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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 OSTI2026

Technoeconomic analysis and life cycle assessment of purification processes for captured CO 2 streams

Captured carbon dioxide (CO 2 ) streams contain impurities that must be removed to meet specifications for safe transport, storage, and utilization. Among these impurities, oxygen poses challenges due to its high reactivity and potential to cause corrosion, motivating stringent purity limits below 10 ppmv. Building on recent experimental demonstrations of catalytic oxygen removal using hydrogen (H 2 ), carbon monoxide (CO), methanol (CH 3 OH), and methane (CH 4 ) as reducing agents, this study presents a technoeconomic (TEA) and life cycle assessment (LCA) of these four catalytic purification pathways. Process flowsheets were developed and simulated in Aspen Plus for CO 2 streams representative of both low-temperature and high-temperature capture processes, with integrated heat recovery and energy optimization. Results showed that total purification costs were dominated by feedstock procurement and electricity consumption. Among the studied reducing agents, the CH 4 -assisted route achieved the lowest purification cost and highest CO 2 recovery. Sensitivity analyses showed that the H 2 route became competitive at H 2 prices below $\$$0.56/kg to $\$$0.84/kg, depending on the CO 2 feed temperature conditions. In conclusion, environmental impacts were primarily driven by indirect CO 2 emissions from raw material production and utility consumption.

CO2 pipeline specifications↗
DOE OSTI2023

An integrated data management and informatics framework for continuous drug product manufacturing processes: A case study on two pilot plants

The pharmaceutical industry continuously looks for ways to improve its development and manufacturing efficiency. In recent years, such efforts have been driven by the transition from batch to continuous manufacturing and digitalization in process development. To facilitate this transition, integrated data management and informatics tools need to be developed and implemented within the framework of Industry 4.0 technology. Here, in this regard, the work aims to guide the data integration development of continuous pharmaceutical manufacturing processes under the Industry 4.0 framework, improving digital maturity and enabling the development of digital twins. This paper demonstrates two instances where a data integration framework has been successfully employed in academic continuous pharmaceutical manufacturing pilot plants. Details of the integration structure and information flows are comprehensively showcased. Approaches to mitigate concerns in incorporating complex data streams, including integrating multiple process analytical technology tools and legacy equipment, connecting cloud data and simulation models, and safeguarding cyber-physical security, are discussed. Critical challenges and opportunities for practical considerations are highlighted.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Chapter 14: Sustainable Biomass Conversion Process Assessment

Process intensification and integration for sustainable design play an essential role in addressing and alleviating severe sustainable development challenges. It is prudent to evaluate a process design in its early stage development to ensure the process can achieve sustainability goals. The primary goal of a sustainability evaluation is to assess the impact of systems on areas sought to be protected and maintained over time, such as human well-being and ecosystems (Schaubroeck, T. and Rugani, B. (2017). A revision of what life cycle sustainability assessment should entail: towards modeling the net impact on human well-being. Journal of Industrial Ecology 21 (6): 1464-1477). Parenthetically, sustainable process design to convert biomass to fuels and chemicals plays an integral part in the bioeconomy sustainability. It is recognized that the integration of sustainability in process design is core to the mission in developing renewable fuels and should be considered a necessary practice in biorefinery design. This study demonstrates the use of Gauging Reaction Effectiveness for ENvironmental Sustainability of Chemistries with a multi-Objective Process Evaluator (GREENSCOPE) as a tool to help track progress on process sustainability performance attributed to conversion improvement. With the incorporation of a wide range of indicators, GREENSCOPE captures the multi-dimensional aspect of the process design and operation. As opposed to conventional techno-economic analysis and life cycle assessment (in which the focuses are limited to economic and environmental aspects), GREENSCOPE enables the consideration of process intensification and integration for sustainable design. A high-octane gasoline production from woody biomass feedstock is used as a case study to demonstrate the approach.

biomass↗
DOE OSTI2023

Integrated Electrocoagulation, Ultrafiltration, Membrane Distillation, and Crystallization for Treating Produced Water

Produced water (PW) generated from hydraulic fracturing operations was treated using an integrated electrocoagulation, ultrafiltration, membrane distillation, and crystallization process (EC UF MDC). The aim was to determine the viability of this integrated process for maximizing water recovery. The results obtained here indicate that optimizing the various unit operations could lead to increased recovery of PW. Membrane fouling limits all membrane separation processes. A pretreatment step to suppress fouling is essential. Here, removal of total suspended solids (TSS) and total organic carbon (TOC) was achieved by electrocoagulation (EC) followed by ultrafiltration (UF). The hydrophobic membrane used in membrane distillation may be fouled by dissolved organic compounds. Reducing membrane fouling is essential to increase the long-term durability of the membrane distillation (MD) system. In addition, combining membrane distillation with crystallization (MDC) can help reduce scale formation. By inducing crystallization in the feed tank, scale formation on the MD membrane was suppressed. The integrated EC UF MDC process can impact Water Resources/Oil & Gas Companies. Conservation of surface and groundwater is possible by treating and reusing PW. Additionally, treating PW reduces the amount of PW disposed in Class II disposal wells and promotes more environmentally sustainable operations.

42 ENGINEERING↗
DOE OSTI2026

Electrode and Microstructure Dependence of Oxygen Diffusion in Ferroelectric Hafnium Zirconium Oxide Thin Films

Hafnia-based ferroelectrics hold promise to reduce energy demand for computing by enabling compute-in-memory and as non-volatile memories. The ferroelectric phase in this material system is, in part, stabilized by oxygen vacancies. While oxygen vacancies may be a necessity for phase stability, they limit device endurance through diffusion and accumulation into conducting channels. Herein, it is shown that oxygen diffusion is spatially variable within individual grains of ferroelectric hafnium zirconium oxide (HZO). Using 18 O tracers and finite difference modeling, it is shown that grain boundaries and regions near electrode interfaces allow for relatively rapid oxygen diffusion, with values as much as 10 4 larger than the grain cores. Further, the selection of electrode material affects the diffusion coefficients across all microstructural regions. HZO films in contact with TiN electrodes result in more oxygen-deficient HZO films and higher oxygen diffusion coefficients. Tungsten electrodes result in fewer vacancies and lower diffusion coefficients. Diffusion activation energy differences between the HZO with the two electrodes is reconciled by differing populations of charged and uncharged oxygen vacancies. This insight into the local vacancy populations and diffusion pathways provides a platform for designing hafnia-based films, deposition processes, and integration strategies to reduce vacancy gradients and improve performance.

36 MATERIALS SCIENCE↗
DOE OSTI2023

High‐Loaded Electrode Filaments for Additive Manufacturing of Structural Batteries

Abstract The unique capability of 3D printing to create geometric complex structures presents a promising avenue for producing 3D electrodes aimed at enhancing power and energy densities within constrained spaces, which is challenging to achieve through traditional slurry casting methods. However, despite advancements over the years, 3D‐printed batteries have faced limitations in terms of mechanical robustness to endure significant volume changes during cycling and restricted electrochemical performance due to the lack of adequate electrode feedstock development or post‐processing treatments. Herein, a high‐loaded electrode filament with ≈65 wt.% fillers, enabling the fabrication of structural electrodes with improved electrochemical performance and superior mechanical properties, is developed. Through a combination of 3D printing and post‐processing techniques, interdigitated structures with high areal‐loading density, resulting in a full cell with an enhanced areal capacity of ≈12.28 mAh cm −2 at ≈0.92 mA cm −2 is fabricated. Moreover, the structural batteries, treated through the carbonizing process, are integrated by the carbon coating generated during carbonization, exhibiting remarkable compressive properties (with a modulus of 18.5 MPa and a strength of 1.09 MPa). Overall, the findings demonstrate the promising potential of 3D printed batteries for practical applications, while showcasing the scalability and design flexibility offered by 3D printing technology.

Chemistry↗
DOE OSTI2023

Manufacturing Water‐Based Low‐Tortuosity Electrodes for Fast‐Charge through Pattern Integrated Stamping

Achieving high energy density and fast charging of lithium‐ion batteries can accelerate the promotion of electric vehicles. However, the increased mass loading causes poor charge transfer, impedes the electrochemical reaction kinetics, and limits the battery charging rate. Herein, this work demonstrated a novel pattern integrated stamping process for creating channels in the electrode, which benefits ion transport and increases the rate performance of the electrode. Meanwhile, the pressure applied during the stamping process improved the contact between electrode and current collector and also enhanced the mechanical stability of the electrode. Compared to the conventional bar‐coated electrode with the same thickness of 155 μm (delivered a discharge capacity of 16 mAh g −1 at the rate of 3 C), the stamped low‐tortuosity LiFePO 4 electrode delivered 101 mAh g −1 capacity. Additionally, water was employed as a solvent in this study. Owing to its eco‐friendliness, high scalability, and minimal waste generation, this novel stamping technique inspire a new method for the industrial‐level efficient roll to roll fabrication of fast‐charge electrodes.

25 ENERGY STORAGE↗
DOE OSTI2023

Imaging the Future Threats of the Sand Dunes Along the Northwestern Coast of Nile Delta Using SAR

Although the Sand dunes screen the coastal cities from the sand dunes hazards and their infrastructures from rising sea levels and storms, they might threaten and hide the surrounding developmental projects. Thus, imaging these coastal dunes' internal anatomy and dynamics are crucial to protect the environment. In this study, the Optical and Synthetic Aperture Radar (SAR) images were processed and integrated with field observations and surveys to extract information about the past, current, and future behavior of coastal dunes in the Nile Delta-Northwest sector. A conventional change detection method using the supervised Landsat-8 images for the years 2015 and 2017 were generated to show a rapid change in the sand dune cover, where the high-resolution images of Google Earth were used to digitize the dune crests and measure its encroachment rate, which has been reached about 4 m/year with the NW–SE direction. The full-polarimetric ALOS/PALSAR-2 images from the years 2015 and 2017 show very low coherence for the sand dunes, which means these dunes are dynamic, where the changes in both power and phase imbalances of different dune fields during the investigated years (2015 and 2017) show high differences in values, which reached 40 dB and 0.06°, respectively. Finally, the extracted radar facies from the field survey show two successive groups of coastal sand dunes show a decline in the heavy minerals content to a level that might threaten the properties at the shoreline due to sea level rise and wave storms if mitigation actions are not taken place soon.

Ramadan, Rabab↗
DOE OSTI2024

Transverse polarization measurement of Λ hyperons in pNe collisions at $\sqrt{{\textrm{s}}_{\textrm{NN}}}$ = 68.4 GeV with the LHCb detector

A measurement of the transverse polarization of the Λ and $\bar{Λ}$ hyperons in p Ne fixed-target collisions at $\sqrt{{\textrm{s}}_{\textrm{NN}}}$ = 68.4 GeV is presented using data collected by the LHCb detector. The polarization is studied using the decay Λ → p $π$ − together with its charge conjugated process, the integrated values measured are $P_Λ = 0.029 ± 0.019$ (stat) $±$ $0.012$ (syst), $P_{\bar{Λ}} = 0.003 ± 0.023$ (stat) $±$ $0.014$ (syst). Furthermore, the results are shown as a function of the Feynman x variable, transverse momentum, pseudorapidity and rapidity of the hyperons, and are compared with previous measurements.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Emerging Technologies for Decarbonizing Silicon Production

Abstract Silicon (Si) is an important material for alloying, solar photovoltaics, and electronics. However, current methods of producing silicon require energy consumption of around 11–13 kWh/kg Si and direct carbon emissions are 4.7–5 tons CO 2 per ton Si which conflicts with global efforts to limit climate change. In this work, we discuss several promising methods for reducing or eliminating carbon emissions from the silicon production process. Such methods include using biocarbon, integrating the current process with carbon capture and utilization/storage (CCU/CCS), metallothermic reduction, hydrogen reduction, and molten salt electrolysis. We present the positive aspects and challenges of each approach. Biocarbon coupled with CCU/CCS is the most industrially mature technology and can be carbon–neutral or -negative but is not carbon-free. Hydrogen directly reducing silicon dioxide is not thermodynamically favorable, but it may be viable to use hydrogen in conjunction with other processes to reduce emissions. Metallothermic and electrochemical methods of production are promising and have the potential to create high-purity silicon with no reduction-related carbon emissions but have only been demonstrated at lab scale. Economic viability will likely be the next determining factor for which technologies are more widely researched and implemented. Graphical Abstract

08 HYDROGEN↗
DOE OSTI2022

Network Optimization of the Electrosynthesis of Chemicals from CO2

Carbon dioxide electroreduction (ECO2R) is gaining attention due to its capacity to mitigate CO2 emissions while using electricity that would otherwise be curtailed. Its foreseeable industrial implementation requires of holistic methods to assess the technological and economic performance of ECO2R processes and integrate them in current chemical supply chains and power systems. Here, we combine techno-economic assessment and mathematical programming to find the optimal paths to electroreduce CO2 into valuable chemicals under variable electricity prices. The proposed approach is tested with a case study addressing the CO2 capture from flue gas or direct air and its electricity-powered reduction into carbon monoxide, formic acid or multi-carbon compounds. The results obtained demonstrate the ability of the framework to build ECO2R networks and provide operation profiles that respond to fluctuating electricity prices.

carbon dioxide↗
DOE OSTI2020

Constrained Bayesian optimization of criticality experiments

The design of criticality experiments is typically an iterative process that employs a Monte Carlo transport code. The goal is to find a design that optimizes some variable, like the sensitivity of a response to a cross section, while simultaneously ensuring criticality. The high fidelity of the Monte Carlo code is a great asset, but it makes exploring the design space computationally expensive. Herein, we present how a constrained Bayesian optimization algorithm can be used to efficiently design a criticality experiment. It uses Gaussian processes as a surrogate model to probe the design space and to reduce the number of code executions that are needed to find the optimum. Furthermore, we demonstrate constrained Bayesian optimization with a Pu-239/polyethylene solution system and a TEX experiment that is designed for criticality safety validation of a nuclear waste model at the Hanford Site. For both systems, a global optimum was found within 75 Monte Carlo simulations.

42 ENGINEERING↗
DOE OSTI2023

Adaptive cold-load pickup considerations in 2-stage microgrid unit commitment for enhancing microgrid resilience

In an extended main grid outage spanning multiple days, load shedding serves as a critical mechanism for islanded microgrids to maintain essential power and energy reserves that are indispensable for fulfilling reliability and resiliency mandates. However, using load shedding for such purposes leads to increasing occurrence of cold load pickup (CLPU) events. Here, this study presents an innovative adaptive CLPU model that introduces a method for determining and incorporating parameters related to CLPU power and energy requirements into a two-stage microgrid unit commitment (MGUC) algorithm. In contrast to the traditional fixed-CLPU-curve approach, this model calculates CLPU duration, power, and energy demands by considering outage durations and ambient temperature variations within the MGUC process. By integrating the adaptive CLPU model into the MGUC problem formulation, it allows for the optimal allocation of energy resources throughout the entire scheduling horizon to fulfill the CLPU requirements when scheduling multiple CLPU events. The performance of the enhanced MGUC algorithm considering CLPU needs is assessed using actual load and photovoltaic (PV) data. Simulation results demonstrate significant improvements in dispatch optimality evaluated by the amount of load served, customer comfort, energy storage operation, and adherence to energy schedules. These enhancements collectively contribute to reliable and resilient microgrid operation.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Mechanochemical synthesis of hydraulically reactive calcium silicate minerals via thermally-assisted mechanical grinding

This study explores a thermally assisted mechanochemical approach alternative to conventional cement synthesis as a potential to produce hydraulically reactive calcium silicate phases. Ball milling of mixed CaO/SiO 2 feedstocks at temperature ranges 100-300 °C increases the formation of the Ca-O-Si bonds and precursor reactivity. Spectroscopic analyses (FTIR, MAS-NMR, UV-Vis DRS) indicate increasing amorphization with milling temperature, attributed to improved mixing and thermally assisted diffusion. Upon hydration, all treated samples exhibit exothermic heat release, with the sample prepared at 300 °C showing the most pronounced reactivity. Thermal analysis reveals weight loss consistent with C-S-H formation, confirming cement-like behavior. In summary, moderate thermal input during milling promotes structural activation and enhances downstream hydraulic reactivity, providing a proof-of-concept for energy-reduced cement precursor processing.

Alite↗
DOE OSTI2026

Crop models: integrating systems from the molecular to global for agricultural productivity and sustainability

Mathematical models that simulate crop growth in response to environmental conditions and management practices are essential tools for exploring agriculture-based strategies to address food security and environmental sustainability challenges. Early applications of crop models focused on supporting farmers in making management decisions. Applications have since expanded to estimating future impacts on local and global food production from changing climates. Emerging applications of crop models aim to leverage how these models integrate plant processes across biological scales to identify engineering or breeding strategies that account for environmentally-responsive dynamics at field scales and for exploring solutions to improve sustainability. In this review, we highlight recent studies across these four broad application areas and highlight potential future directions for the crop modeling field.

Piao, Ximin [Univ. of Illinois at Urbana-Champaign↗
DOE OSTI2024

Fabrication of yeast engineered porous 13X adsorbent layers for CO 2 capture

This study investigates a novel environmentally friendly coating technique using yeast fermentation to obtain super porous Zeolite 13X adsorbent layers through freeze-drying technique for CO 2 capture applications. Several mass ratios of sugar to yeast were used to control the porosity and pore sizes in the adsorbent layer. A unique peeling process was integrated to obtain foamy, hollow structures to have deeper layer accessibility of adsorbent for adsorption applications. These coated adsorbent layers were experimentally characterized as a function of the mass ratio of sugar to yeast and adsorbent solid fraction. Scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDS), and Fourier-transform infrared spectroscopy (FT-IR) are used to analyze the coated layers. Here, the void fraction for coated samples is found to vary between 0.48 and 0.56, making the samples applicable for adsorption applications. Adsorption performance experiments are performed to test the coated samples' performance compared to 13X powder. Due to their simplistic fabrication, cost-effectiveness, rapid pore formation, and high adsorption capacity, these porous 13X layers hold potential for large-scale fabrication and CO 2 capture applications.

Adsorbent coating↗
DOE OSTI2026

A hybrid Penman-Monteith and machine learning model for simulating evapotranspiration and its components

Integrating physical processes with machine learning has advanced evapotranspiration (ET) simulation, yet most hybrid models fail to partition total ET into its components: soil evaporation (E) and vegetation transpiration (T). This study introduces Residual Neural Network–Penman–Monteith (RNN-PM), a novel hybrid dual-source ET model designed to overcome this limitation. The model synergizes the physically-based Penman–Monteith framework with three specialized residual neural networks trained to estimate key conductance parameters (canopy conductance, soil surface conductance, and aerodynamic conductance). Furthermore this explicit parameterization allows for the direct partitioning of total ET. Validation at National Ecological Observatory Network (NEON) flux sites using high-frequency partitioned E and T shows that RNN-PM reliably reproduces ET and the transpiration fraction (T/ET). For ET, the model achieves an average Kling–Gupta efficiency (KGE) of 0.89 and a root-mean-square error (RMSE) of 0.55 mm/day; for T/ET, the KGE is 0.87 with an RMSE of 0.06. Furthermore, RNN-PM demonstrates robust generalization, accurately simulating ET and its components well beyond the initial training dataset, even under extreme climatic conditions. This study extended the analysis by comparing the RNN-PM model with seven established dual-source ET models. The results indicate that RNN-PM outperforms both conventional machine learning models and purely physical process-based models in simulating ET components in most cases. Among the purely physical process-based dual-source models, those based on surface temperature decomposition showed improved performance as the leaf area index (LAI) decreased when evaluated against high-frequency ET component datasets. In contrast, the performance of conductance-based dual-source models declined with decreasing LAI. Although purely machine learning-based models can produce relatively accurate simulations of ET components, they often exhibit limited generalization capability, an issue that the RNN-PM model effectively overcomes. Ultimately, the RNN-PM model represents a significant advance in simulating ET components, offering a novel and scalable approach for improving the representation of land–atmosphere interactions in Earth system models.

54 ENVIRONMENTAL SCIENCES↗