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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 667 records · Page 37
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Electrical and Spectroscopic Diagnostics as Real‐Time Metallization Indicators During Hydrogen Plasma Smelting Reduction

This study investigates the hydrogen (H 2 ) plasma reduction process of direct-reduced-iron-grade hematite ore at different arc currents (100–200 A) in an Ar–5% H 2 atmosphere at 0.9 bar. Iron ore samples (10 g) were exposed to a plasma arc, and the reduction/metallization kinetics were analyzed over fixed time intervals. Electrical diagnostics revealed that the arc voltage exhibited takeover-mode oscillations which were suppressed at higher currents due to stronger electromagnetic coupling. The voltage dropped significantly as metallization approached ∼95%, linked to increased electrical conductivity of the metallic iron (Fe) in the ore as well as Fe evaporation into the arc, lowering the arc resistance. A simplified Elenbaas–Heller model supported this explanation and confirmed that Fe vapor concentration enhances plasma conductivity. Optical emission spectroscopy focused on the plasma–metal interface revealed the plasma's optically thick nature, as the primary Fe I 526.95 nm line experienced self-absorption. However, weaker Fe I lines (404.58, 438.35 nm) normalized to Ar I 696.5 nm provided a reliable proxy for metallization. These diagnostics, electrical and spectroscopic, effectively track metallization in real-time during H 2 plasma smelting reduction.

08 HYDROGEN↗
DOE OSTI2024

Perspective on Lignin Conversion Strategies That Enable Next Generation Biorefineries

The valorization of lignin, a currently underutilized component of lignocellulosic biomass, has attracted attention to promote a stable and circular bioeconomy. Successful approaches including thermochemical, biological, and catalytic lignin depolymerization have been demonstrated, enabling opportunities for lignino-refineries and lignocellulosic biorefineries. Although significant progress in lignin valorization has been made, this review describes unexplored opportunities in chemical and biological routes for lignin depolymerization and thereby contributes to economically and environmentally sustainable lignin-utilizing biorefineries. This review also highlights the integration of chemical and biological lignin depolymerization and identifies research gaps while also recommending future directions for scaling processes to establish a lignino-chemical industry.

09 BIOMASS FUELS↗
DOE OSTI2020

Electrowetting‐Mediated Transport to Produce Electrochemical Transistor Action in Nanopore Electrode Arrays

Abstract Understanding water behavior in confined volumes is important in applications ranging from water purification to healthcare devices. Especially relevant are wetting and dewetting phenomena which can be switched by external stimuli, such as light and electric fields. Here, these behaviors are exploited for electrochemical processing by voltage‐directed ion transport in nanochannels contained within nanopore arrays in which each nanopore presents three electrodes. The top and middle electrodes (TE and ME) are in direct contact with the nanopore volume, but the bottom electrode (BE) is buried beneath a 70 nm silicon nitride (SiN x ) insulating layer. Electrochemical transistor operation is realized when small, defect‐mediated channels are opened in the SiN x . These defect channels exhibit voltage‐driven wetting that mediates the mass transport of redox species to/from the BE. When BE is held at a potential maintaining the defect channels in the wetted state, setting the potential of ME at either positive or negative overpotential results in strong electrochemical rectification with rectification factors up to 440. By directing the voltage‐induced electrowetting of defect channels, these three‐electrode nanopore structures can achieve precise gating and ion/molecule separation, and, as such, may be useful for applications such as water purification and drug delivery.

Kwon, Seung‐Ryong↗
DOE OSTI2019

Microstructure and Properties of Inconel 718 Fabricated by Directed Energy Deposition with In-Situ Ultrasonic Impact Peening

Many inherent issues, such as the detrimental residual stress, columnar grains with anisotropy, and weak mechanical properties, have severely impeded the adoption of metal additive manufacturing (AM) techniques including powder bed fusion and directed energy deposition (DED) processes. In this study, a hybrid AM process that consists of layer-wise laser metal deposition (i.e., a DED process) and in-situ ultrasonic impact peening (UIP) was applied to obtain Inconel 718 superalloy workpieces. Also, for further property enhancement, a post-heat treatment was applied to the deposited material obtained by the hybrid AM process. Scanning electron microscopy and transmission electron microscope were used to investigate the microstructure morphology and reveal the underlying strengthening mechanism. Electron backscatter diffraction was employed to quantitatively study the microstructure resulted from the hybrid AM process and the post-heat treatment. The profile of residual stress along the depth direction was obtained through X-ray diffraction. The results demonstrate that this hybrid AM process is capable of producing high-quality metal parts with significantly refined microstructure, and beneficial compressive residual stress along the depth into surface. Severe plastic strains are introduced by UIP, and the resulted mechanical twinning and dynamic recrystallization play an important role in refining microstructure. The material microstructure is further refined down to 100 µm, and the texture anisotropy is significantly diminished after solution treatment at 980 °C for 1 hour. Under the as-built condition, in-situ ultrasonic peening alters the residual stress component from a tensile state to an overall compressive state with a maximum value of − 190 MPa within the range of measurement depth.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Best of both worlds: Enforcing detailed balance in machine learning models of transition rates

The slow microstructural evolution of materials often plays a key role in determining material properties. When the unit steps of the evolution process are slow, direct simulation approaches such as molecular dynamics become prohibitive and Kinetic Monte-Carlo (kMC) algorithms, where the state-to-state evolution of the system is represented in terms of a continuous-time Markov chain, are instead frequently relied upon to efficiently predict long-time evolution. The accuracy of kMC simulations however relies on the complete and accurate knowledge of reaction pathways and corresponding kinetics. This requirement becomes extremely stringent in complex systems such as concentrated alloys where the astronomical number of local atomic configurations makes the a priori tabulation of all possible transitions impractical. Machine learning models of transition kinetics have been used to mitigate this problem by enabling the efficient on-the-fly prediction of kinetic parameters. While conventional KMC methods based on transition state theory naturally yield reversible dynamics that exactly obey the detailed balance criterion, providing strong guarantees on the properties of the stationary distribution, many recently-proposed ML-based approaches to barrier predictions provide no such guarantees. In this study, we derive conditions under which physics-informed ML architectures exactly enforce the detailed balance condition by construction, even when relying on non-extensive descriptions of states in terms of local environments around mobile defects. In conclusion, using the diffusion of a vacancy in a concentrated alloy as an example, we show that such ML architectures also exhibit superior performance in terms of prediction accuracy, demonstrating that the imposition of physical constraints can facilitate the accurate learning of barriers at no increase in computational cost.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Influence of cementation on the yield surface of rocks numerically determined from digital microstructures

Digital Rock Physics has reached a level of maturity on the characterisation of primary properties that depend on the microstructure – such as porosity, permeability or elastic moduli – by numerically solving field equations on μCT scan images of rock. After small deformations or at depth though, most rocks eventually reach their limit of elasticity and the complementary plastic properties are needed to describe the full mechanical behaviour. Currently, determination of a rock’s yield surface from its microstructure is often restricted to semi-analytical criteria derived by limit analysis or numerical simulations performed on idealised geometries. Such simplification lacks representativeness, particularly for processes that affect directly the pore-grain interface such as the cementation phenomenon, happening during diagenesis. Eventually, only direct numerical simulation of elasto-plasticity performed on digitalised microstructures can be used to assess the strength of different cemented materials and its evolution with the alteration of the microstructure. In this study, we provide a comprehensive parametric study on the impact of cementation on rock strength for real microstructures of cemented granular materials. Compared to most previous studies, the whole yield surface is determined numerically (using Finite Element Method) in order to assess the influence of cementation for different stress-paths. The previously known tendency of rock to strengthen with increasing cementation volume is verified. New results on the influence of cement property namely Young’s modulus, friction and cohesion on the rock’s yield surface are explored. The envelopes obtained are compared to the ones obtained by experimental data and existing models. Finally, the framework presented in this study showcases the wider possibility of determining any rock’s or porous material’s yield surface from its microstructure.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Thermochemical processes for CO 2 hydrogenation to fuels and chemicals: Challenges and opportunities

This manuscript discusses the potential use of CO 2 as a carbon and oxygen carrier to return it to the carbon life cycle in the form of fuels or chemicals via thermochemical catalytic pathways. Theoretically, CO 2 hydrogenation can form a variety of fuels and chemicals. Practically, however, the selectivity, conversion, operating range, and kinetic limitations and operational cost determine the end product. Because of their high value and versatility as a chemical or fuel, small olefins (i.e., C 2 H 4 ) and methanol are often considered as target species. Whether alcohol or olefin formation, CH 4 and CO are the nature’s primary choices of CO 2 conversion. They can be formed over a wide operating temperature, pressure, and CO 2 :H 2 ratios. They are often competitive carbon species in olefin or methanol formation steps. Although they are less valuable as end products, they can be used as intermediate species. Secondary processes of CO and CH 4 to form chemicals and fuels can increase the overall CO 2 hydrogenation yield. Independent of the choice of end product, CO 2 hydrogenation requires hydrogen. Pure hydrogen derived mostly from fossil fuels adds to the overall process cost and also increases the CO 2 emissions. Hydrogen produced from water electrolysis is a renewable green pathway but is limited by the process efficiency and cost. As an alternative to pure hydrogen, low-value, small chain paraffins are suggested as the hydrogen carriers. Carbon dioxide–assisted oxidative dehydrogenation of paraffins to olefins process is a direct pathway to olefin formation. The paper discusses these potential pathways for CO 2 utilization based on theoretical analysis and recent advances in academia and industry.

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

Characterization of flow and transport in a fracture network at the EGS Collab field experiment through stochastic modeling of tracer recovery

Energy extraction from subsurface reservoirs is important for addressing the increasing energy demand and environmental concerns such as global warming. However, the characterization of subsurface reservoirs, particularly reservoirs dominated by fracture networks remains a challenge due to the lack of means to directly observe subsurface processes. This study explores the feasibility and efficacy of characterizing fracture flow and transport processes in an enhanced geothermal system (EGS) testbed through stochastic tracer modeling. There are two enabling factors that allow application of stochastic modeling to characterize a subsurface reservoir. First, an abundance of geological and geophysical measurements enables the development of a high-fidelity and well-constrained fracture network model. Second, high-performance computing (HPC) allows running massive realizations efficiently. Six conservative tracer tests were stochastically modeled and produced satisfactory realizations that successfully reproduce field tracer recovery data from each tracer test. The evolution of flow and transport processes in the fracture network was then analyzed from these satisfactory realizations. This work demonstrates that stochastic tracer modeling on a high-fidelity fracture network model is feasible and can provide important insights regarding flow and transport characteristics in subsurface fractured reservoirs.

58 GEOSCIENCES↗
DOE OSTI2021

Development of high-performance roll-to-roll-coated gas-diffusion-electrode-based fuel cells

This study focuses on determining fabrication conditions to create high-performance roll-to-roll-coated (R2R-coated) gas-diffusion electrodes (GDEs) for proton-exchange-membrane fuel cells (PEMFCs). Here, we examine how process conditions influence the distribution of ionomer in the electrode, which is shown to be critical for high performance. Using a combination of Kelvin probe, X-ray photoelectron spectroscopy, and nano-scale X-ray computed tomography we show that formation of an ionomer-rich surface is promoted by using a higher drying rate. We show that R2R-coated GDEs have higher surface ionomer concentration than spray-coated GDEs, which enables these R2R-coated GDEs to not need an additional ionomer overlayer, as is typically the case for spray-coated GDEs. This will reduce the number of processing steps and lower material costs in a manufacturing setting. This work shows that with the appropriate selection of materials, ink formulation, and processing conditions, direct-coated GDEs are a viable pathway for fuel cell manufacturing.

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

Improving understanding of NpO 2 and Np 2 O 5 through vibrational spectroscopy

Raman spectra of three NpO 2 samples and two samples produced from a modified direct denitration (MDD) process were collected. The spectral features of the NpO 2 samples were consistent and indicated only NpO 2 . The spectra of the MDD samples indicated the presence of NpO 2 and an additional phase attributed to the neptunium binary oxide Np 2 O 5 . These Raman spectra are the first reported of Np 2 O 5 , and the proportions of these neptunium oxide phases varied within the samples, suggesting significant sample inhomogeneity. Peaks in the Raman spectra of Np 2 O 5 at 569 and 782 cm –1 were tentatively assigned to concerted, symmetric stretches of the neptunyl cations. Finally, laser-induced heating of regions in the MDD samples that were rich in Np 2 O 5 showed spectral features that indicated conversion to NpO 2 .

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

GenAI4UQ: A software for forward and inverse uncertainty quantification using conditional generative AI

We introduce GenAI4UQ, a software package for forward and inverse uncertainty quantification in model calibration, parameter estimation, and ensemble forecasting. GenAI4UQ leverages a generative AI-based conditional modeling framework to address limitations of traditional inverse modeling techniques, such as Markov Chain Monte Carlo (MCMC) methods. By replacing computationally intensive iterative processes with a direct, learned mapping, GenAI4UQ enables efficient calibration of input parameters and generation of predictions directly from observations. The software supports rapid ensemble forecasting with robust uncertainty quantification while maintaining computational and storage efficiency. Built-in auto-tuning of hyperparameters simplifies model training, ensuring accessibility for users with varying expertise. Its versatile conditional generative framework is applicable across diverse scientific domains. While GenAI4UQ offers significant advantages in flexibility and efficiency, users should interpret its uncertainty estimates with caution in data-sparse scenarios, as the model may overestimate uncertainty—an effect common to all surrogate-based approaches including MCMC with surrogate models. Despite this, GenAI4UQ transforms inverse modeling by providing a fast, reliable, and user-friendly solution. It empowers researchers and practitioners to quickly estimate parameter distributions and generate model predictions for new observations, facilitating efficient decision-making and advancing the state of uncertainty quantification in computational modeling.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Burkholderia : An Untapped but Promising Bacterial Genus for the Conversion of Aromatic Compounds

Burkholderia , a bacterial genus containing greater than 120 species, is typically reported to inhabit soil and water environments. These Gram-negative bacteria are known to harbor a variety of aromatic catabolic pathways and are thus potential organisms for the bioremediation of sites contaminated with aromatic pollutants. However, there are still substantial knowledge gaps in these catabolic processes that must be elucidated before harnessing these pathways and organisms for biotechnological applications. This review presents recent discoveries on the catabolism of monoaromatic and polycyclic aromatic hydrocarbons as well as heterocyclic compounds by a diversity of Burkholderia strains. We emphasize the advantageous features of Burkholderia for bioremediation processes. Furthermore, future directions for its utilization in bioconversion and upgrading of aromatic compounds are also presented.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Bridge-Mediated Metal-to-Metal Electron and Hole Transfer in a Supermolecular Dinuclear Complex: A Computational Study Using Quantum Electron–Nuclear Dynamics

Bimetallic electron donor–acceptor complexes can facilitate electron and energy transfer with excellent structural control through synthetic design. In this work, we investigate the photochemical dynamics in a Ru–Cu bimetallic complex after photoexcitation of the Ru-centered charge transfer state. The physical underpinnings of the metal-to-metal directional charge transfer process are unraveled via analyses of the quantum electronic dynamics and electron–nuclear trajectories. Here, the effects of molecular vibrations in the photoexcited state on the charge transfer processes are also analyzed.

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

Molecular Insight into the Effects of Clustering on the Dynamics of Ionomers in Solutions

Ionizable groups tethered to polymers enable their many current and potential applications. However, these functionalities drive the formation of physical networks through clustering of the ionic groups, resulting in constrained dynamics of the macromolecules. Understanding the molecular origin of this hindrance remains a critical fundamental question, whose solution will directly impact the processing of ionizable polymers from molecules to viable materials. Here, in this work, using quasielastic neutron scattering accompanied by molecular dynamics simulations, segmental dynamics of slightly sulfonated polystyrene is studied in solutions as the cohesion of the ionic assemblies is tuned. We find that in cyclohexane the ionic assemblies act as centers of confinement, affecting dynamics both on macroscopic lengths and in the vicinity of the ionic assemblies. Addition of a small amount of ethanol affects the packing of the ionizable groups within the assemblies, which in turn enhances the chain dynamics.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Molecular Weight Dependence of Block Copolymer Micelle Fragmentation Kinetics

The effect of molecular weight (M) on the fragmentation kinetics of micelles formed by 1,2-polybutadiene-block-poly(ethylene oxide) (PB-PEO) copolymers was studied in the ionic liquid 1-ethyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide. A series of six samples, with total M ranging from 10 4 to 10 5 g mol –1 and nearly constant composition (f PEO ≈ 0.4), were examined; all six formed spherical micelles with PEO coronas. Nonequilibrium PB-PEO micelles were prepared by direct dissolution, a process that systematically produces nanoparticles with mean aggregation numbers more than twice the equilibrium values. When subjected to high temperature annealing (170 °C), the average micelle radius was found to decrease substantially, as determined by temperature-jump dynamic light scattering (T-jump DLS) and time-resolved small-angle X-ray scattering (TR-SAXS). Furthermore, the characteristic fragmentation times (τ) were found to increase strongly with increasing degree of polymerization N, as τ ~ N 1.8 . This result compares favorably with the prediction of a previously untested model.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2023

Biodiversity and Stoichiometric Plasticity Increase Pico‐Phytoplankton Contributions to Marine Net Primary Productivity and the Biological Pump

Earth System Models generally predict increasing upper ocean stratification from 21st century warming, which will cause a decrease in the vertical nutrient flux forcing declines in marine net primary productivity (NPP) and carbon export. Recent advances in quantifying marine ecosystem carbon to nutrient stoichiometry have identified large latitudinal and biome variability, with low-latitude oligotrophic systems harboring pico-sized phytoplankton exhibiting large phosphorus to carbon cellular plasticity. The climate forced changes in nutrient flux stoichiometry and phytoplankton community composition are thus likely to alter the ocean's biogeochemical response and feedback with the carbon-climate system. We have added three pico-phytoplankton functional types within the Biogeochemical Elemental Cycling component of the Community Earth System Model while incorporating variable cellular phosphorus to carbon stoichiometry for all represented phytoplankton types. The model simulates Prochlorococcus and Synechococcus populations that dominate the productivity and sinking carbon export of the tropical and subtropical ocean, and pico-eukaryote populations that contribute significantly to productivity and export within the subtropical to mid-latitude transition zone, with the western subtropical regions of each basin supporting the most P-poor stoichiometries. Subtropical gyre recirculation regions along the poleward flanks of surface western boundary currents are identified as regional hotspots of enhanced carbon export exhibiting C-rich/P-poor stoichiometry, preferentially inhabited by pico-eukaryotes and diatoms. Collectively, pico-phytoplankton contribute ∼58% of global NPP and ∼46% of global particulate organic carbon export below 100 m through direct and ecosystem processing pathways. Biodiversity and cellular nutrient plasticity in marine pico-phytoplankton combine to increase their contributions to ocean productivity and the biological carbon pump.

Environmental Sciences & Ecology↗
DOE OSTI2023

Basics of the scanning electrochemical microscope and its application in the characterization of lithium-ion batteries: a brief review

A scanning electrochemical microscope (SECM) can directly monitor electrochemical processes at interfaces of electrodes and electrolytes and has been used as an analytical tool for lithium-ion battery (LIB) studies. Through SECM, we can visualize the electrochemical reactivities of active species in LIBs in-situ during cycling. This review begins with introducing SECM-based LIB research and then summarizes the working mechanism and operating modes of the technique as well as combinations of SECM with other techniques for LIB studies. We review the results with a focus on the interfacial properties, surface reactions and electrochemical activity of different electrode materials for LIBs. The investigations of battery degradation, kinetic parameters and electrolyte swelling by SECM are also discussed. Finally, the current limitations and perspectives are also described regarding future developments.

25 ENERGY STORAGE↗