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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 1,153 records · Page 64
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Synergistic Improvement of Carbohydrate and Lignin Processability by Biomimicking Biomass Processing

The sustainability and economic feasibility of modern biorefinery depend on the efficient processing of both carbohydrate and lignin fractions for value-added products. By mimicking the biomass degradation process in white-rote fungi, a tailored two-step fractionation process was developed to maximize the sugar release from switchgrass biomass and to optimize the lignin processability for bioconversion. Biomimicking biomass processing using Formic Acid: Fenton: Organosolv (F 2 O) and achieved high processability for both carbohydrate and lignin. Specifically, switchgrass pretreated by the F 2 O process had 99.6% of the theoretical yield for glucose release. The fractionated lignin was also readily processable by fermentation via Rhodococcus opacus PD630 with a lipid yield of 1.16 g/L. Scanning electron microscope analysis confirmed the fragmentation of switchgrass fiber and the cell wall deconstruction by the F 2 O process. 2D-HSQC NMR further revealed the cleavage of aryl ether linkages (β-O-4) in lignin components. These results revealed the mechanisms for efficient sugar release and lignin bioconversion. The F 2 O process demonstrated effective mimicking of natural biomass utilization system and paved a new path for improving the lignin and carbohydrate processability in next generation lignocellulosic biorefinery.

09 BIOMASS FUELS↗
DOE OSTI2021

Competitive Furfural Production: Producing Additional Revenue From Waste

The competitive furfural synthesis process converts a low-value byproduct of corn ethanol production into a high-value chemical and a high-value feed residue. This easily implemented process may be incorporated alongside existing work flows to create additional revenue streams.

09 BIOMASS FUELS↗
DOE OSTI2025

Strategies for simulating the time evolution of Hamiltonian lattice field theories

Simulating the time evolution of quantum field theories given some Hamiltonian H requires developing algorithms for implementing the unitary operator e -iHt . A variety of techniques exist that accomplish this task, with the most common technique used so far being Trotterization, which is a special case of the application of a product formula. However, other techniques exist that promise better asymptotic scaling in certain parameters of the theory being simulated, the most efficient of which are based on the concept of block encoding. In this work we study the performance of such algorithms in simulating lattice field theories. We derive and compare the asymptotic gate complexities of several commonly used simulation techniques in application to Hamiltonian lattice field theories. Using the scalar $\hat{φ}$ 4 theory as a test, we also perform numerical studies and compare the gate costs required by product formulas and signal-processing-based techniques to simulate time evolution. For the latter, we use the linear combination of unitaries (LCU) construction augmented with the quantum Fourier transform circuit to switch between the field and momentum eigenbases, which leads to immediate order-of-magnitude improvement in the cost of preparing the block encoding. Further, this paper also includes a pedagogical review of the techniques used, in particular product formulas, LCU, qubitization, quantum signal processing, as well as the technique for simulating geometrically-local Hamiltonians developed by Haah, Hastings, Kothari, and Low.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

VFA Biorefinery Design for Informed Production of Ground and Aviation Fuels

The rising demand for low-carbon intensity fuel options requires evaluation of a system which can support their production economically and sustainably. Volatile fatty acids (VFAs) ranging from C2 to C8 can be derived in high yield from arrested anaerobic digestion of biomass. This talk provides an overview of our work in which we upgrade wet waste-derived VFAs using ketonization to elongate their carbon backbone to reach a range relevant to jet or diesel fuels. Kinetic models were used to predict ketone profiles from varying VFA profiles, thereby informing potential carbon flow to either (a) mixed paraffins for use in diesel or aviation fuel, or (b) ethers for use in diesel fuel. To do this, the anticipated products were screened for critical fuel characteristics using predictive tools. The criteria for neat and blended bioblendstocks were chosen based on conventional petrofuel requirements, and they were applied to inform fuel targets, identify limiting characteristics, and guide conversion development. While paraffins can serve as either diesel or aviation fuels, the latter has stringent criteria which include a precise distillation curve range tied to carbon distribution. Fuels which fall outside this range typically fail to meet other property metrics, and as such flashpoint and viscosity were identified as potentially limiting properties of this VFA aviation fuel. However, paraffin fractions which fall outside aviation criteria may meet diesel fuel requirements, which are looser except for the flashpoint minimum. Flashpoint was also a concern for smaller VFA diesel ethers, which posed an additional oxygenate risk of high water solubility. This fuel-informed conversion design process was demonstrated through production of paraffins with reduced sooting as compared to petrodiesel (~34%), and increased renewable aviation fuel blend levels (>70%). VFA-derived ethers improved petrodiesel by increasing fuel autoignition quality by 56% and reducing sooting by 86%. These VFA aviation and diesel fuels could enable greenhouse gas (GHG) reductions of over 165% and 50%, respectively, relative to their purely fossil-derived counterparts. Collectively, this work provides (i) an overview of how we leveraged the flexibility of VFAs for fuel production; and (ii) insight into the potential of a VFA biorefinery to accommodate varied feed and fuel applications, while also considering the merit of tailored fuel production pathways and GHG reduction potential.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Energy, greenhouse gas, and water life cycle analysis of synthetic graphite anode production in the United States

This study presents a comprehensive life cycle analysis of potential synthetic graphite battery anode material (BAM) production in the U.S. based on industrial-scale data. The analysis focuses on three impacts: greenhouse gas (GHG) emissions, total energy use, and water consumption. We also conducted sensitivity analyses to evaluate the effect of variation in process parameters and energy sources used for synthetic graphite BAM production on its life cycle GHG emissions. A detailed supply chain analysis of graphite BAM in the U.S. was also undertaken, along with a study of its associated GHG emissions. The results show GHG emissions of 29.7 kg CO 2 -eq. per kg BAM, total energy use of 580 MJ kg −1 BAM, and water consumption of 121 L kg −1 BAM for the baseline condition. The graphitization step is a major process hotspot, contributing to over 74% of all impacts. This is attributed to the energy and material input requirements for this step, particularly through the use of crucibles. Across the entire synthetic graphite production process, electricity is the primary contributor, followed by crucibles used in graphite block production, and then calcined petroleum coke. Sensitivity analyses indicate that improvement in micronization yield, reuse of crucibles, and use of low-carbon nuclear energy can significantly reduce GHG emissions of potential domestic graphite production (by ∼70%). Supply chain analysis identified major graphite BAM sources in the U.S. and showed that the U.S. has a competitive advantage in domestic production of synthetic graphite BAM in terms of reduced life cycle GHG emissions compared to present-day imported sources (by ∼20%).

Battery anode↗
DOE OSTI2023

An end-to-end pipeline for succinic acid production at an industrially relevant scale using Issatchenkia orientalis

Abstract Microbial production of succinic acid (SA) at an industrially relevant scale has been hindered by high downstream processing costs arising from neutral pH fermentation for over three decades. Here, we metabolically engineer the acid-tolerant yeast Issatchenkia orientalis for SA production, attaining the highest titers in sugar-based media at low pH (pH 3) in fed-batch fermentations, i.e. 109.5 g/L in minimal medium and 104.6 g/L in sugarcane juice medium. We further perform batch fermentation using sugarcane juice medium in a pilot-scale fermenter (300×) and achieve 63.1 g/L of SA, which can be directly crystallized with a yield of 64.0%. Finally, we simulate an end-to-end low-pH SA production pipeline, and techno-economic analysis and life cycle assessment indicate our process is financially viable and can reduce greenhouse gas emissions by 34–90% relative to fossil-based production processes. We expect I. orientalis can serve as a general industrial platform for production of organic acids.

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

Recommendations for developing, documenting, and distributing data products derived from NEON data

The National Ecological Observatory Network (NEON) provides over 180 distinct data products from 81 sites (47 terrestrial and 34 freshwater aquatic sites) within the United States and Puerto Rico. These data products include both field and remote sensing data collected using standardized protocols and sampling schema, with centralized quality assurance and quality control (QA/QC) provided by NEON staff. Such breadth of data creates opportunities for the research community to extend basic and applied research while also extending the impact and reach of NEON data through the creation of derived data products—higher level data products derived by the user community from NEON data. Derived data products are curated, documented, reproducibly-generated datasets created by applying various processing steps to one or more lower level data products—including interpolation, extrapolation, integration, statistical analysis, modeling, or transformations. Derived data products directly benefit the research community and increase the impact of NEON data by broadening the size and diversity of the user base, decreasing the time and effort needed for working with NEON data, providing primary research foci through the development via the derivation process, and helping users address multidisciplinary questions. Creating derived data products also promotes personal career advancement to those involved through publications, citations, and future grant proposals. However, the creation of derived data products is a nontrivial task. Here we provide an overview of the process of creating derived data products while outlining the advantages, challenges, and major considerations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Manufacture of Carbon Foam in Continuous Process at Atmospheric Pressure

The objective is to develop continuous processing of carbon foam products made from coal at atmospheric pressure. Both carbon foam panels and lightweight carbon foam aggregates have been developed. A successful outcome would: 1) significantly reduce the cost to manufacture carbon foam through reductions in capital and labor costs, 2) significantly reduce the manufacturing time from weeks to hours, and 3) enable the manufacture of much larger volumes of carbon foam. All of these features are expected to enable carbon foam to enter much larger markets and create meaningful demand for U.S. coal.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2020

Discovery of single-atom alloy catalysts for CO 2 -to-methanol reaction by density functional theory calculations

The transformations of CO 2 molecules into valuable products are of increasing interest due to the negative impact of anthropogenic CO 2 emissions on global warming. The CO 2 -to-methanol hydrogenation is an economically profitable reaction of carbon fixation, but it still steps away from widespread industrialization because of the lack of efficient and selective catalysts. Recently, single-atom alloy (SAA) catalysts have been developed to work remarkably in CO 2 hydrogenation reactions. Doping isolated single atoms into metallic catalyst can dramatically alter the catalytic performance of the host. Here, we have performed a screening discovery on Ru and 6 RuX (X = Fe, Co, Ni, Cu, Ir and Pt) SAAs using density functional theory (DFT) computations. We considered 13 possible elementary reactions in 4 possible reaction pathways on Ru and all RuX surfaces. In the computed mechanisms, we found that the formation of *H 2 COOH and *HCOO intermediates plays a critical role in determining catalysts’ activities. Doping Co and Pt isolated single atoms into Ru surface can thermodynamically and kinetically facilitate these intermediates formation processes, eventually promoting the production of methanol. The combination of weak binding and enhanced charge redistribution on RuCo and RuPt surfaces give them improved catalytic activities over pure Ru. This work will ultimately facilitate the discovery and development of SAAs for CO 2 to methanol, serving as guidance to experiments and theoreticians alike.

25 ENERGY STORAGE↗
DOE OSTI2020

Day-ahead photovoltaic power production forecasting methodology based on machine learning and statistical post-processing

A main challenge towards ensuring large-scale and seamless integration of photovoltaic systems is to improve the accuracy of energy yield forecasts, especially in grid areas of high photovoltaic shares. The scope of this paper is to address this issue by presenting a unified methodology for hourly-averaged day-ahead photovoltaic power forecasts with improved accuracy, based on data-driven machine learning techniques and statistical post-processing. More specifically, the proposed forecasting methodology framework comprised of a data quality stage, data-driven power output machine learning model development (artificial neural networks), weather clustering assessment (K-means clustering), post-processing output optimisation (linear regressive correction method) and the final performance accuracy evaluation. The results showed that the application of linear regression coefficients to the forecasted outputs of the developed day-ahead photovoltaic power production neural network improved the performance accuracy by further correcting solar irradiance forecasting biases. The resulting optimised model provided a mean absolute percentage error of 4.7% when applied to historical system datasets. Finally, the model was validated both, at a hot as well as a cold semi-arid climatic location, and the obtained results demonstrated close agreement by yielding forecasting accuracies of mean absolute percentage error of 4.7% and 6.3%, respectively. Finally, the validation analysis provides evidence that the proposed model exhibits high performance in both forecasting accuracy and stability.

42 ENGINEERING↗
DOE OSTI2023

Combined effects of lipase and Lactiplantibacillus plantarum 1‐24‐LJ on physicochemical property, microbial succession and volatile compounds formation in fermented fish product

Abstract BACKGROUND Studies have shown that either the addition of starter culture or enzyme can improve fermentation in fish or other products. However, little research has been carried out on the effects of coupling starter cultures with lipase on the microbial community and product quality. Suanzhayu is a Chinese fermented fish product that mainly relies on spontaneous fermentation, resulting in an unstable flavor and quality. The present study investigated the impact of lipase and Lactiplantibacillus plantarum 1‐24‐LJ on the quality of Suanzhayu . RESULTS Inoculation decreased pH and 2‐thiobarbituric acid reactive substances (TBARS) values, and also helped the dominance of the strain in the ecosystem, whereas lipase addition raised TBARS values and had little effect on pH, water activity ( a w ) and microbiota. The addition of lipase and/or Lpb. plantarum increased the content of alcohols, aldehydes, ketones, esters and umami amino acids. The co‐additions with the most significant effect and the total contents of volatile compounds (VCs) and free amino acids (FAAs) were 1801.92 g per 100 g and 21 357.05 mg per 100 g, respectively. Former‐ Lactobacillus was negatively correlated with pH, a w and Prevotella , but positively with VCs (ethyl ester of heptanoic acid, ethyl ester of octanoic acid) and FAAs (Tyr, Phe). Furthermore, adding Lpb. plantarum 1‐24‐LJ alone or in combination with lipase shortened the fermentation process. CONCLUSION The present study provides a recommended Suanzhayu process approach for improving product quality and flavor, as well as shortening fermentation time, by adding Lpb. plantarum 1‐24‐LJ with or without lipase. © 2023 Society of Chemical Industry.

Zhang, Zuoli↗
DOE OSTI2020

Filter Adapters for BI-PAP and CPAP Equipment

Researchers at Los Alamos National Laboratory are researching and designing technology intended to help reduce the exposure of patients and medical staff to pathogens, such as SARS-CoV-2, while providing medical staff the dexterity and flexible work conditions necessary to conduct routine and complex patient care on infected patients. This investigative technology would potentially enable hospitals to adapt, utilize, and repurpose existing Bilevel Positive Airway Pressure (BiPAP) or Continuous Positive Airway Pressure (C-PAP) equipment in the fight against COVID-19, which would potentially save hospitals significant money, reduce exposure to staff and patients, and increase the supply of critically needed devices at a time when supplies are scarce in the market place. A provisional patent has been filed on the technology and we are seeking a commercialization partner to license and further develop the product for commercial purposes, including processing the device through the FDA emergency use authorization or clearance process. One hospital system has indicated that upon FDA authorization or clearance, it would have interest in the product.

42 ENGINEERING↗
DOE OSTI2025

Feedstock-efficient conversion through hydrogen and formate-driven metabolism in Escherichia coli

Product yields for biomanufacturing processes are often constrained by the tight coupling of cellular energy generation and carbon metabolism in sugar-based fermentation systems. To overcome this limitation, we engineered Escherichia coli to utilize hydrogen gas (H 2 ) and formate (HCOO - ) as alternative sources of energy and reducing equivalents, thereby decoupling energy generation from carbon metabolism. This approach enabled precise suppression of decarboxylative oxidation during acetate growth, with 86.6 ± 1.6 % of electrons from hydrogen gas (via soluble hydrogenase from Cupriavidus necator H16) and 98.4 ± 3.6 % of electrons from formate (via formate dehydrogenase from Pseudomonas sp. 101) offsetting acetate oxidation. Hydrogen gas supplementation led to a titratable and stoichiometric reduction in CO 2 evolution in acetate-fed cultures. Metabolomic analysis suggests that this metabolic decoupling redirects carbon flux through the glyoxylate shunt, partially bypassing two decarboxylative steps in the TCA cycle. Here, we demonstrated the utility of this strategy by applying it to mevalonate biosynthesis, where formate supplementation during glucose fermentation increased titers by 57.6 % in our best-performing strain. Flux balance analysis further estimated that 99.0 ± 2.8 % of electrons from formate were used to enhance mevalonate production. These findings highlight a broadly applicable strategy for enhancing biomanufacturing efficiency by leveraging external reducing power to optimize feedstock and energy use.

Biomanufacturing↗
DOE OSTI2024

Synthesizing Lithium Sorbents Using Acid Mine Drainage Solids

In this study, we prepared HMO from coal mine drainage (CMD) solids and examined the practicability of recovering Li from oil and gas produced waters and geothermal brines. We aim to innovate high-value added products from the existing extract REEs and CMs processing chain of legacy byproducts associated with coal production. CMD solids, which are precipitates collected from exhausted limestone gravels of passive CMD treatment beds, are enriched in rare earth elements (REEs) and other critical minerals (CMs), and therefore, considered as a viable alternative source for REEs/CMs to supply the Nation’s demands. A patented extraction process developed by NETL (TREE) has been demonstrated as a cost-effective and efficient approach to recover REEs/CMs from CMD solids. Here, we selected residuals of CMD solids from the TREE process that are enriched in manganese (Mn) (>20% w/w) and successfully prepared LMO using a solid-state method modified from Yoshizuka et al. (2002).

Cheng, Chin-Min↗
DOE OSTI2021

Reactor scale simulations of ALD and ALE: Ideal and non-ideal self-limited processes in a cylindrical and a 300 mm wafer cross-flow reactor

Here, we have developed a simulation tool to model self-limited processes such as atomic layer deposition (ALD) and atomic layer etching inside reactors of arbitrary geometry as well the output of in situ quartz crystal microbalance and mass spectrometry. We have applied this model to two standard types of cross-flow reactors: a cylindrical tube reactor and a model 300 mm wafer reactor, and explored both ideal and nonideal self-limited kinetics. The model results are in agreement with experimental results and analytic expressions obtained using a simple plug-flow model for the cylindrical tube reactor. We also extended the simulations to consider two nonideal self-limited processes: soft-saturating processes characterized by a slow reaction pathway and processes where surface by-products can compete with the precursor for the same pool of adsorption sites. Our results show that it is possible to have a self-limited process with saturated yet inhomogeneous growth profiles due to the competition of reactor by-products. This is in agreement with experimental observations for titanium dioxide ALD from titanium tetraisopropoxide and titanium tetrachloride precursors.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Performance and cost analysis of liquid fuel production from H 2 and CO 2 based on the Fischer-Tropsch process

Electro-fuels can be produced from concentrated sources of carbon dioxide and hydrogen using electricity generated from renewable sources; this process enables energy storage at high volumetric energy density. Among the electro-fuels options, FT (Fischer-Tropsch) fuel is attractive for heavy-duty trucks and non-road transportation applications. This study conducts a techno-economic analysis of FT liquid fuel production from H 2 and CO 2 using a detailed performance analysis. Minimum fuel selling price is estimated for a broad range of H 2 and CO 2 prices and for a range of potential CO 2 credits. The analysis indicates that H 2 price has the largest impact on the minimum selling price of FT fuel. FT fuel production with a CO 2 price of $17.3/metric ton requires an H 2 price of $0.8/kg to be cost-competitive with the pre-tax petroleum diesel price of $3.1/gal in 2050 (before the application of any CO 2 credits). When the H 2 price is $2.0/kg from central water electrolysis (2020 target), the minimum selling price of the FT fuel is $5.4–5.9/gal. A sensitivity analysis shows that future system optimization of FT fuel production could focus on improving the H 2 and CO 2 recycle contributions and FT fuel conversion ratio. The analysis results can be combined with various upstream systems for H 2 and CO 2 production.

08 HYDROGEN↗
DOE OSTI2024

Adaptively remeshed multiphysical modeling of resistance forge welding with experimental validation of residual stress fields and measurement processes

Welding processes used in the production of pressure vessels impart residual stresses in the manufactured component. Computational modeling is critical to predicting these residual stress fields and understanding how they interact with notches and flaws to impact pressure vessel durability. Here, in this work, we present a finite element model for a resistance forge weld and validate it using laboratory measurements. Extensive microstructural changes, near-melt temperatures, and large localized deformations along the weld interface pose significant challenges to Lagrangian finite element modeling. The proposed modeling approach overcomes these roadblocks in order to provide a high-fidelity simulation that can predict the residual stress state in the manufactured pressure vessel; a rich microstructural constitutive model accounts for material recrystallization dynamics, a frictional-to-tied contact model is coordinated with the constitutive model to represent interfacial bonding, and adaptive remeshing is employed to alleviate severe mesh distortion. An interrupted-weld approach is applied to the simulation to facilitate comparison to displacement measures. Several techniques are employed for residual stress measurement in order to validate the finite element model: neutron diffraction, the contour method, and the slitting method. Model-measurement comparisons are supplemented with detailed simulations that reflect the configurations of the residual-stress measurement processes themselves. The model results show general agreement with experimental measurements, and we observe some similarities in the features around the weld region. Factors that contribute to model-measurement differences are identified. Finally, we conclude with some discussion of the model development and residual stress measurement strategies, including how to best leverage the efforts put forth here for other weld problems.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Stem respiration and growth in a central Amazon rainforest

Tropical forests cycle a large amount of CO 2 between the land and atmosphere, with a substantial portion of the return flux due tree respiratory processes. However, in situ estimates of woody tissue respiratory fluxes and carbon use efficiencies (CUEW) and their dependencies on physiological processes including stem wood production (Pw) and transpiration in tropical forests remain scarce. In this work, we synthesize monthly Pw and daytime stem CO 2 efflux (ES) measurements over one year from 80 trees with variable biomass accumulation rates in the central Amazon. On average, carbon flux to woody tissues, expressed in the same stem area normalized units as ES, averaged 0.90 ± 1.2 µmol m -2 s -1 for Pw, and 0.55 ± 0.33 µmol m -2 s -1 for daytime ES. A positive linear correlation was found between stem growth rates and stem CO 2 efflux, with respiratory carbon loss equivalent to 15 ± 3% of stem carbon accrual. CUEW of stems was non-linearly correlated with growth and was as high as 77-87% for a fast-growing tree. Diurnal measurements of stem CO 2 efflux for three individuals showed a daytime reduction of ES by 15-50% during periods of high sap flow and transpiration. The results demonstrate that high daytime ES fluxes are associated with high CUE W during fast tree growth, reaching higher values than previously observed in the Amazon Basin (e.g. maximum CUEW up to 77-87%, versus 30-56%). The observations are consistent with the emerging view that diurnal dynamics of stem water status influences growth processes and associated respiratory metabolism.

54 ENVIRONMENTAL SCIENCES↗