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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Geochemical evolution in Cacapon member: Fluid-rock interaction experiments and model insights for Appalachian Basin geothermal development

Here, this study combines recirculated flow-through experimental results conducted for 17 days at 90C and 200 PSI with reactive transport modeling to estimate fluid-rock interactions occurring in a sandy mudstone using an interbedded sandstone-shale sample from the Cacapon Member of the upper Tuscarora Sandstone/lower Rose Hill Formation for the purpose of geothermal exploration. Results suggest that the fluid and rock are likely to be in or near partial-equilibrium after approximately one year. In addition, after >400 h of continuous injection at 0.05 mL/min (5*10 −8 m 3 /min) the reactive front is restricted to the first ∼13% of the 4 cm*1.6 cm experimental rock length, whereas after >9100 h (∼1 year), the reactive front extends to 30% total length. The rate of changes in dissolution or precipitation are however, very minimal, with all major rock-forming minerals having rates <10 −11 mol/L porous media/s. Reservoir rock in the presence of dilute brine as may be the case during operation of an enhanced geothermal system would experience little alteration during the shut-in phase, and possibly up to one year. These results have utility in geothermal exploration for reservoirs at similar temperatures as well as general fluid-sandy mudstone rock interaction geochemistry.

Appalachian Basin↗
DOE OSTI2025

Selective electrified polyethylene upcycling by pore-modulated pyrolysis

Plastic waste is a increasing problem, accumulating in landfills and the environment. Pyrolysis is a promising and industrially relevant approach for transforming plastic waste into value-added chemicals. However, the selectivity and yield of traditional plastic pyrolysis are poor, with products featuring broad molar mass distributions. Here we report a highly selective, energy-efficient and catalyst-free pyrolysis method that can upcycle plastic into value-added chemicals via pore-modulated pyrolysis. Using a Joule-heated carbon column, we demonstrate the pivotal role of the reactor’s graded porous structure in decreasing the polydispersity of the reaction intermediates, enabling high product selectivity and yield. The decreasing pore size of the reactor modulates the mass transport in an apparent gating effect—preventing high-molar-mass species from exiting the reactor before sufficient pyrolysis has occurred. Using polyethylene as a model reactant, we demonstrate a high yield of 65.9 ± 5.2% and up to 80.8% selectivity toward value-added aviation fuel precursor (C8–C18 hydrocarbons) without the use of any catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Recent Advances and Future Perspectives of Low-Concentration CO 2 Enrichment and Emerging Applications

Low-concentration carbon dioxide (LCCO 2 ) streams, ranging from ambient air to industrial flue gas, represent a significant yet underutilized carbon resource. This review examines recent advances in technologies for enriching LCCO 2 and enabling its integration into a wide range of applications. It covers emerging materials and processes for CO 2 capture, including immobilized amines, metal oxides, polymers, porous carbons, and zeolites, with a focus on performance metrics, regeneration strategies, and process intensification. Beyond capture, the review explores the direct utilization of LCCO 2 through reactive capture pathways enabled by novel catalysts and processes, as well as nonreactive applications, such as greenhouse cultivation, enhanced weathering, and sustainable agriculture. Additionally, this review highlights the role of LCCO 2 in enhancing critical metal recovery. Finally, the review outlines crucial future research directions necessary to fully realize LCCO 2 enrichment’s potential within circular carbon economies and critical material supply chains, paving the way toward a more energy-innovative and resource-resilient industrial sector. The findings are significant for researchers in academia, industry, and government, as well as the public interested in extending the value of LCCO 2 .

atmospheric chemistry↗
DOE OSTI2025

Process Optimization and Modeling for Minerals Sustainability (PrOMMiS) v1.0.0

The U.S. Department of Energy's ("DOE") Process Optimization and Modeling for Minerals Sustainability project ("PrOMMiS Project") was initiated in 2023 to transform the national Critical Minerals and Rare Earth Elements (CM & REE) landscape, thereby supporting DOE's three enduring strategic objectives: security, economic competitiveness, and environmental responsibility. To address this initiative, the PrOMMiS Project will develop, demonstrate, and deploy an open-source, advanced system modeling, optimization, and analysis application ("PrOMMiS Software Application") that will support industry decision-makers by accelerating the scale-up of novel CM & REE technologies by de-risking the development and deployment of commercial scale processes and maximizing learning throughout the development cycle.

Beattie, KeithS [Lawrence Berkeley National Labora↗
DOE OSTI2025

Novel Design and Fabrication of a High Frequency Transient Heat Flux Sensor for Use in an RDE

Rotating detonation engine (RDE) combustion systems have been a topic of interest in the pressure gain combustion community for their benefits over traditional gas turbine engine combustors. However, cooling requirements for these engines are significantly higher and less predictable than non-detonating engines. To understand the high-speed heat transfer dynamics inside an RDE, a novel, high-frequency heat flux gage is presented. This study aims to design a robust, single-sided sensor that can withstand the high temperature and harsh environment of an RDE for extended durations. Sensor bench testing is performed using a hot plate as a heat source, and the sensor response is compared to a finite-element analysis (FEA) model. The sensor response is then tested inside a water-cooled RDE and the wall heat flux is compared to calorimetry data.

rotating detonation engines↗
DOE OSTI2025

Novel Design and Fabrication of a High Frequency Transient Heat Flux Sensor for Use in an RDE

Rotating detonation engine (RDE) combustion systems have been a topic of interest in the pressure gain combustion community for their benefits over traditional gas turbine engine combustors. However, cooling requirements for these engines are significantly higher and less predictable than non-detonating engines. To understand the high-speed heat transfer dynamics inside an RDE, a novel, high-frequency heat flux gage is presented. This study aims to design a robust, single-sided sensor that can withstand the high temperature and harsh environment of an RDE for extended durations. Sensor bench testing is performed using a hot plate as a heat source, and the sensor response is compared to a finite-element analysis (FEA) model. The sensor response is then tested inside a water-cooled RDE and the wall heat flux is compared to calorimetry data.

rotating detonation engines↗
DOE OSTI2025

Design of Experiments for Dynamic Test Runs in Solvent-Based CO 2 Capture Pilot Plants

Test runs in the pilot plants consume significant resources, and therefore, the learning from test runs should be maximized. Test runs conducted in the pilot plants are often steady state. It takes several hours for reaching steady-state in the pilot plants, and thus, the duration of the test runs needs to be long even for collecting few steady-state data points. On the other hand, a large number of measurements can be collected through dynamic test runs in a short span of time. This paper presents a systematic design of dynamic experiments (DoDEs) for identifiability of model parameters, which is achieved by persistently exciting the inputs signals. A pseudorandom binary sequence (PRBS) is designed as the input signal for DoDE due to its efficiency in obtaining sufficient spectral content. However, due to the long sequence size of the PRBS signal, a Schroeder-phase input signal, which is a multisine signal, is also designed. Tests for both types of signals are run in the Pilot Solvent Test Unit (PSTU) at the National Carbon Capture Center in Wilsonville, Alabama. The transient data are used to solve dynamic data reconciliation and parameter estimation problem. The estimated parameters are found to be not only superior to those estimated from using data collected from hundreds of steady-state test runs in a nonreactive (air–water) system, but the parameters could be estimated by using the dynamic data collected for about 24 h from the pilot plant for the MEA-H 2 O–CO 2 system.

CO2 capture↗
DOE OSTI2025

Modeling and Optimization of a Rotating Packed Bed Contactor with a Tetraamine-Appended Metal−Organic Framework for CO 2 Capture

A potential contactor technology for sorbent-based CO 2 capture is the rotating packed bed that contains separate sections for continuous adsorption and desorption. A heat exchanger can be embedded to remove heat in the adsorption section and add heat in the desorption section. In this work, we develop a two-dimensional (2D) model of a rotating packed bed for use in CO 2 capture applications. Mass and energy balances for the model are developed based on a Ljungström-type air preheater, which accounts for the counter-current axial flow of gas phases in separate sections of the bed and the rotation of a solid sorbent, which cycles between adsorption and desorption sections. The sorbent used for this analysis is the tetraamine-appended metal−organic framework Mg 2 (dobpdc)(3−4− 3), chosen for its stability and affinity for CO 2 at low partial pressures, such as those from a natural gas power plant source. An optimization problem is solved that considers the trade-off between maximizing the productivity of the bed and minimizing energy consumption. Maximum productivity and minimum energy are found to be 8.53 kg/h/m 3 and 3.84 MJ/kg, respectively, when these objectives are optimized independently. It is observed that the flue gas pressure and bed rotational speed are the desired operating variables to vary for model-based design of experiments to reduce uncertainty in parameter estimation, as these two variables yielded the most information content based on the Fisher information matrix.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2025

Multi-scale dynamic modeling and validation of radial flow fixed bed contactors for post-combustion CO 2 capture using bench scale and pilot plant data

Here, in this work, a multi-scale model of a radial flow fixed bed contactor packed with a carbon sorbent is developed and validated with laboratory-scale and pilot plant scale dynamic data. For the lab scale system, the model results were compared with low, medium and high gas and sweep flowrates, yielding root mean square error (RMSE) of 0.80, 0.63, 0.96 CO 2 mol%, respectively, for the outlet CO 2 concentration profile considering the entire A-D cycle. For the bed outer temperature profile, maximum RMSE was found to be 5.5 °C considering all flowrates and entire A-D cycles. An experimental campaign was developed and applied to a pilot plant at Technology Center Mongstad (TCM), Norway. Approaches were developed for pre-processing of data including consideration of the effect of gas mixing, measurement delay, and determination of cyclic steady-state conditions. Considering profiles during A-D cycles for all test runs, it was found that the maximum RMSE for pressure drop, temperature for the outer section of the bed, temperature for the middle section of the bed, and outlet CO 2 concentration profile remained less than 1.5 mbar, 3.5 °C, 2.8 °C, and 1.3 CO 2 mol%, respectively. The validated model was used to perform sensitivity studies on several key design operating variables for the adsorption-desorption cycle. It was found that the flow rate and concentration of flue gas have dominant nonlinear effects on the breakthrough time while the desorption time was strongly affected by the sweep gas flowrate for the specific sorbent being evaluated in this study.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2026

Optimal Design and Techno-Economic Analysis of 3D-Printed, Intensified Packings for Absorbers and Strippers in Solvent-Based CO 2 Capture

A potential technology for the CO 2 absorption process is utilizing intensified structured packing with embedded cooling/heating channels for continuous heat exchange, which can overcome limitations of discrete methods, such as discrete intercooling and centralized reboilers, to aid in reducing energy consumption and decreasing costs. This work investigates the modeling of intensified packing (IP) for the stripper tower, extending on previous work for the absorber, which distributes heat internally within the column, improving the thermodynamics for the solvent regeneration process. The model includes submodels for steam turbine extraction to produce steam at various qualities as well as a surrogate model for calculating steam enthalpy. A cost model for a plant-scale absorption capture process was developed, allowing for the design of the plant to be optimized, subject to minimizing capture cost using two different power plant flue gas sources. In this optimization, the placement of IP in both towers is optimized to balance the trade-off between enhanced heat transfer and reduced mass transfer volume. For natural gas combined cycle flue gas, the standard process configuration had a minimum cost of $\$$65.40/tonne CO 2 , and considering IP, the minimum capture cost is reduced to $\$$62.73/tonne, with utilization in the stripper column, which reduces yearly costs by up to $\$$2.67 MM/yr. Cooling the absorber through IP, or intercoolers, was only found to be beneficial at higher capture rates, with IP in both towers having a cost of capture of $\$$68.08/tonne at 99.9% capture, a reduction of $\$$12.64/tonne when using only intercoolers at the same capture rate. When capturing from pulverized-coal power plants, the minimum cost of capture when using IP in both towers is $\$$44.18/tonne (at 97% capture), while the standard configuration with and without intercoolers was $\$$45.69 and $\$$47.22 per tonne, respectively. This results in a reduction in yearly costs of $\$$16.98 MM/yr from the base-case configuration. At this higher CO 2 concentration, cooling in the absorber from the IP becomes extremely beneficial, reducing energy consumption by up to 6%.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2025

Optimal Design and Operation of Intensified Absorbers with 3D-Printed Packing for Solvent-Based CO 2 Capture

Many potential solvent-based carbon capture processes suffer from a high heat of absorption of CO 2 that adversely affects the thermodynamic driving force. While interstage coolers are often used for removing a portion of the generated heat by removing the solvent or a portion of the solvent from a stage and cooling and returning it back to the absorber, they can be placed only at discrete locations in the tower. This work investigates intensified absorbers with 3D-printed packing that includes an internal cooler and therefore can be potentially used for maximizing the operational efficiency of the absorbers for CO 2 capture. The intensified absorber is modeled by using a generic, first-principles, equation-oriented absorber column model. Since the placement of these intensified packings would cause a loss of area/volume used for mass transfer, optimization of the proposed intensified absorber is performed by optimally selecting the locations at which to place these devices and designing them such that the trade-off due to the addition of the heat removal area and the resulting loss in the mass transfer area is accounted for. Results show that optimally placed and designed intensified packings can lead to a significant increase in the capture efficiency of the process in comparison to a similar column with no internal cooling. It is also observed that by optimally placing and designing intensified packings, the lean solvent flow rate to the absorber can be decreased, and the CO 2 lean loading can be increased while still maintaining the same capture efficiency. These process changes can lead to a substantial reduction in the cost of capture.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

CALPHAD-based Bayesian optimization to accelerate alloy discovery for high-temperature applications

Two crucial properties influencing the performance of high-temperature alloys are coefficient of thermal expansion (CTE) and phase constitution. It is desirable to have alloys with low CTE, which reduces CTE mismatch with the surface oxide and the likelihood of oxide spallation. Reducing the amount of brittle intermetallic phases such as Sigma (σ) enhances alloy ductility and processability. Here, we propose a multi-objective Bayesian Optimization (BO) model to simultaneously minimize CTE (at an operational temperature of 1150 °C) and T σ (temperature when the Sigma phase completely dissolves in the metal matrix), properties which are obtained from high-throughput CALculation of PHAse Diagrams (CALPHAD). The model successfully identifies several alloys with CTE ≤ 2 × 10 –5 /K and T σ ≤ 500 °C by exploring just 7% of the nickel–chromium–cobalt–aluminum–iron (Ni–Cr–Co–Al–Fe) composition space. Such multi-objective alloy design frameworks can be used to inform additive manufacturing experiments and accelerate alloy discovery for high-temperature energy applications.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Economic Analysis of Condition-Monitoring-Based Predictive Maintenance in Power Plants under Market Elasticity

Condition-monitoring-based predictive maintenance can increase the power plant availability by preventing forced outages. However, the actual on-stream time depends on market elasticity and dynamics, which are affected by cost and penetration of other power generation technologies. This paper develops a systematic approach for the economic analysis of investment in condition monitoring technologies with due consideration of market elasticity. Focus is on corrosion monitoring in coal-fired power plants (CFFPs) since corrosion in high-temperature coal-fired boilers is a leading cause of equipment failure. Investment in sensor networks for measuring corrosion and operating conditions like metal temperature and concentrations of O 2 and SO 2 is investigated. The unscented Kalman filter is used to estimate corrosion in the waterwall section of the boiler under multiple sensor networks. Electricity produced by CFPPs in the future in the U.S. due to changes in availability under market elasticity is studied. Sensitivity of the incremental net present value to factors like the number, type, and cost of sensors is analyzed.

Electrochemistry↗
DOE OSTI2026

Additively Manufactured Graded Composite Transition Joints for Dissimilar Metal Weldments in Advanced Ultra-Supercritical Power Plant (Final Technical Report)

In this project, we successfully achieved all the goals we proposed: ① Code Development; ② Transition Joint Design; ③ Lab-scale GCTJ Testing Piece Development; ④ Heat Treatment; ⑤ Welding of DMW; ⑥ Mechanical Characterization; ⑦ Corrosion; ⑧ Fabrication of Prototype GCTJ; ⑨In-field Test in SWRI and ⑩Tech-economic Analysis.

36 MATERIALS SCIENCE↗
DOE OSTI2024

The kinetic analog of the pressure–strain interaction

Energy transport in weakly collisional plasma systems is often studied with fluid models and diagnostics. However, the applicability of fluid models is limited when collisions are weak or absent, and using a fluid approach can obscure kinetic processes that provide key insights into the physics of energy transport. Kinetic diagnostics retain all of the information in 3D-3V phase space and thereby reach beyond the insights of fluid models to elucidate the mechanisms responsible for collisionless energy transport. In this work, we derive the Kinetic Pressure–Strain (KPS): a kinetic analog of the pressure–strain interaction, which is the channel between flow energy density and internal energy density in fluid models. Through two case studies of electron Landau damping, we demonstrate that the KPS diagnostic can elucidate kinetic mechanisms that are responsible for energy transport in this channel, just as the related field–particle correlation is known to identify kinetic mechanisms of transport between electromagnetic field energy density and kinetic energy density in particle flows. In addition, we show that resonant electrons play a major role in transferring energy between fluid flows and internal energy during the process of Landau damping.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Instantaneous difference frequency locking observed during toroidicity-induced Alfvén eigenmode coupling in the DIII-D tokamak

In magnetic confinement fusion, toroidicity-induced Alfvén eigenmodes (TAEs) are well-studied, weakly stable solutions of the linearized ideal magnetohydrodynamic equations. Driven unstable by suprathermal populations of energetic particles, TAE pose a key vulnerability to the confinement of high-energy alpha particles generated by fusion reactions. Hence, it is paramount to understand TAE dynamics if a working reactor is to be realized. In this work, we detect and characterize signatures of nonstationary nonlinear coupling between TAE using a novel, time-resolved bispectral analysis; results are supported by analytic signal of band-passed data. Crucially, a stationary phase relationship between two TAE and a nascent low frequency fluctuation is observed precisely when the triple product of magnetic fluctuation amplitudes is enhanced. Local mode number and frequency spectrum, gleaned from beam-emission spectroscopy, corroborates simultaneous satisfaction of nonlinear matching conditions, and provides a tool to identify theorized pathways of energy transfer, e.g. TAE parametric instability.

bispectral analysis↗
DOE OSTI2025

Applications of Nickelate perovskites for neuromorphic computing from electronic structure and Machine Learning

While the limit of Moore's law is presently being reached with current microelectronic technologies, we need to develop new paradigms that overcome this limitation. In that respect, neuromorphic computing is a concept that emulates the neural behavior and response of the human brain, and it has been recognized as a promising alternative approach. In this research project, we will perform multi-fidelity scale bridging to explore the potential use of materials with metal to insulator transition for neuromorphic applications. In particular, rare earth nickelates are promising for such purposes, as the transition in these materials is quite sensitive to a broad set of different external stimuli. Our multi-fidelity approach will bridge the high-fidelity electronic structure calculations with classical potentials. We will bridge dynamical mean field theory with a classical atomistic representation via a deep learning force field. The neural network is trained with energies, charges, and forces obtained by accurate electronic structure theories based on Dynamical Mean Field Theory. The configurational space is generated from known crystal phases, ab initio molecular dynamics with exchange-correlation functionals corrected with the Hubbard model, disordered phases with different concentrations of oxygen vacancies, and nonsymmetrical positions and induced strain by grain interfaces or contact with a substrate. Strategies to train the model with a reduced number of training examples are obtained from active learning methods, and new structures for improving the learning process are generated by using machine learning autoencoders. This classical potential will be validated through a diversity of electronic structure methods and represents an important step to combine the flexibility and accuracy of first-principles with the speed of classical potentials. The generated multi-fidelity surrogate model will be used to understand the role of strain, oxygen vacancies, proton doping, the variation of the crystal phase, substrate effects, vibrational effects as the octahedral rotation, grain boundaries and defect effects on the response of a Metal to Insulator Transition (MIT) in correlated materials. Long time and large-scale simulations will help understand the role of different stimuli to control the hysteresis of the MIT, as it has been experimentally suggested. Selected configurations will be analyzed with higher-level theories to provide an accurate electronic description and to study how the orbitals and charges are rearranged under different conditions.

36 MATERIALS SCIENCE↗