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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Experimental and analytical study of the hydrodynamic and single and two-phase convective heat transfer performance of flexible PDMS microchannels with micropillar arrays

Various copper and silicon based thermal management systems are used in the cooling of electronics. However, the rigid nature of these materials along with their high thermal and electrical conductivity pose a difficulty in developing direct contact embedded flexible cooling systems that can offer robust cooling performance. The low density, thermal stability, chemical inertness, and electrical insulation of Polydimethylsiloxane (PDMS) make it an ideal material to develop lightweight direct contact thermal management systems for electronics. Its ease of fabrication with tunable flexibility provides the opportunity to go beyond traditional electronics and develop advanced active and passive thermal management systems for a wide–range of applications in foldable and wearable electronics, liquid cooling garments, microgravity, and electric motors. In this study, a flexible PDMS based microchannel with micropillar arrays, which enhance the thermal performance of the device through capillary-assisted flow, has been developed. The hydrodynamic and convection heat transfer performance of three PDMS wick pillar geometries, ranging from a porosity of 0.8–0.91, are investigated and compared under single-phase and two-phase conditions. Dielectric coolant FC-3283 is employed and permeability measurements are made for mass fluxes ranging from 53 kg/m 2 s to 369 kg/m 2 s. Given its conformability, the device demonstrates a deviation from Darcy’s Law, within the laminar regime, with an increasing permeability with mass flux at the rate of ~0.5–0.8 Darcy/(kg/m 2 s). A semi-analytical model has been developed and reported to quantify the conformability of the device. The heat transfer performance is experimentally evaluated using the same dielectric fluid for mass flux ranging from 105 kg/m 2 s to 420 kg/m 2 s with heat fluxes ranging from 1.5 W/cm 2 to 16 W/cm 2 . Heat transfer coefficients of up to 7000 W/m 2 K are observed, which are comparable to copper and silicon microchannels. The effect of porosity on the single phase thermal performance has been evaluated against the pumping power to provide a basis for thermal management system design. Finally, high-speed imaging is performed to study the two-phase flow characteristics to provide insight into the vapor formation and removal.

42 ENGINEERING↗
DOE OSTI2021

Accelerator Real-time Edge AI for Distributed Systems (READS) (Proposal)

Over the last decade, Machine Learning (ML) technologies have slowly made their way into the accelerator community. Rapid advances in recent years in deep learning, particularly reinforcement learning for control system applications and the accessibility of deep learning in embedded hardware, have generated renewed interest and spawned a number of applications. The Fermilab Accelerator Complex, shown in Fig. 1, has provided High Energy Physics (HEP) experiments with proton beams for nearly fifty years. The current focus of the laboratory is its world-class experimental program at the intensity frontier. While increasing beam intensity certainly presents its own challenges, preserving beam size while minimizing beam losses – particles lost through interactions with the beam vacuum pipe – turns out to be, in many ways, the main challenge. The accelerator is controlled via a complex system of hundreds of thousands of devices. Enabling fine tuning and real-time optimization of their parameters using ML methods and stepping beyond experience-based reasoning of human operators are key to the success of future intensity upgrades. Our objective will be to integrate ML into accelerator operations and furthermore, provide an accessible framework, which can also be used by a broad range of other accelerator systems with dynamic tuning needs.

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

Wastepaper-derived porous carbon supported cobalt nanocomposites for all solid-state flexible supercapacitor

The conversion of wastepaper into high-value carbon materials has gained significant attention as a sustainable strategy for energy storage applications. Owing to its low cost, abundance, and intrinsic fibrous structure, wastepaper serves as an attractive precursor for carbon-based electrode materials. In this work, a novel electrode comprising cobalt nanoparticles and Co 3 O 4 embedded in wastepaper-derived porous carbon has been developed for use in a flexible all-solid-state asymmetric supercapacitor. The integration of cobalt nanoparticles and Co 3 O 4 introduces redox-active centres, which enhance the electrochemical activity of the carbon framework. Mean while, the interconnected porous and conductive carbon network enables rapid ion diffusion and efficient electron transport, synergistically improving the overall electrochemical performance. It delivers a high specific capacitance of 61.5 Fg -1 , a power density of 5143 W kg -1 , and an energy density of 9 Wh kg -1 at a current density of 2.5 A/ g. Furthermore, the device maintains outstanding cycling stability, retaining 82.86 % of its capacitance after 10,000 charge-discharge cycles. Practical applicability is confirmed through its ability to power

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Virtualized Logical Qubits: A 2.5D Architecture for Error-Corrected Quantum Computing

Current, near-term quantum devices have shown great progress in the last several years culminating recently with a demonstration of quantum supremacy. In the medium-term, however, quantum machines will need to transition to greater reliability through error correction, likely through promising techniques like surface codes which are well suited for near-term devices with limited qubit connectivity. We discover quantum memory, particularly resonant cavities with transmon qubits arranged in a 2.5D architecture, can efficiently implement surface codes with substantial hardware savings and performance/fidelity gains. Specifically, we virtualize logical qubits by storing them in layers of qubit memories connected to each transmon. Surprisingly, distributing each logical qubit across many memories has a minimal impact on fault tolerance and results in substantially more efficient operations. Our design permits fast transversal application of CNOT operations between logical qubits sharing the same physical address (same set of cavities) which are 6x faster than standard lattice surgery CNOTs. We develop a novel embedding which saves approximately 10x in transmons with another 2x savings from an additional optimization for compactness. Although qubit virtualization pays a 10x penalty in serialization, advantages in the transversal CNOT and in area efficiency result in fault-tolerance and performance comparable to conventional 2D transmon-only architectures. Our simulations show our system can achieve fault tolerance comparable to conventional two-dimensional grids while saving substantial hardware. Furthermore, our architecture can produce magic states at 1.22x the baseline rate given a fixed number of transmon qubits. Here, this is a critical benchmark for future fault-tolerant quantum computers as magic states are essential and machines will spend the majority of their resources continuously producing them. This architecture substantially reduces the hardware requirements for fault-tolerant quantum computing and puts within reach a proof-of-concept experimental demonstration of around 10 logical qubits, requiring only 11 transmons and 9 attached cavities in total.

quantum computing↗
DOE OSTI2026

Carbon-Based Quantum Information Science with Symmetry Protected Topological States (Final Report, DOE-BES award DE-SC0023105)

This research program established the scientific foundation for the rational, bottom-up design, synthesis, isolation, and investigation of symmetry-protected topological (SPT) electron spin qubits embedded in graphene nanoribbons (GNRs). The work focused on integrating atomically precise low-dimensional carbon nanostructures with emerging quantum logic architectures, providing a pathway toward scalable quantum materials for next-generation computing and sensing technologies. A central component of the program was the elucidation of fundamental relationships between real-space molecular architecture, local spin density distributions, electronic band dispersion, and energy level alignment in atomically precise GNR systems. These correlations define key operational parameters of SPT qubits and were systematically investigated to establish quantitative benchmarks against established molecular and solid-state spin qubit platforms. Attention was given to properties critical for quantum device performance, e.g. decoherence times, spectral sharpness of energy transitions, and tunable exchange interactions between spin states. The research demonstrated that these parameters can be engineered with atomic precision through scalable bottom-up synthetic strategies. Theory-guided design played a central role in identifying candidate structures hosting topologically protected spin states. Experimental validation was performed using both ensemble measurements and single-molecule characterization. In addition to advances in quantum materials synthesis, the program developed and applied spin-sensitive scanning probe microscopy techniques capable of directly probing quantum states and dynamic processes with atomic-scale spatial resolution. These capabilities enabled direct observation and characterization of quantum structures at the single-atom level. While the research activities were primarily hypothesis-driven fundamental investigations, the program adopted a comprehensive materials-by-design framework aimed at translating scientific discoveries into technological concepts compatible with scalable and intelligent manufacturing approaches.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Tunable Magnetic and Optical Anisotropy in ZrO 2 ‐Co Vertically Aligned Nanocomposites

Abstract Metamaterials have gained great research interest in recent years owing to their potential for property tunability, multifunctionality, and property coupling. As a new group of self‐assembled thin films, vertically aligned nanocomposite (VAN)‐based hybrid metamaterials have been demonstrated with significant anisotropic physical properties and a broad range of property tailorability, such as optical anisotropy, magnetic anisotropy, hyperbolic dispersion, and enhanced second harmonic generation properties. Herein, self‐assembled ZrO 2 ‐Co nanocomposite films, with high epitaxial quality and ultra‐fine vertically aligned Co nanopillars (with an average diameter of ≈2 nm) embedded in a ZrO 2 matrix, are fabricated using a pulsed laser deposition (PLD) method. The Co pillar density can be effectively tuned by varying the Co concentration in the target, which results in tunable optical properties and magnetic properties. Specifically, a high saturation magnetization of 100 emu cm −3 , strong out‐of‐plane magnetic anisotropy and tailorable magnetization properties are achieved via tuning the Co nanopillar density. Coupled with hyperbolic dispersion of dielectric constant from 950 to 1500 nm in wavelength, plasmonic Co metal nanopillars, and the unique dielectric ZrO 2 matrix, this new nanoscale hybrid metamaterial shows great potential for future integrated optical and magnetic device designs.

36 MATERIALS SCIENCE↗
DOE OSTI2024

SPARTAN (Scalable Probabilistic Application Reconfigurable Tensor Autonomous Network)

The technical founder of Ludwig Computing Inc has been competitively selected for support by Cyclotron Road, a U.S. Department of Energy (DOE) Advanced Manufacturing Office (AMO) Lab-Embedded Entrepreneurship Program (LEEP) through an approved merit review process. Ludwig Computing Inc, supported by the U.S. Department of Energy's Advanced Manufacturing Office through the Cyclotron Road program, has investigated the advantages of probabilistic computing for real-world compute-intensive applications. This research adds to the understanding of alternative computing paradigms by exploring a unique hardware-software co-design that integrates quantum computing methods with nature-inspired problem-solving techniques. The project's focus on areas such as combinatorial optimization, graph analytics, and machine learning demonstrates the potential for significant advancements in computational efficiency and performance. By harnessing natural randomness to streamline large circuits into fewer devices, Ludwig's approach enables massive parallelism, potentially offering higher throughput, speed, and energy efficiency compared to conventional hardware solutions. This work benefits the public by paving the way for more efficient computing solutions that could address complex real-world problems while potentially reducing energy consumption in data-intensive industries.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Dual-Wavelength Simultaneous Patterning of Degradable Thermoset Supports for One-Pot Embedded 3D Printing

Vat photopolymerization (VP) techniques have enabled the fabrication of complex geometries while balancing high precision and fast processing times. 3D printed objects are traditionally built layer-by-layer with newly cured layers being structurally supported by previous ones. Fabricating unsupported features such as overhangs and arches risks misalignment and sagging, limiting the range of accessible designs. To overcome this issue, support structures are fabricated along with the primary object as temporary scaffolds that provide stability and conserve print fidelity. For VP specifically, patterning dissolvable sacrificial supports is attractive to avoid manual removal after printing. In this study, we demonstrate a base-degradable thermoset to pattern print supports in a one-pot formulation along with the primary structural material. Efficient printing is enabled using a dual-wavelength negative imaging (DWNI) DLP printer that patterns the degradable thermoset with visible light and the permanent network with UV light, which are simultaneously projected using a single digital micromirror device (DMD). Printed objects undergo thermal postprocessing to enhance the final conversion of the primary material, after which thermoset supports are degraded in a basic, aqueous solution. This approach provides a robust method for the dual-wavelength patterning of sacrificial thermoset supports, broadening the range of accessible 3D printable materials and geometries.

3D printing↗
DOE OSTI2022

CeO 2 Doping of Hf 0.5 Zr 0.5 O 2 Thin Films for High Endurance Ferroelectric Memories

Ferroelectric switching is demonstrated in CeO 2 -doped Hf 0.5 Zr 0.5 O 2 (HZCO) thin films with application in back-end-of-line compatible embedded memories. At low cerium oxide doping concentrations (2.0–5.6 mol%), the ferroelectric orthorhombic phase is stabilized after annealing at temperatures below 400 °C. HZCO ferroelectrics show reliable switching characteristics beyond 10 11 cycles in TiN/HZCO/TiN capacitors, several orders of magnitude greater than identically processed Hf 0.5 Zr 0.5 O 2 (HZO) capacitors, without sacrificing polarization and retention. Internal photoemission and photoconductivity experiments show that CeO 2 -doping introduces in-gap states in HZCO that are nearly aligned with TiN Fermi level, facilitating electron injection through these states. Furthermore, the enhanced average bulk conduction, which may lead to more uniform thermal dissipation in the HZCO films, delays irreversible degradation via breakdown that leads to device failure after repeated programming cycles.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Optimal calibration of gates in trapped-ion quantum computers

Abstract To harness the power of quantum computing, it is essential that a quantum computer provide maximal possible fidelity for a quantum circuit. To this end, much work has been done in the context of qubit routing or embedding, i.e., mapping circuit qubits to physical qubits based on gate performance metrics to optimize the fidelity of execution. Here, we take an alternative approach that leverages a unique capability of a trapped-ion quantum computer, i.e., the all-to-all qubit connectivity. We develop a method to determine a fixed number (budget) of quantum gates that, when calibrated, will maximize the fidelity of a batch of input quantum programs. This dynamic allocation of calibration resources on randomly accessible gates, determined using our heuristics, increases, for a wide range of calibration budget, the average fidelity from 70% or lower to 90% or higher for a typical batch of jobs on an 11-qubit device, in which the fidelity of calibrated and uncalibrated gates are taken to be 99% and 90%, respectively. Our heuristics are scalable, more than 2.5 orders of magnitude faster than a randomized method for synthetic benchmark circuits generated based on real-world use cases.

Maksymov, Andrii (ORCID:0000000282442851)↗
DOE OSTI2023

Artificial Intelligence-Enhanced, Multi-Level, Modular System Design

As Moore’s Law and Dennard Scaling come to an end, it is becoming increasingly important to develop non-von Neumann computing architectures that can perform low-power computing in the domains of scientific computing, artificial intelligence, embedded systems, and edge computing. Next-generation computing technologies, such as neuromorphic computing and quantum computing, have the potential to revolutionize computing. However, in order to make progress in these fields, it is necessary to fundamentally change the current computing paradigm by codesigning systems across all system level, from materials to software. Because skilled labor is limited in the field of next-generation computing, we are developing artificial intelligence-enhanced tools to automate the codesign and co-discovery of next-generation computers. Here, we develop a method called Modular and Multi-level MAchine Learning (MAMMAL) which is able to perform analog codesign and co-discovery across multiple system levels, spanning devices to circuits. We prototype MAMMAL by using it to design simple passive analog low-pass filters. We also explore methods to incorporate uncertainty quantification into MAMMAL and to accelerate MAMMAL by using emerging technologies, such as crossbar arrays. Ultimately, we believe that MAMMAL will enable rapid progress in developing next-generation computers by automating the codesign and co-discovery of electronic systems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Vibration-Based Sensor Design: A Grey-Box Approach

Knowledge of the internal structure of an object or device under investigation proceeds from the basic idea of constructing its dynamic behavioral relations governed by a set of differential/algebraic equations that characterize its response. These equations can be partial differential equations leading to finite element or finite difference relations requiring a complex numerical solution on a super computer or ordinary differential equations requiring sophisticated numerical integration techniques to obtain the desired solution. Discrete dynamic systems evolving from digitized data acquisition are typically captured by sampled-data (continuous-to-discrete) representations characterized by a set of difference equations specifying the underlying system dynamics. In any case, with a mathematical description in hand, Grey-Box modeling techniques have evolved, concerned with the estimation of model parameters embedded in a prescribed set of equations (the system) governing its behavior, while capturing the underlying physical phenomenology of the problem at hand.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Correlation of Surface Acoustic Wave (SAW) force myography sensor output with elbow joint torque

Accurate assessment of skeletal muscle forces and net joint torque is essential for preventing fatigue-related injuries, optimizing physical training, and monitoring disease progression in neuromuscular conditions. However, existing joint torque evaluation techniques are hindered by limited portability and high operational costs, confining their use to controlled laboratory or clinical settings. Despite substantial advances in wearable joint torque estimation systems, ongoing challenges such as power constraints, bulky wired setups, and susceptibility to environmental or motion artifacts underscore the urgent need for truly batteryless, wireless solutions deployable in real-world settings. This paper proposes a novel surface acoustic wave (SAW)-based force myography (FMG) system for noninvasive measurement of joint torque, validated against a gold-standard electromechanical dynamometer. The approach uses a single SAW sensor embedded in an armband to detect volumetric biceps brachii changes, with a second-order polynomial mapping sensor output and elbow angle to torque. Seven participants were tested in both isometric (15°–90°) and isokinetic (10°/s and 20°/s) supinated elbow flexion tasks. Under isometric conditions, subject-specific calibration achieved a normalized root-mean-square error (NRMSE) of 13.6% ± 6.0% and R 2 = 0.834 ± 0.180, while a group-level model yielded 14.4% ± 6.8% and 0.808 ± 0.208, respectively. For isokinetic trials, the group model produced an NRMSE of 24.1% ± 6.6% at 10°/s and 24.9% ± 08.9% at 20°/s, highlighting the feasibility of using a single-sensor SAW-FMG setup across different speeds. Because SAW devices support wireless, battery-free operation, the proposed system offers a pathway to portable, real-time monitoring for sports medicine, rehabilitation, and clinical diagnostics.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Self-assembled HfO 2 -Au nanocomposites with ultra-fine vertically aligned Au nanopillars

Oxide-metal-based hybrid materials have gained great research interest in recent years owing to their potential for multifunctionality, property coupling, and tunability. Specifically, oxide-metal hybrid materials in a vertically aligned nanocomposite (VAN) form could produce pronounced anisotropic physical properties, e.g., hyperbolic optical properties. Herein, self-assembled HfO 2 -Au nanocomposites with ultra-fine vertically aligned Au nanopillars (as fine as 3 nm in diameter) embedded in a HfO 2 matrix were fabricated using a one-step self-assembly process. The film crystallinity and pillar uniformity can be obviously improved by adding an ultra-thin TiN-Au buffer layer during the growth. Here, the HfO 2 -Au hybrid VAN films show an obvious plasmonic resonance at 480 nm, which is much lower than the typical plasmonic resonance wavelength of Au nanostructures, and is attributed to the well-aligned ultra-fine Au nanopillars. Coupled with the broad hyperbolic dispersion ranging from 1050 nm to 1800 nm in wavelength, and unique dielectric HfO 2 , this nanoscale hybrid plasmonic metamaterial presents strong potential for the design of future integrated optical and electronic switching devices.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Nuclear Material Control and Accountancy Approach for Pebble Fueled Reactors using a Novel Pebble-Type Identification and Classification Technology

In FY21, Argonne National Laboratory (ANL) with researchers at Texas A&M University (TAMU) designed and engineered a prototypical device for accounting types of irradiated pebbles (for example with different 235U enrichments or pure graphite) in Pebble-Fueled Reactors (PFRs). Through engagements with reactor designers, a need arose to assist in identifying and categorizing types of pebbles as a complementary nuclear material control method that would synergize with designers’ use of fuel burnup measurements for material accountancy needs. As part of an overall nuclear material control approach, a concept of pebble batch accounting was investigated using extrinsic non-radiological features to identify intrinsic characteristics. This concept of batch accounting led to the ability of identifying types of pebbles based on characteristics such as initial 235U enrichment of pebble batches or dates of introduction into the reactor core. Identification was achieved by embedding the 5-mm thick graphite periphery of pebbles with 2-mm diameter inert Yttria-Stabilized Zirconia (YSZ) microspheres to achieve an averaged volumetric density (i.e., common spacing between microspheres) unique to that type of pebble. With an ultrasound imaging system in proximity with each pebble, the YSZ microspheres in the pebble proved visible and their spacing became the unique feature upon which pebble type categorization could occur. At the culmination of FY21, ANL intended on delivering and installing the prototype at TAMU for initial testing but, due to the on-going pandemic, this was postponed until FY22.

Gariazzo, Claudio↗
DOE OSTI2021

Manipulating ferroelectric behaviors via electron-beam induced crystalline defects

Ferroelectric nanoplates are attractive for applications in nanoelectronic devices. Defect engineering has been an effective way to control and manipulate ferroelectric properties in nanoscale devices. Defects can act as pinning centers for ferroelectric domain wall motion, altering the switching properties and domain dynamics of ferroelectrics. However, there is a lack of detailed investigation on the interactions between defects and domain walls in ferroelectric nanoplates due to the limitation of previous characterization techniques, which impedes the development of defect engineering in ferroelectric nanodevices. In this study, we applied in situ biasing transmission electron microscopy to explore how dislocation loops, which were judiciously introduced into barium titanate nanoplates via electron beam irradiation, affect the motion of ferroelectric domain walls. The results show that the motion was dramatically suppressed by these localized defects, because of the local strain fields induced by the defects. Additionally, the pinning effect can be further enhanced by multiple domain walls embedded with defect arrays. These results indicate the possibility of manipulating domain switching in ferroelectric nanoplates via the electron beam.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2020

User Access to Scientific Facilities via 5G: A Cyber Security Thought Experiment

5G is more than an over-the-air radio technology upgrade. It is a strategy to extend Mobile Network Operator service offerings beyond traditional voice, instant messaging and Internet access. 5G Mobile Network Operators will offer new telecommunication services that include enhanced guarantees of confidentiality, integrity and availability. How could such services change the way Science collaborations connect scientists to supercomputers and other scientific facilities? Current scientific collaborations implicitly trust cloud service providers to securely store and process data. The perceived risks of outsourcing Science data security are counterbalanced by assurances that cloud providers operate at a scale that allows them to implement security measures impractical for Science collaborations (e.g. continuous system administrator behavioral monitoring and strict individual separation of duties). If that is true for a cloud service provider like Amazon Web Services (2018 revenue: $25.7 billion), could it also be true for Mobile Network Operators like Verizon Wireless (2018 revenue: $91.7 billion) or AT&T Mobility (2018 revenue: $71.3 billion)? DOE Leadership Class supercomputer facility users currently access them from the public Internet via Secure Shell. The sponsors and operators of the supercomputer facilities have determined that the public Internet path between the Scientist’s Device and the Login Node does not natively provide enough confidentiality or integrity to protect those communications. Therefore, the facilities achieve additional confidentiality and integrity by requiring Secure Shell encryption across those untrusted network paths. Using 5G Network Slice technology, a Mobile Network Operator may offer communication services between supercomputer users and facilities that natively provide confidentiality and integrity guarantees. Sponsors and operators of supercomputer facilities may determine that these guarantees provide enough confidentiality and integrity to protect those communications. If so, a 5G Network Slice could replace an SSH session running over the public Internet. Finally, this use case could be extended to other Office of Science user facility access requirements. Consider microscopy instruments at (e.g.) the Center for Nanoscale Materials or the Environmental Molecular Sciences Laboratory. The embedded systems controlling such instruments may not always support encrypted network access technologies like SSH. 5G Network Slices may offer an alternative to current VPN or SSH tunneling techniques, with additional benefits like guaranteed minimum bandwidth.

5G↗
DOE OSTI2024

Computer Vision on Edge Devices for the Short Term Prediction of Cloud Cover

Edge Computing and IoT are important pieces of today's technological landscape. Here, we build a low-cost IoT sensor for sky imaging and program it using AWS GreenGrass, one of the leading IoT platforms. We demonstrate remote reprogramming of this device to load software that predicts sun shading events through the linear advection method, which is a baseline algorithm that can be used to benchmark algorithmic improvements in future work. Some future directions for sky imaging research are enumerated.

14 SOLAR ENERGY↗