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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS2002

Differential Flatness and Cooperative Tracking in the Lorenz System

In this paper the control of the Lorenz system for both stabilization and tracking problems is studied via feedback linearization and differential flatness. By using the Rayleigh number as the control, only variable physically tunable, a barrier in the controllability of the system is incidentally imposed. This is reflected in the appearance of a singularity in the state transformation. Composite controllers that overcome this difficulty are designed and evaluated. The transition through the manifold defined by such a singularity is achieved by inducing a chaotic response within a boundary layer that contains it. Outside this region, a conventional feedback nonlinear control is applied. In this fashion, the authority of the control is enlarged to the whole. state space and the need for high control efforts is mitigated. In addition, the differential parametrization of the problem is used to track nonlinear functions of one state variable (single tracking) as well as several state variables (cooperative tracking). Control tasks that lead to integrable and non-integrable differential equations for the nominal flat output in steady-state are considered. In particular, a novel numerical strategy to deal with the non-integrable case is proposed. Numerical results validate very well the control design.

Crespo, Luis G.↗
NASA NTRS2002

High-Power, High-Frequency Si-Based (SiGe) Transistors Developed

Future NASA, DOD, and commercial products will require electronic circuits that have greater functionality and versatility but occupy less space and cost less money to build and integrate than current products. System on a Chip (SOAC), a single semiconductor substrate containing circuits that perform many functions or containing an entire system, is widely recognized as the best technology for achieving low-cost, small-sized systems. Thus, a circuit technology is required that can gather, process, store, and transmit data or communications. Since silicon-integrated circuits are already used for data processing and storage and the infrastructure that supports silicon circuit fabrication is very large, it is sensible to develop communication circuits on silicon so that all the system functions can be integrated onto a single wafer. Until recently, silicon integrated circuits did not function well at the frequencies required for wireless or microwave communications, but with the introduction of small amounts of germanium into the silicon to make silicon-germanium (SiGe) transistors, silicon-based communication circuits are possible. Although microwavefrequency SiGe circuits have been demonstrated, there has been difficulty in obtaining the high power from their transistors that is required for the amplifiers of a transmitter, and many researchers have thought that this could not be done. The NASA Glenn Research Center and collaborators at the University of Michigan have developed SiGe transistors and amplifiers with state-of-the-art output power at microwave frequencies from 8 to 20 GHz. These transistors are fabricated using standard silicon processing and may be integrated with CMOS integrated circuits on a single chip. A scanning electron microscope image of a typical SiGe heterojunction bipolar transistor is shown in the preceding photomicrograph. This transistor achieved a record output power of 550 mW and an associated power-added efficiency of 33 percent at 8.4 GHz, as shown. Record performance was also demonstrated at 12.6 and 18 GHz. Developers have combined these state-of-the-art transistors with transmission lines and micromachined passive circuit components, such as inductors and capacitors, to build multistage amplifiers. Currently, a 1-W, 8.4-GHz power amplifier is being built for NASA deep space communication architectures.

Ponchak, George E.↗
NASA NTRS1991

Control algorithm implementation for a redundant degree of freedom manipulator

This project's purpose is to develop and implement control algorithms for a kinematically redundant robotic manipulator. The manipulator is being developed concurrently by Odetics Inc., under internal research and development funding. This SBIR contract supports algorithm conception, development, and simulation, as well as software implementation and integration with the manipulator hardware. The Odetics Dexterous Manipulator is a lightweight, high strength, modular manipulator being developed for space and commercial applications. It has seven fully active degrees of freedom, is electrically powered, and is fully operational in 1 G. The manipulator consists of five self-contained modules. These modules join via simple quick-disconnect couplings and self-mating connectors which allow rapid assembly/disassembly for reconfiguration, transport, or servicing. Each joint incorporates a unique drive train design which provides zero backlash operation, is insensitive to wear, and is single fault tolerant to motor or servo amplifier failure. The sensing system is also designed to be single fault tolerant. Although the initial prototype is not space qualified, the design is well-suited to meeting space qualification requirements. The control algorithm design approach is to develop a hierarchical system with well defined access and interfaces at each level. The high level endpoint/configuration control algorithm transforms manipulator endpoint position/orientation commands to joint angle commands, providing task space motion. At the same time, the kinematic redundancy is resolved by controlling the configuration (pose) of the manipulator, using several different optimizing criteria. The center level of the hierarchy servos the joints to their commanded trajectories using both linear feedback and model-based nonlinear control techniques. The lowest control level uses sensed joint torque to close torque servo loops, with the goal of improving the manipulator dynamic behavior. The control algorithms are subjected to a dynamic simulation before implementation.

Cohan, Steve↗
DOE OSTI2026

Integrating Maximum Entropy Production Theory and Machine Learning to Improve Global Evapotranspiration Modeling

Accurate estimation of terrestrial evapotranspiration (ET) is vital for understanding global water and energy cycles. However, current global ET estimations are not well constrained. This study introduces an integrated framework combining the Maximum Entropy Production (MEP) theory with Random Forest (RF) model to improve global ET estimation. Specifically, in contrast to direct ET estimation by the RF model, the integrated framework (MEP‐RF) trains to predict error of MEP‐simulated ET. MEP‐RF outperforms RF in spatiotemporal extrapolation. Attribution analysis with in situ observations reveals that the inputs of MEP are the most critical variables for the ET process, including net radiation, vegetated area, soil moisture, and surface temperature. We further drive MEP‐RF with global reanalysis and satellite data sets of these four inputs, yielding a global mean terrestrial ET of 548 mm/year, with 77% attributed to transpiration. The global ET increased at a rate of 0.85 mm/year per year during 2003–2021, primarily due to vegetation greening rather than rising temperature, while decreasing soil moisture led to decreasing regional ET. The integrated framework provides a novel approach for the estimation of global ET without the need for hard‐to‐obtain and thus uncertain inputs, such as wind speed, surface roughness, aerodynamic and canopy stomatal resistance. Therefore, MEP‐RF offers an independent method on existing global ET products. It represents a promising physically based approach that can be incorporated into Earth System Models to enhance water and energy cycle simulations.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1997

Radiation of Sound From a Point Source in a Short Duct

It is the purpose of this paper to provide, in relatively brief form, a summary of a boundary integral approach that has been developed for calculating the sound field radiated from short ducts in uniform axial motion. The method was devised primarily to study sound generated by rotating sources in the duct, as is of current practical interest in connection with ducted-fan aircraft engines. Detailed background on the fan source application of the technique can be found. The author has not previously discussed the simpler monopole source case of interest in these proceedings. However, readers desiring a more detailed treatment than will be included here should have little difficulty in extracting it from those references after making the relatively minor modifications necessary to adapt the analyses to the monopole case. It should be noted that other authors have also considered radiation from short ducts. In particular, readers may find the finite-element approach of Eversman of interest as well as the alternate boundary integral method treatments of Martinez and of Dunn, Tweed, and Farassat.

Myers, M. K.↗
NASA NTRS2001

Training to Enhance Design Team Performance: A Cure for Tunnel Vision

Design Team performance is a function of the quality and degree of academic training and the cumulative, learned experience of the individual members of the team. Teamwork, leadership, and communications certainly are factors that affect the measure of the performance of the team, but they are not addressed here. This paper focuses on accelerating the learned experience of team members and describes an organizational approach that can significantly increase the effective experience level for any engineering design team. The performance measure of the whole team can be increased by increasing the engineering disciplines' cross awareness of each other and by familiarizing them with their affect at the system level. Discipline engineers know their own discipline well, but typically are not intimately familiar with their technical interaction with and dependencies on all the other disciplines of engineering. These dependencies are design integration functions and are worked out well by the discipline engineers as long as they are involved in the design of types of systems that they have experience with.

Parker, James W.↗
DOE OSTI2022

Spatially resolved mass–metallicity relation at $z$ ~ 0.26 from the MUSE-Wide Survey

Galaxies in the local universe have a spatially resolved star-forming main sequence (rSFMS) and mass–metallicity relation (rMZR). We know that the global mass–metallicity relation (MZR) results from the integral of the rMZR, and it evolves with redshift. However, the evolution of the rMZR with redshift is still unclear because the spatial resolution and signal-to-noise ratio are low. Currently, too few observations beyond the local universe are available, and only simulations can reproduce the evolution of the rMZR with redshift. We selected ten emission-line galaxies with an average redshift of $z$ ~ 0.26 from the MUSE-Wide DR1. We obtained the spatially resolved star formation rate (SFR) and metallicity from integral field spectroscopy (IFS), as well as the stellar mass surface density from 3D-HST photometry. We derived the rSFMS and rMZR at $z$ ~ 0.26 and compared them with those of local galaxies. We find that the rSFMS of galaxies at $z$ ~ 0.26 has a slope of ~0.771. The rMZR exists at z ~ 0.26, showing a similar shape to that of the local universe, but a lower average metallicity that is about ~0.11 dex lower than the local metallicity. In addition, we also study the spatially resolved fundamental metallicity relation (rFMR) of these galaxies. However, there is no obvious evidence that an rFMR exists at $z$ ~ 0.26, and it is not an extension of rMZR at a high SFR. Similar to their global versions, the rSFMS and rMZR of galaxies also evolve with redshift. At fixed stellar mass, galaxies at higher redshift show a higher SFR and lower metallicity. In conclusion, these suggest that the evolution of the global galaxy properties with redshift may result from integrating the evolution of the spatially resolved galaxy properties.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2018

NASA's Space Launch System: Unprecedented Payload Capabilities

As part of a renewed focus on deep space exploration, NASA and its private sector and international partners are building a new super heavy-lift launch vehicle, the Space Launch System (SLS), as well as the new Orion crew vehicle, and upgrading launch facilities at Kennedy Space Center. Progress made on the Block 1 vehicle, as well as its expected performance metrics and fiscal support from the U.S. administration and Congress, have opened up additional manifest possibilities that the Agency continues to evaluate. Offering a combination of power, payload capacity and departure energy unmatched in contemporary boosters, the SLS family of launch vehicles features the world's most-proven propulsion system: solid rocket boosters and RS-25 main engines with a modified existing cryogenic in-space stage. The initial SLS configuration, Block 1, will deliver at least 26 metric tons (t) of payload to trans-lunar injection (TLI). The vehicle's flexible architecture will enable the rocket to evolve over the next decade to meet the most demanding deep space mission requirements. The second configuration, Block 1B, will deliver at least 34 to 40 t to TLI, depending on whether the crewed or cargo variant is selected. Although designed to facilitate human exploration of deep space, the vehicle also provides game-changing benefits for large science payloads and even harnesses excess capacity to provide small satellites with affordable access to deep space. For the first integrated mission of SLS and Orion, launching from Kennedy Space Center in fiscal year 2020, SLS Block 1 will send Orion on a 25.5-day mission to a distant retrograde lunar orbit with the primary objective to test and validate new systems and procedures. That first mission, called Exploration Mission-1 (EM-1), also has 13 6U-class CubeSat payloads manifested. Those payloads, which will carry out a variety of scientific experiments and technology demonstrations, will deploy in several locations along the trajectory after Orion has separated from SLS. Contractors and suppliers have made significant progress since last year manufacturing the Block 1 vehicle for EM-1. The upper stage and adapters are complete as are the four RS-25 engines. All other major components are constructed and being outfitted for flight. In fact, hardware for the second flight is currently being manufactured at locations across the United States. This paper will outline hardware, avionics and testing progress toward the first and second flights of SLS. Manifest opportunities for primary, co-manifested and secondary payloads will be discussed. An in-depth look at payload utilization and integration will be provided, as well as lessons learned from installing a secondary payload deployment system for EM-1.

Creech, Steve↗
DOE OSTI2025

Prediction of carbon nanostructure mechanical properties and the role of defects using machine learning

Graphene-based nanostructures hold immense potential as strong and lightweight materials, however, their mechanical properties such as modulus and strength are difficult to fully exploit due to challenges in atomic-scale engineering. This study presents a database of over 2,000 pristine and defective nanoscale CNT bundles and other graphitic assemblies, inspired by microscopy, with associated stress–strain curves from reactive molecular dynamics (MD) simulations using the reactive INTERFACE force field (IFF-R). These 3D structures, containing up to 80,000 atoms, enable detailed analyses of structure-stiffness-failure relationships. By leveraging the database and physics- and chemistry-informed machine learning (ML), accurate predictions of elastic moduli and tensile strength are demonstrated at speeds 1,000 to 10,000 times faster than efficient MD simulations. Hierarchical Graph Neural Networks with Spatial Information (HS-GNNs) are introduced, which integrate chemistry knowledge. HS-GNNs as well as extreme gradient boosted trees (XGBoost) achieve forecasts of mechanical properties of arbitrary carbon nanostructures with only 3 to 6% mean relative error. The reliability equals experimental accuracy and is up to 20 times higher than other ML methods. Predictions maintain 8 to 18% accuracy for large CNT bundles, CNT junctions, and carbon fiber cross-sections outside the training distribution. The physics- and chemistry-informed HS-GNN works remarkably well for data outside the training range while XGBoost works well with limited training data inside the training range. The carbon nanostructure database is designed for integration with multimodal experimental and simulation data, scalable beyond 100 nm size, and extendable to chemically similar compounds and broader property ranges. The ML approaches have potential for applications in structural materials, nanoelectronics, and carbon-based catalysts.

Winetrout, Jordan J.↗
NASA NTRS1989

Airframe/propulsion integration characteristics at transonic speeds

The aerodynamic characteristics for both single and twin-engine high-performance aircraft are significantly affected by shock induced flow interactions as well as other local flow interference effects which usually occur at transonic speeds. These adverse interactions can not only cause high drag, but also cause unusual aerodynamic loadings and/or severe stability and control problems. Many programs are under way to not only develop method for reducing the adverse effects, but also to develop an understanding of the basic flow conditions which are the primary contributors. It is anticipated that these programs will result in technologies which can reduce the aircraft cruise drag through improved integration as well as increase aircraft maneuverability through the application of thrust vectoring. Some of the primary integration problems for twin-engine aircraft at transonic speeds are identified, and several methods are demonstrated for reducing or eliminating the undersirable characteristics, while enhancing configuration effectiveness.

Henderson, William P.↗
DOE OSTI2022

Load Mitigating Feedback Control of WECs

This report outlines the development of load-mitigating feedback control for wave energy converters. A simple, self-tuning multi-objective controller is demonstrated in simulation for a 3-DOF (surge, heave, pitch) point absorber. In previous work, the proposed control architecture has been shown to be effective in experiment for a variety of device archetypes for the single objective of the maximization of electrical power capture: here this architecture is extended to reduce device loading as well. In particular, PTO actuation forces and the minimization of fatigue damage (determined from the sum of wave-exerted and PTO forces) are considered as additional objectives for the self-tuning controller. This controller is demonstrated for two similar, but distinct systems: one described by the identified linear models from physical testing of the WaveBot device, and another based upon a WEC-Sim simulation that expands upon boundary element method data from the WaveBot device. In both cases, because the power surface is consistently fairly flat in the vicinity of control parameters that maximize power capture in contrasting sea-states, it is found to be generally possible to mitigate either fatigue damage or PTO load. However, PTO load is found to conflict with fatigue damage in some sea-states, limiting the efficacy of control objectives that attempt to mitigate both simultaneously. Additionally, coupling between the surge and pitch DOFs also limits the extent to which fatigue damage can be mitigated for both DOFs in some sea-states. Because control objectives can be considered a function of the sea-state (e.g., load mitigation may not be a concern until the sea is sufficiently large) a simple transition strategy is proposed and demonstrated. This transition strategy is found to be effective with some caveats: firstly, it cannot circumvent the aforementioned objective contradictions. Secondly, this objective transition is too slow to act as a system constraint, and objective thresholds must thus be considered quite conservatively. Improvement of the adjustment strategy is demonstrated through the addition of an integral term. Selection of well-performing transition parameters can be a function of sea-state. While a simple selection procedure is proposed, it is non-optimal, and a more robust selection procedure is suggested for future work.

16 TIDAL AND WAVE POWER↗
NASA NTRSDate not supplied

An Examination of Two Non-Cooperative Detect and Avoid Well Clear Definitions

NASA’s Unmanned Aircraft Systems Integration into the National Airspace System (UAS in the NAS) project examines the technical barriers associated with the operation of UAS in civil airspace. The present study explored the differential effects of two candidate non-cooperative Detect-and-Avoid Well Clear (DWC)definitions on pilot and system performance in a human-in-the-loop simulation. Active-duty UAS pilots were recruited to maintain DWC against representative Class 4 encounter types with a low size, weight, and power (SWaP) radar declaration range of 3.5 nautical miles (nmi). Objective performance indicated that pilots could consistently maintain DWC against non-cooperative intruders with either DWC candidate, with negligible differences in response times and separation performance against caution and warning-level threats. While losses of DWC were avoided at rates comparable to Phase 1 findings, pilots uploaded their responses to caution-level alerts over 5 seconds faster in the current setup relative to Phase 1. Encounters with faster closure rates were susceptible to shortened caution-level alert durations, especially when employing the DWC criterion with the additional ‘Tau’ (temporal) component. Consequently, caution-level threats frequently elevated to warning-level status (nearly twice as often with theTau candidate). The variable caution alert durations appeared to impact pilots’ coordination with air traffic control (ATC), as ATC approval rates were lower with the ‘Tau’and ‘Disc’ candidates relative to Phase 1 research. Ultimately, the increased alerting time enabled by the Disc candidate deemed it more suitable for any reductions to the assumed radar declaration range requirement, which was re-evaluated in a follow-on study. Findings from this study will inform Phase 2 Minimum Operational Performance Standards (MOPS)development for UAS with alternative surveillance equipment and performance capabilities.

Kevin J Monk↗
NASA NTRSDate not supplied

SLS Integrated Modal Test Uncertainty Quantification using the Hybrid Parametric Variation Method

Uncertainty in structural loading during launch is a significant concern in the development of spacecraft and launch vehicles. Small variations in launch vehicle and payload mode shapes and their interaction can result in significant variation in system loads. In many cases involving large aerospace systems it is difficult, not economical, or impossible to perform a system modal test. However, it is still vital to obtain test results that can be compared with analytical predictions to validate models. Instead, the “Building Block Approach” is used in which system components are tested individually. Component models are correlated and updated to agree as best they can with test results. The Space Launch System consists of a number of components that are assembled into a launch vehicle. Finite element models of the components are developed, reduced to Hurty/Craig-Bampton models and assembled to represent different phases of flight. The only opportunity to obtain modal test data from an assembled Space Launch System will be during the Integrated Modal Test. There is always uncertainty in every model, which flows into uncertainty in predicted system results. Uncertainty Quantification is used to determine statistical bounds on prediction accuracy based on model uncertainty. For the Space Launch System, model uncertainty is at the Hurty/Craig-Bampton component level. Uncertainty in the Hurty/Craig-Bampton components is quantified using the hybrid parametric variation approach that combines parametric and nonparametric uncertainty. Uncertainty in model form is one of the biggest contributors to uncertainty in complex built-up structures. This type of uncertainty cannot be represented by variations infinite element model input parameters and thus cannot be included in a parametric approach. However, model-form uncertainty can be modeled using a nonparametric approach based on random matrix theory. The hybrid parametric variation method requires the selection of dispersion values for the Hurty/Craig-Bampton fixed-interface eigenvalues, and the Hurty/Craig-Bampton stiffness matrices. Component test/analysis frequency error is used to identify the fixed-interface eigenvalue dispersions, while test/analysis cross-orthogonality is used to identify stiffness dispersion values. The hybrid parametric variation uncertainty quantification approach is applied to the Space Launch System Integrated Modal Test configuration. Monte Carlo analysis is performed, and statistics are determined for modal correlation metrics, frequency response from Integrated Modal Test shakers to selected accelerometers, as well as other metrics for determining how well target modes are excited and identified. If the predicted uncertainty envelopes future Integrated Modal Test results, then there will be increased confidence in the utility of the component-based hybrid parametric variation uncertainty quantification approach.

Uncertainty Quantification↗
DOE OSTI2021

Subsurface Characterization of Hydraulic Fracture Test Site-2 (HFTS-2), Delaware Basin

Hydraulic Fracturing Test Site-2 (HFTS-2) is a field-based research experiment performed in the Wolfcamp Formation of the Permian (Delaware) Basin. This paper focuses on integration, advanced geological characterization, and 3D subsurface modeling of the comprehensive HFTS-2 dataset. The study showcases a multidisciplinary reservoir characterization approach that incorporates geology, petrophysics, geochemistry, geomechanics, microseismic, and subsurface engineering analysis. Subsurface characterization of organic-rich mudstone formations requires understanding complex hydraulic fracture network growth in relation to inherent lithology, geomechanical properties, and interaction with pre-existing natural fractures. This paper presents a characterization workflow incorporating pre- and post-stimulation subsurface data, unique to the HFTS-2 dataset. The study integrated: (1) rock properties from logs, cores, and thin sections; (2) natural and hydraulic fracture descriptions from cores and image logs; (3) local and regional stresses; (4) geomechanics; (5) microseismic; (6) fiber optic (FO) and bottomhole pressure gauge (BHPG) response; and (7) produced fluids analysis. During a stimulation treatment, creation of the stimulated rock volume (SRV) is influenced by several subsurface factors. Key contributing factors include structural context, stress conditions, lithology, facies architecture, pre-existing natural fractures, and geomechanical properties. The HFTS-2 subsurface data integration indicates that the SRV is comprised of a complex juxtaposition of hydraulic fracture swarms, as evidenced by image logs analysis, core description, and microseismic monitoring. The HFTS-2 microseismic event density was used to generate 3D heat maps that serve as a representative SRV footprint, corroborated by secondary datasets. These maps were further integrated with petrophysical and geomechanical characteristics, as well as responses from FO and BHPG, to estimate the lateral and vertical dimensions of the effective fractures. The geological characterization for the HFTS-2 dataset combined with 3D modeling for petrophysical and geomechanical properties provides a strong foundation for subsurface simulation and optimization studies. Downloaded from http://onepetro.org/URTECONF/proceedings-pdf/21URTC/1-21URTC/D011S005R001/2477501/urtec-2021-5243-ms.pdf/1 by Carol Worster on 28 February 2022 URTeC 5243 The workflow improved our understanding of HFTS-2 hydraulic fracture propagation and characteristics in relation to offset pressure depletion and interaction with pre-existing natural fractures. Analysis showed that fracture geometry varies by stage and by well, and a complex fracture network is generated with varying fracture density. The multidisciplinary workflow presented herein for integration and characterization serves as a foundation to evaluate completion efficiency and estimate areal and vertical stimulation and depletion extent for the project. Furthermore, the workflow and learnings can also be transferred to other unconventional plays.

58 GEOSCIENCES↗
DOE OSTI2024

The Multiphasic Teeth of Chiton Articulatus , an Abrasion‐Resistant and Self‐Sharpening Tool for Hard Algae Collection

Abstract Chiton articulatus is a species of mollusk living in the tropical Pacific intertidal rocky shores of Mexico. This species feeds on solid waste organic sources, including hard crustose algae that grow on rocky substrates, by grazing on them with its radula, a flexible chitinous membrane lined with mineralized major lateral teeth. In this study, the composition, morphology, and resulting mechanics of the mature teeth of this species, which have yet to be examined, are revealed. The results show the presence of multiphasic mature teeth, each consisting of aligned hard magnetite nanoparticles on the leading edge of the tooth underneath which are magnetite lamellae, followed by goethite, lepidocrocite, and eventually hydroxyapatite near the trailing edge. This multiregional structure demonstrates a gradation in hardness as well as different microstructural features integrated with tough interfaces. The combination of these microstructural and phase arrangements results in an abrasion‐resistant tough structure with a self‐sharpening ability. The results of this work will help contribute to developing new bioinspired designs while also helping to understand the evolution and feeding habits of these intriguing invertebrates.

36 MATERIALS SCIENCE↗
DOE OSTI2024

A practical approach to using the Genomic Standards Consortium MIxS reporting standard for comparative genomics and metagenomics

Comparative analysis of (meta)genomes necessitates aggregation, integration, and synthesis of well-annotated data using standards. The Genomic Standards Consortium (GSC) collaborates with the research community to develop and maintain the Minimal Information about any (x) Sequence (MIxS) reporting standard for genomic data. To facilitate use of the GSC’s MIxS reporting standard, we provide a description of the structure and terminology, how to navigate ontologies for required terms in MIxS, and demonstrate practical usage through a soil metagenome example.

standards, metadata, genome, metagenome, schema, v↗
DOE OSTI2020

Design and Performance of the First BICEP Array Receiver

Branches of cosmic inflationary models, such as slow-roll inflation, predict a background of primordial gravitational waves that imprints a unique odd-parity “B-mode” pattern in the Cosmic Microwave Background (CMB) at amplitudes that are within experimental reach. The BICEP/Keck (BK) experiment targets this primordial signature, the amplitude of which is parameterized by the tensor-to-scalar ratio r, by observing the polarized microwave sky through the exceptionally clean and stable atmosphere at the South Pole. B-mode measurements require an instrument with exquisite sensitivity, tight control of systematics, and wide frequency coverage to disentangle the primordial signal from the Galactic foregrounds. BICEP Array represents the most recent stage of the BK program and comprises four BICEP3-class receivers observing at 30/40, 95, 150 and 220/270 GHz. The 30/40 GHz receiver will be deployed at the South Pole during the 2019/2020 austral summer. After 3 full years of observations with 30,000+ detectors, BICEP Array will measure primordial gravitational waves to a precision σ(r) between 0.002 and 0.004, depending on foreground complexity and the degree of lensing removal. Here in this paper, we give an overview of the instrument, highlighting the design features in terms of cryogenics, magnetic shielding, detectors and readout architecture as well as reporting on the integration and tests that are ongoing with the first receiver at 30/40 GHz.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Two-dimensional materials for bio-realistic neuronal computing networks

Two-dimensional (2D) van der Waals materials have found broad utility in a diverse range of applications including electronics, optoelectronics, renewable energy, and quantum information technologies. Meanwhile, exponentially growing digital data coupled with the ubiquity of artificial intelligence algorithms have generated significant interest in edge neuromorphic computing as an alternative to centralized cloud computing. The drive to incorporate neuroscience principles into computing hardware is motivated by the low power consumption, parallel processing, and reconfigurability of the human brain. The diverse library of 2D materials with atomic-level thicknesses, exceptional electrostatic tunability, and integration versatility is particularly well-suited for realizing bio-realistic synaptic and neuronal functionality. Here, we summarize past and present work in this field and outline the frontier challenges that have not yet been overcome. Here we also delineate potential solutions and suggest that the neuroscience principles of criticality and synchrony have the potential to inspire breakthrough applications of 2D materials in neuronal computing networks.

36 MATERIALS SCIENCE↗