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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2011

Developement of 3D Vertically Integrated Pattern Recognition Associative Memory (VIPRAM)

Many next-generation physics experiments will be characterized by the collection of large quantities of data, taken in rapid succession, from which scientists will have to unravel the underlying physical processes. In most cases, large backgrounds will overwhelm the physics signal. Since the quantity of data that can be stored for later analysis is limited, real-time event selection is imperative to retain the interesting events while rejecting the background. Scaling of current technologies is unlikely to satisfy the scientific needs of future projects, so investments in transformational new technologies need to be made. For example, future particle physics experiments looking for rare processes will have to address the demanding challenges of fast pattern recognition in triggering as detector hit density becomes significantly higher due to the high luminosity required to produce the rare processes. In this proposal, we intend to develop hardware-based technology that significantly advances the state-of-the-art for fast pattern recognition within and outside HEP using the 3D vertical integration technology that has emerged recently in industry. The ultimate physics reach of the LHC experiments will crucially depend on the tracking trigger's ability to help discriminate between interesting rare events and the background. Hardware-based pattern recognition for fast triggering on particle tracks has been successfully used in high-energy physics experiments for some time. The CDF Silicon Vertex Trigger (SVT) at the Fermilab Tevatron is an excellent example. The method used there, developed in the 1990's, is based on algorithms that use a massively parallel associative memory architecture to identify patterns efficiently at high speed. However, due to much higher occupancy and event rates at the LHC, and the fact that the LHC detectors have a much larger number of channels in their tracking detectors, there is an enormous challenge in implementing pattern recognition for a track trigger, requiring about three orders of magnitude more associative memory patterns than what was used in the original CDF SVT. Significant improvement in the architecture of associative memory structures is needed to run fast pattern recognition algorithms of this scale. We are proposing the development of 3D integrated circuit technology as a way to implement new associative memory structures for fast pattern recognition applications. Adding a 'third' dimension to the signal processing chain, as compared to the two-dimensional nature of printed circuit boards, Field Programmable Gate Arrays (FPGAs), etc., opens up the possibility for new architectures that could dramatically enhance pattern recognition capability. We are currently performing preliminary design work to demonstrate the feasibility of this approach. In this proposal, we seek to develop the design and perform the ASIC engineering necessary to realize a prototype device. While our focus here is on the Energy Frontier (e.g. the LHC), the approach may have applications in experiments in the Intensity Frontier and the Cosmic Frontier as well as other scientific and medical projects. In fact, the technique that we are proposing is very generic and could have wide applications far beyond track trigger, both within and outside HEP.

43 PARTICLE ACCELERATORS↗
DOE OSTI2011

Metrology and Failure Analysis for 3D IC Integration

At the same time as research in 3D TSV technology is advancing quickly, the analytical techniques used in the evaluation of 3D stacks must also advance in capability. Microscopy techniques for which silicon is opaque such as scanning acoustic microscopy (SAM) and confocal infrared (IR) microscopy are capable of inspecting the interface between bonded wafer pairs, while high resolution X-ray computed tomography (XCT) is used to detect voids in TSVs. With nano-XCT, voids in copper TSVs with sub-100 nm size can be visualized. For more detailed failure characterization, a target Focused Ion Beam (FIB) cross-section through the localized region of interest (defect) and subsequent scanning electron microscopy (SEM) imaging is proposed. Currently, the most important requirement is to reduce the so-called time-to-data, e. g. for defect localization using nano-XCT and for cross-section characterization.

36 MATERIALS SCIENCE↗
NASA NTRS1997

Illustrating Surface Shape in Volume Data via Principal Direction-Driven 3D Line Integral Convolution

The three-dimensional shape and relative depth of a smoothly curving layered transparent surface may be communicated particularly effectively when the surface is artistically enhanced with sparsely distributed opaque detail. This paper describes how the set of principal directions and principal curvatures specified by local geometric operators can be understood to define a natural 'flow' over the surface of an object, and can be used to guide the placement of the lines of a stroke texture that seeks to represent 3D shape information in a perceptually intuitive way. The driving application for this work is the visualization of layered isovalue surfaces in volume data, where the particular identity of an individual surface is not generally known a priori and observers will typically wish to view a variety of different level surfaces from the same distribution, superimposed over underlying opaque structures. By advecting an evenly distributed set of tiny opaque particles, and the empty space between them, via 3D line integral convolution through the vector field defined by the principal directions and principal curvatures of the level surfaces passing through each gridpoint of a 3D volume, it is possible to generate a single scan-converted solid stroke texture that may intuitively represent the essential shape information of any level surface in the volume. To generate longer strokes over more highly curved areas, where the directional information is both most stable and most relevant, and to simultaneously downplay the visual impact of directional information in the flatter regions, one may dynamically redefine the length of the filter kernel according to the magnitude of the maximum principal curvature of the level surface at the point around which it is applied.

Interrante, Victoria↗
DOE OSTI2014

3D J-Integral Capability in Grizzly

This report summarizes work done to develop a capability to evaluate fracture contour J-Integrals in 3D in the Grizzly code. In the current fiscal year, a previously-developed 2D implementation of a J-Integral evaluation capability has been extended to work in 3D, and to include terms due both to mechanically-induced strains and due to gradients in thermal strains. This capability has been verified against a benchmark solution on a model of a curved crack front in 3D. The thermal term in this integral has been verified against a benchmark problem with a thermal gradient. These developments are part of a larger effort to develop Grizzly as a tool that can be used to predict the evolution of aging processes in nuclear power plant systems, structures, and components, and assess their capacity after being subjected to those aging processes. The capabilities described here have been developed to enable evaluations of Mode- stress intensity factors on axis-aligned flaws in reactor pressure vessels. These can be compared with the fracture toughness of the material to determine whether a pre-existing flaw would begin to propagate during a pos- tulated pressurized thermal shock accident. This report includes a demonstration calculation to show how Grizzly is used to perform a deterministic assessment of such a flaw propagation in a degraded reactor pressure vessel under pressurized thermal shock conditions. The stress intensity is calculated from J, and the toughness is computed using the fracture master curve and the degraded ductile to brittle transition temperature.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Temperature Mapping of Stacked Silicon Dies from X-Ray-Diffraction Intensities

Increasing power densities in integrated circuits have led to an increased prevalence of thermal hotspots in integrated circuits. Tracking these thermal hotspots is imperative to prevent circuit failures. In three- dimensional (3D) integrated circuits, conventional surface techniques like infrared thermometry are unable to measure the 3D temperature distribution, and optical and magnetic resonance techniques are difficult to apply due to the presence of metals and large current densities. X-rays offer a high penetration depth and can be used to probe 3D structures. We report a method utilizing the temperature dependence of x-ray-diffraction intensity via the Debye-Waller factor to simultaneously map the temperature of individual silicon dies in a stack. Here, utilizing beamline 1-ID-E at the Advanced Photon Source (Argonne), we demonstrate, for each individual silicon die, a temperature resolution of 3 K, a spatial resolution of 100 × 400 μm 2 , and a temporal resolution of 20 s. Utilizing a sufficiently high-intensity laboratory source, e.g., from a liquid-anode source, this method can be scaled down to laboratories for noninvasive temperature mapping of 3D integrated circuits.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

A 3D Implementation of Convolutional Neural Network for Fast Inference

Low latency inference has many applications in edge machine learning. In this paper, we present a run-time configurable convolutional neural network (CNN) inference ASIC design for low-latency edge machine learning. By implementing a 5-stage pipelined CNN inference model in a 3D ASIC technology, we demonstrate that the model distributed on two dies utilizing face-to-face (F2F) 3D integration achieves superior performance. Our experimental results show that the design based on 3D integration achieves 43% better energy-delay product when compared to the traditional 2D technology.

Miniskar, Narasinga Rao↗
DOE OSTI2017

3D-printed, integrated plug-and-play turbine-generator set for very-low-head hydro. Final Technical Report DOE-EMotors-15757-1

Hydro power has been used since the early days of electricity, but is generally limited to very large facilities. There remains a vast array of untapped locations, either rivers, tidal currents, or also man-made facilities where energy harvesting is technically feasible, but still too costly. E-Motors, in partnership with MTI, is developing an integrated design aimed at facilitating manufacturing, installation, and retrofitting. The integrated design includes a rim on the outside of the turbine runner to house the electrical generator rotor, a so-called rim drive. With this approach, a compact, in-line assembly can be produced and placed in straight pipes, without having to resort to elbows, shafts, and outside generators, thus improving efficiency and facilitating assembly. The long term goal of the project is to develop a realistic prototype for market development and start of manufacturing. During this Phase I grant, in collaboration with the University of Wisconsin-Milwaukee (UWM), the team pursued two objectives: First, design and test a small (3”) system in a laboratory at UWM, and second develop a prototype design at higher power between 50 and 100 kW. The tests showed the potential for integrating the generator rotor with the turbine runner. Output power is so far limited due to test conditions, but CFD calculations show good efficiency potential. With the larger system, a number of possibilities were explored, including: a generator design matching the turbine output, and capable of generating a peak of 86 kW from a flow of 136 cfs at 9’ of head; various intake tube geometries, showing that an elliptical shape is quite favorable; removing the hub, something made possible with a rim design, which can improve efficiency by about 10 percentage points.

13 HYDRO ENERGY↗
DOE OSTI2026

BASIN-3D Data Integration for Selected ARM Data Field Campaign Report

The purpose of this data services request was to demonstrate integration of the Atmospheric Radiation Measurement (ARM) User Facility’s “met” datastreams with time series data from other earth science data sources using the BASIN-3D data synthesis software tool. BASIN-3D is an open-source Python library that enables researchers to integrate data across configured public and private data sources. It provides a common query language for researchers to request measurement locations and time series data based on specified locations, variables, time period, statistics, aggregation, and data quality. BASIN-3D acquires the data that match the query from each configured data source and translates the results into harmonized vocabularies, thus reducing researchers' data-wrangling effort. In addition, because the queries are executed on demand, researchers can easily regenerate their synthesized data sets as new data and/or data updates become available, eliminating one-off data products. BASIN-3D can output data using a variety of different data structures for end-user applications including Python pandas data frames and hdf5 output formats.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Scalable fabrication of Chip-integrated 3D-nanostructured electronic devices via DNA-programmable assembly

DNA-based self-assembly methods have demonstrated powerful and unique capabilities to encode nanomaterial structures through the prescribed placement of inorganic and biological nanocomponents. However, the challenge of selectively growing DNA superlattices on specific locations of surfaces and their integration with conventional nanofabrication has hindered the fabrication of three-dimensional (3D) DNA-assembled functional devices. Here, we present a scalable nanofabrication technique that combines bottom-up and top-down approaches for selective growth of 3D DNA superlattices on gold microarrays. This approach allows for the fabrication of self-assembled 3D-nanostructured electronic devices. DNA strands are bound onto the gold arrays, which anchor DNA origami frames and promote ordered framework growth on the specific areas of the surface, enabling control of the lateral placement and orientation of superlattices. DNA frameworks selectively grown on the pads are subsequently templated to nanoscale silica and tin oxide (SnO x ) that follow the architecture, as confirmed by structural and chemical characterizations. The fabricated SnO x superlattices are integrated into devices that demonstrate photocurrent response.

36 MATERIALS SCIENCE↗
DOE OSTI2020

3D-ReG: A 3D ReRAM-based Heterogeneous Architecture for Training Deep Neural Networks

Deep neural network (DNN) models are being expanded to a broader range of applications. The computational capability of traditional hardware platforms cannot accommodate the growth of model complexity. Among recent technologies to accelerate DNN, resistive memory (ReRAM)-based processing-in-memory (PIM) emerged as a promising solution for DNN inference due to its high efficiency for matrix-based computation. We face two major technical challenges in extending the use of ReRAM-based accelerators for training: (1) full-precision data is essential in back-propagation; (2) the need to support both feed-forward and back-propagation aggravates the data-movement burden. We propose a heterogeneous architecture named as 3D-ReG, which leverages full-precision GPU to ensure training accuracy and low-overhead 3D integration to provide low-cost data movements. Moreover, we introduce conservative and aggressive task-mapping schemes, which partition the computation phases in different ways to balance execution efficiency and training accuracy. We evaluate 3D-ReG implemented with two 3D integration technologies, through-silicon vias (TSVs) and monolithic inter-tier vias (MIVs), and compare them with GPU-only and PIM-only counterparts. Various GPU-only platforms using two main-memory technologies (DRAM, ReRAM) and three interconnect technologies (2D, TSV, MIV) are evaluated as well. Experimental results show that 3D-ReG can achieve on average 5.64× training speedup and 3.56× higher energy efficiency compared with the GPU with DRAM as main memory, at the cost of 0.05%–3.39% accuracy drop. We define a new metric, gain-loss ratio (GLR), which quantitatively evaluates the capability of a DNN training hardware in terms of the model accuracy and hardware efficiency. The results of our comparison show that the aggressive task-mapping scheme on MIV-based 3D-ReG outperforms the other methods.

Computer Science↗
DOE OSTI2022

High Temperature Optocoupler for 3D High Density Power Modules

The goal of this proposed research is to develop a reliable high-temperature optocouplers, which can operate at 250°C with at least ten-year lifetime, and replace isolation transforms as the galvanic isolation solution for the 3D integration of high density power modules. The electrification of future transportations (i.e., electric vehicles) will continuously drive the demand for high density power modules. Optocouplers (i.e., packaged light emitter and detector) as a promising candidate to replace bulky isolation transformers are highly desirable to facilitate the continuous scale-down of gate driver circuitry that will lead to 3D high density power modules and achieve disruptive performance in terms of thermal management, power density, power efficiency, reliability and operating environments. However, regular semiconductor optoelectronic materials and devices have significant difficulty functioning in the harsh environments designated for high density power module usage (such as operation at high temperatures). Ultimately, it is not the intrinsic properties of power devices that prevent their use at higher temperatures, but rather the low voltage electronics needed to drive them and the packaging that surrounds them. The typical operating temperature for optocouplers is only up to 100°C, due to the limitations of light emitting diode (LED) devices inside and packaging materials. A systematic characterization methodology will be developed to analyze the performance, lifetime and reliability of LED devices and distinguish multiple failure mechanisms at high temperatures. An original methodology of “design for reliability” will be developed to design the optoelectronic devices with high reliability and long lifetime at high temperatures. A new architecture of high temperature high reliable optocouplers will be developed, fabricated and demonstrated with continuous operating at 250°C. The development of efficient, reliable high density 3D power modules is the foundation for energy efficiency and energy reliability. Enabled with advanced 3D integration and packaging technologies, high density power module solutions can achieve much more superior performance over the conventional discrete solutions in terms of efficiency, thermal management and power density. The proposed concept of high temperature optocouplers as the galvanic isolation solution for high density power modules will bring together interdisciplinary research involving the wide bandgap materials, optoelectronics, high reliable device design, electronics packaging and power modules. A streamline of skilled personnel would be trained including graduate and undergraduate students, local engineers and scientists which are in great demand to both academia and optoelectronics industry. The proposed research topics, such as, solid state lighting and high temperature device reliability, are currently of major interest at the Department of Energy, in particular, Sandia National Laboratories. This project can enhance collaborations between the University of Arkansas (UA) and Sandia National Laboratories. The findings of the proposed research are expected to be integrated into high density 3-D power modules at the Engineering Research Center for Power Optimization for Electro-Thermal Systems (POETS).

42 ENGINEERING↗
DOE OSTI2017

High-gain monolithic 3D CMOS inverter using layered semiconductors

Here, we experimentally demonstrate a monolithic 3D integrated complementary metal oxide semiconductor (CMOS) inverter using layered transition metal dichalcogenide semiconductor N-channel (NMOS) and P-channel (PMOS) MOSFETs, which are sequentially integrated on two levels. The two devices share a common gate. Molybdenum disulphide and tungsten diselenide are used as channel materials for NMOS and PMOS, respectively, with an ON-to-OFF current ratio (I ON /I OFF ) greater than 106 and electron and hole mobilities of 37 and 236 cm 2 /Vs, respectively. The voltage gain of the monolithic 3D inverter is about 45 V/V at a supply voltage of 1.5 V and a gate length of 1 μm. This is the highest reported gain at the smallest gate length and the lowest supply voltage for any 3D integrated CMOS inverter using any layered semiconductor.

42 ENGINEERING↗
NASA NTRS2017

GPS/Optical/Inertial Integration for 3D Navigation Using Multi-Copter Platforms

In concert with the continued advancement of a UAS traffic management system (UTM), the proposed uses of autonomous unmanned aerial systems (UAS) have become more prevalent in both the public and private sectors. To facilitate this anticipated growth, a reliable three-dimensional (3D) positioning, navigation, and mapping (PNM) capability will be required to enable operation of these platforms in challenging environments where global navigation satellite systems (GNSS) may not be available continuously. Especially, when the platform's mission requires maneuvering through different and difficult environments like outdoor opensky, outdoor under foliage, outdoor-urban and indoor, and may include transitions between these environments. There may not be a single method to solve the PNM problem for all environments. The research presented in this paper is a subset of a broader research effort, described in [1]. The research is focused on combining data from dissimilar sensor technologies to create an integrated navigation and mapping method that can enable reliable operation in both an outdoor and structured indoor environment. The integrated navigation and mapping design is utilizes a Global Positioning System (GPS) receiver, an Inertial Measurement Unit (IMU), a monocular digital camera, and three short to medium range laser scanners. This paper describes specifically the techniques necessary to effectively integrate the monocular camera data within the established mechanization. To evaluate the developed algorithms a hexacopter was built, equipped with the discussed sensors, and both hand-carried and flown through representative environments. This paper highlights the effect that the monocular camera has on the aforementioned sensor integration scheme's reliability, accuracy and availability.

Dill, Evan T.↗
DOE OSTI2016

Probing Phase Transformations and Microstructural Evolutions at the Small Scales: Synchrotron X-ray Microdiffraction for Advanced Applications in [Phase 3 Memory,] 3D IC (Integrated Circuits) and Solar PV (Photovoltaic) Devices

Synchrotron x-ray microdiffraction (μXRD) allows characterization of a crystalline material in small, localized volumes. Phase composition, crystal orientation and strain can all be probed in few-second time scales. Crystalline changes over a large areas can be also probed in a reasonable amount of time with submicron spatial resolution. However, despite all the listed capabilities, μXRD is mostly used to study pure materials but its application in actual device characterization is rather limited. This article will explore the recent developments of the μXRD technique illustrated with its advanced applications in microelectronic devices and solar photovoltaic systems. Application of μXRD in microelectronics will be illustrated by studying stress and microstructure evolution in Cu TSV (through silicon via) during and after annealing. Here, the approach allowing study of the microstructural evolution in the solder joint of crystalline Si solar cells due to thermal cycling will be also demonstrated.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Ceria-based nanoflake arrays integrated on 3D cordierite honeycombs for efficient low-temperature diesel oxidation catalyst

A new, surfactant-free hydrothermal method has been developed for the growth of CeO 2 -based nanoflake arrays onto three-dimensional-channeled cordierite honeycomb substrates. Herein, a leaching-crystallization mechanism was proposed where the hydrothermal reaction, only involving cerium nitrate and water, leached the cordierite surface slightly and induced the formation of CeO 2 nanoparticles subsequently. Further continued reaction reincorporated Al and Si atoms leached from cordierite into CeO 2 , finally recrystallizing Ce-Al-Si composite nanoflake structures. Here, by using atomic layer deposition process, well-dispersed, size-controlled Pt nanoparticles were uniformly decorated on the CeO 2 -based nanoflakes to form the Pt/ CeO 2 nano-array-based monolithic catalyst. Despite 5-50 times reduction in the active material usage compared with the traditional wash-coated catalyst, the Pt/CeO 2 nano-array monolithic catalyst exhibited good catalytic oxidation activities over various individual gases, such as propylene, propane, CO, and NO oxidation, with 90% conversion efficiencies at temperatures below 200 °C. Under the simulated exhaust condition of low-temperature diesel combustion (LTC-D) developed by US DRIVE, the monolithic catalyst with low Pt loading (˜1 g/l) exhibits 90% conversion of catalytic oxidation over CO and hydrocarbonsat temperatures as low as ˜180 °C, much superior to the performance of traditional washcoated catalysts.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Magnetic flux imaging in a 3D superconductor integrated circuit

We report on imaging magnetic flux distributions in a multilayered superconductor integrated circuit which emerge during magnetization and after field cooling of the circuit in the DC magnetic field. The obtained complicated field maps expose the flux propagation across the patterned superconducting ground planes sandwiching layers with Josephson junction-based logic cells, fine wire grid around the functional units, and multiple superconducting fill structures located in different inner layers. The observed intricate flux distributions are explained by specific patterns of Meissner screening currents and superconducting critical currents in different mutually interacting parts of the integrated circuit. Our results provide important insights into possible ways of improving the protection of superconductor integrated circuits from magnetic fields and their resilience against flux trapping.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗