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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Designing a Dynamic Material via Interlocking Kraft Lignin with Ultrahigh Molecular Weight Poly(ethylene oxide)

The environmental issues stemming from plastic waste and the excessive use of petroleum-based chemicals are both concerning and urgent. To effectively address this problem, we need to adopt a comprehensive approach involving developing more sustainable and renewable materials. These materials should be capable of demonstrating similar or even better performance than functional polymers synthesized from petroleum-based chemicals. Our research aims to develop more sustainable materials by leveraging the intrinsic characteristics of a natural polymer, lignin, a byproduct of the biorefinery industries. We utilized the three-dimensional branching structure of lignin as a material framework. We employed an approach to co-reactive melt processing of kraft lignin with aliphatic flexible chains of soft cross-linkers through the reaction of the cross-linker epoxy chain ends with lignin functional groups. Our study demonstrates that the interlocked structure formed from the co-blending of kraft lignin with ultrahigh molecular weight poly(ethylene oxide) and the cross-linking of lignin chains through a solvent-free process can manipulate the macromolecular interactions and relaxation. This manipulation results in materials that exhibit a wide range of thermomechanical properties and self-healing and shape memory effects, with drastically improved stiffness in a single material. We have explored the fundamental understanding of the macromolecular chain relaxation dynamics originating from the interlocking structure formation. In conclusion, this investigation utilized various techniques, including thermal, mechanical, rheology, and quasi-elastic neutron scattering.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Estimating Higher-Order Moments Using Symmetric Tensor Decomposition

In this paper, we consider the problem of decomposing higher-order moment tensors, i.e., the sum of symmetric outer products of data vectors. Such a decomposition can be used to estimate the means in a Gaussian mixture model and for other applications in machine learning. The dth-order empirical moment tensor of a set of p observations of n variables is a symmetric d-way tensor. Our goal is to nd a low-rank tensor approximation comprising r $\ll$ p symmetric outer products. The challenge is that forming the empirical moment tensor costs O(pn d ) operations and O(n d ) storage, which may be prohibitively expensive; additionally, the algorithm to compute the low-rank approximation costs O(n d ) per iteration. Our contribution is avoiding formation of the moment tensor, computing the low-rank tensor approximation of the moment tensor implicitly using O(pnr) operations per iteration and no extra memory. This advance opens the door to more applications of higher-order moments since they can now be efficiently computed. We present numerical evidence of the computational savings and show an example of estimating the means for higher-order moments.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Charge Condensation and Lattice Coupling Drives Stripe Formation in Nickelates

Revealing the predominant driving force behind symmetry breaking in correlated materials is sometimes a formidable task due to the intertwined nature of different degrees of freedom. This is the case for La 2–x Sr x NiO 4+δ , in which coupled incommensurate charge and spin stripes form at low temperatures. Here, we use resonant x-ray photon correlation spectroscopy to study the temporal stability and domain memory of the charge and spin stripes in La 2–x Sr x NiO 4+δ . Although spin stripes are more spatially correlated, charge stripes maintain a better temporal stability against temperature change. More intriguingly, charge order shows robust domain memory with thermal cycling up to 250 K, far above the ordering temperature. Furthermore, these results demonstrate the pinning of charge stripes to the lattice and that charge condensation is the predominant factor in the formation of stripe orders in nickelates.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Efficient Parallelization of Irregular Applications on GPU Architectures

With the enlarging computation capacity of general Graphics Processing Units (GPUs), leveraging GPUs to accelerate parallel applications has become a critical topic in academia and industry. However, a wide range of irregular applications with the computation-/memory-intensive nature cannot easily achieve high GPU utilization. The challenges mainly involve the following aspects: first, data dependence leads to coarse-grained kernel and inefficient parallelism; second, heavy GPU memory usage may cause frequent memory evictions and extra overhead of I/O; third, specific computation patterns produce memory redundancies; last, workload balance and data reusability conjunctly benefit the overall performance, but there may exist a dynamic trade-off between them. Targeting these challenges, this dissertation proposes multiple optimizations to accelerate two real-world applications: many-body correlation functions to simulate nuclear physics in a large-scale scientific system; the other is the eALS-based matrix factorization recommendation system. To accelerate the calculations of many-body correlation functions, this dissertation presents three frameworks in GPU memory management and multi-GPU scheduling. Firstly, an optimized systematic GPU memory management framework, MemHC, utilizes a series of new memory reduction designs in GPU memory allocation, CPU/GPU communications, and GPU memory oversubscription. Secondly, an enhanced multi-GPU scheduling framework, MICCO, particularly by taking both data dimension (e.g., data reuse and data eviction) and computation dimension into account. MICCO designs a heuristic scheduling algorithm and a machine learning-based regression model to generate the optimal settings of a proposed new concept to manage the trade-off. Thirdly, a locality-aware multi-GPU scheduling framework. This scheduler leverages pipeline batch generation with a looking-ahead strategy by building local dependency graphs for memory transfer reduction and better data reuse, achieving up to 79.92% memory cost reduction and 1.67x speedup. To parallelize the eALS-based recommendation system, this dissertation proposes an efficient CPU/GPU heterogeneous recommendation system, HEALS. HEALS employs newly designed architecture-adaptive data formats to achieve load balance and good data locality on CPU and GPU. To mitigate the data dependence, HEALS presents a CPU/GPU collaboration model for both task parallelism and data parallelism with multiple kernel computation optimizations. In summary, this dissertation efficiently accelerates two typical irregular applications on GPUs by building four frameworks, including CPU/GPU collaboration, GPU memory management, and multi-GPU scheduling.

Wang, Qihan↗
DOE OSTI2022

Digital coded exposure formation of frames from event-based imagery

Abstract Event-driven neuromorphic imagers have a number of attractive properties including low-power consumption, high dynamic range, the ability to detect fast events, low memory consumption and low band-width requirements. One of the biggest challenges with using event-driven imagery is that the field of event data processing is still embryonic. In contrast, decades worth of effort have been invested in the analysis of frame-based imagery. Hybrid approaches for applying established frame-based analysis techniques to event-driven imagery have been studied since event-driven imagers came into existence. However, the process for forming frames from event-driven imagery has not been studied in detail. This work presents a principled digital coded exposure approach for forming frames from event-driven imagery that is inspired by the physics exploited in a conventional camera featuring a shutter. The technique described in this work provides a fundamental tool for understanding the temporal information content that contributes to the formation of a frame from event-driven imagery data. Event-driven imagery allows for the application of arbitrary virtual digital shutter functions to form the final frame on a pixel-by-pixel basis. The proposed approach allows for the careful control of the spatio-temporal information that is captured in the frame. Furthermore, unlike a conventional physical camera, event-driven imagery can be formed into any variety of possible frames in post-processing after the data is captured. Furthermore, unlike a conventional physical camera, coded-exposure virtual shutter functions can assume arbitrary values including positive, negative, real, and complex values. The coded exposure approach also enables the ability to perform applications of industrial interest such as digital stroboscopy without any additional hardware. The ability to form frames from event-driven imagery in a principled manner opens up new possibilities in the ability to use conventional frame-based image processing techniques on event-driven imagery.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

A simulation study of carbon storage with active reservoir management

As part of the Integrated Midcontinent Stacked Carbon Storage Hub (IMSCS-Hub) project led by Battelle Memorial Institute, a study was conducted to determine the feasibility of storing carbon dioxide (CO 2 ) in the stacked saline rock formations of the Sleepy Hollow Field (SHF), located in Red Willow County, southern Nebraska. A series of CO 2 injection simulation scenarios, with and without active reservoir management (ARM; brine extraction), were evaluated to investigate the feasibility of storing 50+ million tonnes (Mt) of CO 2 . The results indicated CO 2 injection combined with ARM may enable permanent storage of 50+ Mt of CO 2 . The area of review (AOR), the area in which underground sources of drinking water (USDWs) might be endangered during CO 2 injection, was assessed for the simulation scenarios. In comparison to a case without ARM, brine extraction resulted in a much smaller AOR, covering an area of 42 square miles (108.8 km 2 ), roughly one-fourth the size of an AOR resulting from CO 2 injection without ARM. Our findings, presented in this paper, indicate that CO 2 injection with ARM can improve the CO 2 storage capacity of a geologic storage complex up to 100% while also reduce the rate of pressure buildup in the subsurface, resulting in a 75% reduction in AOR. This may help in lowering carbon capture and storage project costs, risks, and effort needed to meet monitoring requirements for a storage project.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Thermodynamic origin of nonvolatility in resistive memory

Electronic switches based on the migration of high-density point defects, or memristors, are poised to revolutionize post-digital electronics. Despite significant research, key mechanisms for filament formation and oxygen transport remain unresolved, hindering our ability to predict and design device properties. For example, experiments have achieved 10 orders of magnitude longer retention times than predicted by current models. Here, using electrical measurements, scanning probe microscopy, and first-principles calculations on tantalum oxide memristors, we reveal that the formation and stability of conductive filaments crucially depend on the thermodynamic stability of the amorphous oxygen-rich and oxygen-poor compounds, which undergo composition phase separation. Including the previously neglected effects of this amorphous phase separation reconciles unexplained discrepancies in retention and enables predictive design of key performance indicators such as retention stability. Furthermore, this result emphasizes non-ideal thermodynamic interactions as key design criteria in post-digital devices with defect densities substantially exceeding those of today’s covalent semiconductors.

36 MATERIALS SCIENCE↗
DOE OSTI2020

High-throughput phase-field simulations and machine learning of resistive switching in resistive random-access memory

Metal oxide-based Resistive Random-Access Memory (RRAM) exhibits multiple resistance states, arising from the activation/deactivation of a conductive filament (CF) inside a switching layer. Understanding CF formation kinetics is critical to achieving optimal functionality of RRAM. Here a phase-field model is developed, based on materials properties determined by ab initio calculations, to investigate the role of electrical bias, heat transport and defect-induced Vegard strain in the resistive switching behavior, using MO 2- x systems such as HfO 2- x as a prototypical model system. It successfully captures the CF formation and resultant bipolar resistive switching characteristics. High-throughput simulations are performed for RRAMs with different material parameters to establish a dataset, based on which a compressed-sensing machine learning is conducted to derive interpretable analytical models for device performance (current on/off ratio and switching time) metrics in terms of key material parameters (electrical and thermal conductivities, Vegard strain coefficients). These analytical models reveal that optimal performance (i.e., high current on/off ratio and low switching time) can be achieved in materials with a low Lorenz number, a fundamental material constant. This work provides a fundamental understanding to the resistive switching in RRAM and demonstrates a computational data-driven methodology of materials selection for improved RRAM performance, which can also be applied to other electro-thermo-mechanical systems.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Defect-induced formation and frustration-driven multiple magnetic transitions in Gd 2 Co 0.90 Si 2.90

A new ternary compound, Gd 2 Co 0.90 Si 2.90 , has been synthesized in a chemically single phase by deliberately introducing lattice vacancies in the Co and Si sites. The system is characterized by DC magnetization, heat capacity, resistivity and density functional theory (DFT) calculations. Here, a detailed experimental study reveals that the system exhibits an antiferromagnetic transition below T N = 11.3 K followed by spin freezing behaviour below T B ~ 4.8 K. An additional high-temperature magnetic transition could also be detected at T H ~ 150 K, which is short range in character and is associated with defect-induced polarization of the conduction electrons. The spin-glass-like state formation in the system is additionally bolstered by the observation of magnetic relaxation and associated aging phenomena as well as the magnetic memory effect. On the basis of non-equilibrium dynamical behaviour, we argue that the glassy state in this compound favours the hierarchical model over the droplet model. DFT calculations and experimental outcomes establish that the ground state is magnetically frustrated due to the small energy difference between distinct spin configurations having closely spaced ground-state energies.

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

Persistence length regulates emergent dynamics in active roller ensembles

Active colloidal fluids, biological and synthetic, often demonstrate complex self-organization and the emergence of collective behavior. Spontaneous formation of multiple vortices has been recently observed in a variety of active matter systems, however, the generation and tunability of the active vortices not controlled by geometrical confinement remain challenging. Here, we exploit the persistence length of individual particles in ensembles of active rollers to tune the formation of vortices and to orchestrate their characteristic sizes. We use two systems and employ two different approaches exploiting shape anisotropy or polarization memory of individual units for control of the persistence length. We characterize the dynamics of emergent multi-vortex states and reveal a direct link between the behavior of the persistence length and properties of the emergent vortices. We further demonstrate common features between the two systems including anti-ferromagnetic ordering of the neighboring vortices and active turbulent behavior with a characteristic energy cascade in the particles velocity field energy spectra. Finally, our findings provide insights into the onset of spatiotemporal coherence in active roller systems and suggest a control knob for manipulation of dynamic self-assembly in active colloidal ensembles.

42 ENGINEERING↗
DOE OSTI2020

A High-Throughput Solver for Marginalized Graph Kernels on GPU

Here, we present the design and optimization of a solver for efficient and high-throughput computation of the marginalized graph kernel on General Purpose GPUs. The graph kernel is computed using the conjugate gradient method to solve a generalized Laplacian of the tensor product between a pair of graphs. To cope with the large gap between the instruction throughput and the memory bandwidth of the GPUs, our solver forms the graph tensor product on-the-fly without storing it in memory. This is achieved by using threads in a warp cooperatively to stream the adjacency and edge label matrices of individual graphs by small square matrix blocks called tiles, which are then staged in registers and the shared memory for later reuse. Warps across a thread block can further share tiles via the shared memory to increase data reuse. We exploit the sparsity of the graphs hierarchically by storing only non-empty tiles using a coordinate format and nonzero elements within each tile using bitmaps. We propose a new partition-based reordering algorithm for aggregating nonzero elements of the graphs into fewer but denser tiles to further exploit sparsity. We carry out extensive theoretical analyses on the graph tensor product primitives for tiles of various density and evaluate their performance on synthetic and real-world datasets. Our solver delivers three to four orders of magnitude speedup over existing CPU-based solvers such as GraKeL and GraphKernels. The capability of the solver enables kernel-based learning tasks at unprecedented scales.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Unveiling the star formation history of the Upper Scorpius association through its kinematics

ABSTRACT Stellar associations can be discerned as overdensities of sources not only in the physical space but also in the velocity space. The common motion of their members, gradually eroded by the galactic tidal field, is partially reminiscent of the initial kinematic structure. Using recent data from Gaia EDR3, combined with radial velocities from GALAH and APOGEE, we traced back the present positions of stars belonging to Upper Scorpius (USCO), a subgroup of Scorpius–Centaurus, the nearest OB association. About one half of the subgroup (the ‘clustered’ population) appears composed of many smaller entities, which were in a more compact configuration in the past. The presence of a kinematic duality is reflected into an age spread between this younger clustered population and an older diffuse population, in turn confirmed by a different fraction fD of disc-bearing stars (fD = 0.24 ± 0.02 versus fD = 0.10 ± 0.01). Star formation in USCO appears to have lasted more than 10 Myr and proceeded in small groups that, after a few Myr, dissolve in the field of the older population but retain for some time memory of their initial structure. The difference of ages inferred through isochrones and kinematics, in this regard, could provide a powerful tool to quantify the time-scale of gas removal.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Nonvolatile memory cells from hafnium zirconium oxide ferroelectric tunnel junctions using Nb and NbN electrodes

Ferroelectric tunnel junctions (FTJs) utilizing hafnium zirconium oxide (HZO) have attracted interest as non-volatile memory for microelectronics due to ease of integration into back-end-of-line (BEOL) complementary metal oxide semiconductor fabrication. This work examines asymmetric electrode NbN/HZO/Nb devices with 7 nm thick HZO as FTJs in a memory structure, with an output resistance that can be controlled by read and write voltages. The individual FTJs are measured to have a tunneling electroresistance of 10 during the read state without significant filament conduction formation and reasonable ferroelectric performance. Endurance and remanent polarizations of up to 10 5 cycles and 20 μC/cm 2 , respectively, are measured and are shown to be dependent on the cycling voltage. Electrical measurements demonstrate how magnitude of the write pulse can modulate the high state resistance and the read pulse influences both resistance values as well as separation of resistance states. Then, by using two opposite switching FTJ devices in series, a programmable nonvolatile resistor divider is demonstrated. Measurements of these two FTJ unit memory cells show wide applicability to a BEOL microfabrication process for a re-readable, rewritable, and nonvolatile memory cell.

42 ENGINEERING↗
DOE OSTI2020

Efficient Treatment of Large Active Spaces through Multi-GPU Parallel Implementation of Direct Configuration Interaction

In this study, we have extended our graphical processing unit (GPU)-accelerated direct configuration interaction program to multiple devices, reducing iteration times for configuration spaces of 165 million determinants to only 3 s using NVIDIA P100 GPUs. Similar improvements in the one- and two-particle reduced density matrix formation allow for fast analytical energy gradients and electronic properties. Our parallel algorithm enables the calculation of arbitrarily large configuration spaces (limited only by available system memory), with iteration times of 13 min for an active space of 18 electrons in 18 orbitals (2.4 billion determinants) using six consumer grade NVIDIA 1080Ti GPUs. These advances enable routine molecular dynamics simulations, geometry optimizations, and absorption spectrum calculations for molecules with large configuration spaces, a task that has heretofore required massive computational effort. In this work, we demonstrate the utility of our program by generating the absorption spectrum for diphenyl acetylene at the floating occupation molecular orbital complete active space configuration interaction level of theory. Lastly, several active spaces were investigated to assess the dependence of spectral features on orbital space dimension.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Multi-level, forming and filament free, bulk switching trilayer RRAM for neuromorphic computing at the edge

CMOS-RRAM integration holds great promise for low energy and high throughput neuromorphic computing. However, most RRAM technologies relying on filamentary switching suffer from variations and noise, leading to computational accuracy loss, increased energy consumption, and overhead by expensive program and verify schemes. We developed a filament-free, bulk switching RRAM technology to address these challenges. We systematically engineered a trilayer metal-oxide stack and investigated the switching characteristics of RRAM with varying thicknesses and oxygen vacancy distributions to achieve reliable bulk switching without any filament formation. We demonstrated bulk switching at megaohm regime with high current nonlinearity, up to 100 levels without compliance current. We developed a neuromorphic compute-in-memory platform and showcased edge computing by implementing a spiking neural network for an autonomous navigation/racing task. Our work addresses challenges posed by existing RRAM technologies and paves the way for neuromorphic computing at the edge under strict size, weight, and power constraints.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1976

A Landsat Digital Image Rectification System

DIRS is a Digital Image Rectification System for the geometric correction of Landsat Multispectral Scanner digital image data. DIRS removes spatial distortions from the data and brings it into conformance with the Universal Transverse Mercator (UTM) map projection. Scene data in the form of landmarks or Ground Control Points (GCPs) are used to drive the geometric correction algorithms. The system offers extensive capabilities for 'shade printing' to aid in the determination of GCPs. Affine, two dimensional least squares polynominal and spacecraft attitude modeling techniques for geometric mapping are provided. Entire scenes or selected quadralaterals may be rectified. Resampling through nearest neighbor or cubic convolution at user designated intervals is available. The output products are in the form of digital tape in band interleaved, single band or CCT format in a rotated UTM projection. The system was designed and implemented on large scale IBM 360 computers with at least 300-500K bytes of memory for user application programs and five nine track tapes plus direct access storage.

Van Wie, P.↗
NASA NTRS1977

A mini/microcomputer-based land use information system

The paper describes the Multipurpose Interactive NASA Information System (MINIS), a data management system for land-use applications. MINIS is written nearly entirely in FORTRAN IV, and has a full range of conditional, Boolean and arithmetic commands, as well as extensive format control and the capability of interactive file creation and updating. It requires a mini or microcomputer with at least 64 K of core or semiconductor memory. MINIS has its own equation-oriented query language for retrieval from different kinds of data bases. It features a graphics output which permits output of overlay maps. Some experience of the U.S. Department of Agriculture and the Tennessee State Planning Office with MINIS is discussed.

Seitz, R. N.↗