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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 OSTI2019

Digital Maskless Photolithographic Patterning of DNA-Functionalized Poly(ethylene glycol) Diacrylate Hydrogels with Visible Light Enabling Photodirected Release of Oligonucleotides

Soft biomaterials possessing structural hierarchy have growing applications in lab-on-chip devices, artificial tissues, and micromechanical and chemomechanical systems. The ability to integrate sets of biomolecules, specifically DNA, within hydrogel substrates at precise locations could offer the potential to form and modulate complex biochemical processes with DNA-based molecular switches in such materials and provide a means of creating dynamic spatial patterns, thus enabling spatiotemporal control of a wide array of reaction-diffusion phenomena prevalent in biological systems. In this paper, we develop a means of photopatterning two-dimensional DNA-functionalized poly(ethylene glycol) diacrylate (PEGDA) hydrogel architectures with an aim toward these applications. While PEGDA photopatterning methods are well-established for the fabrication of hydrogels, including those containing oligonucleotides, the photoinitiators typically used have significant crosstalk with many UV-photoswitchable chemistries including nitrobenzyl derivatives. We demonstrate the digital photopatterning of PEGDA-co-DNA hydrogels using a blue light-absorbing (470 nm peak) photoinitiator system and macromer comprised of camphorquinone, triethanolamine, and poly(ethylene glycol) diacrylate ($M$ n = 575) that minimizes absorption in the UV-A wavelength range commonly used to trigger photoswitchable chemistries. We demonstrate this method using digital maskless photolithography within microfluidic devices that allows for the reliable construction of multidomain structures. The method achieves feature resolutions as small as 25 μm, and the resulting materials allow for lateral isotropic bulk diffusion of short single-stranded (ss) DNA oligonucleotides. Finally, we show how the use of these photoinitiators allows for orthogonal control of photopolymerization and UV-photoscission of acrylate-modified DNA containing a 1-(2-nitrophenyl) ethyl spacer to selectively cleave DNA from regions of a PEGDA substrate.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Magnon confinement in epitaxial antiferromagnetic oxide heterostructures.

Magnons, the quanta of spin waves, have been extensively studied in a range of materials for spintronics, particularly for non-volatile logic-in-memory devices. Controlling magnons in conventional antiferromagnets and harnessing them in practical applications, however, remains a challenge. Here, we demonstrate highly efficient magnon transport in a LaFeO3/ BiFeO3/ LaFeO3 all-antiferromagnetic system, which can be controlled electrically, making it highly desirable for energy-efficient computation. Leveraging spin-orbit-driven spin-charge transduction, we demonstrate that this material architecture permits magnon confinement in ultrathin antiferromagnets, enhancing the output voltage generated by magnon transport by several orders of magnitude, which provides a pathway to enable magnetoelectric memory and logic functionalities. Additionally, the non-volatility of output voltage enables ultralowpower logic-in-memory processing, where magnonic devices can be efficiently reconfigured via electrically controlled magnon spin currents within magnetoelectric channels.

Husain, Sajid↗
DOE OSTI2019

Empirical Refinement of the GADRAS Detector Response Function

The Gamma Detector Response and Analysis Software (GADRAS) was augmented to enable empirical refinement of the Detector Response Function (DRF) for gamma-ray detectors. This capability is included in GADRAS starting with Version 18.8.2, which was released in February 2019 Empirical refinement enables improved computational accuracy for gamma-ray spectra when detectors exhibit characteristics that are essentially unique to a particular sensor. This report discusses how to perform the empirical refinement, and examples are presented for the following scenarios where empirical refinement is appropriate: Large plastic scintillators, which are generally composed of polyvinyl toluene (PVT), often exhibit low-energy peaks that are not associated with incident gamma rays. Regardless of whether they are artifacts produced by poor light collection or pulse processing methods, accurate spectral synthesis requires replication of these features; Some detectors, particularly those using Silicon Photomultipliers (SiPM), exhibit energy shifts of Compton edges and escape peaks relative to the same scintillator material attached to a photomultiplier tube. Empirical refinement compensates for these effects, which derive from nonlinearities in the detector response; The change in the DRF as a function of displacement of the source relative to the detector axis cannot always be replicated adequately using only the few shielding parameters that are used by the response function. Empirical refinement enables improved accuracy for computation of spectra during linear transits or when the detector is close to a large radiation source. This is a particularly important consideration for collimated detectors; and, Gamma-ray imagers exhibit complex relationships between spectral response and spatial locations. Empirical refinement enables substantial improvement of the DRF accuracy for imagers.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2012

A Fixed-Point Iteration Method with Quadratic Convergence

The fixed-point iteration algorithm is turned into a quadratically convergent scheme for a system of nonlinear equations. Most of the usual methods for obtaining the roots of a system of nonlinear equations rely on expanding the equation system about the roots in a Taylor series, and neglecting the higher order terms. Rearrangement of the resulting truncated system then results in the usual Newton-Raphson and Halley type approximations. In this paper the introduction of unit root functions avoids the direct expansion of the nonlinear system about the root, and relies, instead, on approximations which enable the unit root functions to considerably widen the radius of convergence of the iteration method. Methods for obtaining higher order rates of convergence and larger radii of convergence are discussed.

Walker, Kevin P.↗
DOE OSTI2024

Reliable edge machine learning hardware for scientific applications

Extreme data rate scientific experiments create massive amounts of data that require efficient ML edge processing. This leads to unique validation challenges for VLSI implementations of ML algorithms: enabling bit-accurate functional simulations for performance validation in experimental software frameworks, verifying those ML models are robust under extreme quantization and pruning, and enabling ultra-fine-grained model inspection for efficient fault tolerance. We discuss approaches to developing and validating reliable algorithms at the scientific edge under such strict latency, resource, power, and area requirements in extreme experimental environments. We study metrics for developing robust algorithms, present preliminary results and mitigation strategies, and conclude with an outlook of these and future directions of research towards the longer-term goal of developing autonomous scientific experimentation methods for accelerated scientific discovery.

Baldi, Tommaso↗
DOE OSTI2019

Microwave Irradiation Intensified Process for Scalable Functional Device Assembly

The environment pollution is a serious issue worldwide for human beings, which calls for ever-increasing demand towards environmental protection. Efficient enabling and utilization of various functional devices represent an essential solution to pursue the environment sustainability. Nanotechnology is emerging as an effective approach to improve the efficiency of functional devices for a variety of environmental applications. For example, the nanomaterials-based catalysts are being widely used in air pollution control, enabling catalysts with significantly enhanced performance. Scalable integration of functional nanostructural entities such as nanoparticles, nanowires, nanosheets into applicable three-dimensional (3-D) platform holds the keys of industrial-relevant manufacture of high-efficiency catalytic devices for emission control. Among all the integration approaches, the wet-chemical based integration is one of the top options due to its advantages in low-cost, flexibility in substrate geometry and composition, ease of operation, and high repeatability. The wet-chemical based processes usually require continuous heating to initiate the chemical reactions, which is regularly achieved by conventional resistive heating. However, such conventional heating method is plaqued by a poor heating efficiency. Moreover, the conventional heating is not suitable for those substrates with three-dimensional (3D) or complex geometry since it hardly provides sufficient heat transfer and mass transport within substrates, leading to poor uniformity of nanostructure deposition and low production rate. Thus, there is urgent demand to develop high-efficiency wet-chemical based integration strategy for nanostructured functional devices. In this project, a novel microwave-irradiation-intensified hydrothermal manufacturing process was developed for scalable manufacture of nanostructured monolithic catalytic devices. A wide array of metal oxide nanostructured coatings has been in situ grown on various 3D substrates for emission control applicaitons such as cordierite honeycombs and silicon carbide honeycomb. The growth efficiency, production rate, and distribution uniformity of nanostructure coatings obtained from microwave heating and conventional heating are investigated, which reveals the boosting effect of microwave irradiation on hydrothermal reactions. The silicon carbide honeycomb is found to be more favorable to microwave adsorption in contrast to cordierite honeycomb, and the corresponding reaction mechanism is studied. The obtained catalysts are used for catalytic oxidation of Volatile Organic Compounds (VOCs), showing excellent catalytic performance at low temperature for various compounds. As the proof of concept, the design of integrated manufacturing system for the microwave irradiation assisted continuous production of nanostructure array based monolithic catalysts is presented, which holds the key to mass production of monolithic catalysts in near future.

42 ENGINEERING↗
DOE OSTI2015

Inter-Procedural Resource Sharing in High Level Synthesis through Function Proxies

Modular design is becoming increasingly important in High Level Synthesis (HLS) flows. Current HLS flows generate hierarchical and modular designs that mimic the structure and call graph of input specification translating functions into modules. Function calls are translated instantiating the callee module in the data-path of its caller, allowing for resource sharing when the same function is called multiple times. However, if two different callers invoke the same function, current HLS flows cannot share the instance of the module between the two callers, even if they invoke the function in a mutually exclusive way. In this paper, we propose a methodology that enables sharing of (sub)modules across modules boundaries. Sharing is obtained through function proxies, which act as forwarders of function calls in the original specification to shared modules without adding performance penalties. Building on the concept of function proxies, we propose a methodology and the related components to perform HLS of function calls through function pointers, without requiring complete static knowledge of the alias set (point-to set). We show that module sharing through function proxies provides valuable area savings without significant impacts on the execution delays, and that our synthesis approach for function pointers enables dynamic polymorphism.

HLS, function proxy, FPGA, modular HLS,↗
DOE OSTI2021

Energy efficiency and biological interactions define the core microbiome of deep oligotrophic groundwater

While oligotrophic deep groundwaters host active microbes attuned to the low-end of the bioenergetics spectrum, the ecological constraints on microbial niches in these ecosystems and their consequences for microbiome convergence are unknown. Here, we provide a genome-resolved, integrated omics analysis comparing archaeal and bacterial communities in disconnected fracture fluids of the Fennoscandian Shield in Europe. Leveraging a dataset that combines metagenomes, single cell genomes, and metatranscriptomes, we show that groundwaters flowing in similar lithologies offer fixed niches that are occupied by a common core microbiome. Functional expression analysis highlights that these deep groundwater ecosystems foster diverse, yet cooperative communities adapted to this setting. We suggest that these communities stimulate cooperation by expression of functions related to ecological traits, such as aggregate or biofilm formation, while alleviating the burden on microorganisms producing compounds or functions that provide a collective benefit by facilitating reciprocal promiscuous metabolic partnerships with other members of the community. We hypothesize that an episodic lifestyle enabled by reversible bacteriostatic functions ensures the subsistence of the oligotrophic deep groundwater microbiome.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Collaboration and Negotiation

Collaboration and Negotiation is a critical high-level function of an Autonomous Intelligent Cyber-Defense Agent (AICA) that enables communication among agents, central cyber C2, and human operators. Maintaining the Confidentiality, Integrity, and Availability (CIA) triad while achieving mission goals requires stealthy AICA agents to exercise: 1) minimal communication as needed for avoiding detection, 2) verification of information received with possibly limited resources, and 3) active learning during operations to address dynamic conditions. Moreover, negotiations to jointly identify and execute a Course of Action (COA) solution will require building consensus under distributed and/or decentralized multiagent settings with information uncertainties. This chapter presents algorithmic approaches for enabling the collaboration and negotiation function. Strengths and limitations of potential techniques are identified, and a representative example is illustrated. Recommendations for future development are also discussed.

Chatterjee, Samrat↗
DOE OSTI2021

Enabling Long-range Exploration in Minimization of Multimodal Functions

We consider the problem of minimizing multi-modal loss functions with a large number of local optima. Since the local gradient points to the direction of the steepest slope in an infinitesimal neighborhood, an optimizer guided by the local gradient is often trapped in a local minimum. To address this issue, we develop a novel nonlocal gradient to skip small local minima by capturing major structures of the loss’s landscape in black-box optimization. The nonlocal gradient is defined by a directional Gaussian smoothing (DGS) approach. The key idea of DGS is to conducts 1D long-range exploration with a large smoothing radius along d orthogonal directions in Rd, each of which defines a nonlocal directional derivative as a 1D integral. Such long-range exploration enables the nonlocal gradient to skip small local minima. The d directional derivatives are then assembled to form the nonlocal gradient. We use the Gauss-Hermite quadrature rule to approximate the d 1D integrals to obtain an accurate estimator. The superior performance of our method is demonstrated in three sets of examples, including benchmark functions for global optimization, and two real-world scientific problems.

Zhang, Jiaxin↗
DOE OSTI2018

Giant spin-valley polarization and multiple Hall effect in functionalized bismuth monolayers

Abstract Valleytronic materials, characterized by local extrema (valleys) in their bands, and topological insulators have separately attracted great interest recently. However, the interplay between valleytronic and topological properties in one single system, likely to enable important unexplored phenomena and applications, has been largely overlooked so far. Here, by combining a tight-binding model with first-principles calculations, we find the large-band-gap quantum spin Hall effects (QSHEs) and valley Hall effects appear simultaneously in the bismuth monolayers decorated with hydrogen/halogen elements, denoted as Bi 2 XY (X, Y = H, F, Cl, Br, or I). A staggered exchange field is introduced into the Bi 2 XY monolayers by transition-metal atom (Cr, Mo, or W) doping or LaFeO 3 magnetic substrates, which together with the strong spin-orbit coupling of bismuth atoms generates a time-reversal-symmetry-broken QSHE and a huge valley splitting (up to 513 meV) in the system. With gate control, QSHE and anomalous charge, spin, valley Hall effects can be observed in the single system. These predicted multiple and exotic Hall effects, associated with various degrees of freedom of electrons, could enable applications of the functionalized bismuth monolayers in electronics, spintronics, and valleytronics.

Zhou, Tong (ORCID:0000000345885263)↗
DOE OSTI2023

Electrochemical Oxidation and Functionalization of Low‐Density Polyethylene

Abstract Plastic waste is a serious environmental issue, and polyethylene (PE) is a significant component. The chemically inert nature of PE makes its recycling/upcycling process challenging. Thus, a novel method was demonstrated that enables the selective electrochemical functionalization and deconstruction of low‐density polyethylene (LDPE) by using low‐cost transition metal electrocatalysts at room temperature (23±2 °C) and low cell voltage (±1 V). Three different electrode and electrolyte combinations were studied for the oxidation of LDPE: copper metal/copper (II) ions, nickel metal/nickel (II) ions, and stainless steel/iron (II) and (III) ions. The copper and nickel electrode/electrolyte pairs showed a promising capability for oxidation and chain‐scission of LDPE. In contrast, the stainless‐steel and iron electrode/electrolyte pair showed no activity towards LDPE oxidation or depolymerization. The electrolysis of LDPE offers a new vista for the depolymerization and upcycling of plastics, further understanding of the process is needed.

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

Exploring Physics of Ferroelectric Domain Walls in Real Time: Deep Learning Enabled Scanning Probe Microscopy

The functionality of ferroelastic domain walls in ferroelectric materials is explored in real-time via the in situ implementation of computer vision algorithms in scanning probe microscopy (SPM) experiment. The robust deep convolutional neural network (DCNN) is implemented based on a deep residual learning framework (Res) and holistically nested edge detection (Hed), and ensembled to minimize the out-of-distribution drift effects. The DCNN is implemented for real-time operations on SPM, converting the data stream into the semantically segmented image of domain walls and the corresponding uncertainty. Further the pre-defined experimental workflows perform piezoresponse spectroscopy measurement on thus discovered domain walls, and alternating high- and low-polarization dynamic (out-of-plane) ferroelastic domain walls in a PbTiO 3 (PTO) thin film and high polarization dynamic (out-of-plane) at short ferroelastic walls (compared with long ferroelastic walls) in a lead zirconate titanate (PZT) thin film is reported. This work establishes the framework for real-time DCNN analysis of data streams in scanning probe and other microscopies and highlights the role of out-of-distribution effects and strategies to ameliorate them in real time analytics.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Strong Lithium Polysulfide Chemisorption on Electroactive Sites of Nitrogen-Doped Carbon Composites For High-Performance Lithium–Sulfur Battery Cathodes

Despite the high theoretical capacity of lithium–sulfur batteries, their practical applications are severely hindered by a fast capacity decay, stemming from the dissolution and diffusion of lithium polysulfides in the electrolyte. A novel functional carbon composite (carbon-nanotube-interpenetrated mesoporous nitrogen-doped carbon spheres, MNCS/CNT), which can strongly adsorb lithium polysulfides, is now reported to act as a sulfur host. The nitrogen functional groups of this composite enable the effective trapping of lithium polysulfides on electroactive sites within the cathode, leading to a much improved electrochemical performance (1200 mAh g -1 after 200 cycles). The enhancement in adsorption can be attributed to the chemical bonding of lithium ions by nitrogen functional groups in the MNCS/CNT framework. Furthermore, the micrometer-sized spherical structure of the material yields a high areal capacity (ca. 6 mAh cm -2 ) with a high sulfur loading of approximately 5 mg cm -2 , which is ideal for practical applications of the lithium–sulfur batteries.

carbon materials↗
DOE OSTI2018

A Probe-Enabled Approach for the Selective Isolation and Characterization of Functionally Active Subpopulations in the Gut Microbiome

Increasing evidence has shown that microorganisms present in the mammalian gut have a major impact on the metabolism of xenobiotics – chemicals foreign to the body including drugs and environmental contaminants – either by modulating host metabolism or by transforming xenobiotics or their metabolites directly. Being able to predict these interactions will be critical to develop precision medicine strategies utilizing the gut microbiota. However, current knowledge of which microbes are responsible for a given activity is severely limited and is further complicated by the sheer diversity of gut microbes between individuals. Current approaches including metagenomic and metatranscriptomic analyses can only identify enzymes and organisms that have the potential to catalyze a specific reaction, but cannot determine if an enzyme is truly active within the gut. To identify the microorganisms that are directly responsible for an activity in the gut of an individual, new functional approaches are needed. Here, we present an activity-based probe (ABP) approach to define the microbial populations responsible for a specific xenobiotic metabolizing activity. We developed an ABP for β-glucuronidases, enzymes capable of reversing a major pathway in phase II metabolism that is responsible for xenobiotic elimination. Using this ABP, we covalently labelled active β-glucuronidases both in vitro and in bacterial cells in the mouse gut microbiota. Cells possessing β-glucuronidase activity were then fluorescently labeled, isolated using fluorescence-activated cell sorting (FACS), and identified by sequencing. We found that glucuronidase active bacteria in the murine gut are taxonomically diverse, and even within phyla the taxa displaying function are highly disparate. Perturbation of the gut microbiota with vancomycin decreased but did not eliminate β-glucuronidase activity, which corresponded to a shift in the β-glucuronidase active population. These data demonstrate that the metabolic activity of the gut microbiota can be plastic and that during perturbation, functional capacity may be maintained by phylogenetically disparate populations. This work highlights the utility of ABPs to identify currently unknown functional microbial subpopulations responsible for a specific activity of interest within the gut of an individual.

Whidbey, Christopher↗
DOE OSTI2021

Accelerating Biological Insight for Understudied Genes

Synopsis The rapid expansion of genome sequence data is increasing the discovery of protein-coding genes across all domains of life. Annotating these genes with reliable functional information is necessary to understand evolution, to define the full biochemical space accessed by nature, and to identify target genes for biotechnology improvements. The majority of proteins are annotated based on sequence conservation with no specific biological, biochemical, genetic, or cellular function identified. Recent technical advances throughout the biological sciences enable experimental research on these understudied protein-coding genes in a broader collection of species. However, scientists have incentives and biases to continue focusing on well documented genes within their preferred model organism. This perspective suggests a research model that seeks to break historic silos of research bias by enabling interdisciplinary teams to accelerate biological functional annotation. We propose an initiative to develop coordinated projects of collaborating evolutionary biologists, cell biologists, geneticists, and biochemists that will focus on subsets of target genes in multiple model organisms. Concurrent analysis in multiple organisms takes advantage of evolutionary divergence and selection, which causes individual species to be better suited as experimental models for specific genes. Most importantly, multisystem approaches would encourage transdisciplinary critical thinking and hypothesis testing that is inherently slow in current biological research.

Zoology↗
DOE OSTI2012

Colloidal CIGS and CZTS nanocrystals: A precursor route to printed photovoltaics

This review article summarizes our research focused on Cu(In{sub 1-x}Ga{sub x})Se{sub 2} (CIGS) nanocrystals, including their synthesis and implementation as the active light absorbing material in photovoltaic devices (PVs). CIGS PV layers are typically made using a high temperature (>450 Degree-Sign C) process in which Cu, In and Ga are sequentially or co-evaporated and selenized. We have sought to use CIGS nanocrystals synthesized with the desired stoichiometry to deposit PV device layers without high temperature processing. This approach, using spray deposition of the CIGS light absorber layers, without high temperature selenization, has enabled up to 3.1% power conversion efficiency under AM 1.5 solar illumination. Although the device efficiency is too low for commercialization, these devices provide a proof-of-concept that solution-deposited CIGS nanocrystal films can function in PV devices, enabling unconventional device architectures and materials combinations, including the use of flexible, inexpensive and light-weight plastic substrates. - Graphical abstract: The semiconductor light-absorbing layers in photovoltaic devices can be deposited under ambient conditions using nanocrystal inks. Devices can be fabricated on glass or on mechanically flexible plastic substrates. Highlights: Black-Right-Pointing-Pointer CIGS and CZTS nanocrystals are synthesized and formulated into inks. Black-Right-Pointing-Pointer Nanocrystal films are spray deposited and used as light absorbing layers in photovoltaic devices. Black-Right-Pointing-Pointer Photovoltaic devices were constructed from nanowire mats. Black-Right-Pointing-Pointer Photovoltaic device efficiency is limited by electrical transport in the nanocrystal layers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗