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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 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Co-design of a wave energy converter through bi-conjugate impedance matching

As with other oscillatory power conversion systems, the design of wave energy converters can be understood as an impedance matching problem. By representing the wave energy converter as a multi-port network, two separate but related impedance matching conditions can be established. Satisfying these conditions maximizes power transfer to the load. In practice, these impedance matching conditions may be used to influence the design of the system (including the hull, power take-off, controller, mooring, etc.). To this end, this paper considers some example applications of wave energy converter design with the help of the impedance matching framework.

WEC↗
DOE OSTI2021

Recent advances in the mechanical characterization of shales at nano-to micro-scales: A review

Understanding geomechanical properties of shales, such as stiffness properties and fracture toughness, is important in different areas of petroleum industry-related activities. Nanoscale to microscale experiments on shale samples require a much smaller sample compared to macroscale experiments. This is a major advantage because irregularly-shaped drill cuttings from shales can be used for experimental analyses, such as nanoindentation or atomic force microscopy (AFM). However, characterization of mechanical properties at the nano- to micro-scale is a relatively new addition to classical geomechanical experiments on shales, and there is still a lack of both fundamental knowledge and standard procedures for conducting experiments at this scale. The theoretical principles of nanoindentation-based (Gridded Nanoindentation and Modulus Mapping) and AFM-based experimental methods (PeakForce QNMTM and AFM-IR), a review of the literature results and the major findings are explained in Sections 2 and 3, respectively. These experimental techniques are compared in Section 4. Overall, nanoindentation experiments reveal the anisotropy of organic matter (OM)-rich shales at the nanoscale, and it is shown that gridded nanoindentation is capable of characterizing different minerals with respect to their stiffness properties. The capability of AFM (PeakForce QNMTM) to differentiate between different minerals within OM-rich shales with distinct mechanical properties, in particular stiffness, is also demonstrated. It is shown that AFM-based methods are more straightforward than gridded-nanoindentation to characterize OM-rich shales based on the stiffness of different constituent minerals of OM-rich shales, but nanoindentation can apply higher loads than AFM-based methods. Therefore, they can measure creep properties and fracture toughness of OM-rich shales. Here, it is shown that the OM is the most compliant part of the OM-rich shales, but it is still unclear if thermal maturation has an impact on the stiffness of OM. It is necessary to investigate if there is a relationship between the OM type (kerogen, bitumen, etc.) and mechanical properties such as Young’s modulus and Creep rate.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Fully implicit crystal plasticity models representing orientations with modified Rodrigues parameters

Here, this work describes a crystal plasticity formulation combining several mathematical, numerical, and implementation choices to produce a highly efficient model. Specifically, the key choices in the implementation are (1) representing orientations with modified Rodrigues parameters, (2) implementing a fully coupled implicit time integration for the elastic stretch, the crystal orientations, and the model internal variables, (3) implementing the model in the NEML2 constitutive modeling framework, based on PyTorch, to vectorize the calculations and port the computation to GPUs and other hardware accelerators, and (4) an exact implementation of the consistent tangent matrix, even for arbitrary coupling to other field variables beyond the displacements, like temperature, neutron fluence, etc. The first two features of the model are, to our knowledge, novel. The paper considers each of these choices individually as well as the final model as a whole. This includes a full description of modified Rodrigues parameters, their advantages over other representations of orientations, the mathematical formulae and tools required to implement a model with modified Rodrigues parameters, and a detailed description of the geometry of the space of modified Rodrigues parameters (in an appendix). It also includes a description of a fully implicit time integration scheme for the orientations and the advantages in representing orientations with modified Rodrigues parameters in implementing such a model. The work then assess, via numerical examples, the advantages of fully coupled implicit time integration versus more common decoupled and explicit time integration schemes. These studies demonstrate the computational advantages of fully coupled integration versus other time integration algorithms, though the performance of the competing models depends on the complexity of the underlying single crystal model. The study concludes by demonstrating that the choice of time integration method affects the sharpness of the predicted texture, with explicit methods for integrating the orientations overestimating texture sharpness and implicit methods underestimating texture sharpness.

Crystal plasticity↗
DOE OSTI2023

A review of crosstalk polymorphic circuits and their scalability

Using a control variable, the functionality of Polymorphic circuits can be modified, making them adaptable and useful for reconfiguring circuit behavior — all the way from gate level to system level. State-of-the art polymorphic circuits are based on custom non-linear circuit design or emerging devices such as ambipolar FET, configurable magnetic devices etc. While some of these approaches are inefficient in performance, others involve exotic devices. The Crosstalk computing based polymorphic circuits offer a fresh perspective. In Crosstalk, the interconnect interference between nanoscale metal lines is intentionally engineered to exhibit the programmable Boolean logic behavior. This approach relies on the coupling between metal lines and not on the transistors for computing, resulting in better scalability, security by obscurity, and fault tolerance by reconfiguration. Our novel approach is backed by the mathematical formulation that conveys the rationale to generalize and achieve a wide variety of polymorphic circuits. Our experiments, including design, simulation, and Power Performance Area (PPA) characterization results indicate that crosstalk circuits provide significant improvement in transistor count (about 3x), switching energy (2x), and speed (1.5x) for polymorphic logic circuits. In the best-case scenario, the transistor count reduction is 5x. This paper presents Crosstalk computing’s fundamentals, polymorphism and the scalability aspects to compete/co-exist with CMOS for digital logic implementations below 10 nm. Our scalability study uses Open Source 7 nm PDK, considers all process variation aspects and accommodates worst-case scenarios. The study results for various benchmark circuits show that the Crosstalk technology is a viable alternative to CMOS for digital logic implementations below 10 nm, having 48% density, 57% power, and 10% performance gains over equivalent CMOS counterparts. Finally, we compare Crosstalk Polymorphic Circuit design technique with similar approaches described in related works and discuss its features and constraints.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Interfacial interactions between polymers and selective adsorbents influence ion transport properties of boron scavenging ion-exchange membranes

The recent emergence of adsorptive ion-exchange membranes (IEMs), designed by the synergistic integration of highly selective porous aromatic frameworks (PAFs) with ion-exchange polymers, has enabled simultaneous desalination and targeted removal of specific solutes (e.g., mercury, iron, boron, etc.). While the addition of highly selective PAFs to IEMs yields membranes with entirely new functions, PAF-polymer interactions, and the effects of such interactions on ion transport properties of the membranes, are not well understood. In this study, we developed cross-linked adsorptive cation- and anion-exchange membranes (CEMs and AEMs) for simultaneous desalination and boron removal via in-situ formation of the cross-linked polymer network around the boron selective PAF particles. Here we systematically investigated the influence of PAF loading level on PAF-polymer interactions as well as the equilibrium and transport properties of the adsorptive IEMs. The interactions between the PAF and the ion-exchange polymer matrix differed for the CEMs and AEMs due to differences in the fixed charge group chemistry. Notably, the sulfonate groups of the CEMs can form hydrogen bonds with the hydroxyl groups of the PAF, while the quaternary ammonium groups in the AEMs cannot. These differences in interfacial interactions did not significantly impact counter-ion transport across the adsorptive IEMs but had a significant influence on co-ion transport, which affected the counter-ion/co-ion selectivity of the membranes. The selectivity of the adsorptive CEMs decreased while that of the adsorptive AEMs increased with PAF loading level. The results of this study underscore the importance of controlling interfacial interactions when designing adsorptive IEMs for simultaneous water desalination and solute capture and recovery.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Bacterial effectors mimicking ubiquitin-proteasome pathway tweak plant immunity

Plant pathogenic Gram-negative bacteria evade the host plant immune system by secreting Type III (T3E) and Type IV effector (T4E) proteins into the plant cytoplasm. Mostly T3Es are secreted into the plant cells to establish pathogenicity by affecting the vital plant process viz. metabolic pathways, signal transduction and hormonal regulation. Ubiquitin-26S proteasome system (UPS) exists as one of the important pathways in plants to control plant immunity and various cellular processes by employing several enzymes and enzyme components. Pathogenic and non-pathogenic bacteria are found to secrete effectors into plants with structural and/or functional similarity to UPS pathway components like ubiquitin E3 ligases, F-box domains, cysteine proteases, inhibitor of host UPS or its components, etc. The bacterial effectors mimic UPS components and target plant resistance proteins for degradation by proteasomes, thereby taking control over the host cellular activities as a strategy to exert virulence. Thus, the bacterial effectors circumvent plant cellular pathways leading to infection and disease development. Finally, this review highlights known bacterial T3E and T4E proteins that function and interfere with the ubiquitination pathway to regulate the immune system of plants.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Data-driven acoustic measurement of moisture content in flowing biomass

Measuring the moisture content in flowing biomass is critical to processes such as liquid biofuel conversion, such as biogasoline, biodiesel, bio jet kerosene, etc. However, biomass tends to flow in aggregates, which results in significant inhomogeneities in the amount of biomass flowing in front of a sensor at a given time, and there can be significant overlap in the material properties of dry vs wet biomass, leading to poor signal-to-noise ratio. We present a technique for identifying biomass moisture content using a series of acoustic pitch-catch measurements to quantify the sound speed and acoustic amplitude through the biomass, in conjunction with classical machine learning techniques, including Naive Bayes, Random Forest, and K-Nearest Neighbors classification. We amplify the differences between the acoustic measurements in different moisture levels by collecting a series of pulse-echo measurements, which we sort in order of ascending sound speed. We test the accuracy of the technique on experimentally-prepared batches of corn stover biomass with specified moisture levels and measure the average error in the estimated moisture level as a function of the number of pitch-catch measurements used. We observe average estimation errors as low as 6.7% by increasing the number of measurements and optimizing the hyperparameters. This work presents a novel method determining moisture content in flowing biomass with inhomogeneous flow. Additionally, this technique has application in optimizing biomass conversion processes, as well as other fields including, paper production, natural fiber processing, and mineral extraction.

09 BIOMASS FUELS↗
DOE OSTI2023

Nanotwin stability in alloyed copper under ambient and cryo-temperature dependent deformation states

Nanometer size grains, solid solution strengthening, low temperatures, and a high density of nanotwins can provide significant strengthening to a material. Nevertheless, under loading the microstructure may evolve altering the effect of grain size, twin density, etc. on this strengthening. In some cases, these effects can be coupled as in detwinning, which is a mechanism for cryogenic grain growth. Here, in this work, a series of copper nanotwinned columnar grains are solid solution alloyed with aluminum and subject to ambient and cryogenic (–196 °C) environments during mechanical indentation, with the influence of alloying on the detwinning evolution studied. Under indentation, at a lower aluminum solute content (2 at.%), the columnar grains bent corresponding to a loss of twins. At a higher aluminum solute content (8 at.%), the grains shear and retain the nanotwins. Atomistic-scale simulations reveal an increase in the incoherent twin boundary velocity with decreasing temperature, but this boundary velocity is reduced with increasing alloy solute content. The coupling of solid solution strengthening and nanotwin stabilization is then used to explain the microstructural stability as a function of indentation at different temperature conditions.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Towards the applications of mechanophore incorporated feedstocks for additive manufacturing

The ability to additively-manufacture mechanically responsive molecules, known as mechanophores (MPs), that are incorporated into polymer feedstocks provides opportunities for self-healing, real-time damage detection, and improvements in quality assurance and control capabilities to several industries (wind energy technology, building and construction, etc.) who are adopting additive manufacturing (AM). However, before the applications are realized and industrially adopted, further research and development regarding MP-incorporated AM feedstock availability, production scale-up, and processability and printability is needed. Here, the goal of this review is to bridge the gap between the bench top and real world applications of AM of MPs by identifying high impact application spaces and highlighting the challenges that need to be overcome for widespread adoption. The state-of-the-art of AM of MP-incorporated feedstocks is reviewed, followed by a discussion of potential future applications, current challenges, and research areas that work toward commercialization of AM of MP-incorporated feedstocks.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Effect of Fermi surface topology change on the Kagome superconductor CeRu 2 under pressure

The cubic Laves phase compound CeRu 2 with a Kagome substructure of Ru has been investigated to understand myriad fascinating phenomena resulting from competition among its various physical and geometric features. Such phenomena include flat bands, van Hove singularities, Dirac cones, reentrant superconductivity, magnetism, the Fulde–Ferrell–Larkin–Ovchinnikov state, valence fluctuations, time-irreversible anisotropic s-state superconductivity, etc. Extensive studies have thus been carried out since 1958 when the highly unusual coexistence of superconductivity and ferromagnetism was proposed for the mixed compounds (Ce,Gd)Ru 2 . Activity has accelerated in recent years due to increasing interest in topological states in superconductors. However, there has been little investigation of the mutual influence of these fascinating states. Therefore, we systematically investigated the superconductivity and possible Fermi surface topological change in CeRu 2 via magnetic, resistivity, and structural measurements under pressure up to ~168 GPa. An unusual phase diagram that suggests an intriguing interplay between the compound’s superconducting order and Fermi surface topological order has been constructed. A resurgence in its superconducting transition temperature was observed above 28 GPa. Our experiments have identified a structural transition above 76 GPa and a few tantalizing phase transitions driven by high pressure. Our high-pressure results further suggest that superconductivity and Fermi surface topology in CeRu 2 are strongly intertwined.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Effective removal of trace-level toxic metals from flue gas desulfurization wastewater using SiO 2 supported hydrogel sorbent

Flue gas desulfurization (FGD) wastewater generated from coal-fired power plants contain potentially harmful heavy metal pollutants that pose a threat to public health and clean water. In this work, we present a water stable polyethylenimine-n,n’-methylenebisacrylamide (PEI-MBAA) functionalized SiO 2 solid sorbent material (PMS-1.2/1/4) and investigate its metal adsorption kinetics, selectivity, regenerability, and space velocity. The kinetic studies of six of the toxic heavy metals (As, Cd, Cr, Pb, Se, and Hg) prepared with single elements in Milli-Q water showed the effect of chemical bonding and intraparticle mass transfer resistance on the sorption process. The selectivity studies demonstrated the significant adsorption efficiency toward trace-level heavy metals (Se, Cd, U, Al, etc.) from authentic industrial FGD wastewater. Through five consecutive adsorption–desorption cycles with the FGD (uptake)-citrate (release)-based buffer pair, the sorbent showed high heavy metal removal ability and good reusability. The maximum flow rate for the removal of Se from industrial FGD wastewater was determined to be as high as 8 bed volumes/minute of the sorbent bed. Finally, the results demonstrate the PMS-1.2/1.4 sorbent is a promising candidate for the removal of heavy metals from practical aqueous solutions.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Chemometric modeling of power conversion efficiency of organic dyes in dye sensitized solar cells for the future renewable energy

The present study reports chemometric modeling of power conversion efficiency (PCE) of dye sensitized solar cells (DSSCs) using the biggest available data set till date which comprises around 1200 dyes covering 7 chemical classes. To extract the best structural features required for higher PCE, we have developed multiple partial least squares (PLS) quantitative structure-property relationship (QSPR) models for the Triphenylamine, Phenothiazine, Indoline, Porphyrin, Coumarin, Carbazole and Diphenylamine chemical classes using descriptors derived from the best subset selection method followed by selection of best five models in each dataset based on the Mean Absolute Error (MAE) values. The models were validated both internally and externally followed by the consensus predictions employing “Intelligent Consensus Predictor” tool to examine whether the quality of predictions can be improved with the “intelligent” selection of multiple PLS models. The quality of predictions for the respective external sets showed that the consensus models (CM) are better than the individual models (IM) in most of the cases. From the insights of the developed models, we concluded that attributes like a packed structure toward higher conductivity of electrons, auxiliary donor fragment of aromatic tertiary amines, number of thiophenes inducing the bathochromic shift and augmenting the absorption, presence of additional electron donors, enhancement of electron-donating abilities, number of non-aromatic conjugated C(sp 2 ) which helps as conjugation extension units to broaden the absorption and highly conjugated $π$-systems exert positive contributions to the PCE. On the contrary, features negatively contributing to PCE are the followings: fragments which lower the tendency of localized $π–π*$ transition, fragments related to larger volume and surface area of dyes along with hydrophobicity resulting in poor adhesion, fragment RC = N causing dye hydrolysis, steric hindrance for π electronic mobility, fragments enhancing polarity, etc. Finally, the identified features from the best QSPR model of the coumarin dataset was employed in designing of ten more efficient coumarin dyes (predicted %PCE ranging from 8.93 to 10.62) than the existing ones.

14 SOLAR ENERGY↗
DOE OSTI2020

Enhanced detection of volatile organic compounds (VOCs) by caffeine modified carbon nanotube junctions

Detection of vapor phase analytes and gas molecules is primarily essential for numerous applications including medical diagnostic, environmental monitoring, chemical threat detection, food quality control, and chemical warfare agents. Here, we developed Caffeine functionalized carbon nanotubes (CNTs) random network based vapor quantum resistive sensors (vQRSs) for volatile organic compounds (VOCs) detection. The localized transmission electron microscopy (TEM) image and energy dispersive X-ray spectroscopy (EDS) confirm migration of caffeine to CNT–CNT junction (CNTj). We have recorded more than one order of magnitude higher sensitivity and unique selectivity towards selective VOCs (e.g., acetone, toluene, ethanol, methanol, etc.) with short response time (few seconds) for caffeine modified CNT junction (Caf-CNTj) vQRSs. Molecular dynamics (MD) calculations suggest that the sensitivity of the sensor is diffusion limited, with an advective contribution for ethanol. Furthermore, the designed Caf-CNTj sensors can potentially be important candidate to be a part of electronic nose used for various application such as breath analysis and food quality monitoring.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Deep Kronecker neural networks: A general framework for neural networks with adaptive activation functions

Here we propose a new type of neural networks, Kronecker neural networks (KNNs), that form a general framework for neural networks with adaptive activation functions. KNNs employ the Kronecker product, which provides an efficient way of constructing a very wide network while keeping the number of parameters low. Our theoretical analysis reveals that under suitable conditions, KNNs induce a faster decay of the loss than that by the feed-forward networks. This is also empirically verified through a set of computational examples. Furthermore, under certain technical assumptions, we establish global convergence of gradient descent for KNNs. As a specific case, we propose the Rowdy activation function that is designed to get rid of any saturation region by injecting sinusoidal fluctuations, which include trainable parameters. The proposed Rowdy activation function can be employed in any neural network architecture like feed-forward neural networks, Recurrent neural networks, Convolutional neural networks etc. The effectiveness of KNNs with Rowdy activation is demonstrated through various computational experiments including function approximation using feed-forward neural networks, solution inference of partial differential equations using the physics-informed neural networks, and standard deep learning benchmark problems using convolutional and fully-connected neural networks.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Generalist multimodal AI: A review of architectures, challenges and opportunities

Multimodal models are expected to be a critical component to future advances in artificial intelligence. Here, this field is starting to grow rapidly with a surge of new design elements motivated by the success of foundation models in natural language processing (NLP) and vision. It is widely hoped that further extending the foundation models to multiple modalities (e.g., text, image, video, sensor, time series, graph, etc.) will ultimately lead to generalist multimodal models, i.e. one model across different data modalities and tasks. However, there is little research that systematically analyzes recent multimodal models (particularly the ones that work beyond text and vision) with respect to the underling architecture proposed. Therefore, this work provides a fresh perspective on generalist multimodal models (GMMs) via a novel architecture and training configuration specific taxonomy. This includes factors such as Unifiability, Modularity, and Adaptability that are pertinent and essential to the wide adoption and application of GMMs. The review further highlights key challenges and prospects for the field and guide the researchers into the new advancements.

Artificial intelligence (AI)↗
DOE OSTI2025

A compact electromagnetic neutron nutator for precise neutron spin manipulation

A superconducting electromagnetic nutator (EMN) capable of generating a magnetic field vector along an arbitrary direction on a 2D plane has been designed. Its performance in precisely manipulating the neutron polarization vector has been tested at the HB2-D polarized development beamline at the High Flux Isotope Reactor. Unlike mechanical nutators that require physical handling or motor-driven actuation to rotate the magnetic field, the magnitude and orientation of the magnetic field produced by the EMN can be controlled electromagnetically. Further, the compact design (~15 mm depth, not including cryogenic housing) of this device ensures ease of coupling within existing superconducting neutron spin manipulation devices, such as magnetic Wollaston prisms (MWP), resonant radio frequency (RF) flippers, spherical neutron polarimetry (SNP) devices, etc.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Simulation studies for beam commissioning at FRIB Advanced Rare Isotope Separator

The Facility for Rare Isotope Beams (FRIB) includes a powerful superconducting driver accelerator and an Advanced Rare Isotope Separator (ARIS). The ARIS collects and purifies the rare isotope fragments of interest for experiments in nuclear physics, nuclear astrophysics, fundamental symmetries, etc. ARIS consists of a vertical pre-separator and downstream horizontal separator section (C-Bend). Each section can provide a high-resolution separation alternatively. The resolution reduction due to the emittance induced by momentum compression can be avoided by isotope separation in different dispersive planes. Beam commissioning of ARIS for the first experiments was completed and demonstrated particle identification of fragments. The beam tuning in ARIS largely relies on numerical simulations since the limited space for diagnostics. Here, we report the result of the beam trajectory correction, transverse matching, and beam-based misalignment studies at ARIS.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Limitations of traditional tools for beyond design basis external hazard PRA

Probabilistic risk assessment (PRA) is being used increasingly by the nuclear industry for safety during normal operations as well as for the protection against external hazards. Computation of total risk in an external hazard PRA is dependent on hazard assessment, fragility assessment, and systems analysis. A systems analysis for propagation of component fragilities is conducted using event and fault trees. The event and fault trees for an actual power plant can be fairly large in size, which imposes computational challenges. Hence, certain assumptions are employed for computational efficiency. These assumptions typically represent the conditions imposed during the design basis (DB) scenario. The traditional PRA tools based on these assumptions are also widely applied to perform risk assessment in the context of beyond design basis (BDB) scenarios. However, some of these assumptions may not be valid for certain BDB scenarios. In addition, the probability of dependent failures also increases in BDB scenarios due to common cause failures (CCF) which usually results from design modifications, human errors, etc. In this manuscript, a simple and a relatively more complex illustrative examples are used to show the limitation of these assumptions in the numerical quantification of risk for the case of BDB conditions. Case studies with CCF events across multiple fault trees are also presented to illustrate the effect of these assumptions when traditional approach is used in BDB risk assessment. It is shown that the assumptions are valid for the case of DB conditions but may lead to excessively conservative risk estimates in the case of BDB conditions. Finally, a Bayesian network based top-down algorithm is proposed as an alternative tool for accurate numerical quantification of total risk in systems analysis.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗