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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Selectivity Control in Catalytic Reductive Amination of Furfural to Furfurylamine on Supported Catalysts

Abstract Amines are widely used in the manufacture of pharmaceuticals, agricultural chemicals, polymers, and surfactants. However, amines are mostly produced via petrochemical means, which motivates amine production from renewable resources, such as biomass. However, biomass compounds present added challenges involving poor carbon balances. We show that furfural reacts homogeneously with ammonia to produce reactive primary imines, which form large side products and leads to significant carbon losses. The carbon balance is improved by mixing furfural with furfurylamine prior to reaction to form a secondary imine for use as the reaction substrate. While controlling the primary to secondary amine selectivity is a common challenge in reductive amination, supported metal catalysts, including Ni/SiO 2 , Co/SiO 2 , and Ru/SiO 2 optimize the primary amine yield to 90 to 94 % by using the secondary imine as the reaction substrate. A qualitative correlation between the primary to secondary amine selectivity with the nitrogen binding energy of metals is identified.

Gould, Nicholas S.↗
DOE OSTI2024

Optimized Incorporation of Furan into Diketopyrrolopyrrole-Based Conjugated Polymers for Organic Field-Effect Transistors

Flexible electronics have received considerable attention in the past decades due to their promising application in rollable display screens, wearable devices, implantable devices, and other electronic applications. Here, in particular, conjugated polymers are favored for flexible electronics due to their mechanical flexibility and potential for solution-processed fabrication techniques, such as blade-coating, roll-to-roll printing, and high-throughput printing allowing for high-performance transistor devices. Thiophene is the prevailing conjugated unit to construct these conjugated polymers due to its favorable electronic properties. On the other hand, furans are among the few conjugated moieties that are easily derived from bio renewable resources. To promote sustainability, we selectively introduced furan into the conjugated backbone of a high-mobility polymer scaffold and systematically studied the effect on the microstructure and charge transport. We show that partially and selectively replacing thiophene units with furan can yield nearly comparable performance compared to the all-thiophene polymer. This strategy offers an improvement in the sustainability of the polymer by incorporating bio-sourced furan without sacrificing the high-performance characteristics. Meanwhile, polymers with incorrect or complete furan incorporation show reduced mobilities. This work serves to develop coherent structure–morphology–performance relationships; such knowledge will establish guidelines for the future development of sustainable, furan-based conjugated materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

On the Use of Surfactant-Complexed Chitosan for Toughening 3D Printed Polymethacrylate Composites

This work reports a simple approach to prepare toughened 3D-printed polymethacrylate (PMA) composites using surfactant-modified chitosan (SMCS) particles at loadings between 2–10 wt%. Chitosan (CS) is modified with anionic surfactant, sodium dodecyl sulfate, via ionic complexation to facilitate compatibility and dispersion of CS to PMA matrix by non-covalent interactions between the components. The study successfully demonstrates high-accuracy 3D printing of composites with significant improvements in the overall mechanical properties. The composite with the best loading of 8 wt% SMCS shows a tensile modulus of 1.23 ± 0.05 GPa, a tensile strength at 49.8 ± 0.96 MPa, a yield stress at 33.3 ± 1.48 MPa, and a strain-at-ailure 10.3 ± 0.61%, which are 45%, 40%, 32%, and 68% higher than neat PMA, respectively. This provides a significant improvement in toughness at 4.92 ± 0.55 MJ m -3 for the composite, 184% higher than that of neat PMA. The marked increase in toughness is due to enhanced filler-matrix interactions which improve the ability of the 3D printed composite to absorb energy under tensile load. The results from this work provide new understandings into the strategies for design and preparation of stereolithography 3D printed materials reinforced with toughening fillers from renewable resources.

36 MATERIALS SCIENCE↗
DOE OSTI2020

A Combined Thermochemical and Microbial Process for Recycling Polylactic Acid Polymer to Optically Pure L-Lactic Acid for Reuse

Polylactic acid polymer (PLA) produced from renewable resources can be recycled at the end of life to constituent monomer, optically pure lactic acid (LA), by a combination of chemical and biological processes. Efficient application of this closed loop of LA-PLA plastics-LA can minimize accumulation of plastics waste that pollute land and oceans. Temperature-dependent hydrolysis of PLA in water to LA follows apparent first order decay kinetics after a short lag. A modified Gompertz equation can explain the overall hydrolysis process. Alkali increased the rate of hydrolysis of PLA and reduced the length of lag period compared to water alone. The stoichiometry of base added to LA released was 1.0. The highest lactic acid yield was 0.95 g g -1 of PLA. D-LA in the syrup obtained after hydrolysis of PLA-plastics was removed using an engineered Escherichia coli to produce a L-LA syrup with an optical purity ≥ 99%. Here, these results show that thermochemical hydrolysis of PLA-based plastics to LA with optimum amount of base followed by bio-based purification to L-LA is an effective method of recycling PLA-plastics for reuse.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Energy Storage as an Equity Asset

Abstract Purpose of Review This review offers a discussion on how energy storage deployment advances equitable outcomes for the power system. It catalogues the four tenets of the energy justice concept—distributive, recognition, procedural, and restorative—and shows how they relate to inequities in energy affordability, availability, due process, sustainability, and responsibility. Recent Findings Energy storage systems have been deployed to support grid reliability and renewable resource integration, but there is additional emerging value in considering the connections between energy storage applications and equity challenges in the power system. Through a thorough review of the energy justice and energy transitions literature, this paper offers the equity dimensions of storage project design and implementations. Summary Emerging energy programs and projects are utilizing energy storage in pursuit of improved equity outcomes. Future research and policy design should integrate energy justice principles to align storage penetration with desired equity outcomes.

25 ENERGY STORAGE↗
DOE OSTI2025

Evaluating grid stress and reliability in future electricity grids across a range of demand, generation mix, and weather trends

The reliability of power grids in the future will depend on how system planners account for the integration of new technologies, extreme weather events, and uncertainties in demand growth from increased electrification and data centers. This study introduces an open-source, multisectoral, multiscale modeling framework that projects grid stress and reliability trends between 2020 and 2055 in the Western Interconnection of the United States. The framework integrates global to national energy-water-land dynamics with power plant siting and hourly grid operations modeling. We analyze future wholesale electricity price shocks and unserved energy events across eight scenarios spanning a range of population growth and economic change, generation mixes, and weather conditions. Our results show future grids with high percentage of non-renewable generation and strong economic growth are characterized by higher reliability and lower wholesale electricity prices than lower growth scenarios because of larger reliance on dispatchable generators and lower fossil fuel extraction costs. Scenarios with high percentage of renewable resources have lower median but more volatile wholesale electricity prices as well as more frequent and severe unserved energy events compared to scenarios relying more on dispatchable generators. These events occur because higher proportion of solar and wind energy causes net demand curves to deepen during midday (duck curves get progressively severe), exacerbating the challenge of meeting demand during summer evening peaks. This study suggests that robust and co-optimized transmission and energy storage planning could help maintain low wholesale electricity prices and high reliability levels in future electricity grids across uncertainties in generation mixes.

Electric grid reliability↗
DOE OSTI2022

Decarbonization scenarios of the U.S. Electricity system and their costs

Decarbonizing the electricity system to zero-carbon emission is crucial for climate change mitigation. Previous studies have shown that such a transition in the United States (U.S.) may lead to higher system cost compared to a business-as-usual case, but it is not well-known how the cost of electricity generation varies at sub-regional level under the transition, and studies have rarely evaluated the trade-off between the cost and avoided climate damages, as well as the potential roles of negative emission technologies (NETs) in the electricity decarbonization. In this work, we present a regionally resolved national model to quantify the cost of decarbonizing the U.S. electricity system under a set of possible scenarios. The results show that, compared to the reference scenario without a decarbonization policy, reaching zero CO 2 emission by 2050 would incur, depending on the scenarios, 335-494 billion USD additional cost to the U.S. electric power sector during 2020-2050. The regional costs of electricity generation ranges from 2.4 to 4.7 cent/kWh, largely due to the generation profiles and renewable resources availability of those regions. The additional costs can be translated to an average CO 2 abatement cost of 29-59 USD/metric ton CO 2 (with 2%-7% discount rates), which are comparable to the social cost of carbon in the literature at around 4% discount rate. The results also show that the cost of mitigating the last few percent CO 2 emission from the U.S. electricity system may exceed the costs of NETs, indicating an opportunity for NETs to contribute to electricity decarbonization.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Power System Operational Impacts of Electric Vehicle Dynamic Wireless Charging

The electrification of the transportation sector poses an opportunity for reducing greenhouse gas (GHG) emissions from passenger vehicles. Electric vehicle (EV) charging through dynamic wireless power transfer (DWPT), known as roadway electrification, could shift EV demand profiles to better coincide with renewable electricity generation. However, this would be a very large new load and few studies evaluate the regional impacts of DWPT charging in a power transmission system. This paper defines methods that address dataset generation for passenger vehicle trips and models to evaluate regional impacts for this emerging technology. Household vehicle miles traveled (VMT) data form localized EV demand profiles through discrete-event simulation. This data serves as exogenous inputs for a Production Cost Model (PCM) of a synthetic transmission system based on the Electric Reliability Council of Texas's (ERCOT) network. EV charging methods are compared for both a 2018 baseline generation mixture and a high-renewable generation case incorporating 20 GW of installed solar photovoltaic (PV) capacity. The PCM employs unit commitment and economic dispatch (UC&ED) models to compare financial, environmental, and grid reliability impacts from EV charging across passenger EV adoption levels. In-transit charging could reduce grid operational costs by as much as 1.49%, with up to $13.7B saved in annual vehicle operational costs for consumers compared to gas-powered vehicles. Health impacts analysis from power plant and vehicle tailpipe emissions from this study show net health benefits increase by 40% for in-transit charging coupled with high renewable generation. Renewable resources provide an avenue for cost-effective in-transit charging with reduced emissions. The combination of dataset generation and open-source power system modeling establish a foundation for the holistic evaluation of regional DWPT impacts.

dynamic wireless power transfer↗
DOE OSTI2020

Hydrogen production from lignocellulosic hydrolysate in an up-scaled microbial electrolysis cell with stacked bio-electrodes

Hydrogen production from renewable resources via microbial electrolysis cells (MECs) is a promising approach for sustainable energy production. Yet high hydrogen yield from real feedstocks has not been demonstrated in up-scaled MECs. In this study, a 10-L single chamber MEC with a high electrode surface area to volume ratio (66 m 2 /m 3 ) was constructed and electroactive cathodic biofilms were enriched for hydrogen evolution reaction. A high hydrogen yield of 91% was achieved using lignocellulosic hydrolysate with a hydrogen production rate of 0.71 L/L/D at an organic loading rate of 0.4 g/D. The anodic and cathodic microbial communities, with Enterococcus spp. as the known electroactive bacteria, were capable of achieving current densities of 13.7 A/m 2 and 16.5 A/m 2 , respectively. Finally, a machine learning algorithm was used to investigate the correlation between community data and electrochemical performance, and the critical genera on determining current density were identified.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Sr 2 MnO 4 as a reactive CO 2 sorbent for sorption-enhanced steam reforming of biogas to green hydrogen

Sorption-enhanced steam biogas reforming is an attractive approach for hydrogen production from renewable resources, with the performance of the CO 2 sorbents being a critical factor. In this study, Sr 2 MnO 4 was investigated as a redox-activated CO 2 sorbent for sustainable hydrogen production from biogas. The Sr 2 MnO 4 sorbents exhibited a CO 2 sorption capacity of over 26 g per 100 g of sorbents, along with excellent cyclic stability in thermogravimetric analysis. Complete regeneration of the sorbent was achieved with a relatively small temperature swing (100 °C). Fixed-bed reactor experiments further demonstrated the application of Sr 2 MnO 4 sorbents in sorption-enhanced steam biogas reforming. Biogas simulants with varying CO 2 contents were converted to ~94 vol% H 2 before CO 2 breakthrough. Stable CO 2 capacity and hydrogen production were maintained over 20 cycles. In addition, optimization of the regeneration duration enabled the generation of highly pure CO 2 and more efficient use of O 2 . These results support the feasibility of biogas-to‑hydrogen conversion with net-negative carbon emissions through integration with CO 2 capture and sequestration.

09 BIOMASS FUELS↗
DOE OSTI2023

Urban mining from biomass, brine, sewage sludge, phosphogypsum and e-waste for reducing the environmental pollution: Current status of availability, potential, and technologies with a focus on LCA and TEA

We discuss how rapid industrialization, improved standards of living, growing economies and ever-increasing population has led to the unprecedented exploitation of the finite and non-renewable resources of minerals in past years. It was observed that out of 100 BMT of raw materials processed annually only 10% is recycled back. This has resulted in a strenuous burden on natural or primary resources of minerals (such as ores) having limited availability. Moreover, severe environmental concerns have been raised by the huge piles of waste generated at landfill sites. To resolve these issues, ‘Urban Mining’ from waste or secondary resources in a Circular Economy’ concept is the only sustainable solution. The objective of this review is to critically examine the availability, elemental composition, and the market potential of the selected secondary resources such as lignocellulosic/algal biomass, desalination water, sewage sludge, phosphogypsum, and e-waste for minerals sequestration. This review showed that, secondary resources have potential to partially replace the minerals required in different sectors such as macro and microelements in agriculture, rare earth elements (REEs) in electrical and electronics industry, metals in manufacturing sector and precious elements such as gold and platinum in ornamental industry. Further, inputs from the selected life cycle analysis (LCA) & techno economic analysis (TEA) were discussed which showed that although, urban mining has a potential to reduce the greenhouse gaseous (GHG) emissions in a sustainable manner however, process improvements through innovative, novel and cost-effective pathways are essentially required for its large-scale deployment at industrial scale in future.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

A Decomposition-Based Learn-To-Optimize Approach with Feasibility Layer Assistance for Sub-Hourly Unit Commitment

Sub-hourly unit commitment (UC) with 15-min intervals is gaining significant attention as a way to respond rapidly to the fluctuations in electricity supply and demand introduced by renewable resources. However, the increased temporal resolution and complex inter-temporal dependencies pose substantial computational challenges for traditional optimization methods. To this end, this paper explores a decomposition-based learn-to-optimize approach. Building on recent advances in machine learning, our method revisits the long- overlooked Lagrangian relaxation framework, which is a classical decomposition technique that enables tractable subproblem solving. These smaller subproblems are inherently well-suited for machine learning, as their reduced dimensionality and structural regularity allow predictive models to efficiently learn and generalize solution patterns. We thus propose a generic predictive model, which embeds Gated Recurrent Units (GRUs) and Attention in the encoder-decoder structure, and integrate a rule-based feasibility layer to capture temporal dependencies, reduce training effort, and improve feasibility w.r.t. unit-level constraints. Our method has been validated on the IEEE 118-bus system, demonstrating promising performance in solving sub-hourly UC problems efficiently and feasibly.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Reviewing flexibility in industrial electrification: Focusing on green ammonia and steel in the United States

The renewable energy transition in the power sector involves a paradigm shift for flexibility. Flexible demand is more attainable than before, while supply flexibility faces new constraints due to the increased share of variable renewable resources. Increased demand flexibility can allow less use of peaking power plants and avoid need for additional capacity. Industrial flexibility could be especially interesting in this regard, as industrial customers are larger on average than other customers and have typically provided the largest share of demand response in the United States. We consider industrial demand, studying characteristics of flexible industrial loads. We then examine the dynamics of change occurring around industrial load flexibility by focusing on two case studies: green ammonia and steel production via electric arc furnaces. Electric arc furnace steel production is an important component of current demand response programs, whereas green ammonia and green fuels offer new paradigms for flexibility. We analyze the structure and functions of the technological innovation systems of load flexibility in those two industries via interviews with twenty-two stakeholders. Here, we conclude that in the United States these technological innovation systems are not well-functioning for industry in general or for steel, but do seem to be present for green ammonia. Additionally, explicit connections between scope two greenhouse gas emissions (those from purchased energy) and flexibility are lacking, and likewise industry stakeholders do not appear to make a connection between decarbonization and load flexibility, thus flexible demand is not viewed as a tool in industrial decarbonization.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Efficient data-driven models for prediction and optimization of geothermal power plant operations

Increasing the capacity of geothermal energy as a renewable resource calls for development and deployment of efficient control and optimization technologies for geothermal power plants. A data-driven prediction and optimization model is presented as a cost-effective and efficient alternative to physics-based approach. The model predicts power output and operational cost by propagating the influence of control and disturbance variables within an artificial neural network (ANN). Numerical experiments with simulated and field data from a real geothermal power plant are first used to demonstrate the prediction performance of the ANN model. The model is then adopted to maximize the net predicted power production by automatically adjusting the working fluid circulation rate. The optimization performance of the model in evaluated using a thermodynamic flowsheet simulation model. The workflow is applied to model and control the effect of ambient temperature on an air-cooled binary cycle power plant, which is complex and costly to perform using a physics-based predictive model. As a result, the performance of the method is demonstrated by applying it to both simulated and field datasets from a binary cycle geothermal power plant.

15 GEOTHERMAL ENERGY↗
DOE OSTI2023

A hybrid data-driven and model-based approach for computationally efficient stochastic unit commitment and economic dispatch under wind and solar uncertainty

Stochastic unit commitment (UC) and economic dispatch (ED) are imperative in dealing with uncertainty in renewable forecast for power system operation and planning such that the overall expected production cost is minimized over the planning horizon. However, accurate calculation of the expected production cost requires assessment of a very large number of different scenarios of uncertain renewable resources, such as solar and wind, which is practically infeasible to simulate in real time. This article proposes a hybrid datadriven and physics-based model-predictive paradigm to efficiently solve for stochastic unit commitment and economic dispatch considering uncertainty in wind and solar power forecasts. Here, the novelty of the approach lies in decoupling the production cost estimation from the unit commitment and economic dispatch optimization problems under uncertainty without compromising on the fidelity of the solutions. A data-driven machine learning model is first developed to predict the mean optimal production cost. A physics-based inverse problem is then solved to get the stochastic UC and ED profiles from the expected cost. The presented approach considers, for the first time, solar uncertainty in UC/ED determination and enables efficient and accurate propagation of wind and solar uncertainty to estimate the statistics of the production cost. The effectiveness of the developed approach is demonstrated systematically on a stylized RTS-GMLC single-node system. The overall framework predicts the expected cost 62.5% more accurately than the existing state-of-the-art, on unforeseen days during the entire year, and yields, for the first time, the associated physically consistent UC and ED profiles. The solutions are also shown to be flexible in providing adequate daily reserves to address any statistical deviations from probabilistic power forecasts. The computational time associated with the presented method is only about 10 s compared to over 24 h needed for a conventional stochastic UC/ED determination under uncertainty on an Intel Core i9 processor with 32 GB of RAM.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

GPU-resident sparse direct linear solvers for alternating current optimal power flow analysis

Integrating renewable resources within the transmission grid at a wide scale poses significant challenges for economic dispatch as it requires analysis with more optimization parameters, constraints, and sources of uncertainty. This motivates the investigation of more efficient computational methods, especially those for solving the underlying linear systems, which typically take more than half of the overall computation time. In this paper, we present our work on sparse linear solvers that take advantage of hardware accelerators, such as graphical processing units (GPUs), and improve the overall performance when used within economic dispatch computations. We treat the problems as sparse, which allows for faster execution but also makes the implementation of numerical methods more challenging. We present the first GPU-native sparse direct solver that can execute on both AMD and NVIDIA GPUs. We demonstrate significant performance improvements when using high-performance linear solvers within alternating current optimal power flow (ACOPF) analysis. Furthermore, we demonstrate the feasibility of getting significant performance improvements by executing the entire computation on GPU-based hardware. Finally, we identify outstanding research issues and opportunities for even better utilization of heterogeneous systems, including those equipped with GPUs.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Dynamic operation of metal-supported solid oxide electrolysis cells

Symmetric-structure metal-supported solid oxide fuel cells and electrolysis cells (MS-SOFCs, MS-SOECs) offer several advantages over conventional solid oxide cells, including the use of inexpensive materials, high mechanical strength, and rapid ramp-up ability. Aggressive operation of MS-SOCs in fuel cell mode is well-established, including extremely fast start-up, redox tolerance, and imbalanced pressure. Here, we extend dynamic operation to MS-SOCs in SOEC mode with high steam content for both small button cells and a large rectangular cell, including: steam cycling, thermal cycling, redox cycling and power cycling. Steam cycling entailed switching between 3:97 and 50:50 steam:hydrogen ratio. For thermal cycling, the temperature was rapidly varied between 150°C and 700°C for 50 cycles. Redox cycling involved switching the steam side gas between 50 % humidified H 2 and 50 % humidified N 2 for 5 cycles. Power cycling was performed by operating the cell under variable current density, resulting in cell voltage between 1.3V and 2.8V. Degradation rates for each testing strategy were compared to a baseline cell, and found to be similar. In conclusion, the excellent tolerance to dynamic operation increases confidence that MS-SOECs will be compatible with dynamic or intermittent renewable resources.

08 HYDROGEN↗
DOE OSTI2023

Towards functionalized lignin and its derivatives for high-value material applications

In pursuit of low-carbon development, the production of diverse functional materials from renewable resources, especially lignocellulosic biomass, is of vital importance. Lignin is a major component of lignocellulose, and it is nature's only true high-volume aromatic polymer, which has the advantages of biodegradability, biocompatibility, and low acquisition cost. After modification by a variety of physicochemical strategies, it can be applied as an alternative to basic industrial materials, including polyurethanes, phenolic, and epoxy resins, which stands comparably to conventional synthetic polymers in terms of both performance and reduced cost. To further unlock the potential of lignin, an alluring opportunity is the exploitation of lignin for high-value materials, especially nanomaterials, that find extensive applications in energy and environment areas. This review provides a systematic summary and perspective of research that has been devoted to lignin transformation to high-value materials, ranging from industrially well-established engineering materials to the recently emerged nanomaterials that were used for energy and environment applications. Latest cutting-edge innovations on lignin modification, controlled depolymerization, and assembly during the last five years are summarized. Structure-function relationships of lignin materials in terms of their specific applications are analyzed. Furthermore, challenges and future opportunities for lignin conversion to high-value materials are also provided. We wish this review will stimulate further advances in lignin based high-value materials, and promote “waste” into “wealth”.

36 MATERIALS SCIENCE↗