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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 523 records · Page 29
All sourcesNASA NTRSDOE OSTI
DOE OSTI2011

Kernel principal component analysis for stochastic input model generation

Highlights: {yields} KPCA is used to construct a reduced order stochastic model of permeability. {yields} A new approach is proposed to solve the pre-image problem in KPCA. {yields} Polynomial chaos is used to provide a parametric stochastic input model. {yields} Flow in porous media with channelized permeability is considered. - Abstract: Stochastic analysis of random heterogeneous media provides useful information only if realistic input models of the material property variations are used. These input models are often constructed from a set of experimental samples of the underlying random field. To this end, the Karhunen-Loeve (K-L) expansion, also known as principal component analysis (PCA), is the most popular model reduction method due to its uniform mean-square convergence. However, it only projects the samples onto an optimal linear subspace, which results in an unreasonable representation of the original data if they are non-linearly related to each other. In other words, it only preserves the first-order (mean) and second-order statistics (covariance) of a random field, which is insufficient for reproducing complex structures. This paper applies kernel principal component analysis (KPCA) to construct a reduced-order stochastic input model for the material property variation in heterogeneous media. KPCA can be considered as a nonlinear version of PCA. Through use of kernel functions, KPCA further enables the preservation of higher-order statistics of the random field, instead of just two-point statistics as in the standard Karhunen-Loeve (K-L) expansion. Thus, this method can model non-Gaussian, non-stationary random fields. In this work, we also propose a new approach to solve the pre-image problem involved in KPCA. In addition, polynomial chaos (PC) expansion is used to represent the random coefficients in KPCA which provides a parametric stochastic input model. Thus, realizations, which are statistically consistent with the experimental data, can be generated in an efficient way. We showcase the methodology by constructing a low-dimensional stochastic input model to represent channelized permeability in porous media.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2021

A Systematic Approach to Developing Paths Towards Airborne Vehicle Autonomy

Advanced Air Mobility (AAM) demands greater levels of aircraft autonomy than are currently implemented today. To enable this requirement, novel aircraft functionalities and technologies as well as supporting airworthiness and operational regulations are required. A structured method to derive a comprehensive list of aircraft level decision-making functions is defined and applied. The resulting function set is programmed into an ontology, and enables autonomous decision-making through the application of a defined decision-making process. Paths to implementing the functions are generated by applying a structured four step method. By surveying current technologies, airspace, procedures and regulations, the paths generation method defines incremental paths to autonomy that the current regulatory environment can support. Opportunities to implement novel technologies and functions are identified, and regulatory mechanisms supporting their implementation are underscored. The analysis provides the tools to further define aircraft functions and paths to their implementation, while demonstrating that for particular use cases, aircraft autonomy is attainable in the medium-term.

Paul Vajda↗
DOE OSTI2025

Entanglement Structure of Non-Gaussian States and How to Measure It

Rapidly growing capabilities of quantum simulators to probe quantum many-body phenomena require new methods to characterize increasingly complex states. Here, we present a protocol that constrains quantum states using experimentally measured correlation functions. This method enables measurement of a quantum state’s entanglement structure, opening a new route to study entanglement-related phenomena. Our approach extends Gaussian state parameterizations by systematically incorporating higher-order correlations. We show the protocol’s usefulness in conjunction with current and forthcoming experimental capabilities, focusing on weakly interacting fermions as a proof of concept. Here, the lowest nontrivial expansion quantitatively predicts early time thermalization dynamics, including signaling the onset of quantum chaos indicated by the entanglement Hamiltonian.

Fermi gases↗
DOE OSTI2020

Boosting the Performance of Plug-and-Play Priors via Denoiser Scaling

Plug-and-play priors (PnP) is an image reconstruction framework that utilizes an image denoiser as an imaging prior. Unlike traditional regularized inversion, PnP does not require the prior to be expressible in the form of a regularization function. This flexibility enables PnP algorithms to exploit the most effective image denoisers, leading to their state-of-the-art performance in various imaging tasks. However, many powerful denoisers, such as the ones based on convolutional neural networks (CNNs), do not have tunable parameters that would allow controlling their influence within PnP. To address this issue, in this paper, we introduce a scaling parameter that adjusts the magnitude of the denoiser input and output. We theoretical justify the denoiser scaling from the perspectives of proximal optimization, statistical estimation, and consensus equilibrium. Finally, we provide numerical experiments demonstrating the ability of denoiser scaling to systematically improve the performance of PnP for denoising CNN priors that do not have explicitly tunable parameters.

Boosting↗
DOE OSTI2022

Silicon nitride stress-optic microresonator modulator for optical control applications

Modulation-based control and locking of lasers, filters and other photonic components is a ubiquitous function across many applications that span the visible to infrared (IR), including atomic, molecular and optical (AMO), quantum sciences, fiber communications, metrology, and microwave photonics. Today, modulators used to realize these control functions consist of high-power bulk-optic components for tuning, sideband modulation, and phase and frequency shifting, while providing low optical insertion loss and operation from DC to 10s of MHz. In order to reduce the size, weight and cost of these applications and improve their scalability and reliability, modulation control functions need to be implemented in a low loss, wafer-scale CMOS-compatible photonic integration platform. The silicon nitride integration platform has been successful at realizing extremely low waveguide losses across the visible to infrared and components including high performance lasers, filters, resonators, stabilization cavities, and optical frequency combs. Yet, progress towards implementing low loss, low power modulators in the silicon nitride platform, while maintaining wafer-scale process compatibility has been limited. Here we report a significant advance in integration of a piezo-electric (PZT, lead zirconate titanate) actuated micro-ring modulation in a fully-planar, wafer-scale silicon nitride platform, that maintains low optical loss (0.03 dB/cm in a 625 µm resonator) at 1550 nm, with an order of magnitude increase in bandwidth (DC - 15 MHz 3-dB and DC - 25 MHz 6-dB) and order of magnitude lower power consumption of 20 nW improvement over prior PZT modulators. The modulator provides a >14 dB extinction ratio (ER) and 7.1 million quality-factor (Q) over the entire 4 GHz tuning range, a tuning efficiency of 162 MHz/V, and delivers the linearity required for control applications with 65.1 dB·Hz 2/3 and 73.8 dB·Hz 2/3 third-order intermodulation distortion (IMD3) spurious free dynamic range (SFDR) at 1 MHz and 10 MHz respectively. We demonstrate two control applications, laser stabilization in a Pound-Drever Hall (PDH) lock loop, reducing laser frequency noise by 40 dB, and as a laser carrier tracking filter. This PZT modulator design can be extended to the visible in the ultra-low loss silicon nitride platform with minor waveguide design changes. This integration of PZT modulation in the ultra-low loss silicon nitride waveguide platform enables modulator control functions in a wide range of visible to IR applications such as atomic and molecular transition locking for cooling, trapping and probing, controllable optical frequency combs, low-power external cavity tunable lasers, quantum computers, sensors and communications, atomic clocks, and tunable ultra-low linewidth lasers and ultra-low phase noise microwave synthesizers.

Wang, Jiawei (ORCID:0000000257965220)↗
DOE OSTI2011

Cesium Delivery System for Negative Ion Source at IPR

The technique of surface production of negative ions using cesium, Cs, has been efficiently exploited over the years for producing negative ion beams with increased current densities from negative ion sources used on neutral beam lines. Deposition of Cs on the source walls and the plasma grid lowers the work function and therefore enables a higher yield of H{sup -}, when hydrogen particles (H and/or H{sub x}{sup +}) strike these surfaces.A single driver RF based (100 kW, 1 MHz) negative ion source test bed, ROBIN, is being set up at IPR under a technical collaboration between IPR and IPP, Germany. The optimization of the Cs oven design to be used on this facility as well as multidriver sources is underway. The characterization experiments of such a Cs delivery system with a 1 g Cs inventory have been carried out using surface ionization technique. The experiments have been carried by delivering Cs into a vacuum chamber without plasma. The linear motion of the surface ionization detector, SID, attached with a linear motion feedthrough allows measuring the angular distribution of the Cs coming out of the oven. Based on the experimental results, a Cs oven for ROBIN has been proposed. The Cs oven design and experimental results of the prototype Cs oven are reported and discussed in the paper.

43 PARTICLE ACCELERATORS↗
DOE OSTI2026

Vibrational and electronic properties of Np 2 O 5 from experimental spectroscopy and first principles calculations

High-valence actinide oxides are critical to understanding the behavior of 5f-electrons, yet their structural and electronic properties remain poorly understood due to challenges in synthesis and handling. We report the first Raman spectroscopic study of single-crystalline Np 2 O 5 and the first scanning tunneling spectroscopy (STS) measurement on any neptunium-containing material. Hydrothermally synthesized crystals were structurally verified by X-ray diffraction. Raman spectra revealed sharply resolved vibrational features, including previously unreported low-frequency modes. STS measurements revealed a band gap of 1.5 eV. Density functional theory (DFT) enables vibrational mode assignments, reveals neptunium-dominated low-frequency phonons, oxygen-dominated high-frequency modes, and predicts an indirect band gap of 1.68 eV. This predicted value is in excellent agreement with the experimentally measured STS gap. This combined Raman, DFT, and STS approach provides a robust framework for correlating lattice dynamics and electronic structure in actinide materials, providing benchmark data for Np 2 O 5 , and opening new avenues for probing structure–property relationships in complex f-electron materials.

36 - MATERIALS SCIENCE↗
DOE OSTI2026

Identifying mechanistic differences between co-fed CO 2 hydrogenation and reactive CO 2 capture using Ru and Pd dual function materials

Dual function materials (DFMs) enable reactive carbon capture (RCkeC), an intensified approach to carbon dioxide capture and utilization for cost and energy input reductions. Yet, there is a fundamental lack of understanding of mechanisms around CO 2 adsorption and subsequent conversion on these materials, hindering further development. Herein, we investigated several supported alkaline metal oxides for their CO 2 adsorption characteristics to find that Na/Al 2 O 3 had the highest CO 2 adsorption capacity, accompanied by a variety of CO 2 adsorption geometries as identified by in situ DRIFTS and computational modeling. The addition of catalytic metals (Ru, Pd) increased the adsorption capacity of Na/Al 2 O 3 without altering binding modes. In the subsequent reactive desorption step, acetate and formate intermediates were observed. Notably, this mechanistic investigation identified that the formation of acetate species was unique to RCC on a DFM, as these species were not observed in co-fed hydrogenation over the DFM or RCC over a Na-free catalyst.

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

Virus‐Based Pyroelectricity

Abstract The first observation of heat‐induced electrical potential generation on a virus and its detection through pyroelectricity are presented. Specifically, the authors investigate the pyroelectric properties of the M13 phage, which possesses inherent dipole structures derived from the noncentrosymmetric arrangement of the major coat protein (pVIII) with an α‐helical conformation. Unidirectional polarization of the phage is achieved through genetic engineering of the tail protein (pIII) and template‐assisted self‐assembly techniques. By modifying the pVIII proteins with varying numbers of glutamate residues, the structure‐dependent tunable pyroelectric properties of the phage are explored. The most polarized phage exhibits a pyroelectric coefficient of 0.13 µC m −2 °C −1 . Computational modeling and circular dichroism (CD) spectroscopy analysis confirm that the unfolding of α‐helices within the pVIII proteins leads to changes in phage polarization upon heating. Moreover, the phage is genetically modified to enable its pyroelectric function in diverse chemical environments. This phage‐based approach not only provides valuable insights into bio‐pyroelectricity but also opens up new opportunities for the detection of various viral particles. Furthermore, it holds great potential for the development of novel biomaterials for future applications in biosensors and bioelectric materials.

Kim, Han↗
DOE OSTI2025

Nanometer Resolution Structure‐Emission Correlation of Individual Quantum Emitters via Enhanced Cathodoluminescence in Twisted Hexagonal Boron Nitride

Understanding the atomic structure of quantum emitters, often originating from point defects or impuritie, is essential for designing and optimizing materials for quantum technologies such as quantum computing, communication, and sensing. Despite the availability of atomic-resolution scanning transmission electron microscopy and nanoscale cathodoluminescence microscopy, experimentally determining the atomic structure of individual emitters is challenging due to the conflicting needs for thick samples to generate strong cathodoluminescence signals and thin samples for structural analysis. To overcome this challenge, significantly enhanced cathodoluminescence at twisted interfaces is leveraged to achieve sub-nanometer localization precision for the first time in mapping individual quantum emitters in carbon-implanted hexagonal boron nitride. This unprecedent spatial sensitivity, together with correlative electron energy loss spectroscopy quantitative scanning transmission electron microscopy imaging, and first principles density functional theory calculations, enables the identification of the atomic structure of the 440 nm blue emitter in hexagonal boron nitride as a substituted vertical carbon dimer. Building on the atomic structure insights, nanoscale spatially precise creation of blue emitters is demonstrated by electron beam irradiation of carbon-coated hexagonal boron nitride. This advancement in correlating atomic structures with optical properties lays the foundation for a deeper understanding and precise engineering of quantum emitters, significantly advancing the development of cutting-edge quantum information technologies.

2D material↗
DOE OSTI2025

Refining T c Prediction in Hydrides via Symbolic‐Regression‐Enhanced Electron‐Localization‐Function‐Based Descriptors

Hydrogen‐based materials are able to possess extremely high superconducting critical temperatures, T c s , due to hydrogen's low atomic mass and strong electron–phonon interaction. Recently, a descriptor based on the Electron Localization Function (ELF) has enabled the rapid estimation of the T c of hydrogen‐containing compounds from electronic networking properties, but its applicability has been limited by the small size and homogeneity of the training dataset used. Herein, the model is re‐examined, compiling a publicly available combined dataset of 244 binary and ternary hydride superconductors. The analysis shows that though ELF‐based networking remains a valuable descriptor, its predictive power declines with increasing compositional complexity. However, by introducing the molecularity index, defined as the highest value of the ELF at which two hydrogen atoms connect, and applying symbolic regression, the accuracy of the predictions can be substantially enhanced. These results establish a more robust framework for assessing superconductivity in hydride materials, facilitating accelerated screening of novel candidates through integration with crystal structure prediction methods or high‐throughput searches.

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

Exploring the Vibrational Side of Spin-Phonon Coupling in Single-Molecule Magnets via 161 Dy Nuclear Resonance Vibrational Spectroscopy

Synchrotron-based nuclear resonance vibrational spectroscopy (NRVS) using the Mossbauer isotope 161 Dy has been employed for the first time to study the vibrational properties of a single-molecule magnet (SMM) incorporating Dy III , namely [Dy(Cy3PO)(2)(H2O)(5)]Br-3•2 (Cy3PO)•2 H2O•2 EtOH. The experimental partial phonon density of states (pDOS), which includes all vibrational modes involving a displacement of the Dy III ion, was reproduced by means of simulations using density functional theory (DFT), enabling the assignment of all intramolecular vibrational modes. This study proves that 161 Dy NRVS is a powerful experimental tool with significant potential to help to clarify the role of phonons in SMMs.

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

Chemical–Switching Strategy for Synthesis and Controlled Release of Norcantharimides from a Biomass–Derived Chemical

Catalytic strategies were developed to synthesize and release chemicals for applications in fine chemicals, such as drugs and polymers, from a biomass-derived chemical, 5-hydroxymethyl furfural (HMF). The combination of the diene and aldehyde functionalities in HMF enabled catalytic production of acetalized HMF derivatives with diol or epoxy reactants to allow reversible synthesis of norcantharimide derivatives upon Diels-Alder reaction with maleimides. Reverse-conversion of the acetal group to an aldehyde yielded mismatches of the molecular orbitals in norcantharimides to trigger retro Diels-Alder reaction at ambient temperatures and released reactants from the coupled molecules under acidic conditions. In conclusion, these strategies provide for the facile synthesis and controlled release of high-value chemicals.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

3D Printing Amorphous Polysiloxane Terpolymers via Vat Photopolymerization

Abstract Photocuring and vat photopolymerization (VP) additive manufacturing (AM) is reported for two families of fully amorphous poly(dimethyl siloxane) (PDMS) terpolymers containing either diphenylsiloxy (DiPhS) or diethylsiloxy (DiEtS) repeating units. A thiol‐functionalized PDMS crosslinker enables rapid crosslinking in air using efficient thiol–ene addition. Differential scanning calorimetry and dynamic mechanical analysis (DMA) confirm the absence of crystallinity for the DiPhS‐containing systems, while DMA shows a rubbery plateau extending to greater than 200 °C for the DiEtS‐containing system. VP‐AM of both photopolymer systems afford well‐defined 3D geometries, including high aspect ratio structures, which demonstrate feasibility of these photopolymers for the 3D printing of unique geometric objects that require elastomeric performance to temperatures as low as −120 °C.

Sirrine, Justin M.↗
DOE OSTI2021

NanoSIP: NanoSIMS Applications for Microbial Biology

High-resolution imaging with secondary ion mass spectrometry (nanoSIMS) has become a standard method in systems biology and environmental biogeochemistry and is broadly used to decipher ecophysiological traits of environmental microorganisms, metabolic processes in plant and animal tissues, and cross-kingdom symbioses. When combined with stable isotope-labeling—an approach we refer to as nanoSIP—nanoSIMS imaging offers a distinctive means to quantify net assimilation rates and stoichiometry of individual cell-sized particles in both low- and high-complexity environments. While the majority of nanoSIP studies in environmental and microbial biology have focused on nitrogen and carbon metabolism (using 15 N and 13 C tracers), multiple advances have pushed the capabilities of this approach in the past decade. The development of a high-brightness oxygen ion source has enabled high-resolution metal analyses that are easier to perform, allowing quantification of metal distribution in cells and environmental particles. New preparation methods, tools for automated data extraction from large data sets, and analytical approaches that push the limits of sensitivity and spatial resolution have allowed for more robust characterization of populations ranging from marine archaea to fungi and viruses. Further, NanoSIMS studies continue to be enhanced by correlation with orthogonal imaging and ‘omics approaches; when linked to molecular visualization methods, such as in situ hybridization and antibody labeling, these techniques enable in situ function to be linked to microbial identity and gene expression. Here we present an updated description of the primary materials, methods, and calculations used for nanoSIP, with an emphasis on recent advances in nanoSIMS applications, key methodological steps, and potential pitfalls.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2018

Sequential Infiltration Synthesis of Al 2 O 3 in Polyethersulfone Membranes

We report the sequential infiltration synthesis (SIS) of aluminum oxide (Al 2 O 3 ) into polyethersulfone (PES) ultrafiltration (UF) membranes to form hybrid nanocomposites. SIS relies on chemical interactions between precursor vapors and polymer functional groups, and enables nucleation and growth of inorganic materials to controlled depth. Using in situ Fourier-transform infrared spectroscopy and ellipsometry measurements, we demonstrate that trimethylaluminum associates with the sulfonyl groups in PES, extending the library of SIS-modified polymer nanocomposites to a previously undescribed polymer system and new application space: PES UF membranes. Depth-profiled x-ray photoelectron spectroscopy showed that the trimethylaluminum purge time dictates the extent of Al 2 O 3 infiltration. Energy dispersive spectroscopy revealed the differences between SIS and atomic layer deposition in the membranes. Furthermore, this work demonstrates the viability of SIS to access the entire macroporous volume of PES UF membranes.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Cellulose-MOFs hybrid materials: Chemistry and mechanism of applications in biomedical - A review

Rising costs and performance limits of modern biomedical materials motivate the search for advanced, biocompatible alternatives. Cellulose-based metal-organic frameworks (cellulose-MOFs) emerge as distinctive hybrids combining renewable polymer chemistry with tunable porous architectures, enabling uncommon structure–function relationships. Their large surface area, controllable pore size, adaptable functional groups, and efficient host–guest interactions underpin diverse biomedical functions. Till now, no comprehensive, application-focused review has systematically summarized cellulose-MOFs synthesis for biomedical applications. This review critically analyzes cellulose-MOFs, emphasizing mechanistic links between chemistry, synthesis routes, interfacial interactions, and biomedical performance, rather than cataloging applications alone. Antibacterial action, targeted drug delivery, and sensing/biosensing are discussed through comparative insights. The article identifies unresolved challenges and proposes future research pathways to rationally design next-generation cellulose-MOFs systems, guiding researchers and clinicians alike.

Biomedical↗
DOE OSTI2015

Clinical Validation of 4-Dimensional Computed Tomography Ventilation With Pulmonary Function Test Data

Purpose: A new form of functional imaging has been proposed in the form of 4-dimensional computed tomography (4DCT) ventilation. Because 4DCTs are acquired as part of routine care for lung cancer patients, calculating ventilation maps from 4DCTs provides spatial lung function information without added dosimetric or monetary cost to the patient. Before 4DCT-ventilation is implemented it needs to be clinically validated. Pulmonary function tests (PFTs) provide a clinically established way of evaluating lung function. The purpose of our work was to perform a clinical validation by comparing 4DCT-ventilation metrics with PFT data. Methods and Materials: Ninety-eight lung cancer patients with pretreatment 4DCT and PFT data were included in the study. Pulmonary function test metrics used to diagnose obstructive lung disease were recorded: forced expiratory volume in 1 second (FEV1) and FEV1/forced vital capacity. Four-dimensional CT data sets and spatial registration were used to compute 4DCT-ventilation images using a density change–based and a Jacobian-based model. The ventilation maps were reduced to single metrics intended to reflect the degree of ventilation obstruction. Specifically, we computed the coefficient of variation (SD/mean), ventilation V20 (volume of lung ≤20% ventilation), and correlated the ventilation metrics with PFT data. Regression analysis was used to determine whether 4DCT ventilation data could predict for normal versus abnormal lung function using PFT thresholds. Results: Correlation coefficients comparing 4DCT-ventilation with PFT data ranged from 0.63 to 0.72, with the best agreement between FEV1 and coefficient of variation. Four-dimensional CT ventilation metrics were able to significantly delineate between clinically normal versus abnormal PFT results. Conclusions: Validation of 4DCT ventilation with clinically relevant metrics is essential. We demonstrate good global agreement between PFTs and 4DCT-ventilation, indicating that 4DCT-ventilation provides a reliable assessment of lung function. Four-dimensional CT ventilation enables exciting opportunities to assess lung function and create functional avoidance radiation therapy plans. The present work provides supporting evidence for the integration of 4DCT-ventilation into clinical trials.

62 RADIOLOGY AND NUCLEAR MEDICINE↗