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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Sulfonated Aromatic Polypentenamers: Scope of the Acetyl Sulfate Reaction

A precision polymer featuring one phenyl pendant at every fifth carbon on a polyethylene backbone was modified to varying degrees of sulfonation (DS = 33–98%) using acetyl sulfate with standard conditions by varying reaction times (up to 48 h). This soft, homogeneous method allows for evenly distributed phenylsulfonic acid groups with minimal side reactions and results in light brown, transparent materials with glass transition temperatures of 33–78 °C that increase with DS and parent polymer molar mass. The DS was accurately determined through well-resolved 1 H NMR (DSHNMR) signals of the regularly spaced phenyl groups and corroborated by inverse-gated decoupling 13 C NMR analysis. These analyses were compared to a series of other commonly accepted methods for DS determination including titration and elemental analysis (EA). The DS by titration (DS titr ) also increased with reaction time but was consistently lower than those determined by NMR. Significant discrepancies between theoretical and measured sulfur mass were observed for several samples through EA. Qualitative methods, such as infrared spectroscopy and thermal analyses, were also performed and correlated well with the DS determined by NMR. Here, this study presents a promising method to achieve a complete scope of homogeneous sulfonation from mild reaction conditions and presents a case to determine DS through multiple methods, with spectroscopic analyses, such as NMR, being potentially the most valuable.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Sequence-Structure–Property Relationships in Short-Chain Polyesters: How Primary Structure Governs Macroscopic Performance

While polymer properties are fundamentally linked to their nanostructure, the influence of monomer sequence remains less understood than stereochemical factors like tacticity. This study examines how sequence distribution affects the thermal behavior and morphology of homo- and copolyesters, specifically comparing polymers derived from constitutionally identical monomers but with varying degrees of sequence regularity depending on monomer structure or polymerization selectivity. Our findings show that increasing sequence defects progressively diminish thermal stability, crystallinity, melting temperatures, and morphological order. As new materials become more compositionally complex, this work underscores the importance of sequence control in the design of advanced polymers for emerging applications.

Bocharova, Vera [Oak Ridge National Laboratory (OR↗
DOE OSTI2024

Magnetic Solitons in Hierarchical 3D Magnetic Nanoarchitectures of Nanoflower Shape

Curvilinear magnetism emerged as a new route to tailor properties of magnetic solitons by the choice of geometry and topology of a magnetic architecture. Here, we develop an anodized aluminum oxide template-based approach to realize hierarchical 3D magnetic nanoarchitectures of nanoflower shape. The technique provides defect-free regular arrays of magnetic nanoflowers of tunable shape with a period of 400 nm over cm 2 areas. We combined advanced magnetic imaging methods with micromagnetic simulations to study complex magnetic states in nanoflowers originating due to magnetostatics-driven symmetry break in curvilinear nanomembranes. An interaction between surface and volume magnetostatic charges in 3D curved nanoflowers leads to the stabilization of asymmetric and shifted vortices as well as states with two Bloch lines. Ordered large area arrays of complex-shaped magnetic nanoarchitectures developed in this work are relevant for prospective research on 3D magnonics and spintronics.

3D nanoarchitectures↗
DOE OSTI2025

Observation of Vortex Stripes in UTe 2

In conventional type-II superconductors, quantum vortices determine the magnetic response of the system and tend to form regular lattices. UTe 2 is a recently discovered heavy Fermion superconductor exhibiting many anomalous macroscopic behaviors, but whether it has a multicomponent order parameter remains open. Here, in this work, we study the vortices of UTe 2 by employing scanning superconducting quantum interference device microscopy. While a small out-of-plane magnetic field produces typical isolated vortices, a higher field generates vortex stripe patterns that evolve with the vortex density. The stripes form at different locations and along different directions in the surface plane when the field is along the b or c axis. The behavior is reproduced by our simulation based on an anisotropic two-component order parameter. This study shows that UTe 2 has a nontrivial disparity of multiple length scales, placing constraints on the multicomponent superconductivity.

UTe2↗
DOE OSTI2025

Self-Supported Branched Poly(ethylenimine) Monoliths from Inverse Template 3D Printing for Direct Air Capture

3D-printed inverse templates are combined with ice templating to develop self-supported branched poly(ethylenimine) monoliths with regular channels of varying channel density and ordered macropores. A maximum uptake of 0.96 mmol of CO 2 /g of monolith from ambient air containing 45.5% RH is achieved from dynamic breakthrough experiments, which is a 31% increase compared to the CO 2 uptake from adsorption under dry conditions for the same duration. The breakthrough experiments show characteristics of internal mass-transfer limitations. The cyclic dynamic breakthrough experiments indicate stable operation without significant loss in CO 2 uptake across eight cycles. Moreover, the self-supported monolith shows minimal loss in adsorption capacity (7.7%) upon exposure to air containing 21% oxygen at 110 °C, in comparison to a conventional sorbent consisting of poly(ethylenimine) impregnated on Al 2 O 3 (18.9%). The monoliths exhibit good mechanical stability, contributed by elastic deformation, corresponding to up to 74% strain and lower pressure drop compared to many existing monoliths in the literature.

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

Structural Effects on Solubility and Crystallinity in Polyamide Ionomers

Although polyamides have been an industrial staple for decades, their solubility and processability remain limited due to the strong hydrogen bonding between amide groups. Here, we report a family of polyamides in which aryl rings, alkyl spacers, sulfonate groups, and amide linkages are regularly spaced along the polymer backbone, allowing us to probe the structural elements that affect processability. We accessed these polymers through a synthetic route based on an expanded diamine monomer and characterized them through a range of physical and spectroscopic techniques. Our results show that the combination of sulfonate groups with increased amide content results in highly soluble polymers, which can dissolve in polar solvents such as water, methanol, and N,N-dimethylformamide. Infrared spectroscopy on the solid polymers shows that the aliphatic amides engage in hydrogen bonding with the sulfonate groups, thus inhibiting ion aggregation, crystallization, and microphase separation. These findings expand the avenue to sulfonate-containing polyamide chemistry and provide design rules for the synthesis of more processable ionic polyamides.

amides↗
DOE OSTI2026

Miscibility and Cocrystallization in Ethylene–Vinyl Alcohol Copolymer Blends

The compatibility among different ethylene−vinyl alcohol (EVOH) copolymer grades plays a crucial role in determining how easily they can be recycled when present together in a mixed waste stream. In this work, melt miscibility and cocrystallization in 50/50 wt/wt binary blends of EVOH copolymers with differing ethylene content were studied. Blends with up to a 21 mol % difference in composition were analyzed. Thin films of miscible blends appeared homogeneous in the melt as observed under an optical microscope, whereas AFM height images showed that immiscible blends underwent surface roughening due to phase separation. For copolymers with modest composition differences, the blend behaved as a single component, showing single, narrow melting and crystallization peaks in DSC thermograms, indicating cocrystallization at the level of crystal stems. Interestingly, even phase-separated blends demonstrated partial cocrystallization due to partial miscibility of the components in the molten phase-separated domains. The extent of cocrystallization is governed by the difference in freezing points of the components; rapid cooling increased cocrystallization in the blends. The maximum compositional difference allowed for miscibility is not constant but depends on the blend’s average comonomer content, in agreement with the “miscibility window” calculated from literature pressure−volume−temperature behavior for the individual EVOH copolymers and regular mixing theory. This study helps illuminate the effect of copolymer composition on miscibility, as well as cocrystallization behavior in blends of random copolymers with cocrystallizable units.

Cocrystallization↗
DOE OSTI2025

Degrees of Rate Control in Interconnected Reaction Networks

Overall reactions in interconnected networks exhibit net, forward, and reverse rates that are governed by both constitutive elementary steps in the pathway of interest and branching elementary steps that lead to alternative products. Accordingly, steps in branching pathways exhibit negative net, forward, and reverse degrees of rate control, as they reduce reaction flux to the desired product. We here contextualize the forward and reverse degrees of rate control in terms of kinetic resistances (inverse of rates) and leverage the additive nature of kinetic resistance to decouple kinetic driving forces contributed by constitutive elementary steps and branching points (nodal species) in interconnected networks. Regardless of the network connectivity, forward and reverse degrees of rate control are shown to converge at equilibrium. Away from equilibrium, we identify two critical features of interconnected networks: stoichiometric regularity─condition where all stoichiometric numbers are unity─and pathway symmetry around nodal species─condition where branching pathways share the same rate constants, stoichiometry, and species concentrations/activities─that result in (i) equal forward, reverse, and consequently net degrees of rate control and (ii) forward and reverse degrees of rate control that exhibit constant offsets, respectively, across all extents of reaction. Furthermore, our discourse further provides a mathematical description for the influence of stoichiometric irregularity and pathway asymmetry on forward and reverse degrees of rate control. Altogether, the presented work details the effects of network (inter)connectivity and stoichiometry on reaction kinetics and, in doing so, establishes general protocols for capturing these effects as additive terms in the formulation of forward and reverse degrees of rate control.

10 SYNTHETIC FUELS↗
DOE OSTI2025

Unraveling Adsorbate-Induced Structural Evolution of Iron Carbide Nanoparticles

Iron carbide (Fe x C y ) nanoparticles (NPs) are promising candidates for replacing platinum group metals in industrial applications, such as high-temperature Fischer–Tropsch synthesis. However, due to their amorphous nature, characterization of the active sites has been challenging experimentally and computationally. Here, using a combined density functional theory (DFT), neural network interatomic potential-assisted global optimization, and ensemble learning study, we evaluate dynamic surface changes associated with syngas (H and CO) interactions. For this purpose, we have developed a general procedure that we use to model an experimentally relevant 270-atom Fe 182 C 88 NP using the neural network-assisted stochastic surface walk global optimization algorithm (SSW-NN). Once generated, the Fe 182 C 88 NP active sites and particle morphology are thoroughly characterized before the effects of syngas adsorbate interactions are explored by using DFT and molecular dynamics simulations. Lastly, we explore correlations between geometric and electronic features of the active sites and the adsorption of H (H ads ), using a regularized random forest machine learning algorithm. In doing so, we identified the Fe–C coordination number and p orbital occupancy as the most important descriptors affecting H ads . Furthermore, using a combined ML and quantum chemistry approach, our work demonstrates a general and efficient procedure for generating and probing complex surface phenomena on binary nanoparticles.

Adsorption↗
DOE OSTI2024

Ligand Controls Excited Charge Carrier Dynamics in Metal-Rich CdSe Quantum Dots: Computational Insights

Small metal-rich semiconducting quantum dots (QDs) are promising for solid-state lighting and single-photon emission due to their highly tunable yet narrow emission line widths. Nonetheless, the anionic ligands commonly employed to passivate these QDs exert a substantial influence on the optoelectronic characteristics, primarily owing to strong electron–phonon interactions. In this work, we combine time-domain density functional theory and nonadiabatic molecular dynamics to investigate the excited charge carrier dynamics of Cd 28 Se 17 X 22 QDs (X = HCOO – , OH – , Cl – , and SH – ) at ambient conditions. These chemically distinct but regularly used molecular groups influence the dynamic surface-ligand interfacial interactions in Cd-rich QDs, drastically modifying their vibrational characteristics. The strong electron–phonon coupling leads to substantial transient variations at the band edge states. The strength of these interactions closely depends on the physicochemical characteristics of passivating ligands. Consequently, the ligands largely control the nonradiative recombination rates and emission characteristics in these QDs. Our simulations indicate that Cd 28 Se 17 (OH) 22 has the fastest nonradiative recombination rate due to the strongest electron–phonon interactions. Conversely, QDs passivated with thiolate or chloride exhibit considerably longer carrier lifetimes and suppressed nonradiative processes. The ligand-controlled electron–phonon interactions further give rise to the broadest and narrowest intrinsic optical line widths for OH and Cl-passivated single QDs, respectively. Finally, obtained computational insights lay the groundwork for designing appropriate passivating ligands on metal-rich QDs, making them suitable for a wide range of applications, from blue LEDs to quantum emitters.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Synthesis and Self-Assembly of Monodisperse Graphene Nanoribbons: Access to Submicron Architectures with Long-Range Order and Uniform Orientation

Fabricating organic semiconducting materials into large-scale well-organized architectures is critical for building high performance molecular electronics. While graphene nanoribbons (GNRs) hold enormous promise for various device applications, their assembly into a well-structured monolayer or multilayer architecture poses a substantial challenge. Here we report the preparation of length-defined monodisperse GNRs via the integrated iterative binomial synthesis (IIBS) strategy and their self-assembly into submicron-architectures with long-range order, uniform orientation as well as regular layers. Further, the use of short alkyl side chains benefits forming stable multi-layers through interlocking structures. By changing the length and backbone shapes of these monodisperse GNRs, various three-dimensional assemblies including multilayer stripes, monolayer stripes, and nanowires, can be achieved, leading to different photophysical properties and band gaps. The discovery of these intriguing self-assembly behaviors of length-defined GNRs is expected to open the door for various future applications.

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

Optimization of La 2 NiO 4+δ Electrolysis Cell Oxygen Electrode through Surfactant-Enabled LaCoO 3±δ Nanocatalyst Deposition

Lanthanum nickelate (LNO) has shown promise as a Cr-resistant air electrode material for SOECs but has suboptimal surface oxygen exchange properties. Nanocoating of the LNO surface with lanthanum cobaltite (LCO) was chosen to improve cell performance as a surface oxygen conductor. The work focused on the implementation of a two-step nano-LCO film deposition utilizing catechol molecules in a porous LNO electrode. The subgoals of the work were to maintain nanosized LCO particles/ grains to increase active surface area and to control the regularity/ homogeneity of the coating across the microstructure. To achieve these goals, a novel surfactant-enhanced liquid infiltration method was utilized, where nucleation sites were spread across the electrode structure to control the location and size of LCO particles. Various catechol surfactant compositions were evaluated for their ability to control the kinetics of nanoparticle deposition and the homogeneity of the coating. Chelated LCO was characterized by X-ray diffraction (XRD), which found a substantial improvement in LCO formation with surfactant addition and determined polymerized norepinephrine to be the best-performing surfactant, with 88.4% pure LCO formed at low temperature. X-ray photoelectron spectroscopy (XPS) confirmed LCO nanostructures formed by the two-step infiltration process, showing no impurities and a stable perovskite structure. Deposition kinetics were analyzed using atomic force microscopy (AFM), correlating infiltration times and solution molarity to nanoparticle size and distribution, the results of which were confirmed in symmetrical cell samples by scanning electron microscopy (SEM). Electrochemical impedance spectroscopy (EIS) testing demonstrated substantial improvements in polarization resistance, where the nanocoating reduced the resistance by ∼55% to 0.152 Ω·cm 2 at 700 °C and 0.039 Ω·cm 2 at 800 °C. Electrical conductivity relaxation (ECR) at this temperature confirmed an improved surface oxygen exchange coefficient of the LCO + LNO heterostructure predicted by the Bode data from EIS, alongside a reduction in activation energy by about 30%.

Deposition↗
DOE OSTI2025

Precise Synthesis of 4.75 V-Tolerant LiCoO 2 with Homogeneous Delithiation and Reduced Internal Strain

The rapid advancements in 3C electronic devices necessitate an increase in the charge cutoff voltage of LiCoO 2 to unlock a higher energy density that surpasses the currently available levels. However, the structural devastation and electrochemical decay of LiCoO 2 are significantly exacerbated, particularly at ≥4.5 V, due to the stress concentration caused by more severe lattice expansion and shrinkage, coupled with heterogeneous Li + intercalation/deintercalation reactions. Herein, employing the molten-salt synthesis technique, we propose a universal morphology-shaping strategy to attain bulk reaction homogeneity and reduce internal strains, even at extremely high charge voltages. The newly designed flattened polygon prismlike LiCoO 2 (P-LCO) particle, featuring a regular symmetrical arrangement along the c-axis, demonstrates a more homogeneous Li + extraction/insertion reaction, which results in a restrained transformation to detrimental O1 phase and reduced variation in lattice volume throughout the (de)lithiation processes. This benefits the mitigation of the local stress accumulation misfit dislocations and particle cracking, ultimately maintaining the mechanical stability of the cathode. Consequently, P-LCO is capable of breaking the voltage ceiling and exhibits exceptional long-term cycling capability at an ultrahigh voltage of 4.75 V. In conclusion, this work offers a brand-new perspective for the rational design of cathode morphology to address capacity deterioration caused by inhomogeneous delithiation and internal strain, thus inspiring the development of high-energy-density cathodes with improved durability.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Electron Inversion and Tunneling at Silicon Thermal Oxide Interfaces for Solar-Driven Molecular Catalysis to Syngas

Semiconductor photoelectrodes are regularly coupled to solid-state heterogeneous catalysts to perform solar-driven reduction of CO 2 . Less frequently, molecular catalysts are employed to better control the reactivity toward desired products, yet the development of robust semiconductor/molecule interfaces has proven challenging. Here, we demonstrate that a 2–3 nm thermal oxide layer on Si exhibits stability in aqueous solution, high photovoltage, and a photocurrent density of ∼10 mA/cm 2 for the solar-driven photoelectrochemical reduction of a homogeneous molecular catalyst, producing syngas with an ∼2:1 H 2 to CO ratio. Because of a low defect density, the oxide interface forms an electron inversion layer with metal-like electron density at cathodic potentials. This inversion layer facilitates electron transfer to redox-active molecules via tunneling even if the molecule’s reduction potential is beyond the semiconductor’s conduction band edge. Using an electrolyte solution composed of a homogeneous cobalt bis(terpyridine) catalyst in a water/organic solvent mixture, stable photoelectrochemistry was observed under 1-sun illumination, exhibiting an ∼30% Faradaic efficiency for CO that was similar to a glassy carbon electrode under comparable conditions. Furthermore, the results demonstrate that an ultrathin thermal oxide interface is a robust platform for development of aqueous-stable, molecule-driven photoelectrocatalysis.

Catalysts↗
DOE OSTI2024

Trends and Drivers of Terrestrial Sources and Sinks of Carbon Dioxide: An Overview of the TRENDY Project

The terrestrial biosphere plays a major role in the global carbon cycle, and there is a recognized need for regularly updated estimates of land-atmosphere exchange at regional and global scales. An international ensemble of Dynamic Global Vegetation Models (DGVMs), known as the “Trends and drivers of the regional scale terrestrial sources and sinks of carbon dioxide” (TRENDY) project, quantifies land biophysical exchange processes and biogeochemistry cycles in support of the annual Global Carbon Budget assessments and the REgional Carbon Cycle Assessment and Processes, phase 2 project. DGVMs use a common protocol and set of driving data sets. A set of factorial simulations allows attribution of spatio-temporal changes in land surface processes to three primary global change drivers: changes in atmospheric CO 2 , climate change and variability, and Land Use and Land Cover Changes (LULCC). Here, we describe the TRENDY project, benchmark DGVM performance using remote-sensing and other observational data, and present results for the contemporary period. Simulation results show a large global carbon sink in natural vegetation over 2012–2021, attributed to the CO 2 fertilization effect (3.8 ± 0.8 PgC/yr) and climate (–0.58 ± 0.54 PgC/yr). Forests and semi-arid ecosystems contribute approximately equally to the mean and trend in the natural land sink, and semi-arid ecosystems continue to dominate interannual variability. The natural sink is offset by net emissions from LULCC (–1.6 ± 0.5 PgC/yr), with a net land sink of 1.7 ± 0.6 PgC/yr. Despite the largest gross fluxes being in the tropics, the largest net land-atmosphere exchange is simulated in the extratropical regions.

58 GEOSCIENCES↗
DOE OSTI2025

Convolutional Neural Networks Trained on Internal Variability Predict Forced Response of TOA Radiation by Learning the Pattern Effect

Abstract Predicting forced, long‐term radiative feedbacks from internal climate variability has been a decades‐long quest in climate science. We train a convolutional neural network (CNN) to predict annual‐ and global‐mean top of the atmosphere radiation anomalies from time‐varying maps of near‐surface temperature in climate models. Trained on internal variability alone, the nonlinear CNN can predict radiation under strong climate change, outperforms a regularized linear regression approach, and works within and across different climate models. We show with explainable artificial intelligence methods that the CNN draws predictive skill from physically meaningful regions but at much smaller spatial scales than currently assumed.

Rugenstein, Maria [Colorado State University Fort ↗
DOE OSTI2025

Sequential Precipitation Input Tagging (SPIT) to Estimate Water Transit Times and Hydrologic Tracer Dynamics Within Water‐Tagging Enabled Hydrologic Models

Determining the age distribution of water exiting a catchment is important for understanding groundwater storage and mixing. New water-tagging capabilities within models track precipitation events as they move through simulated storages, yet forward modeling of individual events may not systematically capture the full transit time distribution (TTD). Here, we present a “sequential precipitation input tagging” (SPIT) framework to tag all input precipitation at regular intervals during extended model simulations. Monthly tags over 7 years were applied at six National Ecological Observatory Network sites to calculate TTDs and derive mean virtual tracer age, $\overline{T_{V}}$, fractions of young water, F yw , and hydrologic tracer concentrations (water isotopes δ 18 O and δ 2 H) within a tagging enabled version of the Weather Research and Forecast hydrologic model (WRF-Hydro). Throughout seven simulation years, the fraction of simulated discharge derived from tagged events, F tag , increased each year, with the final year's F tag ranging from 66% to 100% and highlights the need to apply SPIT over many years to understand TTDs. When the F tag was >75%, simulated $\overline{T_{V}}$ ranged 179–923 days and F yw 0.6%–23.9%, with daily values exhibiting a power-law relationship with precipitation, discharge, and groundwater. Through implementation of SPIT, we find this hydrologic model configuration performs poorly in estimation of $\overline{T_{V}}$ and F yw (root mean squared error of 469 days and 14.4% respectively), suggesting it misrepresents subsurface mixing. Thus, the SPIT framework provides a reproducible approach to calculate watershed transit times within tagging enabled models and thereby assess and improve representation of hydrologic processes.

fraction of young water↗
DOE OSTI2024

Self‐Potential Tomography Preconditioned by Particle Swarm Optimization—Application to Monitoring Hyporheic Exchange in a Bedrock River

Abstract A self‐potential (SP) data‐inversion algorithm was developed and tested on an analytical model of electrical‐potential profile data attributed to single and multiple polarized electrical sources. The developed algorithm was then validated by an application to SP‐monitoring field data measured on the floodplain of East Fork Poplar Creek, Oak Ridge, Tennessee, to image electrical sources in areas conducive to preferential flow into the flood plain from the bedrock‐lined riverbed. The algorithm combined stochastic source‐localization by particle‐swarm‐optimization (PSO) of electrical sources characterized by simplified geometries with source tomography by regularized weighted least‐squares minimization of a quadratic objective function. Prior information was incorporated by preconditioning the tomography algorithm by PSO results. Variable percentages of random noise were added to analytical‐model data to evaluate the algorithm performance. Results indicated that true parameters of single‐source models were inverted and approximated with small residual error, whereas inversion of analytical‐model data representing multiple electrical sources accurately approximated the locations of the sources but miscalculated some parameters because of the non‐uniqueness of the inverse‐model solution. Source tomography applied to analytical model data during testing produced a spatially continuous parameter field that identified the locations of point‐scale synthetic dipole sources of electrical current flow with varying degrees of accuracy depending on the prior information incorporated into the tomography. When applied to SP‐monitoring field data, the algorithm imaged electrical sources within a known fault that intersects the bedrock riverbed and flood plain of East Fork Poplar Creek and depicted dynamic electrical conditions attributed to hyporheic exchange.

54 ENVIRONMENTAL SCIENCES↗