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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Dark and Bright Excitons in Halide Perovskite Nanoplatelets

Semiconductor nanoplatelets (NPLs), with their large exciton binding energy, narrow photoluminescence (PL), and absence of dielectric screening for photons emitted normal to the NPL surface, could be expected to become the fastest luminophores amongst all colloidal nanostructures. However, super-fast emission is suppressed by a dark (optically passive) exciton ground state, substantially split from a higher-lying bright (optically active) state. Here, the exciton fine structure in 2-8 monolayer (ML) thick Cs n - 1 Pb n Br 3n + 1 NPLs is revealed by merging temperature-resolved PL spectra and time-resolved PL decay with an effective mass model taking quantum confinement and dielectric confinement anisotropy into account. This approach exposes a thickness-dependent bright-dark exciton splitting reaching 32.3 meV for the 2 ML NPLs. The model also reveals a 5-16 meV splitting of the bright exciton states with transition dipoles polarized parallel and perpendicular to the NPL surfaces, the order of which is reversed for the thinnest NPLs, as confirmed by TR-PL measurements. Accordingly, the individual bright states must be taken into account, while the dark exciton state strongly affects the optical properties of the thinnest NPLs even at room temperature. Significantly, the derived model can be generalized for any isotropically or anisotropically confined nanostructure.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Localizing Tungsten Single Atoms around Tungsten Nitride Nanoparticles for Efficient Oxygen Reduction Electrocatalysis in Metal–Air Batteries

Combining isolated atomic active sites with those in nanoparticles for synergizing complex multistep catalysis is being actively pursued in the design of new electrocatalyst systems. However, these novel systems have been rarely studied due to the challenges with synthesis and analysis. Herein, a synergistically catalytic performance is demonstrated with a 0.89 V (vs reversible hydrogen electrode) onset potential in the four-step oxygen reduction reaction (ORR) by localizing tungsten single atoms around tungsten nitride nanoparticles confined into nitrogen-doped carbon (W SAs/WNNC). Through density functional theory calculations, it is shown that each of the active centers in the synergistic entity feature a specific potential-determining step in their respective reaction pathway that can be merged to optimize the intermediate steps involving scaling relations on individual active centers. Impressively, the W SAs/WNNC as the air cathode in all-solid-state Zn-air and Al-air batteries demonstrate competitive durability and reversibility, despite the acknowledged low activity of W-based catalyst toward the ORR.

25 ENERGY STORAGE↗
DOE OSTI2023

The Mechanism of Fluorine Doping for the Enhanced Lithium Storage Behavior in Cation-Disordered Cathode Oxide

Li-rich cation-disordered rock-salt (DRX) materials have emerged as promising candidates for high-capacity oxide cathodes. Their fluorinated variants have shown improved cycling stability with effectively suppressed oxygen loss. However, a comprehensive understanding of how fluorination impacts the multiscale structure and lithium transportation in DRX remains elusive in experiments. In this study, the neutron total scattering technique in conjunction with the advanced reverse Monte Carlo (RMC) fitting method is employed to characterize the intricate structure of Li 1.16 Ti 0.37 Ni 0.37 Nb 0.1 O 2 (LTNNO) and the fluorinated Li 1.2 Ti 0.35 Ni 0.35 Nb 0.1 O 1.8 F 0.2 (LTNNOF). Through rigorous statistical analysis, the multiscale structural evolution upon fluorination is quantified from atomic (≤5 Å) to long-range scale (≈100 Å). The local Li-rich environments around F induce a modest 2.4% increment in the number of fast Li 0TM (transition metal) channels. Crucially, at a broader scale, the proportion of 0TM channels participating in percolation increases significantly from 2.9% in LTNNO to 8.7% in LTNNOF. Fluorination improves the capacity release mainly through merging isolated fast Li channels into the percolation network. This work experimentally unravels the multiscale mechanism of fluorination-induced performance improvement in DRX materials and highlights the necessity of adopting an advanced RMC fitting method to obtain a full view of the complex structural features in developing high-capacity DRX cathodes.

25 ENERGY STORAGE↗
DOE OSTI2022

Quantifying the impact of temporal analysis of products reactor initial state uncertainties on kinetic parameters

The temporal analysis of products (TAP) reactor, a transient kinetic tool, provides users with information as the catalyst state evolves. However, the state of the art for TAP uncertainty quantification only considers the experimental noise present in the outlet flow signal. Additional sources of uncertainty, including, but not limited to, initial surface coverages, the catalyst zone location, the inert void fraction, and the gas pulse intensity and pulse delay, are not included. For this reason, a framework for quantifying all uncertainty sources present in TAP experiments is presented and applied to a carbon monoxide oxidation case study. Herein, two methods for quantifying these sources of uncertainty are introduced. The first utilizes initial state sensitivities to approximate the parameter variances, as well as to provide insights into the structural certainty of the model. The second generates parameter confidence distributions through an ensemble-based sampling algorithm. This initial state covariance matrix can ultimately be merged with the experimental noise covariance matrix, providing a unified description of the parameter uncertainties for a single TAP experiment.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Predicting High‐Resolution Spatial and Spectral Features in Mass Spectrometry Imaging with Machine Learning and Multimodal Data Fusion

Recent advancements in molecular Mass Spectrometry Imaging have sparked interest in integrating high spatial resolution methods with molecular mass-spectrometry-based chemical imaging. Fusion-based algorithms have proven effective in generating high spatial-resolution molecular mass spectra. However, a significant challenge stems from the differing physical mechanisms underlying image generation and data upsampling techniques, potentially leading to discrepancies in integrated information channels. Integrating physical constraints into data processing workflows is essential to tackle this issue. In this study, we propose an innovative approach that merges data from Fourier transform ion cyclotron resonance (FTICR), time-of-flight matrix-assisted laser desorption/ionization, and time-of-flight secondary ion mass spectrometry imaging techniques. By leveraging FT-ICR's unparalleled spectral resolution and ToF-SIMS's exceptional spatial resolution, we achieve submicron spatial resolution, enabling the observation of intact molecular species with remarkable spectral precision. Canonical correlation analysis is employed to incorporate physical constraints. Through sophisticated image processing and machine learning techniques, the results of this fusion hold significant promise for advancing our comprehension of complex systems and unveiling concealed molecular intricacies.

canonical correlation analysis↗
DOE OSTI2024

Positron emission tomography harmonization in the Alzheimer's Disease Neuroimaging Initiative: A scalable and rigorous approach to multisite amyloid and tau quantification

Abstract INTRODUCTION A key goal of the Alzheimer's Disease NeuroImaging Initiative (ADNI) positron emission tomography (PET) Core is to harmonize quantification of β‐amyloid (Aβ) and tau PET image data across multiple scanners and tracers. METHODS We developed an analysis pipeline (Berkeley PET Imaging Pipeline, B‐PIP) for ADNI Aβ and tau PET images and applied it to PET data from other multisite studies. Steps include image pre‐processing, refacing, magnetic resonance imaging (MRI)/PET co‐registration, visual quality control (QC), quantification of tracer uptake, and standardization of Aβ and tau standardized uptake value ratios (SUVrs) across tracers. RESULTS Measurements from 10,105 cross‐sectional and longitudinal Aβ and tau PET scans acquired in several studies between 2010 and 2024 can be processed, harmonized, and directly merged across tracers and cohorts. DISCUSSION The B‐PIP developed in ADNI is a scalable image harmonization approach used in several observational studies and clinical trials that facilitates rigorous Aβ and tau PET quantification and data sharing. Highlights Quantitative results from ADNI Aβ and tau PET data are generated using a rigorous, scalable image processing pipeline This pipeline has been applied to PET data from several other large, multisite studies and trials Quantitative outcomes are harmonizable across studies and are shared with the scientific community

Neurosciences & Neurology↗
DOE OSTI2024

Cellular Phosphate Sensing and Anion Binding by an Azacrown‐Calixpyrrole Hybrid

A hybrid receptor-sensor for anions originating from the merging of positively charged ammonium moieties for electrostatic attraction/stronger binding of azacrowns with directionality of calixpyrrole hydrogen bond donors for selectivity is investigated. As demonstrated this hybrid receptor-sensor shows a remarkable selectivity for orthophosphate even in the presence of other phosphates and anions found in cellular materials (K assoc H 2 PO 4 − >H 2 P 2 O 7 2− >AMP − ≫ADP 2− or ATP 3− over halides, nitrate, or hydrogen sulfate; all Na + salts in water) but also cellular polyphosphate or phospholipids. This selectivity is harnessed in a real-time monitoring of cell lysis by lysozyme, which releases orthophosphate and other phosphates and anions from the cells. This sensitive (LOD 0.4 μM) fluorescence-based microscale method compares favorably with the state-of-the-art techniques but can easily be practiced in a high-throughput screening (HTS) manner. The anion binding and selectivity in aqueous solutions were investigated by NMR and put in context with phosphate binding of the parent calix[4]pyrrole. The microscopic understanding of anion binding by the hybrid receptor was then obtained from a combination of density functional theory (DFT), classical molecular dynamics (MD) with explicit water solvation, and ab initio MD (AIMD) simulations. Correlating the NMR and fluorescence binding data with studies of solvation of the receptor, phosphate anion, and the resulting complex confirms the binding is largely driven by entropic component (TΔS) associated with receptor and anion desolvation.

Anions↗
DOE OSTI2020

Fractionating and Purifying Softwood Kraft Lignin with Aqueous Renewable Solvents: Liquid–Liquid Equilibrium for the Lignin–Ethanol–Water System

Hot ethanol–water solutions can be used to simultaneously fractionate and purify softwood Kraft lignin through the Aqueous Lignin Purification with Hot Agents (ALPHA) process, using the regions of liquid–liquid equilibrium (LLE) that form at selected temperatures and solvent-to-lignin feed (S/F) ratios. Lignin, ethanol, and water compositions are measured for the solvent-rich (SR) and lignin-rich (LR) liquid phases in mutual equilibrium, as well as the lignin and metals mass distributions between the two phases. As depicted in quasi-ternary diagrams for clarity, both temperature and S/F ratio can be used to grow, merge, and even split the regions of LLE, giving significant control over both molecular weight (MW) and lignin purity. For example, a solvent comprising 45:55 EtOH/H 2 O at 75 °C and an S/F ratio of 6:1 enables recovery of an ultrapure (95 % of Na removed), higher MW (M n =8400 Da) lignin fraction in the LR phase. On the other hand, 95:5 EtOH/H 2 O at 45 °C and S/F=3:1 enables recovery of an ultrapure, low MW (1500 Da) lignin in the SR phase.

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

Endowing Polythioester Vitrimer with Intrinsic Crystallinity and Chemical Recyclability

Abstract Technologically important thermosets face a long‐standing end‐of‐life (EoL) problem of non‐reprocessability, a more sustainable solution of which has resolved to nascent vitrimers that can merge the robust material properties of thermosets and the reprocessability of thermoplastics. However, the lifecycle of vitrimers is still finite, as they often suffer from significant deterioration of mechanical performance following multiple reprocessing cycles, analogous to mechanical recycling, and they often show undesired creep under working conditions. To address these two key limitations, we have developed a cross‐linked semi‐crystalline polythioester with both dynamic covalent bonds and intrinsic crystallinity and chemical recyclability, affording a vitrimeric system that exhibits not only reprocessability and crystallinity‐restricted creep but also complete chemical recyclability to initial monomer by catalyzed depolymerization in solution or bulk. Therefore, reported herein is an “infinite” vitrimer system that is empowered with a facile closed‐loop EoL option once serial reprocessing deteriorates performance and the material can no longer meet the application requirements. Specifically, the polythioester vitrimer was constructed by copolymerization of a bicyclic thioester with a bis‐dithiolane, producing dynamically cross‐linked polythioesters with excellent property tunability, from amorphous to semi‐crystalline states and melting transition temperatures from 91 to 178 °C.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Oxides and Nitrides with Asymmetric Pore Structure from Block Copolymer Co–Assembly and Non–Solvent Induced Phase Separation

Materials combining an asymmetric pore structure with mesopores everywhere enable high surface area accessibility and fast transport, making them attractive for e.g., energy conversion and storage applications. Block copolymer (BCP)/inorganic precursor co-assembly combined with non-solvent induced phase separation (NIPS) provides a route to materials in which a mesoporous top surface layer merges into an asymmetric support with graded porosity along the film normal and mesopores throughout. Here, the co-assembly and non-solvent-induced phase separation (CNIPS) of poly(isoprene)-b-poly(styrene)-b-poly(4-vinylpyridine) (ISV) triblock terpolymer and titanium dioxide (TiO 2 ) sol-gel nanoparticlesare reported. Heat-treatment in air results in free-standing asymmetric porous TiO 2 . Further thermal processing in ammonia results in free-standing asymmetric porous titanium nitride (TiN). processing changes alter structural membrane characteristics is demonstrated. Changing the CNIPS evaporation time results in various membrane cross-sections ( finger-like to sponge-like). Further, oxide and nitride material composition, crystallinity, and porosity are tuned by varying thermal processing conditions. Finally, thermal processing condition effects are probed on phase-pure asymmetric nitride membrane behavior using cyclic voltammetry to elucidate their influence, e.g., on specific capacitance. Results provide further insights into improving asymmetric and porous materials for applications including energy conversion and storage, separation, and catalysis and motivate a further expansion of CNIPS to other (in)organic materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Controlling hydrocarbon transport and electron beam induced deposition on single layer graphene: Toward atomic scale synthesis in the scanning transmission electron microscope

Abstract Focused electron beam induced deposition (FEBID) is a direct write technique for depositing materials on a support substrate akin to 3D printing with an electron beam (e‐beam). Opportunities exist for merging this existing technique with aberration‐corrected scanning transmission electron microscopy to achieve molecular‐ or atomic‐level spatial precision. Several demonstrations have been performed using graphene as the support substrate. A common challenge that arises during this process is e‐beam‐induced hydrocarbon deposition, suggesting greater control over the sample environment is needed. Various strategies exist for cleaning graphene in situ. One of the most effective methods is to rapidly heat to high temperatures, for example, 600℃ or higher. While this can produce large areas of what appears to be atomically clean graphene, mobile hydrocarbons can still be present on the surfaces. Here, we show that these hydrocarbons are primarily limited to surface migration and demonstrate an effective method for interrupting the flow using e‐beam deposition to form corralled hydrocarbon regions. This strategy is effective for maintaining atomically clean graphene at high temperatures where hydrocarbon mobility can lead to substantial accumulation of unwanted e‐beam deposition.

36 MATERIALS SCIENCE↗
DOE OSTI2024

A novel digital lifecycle for Material‐Process‐Microstructure‐Performance relationships of thermoplastic olefins foams manufactured via supercritical fluid assisted foam injection molding

Abstract This research significantly enhances the applicability of thermoplastic olefins (TPOs) in the automotive industry using supercritical N 2 as a physical foaming agent, effectively addressing the limitations of traditional chemical agents. It merges experimental results with simulations to establish detailed material‐process‐microstructure‐performance (MP2) relationships, targeting 5–20% weight reductions. This innovative approach labeled digital lifecycle (DLC) helps accurately predict tensile, flexural, and impact properties based on the foam microstructure, along with experimentally demonstrating improved paintability. The study combines process simulations with finite element models to develop a comprehensive digital model for accurately predicting mechanical properties. Our findings demonstrate a strong correlation between simulated and experimental data, with about a 5% error across various weight reduction targets, marking significant improvements over existing analytical models. This research highlights the efficacy of physical foaming agents in TPO enhancement and emphasizes the importance of integrating experimental and simulation methods to capture the underlying foaming mechanism to establish material‐process‐microstructure‐performance (MP2) relationships. Highlights Establishes a material‐process‐microstructure‐performance (MP2) for TPO foams Sustainably produces TPO foams using supercritical (ScF) N 2 with 20% lightweighting Shows enhanced paintability for TPO foam improved surface aesthetics Digital lifecycle (DLC) that predicts both foam microstructure and properties DLC maps process effects & microstructure onto FEA mesh for precise prediction

Engineering↗
DOE OSTI2021

A causal data fusion method for the general exposure and outcome

Abstract With the advent of the big data era, the need to combine multiple individual data sets to draw causal effects arises naturally in many medical and biological applications. Especially each data set cannot measure enough confounders to infer the causal effect of an exposure on an outcome. In this article, we extend the method proposed by a previous study to causal data fusion of more than two data sets without external validation and to a more general (continuous or discrete) exposure and outcome. Theoretically, we obtain the condition for identifiability of exposure effects using multiple individual data sources for the continuous or discrete exposure and outcome. The simulation results show that our proposed causal data fusion method has unbiased causal effect estimate and higher precision than traditional regression, meta‐analysis and statistical matching methods. We further apply our method to study the causal effect of BMI on glucose level in individuals with diabetes by combining two data sets. Our method is essential for causal data fusion and provides important insights into the ongoing discourse on the empirical analysis of merging multiple individual data sources.

Li, Hongkai↗
DOE OSTI2022

In Situ Growth of Crystalline and Polymer-Incorporated Amorphous ZIFs in Polybenzimidazole Achieving Hierarchical Nanostructures for Carbon Capture

We report mixed matrix materials (MMMs) hold great potential for membrane gas separations by merging nanofillers with unique nanostructures and polymers with excellent processability. In situ growth of the nanofillers is adapted to mitigate interfacial incompatibility to avoid the selectivity loss. Surprisingly, functional polymers have not been exploited to co-grow the nanofillers for membrane applications. Herein, in situ synergistic growth of crystalline zeolite imidazole framework-8 (ZIF-8) in polybenzimidazole (PBI), creating highly porous structures with high gas permeability, is demonstrated. More importantly, PBI contains benzimidazole groups (similar to the precursor for ZIF-8, i.e., 2-methylimidazole) and induces the formation of amorphous ZIFs, enhancing interfacial compatibility and creating highly size-discriminating bottlenecks. For instance, the formation of 15 mass% ZIF-8 in PBI improves H- 2 permeability and H- 2 /CO 2 selectivity by approximate to 100% at 35 degrees C, breaking the permeability/selectivity tradeoff. This work unveils a new platform of MMMs comprising functional polymer-incorporated amorphous ZIFs with hierarchical nanostructures for various applications.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2026

Metalloborophenes: Structural Diversity and Emerging Properties of Metal–Boron Two‐Dimensional Frameworks

Metalloborophenes, an emerging subclass of 2D materials, have attracted growing attention owing to their exceptional structural diversity and highly tunable electronic and magnetic properties. Constructed from vacancy‐rich borophene frameworks stabilized by electron donation from incorporated metal atoms, metalloborophenes merge the chemical versatility of boron with the functional richness of metal dopants. The first experimental realization of Cu–borophene nanoribbons in 2024 marked a pivotal advance, confirming long‐standing theoretical predictions and revitalizing interest in this new frontier of boron‐based 2D chemistry. Despite this progress, most studies to date remain conceptual and theoretical, constrained by challenges in scalable synthesis, dopant precision, and substrate control. Computational investigations have revealed a broad landscape of stable metalloborophene structures, exhibiting metallic, semiconducting, and magnetic behavior across diverse dopant families, including alkali, alkaline‐earth, transition, and lanthanide elements. These tunable characteristics open promising avenues for applications in spintronics, catalysis, and hydrogen storage. This review provides a comprehensive overview of metalloborophenes, emphasizing the interplay between structure, stability, and functionality, and outlining future directions toward bridging predictive modeling with experimental realization of this rapidly evolving class of 2D materials.

2D materials↗
DOE OSTI2024

In situ Synchrotron X‐ray Metrology Boosted by Automated Data Analysis for Real‐time Monitoring of Cathode Calcination

Abstract Synchrotron X‐ray‐based in situ metrology is advantageous for monitoring the synthesis of battery materials, offering high throughput, high spatial and temporal resolution, and chemical sensitivity. However, the rapid generation of massive data poses a challenge to on‐site, on‐the‐fly analysis needed for real‐time process monitoring. Here, a weighted lagged cross‐correlation (WLCC) similarity approach is presented for automated data analysis, which merges with in situ synchrotron X‐ray diffraction metrology to monitor the calcination process of the archetypal nickel‐based cathode, LiNiO 2 . The WLCC approach, incorporating variables that account for peak shifts and width changes associated with structural transformations, enables rapid extraction of phase progression within 10 seconds from tens of diffraction patterns. Details are captured, from initial precursors to intermediates and the final layered LiNiO 2 , providing information for agile on‐site adjustments during experiments and complementing post hoc diffraction analysis by offering insights into early‐stage phase nucleation and growth. Expanding this data‐powered platform paves the way for real time calcination process monitoring and control, which is pivotal to quality control in battery cathode manufacturing.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Experimental and Computational Insights into the Structural Dynamics of the Fc Fragment of IgG1 Subtype from Biosimilar VEGF‐Trap

The constant fragment (Fc) of the immunoglobulin G1 (IgG1) subtype is increasingly recognized as a crucial scaffold in the development of advanced therapeutics due to its enhanced specificity, efficacy, and extended half‐life. A prime example is VEGF‐Trap (Aflibercept), a recombinant fusion protein that merges the Fc region of the IgG1 subtype with the binding domains of vascular endothelial growth factor receptors (VEGFR)‐1 and VEGFR‐2. The Fc region's role in N‐glycosylation is particularly important, as it significantly influences protein stability. Herein, the first near‐physiological temperature structures of the N‐glycan‐bound Fc fragment of IgG1 subtype from a biosimilar VEGF‐Trap are presented, determined using the SPring‐8 Angstrom Compact free electron LAser (SACLA) and the Turkish Light Source (Turkish DeLight). Comparative analysis with cryogenic structures, including existing data, reveals alternate conformations within the glycan‐binding pocket. Furthermore, molecular dynamics simulations indicate the presence of a high degree of structural plasticity, explaining how the protein adapts its structure through conformational changes. The observed structural fluctuations/conformational changes demonstrate the effect of N‐glycans on protein stability. These findings offer new insights into the molecular basis of Fc‐mediated functions and provide valuable information for the design of next‐generation therapeutics.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Phoenix: A Scalable Streaming Hypergraph Analysis Framework

We present Phoenix, a scalable hypergraph analytics framework for data analytics and knowledge discovery that was implemented on the leadership class computing platforms at Oak Ridge National Laboratory (ORNL). Our software framework comprises a distributed implementation of a streaming server architecture which acts as a gateway for various hypergraph generators/external sources to connect. Phoenix has the capability to utilize diverse hypergraph generators, including HyGen, a very large-scale hypergraph generator developed by ORNL. Phoenix incorporates specific algorithms for efficient data representation by exploiting hidden structures of the hypergraphs. Our experimental results demonstrate Phoenix’s scalable and stable performance on massively parallel computing platforms. Phoenix’s superior performance is due to the merging of high-performance computing with data analytic.

Kurte, Kuldeep↗