simplification, as in the mathematical model the distribution of nanoparticles is uniform. This work is directly connected to the use of gold nanoparticles for energy conversion, as well as the field of bacterial inactivation in microfluidic systems such as lab-on-a-chip. Presented mathematical and numerical models can be extended to the entire spectrum of wavelengths with particular use of white light in the inactivation of bacteria. This work represents a significant advancement in the field, as to the best of the authors’ knowledge, it is the first to employ a single-phase computational fluid dynamics (CFD) approach specifically combined with the thermal inactivation of bacteria. Moreover, this research pioneers the use of a numerical simulation to analyze the temperature threshold of photothermal inactivation of E. coli mediated by gold nanorods (AuNRs). The integration of these methodologies offers a new perspective on optimizing bacterial inactivation techniques, making this study a valuable contribution to both computational modeling and biomedical applications.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Thermal Performance of a Conduction-Cooled CCT Dipole ReBCO Magnet: Several Cycles of Cool-Down and Thermal Gradient Measurements

Here, this paper presents experimental results from conduction-cooled thermal testing of a ReBCO canted cosine theta (CCT) magnet (C2), originally designed and fabricated at LBNL using CORC cables. While the performance of the coil under liquid helium and nitrogen environments has been previously established, this study explores its behavior under conduction cooling using a large test cryostat at The Ohio State University. The magnet, measuring 613 mm in length and weighing ∼75 kg, consists of four helical layers wound with ReBCO-based CORC wire and was thermally anchored to a copper cold ring supported by a G-10 strongback. Cooling was provided by two Sumitomo RDK-415D cryocoolers, offering a combined 3 W at 4.2 K and 150 W at 77 K. Multiple thermal cycles were performed, with cooldown durations of up to 45 hours. Final base temperatures of approximately 10.8 K (at the coil edge) and 12.0 K (at the coil center) were achieved, with an axial temperature difference of approximately 1.2 K. The warm-up period extended over approximately 24.6 hours. Voltage measurements from all four layers were recorded during cooldown and warmup. The system demonstrated stable cooldown performance, repeatable gradients, and good thermal anchoring. These results support the feasibility of conduction cooling in large-scale HTS magnets, aligning with broader goals for “green” cryogen-free accelerator technologies and paving the way for more sustainable, scalable, and energy-efficient high-field magnet systems in next-generation particle accelerators.

Canted cosine theta magnets↗
DOE OSTI2024

Semicoherent symmetric quantum processes: Theory and applications

Discovering pragmatic and efficient approaches to construct ε-approximations of quantum operators such as real (imaginary) time-evolution propagators in terms of the basic quantum operations (gates) is challenging. Prior ε-approximations are invaluable, in that they enable the compilation of classical and quantum algorithm modeling of, e.g., dynamical and thermodynamic quantum properties. In parallel, symmetries are powerful tools concisely describing the fundamental laws of nature; the symmetric underpinnings of physical laws have consistently provided profound insights and substantially increased predictive power. In this work, we consider the interplay between the ε-approximate processes and the exact symmetries in a semicoherent context—where measurements occur at each logical clock cycle. Here we draw inspiration from Pascual Jordan's groundbreaking formulation of nonassociative, but commutative, symmetric algebraic form. Our symmetrized formalism is then applied in various domains such as quantum random walks, real-time evolutions, variational algorithm ansatzes, and efficient entanglement verification. Our work paves the way for a deeper understanding and greater appreciation of how symmetries can be used to control quantum dynamics in settings where coherence is a limited resource.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Modifying the Asynchronous Jacobi Method for Data Corruption Resilience

Moving scientific computation from high-performance computing (HPC) and cloud computing (CC) environments to devices on the edge, i.e., physically near instruments of interest, has received tremendous interest in recent years. Such edge computing environments can operate on data in situ, offering enticing benefits over data aggregation to HPC and CC facilities that include avoiding costs of transmission, increased data privacy, and real-time data analysis. Because of the inherent unreliability of edge computing environments, new fault-tolerant approaches must be developed before the benefits of edge computing can be realized. Motivated by algorithm-based fault tolerance, a variant of the asynchronous Jacobi (ASJ) method is developed that achieves resilience to data corruption by rejecting solution approximations from neighbor devices according to a bound derived from convergence theory. Numerical results on a two-dimensional Poisson problem show that the new rejection criterion, along with a novel approximation to the shortest path length on which the criterion depends, restores convergence for the ASJ variant in the presence of certain types data corruption. Numerical results are obtained for when the singular values in the analytic bound are approximated. Additional linear systems are also explored, one with a more dense sparsity pattern and one that includes advection. All results indicate that successful resilience to data corruption depends on whether the bound tightens fast enough to reject corrupted data before the iteration evolution deviates significantly from that predicted by the convergence theory defining the bound. This observation generalizes to future work on algorithm-based fault tolerance for other asynchronous algorithms, including upcoming approaches that leverage Krylov subspaces.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Bias-Variance Trade-Off in Physics-Informed Neural Networks with Randomized Smoothing for High-Dimensional PDEs

Physics-Informed Neural Networks (PINNs) have triggered a paradigm shift in scientific computing, leveraging mesh-free properties and robust approximation capabilities. While proving effective for low-dimensional partial differential equations (PDEs), the computational cost of PINNs remains a hurdle in high-dimensional scenarios. This is particularly pronounced when computing high-order and high-dimensional derivatives in the physics-informed loss. Randomized Smoothing PINN (RS-PINN) introduces Gaussian noise for stochastic smoothing of the original neural net model, enabling the use of Monte Carlo methods for derivative approximation, which eliminates the need for costly automatic differentiation. Despite its computational efficiency, especially in the approximation of high-dimensional derivatives, RS-PINN introduces biases in both loss and gradients, negatively impacting convergence, especially when coupled with stochastic gradient descent (SGD) algorithms. We present a comprehensive analysis of biases in RS-PINN, attributing them to the nonlinearity of the Mean Squared Error (MSE) loss as well as the intrinsic nonlinearity of the PDE itself. We propose tailored bias correction techniques, delineating their application based on the order of PDE nonlinearity. The derivation of an unbiased RS-PINN allows for a detailed examination of its advantages and disadvantages compared to the biased version. Specifically, the biased version has a lower variance and runs faster than the unbiased version, but it is less accurate due to the bias. To optimize the bias-variance trade-off, we combine the two approaches in a hybrid method that balances the rapid convergence of the biased version with the high accuracy of the unbiased version. In addition to methodological contributions, we present an enhanced implementation of RS-PINN. Extensive experiments on diverse high-dimensional PDEs, including Fokker-Planck, Hamilton-Jacobi-Bellman (HJB), viscous Burgers’, Allen-Cahn, and Sine-Gordon equations, illustrate the bias-variance trade-off and highlight the effectiveness of the hybrid RS-PINN. Empirical guidelines are provided for selecting biased, unbiased, or hybrid versions, depending on the dimensionality and nonlinearity of the specific PDE problem.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Gaussian Process Regression under Computational and Epistemic Misspecification

Gaussian process regression is a classical kernel method for function estimation and data interpolation. In large data applications, computational costs can be reduced using low-rank or sparse approximations of the kernel. This paper investigates the effect of such kernel approximations on the interpolation error. We introduce a unified framework to analyze Gaussian process regression under important classes of computational misspecification: Karhunen-Loève expansions that result in low-rank kernel approximations, multiscale wavelet expansions that induce sparsity in the covariance matrix, and finite element representations that induce sparsity in the precision matrix. Furthermore, our theory also accounts for epistemic misspecification in the choice of kernel parameters.

Gaussian process regression↗
DOE OSTI2026

Spatially Accelerated Winding Numbers for Curved Geometry

The generalized winding number (GWN) is a scalar field that supports robust containment queries on curved geometry, including non-watertight, overlapping, and nested boundary representations. While queries can be easily parallelized over samples, direct evaluation on parametric curves and surfaces remains costly for large and complex models. Fast, state-of-the-art GWN approaches leverage a spatial index to approximate the GWN, typically coupled with a Taylor expansion which approximates the GWN contribution for far clusters of geometric primitives. However, such methods operate only on discrete inputs such as triangle meshes and point clouds, and would introduce containment errors near boundaries if applied to curved input. We extend support for fast GWN evaluation over arbitrary collections of NURBS curves in 2D and trimmed NURBS patches in 3D via a Bounding Volume Hierarchy that stores efficiently precomputed moment data in the hierarchy nodes. When querying the hierarchy, approximations for far clusters are used alongside direct evaluation for nearby NURBS primitives, achieving sub-linear complexity while preserving the geometric features in the vicinity of the query point. Central to our performance improvements is an adaptive subdivision strategy for NURBS primitives during a preprocessing phase, creating better spatial partitions while retaining the same accuracy for containment decisions as a direct evaluation. We demonstrate the performance and accuracy of our approach across a large collection of 2D and 3D datasets.

Computer science↗
DOE OSTI2025

Pxl

The code consists of several scripts. The image is fetched from a predefined URL, downloaded, and is displayed in the virtual environment at a predefined location. The image is also dynamically scaled to fit in the virtual environment depending on its size. The image is sent to have each pixel's value written to a CSV file. While the CSV is being written, a dictionary is populated with values that map each pixel to a temperature reading. The image's height, width, position and references to its corners are sent to make a button that is the same size as the image and placed right behind the image in the virtual scene. The button defines behavior that should be triggered when the user pushes the image. Unity provides visual cues that alert the user when they are about to touch something in the virtual environment. The code holds references to the cues for the left and right hands. The button queries the cue tracker and receives the position of the active cue in the form of a 3D vector. The 3D vector is compared to the bottom left corner of the image to transform the world space coordinates of the cue to the pixel space of the image. The specific pixel is approximated relative to how far left and up the user touched from the bottom left corner of the image. The approximated pixel value, which is represented as a coordinate in 2D space, is used to retrieve the temperature value associated with the approximated pixel. A window of text is then updated to display the temperature reading.

. Otis, KrystianeS [Idaho National Laboratory (INL↗
DOE OSTI2024

Spatially Local Surrogate Modeling of Subgrid-Scale Effects in Idealized Atmospheric Flows: A Deep Learned Approach Using High-Resolution Simulation Data

Abstract We introduce a machine learned surrogate model from high-resolution simulation data to capture the subgrid-scale effects in dry, stratified atmospheric flows. We use deep neural networks (NNs) to model the spatially local state differences between a coarse-resolution simulation and a high-resolution simulation. The setup enables the capture of both dissipative and antidissipative effects in the state differences. The NN model is able to accurately capture the state differences in offline tests outside the training regime. In online tests intended for production use, the NN-coupled coarse simulation has higher accuracy over a significant period of time compared to the coarse-resolution simulation without any correction. We provide evidence of the capability of the NN model to accurately capture high-gradient regions in the flow field. With the accumulation of the errors, the NN-coupled simulation becomes computationally unstable after approximately 90 coarse simulation time steps. Insights gained from these surrogate models further pave the way for formulating stable, complex, physics-based spatially local NN models which are driven by traditional subgrid-scale turbulence closure models. Significance Statement Flows in the atmosphere are highly chaotic and turbulent, comprising flow structures of broad scales. For effective computational modeling of atmospheric flows, the effects of the small- and large-scale structures need to be captured by the simulations. Capturing the small-scale structures requires fine-resolution simulations. Even with the current state-of-the-art supercomputers, it can be prohibitively expensive to simulate these flows when computed for the entire earth over climate time scales. Thus, it is necessary to focus on the larger-scale structures using a coarse-resolution simulation while capturing the effects of the smaller-scale structures using some parameterization (approximation) scheme and incorporating it into the coarse-resolution simulation. We use machine learning to model the effects of the small-scale structures (subgrid-scale effects) in atmospheric flows. Data from a fine-resolution simulation is used to compute the missing subgrid-scale effects in coarse-resolution simulations. We then use machine learning models to approximate these differences between the coarse- and fine-resolution simulations. We see improved accuracy for the coarse-resolution simulations when corrected using these machine learned models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

AmeriFlux US-MEF Manitou Experimental Forest

This is the AmeriFlux version of the carbon flux data for the site US-MEF Manitou Experimental Forest. Site Description - This site was established on an existing 30-m tower structure at the Forest Service's Manitou Experimental Forest, Colorado. Manitou Experimental Forest is located approximately 38 km northwest of Colorado Springs, within the Pike National Forest. The tower was constructed and used between 2008 and 2013 by NCAR for the BEACHON project and has line power and internet connections. The tower is located in approximately 12 km^2 of ponderosa pine forest and savannah with a land use history of thinning and prescribed burning, though these disturbances have not occurred for many years. The tower is situated in a broad, flat valley that drains to the north. Early research at the site was focused mainly on grazing, while more recently it has turned broadly to the ecology and management of ponderosa pine ecosystems. In 2002, the Hayman Fire burned approximately 56,000 ha to the west and northwest of the tower location.

Frank, John [US Forest Service, Rocky Mountain Res↗
DOE OSTI2026

AmeriFlux FLUXNET-1F US-MEF Manitou Experimental Forest

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-MEF Manitou Experimental Forest. This is the FLUXNET version of the carbon flux data for the site US-MEF Manitou Experimental Forest produced by applying the standard ONEFlux (1F) software. Site Description - This site was established on an existing 30-m tower structure at the Forest Service's Manitou Experimental Forest, Colorado. Manitou Experimental Forest is located approximately 38 km northwest of Colorado Springs, within the Pike National Forest. The tower was constructed and used between 2008 and 2013 by NCAR for the BEACHON project and has line power and internet connections. The tower is located in approximately 12 km^2 of ponderosa pine forest and savannah with a land use history of thinning and prescribed burning, though these disturbances have not occurred for many years. The tower is situated in a broad, flat valley that drains to the north. Early research at the site was focused mainly on grazing, while more recently it has turned broadly to the ecology and management of ponderosa pine ecosystems. In 2002, the Hayman Fire burned approximately 56,000 ha to the west and northwest of the tower location.

Frank, John [US Forest Service, Rocky Mountain Res↗
DOE OSTI2024

Overview of Collaborative Research Between UNICAMP in Brazil and Fermilab in Cryogenics

The Long-Baseline Neutrino Facility (LBNF) situated at the Sanford Underground Research Facility (SURF) in Lead, South Dakota, serves as the host for the Deep Underground Neutrino Experiment (DUNE), employing cryostats with nearly 70,000 metric tons of high purity liquid argon (LAr). The integrity of LAr quality is pivotal in determining the electron lifetime within DUNE, directly impacting its signal-to-noise ratio. Specifically, Far Detector 1 (FD-1) in cryostat 1 requires an electron lifetime over 3 ms within its 3.5 m drift, corresponding to less than 100 parts-per-trillion (ppt) Oxygen equivalent contamination. Far Detector 2 (FD-2) in cryostat 2 demands over 6 ms electron lifetime within its 6.0 m drift, corresponding to less than 50 ppt Oxygen equivalent contamination. Nitrogen (N2) absorption of LAr scintillation light, known as quenching, necessitates N2 contamination in LAr to remain below 1 ppm to minimize photon loss and enhance energy reconstruction. Studies indicate that at 1 ppm N2, approximately 20% of scintillation light is lost, highlighting the importance of minimizing N2 contamination. Brazil State University of Campinas's (UNICAMP) contribution to LBNF focuses on developing argon purification and regeneration for DUNE FD-1 and FD-2. To that effect, they constructed a test facility to perform studies on LAr purification at a smaller scale, the Purification Liquid Argon Cryostat (PuLArC) with approximately 90 liters of LAr. One of the filtration materials was considered and tested Li-FAU molecular sieve. Value engineering on argon purification media was conducted, leading to the identification of Li-FAU zeolite's ability to effectively capture N2 impurities during LAr circulation. Testing at UNICAMP's PuLArC facility demonstrated that 1 kg of Li-FAU is capable of reducing N2 contamination from 20-50 ppm to 0.1-1.0 ppm within 1-2 hours of circulation. In October 2023, testing at the Iceberg cryostat in Fermilab's Noble Liquid Test Facility (NLTF), with approximately 2,625 liters of LAr, confirmed the efficacy of 3 kg of Li-FAU in reducing N2 contamination from ~ 5 ppm of injected N2 down to less than 1 ppm over 96-hour cycles, showcasing its potential for larger-scale LAr cryostats. Further tests are planned to validate Li-FAU's use as a possible alternative to Molecular Sieve 4A in LBNF-DUNE and related liquid argon experiments. This contribution will describe how the research was performed and present the test setups and results in detail. This advancement not only has the potential to enhance DUNE's precision but also to elevate liquid argon experiments globally, showcasing the power of international scientific collaboration.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Integrity Monitoring, Prediction and Assessment, Corrosion Control, and Repair of the Hanford Storage Tanks – 25213

The Hanford Nuclear Reservation site contains approximately 211 million liters of radioactive and chemically hazardous waste arising from nuclear weapons production, beginning with World War II, and continuing through the Cold War [1]. The waste is stored in 177 carbon-steel underground storage tanks, of which 149 are single-shell tanks (SSTs) and the remaining are double-shell tanks (DSTs). The mission of an ongoing River Protection Project is to retrieve the waste from the underground storage tanks and then treat and immobilize (i.e., vitrify) it for disposal. Waste from the older SSTs is being progressively retrieved into the newer DSTs for storage pending treatment, immobilization, and disposal. Figure 1 depicts a typical DST design [2]. The tank is approximately 23 m in diameter and 9 m high and has a domed structure and has a capacity of 4000 m3. The tank wall and floor vary in thickness between approximately 10 mm and 25 mm depending on location. The thicker wall sections are near the curved transition between the tank wall and the floor, while the thinner sections are located near the top of the tank wall. The tank floor thickness varies from 25 mm at the tank center to 10 mm near the tank wall. The tanks were constructed of either ASTM A516 Grade 65 or ASTM A537 Class 1 carbon steel and were post-weld heat treated to reduce the risk of SCC.

Shukla, Pavan K. [Savannah River National Laborato↗
DOE OSTI2025

Window Cooling Studies and Disk Vibration Testing on a Subset of Mo-100 Disks

Production of metastable Technetium-99 (Tc-99m), a radioactive tracer that emits gamma rays, is vital to the medical imaging community. Tc-99m is extracted from the decay of Molybdenum-99 (Mo-99) which has a half-life of about 2-3 days. The work presented in this report is part of the NNSA’s mission to produce Mo-99 commercially, within the US, without the use of highly enriched uranium (HEU) in support of nonproliferation and global security. Los Alamos National Laboratory (LANL) is working with NorthStar Medical Radioisotopes (NMR) on their efforts to produce Mo-99 through the irradiation of Mo-100 targets using an electron beam. The NMR target comprises a stack of approximately 60-70 Mo-100 disks with diameter 24 mm and thickness 0.74 mm held in stainless steel laminations, each separated using 0.25 mm thick stainless-steel spacers. The symmetric target stack is housed in an Inconel vessel with two Inconel windows on either side. Two electron accelerators are used to produce 40 MeV, 3.16 µA electron beams each that penetrate the Inconel windows and irradiate the Mo-100 disks. Approximately 90% of the total 250 kW beam power is deposited in the NMR target during the irradiation process, with a smaller percentage adding up to 2.2 kW of heat deposited on the Inconel window. During irradiation, pressurized helium gas flows through thin gaps between the disks cooling the beam window, target disks, disk laminations and spacers. Both NMR and LANL have found during cold testing of the target system (no heat deposition) that the Mo 100 disks undergo significant mass loss and disk breakage due to vibrations induced by the flowing helium gas. The mass loss is not only undesirable due to monetary loss from reduced final quantities of Mo-99, but also due to the hazards associated with radioactive material trapped in the cooling lines and particle filters. The effect of flow rate and target geometry on the flow induced vibrations need to be quantified, and recommendations provided to minimize this mass loss. LANL has previously also tested NMR’s Inconel beam window by heating the window, while flowing pressurized helium, using the average heat deposited on the window. However, the NMR beam is pulsed with a duty cycle of 12.5%, which introduces oscillation in temperature around the nominal 600 °C steady state value with each pulse. Available fatigue curves for Inconel are few, established for room temperature, and they are based on mechanical strain cycles not thermally induced strain as in the NMR target. The effect of pulsed beam heating on the Inconel window therefore needs to be quantified. This report details the experiments conducted to assess the factors that lead to mass loss in the NMR target disks as well as to understand the effect of a pulsed beam on NMR’s Inconel window. This work describes LANL’s experimental characterization of the flow induced vibrations and disk mass loss in a reduced scale set-up containing 5 to 10 Mo-100 disks. We use high speed imaging, displacement measurements and microphone measurements combined with signal processing to estimate the vibration frequency of each disk. The effect of disk thickness, target fit and duration of testing on the mass loss is described. We find that in the current configuration of NMR targets, the vibrations and mass loss on the first disk are minimized, while those in the adjacent disks are highest. The microphone and high-speed image data show that increased flow rates and increased duration of testing increases vibration frequency and mass loss. The mass loss is due to both disk rotation and back and forth motion. There are visible wear marks on the disks with the highest mass loss. We also note that the current NMR window gap reduces flow induced vibrations compared to the previous smaller gaps. Improved target holders significantly reduce disk mass loss to almost negligible quantities. This work finds that the larger window to first disk gap and improved target holder geometry should allow NMR to successfully conduct irradiations with minimal mass loss. The window tests were conducted to understand the effect of a pulsed beam on both the window longevity and to estimate the window temperature and displacement during pulsing. The experiments presented here were performed at significantly low power, due to the limitations of the induction heating system. The window temperature rose to approximately 73 °C with a significantly reduced power of 45 W without beam pulsing. With a 5 Hz pulse rate, 12.5% duty cycle, the window temperature remained constant at 26 °C. These experiments will be repeated with improved coil geometry and reported in upcoming journal papers.

42 ENGINEERING↗
DOE OSTI2025

4.3.1.1 TCF: Recovery of Lithium from Geothermal Brine with Lithium-Aluminum Layered Double Hydroxide Chloride Sorbents

Lithium has gained importance as a near-critical element for various energy storage applications, and efforts are ongoing to develop simple and cost-effective methods for lithium recovery. For instance, in a typical 50 MW geothermal power plant in the Salton Sea, United States, approximately 15,000 metric tons of Li 2 CO 3 or LiOH salts can be produced annually by recovering and converting LiCl from geothermal plant waste solutions. Currently, approximately 390 MW of geothermal power is generated in the Salton Sea Known Geothermal Resource Area, which corresponds to potential Li 2 CO 3 production of approximately 120,000 metric tons per year. This makes lithium recovery from geothermal brines a promising, potentially low-cost source of lithium, contributing significantly to the global supply chain.

15 GEOTHERMAL ENERGY↗
DOE OSTI2025

Williston Basin Resource Study for Commercial-Scale Subsurface Hydrogen Storage

The Energy & Environmental Research Center (EERC), in partnership with the U.S. Department of Energy (DOE) National Energy Technology Laboratory (NETL), the EERC’s State Energy Research Center (SERC), MPLX Operations LLC, and TC Energy Development Holdings Inc. (a subsidiary of TC Energy Corporation), studied the potential for subsurface hydrogen storage and recovery in the Williston Basin of western North Dakota. The project’s goal was to evaluate the feasibility of large-scale, secure geologic H 2 storage to support future hydrogen generation, storage, and use. This work included laboratory testing, H 2 –rock–fluid exposure experiments, literature reviews on H 2 embrittlement, and reservoir modeling and simulations. The study included an assessment of storage potential across three types of storage reservoirs using both reservoir simulation and DOE’s web-based tool SHASTA-HELP (Subsurface Hydrogen Assessment, Storage, and Technology Acceleration – Hydrogen Estimator for Logistical Planning), as well as investigation of potential H 2 production and markets for commercial-scale deployment. Building on prior EERC gas storage research, three storage options were selected for detailed evaluation: the Broom Creek Formation (a clastic saline reservoir), the Dickinson Lodgepole Mounds (DLM) complex (carbonate mud mound structures) of the Lodgepole Formation (an active oil and gas producing reservoir), and the Dunham Salt Interval of the Piper Formation (to be used for engineered salt cavern development). These targets were prioritized based on prior EERC research using datasets related to seal capacity, reservoir quality, mechanical integrity, and injectivity. Exposure tests on Broom Creek and DLM samples showed mineral dissolution and precipitation that increased brine salinity and altered reservoir rock surfaces. Although these results provide useful insight, they are limited by small sample sizes and short-term (30-day) exposure, requiring further study to assess long-term storage integrity. Salt formations were not tested because of their known nonreactivity and established mechanical stability. Results of reservoir simulations performed for a single site demonstrated that the Broom Creek Formation may be capable of receiving up to 42,000 tonnes of injected H 2 over 7 months via one well. H 2 recovery took place over 5 months, resulting in approximately 26,000 tonnes (~62% without cushion gas [CG]). This work suggests water production may be important and subsequent cycles of injection and production may perform more efficiently; however, significant site-specific work in the future is needed to assess actual reservoir performance of injection and withdrawal of H 2 storage. For oil reservoir potential, a multiple-well model was used to simulate injection of approximately 32,000 tonnes of H 2 into a single wellbore while simultaneously producing in place reservoir fluids from four offset wells to maintain reservoir pressure. The simulation results suggested a high recovery (~98%); in addition, cost advantages through existing infrastructure could be realized. Challenges in this reservoir include vi managing gas purity and leakage risks. In both scenarios, production of H 2 takes place in a single-well scenario with 10 cycles (7 months of injection and 5 months of production) over 10 years. Finally, the use of engineered caverns in the Dunhan Salt was evaluated, and the results suggest that while they have a smaller capacity (<1000 tonnes per cavern), they exhibit nearly complete gas recovery (>99%), fast response times, and low purity risk. While caverns in North Dakota may be smaller in capacity, fields can be developed in galleries to accommodate the volumetric needs and rapid turnaround times necessary to meet market demands. Geographic limitations and thin salt intervals in North Dakota may represent less total storage potential than salt domes elsewhere, but significant opportunities exist to expand this market for gas storage in North Dakota. A basinwide assessment was performed to estimate a first-of-its-kind value for H 2 storage on a large scale. DOE’s SHASTA-HELP, combined with EERC simulation work, was used to perform the assessment. Estimated H 2 storage potential varied widely for each formation type. The Broom Creek saline formation was estimated to have a storage potential of approximately 1.7–90.5 million tonnes (MMt). The DLM oil reservoirs were estimated to have 0.07–0.19 MMt of capacity. Notably, each of these estimates relies on significant assumptions regarding reservoir thickness, porosity, permeability, and CG needed for operation. Much research is needed to understand the true site-specific storage resource potential of each formation. Using the Dunham Salt Interval for cavern development may result in as much as 4.79 MMt (up to 2.87 MMt working gas) of H 2 storage potential. An important note for consideration is that the values presented here need significantly more geological characterization and engineering assessments prior to gaining confidence in performance. This will be a focal point for future research and development needs. The basinwide evaluation also indicated that North Dakota has significant H 2 generation potential, with estimates up to a possible 13 MMt annually, suggesting a substantial opportunity for H 2 market development and thus the need for commercial-scale H 2 storage to facilitate growth and resilience. Key Recommendations 1. Conduct detailed site characterization (3D seismic, well logs, core sampling) to reduce geologic uncertainty. 2. Perform techno-economic analyses incorporating market, regulatory, and incentive frameworks. 3. Investigate long-term interactions among H 2 , CGs, well materials, and formations to assess risks. 4. Develop pilot- and field-scale demonstrations to validate models and establish best practices.

03 NATURAL GAS↗
DOE OSTI2024

Mathematical methods for optimal polynomial recovery of high-dimensional systems from noisy data

The goal of our Early Career Research Project (ECRP) is to establish a modern mathematical foundation that will enable next-generation computational methods for polynomial approximation of high-dimensional systems, having a certain set of constraints, from a limited amount of noisy data. Such a foundation is critical to realizing the future potential of the DOE user facilities, and will ultimately empower scientists to address a fundamental question, namely, “how many realizations of a nonlinear manifold are required to recover the entire high-dimensional solution map, with optimal approximation guarantees and minimal computational cost?” The central theme of this effort aims to conquer this challenge by pioneering the development of extraordinarily innovative theoretical analysis and transformational non-intrusive computational methodologies. Such approaches will enable the reconstruction of the entire high-dimensional solution map, with accuracy comparable to the best approximation, while utilizing an optimal number of samples. During this reporting period we have made significant progress on four thrusts.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Dual-loop Solvent-based CCS for Net Negative CO 2 Emissions with Lower Cost

This final technical report details the successful design, construction, and operational validation of an innovative dual-loop CO 2 capture technology designed to achieve deep decarbonization (>99%) from Natural Gas Combined Cycle (NGCC) power plants that results in the electricity with carbon intensity of approximate 42 kg CO 2 -eq/MWh, less than the electricity produced by solar PV. The integrated process couples a primary aqueous solvent (in this project, a water lean solvent – WLS) absorption loop for bulk CO 2 removal with a secondary potassium hydroxide (KOH) polishing loop featuring electrochemical regeneration. This architecture leverages the higher exergy efficiency of the primary loop while utilizing the fastest kinetic of the secondary loop to capture dilute residual CO 2 , achieving an overall capture rate of 99.9% and co-producing pure hydrogen after moisture being condensed and dehydrated. Technical feasibility was established through a comprehensive 2,000-hour experimental campaign on a bench-scale fully-integrated unit (using 4” absorber and 4” stripper) with the feeding flue gas flowrate in the range of 8-20 cfm, confirming the attainment of Technology Readiness Level (TRL) 4. The project executed extensive parametric testing followed by 1,000 hours of continuous steady-state testing, demonstrating exceptional process stability with the electrochemical regenerator exhibiting less than a 10% reduction in electrical conductivity over the duration of the campaign. Operational characterization gathering on the bench unit revealed distinct energy profiles for the hybrid system: the primary loop required approximately 280 kJ mol -1 for bulk removal, while the polishing loop required approximately 1,600 kJ mol -1 specifically when reducing dilute CO 2 concentrations from ~740 ppm down to <50 ppm. (Please note those energy values/numbers can only be viewed as relative relationship and should not be extrapolated as absolute values required for CO 2 capture). Furthermore, dynamic testing validated the system’s flexibility for utility applications, demonstrating a rapid process response time of <30 minutes to changes in flue gas flowrate. Emission monitoring confirmed that the dual-loop architecture effectively mitigates solvent losses, utilizing a water wash to remove entrained aerosols to <1 ppm. The Techno-Economic Analysis (TEA) indicates a cost of capture of $\$$59.3/tonne and a Levelized Cost of Electricity (LCOE) of 71.7 $\$$/MWh at the overall capture efficiency of 99.8% of total carbon in the flue gas stream, with sensitivity analysis identifying an economic optimum when the primary loop captures 97% of the total CO 2 . A Life Cycle Assessment (LCA) confirms the technology’s potential for net-negative emissions, determining a Global Warming Potential (GWP) of 52 kg CO 2 -eq/MWh—significantly lower than the baseline—which further decreases to 42 kg CO 2 -eq/MWh when crediting the displacement of conventional hydrogen production.

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