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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 667 records · Page 37
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Adaptive Protection and Validated Models to Enable Deployment of High Penetrations of Solar PV (PV-MOD)

The availability and validation of various PV models in commercial tools differ, with some models not yet thoroughly validated for advanced inverter functionalities and reliable performance under weak system conditions. Many existing models do not fully incorporate new inverter control functions, which can affect system stability. The increasing deployment of solar PV and other inverter-based resources (IBRs), including distributed energy resources (DERs), is influencing the reliable operation of protection schemes in distribution systems and microgrids. Emerging adaptive protection schemes (APS) offer new opportunities for protecting these systems during varying configurations and DER operating conditions, though their demonstration and validation remain limited. Adaptive protection schemes face similar challenges, as they are typically designed for specific configurations. There is a growing need for tools and methodologies to streamline the deployment of adaptive protection for safe and reliable DER integration. The project main objective was to develop and validate high-fidelity generic models of solar PV facilities for stability, protection, EMT, and QSTS analyses. This objective was achieved, and these models can now be integrated into commercial software tools, enabling utilities, vendors, and developers to study high-penetration PV systems more confidently. The project also demonstrated advanced applications of these models, including the design and deployment of adaptive protection schemes in high-penetration field applications and microgrids, supporting grid safety and reliability. Several milestones were reached by the end of the project. A sophisticated inverter test plan was developed, and inverters representative of the North American marketplace were selected. EPRI and NREL tested various inverters, conforming to IEEE standards. Improvements were made to existing generic models of IBR units, IBR plants, and aggregated feeders for various analyses. The first generic electromagnetic transient (EMT) model for a solar PV plant was developed, conforming to IEEE Std 2800™-2022 and validated against laboratory measurements of a 2.2 MVA large-scale battery energy storage system (BESS) inverter. That model was then used to produce reference responses illustrating examples of validated and verified IBR plant models that pass or fail tests for technical minimum capability and performance as specified in the IEEE standard. The developed, tested, and validated generic models can be used for transmission planning, stability assessments, expansion planning, and evaluating potential future IBR interconnection requirements. They can also support interconnection screens and conformity assessments of IBR plants, including solar PV. The project significantly contributed to the ongoing standardization and model-based representation and verification of IBR responses. The project further addressed challenges of common distribution protection schemes with increasing deployment of DER by developing, validating, and demonstrating adaptive protection schemes (APS) that can improve the reliable and safe integration of DER into distribution systems. New APS were designed using improved DER models for three common distribution systems: a radial feeder, a meshed network, and a microgrid. Modeling and hardware-in-the-loop (HIL) testing of the APS were conducted, successfully showing their effectiveness and selectivity. Proof-of-concept field demonstration was achieved for two APS, i.e., one on a radial feeder and another one in a microgrid. Field demonstration could not be achieved for the APS on a meshed network, primarily due apprehension of one utility partner and also due to limited access to the protective algorithms in the network protectors. Guidelines developed from the lessons learned in the project lay out the general process followed in the design, installation, and commissioning of APS for various distribution systems. Distribution utility partners’ apprehension about field demonstration of the new APS were addressed—with varying success—by taking a stepped risk-management approach of modeling of a wide range of sensitivities first, performing in-depth proof-of-concept testing in the laboratory including HIL next, and finally deliberately implementing and commissioning the actual protection equipment and algorithms into parts of—or in parallel operation to—the three real distribution systems. Future work should include pilot projects that further show the acceptable performance of the developed APS before these schemes be rolled out more widely. Inclusion of both utility and original equipment manufacturers (OEMs) in future projects could increase chances of successful field demonstration. Despite challenges in achieving the field demonstration goal of the project for all three APS, the research significantly contributed to the innovation of adaptive protection solutions for scalable and reliable DER integration into distribution systems. This project significantly enhances the understanding of the impact of using appropriate inverter models on distribution and transmission (T&D) systems. By addressing the limitations of existing generic models, the project introduces high-fidelity models for stability, protection, electromagnetic transient (EMT), and quasi-static time series (QSTS) analyses. These models, integrated into commercial software tools, enable utilities, vendors, and developers to confidently study high-penetration PV systems. The project also demonstrates advanced applications, including adaptive protection schemes (APS) for distribution systems and microgrids, ensuring grid safety and reliability. The technical effectiveness and economic feasibility of the methods are evident through the development and validation of sophisticated inverter test plans and the selection of representative inverters. Testing by EPRI and NREL on retail, commercial, and utility-scale inverters, conforming to IEEE standards, underscores the robustness of the models. Improvements to existing generic models for various analyses further enhance their validity and applicability. The project also identifies gaps in common distribution protection schemes and designed new APS using improved DER models, demonstrating their effectiveness through modeling and hardware-in-the-loop (HIL) testing. The project’s benefits to the public are manifold. By advancing the standardization and model-based representation of IBR response, it supports transmission planning, stability assessments, and future IBR interconnection requirements. The generic models can facilitate better communication between transmission planners and developers, supporting expected IBR plant capability and performance. Additionally, the development of APS for radial feeders, meshed networks, and microgrids supports the integration of distributed energy resources (DERs) into distribution systems, enhancing grid reliability and safety. The project’s emphasis on thorough testing and simplicity in design ensures practical and scalable solutions for DER integration.

14 SOLAR ENERGY↗
DOE OSTI2026

Feedback, physics, and forecasts: The emerging paradigm of machine learning-driven battery research

Machine learning (ML) is reshaping how we understand, predict, and optimize electrochemical systems. In batteries, ML accelerates discovery across chemistry, design, and operation by transforming massive experimental and simulated datasets into predictive, interpretable models. This review consolidates a decade of progress in ML-driven battery innovation, from early-cycle feature extraction to operando image analysis and physics-informed modeling. We categorize approaches by data domain and physical fidelity, emphasizing interpretable ML for diagnostics, reinforcement learning for control, and multi-objective optimization for lifetime extension strategies. Additionally, we demonstrate how integrated models accelerate discovery, reduce testing time, and guide sustainable design. Economic analyses furthermore illustrate how these advances can lower cost per cycle and improve circularity. Together, these developments chart a path toward self-optimizing, sustainable battery technologies.

artificial intelligence↗
DOE OSTI2022

Mechanical, Microstructural, and Electrochemical Characterization of NaSICON Sodium Ion Conductors [Poster]

The DOE Office of Electricity views sodium batteries as a priority in pursuing a safe, resilient, and reliable grid. Improvements in solid-state electrolytes are key to realizing the potential of these large-scale batteries. NaSICON structure consists of SiO 4 or PO 4 tetrahedra sharing common corners with ZrO 6 octahedra. Structure forms “tunnels” in three dimensions that can transport interstitial sodium ion. 3D structure provides higher ionic conductivity than other conductors (β’’-alumina), particularly at low temperature. Lower temperature (cheaper) processing compared to β’’-alumina. Our objective was to identify fundamental structure-processing-property relationships in NaSICON solid electrolytes to inform design for use in sodium batteries. In this work, the mechanical properties of NaSICON sodium ion conductors are affected by sodium conduction. Electrochemical cycling can alter modulus and hardness in NaSICON. Excessive cycling can lead to secondary phases and/or dendrite formation that change mechanical properties in NaSICON. Mechanical and electrochemical properties can be correlated with topographical features to further inform design decisions

25 ENERGY STORAGE↗
DOE OSTI2026

Monolithic Mesoporous Metamaterials for R-10 to R-15 Glazing (Final Scientific Technical Report)

The objective of the project was to develop and validate monolithic mesoporous metamaterials (MMMs), to which we also refer as Mesoporous Optically Clear Heat Insulators (MOCHIs) capable of serving as High-thermal-barrier Glazing (including Windows, Skylights, and Daylighting) with Transparency ≥99%, Color Rendering Index ≥99%, Haze ≤1%, Thermal Insulation per inch ≥R-15, Manufacturing Cost per Square Foot ≤$0.3; In addition, MMM-Based Frame Insulation and Glazing Products with Thermal Insulation per inch R-10 to R-15. All objectives of the project were successfully accomplished.

14 SOLAR ENERGY↗
DOE OSTI2025

Emergent Dimer-Model Topological Order and Quasiparticle Excitations in Liquid Crystals: Combinatorial Vortex Lattices

Liquid crystals have proven to provide a versatile experimental and theoretical platform for studying topological objects such as vortices, skyrmions, and hopfions. In parallel, in hard condensed matter physics, the concept of topological phases and topological order has been introduced in the context of spin liquids to investigate emergent phenomena like quantum Hall effects and high-temperature superconductivity. Here, we bridge these two seemingly disparate perspectives on topology in physics. Combining experiments and simulations, we show how topological defects in liquid crystals can be used as versatile building blocks to create complex, highly degenerate topological phases, which we refer to as “combinatorial vortex lattices” (CVLs). CVLs exhibit extensive residual entropy and support locally stable quasiparticle excitations in the form of charge-conserving topological monopoles, which can act as mobile information carriers and be linked via Dirac strings. CVLs can be rewritten and reconfigured on demand, endowed with various symmetries, and modified through laser-induced topological surgery—an essential capability for information storage and retrieval. We demonstrate experimentally the realization, stability, and precise optical manipulation of CVLs, thus opening new avenues for understanding and technologically exploiting higher-hierarchy topology in liquid crystals and other ordered media.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Front-End Engineering Design Study for Retrofit Post-Combustion Carbon Capture on a Natural Gas Combined Cycle Power Plant

The objective of the project is to conduct a Front-End Engineering Design (FEED) study to determine the technical and economic feasibility of installing a retrofit, post-combustion, carbon capture facility on a commercially operating, natural gas-fired, combined cycle (NGCC) power plant. The Electric Power Research Institute (EPRI), California Resources Corporation (CRC), and Fluor Corporation used Fluor's Econamine FG Plus SM (EFG+) conducted the FEED study for capturing CO 2 produced by CRC's 550 MWe Elk Hills Power Plant (EHPP), located in the Elk Hills Oil Field near Tupman, Kern County, California. The EHPP was commissioned in 2003 and is powered by two General Electric 7FA gas turbines, with two heat recovery steam generators (HRSGs) providing steam to a General Electric D11 steam turbine. The target capture amount is 4,000 tonnes CO 2 /day for use in either enhanced oil recovery or dedicated geological saline storage located on CRC property at or nearby EHPP. This CO 2 is captured from a combination of the CO 2 emitted from the flue gas from EHPP and the flue gas generated from a natural gas-fired auxiliary boiler that supplies steam to the EFG+ process.

03 NATURAL GAS↗
DOE OSTI2021

Redefining Resource Adequacy for Modern Power Systems: A Report of the Redefining Resource Adequacy Task Force

Today's rapidly increasing levels of wind, solar, storage, and load flexibility require the industry to rethink reliability planning and resource adequacy methods for modern power systems. Periods with a risk of shortfall often no longer coincide with peak demand - reliability risks are less about peak load and more about the daily setting of the sun, extended cloud cover, wind speeds, cold snaps, and heat waves. In addition, demand is increasingly flexible. Key resources are time-sensitive, as batteries need time to recharge and electricity customers can only be asked to provide demand response for just so long. And reliability failures are often correlated - with one another and with the weather. Two driving factors require the industry to reconsider its analytical approach for resource adequacy: (1) Chronological grid operations: The increasing importance of variable renewable resources (such as wind and solar) and of energy-limited resources (storage and demand response) make it essential to understand the full year of chronological operation of the grid. Specific attention must be paid to hourly, seasonal, and inter-annual resource variability. The sequence of the variability is key, as energy-limited resources such as batteries or demand response require either a preceding period or subsequent period of high production to be useful for grid reliability. (2) Correlated events: Historically, resource adequacy analysis focused on shortfalls caused by random, discrete mechanical failures of large generating units. In contrast, shortfalls today are often caused by multiple, correlated events caused by common weather patterns. Resource adequacy analysis must increasingly shift its focus to these correlated events. The redesign of resource adequacy methods will benefit from a set of guiding principles to better allow for sharing of insights and best practices, interregional resource coordination, and a smoother regulatory process for resource procurement. The objective of this report is to move this redesign forward. It provides an overview of key drivers changing the way resource adequacy needs to be evaluated, identifies shortcomings of conventional approaches, and outlines first principles for practitioners to consider as they adapt their approaches. The central message is: what got us here won't get us there.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Photometric redshifts probability density estimation from recurrent neural networks in the DECam local volume exploration survey data release 2

Photometric wide-field surveys are imaging the sky in unprecedented detail. These surveys face a significant challenge in efficiently estimating galactic photometric redshifts while accurately quantifying associated uncertainties. In this work, we address this challenge by exploring the estimation of Probability Density Functions (PDFs) for the photometric redshifts of galaxies across a vast area of 17,000 square degrees, encompassing objects with a median 5 σ point-source depth of g = 24.3, r = 23 . 9 , i = 23.5, and z = 22.8 mag. Our approach uses deep learning, specifically integrating a Recurrent Neural Network architecture with a Mixture Density Network, to leverage magnitudes and colors as input features for constructing photometric redshift PDFs across the whole DECam Local Volume Exploration (DELVE) survey sky footprint. Subsequently, we rigorously evaluate the reliability and robustness of our estimation methodology, gauging its performance against other well-established machine learning methods to ensure the quality of our redshift estimations. Our best results constrain photometric redshifts with the bias of − 0 . 0013 , a scatter of 0.0293, and an outlier fraction of 5.1%. These point estimates are accompanied by well-calibrated PDFs evaluated using diagnostic tools such as Probability Integral Transform and Odds distribution. We also address the problem of the accessibility of PDFs in terms of disk space storage and the time demand required to generate their corresponding parameters.We present a novel Autoencoder model that reduces the size of PDF parameter arrays to one-sixth of their original length, significantly decreasing the time required for PDF generation to one-eighth of the time needed when generating PDFs directly from the magnitudes.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Plan for a Data Base Approach to Evaluating LWR Plant Integration with Hydrogen and Industrial Facilities

The purpose of this report is to provide an outline and scope of a database tool that could be used to identify the most beneficial locations to site a hydrogen, chemical facility or other industrial facility that would be powered by nuclear energy. This energy may be in the form of electricity produced by the plant, heat in the form of steam or both. In addition, this siting tool should consider factors such as economics, geography, industries, residences, geological hydrogen storage, and key infrastructure. The infrastructure to be considered could include pipelines or other storage and transportation facilities to carry the created products from the production facility to the end user. Also considered should be infrastructure that could deliver needed chemicals or gasses to allow the production of desired products such as ammonia or biofuels. This data base tool should allow a screening study of all U.S. nuclear plants to identify opportunities and barriers to creating hydrogen hubs around nuclear power plants. For this effort, it has been decided that the Siting Tool for Advanced Nuclear Development (STAND) would be used to conduct this screening study which is a follow-on research project to this present effort. Currently, plans are being developed to modify the STAND tool to provide the capability necessary to perform screening of each US commercial nuclear plant to identify the best locations to site hydrogen or chemical production facilities. Many features of the current STAND tool will be employed to meet this objective, but additional infrastructure data (such as the location of pipelines) may need to be added to allow these locations to be fully vetted. In addition, new analysis capabilities may need to be added so economic considerations can be understood

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Immersive Scientific Visualization of Molten-Salt Reactor Waste Characteristics Using Virtual Reality

Immersive visualization is changing how we explore, communicate, and understand complex scientific systems. In nuclear energy, an area in which data are often multidimensional, time-dependent, and difficult to interpret, virtual reality (VR) represents a powerful and intuitive informational medium. This work introduces a VR-based platform that visualizes the post-shutdown behavior and waste management lifecycle of molten-salt reactors (MSRs), a next-generation reactor type with unique operational and safety characteristics. The platform, built in Unity, is streamed on the Meta Quest 3 headset. It transforms high-fidelity simulation data into an interactive, immersive experience. Users can explore time-dependent reactor characteristics such as nuclide decay, which is a key factor for evaluating reactor waste strategies. The datasets were generated using the MOOSE (Multiphysics Object-Oriented Simulation Environment) framework and then processed through ParaView scripting for smooth integration into Unity. From a visualization standpoint, the platform emphasizes spatial storytelling, temporal exploration, and user-centered interaction. Users can navigate 3D reactor geometries, slice through volumetric data, and manipulate time to observe how physical phenomena evolve. Real-scale rendering and embodied interaction make the experience feel tangible. The interface is designed to be accessible, even to those without nuclear or simulation expertise. This lowers the barrier for stakeholders, policymakers, and the general public, while still supporting expert analysis and collaborative decision-making. This work shows how immersive visualization can function as both a scientific tool and a communication interface. By integrating simulation, processing, and visualization into a cohesive workflow, we offer a scalable framework for immersive scientific storytelling. The modular design supports future extensions to other reactor types and lifecycle stages, from shutdown to long-term storage, making the platform adaptable for both research and outreach.

99 - GENERAL AND MISCELLANEOUS↗
DOE OSTI2020

Coupled methane and NO x conversion on Pt + Pd/Al 2 O 3 monolith: Conversion enhancement through feed modulation and Mn 0.5 Fe 2.5 O 4 spinel addition

The performance of a dual-layer Pt-Pd/Al 2 O 3 washcoated monolith promoted by an Al 2 O 3 -supported Mn 0.5 Fe 2.5 O 4 spinel base layer was evaluated with the objective to develop a catalyst with a lower loading of Platinum group metal (PGM) for stoichiometric natural gas vehicle (NGV) emission control. Flow reactor results show that a combination of a lean/rich modulated feed and spinel addition gives enhanced methane and NO conversions compared to a steady-state feed having the same overall composition. Washcoated catalysts – PGM-only, spinel-only, PGM + spinel – were compared over a wide range of operating conditions. The results show a decrease in the methane conversion light-off temperature of up to 85 °C for an application-relevant feed (CH 4 + NO + H 2 + CO + O 2 + H 2 O + CO 2 ) while a moderate 40 °C decrease was observed for a simple feed (CH 4 + O 2 + H 2 O + CO 2 ). In the absence of spinel the modulation enhancement is negatively impacted at high methane conversion (> 80 %). The data show that the O 2 storage and release property of the spinel is needed to fully exploit the modulation enhancement. The mechanism responsible for the enhancement is linked to suppression of O 2 inhibition on the methane oxidation rate near the stoichiometric neutral point (λ = 1). Sufficiently fast cycling achieves a balance between a metallic and oxidic precious metal crystallites favorable for methane activation. The addition of spinel moves this balance closer to the λ = 1 feed, enabling a high oxidation efficiency with lower byproduct NH 3 selectivity. Enhancement in the NO conversion follows the methane conversion due to an easier NO reduction under the slightly rich of stoichiometric feed. Comparison of the PGM + spinel catalysts to PGM-only catalysts shows that the addition of spinel in combination with modulation can achieve the same activity with a lower PGM loading.

03 NATURAL GAS↗
DOE OSTI2024

SolarAPP+ Performance Review: Final Technical Report

The National Renewable Energy Laboratory (NREL) and its project partners have developed the novel Solar Automated Permit Processing plus (SolarAPP+) software platform that provides a flexible, web-based PV-permitting tool for residential systems that can be integrated with existing and complementary software platforms. The main objective of this research is to analyze the implementation of SolarAPP+. Analysis was conducted by identifying the benefits, tradeoffs, and overall performance of SolarAPP+, including achieving its goals of delivering automated, code compliant systems, influencing permitting cycle times, and improving application submittals and/or inspection performance. The NREL team published the results of this analysis in annual SolarAPP+ Performance Review technical reports.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

High Throughput Solvent-free Manufacturing of Battery Electrodes

The project goal is to develop and demonstrate an advanced solvent-free lithium-ion battery electrode process through proposed Advanced Dry Electrode Process (ADEP) equipment, which is expected to exhibit a better binder fibrillization and high throughput and suitable for high performance electrode manufacturing, and commonize the anode and cathode dry processing equipment, supply chain and operation for lithium-ion battery OEMs for replacing the solvent-based slurry casting. Our proposed approach will facilitate low-cost battery production by addressing the following gaps in present dry electrode processing: • Extend the dry electrode fabrication process to lithium-ion battery anode manufacturing • Increase the active material content for anodes and cathodes • Intensify the process through improved mixing, powder rheology and surface modifications • Enable processing of next-generation electrode materials that are not stable to solvent or ambient air exposure. The project objectives include the development of anode-compatible binder and binder fibrillization promoter for low irreversible capacity loss, low electrode binder content yet higher film mechanical strength, and the optimization of solvent-free anode and cathode process for low cost (>60% electrode cost reduction), high performance (10% increase in energy density without sacrificing cycle life) and high throughput to enable next generation lithium-ion battery electrode production. Solvent-free electrode manufacturing will also enable next-generation cell designs based on prelithiated anodes or solid-state electrolytes.

25 ENERGY STORAGE↗
DOE OSTI2021

Topical Report – Findings on Subtask 2.7 – Wet ESP and Aerosol Testing at Coal Creek Station

Growing concerns over the impact of CO 2 emissions from combustion sources on global climate change have prompted numerous research and development projects aimed at developing cost-effective technologies for CO 2 capture. One family of technologies being demonstrated at pilot and full scale globally is postcombustion carbon capture (PCCC) systems that employ amine-based solvents. The captured CO 2 can be compressed and permanently stored underground or used for enhanced oil recovery. The proximity of North Dakota’s lignite-fired fleet of power plants to potential CO 2 storage options creates a unique atmosphere for PCCC within the state. However, the unique components present in lignite flue gas present a challenge for large-scale PCCC at North Dakota power plants by contributing to aerosol formation. Aerosols can negatively impact the long-term performance of amine-based solvents for CO 2 capture. Amine-based solvents are volatile, and flue gas particulate provides nucleation sites where amine vapors can condense as aerosols. Because aerosols cannot be easily captured at the column outlet using conventional technologies, the amine-laden aerosols escape the system and lead to accelerated solvent losses. Moreover, particulate components can chemically react with amines to form degradation products that can permanently deactivate the amine, cause fouling, and lead to hazardous emissions. Many of the elements that have been shown to catalyze solvent degradation are present in lignite coals and can exacerbate solvent replacement economics. Understanding this issue is critical to the implementation of solvent-based CO 2 capture systems as applied to lignite-fired generation systems. The Energy & Environmental Research Center (EERC) designed and carried out this project to fully characterize aerosol behavior with various control technologies installed to better optimize aerosol mitigation technology for CO 2 capture. To meet the goal of this project, the following objectives were identified: Determine the effectiveness of a wet electrostatic precipitator (WESP) on mitigating formation of problematic aerosols at Great River Energy’s Coal Creek Station, upstream of the PCCC system. Determine the effectiveness of the Mitsubishi Heavy Industries (MHI) proprietary amine emission reduction unit (AERU) as a postcapture solvent recovery system for reducing aerosol emissions and extending solvent life downstream of the PCCC system. Determine the impact of aerosols on the efficiency and degradation products of both commercial and advanced solvents within the PCCC system. Work was conducted at Coal Creek Station Unit 1 using a slipstream of flue gas from the outlet of the plant’s flue gas desulfurization (FGD) unit. Flue gas was routed through a pilot-scale FGD unit to remove SO 2 to very low levels (~1 ppm) and then through a direct contact cooler (DCC) to further cool the gas and to remove moisture. The gas exiting the DCC was then optionally routed through a WESP before passing to the CO 2 absorber columns. The MHI solvent was used to scrub CO 2 from the slipstream through a set of two absorber columns. The rich solvent was regenerated in a stripper column by heating to drive off captured CO 2 . Flue gas exiting the absorber column was routed to MHI’s proprietary AERU to recover entrained solvent. The system operated using a catch-and-release method where the CO 2 was separated to provide data on the process, but the captured CO 2 was released back into the host site stack. Particulate was measured, collected, and analyzed from multiple locations throughout the pilot-scale system. Unlike the performance observed in prior work, the inlet FGD and DCC did not remove significant particulate matter from the flue gas. This appears to be due to a difference in the nature of the particulate. The DCC seemed to increase particulate size and count, most likely owing to water condensing onto the surfaces of fly ash particles. When the WESP was operated, it achieved >95% particulate capture. Very little particulate matter or indications of solvent were detected at the AERU outlet. When operating with advanced KS 21 solvent, the particulate material at the AERU outlet was even further decreased. Solvent analysis showed that some species derived from flue gas and ash were slowly concentrating in the solvent over the duration of the test. The levels observed were reported to be within expected ranges and were not of concern to MHI. A high-level techno-economic assessment of installing CO 2 capture at Coal Creek Station suggested that, when using a standard monoethanolamine (MEA)-based solution with simple heat integration, the energy penalty to net generation would be 34%. The bulk of this was due to steam losses for regenerating solvent, followed by parasitic electrical demand for CO 2 compression and then by increased parasitic load for pushing flue gas through the absorber column. These demands could be decreased with a more advanced solvent that exhibits lower heat of regeneration and lower pressure drop than does a simple MEA solution. Further energy could be saved with more thorough heat integration to recover useful energy from the steam used for solvent regeneration. Installing a WESP was predicted to increase the cost of electricity by nearly $5/MWh. This would become cost-effective if solvent losses were roughly 10 times the baseline estimate when not using a WESP but could be returned to baseline by installing the WESP. Piping CO 2 for storage in more favorable geology could help with carbon capture and storage economics. Although storing off-site would necessitate construction of a CO 2 transport pipeline, the cost of this pipeline might be more than offset by reducing the number of wells required, the depths of the wells required, and the electrical demand for the CO 2 compressor. Additional factors that favor off-site storage costs include smaller expected CO 2 plume sizes, which translates to less monitoring and fewer landowner agreements. More detailed assessment of the specific geology in the region under and around Coal Creek Station would be needed to accurately assess the costs and benefits of different storage site options. This subtask was cofunded through the Energy & Environmental Research Center–U.S. Department of Energy Joint Program on Research and Development for Fossil Energy-Related Resources Cooperative Agreement No. DE-FE0024233. Nonfederal funding was provided by the North Dakota Industrial Commission.

Strege, Joshua↗
DOE OSTI2026

Biomass carbon removal can help sustainable aviation fuels achieve on-time arrival

Biofuels, including sustainable aviation and marine fuels, and biomass carbon removal and storage (BiCRS) are often viewed as potentially competing pathways for advancing climate and energy goals. Their comparative economic, environmental, and temporal advantages remain debated. Rather than identifying a “best-use” for biomass, we show that the relative economic advantages of BiCRS versus biofuels exist along a continuum shaped by energy- and decarbonization-focused market conditions. These pathways need not be adversarial: BiCRS can enable, rather than displace, future biofuel deployment. While the lignocellulosic biofuel sector continues to face barriers associated with underdeveloped supply chains and technologies that have not yet been commercialized at scale, emerging BiCRS approaches are comparatively feedstock-flexible, rapidly deployable, and responsive to carbon removal markets. Early BiCRS deployment can help establish reliable biomass supply chains, reducing investment risk for future lignocellulosic biorefineries. By easing initial supply chain constraints, BiCRS can serve as a practical stepping stone toward meeting both near-term carbon removal needs and long-term sustainable fuel objectives under uncertain future market and policy conditions.

bioenvironmental engineering↗
DOE OSTI2022

Mechanically and Thermally Enhanced 3D-Printed Photocurable Polymer Nanocomposites Containing Functionalized Chitin Nanowhiskers by Stereolithography

Additive manufacturing, or simply 3D printing (3DP), where objects are built through layer-wise material deposition, has gained significant academic and industrial attention as a result of the development of advanced and functional materials requiring rapid, customized, and flexible solutions. In the context of green manufacturing, diversifying environmentally and economically sustainable material portfolios is an essential endeavor for the success of 3DP technology that uses widely available, highly valuable, and renewable materials. Here, we used stereolithography (SLA) for processing methacrylate-based photocurable resins containing crab shell-derived chitin nanowhiskers (CNWs), which are surface-functionalized by reactive acrylate groups. Results from full spectral, thermal, structural, and topological analyses corroborate not only the surface functionalization of CNWs but also indicate the presence of these photocurable CNW (pCNW) fillers in the 3D-printed nanocomposites. Owing to the strong interfacial bond induced by the physical and chemical crosslinking between the pCNW and methacrylate (MA) polymer matrix, the internally formulated nanocomposites displayed enhanced thermomechanical properties (e.g., storage modulus and glass transition temperature) compared to those of commercially available pure SLA resins. For instance, the inclusion of 0.5 wt % pCNW improved the tensile strength and stiffness to up to 78 and 71%, respectively, without compromising the toughness and ductility of the printed material. Accordingly, this result also evidences the compatibility between the filler and resin materials. Consequently, the formation of a crosslinked network in the nanocomposite structure results in a higher thermal stability and activation energy (i.e., up to ~79%) for all the hybrid materials than the pristine MA. Finally, the high-resolution SLA print features, dimensional accuracy, and enhanced mechanical performance of our microstructure-forming functionalized chitin-based nanocomposites make them promising materials for a wide range of robust and high-performance industrial applications.

36 MATERIALS SCIENCE↗
DOE OSTI2024

2024 roadmap on magnetic microscopy techniques and their applications in materials science

Considering the growing interest in magnetic materials for unconventional computing, data storage, and sensor applications, there is active research not only on material synthesis but also characterisation of their properties. In addition to structural and integral magnetic characterisations, imaging of magnetisation patterns, current distributions and magnetic fields at nano- and microscale is of major importance to understand the material responses and qualify them for specific applications. In this roadmap, we aim to cover a broad portfolio of techniques to perform nano- and microscale magnetic imaging using superconducting quantum interference devices, spin centre and Hall effect magnetometries, scanning probe microscopies, x-ray- and electron-based methods as well as magnetooptics and nanoscale magnetic resonance imaging. The roadmap is aimed as a single access point of information for experts in the field as well as the young generation of students outlining prospects of the development of magnetic imaging technologies for the upcoming decade with a focus on physics, materials science, and chemistry of planar, three-dimensional and geometrically curved objects of different material classes including two-dimensional materials, complex oxides, semi-metals, multiferroics, skyrmions, antiferromagnets, frustrated magnets, magnetic molecules/nanoparticles, ionic conductors, superconductors, spintronic and spinorbitronic materials.

2D materials↗
DOE OSTI2022

kynema-fmb [SWR-23-07]

Kynema-FMB (FKA: Kynema) is an open-source performance portable flexible multibody (FMB) dynamics solver designed for time-domain simulations. While originally tailored for wind turbine structural dynamics, the formulation and implementation are those of a general flexible-multidbody dynamics solver that can readily be applied to a wide range of systems. Kynema was designed with a narrow focus, namely to provide a lightweight, fast, accurate FMD solver for coupling to computational-fluid-dynamics (CFD) codes, especially the CFD codes in the Kynema suite, for fluid-structure-interaction (FSI) simulations. Kynema-FMB is equipped to model systems that can be represented as a collection of beams and rigid bodies that are connected through constraints. Degrees of freedom are defined in the inertial/global frame of reference and include displacements and rotations (formally as rotation matrices, but stored as quaternions). The underlying formulation is built on a Lie-group time integrator designed for index-3 differential-algebraic equations, which is second-order accurate in time (Bruls et al., 2012). Beam models are based on geometrically exact beam theory and are discretized as high-order spectral finite elements similar to those in BeamDyn (Wang et al., 2017). The governing equations for a FMD system like a wind turbine constitute a highly nonlinear system of constrained partial-differential equations. Kynema-FMB uses analytical Jacobians in the nonlinear-system solves in each time step. Linear systems use sparse storage and several third-party sparse-linear-system solvers are enabled. Ill conditioning of linear systems is mitigated with preconditioning described in Bottasso et al, 2008. Kynema-FMB is integrated with a simple open-source controller (ROSCO). There is an application programming interface (API) for coupling to geometry-resolved CFD (like that in Sharma et al., 2023) and actuator-force CFD (like that in Kuhn et al., 2025). In the latter, for actuator-line models, Kynema-FMB includes an internal blade-element solver that depends on user-provided lookup tables for coefficients of lift and drag, i.e., aerodynamic polars. Kynema-FMB is written in C++ and leverages Kokkos and Kokkos-Kernels (KokkosEcosystem) as its performance portability layer enabling simulations on both CPU and GPU systems. The repository is equipped with extensive automated testing at the unit and regression/system levels. The following describes the high-level development objectives conceived for Kynema: *Kynema will follow modern software development best practices, including test-driven development (TDD), version control, hierarchical automated testing, and continuous integration (CI) for a robust development environment. *The core data structures are memory efficient and enable vectorization and parallelization at multiple levels. *Data structures are data-oriented to exploit methods for accelerated computing including high utilization of chip resources (e.g., single instruction multiple data (SIMD) instruction sets) and parallelization using GP-GPUs. *The computational algorithms incorporate robust open-source libraries for mathematical operations, resource allocation, and data management. *The API design considers multiple stakeholder needs and ensure integration with existing and future ecosystems for data science, machine learning, and AI. *Kynema-FMB is written in modern C++ and leverages Kokkos as its performance-portability library with inspiration from the kynema stack.

Sprague, MichaelA.↗