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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Monolithic Integration of Lateral HV Power MOSFET with LV CMOS for SiC Power IC Technology

This paper reports the design and process flow for monolithic integration of lateral high voltage (HV) power MOSFET with low voltage (LV) CMOS circuits for SiC Power IC technology. The reported devices and circuits are fabricated on a N-/N+ 4H-SiC substrate at 150mm, production grade- Analog Devices Inc. (ADI) Hillview fabrication facility located in San Jose. Here, the static performance characteristics of HV NMOS and LV CMOS are reported. For future high temperature applications, the static performances are fully characterized and are reported up to 200oC. Finally, to validate the fabricated CMOS, a 5-stage ring oscillator is also demonstrated.

4H-SiC↗
DOE OSTI2026

Knowledge gaps for neuromorphic ionic computing

BACKGROUND Neuromorphic computing, inspired by the human brain’s ability to process information efficiently, represents a transformative approach to computation. In this Review, we explore the emerging field of neuromorphic ionic computing, which leverages ionic conduction and coupling to mimic neural processes, and identify critical knowledge gaps that must be addressed to realize its full potential. A central theme of the discussion is energy efficiency, a challenge that is both a limitation and an opportunity for this technology. Although complementary metal-oxide semiconductor (CMOS)–based neuromorphic technologies have made strides in scaling to billions of neurons and are increasingly applied in artificial intelligence and numerical computing, they remain orders of magnitude behind the human brain in terms of connectivity and energy efficiency. Neuromorphic ionic computing promises to overcome these limitations by leveraging the distinct architectural and operational principles of the brain. Our brains achieve this energy efficiency by combining several key features: using the same network elements to store and process information; using an incredibly complex and massively interconnected three-dimensional (3D) network of locally active elements that enables sparsity, robustness in the presence of noise, adaptation, and life-long learning; computing at comparatively low voltage and frequency; and last, taking advantage of a plethora of ions and small molecules as information carriers. Here, we propose that ionic computing systems can take advantage of similar features to achieve substantial gains in energy efficiency. ADVANCES Since the first reports of neuromorphic ionic behavior in nanofluidic channels, we have witnessed an explosion of reports that used ionic devices to produce synaptomimetic behaviors. However, achieving the goals of ionic computing requires not only implementation of much more sophisticated device functionality but also overcoming fundamental barriers in materials science, device architecture, and system integration. Current ionic devices, even those incorporating state-of-the-art materials, still suffer from limited functionality and stability, which restrict their performance and increase energy demands. Developing new materials with enhanced ionic properties is essential to overcome these limitations. Similarly, the design of neuromorphic devices must evolve to leverage the particular advantages of ionic processes. Existing architectures often follow a single-information-carrier logic of conventional electronics or are constructed of mesoscale fluidics, failing to capitalize on the energy-efficient mechanisms inherent to ionic systems or implement the multiple-information-carrier paradigm. Current neuromorphic chips focus on large-scale networks of analog memory elements based on mechanisms such as charge trap (flash), filamentary, phase change, or spin, which are built on top of a network of artificial CMOS neurons. Although such prototype networks have achieved impressive performance, it is difficult to envision how they can implement the key features such as massive connectivity, sophisticated plasticity, adaptability, sparsity, and “multichromatic” computing. Although small-scale devices have demonstrated promising results, integrating them, maintaining energy efficiency, and implementing temperature control as systems grow in complexity and size to computationally relevant scale remain major hurdles. Furthermore, interfacing neuromorphic ionic devices with existing computing technologies presents technical and conceptual challenges that will require innovative approaches that combine insights from neuroscience, materials science, and engineering. OUTLOOK Despite these challenges, the potential impact of neuromorphic ionic computing is profound with potential applications ranging from artificial intelligence to robotics and beyond. We also argue that neuromorphic ionic computing systems should not, at least in the beginning, compete with CMOS technologies but rather should focus on applications that require extreme energy efficiency with chemical and/or biological compatibility, such as biomedical applications (for example, brain-computer interfaces), environmental monitoring, and agricultural and food applications. Ultimately, this Review highlights the crucial role of interdisciplinary collaboration in advancing the field. Neuromorphic ionic computing is not merely a technological innovation; it represents a substantial step toward sustainable computation, aligning with the growing demand for energy-conscious solutions in a world that is increasingly reliant on data and computation.

Neuromorphic↗
NASA NTRS2005

Radiation Testing and Evaluation Issues for Modern Integrated Circuits

Abstract. Changes in modern integrated circuit (IC) technologies have modified the way we approach and conduct radiation tolerance and testing of electronics. These changes include scaling of geometries, new materials, new packaging technologies, and overall speed and device complexity challenges. In this short course section, we will identify and discuss these issues as they impact radiation testing, modeling, and effects mitigation of modern integrated circuits. The focus will be on CMOS-based technologies, however, other high performance technologies will be discussed where appropriate. The effects of concern will be: Single-Event Effects (SEE) and steady state total ionizing dose (TID) IC response. However, due to the growing use of opto-electronics in space systems issues concerning displacement damage testing will also be considered. This short course section is not intended to provide detailed "how-to-test" information, but simply provide a snapshot of current challenges and some of the approaches being considered.

LaBel, Kenneth A.↗
NASA NTRS2012

Radiation-Hard SpaceWire/Gigabit Ethernet-Compatible Transponder

A radiation-hard transponder was developed utilizing submicron/nanotechnology from IBM. The device consumes low power and has a low fabrication cost. This device utilizes a Plug-and-Play concept, and can be integrated into intra-satellite networks, supporting SpaceWire and Gigabit Ethernet I/O. A space-qualified, 100-pin package also was developed, allowing space-qualified (class K) transponders to be delivered within a six-month time frame. The novel, optical, radiation-tolerant transponder was implemented as a standalone board, containing the transponder ASIC (application specific integrated circuit) and optical module, with an FPGA (field-programmable gate array) friendly parallel interface. It features improved radiation tolerance; high-data-rate, low-power consumption; and advanced functionality. The transponder utilizes a patented current mode logic library of radiation-hardened-by-architecture cells. The transponder was developed, fabricated, and radhard tested up to 1 MRad. It was fabricated using 90-nm CMOS (complementary metal oxide semiconductor) 9 SF process from IBM, and incorporates full BIT circuitry, allowing a loop back test. The low-speed parallel LVCMOS (lowvoltage complementary metal oxide semiconductor) bus is compatible with Actel FPGA. The output LVDS (low-voltage differential signaling) interface operates up to 1.5 Gb/s. Built-in CDR (clock-data recovery) circuitry provides robust synchronization and incorporates two alarm signals such as synch loss and signal loss. The ultra-linear peak detector scheme allows on-line control of the amplitude of the input signal. Power consumption is less than 300 mW. The developed transponder with a 1.25 Gb/s serial data rate incorporates a 10-to-1 serializer with an internal clock multiplication unit and a 10-1 deserializer with internal clock and data recovery block, which can operate with 8B10B encoded signals. Three loop-back test modes are provided to facilitate the built-in-test functionality. The design is based on a proprietary library of differential current switching logic cells implemented in the standard 90-nm CMOS 9SF technology from IBM. The proprietary low-power LVDS physical interface is fully compatible with the SpaceWire standard, and can be directly connected to the SFP MSA (small form factor pluggable Multiple Source Agreement) optical transponder. The low-speed parallel interfaces are fully compatible with the standard 1.8 V CMOS input/output devices. The utilized proprietary annular CMOS layout structures provide TID tolerance above 1.2 MRad. The complete chip consumes less than 150 mW of power from a single 1.8-V positive supply source.

Katzman, Vladimir↗
NASA NTRS2002

Battling Brittle Bones

The accuDEXA(R) Bone Mineral Density Assessment System, manufactured by Schick Technologies, Inc., utilizes "camera on a chip" sensor technology invented and developed by NASA's Jet Propulsion Laboratory. Schick's accuDEXA system offers several advantages over traditional osteoporosis tests, which assess bone density loss in the hip and spine, and require specialized personnel to conduct. With accuDEXA, physicians can test the entire body's bone density at a peripheral site, such as the finger, without applying gels or having patients remove garments. Results are achieved in 30 seconds and printed out in less than a minute, compared to the estimated exam time of 15 minutes for hip and spine density analyses. Schick has also applied the CMOS APS technology to a new software product that performs dental radiography using up to 90 percent less radiation exposure than conventional X-rays. Called Computed Dental Radiography(R), the new digital imaging product utilizes an electronic sensor in place of X-ray film to generate sharp and clear images that appear on a computer screen within 3 seconds, and can be enlarged and enhanced to identify problems.

Source record↗
NASA NTRS2018

Micromechanical Broadband Infrared Sensors based on Piezoelectric Bending Resonators

There is a high demand for high-performance and low-cost uncooled infrared (IR) detectors. In order to meet this need we are investigating the use of MEMS piezoelectric resonator technology using aluminum nitride (AlN) thin films. Recent research has shown that piezoelectric resonators have the potential to be used as a core element for highly sensitive, low-noise, and low-power uncooled IR detectors. A novel design of an AlN IR sensor based on piezoelectric bending resonator is described and analyzed in this paper. The detector is constructed by using thermally mismatched materials which stress the resonator and shift the resonance frequency. The IR thermal input is sensed by monitoring the frequency shift induced by the in-plan thermal stress. These designs have the potential for very high sensitivity and are compatible with commercially viable CMOS fabrication technology.

Rais-Zadeh, Mina↗
DOE OSTI2022

The Timepix4 analog front-end design: Lessons learnt on fundamental limits to noise and time resolution in highly segmented hybrid pixel detectors

This manuscript describes the optimization of the front-end readout electronics for high granularity hybrid pixel detectors. The theoretical study aims at minimizing the noise and jitter. The model presented here is validated with both circuit post layout simulations and measurements on the Timepix4 Application Specific Integrated Circuit (ASIC). The analog front-end circuit and the procedure to optimize the dimensions of the main transistors are described with detail. The Timepix4 is the most recent ASIC designed in the framework of the Medipix4 Collaboration. It was manufactured in 65nm CMOS process, and consists of a four side buttable matrix of 448 × 512 pixels with 55µm pitch. The analog front-end has a gain of ~36mV/ke - when configured in High Gain Mode, and ~20mV/ke - when configured in Low Gain Mode. The Equivalent Noise Charge (ENC) is ~68e - rms and ~80e - rms in High Gain Mode and in Low Gain Mode respectively. In event driven mode the incoming hits can be time stamped within a ~ 200ps time bin and the chip can deal with a maximum flux of ~ 3.6MHzmm –2 s –1 . In photon counting mode, the chip can deal with up to ~ 5GHzmm –2 s –1 . The routine designed to optimize the Timepix4 front-end is then used to analyze the performance limits in terms of jitter and noise for Charge Sensitive Amplifiers in pixel detectors.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

PANTHER: A Programmable Architecture for Neural Network Training Harnessing Energy-Efficient ReRAM

The wide adoption of deep neural networks has been accompanied by ever-increasing energy and performance demands due to the expensive nature of training them. Additionally, numerous special-purpose architectures have been proposed to accelerate training: both digital and hybrid digital-analog using resistive RAM (ReRAM) crossbars. ReRAM-based accelerators have demonstrated the effectiveness of ReRAM crossbars at performing matrix-vector multiplication operations that are prevalent in training. However, they still suffer from inefficiency due to the use of serial reads and writes for performing the weight gradient and update step. A few works have demonstrated the possibility of performing outer products in crossbars, which can be used to realize the weight gradient and update step without the use of serial reads and writes. However, these works have been limited to low precision operations which are not sufficient for typical training workloads. Moreover, they have been confined to a limited set of training algorithms for fully-connected layers only. To address these limitations, we propose a bit-slicing technique for enhancing the precision of ReRAM-based outer products, which is substantially different from bit-slicing for matrix-vector multiplication only. We incorporate this technique into a crossbar architecture with three variants catered to different training algorithms. To evaluate our design on different types of layers in neural networks (fully-connected, convolutional, etc.) and training algorithms, we develop PANTHER, an ISA-programmable training accelerator with compiler support. Our design can also be integrated into other accelerators in the literature to enhance their efficiency. Our evaluation shows that PANTHER achieves up to 8.02×, 54.21×, and 103× energy reductions as well as 7.16×, 4.02×, and 16× execution time reductions compared to digital accelerators, ReRAM-based accelerators, and GPUs, respectively.

42 ENGINEERING↗
NASA NTRS1986

A new VLSI complex integer multiplier which uses a quadratic-polynomial residue system with Fermat numbers

A quadratic-polynomial Fermat residue number system (QFNS) has been used to compute complex integer multiplications. The advantage of such a QFNS is that a complex integer multiplication requires only two integer multiplications. In this article, a new type Fermat number multiplier is developed which eliminates the initialization condition of the previous method. It is shown that the new complex multiplier can be implemented on a single VLSI chip. Such a chip is designed and fabricated in CMOS-pw technology.

Truong, T. K.↗
NASA NTRS1987

A new VLSI complex integer multiplier which uses a quadratic-polynomial residue system with Fermat numbers

A quadratic-polynomial Fermat residue number system (QFNS) has been used to compute complex integer multiplications. The advantage of such a QFNS is that a complex integer multiplication requires only two integer multiplications. In this article, a new type Fermat number multiplier is developed which eliminates the initialization condition of the previous method. It is shown that the new complex multiplier can be implemented on a single VLSI chip. Such a chip is designed and fabricated in CMOS-Pw technology.

Shyu, H. C.↗
NASA NTRS1997

Sequence information signal processor for local and global string comparisons

A sequence information signal processing integrated circuit chip designed to perform high speed calculation of a dynamic programming algorithm based upon the algorithm defined by Waterman and Smith. The signal processing chip of the present invention is designed to be a building block of a linear systolic array, the performance of which can be increased by connecting additional sequence information signal processing chips to the array. The chip provides a high speed, low cost linear array processor that can locate highly similar global sequences or segments thereof such as contiguous subsequences from two different DNA or protein sequences. The chip is implemented in a preferred embodiment using CMOS VLSI technology to provide the equivalent of about 400,000 transistors or 100,000 gates. Each chip provides 16 processing elements, and is designed to provide 16 bit, two's compliment operation for maximum score precision of between -32,768 and +32,767. It is designed to provide a comparison between sequences as long as 4,194,304 elements without external software and between sequences of unlimited numbers of elements with the aid of external software. Each sequence can be assigned different deletion and insertion weight functions. Each processor is provided with a similarity measure device which is independently variable. Thus, each processor can contribute to maximum value score calculation using a different similarity measure.

Peterson, John C.↗
NASA NTRS2008

Analysis of Single-Event Latchup Cross Section in 65 nm SRAMs

Single event latchup (SEL) in a 65 nm CMOS SRAM technology is observed and sensitivity is shown to be a strong function of lateral beam orientation, angle of incidence, and temperature. The significance of these results are discussed and the foundation for a predictive model of SEL is laid out for use with the MRED tool.

Hutson, J. M.↗
NASA NTRS1992

Low energy CMOS for space applications

The current focus of NASA's space flight programs reflects a new thrust towards smaller, less costly, and more frequent space missions, when compared to missions such as Galileo, Magellan, or Cassini. Recently, the concept of a microspacecraft was proposed. In this concept, a small, compact spacecraft that weighs tens of kilograms performs focused scientific objectives such as imaging. Similarly, a Mars Lander micro-rover project is under study that will allow miniature robots weighing less than seven kilograms to explore the Martian surface. To bring the microspacecraft and microrover ideas to fruition, one will have to leverage compact 3D multi-chip module-based multiprocessors (MCM) technologies. Low energy CMOS will become increasingly important because of the thermodynamic considerations in cooling compact 3D MCM implementations and also from considerations of the power budget for space applications. In this paper, we show how the operating voltage is related to the threshold voltage of the CMOS transistors for accomplishing a task in VLSI with minimal energy. We also derive expressions for the noise margins at the optimal operating point. We then look at a low voltage CMOS (LVCMOS) technology developed at Stanford University which improves the power consumption over conventional CMOS by a couple of orders of magnitude and consider the suitability of the technology for space applications by characterizing its SEU immunity.

Panwar, Ramesh↗
NASA NTRS2010

Optimal and Local Connectivity Between Neuron and Synapse Array in the Quantum Dot/Silicon Brain

This innovation is used to connect between synapse and neuron arrays using nanowire in quantum dot and metal in CMOS (complementary metal oxide semiconductor) technology to enable the density of a brain-like connection in hardware. The hardware implementation combines three technologies: 1. Quantum dot and nanowire-based compact synaptic cell (50x50 sq nm) with inherently low parasitic capacitance (hence, low dynamic power approx.l0(exp -11) watts/synapse), 2. Neuron and learning circuits implemented in 50-nm CMOS technology, to be integrated with quantum dot and nanowire synapse, and 3. 3D stacking approach to achieve the overall numbers of high density O(10(exp 12)) synapses and O(10(exp 8)) neurons in the overall system. In a 1-sq cm of quantum dot layer sitting on a 50-nm CMOS layer, innovators were able to pack a 10(exp 6)-neuron and 10(exp 10)-synapse array; however, the constraint for the connection scheme is that each neuron will receive a non-identical 10(exp 4)-synapse set, including itself, via its efficacy of the connection. This is not a fully connected system where the 100x100 synapse array only has a 100-input data bus and 100-output data bus. Due to the data bus sharing, it poses a great challenge to have a complete connected system, and its constraint within the quantum dot and silicon wafer layer. For an effective connection scheme, there are three conditions to be met: 1. Local connection. 2. The nanowire should be connected locally, not globally from which it helps to maximize the data flow by sharing the same wire space location. 3. Each synapse can have an alternate summation line if needed (this option is doable based on the simple mask creation). The 10(exp 3)x10(exp 3)-neuron array was partitioned into a 10-block, 10(exp 2)x10(exp 3)-neuron array. This building block can be completely mapped within itself (10,000 synapses to a neuron).

Duong, Tuan A.↗
NASA NTRS1998

Buried Oxide Densification for Low Power, Low Voltage CMOS Applications

Special technology and circuit architecture are of growing interest for implementation of circuits which operate at low supply voltages and consume low power levels without sacrificing performance[1]. Use of thin buried oxide SOI substrates is a primary approach to simultaneously achieve these goals. A significant aspect regarding SIMOX SOI for low voltage, low power applications is the reliability and performance of the thin buried oxide. In addition, when subjected to high total dose irradiation, the silicon islands within the BOX layer of SIMOX can store charges and significantly effect the back channel threshold voltages of devices. Thus, elimination of the islands within the buried oxide (BOX) layer is preferred in order to prevent leakage through these conductive islands and charge build-up within the buried oxide layer. A differential (2-step) ramp rate as applied to full and 100 nm BOX SIMOX was previously reported to play a significant role in the stoichiometry and island formation within the buried layer[2]. This paper focus is on the properties of a thin (120nm) buried oxide as a function of the anneal ramp rate and the temperature of anneal. In this research, we have found an improvement in the buried oxide stoichiometry with the use of a slower, singular ramp rate for specified thin buried oxides, with slower ramp rates and higher temperatures of anneal suggested for reducing the presence of Si islands within the BOX layer.

Allen, L. P.↗
NASA NTRS1982

Electron lithography STAR design guidelines. Part 2: The design of a STAR for space applications

The STAR design system developed by NASA enables any user with a logic diagram to design a semicustom digital MOS integrated circuit. The system is comprised of a library of standard logic cells and computr programs to place, route, and display designs implemented with cells from the library. Also described is the development of a radiation-hard array designed for the STAR system. The design is based on the CMOS silicon gate technology developed by SANDIA National Laboratories. The design rules used are given as well as the model parameters developed for the basic array element. Library cells of the CMOS metal gate and CMOS silicon gate technologies were simulated using SPICE, and the results are shown and compared.

Trotter, J. D.↗
DOE OSTI2022

Design and Challenges of Edge Computing ASICs on Front-End Electronics

In situ or hardware-embedded data processing of raw signals, close to their source, in radiation detectors is expected to provide dramatic improvements in data quality and volumes. However, the implementation of artificial neural networks (ANNs) in the front-end electronics, and the design of custom integrated circuits (ASICs), comes with challenges. In addition, detectors have to operate with limited power budget and implement complex functionalities in a very dense space. They often are exposed to extreme conditions as they work in high-radiation environments and/or cryogenic temperatures. This paper presents examples of applications and design methodologies for in-situ ANNs, along with the challenges of retaining the fidelity of the trained networks. For illustration, we use the problem of estimating the energy deposited by the radiation from digitized waveforms. The proposed implementation starts with an ML algorithm trained in Qkeras and eventually leads to an equivalent ASIC implementation. The associated design challenges in realizing energy and area efficient implementations in CMOS processes are reviewed. Novel approaches that employ hybrid technologies (combination of CMOS with memristors), in-memory computing models, and bio-inspired spiking neural networks are also highlighted

47 OTHER INSTRUMENTATION↗