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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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DOE OSTI2024

Membrane Separations in Biomass Processing

The development of integrated biorefineries and the greater utilization of biomass resources to reduce dependence on fossil fuel-derived products require research emphasis not just on conversion strategies but also on improving separations associated with biorefining. A significant roadblock towards developing biorefineries is the lack of effective separation techniques evidenced by the relative deficiency of literature in this area. Additionally, high conversion yields may only be realized if effective separations generate feedstock of sufficient purity – this makes research into biomass conversion strategies all the more critical. In this review, the challenges associated with biomass separations are discussed, followed by an overview of the most appropriate separation strategies for processing biomass. One of the unit operations most appealing for biorefining, membrane separations (MS), is then considered along with a review of the recent literature utilizing this technique in biomass processing.

09 BIOMASS FUELS↗
DOE OSTI2025

Genetically engineered poplar wood effectively enhances the efficiency of deep eutectic solvent-mediated one-pot processing

Although lignocellulosic biomass is a renewable resource with the potential to replace fossil-derived fuels and chemicals, its recalcitrance, largely due to lignin, limits its utilization. Recent advancements in genetic engineering have produced transgenic trees with reduced lignin content and/or modified lignin structure without compromising growth traits. Here, three engineered poplar varieties are evaluated as feedstocks using a biocompatible one-pot deep eutectic solvent-mediated process that integrates biomass fractionation and enzymatic saccharification within a single reactor, eliminating water washing and reconditioning. All transgenic poplars exhibit higher fermentable sugar yields than wild-type (WT) trees. Notably, QsuB poplar, incorporating 3,4-dihydroxybenzoate in lignin, achieves the highest glucose conversion yield of 91.3% (vs. 73.0% from WT). AT5 and MdCHS3 poplars, incorporating ferulate esters and naringenin, also demonstrate improved glucose yields (86.7 and 84.7%, respectively), confirming reduced biomass recalcitrance. Additionally, residual lignins are valorized via hydrogenolysis into phenolic compounds, with comparable alkylphenol production across all lines. These findings demonstrate that the transgenic poplar lines not only serve as superior feedstocks for sugar conversion but also provide a rich resource for phenolic compound production, enhancing the operational and economic viability of integrated biorefinery processes.

biomasses↗
DOE OSTI2022

Research needs targeting direct air capture of carbon dioxide: Material & process performance characteristics under realistic environmental conditions

The extraction of CO 2 from ambient air, or direct air capture (DAC), is a crucial negative CO 2 emissions technology with great potential for contributing to the mitigation of global warming and climate change. Furthermore, nearly all published research on DAC has been conducted under indoor temperature conditions, i.e. 20 to 30 °C. In contrast, the future global implementation of DAC requires it to be operational across a wide expanse of geographical areas, of which the local temperatures can vary between -30 to 50 °C. Similarly, the absolute humidity can vary from ~0 to 84 g/m 3 in various locations. Due to the massive amount of air that would be processed, it may be impractical to preheat or dehumidify the air before the CO 2 separation. Therefore, it is important to develop DAC materials with good performance at realistic outdoor conditions, especially at sub-ambient conditions, i.e. -30 to 20 °C. In addition to material development, system-level studies at sub-ambient conditions are also needed for the DAC processes to reach optimal designs, which may be very different from those at ambient conditions. In this perspective article, we first assess the literature to identify the technical gaps that need to be filled for DAC to be applicable at realistic outdoor conditions. We then suggest additional research directions needed for DAC to be viable under varied conditions from the perspectives of materials and system designs. For materials, we discuss the expected physical and chemical property changes for the sorbents when the temperature or humidity reaches extremes within their range, and how that will impact performance. Similarly, for system design, we indicate how varied conditions will impact performance and how these changes will impact process optimization.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2020

Residual Stress Modeling with Phase Transformation for Wire Arc Additive Manufacturing of B91 Steel

Wire arc additive manufacturing (WAAM) is an energy-efficient manufacturing technique used for near-net-shape production of functional industrial components. However, heat accumulation during deposition and the associated mechanical and metallurgical changes result in complex residual stress profiles across the cross section of the fabricated components. These residual stresses are detrimental to the service life of the components. In this study, sequentially coupled thermomechanical analysis of WAAM B91 steel is conducted to quantify the residual stress variation across the component. The thermomechanical analysis includes a transient heat transfer model and a static stress model that incorporates the transformation-induced plasticity due to martensitic phase transformation. Here, the experimentally calibrated heat transfer model mirrors the temperature variation of the system during the deposition. The results from the stress model are validated via x-ray diffraction measurements, and the numerical results are in good agreement with the experimental data.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2020

Enzyme interactions on lignocellulosic biomass structure

This chapter shows that, although well studied over the years, the cellulose enzymatic hydrolysis process has still many obstacles to be overcome or minimized. High enzyme loading and relatively long incubation periods are generally required for effective cellulose saccharification to be achieved. These limitations make the process unattractive from an economic perspective. Most studies show that the conversion rate of cellulose hydrolysis decreases over reaction time due to several factors that may inhibit, deactivate, or slow the work of enzymes. Some of these factors are inhibition by the product generated; inhibition/deactivation of enzymes by by-products generated during pretreatment (PT); limitation of mass transfer; shear stress by high stirring; air–liquid interfacial area; and unproductive adsorption on lignin or other compounds present in the biomass. The interaction between cellulases and the lignin present in these biomasses has a major negative impact on the process, with the source of the raw material and the type of PT used having a strong influence on it. Finally, the use of nonenzymatic proteins seems to be the best way to mitigate this problem.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2022

Evaluating the intrinsic resistance to balling of alloys: A High-throughput physics-informed and data-enabled approach

To date, the vast majority of work on metal additive manufacturing (AM) has been framed in terms of the need to tune processing conditions for a particular AM technology in order to print conventional alloys, oftentimes developed for fabrication methods other than AM. This approach overlooks the fact that historically, many engineering alloy system has been designed with a particular processing route in mind, e.g., ingot metallurgy, powder metallurgy, rapid quenching, etc. There are thus significant opportunities to design alloys specifically for AM. A key challenge is that alloy design requires performance metrics that can be optimized by exploring the alloy chemistry space. Here, we present a study in which we examine how intrinsic thermophysical properties can be used to estimate performance metrics related to the behavior of a solidifying metal droplet under AM-relevant conditions. By identifying these intrinsic properties, it is possible to directly incorporate ‘intrinsic printability’, specifically ‘intrinsic resistance to balling’, into AM-focused alloy design.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2020

A Discrete Dendrite Dynamics Model for Epitaxial Columnar Grain Growth in Metal Additive Manufacturing with Application to Inconel

Epitaxial columnar grain growth is a prevalent microstructural feature in the additive manufacturing (AM) of metal components such as Inconel, with cubic unit cell crystal lattice structure (face centered cubic (FCC) or body centered cubic (BCC)). These columnar grains evolve from the partly molten grains in the substrate or the solidified metal. This work proposes an efficient model to simulate the competitive growth of epitaxial columnar dendritic grains. The proposed model tracks the dynamic changes in the dendrites emanating from discrete points along the solid/liquid interface of a quasi-steady melt pool (MP). These dynamic changes include convergence and divergence of growing dendrites. The model is extended to predict the microstructure of large 3D parts and experimentally validated by comparing the simulation results for laser powder bed fusion (L-PBF) and wire-arc additive manufacturing (WAAM) processes. The microstructure and pole figures are predicted for Inconel 718 samples produced by L-PBF and Inconel 740H samples produced by WAAM processes. Finally, the model predictions compare well with the observed microstructure and pole figures results for both the L-PBF and WAAM processes.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2025

Impact of salinity on morphology, growth, and pigment profiles of Scenedesmus obliquus HTB1 under ambient air and elevated CO 2 (10 %) conditions

Certain microalgal species, such as Scenedesmus obliquus strain HTB1, thrive under high CO 2 concentrations, making them promising for carbon sequestration to mitigate climate change. Isolated from the Baltimore Inner Harbor, HTB1 grows faster with 10 % CO 2 than with ambient air. To investigate its responses to salinity and elevated CO 2 , two experiments were conducted. In the first, HTB1 was cultured at seven different salinities (0, 17.5, 20, 22.5, 25, 27.5, and 30 ppt) (parts per thousand) under ambient air. Higher salinity caused cell shrinkage, color changes from green to pale white, reduced pigments like zeaxanthin, lutein, and chlorophyll b, but increased canthaxanthin. Growth declined significantly above 22.5 ppt. The second experiment compared HTB1's response to salinity (0, 10, 20 ppt) under air and 10 % CO 2 . Cultures under 10 % CO 2 showed minimal color changes, while those under air shifted from green to brown, with salinity having less inhibitory effects on growth under elevated CO 2 . Interestingly, lutein and canthaxanthin levels rose with salinity in 10 % CO 2 . These findings indicate that elevated CO 2 mitigates salt stress in HTB1, reducing its impact on growth and promoting adaptive pigment changes. This study sheds light on how salinity and CO 2 interact to influence HTB1's morphology, growth, and pigment composition, enhancing our understanding of its resilience and potential applications.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2023

Quantifying agricultural productive use of energy load in Sub-Saharan Africa and its impact on microgrid configurations and costs

The use of advanced energy technologies for agricultural purposes—such as irrigation, refrigeration, crop processing, and egg incubation—has the potential to increase crop yield, reduce vulnerability to changing precipitation patterns, increase shelf life, strengthen income and employment opportunities in rural areas, and reduce emissions by displacing fossil fuel-based technologies. These productive uses of energy (PUE) in remote areas could potentially be powered by microgrids that additionally serve otherwise unelectrified communities, most of which are located in rural Sub-Saharan Africa. Here, in this paper, we use high-resolution geospatial data to estimate the end-use electricity demand for a range of agricultural PUE across Sub-Saharan Africa, and we share these data in an open-access mapping tool. Next, we use REopt®, a techno-economic optimization model of energy systems, to determine the cost and system sizing implications of incorporating agricultural PUE into microgrid designs in Kenya and Zambia. We estimate the upper bound of agricultural PUE demand for irrigation, milling, shelling, refrigeration, and egg incubation across Sub-Saharan to be 16.8 TWh/yr. We find that incorporating local agricultural PUE into microgrid system designs increases the required system sizing while having minimal impact on the levelized cost of energy of these systems. Our analysis is the first to demonstrate the PUE potential in the agricultural sector at a 10x10-kilometer resolution across Sub-Saharan Africa and to show, at scale, how site-specific PUE can impact the cost and sizing of microgrids that are otherwise deployed to serve local household and community load.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Market analysis for the integration of new power technologies: A case study of the deployment of hybrid fossil-based generator plus energy storage (ES-FE)

This study examines the national landscape of hybridized fossil energy (FE) power plants with energy storage (ES) technologies (“ES-FE”) and presents the compilation of an ES-FE dataset, which includes over 65 ES-FE projects and concepts in the United States, comprising approximately 500 MWh of co-located ES capacity with FE power plants. This study also estimates the economic feasibility of adding ES to existing FE power plants by characterizing the potential revenues that can be generated by the ES component through flexibility and capacity value. The analysis focuses on ES technologies with 2- to 10-h. durations located in four U.S. independent system operators (ISOs): Midcontinent ISO (MISO), Electric Reliability Council of Texas (ERCOT), PJM Interconnection (PJM), and California ISO (CAISO), which have +70,000 MW of combined FE power capacity that could add ES. Annual revenues are estimated for the ES component using a what-if-analysis approach, for capacity value, price arbitrage, or ancillary services provision. The results show that annual revenues depend on the end-use storage service, wholesale electricity and capacity market prices, and ES technology operation parameters such as discharging duration and cycling frequency. When performing a sensitivity analysis, ES accrues $7–178/kW-yr. via price arbitrage and ancillary services provision in the four ISOs, and $13–92/kW-yr. when providing capacity value only in MISO and PJM. A cash flow analysis is performed to estimate the net present value (NPV) of the ES addition using a range of ES costs. The study finds that for most ES technologies considered, these revenues alone are insufficient to achieve economic feasibility. In conclusion, of the 1645 total runs analyzed, 115 had positive NPVs (7%). Therefore, other revenue streams or monetizable benefits are necessary to achieve the break-even point.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2023

Tailoring biogenic straw insulation from additive manufacturing

In the pursuit of carbon-storing materials that could help accomplish high levels of building sustainability, wheat straw has emerged as a promising alternative to fossil fuel-based building materials. Straw is 100% biodegradable and abundant agricultural waste used in the construction 400 years ago, and it has been reported to have the lowest embodied carbon when measured against other typical insulating materials. Here, in this study, we report additive manufacturing of carbon-sequestration insulation panel materials by upcycling cellulose fibrils from wheat straw. Cellulose obtained from alkaline and 2,2,6,6-tetramethylpiperidine-1-oxyl radical-mediated oxidation shows thermal conductivity of 0.036 W m -1 K -1 , alongside elastic and flexural modulus of 900 MPa and 502 MPa, respectively. In addition, an in-situ hydrophobic treatment in the cellulose-based insulation panels is achieved with an average water contact angle of 133.7° Furthermore, the extrusion-based additive manufacturing of a 3D-printable ink obtained by mixing the cellulose and silica aerogel precursor is accomplished, with the printed material exhibiting structural integrity, thus showing great potential towards the development of state-of-the-art, sustainable materials for carbon-sequestration building applications.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Water-gas shift reaction in ceramic-carbonate dual-phase membrane reactor at high temperatures and pressures

Water-gas-shift (WGS) reaction is a critical step in integrated gasification combined cycles (IGCC) power plants with CO 2 capture. Membrane reactors made with a CO 2 -permselective ceramic-carbonate dual-phase (CCDP) membrane offers the potential to enhance hydrogen yield with simultaneous CO 2 capture for WGS reaction. The present work studies operation of WGS reaction in a tubular membrane reactor made of samarium-doped ceria infiltrated with lithium/sodium molten carbonate mixture. The WGS reaction was performed in the membrane reactor with and without a high-temperature WGS catalyst at 800–850 °C, feed pressure of 7 bar, the space velocity of 150–3000 h –1 , and a feed gas mixture of 45.7/13.1/41.3 mol% CO/CO 2 /N 2 with steam to carbon ratio of 4. The results show that the catalyst-free membrane reactor can convert 92% of carbon monoxide into CO 2 and H 2 and recover 29% CO 2 at 850 °C and a space velocity of 150 h –1 . However, in the catalyst-free membrane reactor, a significant amount of unwanted carbon deposition is observed. The side reactions can be minimized by reducing the operating pressure and increasing the operating temperature and space velocity, and completely avoided using a high-temperature catalyst at space velocity>500 h –1 . The membrane reactor with a WGS catalyst achieves CO conversion of about 85%, above the equilibrium conversion, and 40% CO 2 recovery without carbon deposition at high temperature and pressure. Finally, the membrane remains in the same structure and gas-tightness after the WGS reaction tests.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2022

Multiscale modeling and nonlinear model predictive control for flue gas desulfurization

The primary source of sulfur dioxide (SO 2 ) emissions is flue gas from fossil fuels-based power plants. SO 2 emissions are known to not only cause health issues, but also have an adverse effect on the environment in various ways. Several Flue Gas Desulfurization (FGD) technologies have been incorporated in power plants. The most popular technology is Wet FGD, where a limestone slurry is used to absorb SO 2 from the flue gas. A detailed droplet scale model describing the instantaneous and finite rate chemistry is developed. The ill-posed Differential-Algebraic Equation (DAE) droplet model is reformulated to a well-posed index-1 DAE through index reduction. The droplet model is integrated with the bulk phase by incorporating gas-liquid mass transfer, and an oxidation reactor model to simulate the dynamic operation of the counter-current spray scrubber. As a result, the model has a well-conditioned Jacobian and overcomes the modeling challenges of previous works and enables numerical solution without requiring carefully selected initialization or specialized solution procedures. The model is successfully validated using power plant measurements, and nonlinear model predictive control (NMPC) studies are demonstrated to optimize recycle stream flowrates to minimize pumping costs.

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

Energy catalysis needs ligands with high oxidative stability

Replacing fossil fuel-based energy by renewable sources is a transition that society needs to make to meet future energy demand and simultaneously address climate change. Coupling renewable energy sources with electrochemical catalysis provides a promising path to carbon-neutral fuels and chemicals when the necessary reducing equivalents and protons are harvested from water. Developing highly active, stable, and inexpensive electrocatalysts for the oxygen evolution reaction (OER) is accordingly a centerpiece of a renewable energy portfolio. Whereas viable OER catalysts are heterogeneous in nature, owing to their oxidative stability, the realization of stable molecular OER catalysts greatly expands the horizon of energy science with the ability to tune OER energetics and mechanisms with fidelity. In this perspective, current challenges in the field of molecular OER catalysis are addressed with promising lines of research that are directed to designing ligands that can withstand the harsh oxidizing environment of OER.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Targeted electrochemical reduction of carcinogenic N -nitrosamines from emission control systems within CO 2 capture plants

N-Nitrosamines are one of the environmentally significant byproducts from aqueous amine-based post-combustion carbon capture systems (CCS) due to their potential risk to human health. Safely mitigating nitrosamines before they are emitted from these CO 2 capture systems is therefore a key concern before widescale deployment of CCS can be used to address worldwide decarbonization goals. Electrochemical decomposition is one viable route to neutralize these harmful compounds. The circulating emission control waterwash system, commonly installed at the end of the flue gas treatment trains to minimize amine solvent emissions, plays an important role to capture N-nitrosamines and control their emission into the environment. The waterwash solution is the last point where these compounds can be properly neutralized before becoming an environmental hazard. In this study, the decomposition mechanisms of N-nitrosamines in a simulated CCS waterwash with residual alkanolamines was investigated using several laboratory-scale electrolyzers utilizing carbon xerogel (CX) electrodes. Hcell experiments revealed that N-nitrosamines were decomposed through a reduction reaction and are converted into their corresponding secondary amines thereby neutralizing their environmental impact. Batch-cell experiments statistically examined the kinetic models of N-nitrosamine removal by a combined adsorption and decomposition processes. The cathodic reduction of the N-nitrosamines statistically obeyed the first-order reaction model. Finally, a prototype flow-through reactor using an authentic waterwash was used to successfully target and decompose N-nitrosamines to below the detectable level without degrading the amine solvent compounds allowing them to be return to the CCS and lower the system operating costs. Furthermore, the developed electrolyzer was able to efficiently remove greater than 98% of N-nitrosamines from the waterwash solution without producing any additional environmentally harmful compounds and offers an effective and safe route to mitigate these compounds from CO 2 capture systems.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2020

A Tchebycheff-based multi-objective combined with a PSO–SQP dynamic real-time optimization framework for cycling energy systems

The aim in this work is to develop an optimization framework to address cycling of baseload energy systems due to the penetration of renewables into the grid. The developed strategy corresponds to a multi-objective and dynamic real-time optimization (MOO-DRTO) framework applied to a postcombustion MEA-based CO 2 capture process from a baseload coal-fired power plant under cycling conditions. A Tchebycheff-based method is used for the multi-objective optimization (MOO) component. Also, a hybrid approach consisting of Particle Swarm Optimization (PSO) and Sequential Quadratic Programming (SQP) is implemented for the first time in process systems engineering to solve the dynamic real-time optimization (DRTO) component. The objectives considered in the MOO-DRTO framework are economic and environmental. The proposed MOO-DRTO strategy is successfully implemented and 24-h optimal output trajectories for the carbon capture system under cycling are generated. Also, the optimal compromise is chosen from the Pareto front according to a set of selected weights for the objectives with minimal interaction between the framework and decision maker. The results indicated that the developed framework has potential to be extended to plant-wide optimization applications under cycling.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Effects of input gradient regularization on neural networks time-series forecasting of thermal power systems

This study proposes using neural networks, specifically gated recurrent unit (GRU), long-short-term memory (LSTM), and transformer networks, to improve control strategies in a 450 MW coal-fired power plant. However, neural networks face issues of becoming overly dependent on just a few variables to make predictions, which negatively impacts control decisions that rely on the model to determine the value of all manipulated variables. The paper introduces regularization techniques, including noise injection and input gradient regularization, during the training phase. Here, the work presents novel contributions in adapting neural networks to control industrial systems and applying regularization techniques from computer vision to industrial process control. Results demonstrate the effectiveness of input gradient regularization in reducing model dependence on subsets of variables, emphasizing the balance between fidelity and controllability. Further exploration is recommended, including the development of recurrent transformers, closed-loop control testing, and a sensitivity analysis on computer models to provide further insight.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2022

Data-driven modeling of power generation for a coal power plant under cycling

Increased penetration of renewables for power generation has negatively impacted the dynamics of conventional fossil fuel-based power plants. The power plants operating on the base load are forced to cycle, to adjust to the fluctuating power demands. This results in an inefficient operation of the coal power plants, which leads up to higher operating losses. To overcome such operational challenge associated with cycling and to develop an optimal process control, this work analyzes a set of models for predicting power generation. Moreover, the power generation is intrinsically affected by the state of the power plant components, and therefore our model development also incorporates additional power plant process variables while forecasting the power generation. We present and compare multiple state-of-the-art forecasting data-driven methods for power generation to determine the most adequate and accurate model. We also develop an interpretable attention-based transformer model to explain the importance of process variables during training and forecasting. The trained deep neural network (DNN) LSTM model has good accuracy in predicting gross power generation under various prediction horizons with/without cycling events and outperforms the other models for long-term forecasting. The DNN memory-based models show significant superiority over other state-of-the-art machine learning models for short, medium and long range predictions. The transformer-based model with attention enhances the selection of historical data for multi-horizon forecasting, and also allows to interpret the significance of internal power plant components on the power generation. This newly gained insights can be used by operation engineers to anticipate and monitor the health of power plant equipment during high cycling periods.

01 COAL, LIGNITE, AND PEAT↗