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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 739 records · Page 41
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Optical image analysis of WSe 2 − thresholding for layer detection

The fast and reliable layer identification of two-dimensional transition metal dichalcogenide (TMD), such as WSe 2 , is essential to investigating their thickness-dependent electronic and optical properties. This article presents efficient optical image thresholding methodology designed to segment the mono, bi, and tri-layer regions of WSe 2 flakes mechanically exfoliated onto a SiO 2 /Si substrate. The optical images were first preprocessed to exclude the background effect and analyzed using the pixel medians and interquartile ranges for fundamental color channels—red, green, and blue (RGB). The analysis of red channel pixel intensities yielded three distinct ranges, serving as thresholds for layer segmentation: monolayer (111.0–118.0), bilayer (103.0–110.0), and tri-layer (93.0–103.0). Similarly, thresholds were established for each color channel, facilitating a comparative study of the segmentation performances. Further, the intersection-over-union ($IoU$) calculations revealed that the red and green channels demonstrated greater than 99 % and 90 % accuracy in differentiating each layer, respectively. This approach yields remarkable results without substantial data calibration that utilizes time-intensive heuristic techniques. Moreover, the proposed methodology offers the flexibility to compare performances across different color channels, expanding the applicability for other 2D material systems.

2D Materials↗
DOE OSTI2025

Screening green solvents for multilayer plastic film recycling processes

Multilayer (ML) plastic films are essential packaging materials that help protect products from diverse external factors; however, only 5% of all ML films are recycled in the United States. Solvent-based technologies are a promising alternative for recycling ML films because they enable recovery of constituent polymer resins. For example, the Solvent Targeted Recovery and Precipitation (STRAPTM) process sequentially dissolves and separates polymer components using a series of targeted solvent washes. A crucial design aspect of this process is the impact of selected solvents on human health and on the environment. Here, this work introduces a computational framework that integrates molecular modeling, process modeling, techno-economic analysis (TEA), and life-cycle analysis (LCA) to quickly screen green solvents for solvent-based ML recycling processes. Initial screening for solvents based on selectivity is performed by estimating temperature-dependent solubilities using molecular-scale models. Subsequent screening uses basic estimates of energy use and octanol-water partition coefficients (logP) as key measures of health, safety, and environmental hazards. Detailed process modeling, TEA, and LCA are used on a reduced set of promising solvents identified in early screening steps to more accurately determine how solvent selection and associated operating conditions impact overall economics and environmental impacts. The framework is used for the identification of green solvents (from a database of 1,000 solvents) that separate an industrial ML film composed of polyethylene (PE), ethylene vinyl alcohol (EVOH), and polyethylene terephthalate (PET). Our analysis shows the effectiveness of the framework and reveals fundamental trade-offs between solvent greenness, solubility, and economics. Our work emphasizes the importance of taking a holistic systems view during solvent design and aims to inform the development of new processes for ML film recycling and the identification of new ML films that are easier to recycle.

economics↗
DOE OSTI2025

Borate-assisted alkaline extraction of hemicellulose from switchgrass with enhanced structural stability and purity

Valorization of non-cellulosic polysaccharides is crucial for enhancing the economic competitiveness of biorefinery processes. In this study, a mixture of boric acid and sodium hydroxide was employed to efficiently extract hemicellulose from holocellulose switchgrass. Borate-assisted alkaline extraction resulted in a higher xylan content (59.5 %) compared to conventional alkaline extraction. Here, the hemicellulose fractions derived from the borate-alkaline treatment exhibited a higher molecular weight (M w = 51.2 kDa) and a relatively lower degree of polydispersity (1.28), indicating improved structural stability. The presence of borate had a protective effect against chain scission, preserving glucuronic acid residues and increasing galactose content. Additionally, borate improved hemicellulose purity, with up to 74.1 % of the extracted hemicellulose being suitable for further enzymatic applications. Extended extraction time further enhanced hemicellulose recovery, reaching 97.9 % under NaOH/boric acid conditions while maintaining structural integrity, as confirmed by SEM, FTIR and 2D HSQC NMR analyses. These findings provide insights into the role of borate in optimizing hemicellulose extraction and improving its potential for bioconversion processes.

Borate alkaline↗
DOE OSTI2026

Evaluating CO 2 mitigation strategies in SAF biorefineries: Techno-economic and life cycle analysis

The aviation sector requires scalable decarbonization strategies, and lignocellulosic sustainable aviation fuel (SAF) represents a promising pathway. This study comparatively evaluates the techno-economic analysis and life cycle assessment (LCA) of three CO 2 management strategies integrated within a U.S.-based gasification–Fischer–Tropsch SAF biorefinery: (i) catalytic hydrogenation of captured CO 2 to methanol, (ii) geological CO 2 sequestration, and (iii) mineralization to sodium bicarbonate (NaHCO 3 ). Techno-economic analysis indicates that methanol synthesis requires approximately 26% higher capital investment and 33% higher operating costs than mineralization. Although methanol co-production generates the highest gross revenue, NaHCO 3 production reduces the SAF minimum selling price by approximately 38% relative to both methanol synthesis and geological sequestration pathways, reflecting a more balanced cost allocation through mineral co-product valorization. Geological sequestration lowers operating costs by nearly 50% compared with methanol synthesis but remains highly dependent on carbon credit mechanisms. LCA reveals substantial divergence in climate performance. Relative to methanol synthesis, sequestration improves net greenhouse gas performance by approximately 163%, transitioning the system from net-positive to net-negative emissions. Mineralization further enhances carbon mitigation, achieving roughly 85% greater carbon reduction than sequestration and over sixfold improvement relative to methanol synthesis within the defined system boundary. Sensitivity analysis identified hydrogen price, co-product market value, and process emissions as dominant drivers. Under baseline assumptions, CO 2 mineralization is found to offer the most balanced pathway.

Carbon capture and storage↗
DOE OSTI2025

Magnetic properties of (Mo 2/3 Dy 1/3 ) 2 AlC arc melted polycrystalline samples

Here, this study investigates the structural and magnetic properties of arc-melted (Mo 2/3 Dy 1/3 ) 2 AlC polycrystalline samples, a member of the i-MAX phase family. Temperature-dependent magnetization and specific heat measurements confirm the low-temperature antiferromagnetic transitions around 14 K and 17 K. Neutron diffraction data collected at 4 K reveal the emergence of magnetic Bragg peaks that are not allowed in the paramagnetic space group C2/c, further confirming the presence of antiferromagnetic ordering. The detection of a secondary phase, DyAl 2 , is complicated by overlapping Bragg peaks with the monoclinic phase of (Mo 2/3 Dy 1/3 ) 2 AlC in powder XRD patterns. However, magnetization and neutron diffraction data suggest the presence of DyAl 2 , evidenced by a ferromagnetic phase transition around 62 K.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Improved liquid lithium surfaces in the Lithium Tokamak Experiment-β

Advances in vacuum, surface, and lithium conditioning techniques throughout five years of continuous operations in LTX-β have produced mirror-like liquid lithium surfaces and demonstrated the feasibility of high-performance tokamak discharges fully surrounded by liquid metal without significant operational problems. Improvements in conditioning techniques and procedures, including many weeks of baking and accumulation of 70 g of Li, led to reduced residual gasses and clean Li surfaces - all while still maintaining enough operational flexibility for multiple in-vacuum diagnostic upgrades and calibrations. Coatings had a visibly clean appearance, with reflective liquid metal demonstrating good wetting and surface adhesion with films that were now macroscopically thick. Solidified Li showed large crystal grains, while surface science measurements observed reduced impurities in the lithium. Steadily improved plasma performance was achieved with liquid lithium, with discharges able to match solid Li in terms of evolution of I p and n e , including rapid density pumping indicating low recycling. There were indications of moderately increased Li impurity influx, though few significant disturbances by the large liquid surfaces on tokamak operations over hundreds of discharges. Liquid metal plasma facing components are a potential solution to the extreme heat and particle fluxes that could cause unacceptable damage to solid materials, while liquid lithium also has the potential for greatly increased confinement in the low-recycling regime. While many liquid metal approaches are possible, and numerous experiments have been conducted in test stands and small modules in fusion devices, LTX-β is the only tokamak operated while fully surrounded by liquid metal.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Variable rate neural compression for sparse detector data

Particle colliders produce data at extraordinary rates, posing major challenges for transmission and storage. High-throughput compression algorithms are therefore essential. In the sPHENIX experiment taking data at the Relativistic Heavy Ion Collider, a time projection chamber records three-dimensional (3D) particle trajectories that are highly sparse, making conventional learning-free lossy compression ineffective. Convolutional neural networks have surpassed traditional methods in compression ratio and accuracy. However, they fail to exploit sparsity for efficiency. To address these gaps, we present BCAE-VS, a bicephalous convolutional autoencoder with variable compression ratio for sparse data, which adapts compression to input complexity through key-point identification and sparse convolution. BCAE-VS achieves higher accuracy and compression ratios than prior neural approaches while being orders of magnitude smaller. Moreover, its throughput increases with sparsity—a property not observed in other methods. Although it was developed for collider experiments, BCAE-VS readily extends to other sparse data domains, such as light detection and ranging (LiDAR) sensing and 3D microscopy.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Graphene Oxide Nanoribbons for High Early-Strength Cement Concrete

Longitudinal oxidative unzipping of the outer walls of multiwalled carbon nanotubes (MWCNTs) yields graphene oxide nanoribbons (GONRs), which exhibit greater open surface area and functional edge content than MWCNTs. This paper presents a study of the nano-amendment of Portland cement concrete with GONRs in concentrations between 0.05% (in weight of cement, wt%) and 0.0005 wt%, thus up to two orders of magnitude lower than that reported as lower-bound in the archival literature. The dispersibility in aqueous solution as a function of GONR concentration and oxygen weight content (O%) was assessed through dynamic light scattering (DLS) and zeta potential analysis. The results indicated that less effective suspensions were obtained for 0.05 wt% of GONRs and 22.7 O%. Therefore, GONR water suspensions with 30-40% O% were used to manufacture 50 mm × 100 mm cylindrical concrete specimens. After 7 days of curing, results from uniaxial compression tests using four specimens per configuration (MWCNT concentration and O%) showed that the incorporation of GONRs resulted in an average increase in compressive strength up to 45%. Consistent with the DLS and compression test results, SEM micrographs showed well-dispersed GONRs together with accelerated and preferential formation of calcium silicate hydrates (C-S-H) for all GONR concentrations. The results indicate, for the first time, that the incorporation of very small concentrations (as low as 0.0005 wt%) of well-dispersed GONR amendments can significantly enhance the early-age concrete strength. However, such enhancement became insignificant after 28 days of curing.

cement↗
DOE OSTI2025

Microbial inoculants and invasions: a call to action

Microbial inoculants are increasingly used for beneficial purposes in agriculture, bioremediation, and medicine, but they can carry risks of generating invasive microbes. Here, we present a roadmap for guarding against these invasions, proposing developing (i) coherent mechanistic understandings of how microbial inoculants can effect invasions, (ii) predictive models forecasting microbial invasion risks, and (iii) effective management strategies. To guide mechanistic understandings, we distill 17 guiding hypotheses. For predictive modeling, we highlight data collection needs and qualitative approaches. For management strategies, we stress the importance of accurately weighing the risks against benefits. The unified approach presented here provides a route toward an effective research and management infrastructure for microbial inoculants in order to avoid potentially catastrophic microbial invasions.

invasive species↗
DOE OSTI2026

Machine Learning Interatomic Potentials for Modeling Framework Flexibility and Water Uptake in NbOFFIVE-1-Ni Metal–Organic Framework

Metal–organic frameworks (MOFs), with their distinctive porous structures and tunable chemical properties, have shown immense promise in the separation and storage of gases. Currently, the accurate simulation of their adsorptive properties remains challenging, especially for systems where the molecules fit very tightly into the pores. Traditional simulation methods often approximate the frameworks as rigid and do not account for the framework flexibility seen in materials such as NbOFFIVE-1-Ni. First-principles molecular dynamics (FPMD) simulations offer the desired accuracy in modeling this flexibility but are limited by their extensive computational demands, rendering them impractical for long simulations. Conversely, classical force field-based simulations offer computational efficiency but lack the necessary accuracy. Here, to break this accuracy-efficiency trade-off, we have developed machine learning interatomic potentials trained on energies and forces from FPMD to model the framework flexibility of NbOFFIVE-1-Ni in the presence of water over nanosecond time scales. Furthermore, by integrating MLIP-driven molecular dynamics (MLIP-MD) with grand canonical Monte Carlo (GCMC) simulations, we further incorporated framework flexibility into adsorption predictions, yielding water adsorption isotherms that better align with experimental data compared to those of conventional GCMC simulations. These advances offer new opportunities for the design and optimization of MOFs in gas storage and separation applications.

adsorption↗
DOE OSTI2026

Diffusion and Adsorption of 2-Methylpentane and 3-Methylpentane in MFI-Type Zeolite Crystals

Due to the intimate contact of guest molecules with the inner surface of microporous adsorbents, slight changes in the structure of the guest molecules may lead to remarkable changes in their microdynamics. As an impressive example, in this work, diffusion measurements via IR microimaging (IRM) show that the transport diffusivity of 2-methylpentane (2MP) exceeds the value attained for 3-methylpentane (3MP) by a factor of 2−4.5 in silicalite- 1, an MFI-type zeolite crystal and a technically relevant porous host system. This experimental finding is rationalized by comparison with the outcome of dynamically corrected transition state theory (dcTST) simulations.

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

Single-Molecule Conductance through Hybrid Radially and Linearly π-Conjugated Macromolecules Reveals an Unusual Intramolecular π-Interaction

We describe the design, synthesis, and single-molecule junction conductance of π-electron molecules bearing both radial and linear π-conjugation pathways, whereby cycloparaphenylene (CPP) radial cores are π-extended linearly with aryl alkyne substituents as models for previously reported CPP-arylene ethynylene conjugated polymers. Although radially and linearly conjugated molecules have been studied previously in isolation as junction-bridging molecular electronic units, this is the first study to examine molecules where both topologies are operative. Our results reveal that the presence of radial CPP components within the junction-spanning pathway leads to a reduction in the conductance of the backbone compared to model linear phenyl substituents. Through tight-binding and DFT-based calculations, we attribute this conductance change to intramolecular van der Waals (vdW) interactions between the CPP ring and the junction-spanning arylene-ethynylene molecular backbone. These interactions induce changes in the dihedral angles of the backbone, leading to a reduced overlap of π orbitals within the molecular junction.

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

Sensitized Near-Infrared Emission of SiGe Nanocrystals via Heterostructuring with Quasi Two-Dimensional Perovskite

The near-infrared (NIR) emission of silicon–germanium alloy nanocrystals (SiGe NCs) was sensitized by heterostructuring with a quasi two-dimensional (Q-2D) perovskite (CsPbBr 3 blended with butylammonium bromide (BABr)). Colloidal SiGe NCs were synthesized by using a nonthermal plasma method with chloride precursors. As-synthesized SiGe NCs showed no detectable photoluminescence (PL). Embedding the SiGe NCs within the perovskite matrix via spin coating led to a heterostructure exhibiting dual emissions: green emission at 520 nm from the perovskite and NIR emission at 1035 nm from the SiGe NCs. Time-integrated and resolved PL measurements and transient absorption spectroscopy revealed energy transfer from the perovskite to the SiGe NCs, which sensitized the NIR emission from the SiGe NCs and quenched the green PL for the perovskite. These results demonstrate that Ge alloying can effectively tune the bandgap of Si NCs and highlight the feasibility of heterostructuring perovskites and photoluminescent NCs to enhance or activate their PL. In conclusion, this approach broadens their potential applications in the NIR region.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Boosting the Oxygen Evolution Reaction by Tuning the Interfacial Iron Adsorption on Layered Double Hydroxide

Understanding the interaction between ions in the electrolyte and electrode materials plays an important role in optimizing the water electrolysis performance for hydrogen production. Herein, the synergistic effect of iron (Fe) in the electrolyte and interlayer anions within the layered structure on the oxygen evolution reaction (OER) has been investigated by combining material synthesis with controlled structure, multiple characterization techniques, and first-principles calculations. Nickel aluminum layered double hydroxides (NiAl-LDHs) with different interlayer anions (CO 3 2– , Cl – , and Br – ) show similar oxygen evolution activity in the absence of Fe species in the electrolyte. The addition of Fe into the electrolyte results in improved performance for all of the NiAl-LDHs, following the rank LDH-Br > LDH-Cl > LDH-CO 3 , under all of the conditions with varied concentration of Fe. X-ray absorption spectroscopy and identical location electron microscopy analyses show that the LDH structure remains unchanged after the OER activity test, while in situ stationary probe rotating disk electrode inductively coupled plasma mass spectrometry (SPRDE-ICP-MS) measurements show partial dissolution of the intercalating halide ions during cycling, with less dissolution for Br-intercalated materials. Insights from theoretical calculations demonstrate the thermodynamic preference of Br – to remain intercalated in the presence of Fe, while the stronger adsorption of Fe(OH) 3 species on the LDH-Br sample promotes the OER activity. In conclusion, these results provide mechanistic insights into the rational design of active layered materials with an enhanced OER performance for efficient water electrolysis.

58 GEOSCIENCES↗
DOE OSTI2025

Mechanistic Studies of Oxidative Degradation in Diamine-Appended Metal–Organic Frameworks Exhibiting Cooperative CO 2 Capture

Understanding the impact of O 2 during a carbon capture process is vital for designing robust, cost-effective materials for carrying it out. However, mechanistic studies of the O 2 -induced degradation of materials are not easily undertaken owing to the complex sequential reaction pathways that arise. Here, we report comprehensive mechanistic investigations of the O 2 -induced degradation of diamine-appended metal−organic frameworks (MOFs) exhibiting cooperative CO 2 adsorption. Oxygen exposure experiments were performed on seven different diamine-appended MOFs, including e-2−Mg 2 (dobpdc) (e-2 = N-ethylethylenediamine, dobpdc 4− = 4,4′-dioxidobiphenyl-3,3′-dicarboxylate), under various temperatures and O 2 pressures. These experiments show that diamine degradation inhibits CO 2 chemisorption and that the degradation rate is significantly influenced by the diamine structure. In contrast, the parent frameworks remain essentially intact upon O 2 exposure. Detailed characterization of O 2 -exposed e-2−Mg 2 (dobpdc) revealed the formation of various degradation products, including acetaldehyde, carbon dioxide, water, ethylamine, and other aldehyde- and imine-containing species. Together, these observations suggest that diamine degradation occurs via C−N bond cleavage through pathways involving C-centered radicals. Furthermore, computational evaluation of the initiation and propagation pathways for amine degradation in diamine-appended MOFs indicates that (i) degradation is likely initiated by OH • , (ii) carbon-centered radicals generated via radical transfer reactions react with O 2 , leading to amine degradation, and (iii) the ratelimiting step of the degradation reactions likely involves O−O bond cleavage. Overall, these mechanistic insights could inform strategies for mitigating O 2 -induced amine degradation in next-generation carbon capture technologies.

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

Unravelling the Stability Stressors of Atomically Dispersed Fe–N–C Oxygen Reduction Catalysts

Enhancing the catalytic stability of Fe–N–C catalysts for cathodic oxygen reduction in proton-exchange membrane fuel cells (PEMFCs) necessitates an in-depth understanding of their degradation mechanisms. Here, this study identifies key stressors affecting the stability of Fe–N–C catalysts, specifically acidic environment, oxygen (O 2 ), and reactive oxygen species (ROS). Through ex situ/operando experiments, we show that the oxidation of local carbon by acidic environment + O 2 + ROS, along with the demetalation of catalytic FeN x C y sites by O 2 or O 2 + ROS, is the primary factor responsible for the initial fast degradation of Fe–N–C catalysts. The demetalation of FeN x C y sites, influenced by O 2 , in particular by O 2 + ROS, leads to the subsequent gradual degradation of Fe–N–C. Notably, FeN 4 C 12 -type active sites are more susceptible to demetalation than FeN 4 C 10 -type sites in O 2 or O 2 + ROS. Our findings indicate that, besides constructing more stable FeN x C y sites, preventing local carbon oxidation and scavenging of ROS are all critical for maintaining the stability of Fe–N–C catalysts.

Xie, Xiaohong [Pacific Northwest National Laborato↗
DOE OSTI2025

Advancing AI-Driven Analysis in X-ray Absorption Spectroscopy: Spectral Domain Mapping and Universal Models

In recent years, rapid progress has been made in developing artificial intelligence (AI) and machine learning (ML) methods for X-ray absorption spectroscopy (XAS) analysis. Compared to traditional XAS analysis methods, AI/ML approaches offer dramatic improvements in efficiency and help eliminate human bias. To advance this field, we advocate an AI-driven XAS analysis pipeline that features several interconnected key building blocks: benchmarks, workflows, databases, and AI/ML models. Specifically, we present two case studies for XAS ML. In the first study, we demonstrate the importance of reconciling the discrepancies between simulation and experiment using spectral domain mapping (SDM). Our ML model, which is trained solely on simulated spectra, predicts an incorrect oxidation state trend for Ti atoms in a combinatorial zinc titanate film. After transforming the experimental spectra into a simulation-like representation using SDM, the same model successfully recovers the correct oxidation state trend. In the second study, we explore the development of universal XAS ML models that are trained on the entire periodic table, which enables them to leverage common trends across elements. Looking ahead, we envision that an AI-driven pipeline can unlock the potential of real-time XAS analysis to accelerate scientific discovery.

36 MATERIALS SCIENCE↗
DOE OSTI2026

A Mountain Glacier Perspective on the Bipolar Seesaw

A global record of mountain glacier terminations during the last deglaciation (∼19–11 ka) dated by a large, uncurated data set of cosmogenic-nuclide exposure ages highlights a statistically significant asynchrony in termination ages between the Northern and Southern Hemispheres. This interhemispheric offset in the timing of glacier terminations is consistent with previously correlated ice core records that show a systematic interhemispheric lag in the timing of abrupt climate events, with the Southern Hemisphere leading the Northern Hemisphere by ∼300–3,500 years. Our analysis (a) aggregates cosmogenic-nuclide exposure ages from a global data set of moraines to discern climatically driven peaks in moraine emplacement events, and (b) utilizes a Monte Carlo simulation based on a null hypothesis that moraine emplacement is interhemispherically synchronous to estimate the statistical significance of the observed offset. The observed lag of Northern Hemisphere emplacement events compared to the Southern Hemisphere is statistically significant and is consistent with the “bipolar seesaw” pattern observed in ice core records.

58 GEOSCIENCES↗