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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 631 records · Page 35
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

3D-Printed pHEMA Materials for Topographical and Biochemical Modulation of Dorsal Root Ganglion Cell Response

Understanding and controlling the interactions occurring between cells and engineered materials are central challenges toward progress in the development of biomedical devices. In this work, we describe materials for direct ink writing (DIW), an extrusion-based type of 3D printing, that embed a custom synthetic protein (RGD-PDL) within the microfilaments of 3D-hydrogel scaffolds to modify these interactions and differentially direct tissue-level organization of complex cell populations in vitro. The RGD-PDL is synthesized by modifying poly-d-lysine (PDL) to varying extents with peptides containing the integrin-binding motif Arg-Gly-Asp (RGD). Compositional gradients of the RGD-PDL presented by both patterned and thin-film poly(2-hydroxyethyl) methacrylate (pHEMA) substrates allow the patterning of cell-growth compliance in a grayscale form. The surface chemistry-dependent guidance of cell growth on the RGD-PDL-modified pHEMA materials is demonstrated using a model NIH-3T3 fibroblast cell line. The formation of a more complex cellular system—organotypic primary murine dorsal root ganglion (DRG)—in culture is also achieved on these scaffolds, where distinctive forms of cell growth and migration guidance are seen depending on their RGD-PDL content and topography. In conclusion, this experimental platform for the study of physicochemical factors on the formation and the reorganization of organotypic cultures offers useful capabilities for studies in tissue engineering, regenerative medicine, and diagnostics.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Controlling Nanoparticle Orientations in the Self-Assembly of ‘Patchy’ Quantum Dot-Gold Heterostructural Nanocrystals

Self-assembly of nanocrystals is a promising route for creating macroscale materials that derive function from the properties of their nanoscale building blocks. While much progress has been made assembling nanocrystals into different superlattices, controlling the relative orientations of nanocrystals in those lattices remains a challenge. Here, we combine experiments with computer simulations to study the self-assembly of patchy heterostructural nanocrystals (HNCs), consisting of near-spherical quantum dots decorated with regular arrangements of small gold satellites, into close-packed superlattices with pronounced orientational alignment of HNCs. Our simulations indicate that the orientational alignment is caused by van der Waals interactions between gold patches and is sensitive to the interparticle distance in the superlattice. We demonstrate experimentally that the degree and type of orientational alignment can be controlled by changing ligand populations on HNCs. This study provides guidance for the design and fabrication of nanocrystal superlattices with enhanced structural control.

ZHu, Hua↗
DOE OSTI2020

Analyzing Wildland Fire Smoke Emissions Data Using Compositional Data Techniques

By conservation of mass, the mass of wildland fuel that is pyrolyzed and combusted must equal the mass of smoke emissions, residual char and ash. For a given set of conditions, these amounts are fixed. This places a constraint on smoke emissions data which violates statistical assumptions for many of the methods currently used to analyze these data such as linear regression, analysis of variance, and t-tests. These data are inherently multivariate and non-negative parts of a whole. This paper introduces the field of compositional data analysis to the emissions community and provides examples of appropriate statistical treatment of emissions data. It is shown that modified combustion efficiency should not be used as a predictor variable for other smoke emissions because it is not an independent variable. An alternative method based on compositional linear trends to estimate trace gas composition using CO and CO2 is presented. The data used in this paper resulted from projects the DOD/DOE/EPA Strategic 586 Environmental Research and Development Program projects RC-1648 and 1649. The senior 587 author appreciates the guidance and R scripts provided by Prof. Girty at San Diego State 588 University to estimate linear trends by perturbation. J. P.-A. was supported by the Spanish 589 Ministry of Science, Innovation and Universities under the project CODAMET (RTI2018-590 095518-B-C21, 2019-2021). The data used in this study have been previously published and are 591 available in the original publications. DRW conceived the initial manuscript (70 percent) and 592 performed the bulk of the data analysis. JPA provided statistical guidance and compositional data 593 expertise and contributed 20 percent of the manuscript. TJJ and HJ were extensively involved in 594 the study that provided the data. TJJ provide smoke emissions expertise and HJ provided 595 combustion expertise. The authors declare that they have no conflict of interest. The use of trade 596 or firm names in this publication is for reader information and does not imply endorsement by 597 the U.S. Department of Agriculture of any product or service.

simplex, compositional data analysis, balance, log↗
DOE OSTI2023

Stream Temperature Prediction in a Shifting Environment: Explaining the Influence of Deep Learning Architecture

Stream temperature is a fundamental control on ecosystem health. Recent efforts incorporating process guidance into deep learning models for predicting stream temperature have been shown to outperform existing statistical and physical models. This performance is in part because deep learning architectures can actively learn spatiotemporal relationships that govern how water and energy propagate through a river network. However, exploration of how spatiotemporal awareness and process guidance influence a model's generalizability under shifting environmental conditions such as climate change is limited. Here, we use Explainable Artificial Intelligence (XAI) to interrogate how differing deep learning architectures affect a model's learned spatial and temporal dependencies, and how those learned dependencies affect a model's ability to maintain high accuracy when applied to unseen environmental conditions. Using the Delaware River Basin in the northeastern United States as a test case, we compare two spatiotemporally aware process–guided deep learning models for predicting stream temperature (a recurrent graph convolution network—RGCN, and a temporal convolution graph model—Graph WaveNet). Both models achieve equally high predictive performance when testing data are well represented in the training data (test root mean squared errors of 1.64°C and 1.65°C); however, Graph WaveNet significantly outperforms RGCN in 4 out of 5 experiments where test partitions represent different types of unseen environmental conditions. XAI results show that the architecture of Graph WaveNet leads to learned spatial relationships with greater fidelity to physical processes, and that this fidelity improves the generalizability of the model when applied to shifting and/or unseen environmental conditions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Prediction of intrinsic topological superconductivity in Mn-doped GeTe monolayer from first-principles

The recent discovery of topological superconductors (TSCs) has sparked enormous interest. The realization of TSC requires a delicate tuning of multiple microscopic parameters, which remains a great challenge. Here, we develop a first-principles approach to quantify realistic conditions of TSC by solving self-consistently Bogoliubov-de Gennes equation based on a Wannier function construction of band structure, in presence of Rashba spin-orbit coupling, Zeeman splitting and electron-phonon coupling. We further demonstrate the power of this method by predicting the Mn-doped GeTe (Ge 1- x Mn x Te) monolayer—a well-known dilute magnetic semiconductor showing superconductivity under hole doping—to be a Class D TSC with Chern number of -1 and chiral Majorana edge modes. By constructing a first-principles phase diagram in the parameter space of temperature and Mn concentration, we propose the TSC phase can be induced at a lower-limit transition temperature of ~40 mK and the Mn concentration of x ~0.015%. Our approach can be generally applied to TSCs with a phonon-mediated pairing, providing useful guidance for future experiments.

Chemistry↗
DOE OSTI2016

Systems level analysis of the Chlamydomonas reinhardtii metabolic network reveals variability in evolutionary co-conservation

Metabolic networks, which are mathematical representations of organismal metabolism, are reconstructed to provide computational platforms to guide metabolic engineering experiments and explore fundamental questions on metabolism. Systems level analyses, such as interrogation of phylogenetic relationships within the network, can provide further guidance on the modification of metabolic circuitries. Chlamydomonas reinhardtii , a biofuel relevant green alga that has retained key genes with plant, animal, and protist affinities, serves as an ideal model organism to investigate the interplay between gene function and phylogenetic affinities at multiple organizational levels. Here, using detailed topological and functional analyses, coupled with transcriptomics studies on a metabolic network that we have reconstructed for C. reinhardtii , we show that network connectivity has a significant concordance with the co-conservation of genes; however, a distinction between topological and functional relationships is observable within the network. Dynamic and static modes of co-conservation were defined and observed in a subset of gene-pairs across the network topologically. In contrast, genes with predicted synthetic interactions, or genes involved in coupled reactions, show significant enrichment for both shorter and longer phylogenetic distances. Based on our results, we propose that the metabolic network of C. reinhardtii is assembled with an architecture to minimize phylogenetic profile distances topologically, while it includes an expansion of such distances for functionally interacting genes. This arrangement may increase the robustness of C. reinhardtii 's network in dealing with varied environmental challenges that the species may face. As a result, the defined evolutionary constraints within the network, which identify important pairings of genes in metabolism, may offer guidance on synthetic biology approaches to optimize the production of desirable metabolites.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Photo-assisted intersystem crossing: The predominant triplet formation mechanism in some isolated polycyclic aromatic molecules excited with pulsed lasers

Naphthalene, anthracene, and phenanthrene are shown to have very long-lived triplet lifetimes when the isolated molecules are excited with nanosecond pulsed lasers resonant with the lowest singlet state. For naphthalene, triplet state populations are created only during the laser pulse, excluding the possibility of normal intersystem crossing at the one photon level, and all molecules have triplet lifetimes greater than hundreds of microseconds, similar to the behavior previously reported for phenylacetylene. Although containing 7–12 thousand cm{sup −1} of vibrational energy, the triplet molecules have ionization thresholds appropriate to vibrationless T{sub 1} states. The laser power dependences (slopes of log-log power plots) of the excited singlet and triplet populations are about 0.7 for naphthalene and about 0.5 for anthracene. Kinetic modeling of the power dependences successfully reproduces the experimental results and suggests that the triplet formation mechanism involves an enhanced spin orbit coupling caused by sigma character in states at the 2-photon level. Symmetry adapted cluster-configuration interaction calculations produced excited state absorption spectra to provide guidance for estimating kinetic rates and the sigma character present in higher electronic states. It is concluded that higher excited state populations are significant when larger molecules are excited with pulsed lasers and need to be taken into account whenever discussing the molecular photodynamics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Mechanism of electrochemical lithiation of a metal-organic framework without redox-active nodes

Metal-organic frameworks (MOFs) have many potential uses for separations, storage, and catalysis, but their use as intercalation hosts for batteries has been scarce. In this article, we examine the mechanism of Li insertion in a MOF to provide guidance to future design efforts in this area. As a model system, we choose UiO-66, a MOF with the formula (Zr{sub 6}O{sub 4}(OH){sub 4}){sub 4}(1,4-benzenedicarboxylate){sub 6}, as an electrode material for lithium-ion batteries; this MOF is of special interest because the zirconium is not redox active. We report both quantum mechanical characterization of the mechanism and experimental studies in which the material is synthesized as nanoparticles to reduce diffusion lengths for lithium ions and increase the contact area with a conductive carbon phase. The calculated changes in the IR spectra of UiO-66 and lithiated UiO-66 are consistent with the experimental FTIR results. We found experimentally that this MOF can maintain a specific discharge capacity of at least 118 mAh/g for 30 lithiation and delithiation cycles at a rate of C/5, exhibiting good cyclability. Density functional electronic structure calculations show that the charge transfer during lithiation is mainly from Li to node oxygens and carboxylate oxygens, that is, it involves anions rather than cations or aromatic rings, and they provide a mechanistic understanding of the potential for increased Li capacity because the theoretical capacity of UiO-66 with Li at the oxygens in the metal oxide nodes and the carboxylate linkers is more than 400 mAh/g. The lithiation process greatly decreases the bandgap of UiO-66, which is expected to increase its electronic conductivity. The electrode material was also characterized by X-ray diffraction and scanning electron microscopy, which were consistent in confirming that smaller particle sizes were obtained in lower-temperature syntheses.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

The onset of plasma potential locking

In this study, we provide insight into the role and impact that a positively biased electrode (anode) has on bulk plasma potential. Using two-dimensional Particle-in-Cell simulations, we investigate the plasma potential as an anode transitions from very small (“probe” mode) to large (“locking” mode). Prior theory provides some guidance on when and how this transition takes place. Initial experimental results are also compared. The simulations demonstrate that as the surface area of the anode is increased transitions in plasma potential and sheath polarity occur, consistent with experimental observations and theoretical predictions. It is expected that understanding this basic plasma behavior will be of interest to basic plasma physics communities, diagnostic developers, and plasma processing devices where control of bulk plasma potential is important.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2018

A practical field guide to thermoelectrics: Fundamentals, synthesis, and characterization

The study of thermoelectric materials spans condensed matter physics, materials science and engineering, and solid-state chemistry. The diversity of the participants and the inherent complexity of the topic mean that it is difficult, if not impossible, for a researcher to be fluent in all aspects of the field. This review, which grew out of a one-week summer school for graduate students, aims to provide an introduction and practical guidance for selected conceptual, synthetic, and characterization approaches and to craft a common umbrella of language, theory, and experimental practice for those engaged in the field of thermoelectric materials. This review does not attempt to cover all major aspects of thermoelectric materials research or review state-of-the-art thermoelectric materials. Rather, the topics discussed herein reflect the expertise and experience of the authors. We begin by discussing a universal approach to modeling electronic transport using Landauer theory. The core sections of the review are focused on bulk inorganic materials and include a discussion of effective strategies for powder and single crystal synthesis, the use of national synchrotron sources to characterize crystalline materials, error analysis, and modeling of transport data using an effective mass model, and characterization of phonon behavior using inelastic neutron scattering and ultrasonic speed of sound measurements. The final core section discusses the challenges faced when synthesizing carbon-based samples and the measuring or interpretation of their transport properties. We conclude this review with a brief discussion of some of the grand challenges and opportunities that remain to be addressed in the study of thermoelectrics.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

A Methodology to Support the Development of a New State Vision for the U.S. Nuclear Industry

Recent changes in natural gas prices combined with reduced capital costs for solar and wind systems has created challenges for the continued operation of existing nuclear power plants (NPPs) in the United States. A new strategy in the way in which U.S. NPPs are operated, maintained, and supported is needed. One such strategy is to transform the NPP operating model through a business-driven approach that leverages technology to enable new capabilities that improve performance and reduce costs. This paper presents a methodology for developing an achievable yet transformative new state vision that ensures the continued safe and efficient operations of the U.S. NPP fleet. Here this work builds on existing guidance and leverages previous research to comprehensively address both utility needs and high-level human factors engineering design principles when developing a new state vision. The proposed methodology is intended to provide industry-wide guidance for developing a new state vision that leverages both the selected vendor’s capabilities in a way that meets the utility’s modernization goals while ensuring state-of-the-art systems engineering and human factors engineering principles are applied that promote overall plant safety, performance, and efficiency.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2021

Design of nematic liquid crystals to control microscale dynamics

The dynamics of small particles, both living such as swimming bacteria and inanimate, such as colloidal spheres, has fascinated scientists for centuries. If one could learn how to control and streamline their chaotic motion, that would open technological opportunities in the transformation of stored or environmental energy into systematic motion, with applications in micro-robotics, transport of matter, guided morphogenesis. This review presents an approach to command microscale dynamics by replacing an isotropic medium with a liquid crystal. Orientational order and associated properties, such as elasticity, surface anchoring, and bulk anisotropy, enable new dynamic effects, ranging from the appearance and propagation of particle-like solitary waves to self-locomotion of an active droplet. By using photoalignment, the liquid crystal can be patterned into predesigned structures. In the presence of the electric field, these patterns enable the transport of solid and fluid particles through nonlinear electrokinetics rooted in anisotropy of conductivity and permittivity. Director patterns command the dynamics of swimming bacteria, guiding their trajectories, polarity of swimming, and distribution in space. This guidance is of a higher level of complexity than a simple following of the director by rod-like microorganisms. Namely, the director gradients mediate hydrodynamic interactions of bacteria to produce an active force and collective polar modes of swimming. The patterned director could also be engraved in a liquid crystal elastomer. When an elastomer coating is activated by heat or light, these patterns produce a deterministic surface topography. The director gradients define an activation force that shapes the elastomer in a manner similar to the active stresses triggering flows in active nematics. Finally, the patterned elastomer substrates could be used to define the orientation of cells in living tissues. The liquid-crystal guidance holds a major promise in achieving the goal of commanding microscale active flows.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Wall diffuser velocity effects on American Shad ( Alosa sapidissima ) inside a fishway entrance channel

Attraction water for fishways is typically introduced through a diffuser inside the entrance channel, often through the floor or wall. In the spring of 2019, this laboratory study examined how 151 adult American Shad (Alosa sapidissima) responded to different gross velocities through a wall diffuser inside a full-scale fishway entrance channel. Two velocity conditions were studied, 0.152 m/s and 0.305 m/s, both without turning vanes inside the auxiliary water channel. The fish were tracked using the passive integrated transponder telemetry technique. The results of the experiments showed no difference in American Shad behavior when exhibited to the low and high velocity treatments. Moreover, shad passed the diffuser in roughly 3 out of every 4 attempts, regardless of the treatment. However, the similarity in shad behavior and passage performance is believed to be more of a result of the similarity in flow fields that resulted from the lack of flow guidance devices inside the auxiliary water channel. Furthermore, these findings therefore highlight the importance of properly maintained flow guidance devices, an often-overlooked component of an auxiliary water system.

13 HYDRO ENERGY↗
DOE OSTI2021

Dynamics and chemical mode analysis of plasma thermal-chemical instability

The stability of the weakly ionized plasma and the transition from a stable homogeneous discharge to unstable filaments play an important role in gas laser physics, plasma-assisted combustion, chemical reforming, and material synthesis. Here, theoretical stability analysis and thermal-chemical mode analysis were performed to understand the mechanism of plasma thermal-chemical instability by using a zero-dimensional plasma system with both simplified and detailed chemical kinetics of H 2 /O 2 /N 2 mixtures. The plasma dynamic and kinetic models accounted for multiple physical mechanisms in the chemically-reactive weakly ionized plasma, including ionization, attachment/detachment, recombination, vibrational and electronic energy relaxation, convective and diffusive species/heat removal, Joule heating, and detailed chemical kinetics. An analytical criterion and the explosive mode species/temperature pointers were formulated while the representative active species were identified for different thermal-chemical modes. The results showed that in addition to the classical thermal-ionization mechanism, various chemical modes from chemical heat imbalance and elementary kinetics significantly modified the time dynamics and the stability of the weakly ionized plasma. The present analysis provides insights and guidance to control plasma instability using chemical kinetics.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2017

Development of ITER non-activation phase operation scenarios

Non-activation phase operations in ITER in hydrogen (H) and helium (He) will be important for commissioning of tokamak systems, such as diagnostics, heating and current drive (HCD) systems, coils and plasma control systems, and for validation of techniques necessary for establishing operations in DT. The assessment of feasible HCD schemes at various toroidal fields (2.65–5.3 T) has revealed that the previously applied assumptions need to be refined for the ITER non-activation phase H/He operations. A study of the ranges of plasma density and profile shape using the JINTRAC suite of codes has indicated that the hydrogen pellet fuelling into He plasmas should be utilized taking the optimization of IC power absorption, neutral beam shine-through density limit and H-mode access into account. The EPED1 estimation of the edge pedestal parameters has been extended to various H operation conditions, and the combined EPED1 and SOLPS estimation has provided guidance for modelling the edge pedestal in H/He operations. The availability of ITER HCD schemes, ranges of achievable plasma density and profile shape, and estimation of the edge pedestal parameters for H/He plasmas have been integrated into various time-dependent tokamak discharge simulations. In this paper, various H/He scenarios at a wide range of plasma current (7.5–15 MA) and field (2.65–5.3 T) have been developed for the ITER non-activation phase operation, and the sensitivity of the developed scenarios to the used assumptions has been investigated to provide guidance for further development.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Energy Storage in Long-Term System Models: A Review of Considerations, Best Practices, and Research Needs

Technological change and policy support have heightened expectations for the role of energy storage in power systems, creating a need to enhance representations of energy storage in long-term models to inform decision-making. Energy storage technologies have complex and diverse cost, value, and performance characteristics that make them challenging to model, but there is limited guidance about best practices and research gaps for energy storage analysis. This paper reviews the literature and draws upon our collective experience to provide recommendations to analysts on approaches for representing energy storage in long-term electric sector models, navigating tradeoffs in model development, and identifying research gaps for existing tools and data. The review focuses on national-scale models with technological, temporal, and regional detail given their prevalence in planning and policy, though many insights are transferable to other modeling contexts. It also offers guidance to consumers of model outputs on proper use and interpretation based on model strengths and limitations. In particular, this review demonstrates the importance of capturing how the values of energy storage and other resources change as the system composition changes (e.g. with different levels of storage, renewables deployment, and emissions outcomes). These considerations require model detail like high spatiotemporal resolutions and endogenous investments that global integrated assessment models and price-taker frameworks do not typically resolve. Research gaps include linking tools of different resolutions, developing reduced-form representations of value streams, incorporating hybrid energy storage and renewable systems, and representing longer-duration energy storage technologies.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2022

Deep-learning-guided high-resolution subsurface reflectivity imaging with application to ground-penetrating radar data

Subsurface reflectivity imaging is one of the most important geophysical characterization methods for revealing subsurface structures. In many cases, accurate subsurface reflectivity imaging is challenging because of, for example, random or coherent noise in the data and sparse source-receiver observation geometry. Here, we develop a deep-learning-guided iterative imaging method to improve subsurface structure imaging. Specifically, we train a supervised neural network to infer a noise-free, high-resolution image from a noisy, low-resolution image and use this estimated image as guidance to regularize least-squares imaging. We develop a systematic method to generate high-quality synthetic training data (data-label pairs) to train the guidance neural network. The trained neural network can provide high-fidelity predictions even for field-data images that are not in the training data. We validate our new imaging method using one synthetic and two field ground-penetrating radar data examples, and find that our method can produce clean, high-resolution subsurface reflectivity images where existing single-pass and least-squares imaging methods fail due to noise and insufficient data coverage.

58 GEOSCIENCES↗
DOE OSTI2021

Imaging the structural organization of chemical elements in growth cones of developing hippocampal neurons

Abstract During neurodevelopment, neurons form growth cones, F-actin rich extensions located at the distal end of the neurites. Growth cones allow dendrites and axons to build synaptic connections through a process of neurite guidance whose mechanisms have not been fully elucidated. Calcium is an important element in this process by inducing F-actin reorganization. We hypothesized that other biologically active elements might be involved in the growth cone-mediated neurite guidance mechanisms. We performed super resolution and confocal microscopy of F-actin, followed by synchrotron X-ray fluorescence microscopy of phosphorous, sulfur, chlorine, potassium, calcium, iron and zinc on growth cones from primary rat hippocampal neurons. We identified two main patterns of element organization. First, active growth cones presenting an asymmetric distribution of Ca co-localized with the cytoskeleton protein F-actin. In active growth cones, we found that the distributions of P, S, Cl, K, and Zn are correlated with Ca. This correlation is lost in the second pattern, quiescent growth cones, exhibiting a spread elemental distribution. These results suggest that Ca is not the only element required in the F-actin rich active regions of growth cones. In addition, highly concentrated Fe spots of submicrometer size were observed in calcium-rich areas of active growth cones. These results reveal the need for biological active elements in growth cones during neural development and may help explain why early life deficiencies of elements, such as Fe or Zn, induce learning and memory deficits in children.

60 APPLIED LIFE SCIENCES↗