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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 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Structure-Informed Graph Learning of Networked Dependencies for Online Prediction of Power System Transient Dynamics

Online transient analysis plays an increasingly important role in dynamic power grids as the renewable generation continues growing. Traditional numerical methods for transient analysis not only are computationally intensive but also require precise contingency information as input, and therefore, are not suitable for online applications. Existing online transient assessment studies focus on the determination of post-contingency system stability or stability margin. Here, this paper develops a novel graph-learning framework, Deep-learning Neural Representation or DNR, for online prediction, of the time-series trajectories of the system states using initial system responses that can be measured by phasor measurement units (PMUs). The proposed DNR framework consists of two sequential modules: a Network Constructor that captures network dependencies among generators, and a Dynamics Predictor that predicts the system trajectories. The key to improved prediction performance is the introduction of the spatio-temporal message-passing operations into graph neural networks with structural knowledge. Its effectiveness and scalability are validated through comparative studies, demonstrating the prediction performance under different contingency scenarios for systems of different sizes. This framework provides a solution to online predicting post-fault system dynamics based on real-time PMU measurements. Additionally, it can also be applied to facilitate the offline transient simulation without simulating the entire trajectories.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Influence of extreme temperature conditions on CO 2 direct air capture using amino-acid solutions

Geological features play a pivotal role in determining the feasibility of deploying CO₂ direct air capture (DAC) technologies, primarily because they influence the availability of cost-effective energy sources, such as natural gas and geothermal energy, and also due to the potential for CO₂ sequestration. Many regions face challenges due to variable weather conditions including seasonal temperature fluctuations, high or low humidity, and sub-ambient temperatures. These extremes can reduce DAC performance or even lead to catastrophic events. Aqueous solvents considered for DAC systems are particularly vulnerable to seasonal variations in colder climates, where the solvent may underperform or freeze. It is therefore essential to investigate the CO₂ capture efficiency of aqueous solvents across a broad range of environmental temperatures, spanning sub-zero to hot conditions (>30 °C). In this study, DAC operation is examined using a high-flux solvent–air crossflow contactor under two major weather scenarios: (i) cold conditions below 0 °C and (ii) hot conditions above 30 °C. A parametric study is conducted to investigate the contactor performance regarding CO₂ removal efficiency, uptake capacity, and reaction kinetics versus temperature when the air velocity through the contactor exceeds 1 m/s. The efficacy of the contactor is systematically investigated using various anti-freeze amino-acid solvent formulations. A mass-transfer mechanistic model is developed to assess the process performance over a wide temperature range and propose scalable design guidelines. Machine learning is also employed to identify key parameters affecting the CO₂ capture efficiency. It is shown that air velocity and temperature are the primary factors influencing CO₂ uptake. Based on performance data obtained under subfreezing temperatures, a technoeconomic analysis is conducted to evaluate the feasibility of using aqueous solvents in seasonal cold regions. In conclusion, the findings of this study provide valuable insights into siting considerations for deploying solvent-based DAC, thereby contributing to the advancement of sustainable carbon removal solutions.

Air–liquid contactor↗
DOE OSTI2022

Tailorable thermoplastic insulation foam composites enabled by porous-shell hollow glass spheres and expandable thermoplastic microspheres

Here we report a simple and commercially viable strategy to produce thermoplastic composite foams using synergistic foaming approaches – incorporating porous-shell hollow-interior glass spheres (PHGS) as a filler and utilizing expandable thermoplastic microspheres (EMS) as a physical blowing agent – for thermal insulation applications. The EMS in these composites ensure formation of highly porous, low-density foam while the PHGSs provide low thermal conductivity and lightweight mechanical reinforcement. Through systematic optimization of the PHGS and EMS loadings, a lightweight, and robust insulation with thermal resistivity greater than 27.7 m·K/W (R/in. > 4) is achieved. Notably, the fabricated foams also demonstrated comparable compressive strength than some commercial thermoplastic insulating materials. Through optimization of PHGS and EMS concentrations, results indicated similar thermal performance characteristics at varying foam densities, while higher loadings of both components lead to reduced insulation performance and weak mechanical stability of the foams. The results obtained, when coupled with the potential scalability and tailor ability of the overall process towards targeted insulation performance, not only endows competitiveness with current commercial thermoplastic insulating materials but also offers great promise for the development of unique thermoplastic composite foams for a variety of insulation systems.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Scalable Techniques for Stochastic Power Flow Problems (Final Report)

The proposed research focuses on developing scalable algorithms for two-stage security-constrained OPF problems with AC power flow constraints, a class of problems complicated by (i) scale arising from a scenario representation; and (ii) the presence of nonlinearity, nonconvexity, and possibly second-stage discreteness or complementarity. Unfortunately, most existing solvers cannot contend with both challenges simultaneously; accordingly, the proposed research focuses on developing solution techniques that can both scale with the number of scenarios and contend with nonconvexity and second-stage complementarity. We consider three avenues for addressing such problems: (i) Variable sample-size SQP (VS-SQP) methods that combine sparse Quasi-Newton updates with a scalable variance-reduced stochastic gradient scheme for stochastic QP subproblems, allowing for contending with second-stage complementarity via regularization; (ii) Variable sample-size stochastic Interior-point (VS-sIP) schemes that propose a sampling-based regularized (to allow for contending with complementarity) interior-point schemes in which a Schur-complement technique is employed for decomposing the Newton direction computation step; (iii) Variable sample-size tractable ADMM (VS-tADMM) schemes combine variable sample-sizes with carefully designed techniques for resolving each of the nonconvex updates (by leveraging the QCQP structures). We intend to compare the three schemes using performance profiles in terms of solution quality, scalability, etc. and then select one scheme which will then be developed and further refined in Python for purposes of the GO competition.

42 ENGINEERING↗
DOE OSTI2024

Electrochemical Conversion of CO 2 to Methyl Formate in a Flow Electrolyzer with Mixed Propylene Carbonate/Methanol Catholyte

Despite the promise of electrochemical carbon dioxide reduction as a technology for the production of clean fuels and decarbonization of the chemical industry, research has mostly focused on aqueous systems with a relatively limited set of products that have been achieved via electrosynthesis. Increasingly, CO 2 electroreduction in nonaqueous solvents is being pursued to develop new avenues for expanding the suite of products that can be made with high selectivity. CO 2 reduction in alcohols coupled with in situ esterification to produce esters is one such route that utilizes nonaqueous electrolyte. To be practical, such electrochemical syntheses need to be translated to a high-performance reactor such as a flow electrolyzer. However, many organic solvents, such as alcohols, wet and flood porous electrodes, thus impeding reactor performance. In this work, methanol was mixed with propylene carbonate as a catholyte for a gas-fed CO 2 flow electrolyzer that avoided cathode flooding. Simultaneously, a dual aqueous anolyte was used for water oxidation as a scalable and sustainable anodic half-reaction. The performance effect of methanol concentration, catholyte acidity, CO 2 flow rate, and dilute water in the catholyte were investigated. With 10 vol % methanol in 90 vol % propylene carbonate, 63% faradaic efficiency for methyl formate ester product was sustained without cathode flooding. However, improvements are still needed to lower the cell resistance and further increase the operating current density.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Accelerated Scaling to Rapid Open-Air Fabrication of Durable Perovskite Solar Modules

The goals of this SETO project (DE-EE0008559, Accelerated Scaling to Rapid Open-Air Fabrication of Durable Perovskite Solar modules) are to address the principal challenges towards the successful commercialization of perovskite solar modules utilizing scalable, high-throughput open-air spray deposition. The successful outcome of the project will provide the foundation of an all open-air spray deposited perovskite solar module with hole transport layer (HTL), perovskite, electron transport layer (ETL), and barrier layer development while establishing a fundamental understanding of perovskite device behavior under accelerated aging conditions. Through this program, we have made significant progress towards a commercializable pathway for perovskites. (1) We’ve demonstrated the successful open-air deposition of perovskite and transport layer materials. These deposition methods were chosen for their inherent scalability, and open-air processing enables a significant reduction in processing costs. These methods are also compatible with high throughputs, demonstrating the fastest perovskite film deposition at these performance levels. (2) Development of a unique all-fiber laser scribing procedure provides a high-performance, low-cost method for further improvements in scalability. (3) Our group has also placed a unique emphasis on device stability. The development of testing standards for perovskite modules is required to thoroughly evaluate potential candidates for commercialization, and we’ve taken inspiration from current industry standards to provide an honest insight into the performance and reliability of our devices. (4) An extensive cost model detailing the specific contributions of each device layer and production component provides the most thorough evaluation of any perovskite technology against conventional silicon and compound semiconductor solar devices. The cost model is a critical advancement that will provide the foundation for evaluating the levelized cost of energy (LCOE) of this technology.

14 SOLAR ENERGY↗
DOE OSTI2023

An implicit barotropic mode solver for MPAS-ocean using a modern Fortran solver interface

Here, we demonstrate use of a modern Fortran solver interface to manage solver algorithms for an implicit barotropic mode solver in the Model for Predictions Across Scales-Ocean (MPAS-O). ForTrilinos, a Fortran interface to Trilinos that contains a large collection of solver capabilities written in C++, has been implemented in MPAS-O to provide access to a suite of linear solver options. By virtue of the simplified wrapper and interface generator (SWIG) automation tool that generates modern Fortran interfaces to C++ code, we were able to implement the Fortran solver interface in MPAS-O using a familiar Fortran coding style while minimizing performance degradation. The ForTrilinos solver interface is written within MPAS-O’s time stepping modules as a subroutine in conjunction with MPAS-O code. Applied to an idealized ocean and a high-resolution realistic ocean test case, parallel performance of ForTrilinos solvers is examined. It is found that parallel scalability of the ForTrilinos solvers is highly dependent on the number of global synchronization points per solver iteration in each iterative solver algorithm. ForTrilinos solvers perform best compared to the Fortran hand-crafted (FHC) solver when the amount of work per processor is large enough. However, parallel scalability is better with the FHC solver and so when the work per core is modest FHC outperforms ForTrilinos. The intercomparison between the ForTrilinos and FHC solvers reveals that this performance hit in the ForTrilinos solver mostly comes from the global synchronization process, while suggesting that the matrix-vector multiplication process in the FHC solver needs to be optimized for better performance.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Piezo-electrocatalytic oxidation of methanol with UV-ozone treated wurtzite zinc oxide nanostructures

Leveraging mechanically-induced piezoelectric polarization, piezocatalysis emerges as a viable mechanism for enhancing the efficiency of catalytic processes. Nanostructured, catalytically active, rationally designed piezoelectric semiconductors can achieve high-performance catalysts for various applications using cost-effective electrocatalytic pathways, such as mechanical stimuli. We design and demonstrate for the first time a cost-effective, high-performance piezo-electrocatalyst for anodic methanol oxidation, which is crucial for the practical application and deployment of direct methanol fuel cells in a variety of emerging clean energy technologies. We synthesized wurtzite ZnO nanorods and nanosheets treated with UV-O 3 to characterize and compare their efficacy for piezo-electrocatalytic methanol oxidation. The generation of piezoelectric polarization charges in nanostructured semiconducting ZnO catalysts significantly increased their electrocatalytic performance. By elucidating the charge transfer between mechanically-deformed ZnO nanostructures and methanol molecules, we identified the underlying mechanism for the piezo-electrocatalytic process for methanol oxidation. The facile synthesis of high-quality ZnO nanostructures enables low-cost, scalable manufacture and direct integration into electrocatalysts whose performance could be enhanced by harvesting mechanical energy that would otherwise be wasted in the working environment.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2020

Deffe: A Data-efficient Framework for Performance Characterization in Domain-Specific Computing

Predicting workload performance is a crucial task for many architecture and system research. In this paper we present De￿e, a framework to estimate the workload performances under varying architectural configurations. The infrastructure component of Deffe is based on scalable and easy-to-use open-source software components. By casting the performance modeling as transfer learning tasks, the modeling component of Deffe can leverage the learned knowledge on one workload, and “transfer” it to a new workload. Extensive experimental results show that the method can achieve superior testing accuracy with an effective reduction of 32-80x in terms of the amount of required training data.

Liu, Frank↗
DOE OSTI2025

3D printing of architected sulfur cathodes with dual-site atomic catalysts for accelerated polysulfide kinetics and Li-ion transport in high areal-loading lithium–sulfur batteries

The practical deployment of lithium–sulfur batteries (LSBs) is hindered by fundamental limitations in conventional slurry-cast cathodes, including poor sulfur utilization, sluggish ion transport, and low areal capacity, particularly in thick electrodes required for high energy density. To address these challenges, we present direct ink writing (DIW) as an additive manufacturing strategy to fabricate advanced current-collector-free, 3D-printed sulfur cathodes (3DP S@CoNi-DSACs/NC) with hierarchically porous architectures that enhance lithium-ion diffusion, promote electrolyte penetration, and reduce interfacial resistance. The synergistic effects of Co/Ni dual-atom sites accelerate redox kinetics and mitigate polysulfide shuttling. As a result, the optimized 3DP cathode with a sulfur loading of 5.4 mg cm −2 demonstrated excellent rate capability, delivering a high reversible capacity of 1041.4 mAh g −1 at 1C with 85.5% capacity retention after 1000 cycles, significantly outperforming its cast counterpart. Remarkably, even at a higher sulfur loading of 8.1 mg cm −2 , the 3DP cathode maintains outstanding performance, achieving a discharge capacity of 1538.4 mAh g −1 and an areal capacity of 12.5 mAh cm −2 at 0.1C. This study not only demonstrates the functional integration of catalytically active materials into 3D printable sulfur cathode architectures but also offers a scalable and transformative platform for building high-performance LSBs beyond conventional electrode manufacturing methods.

3D electrode↗
DOE OSTI2024

Amorphous Iridium Oxide-Integrated Anode Electrodes with Ultrahigh Material Utilization for Hydrogen Production at Industrial Current Densities

Herein, ionomer-free amorphous iridium oxide (IrO x ) thin electrodes are first developed as highly active anodes for proton exchange membrane electrolyzer cells (PEMECs) via low-cost, environmentally friendly, and easily scalable electrodeposition at room temperature. Combined with a Nafion 117 membrane, the IrO x -integrated electrode with an ultralow loading of 0.075 mg cm –2 delivers a high cell efficiency of about 90%, achieving more than 96% catalyst savings and 42-fold higher catalyst utilization compared to commercial catalyst-coated membrane (2 mg cm –2 ). Additionally, the IrO x electrode demonstrates superior performance, higher catalyst utilization and significantly simplified fabrication with easy scalability compared with the most previously reported anodes. Notably, the remarkable performance could be mainly due to the amorphous phase property, sufficient Ir 3+ content, and rich surface hydroxide groups in catalysts. Overall, due to the high activity, high cell efficiency, an economical, greatly simplified and easily scalable fabrication process, and ultrahigh material utilization, the IrO x electrode shows great potential to be applied in industry and accelerates the commercialization of PEMECs and renewable energy evolution.

08 HYDROGEN↗
DOE OSTI2021

Impact of secondary particle size and two-layer architectures on the high-rate performance of thick electrodes in lithium-ion battery pouch cells

Increasing lithium-ion battery gravimetric energy density to > 300 Wh/kg, while simultaneously meeting a cost target of $80/kWh, is of paramount importance to increasing the driving range and affordability of electric vehicles. One way to address this goal is to reduce inactive components by increasing electrode areal capacities, but conventional thick electrode designs typically perform poorly at high discharge rates due to Li + mass transport limitations. Here we compare the rate capability and cycle life of NMC 532/graphite pouch cells made with five different thick cathode and anode designs paired together in 25 combinations. We find that using different particle sizes to structure both the cathode and anode architectures in two-layer configurations results in a 2X capacity improvement over the worst-performing combination at high discharge rates (97 vs. 46 mAh/g at 2C). These different cathode/anode designs also translate to different cycle life performance, with many cells cycled at C/2 achieving ~80% capacity retention after 1000 cycles, and cells cycled at 2C showing different degrees of capacity fade. Altogether, these results demonstrate that simple, scalable changes in electrode design can significantly improve the performance of thick electrodes for high energy density batteries.

25 ENERGY STORAGE↗
DOE OSTI2026

Covalent adaptable networks for electrolyte–binder integration in recyclable lithium metal batteries

Lithium-metal batteries (LMBs) are considered a promising next-generation energy storage technology due to their exceptionally high energy density. However, the development of solid polymer electrolytes and cathode binders for LMBs faces critical challenges, including interfacial instability, poor recyclability, and growing environmental concerns. In particular, current systems often rely on non-recyclable components featuring permanently crosslinked networks and polyfluoroalkyl substances (PFAS), such as poly(vinylidene fluoride) (PVDF), which cause battery waste and environmental harm. Herein, we introduce a multifunctional covalent adaptable network (CAN) platform based on thermally reversible Diels–Alder (DA) chemistry, designed for dual functionality as a CAN-based electrolyte (CAE) and a CAN-based cathode binder. The CAE achieves high ionic conductivity and strong storage modulus (1.4 mS cm −1 and ∼ 10 5 Pa at room temperature, respectively) and enables stable long-term cycling in symmetric Li||Li cells for over 2000 h with low overpotential. When it is applied as a cathode binder in LiFePO 4 (LFP) composite electrodes (C-LFP), the CAN matrix significantly reduces interfacial resistance and enhances discharge capacity compared to conventional PVDF-based systems. Thermal treatment induces self-healing at the cathode–electrolyte interface, further improving contact and yielding a discharge capacity of 150 mAh g −1 at 0.5 C. Moreover, the dynamic CAN architecture allows efficient recovery and reuse of lithium salts from spent electrolytes through retro-DA reactions under mild conditions (∼80 °C), establishing a low-energy, cost-effective recycling pathway. In conclusion, this work presents a scalable and sustainable strategy for high-performance LMBs by integrating recyclability, interfacial healing, and PFAS-free design, offering a holistic solution aligned with circular economy principles and next-generation battery demands.

Diels–Alder↗
DOE OSTI2025

OpenEdge: A collaborative, open-source, multi-purpose direct simulation Monte Carlo for plasma simulation in magnetic fusion environments

OpenEdge is a collaborative, open-source, object-oriented Direct Simulation Monte Carlo (DSMC) code, designed specifically for plasma simulations in magnetic fusion environments. Here, the code features include advanced structures, robust capabilities, and an effective parallelization strategy, all of which significantly enhance performance. It includes specialized modules for managing complex particle interactions, including collisions, ionization/recombination, and reflection/sputtering. Benchmarks and performance analyses have confirmed its efficiency and scalability. Versatile and adaptable, OpenEdge is applied across a broad spectrum of plasma-material interaction studies and charged particle transport in various fusion research settings.

Boundary plasma↗
DOE OSTI2023

Enhanced thermal reliability and performance of calcium chloride hexahydrate phase change material using cellulose nanofibril and graphene nanoplatelet

In recent years, thermal energy storage (TES) has gained attention for its role in enhancing renewable energy solutions and sustainable energy consumption. The usage of strontium chloride hexahydrate (SCH), graphene nanoplatelet (GNP), and cellulose nanofibril (CNF) additives were investigated to enhance the performance of calcium chloride hexahydrate (CCH) based on the melting/solidification behavior for TES applications. In this work, we develop a promising phase-change-material (PCM) formulation by introducing these additives that reduce supercooling, improve the thermal conductivity and stabilizing the energy storage capacity of CCH. Rheological characterizations demonstrated that the addition of 1 wt% of CNF into CCH produced the required improvement in viscosity and boosted solid-like rheological behavior. Structural characterizations show a physical mixing of the materials within the PCM composites. Our observations show that the amphiphilicity of CNF enables the surface attachment to GNP via hydrophobic interactions providing effective dispersion of GNP throughout the PCM composite. The addition of a nucleating agent, SCH decreased the degree of supercooling of ~20 g of CCH from >20 °C to 3 °C at a cooling rate of 5 °C/min. Thermal characterization showed the resulting PCM composite has a latent heat of melting of 186 Jg -1 , phase change temperature of 32 °C, and stable thermal properties after being subjected to 70 melt-freeze cycles. Adding CNF and GNP to pure CCH increased its thermal conductivity by 76 %. The high thermal conductivity of GNP and its effective dispersion by CNF is responsible for this enhancement. The study highlights the use of biodegradable nanocellulose for the preparation of sustainable PCM composites with improved performance. In conclusion, these PCM composites are scalable, they have potential to increase energy efficiency and revolutionalize the heating/cooling applications in buildings and other TES systems.

25 ENERGY STORAGE↗