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DOE OSTI2017

Fast and accurate implementation of Fourier spectral approximations of nonlocal diffusion operators and its applications

This work is concerned with the Fourier spectral approximation of various integral differential equations associated with some linear nonlocal diffusion and peridynamic operators under periodic boundary conditions. For radially symmetric kernels, the nonlocal operators under consideration are diagonalizable in the Fourier space so that the main computational challenge is on the accurate and fast evaluation of their eigenvalues or Fourier symbols consisting of possibly singular and highly oscillatory integrals. For a large class of fractional power-like kernels, we propose a new approach based on reformulating the Fourier symbols both as coefficients of a series expansion and solutions of some simple ODE models. We then propose a hybrid algorithm that utilizes both truncated series expansions and high order Runge–Kutta ODE solvers to provide fast evaluation of Fourier symbols in both one and higher dimensional spaces. It is shown that this hybrid algorithm is robust, efficient and accurate. As applications, we combine this hybrid spectral discretization in the spatial variables and the fourth-order exponential time differencing Runge–Kutta for temporal discretization to offer high order approximations of some nonlocal gradient dynamics including nonlocal Allen–Cahn equations, nonlocal Cahn–Hilliard equations, and nonlocal phase-field crystal models. Numerical results show the accuracy and effectiveness of the fully discrete scheme and illustrate some interesting phenomena associated with the nonlocal models.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2017

Modeling and Analysis of Coupled Flow Through Packed Beds as a Diagnostic Tool for Packed Bed Reactor Health - 17172

The US Department of Energy, Office of River Protection, is building the Waste Treatment and Immobilization Plant (WTP) in Richland, Washington, to immobilize the hundreds of millions of liters of radioactive waste stored at the Hanford Site in Washington state. The offgas generated during vitrification of these wastes requires treatment to remove and/or destroy chemical and radioactive hazardous components before release to the atmosphere. In particular, volatile and semi-volatile hydrocarbon components are to be catalytically oxidized to carbon dioxide and water, whereas nitrogen oxides (NOx) are to be catalytically reduced to nitrogen and water. These tasks are accomplished in a series of packed bed reactors. Achieving the requisite Destruction/Removal Efficiency (DRE) for each of the tracked components is highly dependent on the flow characteristics of the offgas through the packed beds. The flow kinetics may be monitored and characterized during the initial warm-up of the system. The gases, initially at 76 deg. C (169 deg. F), (a) flow through one side of a countercurrent heat exchanger to recover heat from the exiting gases (which have already passed through the catalytic beds), (b) are then further heated electrically to approximately 400 deg. C (750 deg. F; the preferred operating temperature of the Thermo Catalytic Oxidizer (TCO)), (c) pass through the TCO where the reduced components of the offgas are oxidized over a supported Pt catalyst bed, (d) are partially cooled to approximately 315 deg. C (600 deg. F) by addition of approximately 25% (by weight) diluted ammonia/air mixture, (e) pass through the Selective Catalytic Reducer (SCR) where the NOx components are converted to N{sub 2} and H{sub 2}O over a supported V2O{sub 5}/TiO{sub 2} catalyst bed, and (f) exit through the hot side of the countercurrent heat exchanger. The electrical heater is not powerful enough to raise the temperature of the offgas to the desired 400 deg. C without the contribution of the heat recovered in the heat exchanger. Moreover, the thermal mass of the beds and housings of the TCO and SCR require a significant input of thermal energy to reach the desired operating temperatures; the better part of a day is required to bring the unit from ambient temperatures to operating temperatures. Therefore, the temperature of the stream during the initial warm-up of the system at each point in the system is dependent upon the thermal mass, flow dispersion, and permeability of the components, quantified as characteristic/representative volumes and residence times. By monitoring the temperature of the offgas as it enters and exits each portion of the system during this warm-up period one may model the system as a series of small Continuously Stirred Tank Reactors (CSTR)s (referred to as 'CSTRlets') to explain the flow kinetics through the catalyst beds. These component CSTRlets are adjustable in size and number, that one may model the flow profile of the gases through the catalyst beds. For example, a single large CSTR will present an effluent temperature profile with a simple exponential decay shape. Concatenating more CSTRlets generate more complex sigmoidal responses. Concatenating one CSTRlet significantly larger than the others in the train also alters the shape of the effluent temperature profile, in a fashion not replicable by a train of equal-sized CSTRlets. The ultimate goal is to accurately emulate the entire system as a representative CSTRlet train. Once accomplished, this characterization may be used in subsequent warm-ups (following shutdown for catalyst maintenance, for example) or by an intentional step change in inlet offgas temperature to detect/diagnose anomalies in flow through the beds (e.g., channeling or partial blockage.) This work presents development of this model through analytical, calculational, and empirical means. - The analytic model is accomplished by Laplace transform analysis of each component to recover component process transfer functions. - The calculational portion is performed via brute force finite element calculation. - Fitting empirical data from the warm-up of the TCO skid allows one to select the hypothetical CSTRlet trains which best fit the TCO and SCR beds for the analytical and finite element calculations. The first portion of this paper presents the development of the analytical (Laplace space) model of the coupled system. Estimated values for the initial temperature, mass, specific heat, electrical heat, and relative quantities of the offgas, catalyst beds, stainless steel housings, and ammonia dilution stream are used to generate expected temperature profiles at several selected junctures of the system. The number and size of the component hypothetical CSTRlets are calculated from the analytical model and are used to predict temperature profiles at the exit of the system and at intermediate junctions between system components (where thermocouples are present in the actual unit.) The finite element calculations employ a series of CSTRlet volumes to produce a similar suite of temperature profiles, for comparison with the analytical model results. Finally, empirical data from the Factory Acceptance Test system warm-up are used to select and compare the results from each modeling strategy to select the CSTRlet train(s) which best model the behavior of the actual system. This work presents a novel method of system component characterization, of value to the WTP plant and similar vitrification facilities as well as chemical process industries unrelated to waste management. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2026

Statistical Correlation of Heliostat Pointing Deviation With Wind

This work was carried out as part of the Heliostat Consortium (HelioCon) Field Deployment subtask with the aim to develop a reduced order model framework for correlating wind speed and pointing deviation of a heliostat facet. There are only sparse field measurements of heliostat pointing deviations and accompanying wind conditions published in the literature. Heliostat test standards, such as IEC 62862-4-3, propose a suite of tests including laser pointing repeatability at wind speeds below 4 m/s, and provide technical requirements for heliostat slope and tracking deviations in coarse average wind speed bins of 4 m/s, 6 m/s, and 8 m/s. In addressing the gap of the variation of heliostat pointing deviation with wind speed, field measurements of laser pointing on a grid target and wind conditions were analyzed in this study at the Third-Party Metrology Platform at the National Laboratory of the Rockies (NLR) Flatirons Campus. Horizontal pointing deviations were found to follow a logarithmic relationship with peak wind speed, whereas vertical pointing deviations follow an exponential relationship with peak wind speed. Both horizontal and vertical pointing deviations also follow a second order polynomial relationship, as expected from the proportionality of elastic loads and deformations with the square of wind speed. The results indicate that heliostat facet pointing deviations in the vertical direction increase at a faster rate than in the horizontal direction with increasing wind speed over the tested range, however these are dependent on the heliostat structural design. Next steps are recommended for additional field measurements to confirm a linear relationship of pointing deviation with applied moment on a heliostat facet, and to distinguish between gravity-induced and wind-induced pointing deviations at different elevation angles. The derived correlations in the preliminary analysis in this report serve as a case study for heliostat developers and plant operators to estimate the wind-induced pointing deviations and their variation with peak gust wind speed. Next steps in future work would recommend higher resolution and longer duration datasets for different elevation angles and wind directions to reduce uncertainties and variance of collected laser beam spot data and their correlations with bin-averaged wind speed.

17 WIND ENERGY↗

DOE OSTI2016

HUMAN FAILURE EVENT DEPENDENCE: WHAT ARE THE LIMITS

Abstract Objectives: This paper discusses the differences between classical human reliability analysis (HRA) dependence and the full spectrum of probabilistic dependence. Positive influence suggests an error increases the likelihood of subsequent errors or success increases the likelihood of subsequent success. Currently the typical method for dependence in HRA implements the Technique for Human Error Rate Prediction (THERP) positive dependence equations. This assumes that the dependence between two human failure events varies at discrete levels between zero and complete dependence (as defined by THERP). Dependence in THERP does not consistently span dependence values between 0 and 1. In contrast, probabilistic dependence employs Bayes Law, and addresses a continuous range of dependence. Methods: Using the laws of probability, complete dependence and maximum positive dependence do not always agree. Maximum dependence is when two events overlap to their fullest amount. Maximum negative dependence is the smallest amount that two events can overlap. When the minimum probability of two events overlapping is less than independence, negative dependence occurs. For example, negative dependence is when an operator fails to actuate Pump A, thereby increasing his or her chance of actuating Pump B. The initial error actually increases the chance of subsequent success. Results: Comparing THERP and probability theory yields different results in certain scenarios; with the latter addressing negative dependence. Given that most human failure events are rare, the minimum overlap is typically 0. And when the second event is smaller than the first event the max dependence is less than 1, as defined by Bayes Law. As such alternative dependence equations are provided along with a look-up table defining the maximum and maximum negative dependence given the probability of two events. Conclusions: THERP dependence has been used ubiquitously for decades, and has provided approximations of the dependencies between two events. Since its inception, computational abilities have increased exponentially, and alternative approaches that follow the laws of probability dependence need to be implemented. These new approaches need to consider negative dependence and identify when THERP output is not appropriate.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2020

Description of Sensor Assignment Optimization Method as Deployed on a Multi-Node Cluster

Data analytic methods are being developed to address the problem of how to assign a sensor set in a nuclear facility such that a requisite level of process monitoring capability is realized and that the sensor set is sufficiently rich to determine the status of the individual sensors with respect to need for calibration. There is an awareness in the nuclear industry that data analytics combined with rich sensor sets represent a means to improve operations and reduce costs. In the industry the calibration problem has been previously approached as an empirical data-driven problem with several methods having been developed. However, the experience of the utilities over the past ten years with these methods indicates that the absence of physics-based information renders the data-driven approach less reliable. Complicating factors such as the inherent variability of operation (both equipment alignment and operating condition) can confound a pure data-driven approach while there are no rigorous guidelines for determining what constitutes an adequate sensor set. The solution under development to overcome these shortcomings supplements the data analytic method with process information in a so-called process-constrained data-analytic approach. Simple balance equations are written for generic components (e.g., mechanical pump, valve, and heat exchanger). These do not require a priori knowledge of process parameters, such as heat transfer coefficients or friction factors. All that is needed on the part of the utility user is to identify the components and how they are connected. This report describes the development of a parallel computing capability for determining the optimal sensor set. The optimal sensor set problem suffers from the curse of dimensionality. Computation time increases exponentially as the size of the system grows. To overcome this difficulty a pre-conditioner algorithm is developed to find an approximate solution close the actual solution. This serves as a seed for the full-blown algorithm and acts to constrain the space that must searched. The optimization algorithms are described and the implementation on a parallel computing platform is described. The application of the method to a use case we are solving in collaboration with our utility partner served to illustrate how the default sensor set in a nuclear plant may not provide sufficient coverage to infer sensor calibration status.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2023

The DESC stellarator code suite. Part 1. Quick and accurate equilibria computations

Three-dimensional equilibrium codes are vital for stellarator design and operation, and high-accuracy equilibria are also necessary for stability studies. This paper details comparisons of two three-dimensional equilibrium codes: VMEC, which uses a steepest-descent algorithm to reach a minimum-energy plasma state, and DESC, which minimizes the magnetohydrodynamic (MHD) force error in real space directly. Accuracy as measured by satisfaction of MHD force balance is presented for each code, along with the computation time. It is shown that DESC is able to achieve more accurate solutions, especially near axis. The importance of higher-accuracy equilibria is shown in DESC's better agreement of stability metrics with asymptotic formulae. DESC's global Fourier–Zernike basis also yields solutions with analytic derivatives explicitly everywhere in the plasma volume, provides improved accuracy in the radial direction versus conventional finite differences and allows for exponential convergence. Further, DESC can compute a solution with the same accuracy as VMEC in order-of-magnitude less time.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2020

Grid Integration of Small-Scale Photovoltaic Systems in Secondary Distribution Network—A Review

The relative share of renewable energy, specifically the solar photovoltaic (PV), is increasing exponentially in the world electric energy sector. This is a cumulative result of reduction in the cost of solar panels, improvement in the panel efficiency, and advancement in the associated power electronics. Among different types of PV plants, installation of small-scale rooftop PV is growing rapidly due to direct end-user benefits and lucrative governmental incentives. There are various standards developed in regards to grid integration of PVs and other distributed generations (DGs). Different power converter topologies are developed to interface the PV panel with the utility grid. To keep up with the stringent regulations imposed by the standards, various control strategies and grid synchronization methods have been developed. This review article amalgamates and summarizes all of the aforementioned aspects of a grid-integrated PV system including various standards, power stage architectures, grid synchronization methods, operation under extreme events, and control methodologies, pertaining to small-scale PV plants. This article will help freshman researchers to gain some familiarity with the topic and introduce them to some of the key issues encountered in this field.

14 SOLAR ENERGY↗

NASA NTRS2018

Collaborative Data Curation to Support the Multi-Mission Algorithm and Analysis Platform (MAAP)

Upcoming space-borne missions will offer unprecedented data about Earth but will also feature exponentially high data volumes. These high data volumes will change the way the scientific community works with data and will also create a unique need for improved data sharing and collaboration. NASA and ESA are working together to address these issues by collaboratively developing the Multi-Mission Algorithm and Analysis Platform (MAAP) to improve the understanding of global aboveground terrestrial carbon dynamics. The MAAP will support ESA’s BIOMASS mission, NASA’s GEDI mission and NASA/ISRO’s NISAR mission. The MAAP will be developed in two phases: a pilot phase and a full production phase. The pilot phase will demonstrate collaboration and basic capabilities. The pilot phase will focus on biomass relevant airborne and field campaign data. Two NASA teams are supporting the development of the MAAP. The MAAP engineering team is responsible for the development, maintenance and operations of the MAAP system while the MAAP data team ensures the ongoing quality of the data, metadata and other information provided in the MAAP. The MAAP data team also supports the ingest and archive of identified data to the MAAP platform. This poster describes the use case development process for the pilot MAAP and the data curated in support of those use cases. Additionally, this presentation will outline the pilot MAAP data ingest process and metadata curation effort along with efforts to ensure interoperability between ESA and NASA data and metadata.

Bugbee, Kaylin↗

DOE OSTI2025

Advancing quantum simulations of the nuclear shell model with Gray-code–based resource-efficient protocols

Background: Some of the computational limitations in solving the nuclear many-body problem could be overcome by utilizing quantum computers. The nuclear shell-model calculations providing deeper insights into the properties of atomic nuclei are one such case with high demand for resources, as the size of the Hilbert space grows exponentially with the number of particles involved. Quantum algorithms are being developed to overcome these challenges and advance such calculations. Purpose: To develop quantum circuits for the nuclear shell-model, leveraging the capabilities of noisy intermediate-scale quantum (NISQ) devices. Here, we aim to minimize resource requirements (specifically in terms of qubits and gates) and strive to reduce the impact of noise by employing relevant mitigation techniques. Methods: We achieve noise resilience by designing an optimized Ansatz for the variational quantum eigensolver (VQE) based on Givens rotations and incorporating qubit-ADAPT-VQE in combination with variational quantum deflation (VQD) to compute ground and excited states, incorporating the zero-noise extrapolation mitigation technique. Furthermore, the qubit requirements are significantly reduced by mapping the basis states to qubits using Gray-code encoding and generalizing transformations of fermionic operators to efficiently represent many-body states. Results: By employing the resource-efficient protocols, we achieve the ground and excited state energy levels of 38 Ar and 6 Li with better accuracy. These energy levels are presented for noiseless simulations, noisy conditions, and after applying noise mitigation techniques. Results are compared for Jordan-Wigner and Gray-code encoding using VQE, qubit-ADAPT-VQE, and VQD. Conclusions: Our work highlights the potential of resource-efficient protocols to leverage the full potential of NISQ devices in scaling the nuclear shell model calculations, offering a pathway toward more complex quantum simulations in nuclear physics. This approach establishes a framework for studying other nuclear systems with improved quantum resource efficiency, marking a significant advancement in applying quantum computing to realistic nuclear physics applications.

Physics - Nuclear physics and radiation physics↗

NASA NTRS2017

NIAC Swarm Flyby Gravimetry Phase II Report

This NASA Innovative Advanced Concept (NIAC) grant has enabled the research and development of a method for conducting small body gravimetry from a spacecraft, using relative measurements to a set of deployed test-masses. The test-masses are tracked from a host spacecraft, which dispenses them near to the small body's surface. Thanks to this close proximity, the probes' orbits can be highly perturbed, which yields useful gravimetric measurements. The most readily achievable approach for tracking the probes is to use an optical instrument on- board the spacecraft. The probes then need only be reflective to sunlight. This implementation, called optical gravimetry (OpGrav), has the fewest requirements for the host spacecraft and probes.The results of this study indicate that OpGrav is feasible and offers meaningful improvement over existing methods. Parametric studies suggest roughly an order of magnitude improvement in accuracy or asteroid accessibility (how small an asteroid one can measure) over Earth-based Doppler-only mass estimation. This exponentially expands the number of potential near-Earth objects that one could study, which has implications for planetary defense.As a sample mission, we evaluated OpGrav as an added instrument on a main- belt asteroid tour mission. In this case, simulations show that OpGrav would increase the number of asteroid mass estimates from 3 of 9 to 7 of 9. That is, OpGrav has sufficient sensitivity to offer utility in missions for which it is not explicitly designed for.We designed and fabricated a prototype hardware implementation for this concept called the Small-body In-situ Multi-probe Mass Estimation Experiment (SIMMEE). This hardware provides a basis for many inputs into the simulations and grounds the models with physical values. The primary design driver for the hardware is a long life, on the order of five years prior to operation, and a need for high pointing accuracy to enable flybys of the smallest objects.The next steps include further hardware testing and extension of the concept to rendezvous cases. We believe that this concept offers planetary scientists a new and relevant means of better understanding small-bodies.

Atchison, Justin A.↗

DOE OSTI2019

Quantum chaos in the Brownian SYK model with large finite N: OTOCs and tripartite information

We consider the Brownian SYK model of N interacting Majorana fermions, with random couplings that are taken to vary independently at each time. We study the out-of-time-ordered correlators (OTOCs) of arbitrary observables and the Rényi-2 tripartite information of the unitary evolution operator, which were proposed as diagnostic tools for quantum chaos and scrambling, respectively. We show that their averaged dynamics can be studied as a quench problem at imaginary times in a model of N qudits, where the Hamiltonian displays site-permutational symmetry. By exploiting a description in terms of bosonic collective modes, we show that for the quantities of interest the dynamics takes place in a subspace of the effective Hilbert space whose dimension grows either linearly or quadratically with N, allowing us to perform numerically exact calculations up to N = 10 6 . We analyze in detail the interesting features of the OTOCs, including their dependence on the chosen observables, and of the tripartite information. We observe explicitly the emergence of a scrambling time t* ~ ln N controlling the onset of both chaotic and scrambling behavior, after which we characterize the exponential decay of the quantities of interest to the corresponding Haar scrambled values.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

NASA NTRS2005

Future Visions for Scientific Human Exploration

Today, humans explore deep-space locations such as Mars, asteroids, and beyond, vicariously here on Earth, with noteworthy success. However, to achieve the revolutionary breakthroughs that have punctuated the history of science since the dawn of the Space Age has always required humans as "the discoverers," as Daniel Boorstin contends in this book of the same name. During Apollo 17, human explorers on the lunar surface discovered the "genesis rock," orange glass, and humans in space revamped the optically crippled Hubble Space Telescope to enable some of the greatest astronomical discoveries of all time. Science-driven human exploration is about developing the opportunities for such events, perhaps associated with challenging problems such as whether we can identify life beyond Earth within the universe. At issue, however, is how to safely insert humans and the spaceflight systems required to allow humans to operate as they do best in the hostile environment of deep space. The first issue is minimizing the problems associated with human adaptation to the most challenging aspects of deep space space radiation and microgravity (or non-Earth gravity). One solution path is to develop technologies that allow for minimization of the exposure time of people to deep space, as was accomplished in Apollo. For a mission to the planet Mars, this might entail new technological solutions for in-space propulsion that would make possible time-minimized transfers to and from Mars. The problem of rapid, reliable in-space transportation is challenged by the celestial mechanics of moving in space and the so-called "rocket equation." To travel to Mars from Earth in less than the time fuel-minimizing trajectories allow (i.e., Hohmann transfers) requires an exponential increase in the amount of fuel. Thus, month-long transits would require a mass of fuel as large as the dry mass of the ISS, assuming the existence of continuous acceleration engines. This raises the largest technological stumbling block to moving humans on site as deep-space explorers, delivering the masses required for human spaceflight systems to LEO or other Earth orbital vantage points using the existing or projected fleet of Earth-to-orbit (ETO) launch vehicles. Without a return to Saturn V-class boosters or an alternate path, one cannot imagine emplacing the masses that would be required for any deep-space voyage without a prohibitive number of Shuttle-class launches. One futurist solution might involve mass launch systems that could be used to move the consumables, including fuel, water, food, and building materials, to LEO in pieces rather than launching integrated systems. This approach would necessitate the development of robotic assembly and fuel-storage systems in Earth orbit, but could provide for a natural separation of low-value cargo (e.g., fuel, water).

Garvin, James↗

NASA NTRSDate not supplied

Quantum-Compatible Variational Segmentation for Image-to-Image Wildfire Detection Using Satellite Data

Wildfire occurrences have been increasing for the past decade, leaving devastating traces across the world. In the recent efforts, remote sensing and airborne missions have been utilized to better understand and manage wildfires. This has resulted in an exponential increase in volume of remote sensing data, which has pushed the need for intelligent automation of data extraction for wildfire studies. Machine learning offers accurate automation in detecting such natural anomalies and enable decision-makers to take actions in a timely manner. Recent advances in machine learning algorithms, namely probabilistic generative methods, allow researchers and decisionmakers to step beyond detection and study “what-if” scenarios for wildfire occurrences. Additionally, they offer better imitations to the stochastic behavior of nature, and wildfire events. However, optimizing the performance of these probabilistic generative models is a computationally expensive process, specially using digital computers. On the other hand, quantum computers have recently shown a promise to reduce computationally costly training of such models and provide performance improvements. There is a body of research investigating the potential for improved machine learning methods in which key operations are performed on a quantum computer. In this study, we propose a probabilistic image-toimage segmentation approach combining a very well-known segmentation method, U-NET, with a Conditional Variational Auto-Encoder (CVAE) to not only detect wildfires but also describe the stochasticity of the phenomenon and be capable of running “what-if” scenarios. Our proposed model is compatible with training on quantum computers, which results in a quantum-assisted image-to-image segmentation approach and can be used to benchmark the potential benefit of quantum computing over the classical one.

quantum↗

NASA NTRSDate not supplied

Rolling Horizon with K-Position Search Method for Strategic Deconfliction of Package Delivery UAS

This research focuses on the strategic deconfliction of unmanned aircraft systems (UAS) in an urban package delivery environment with two depots and multiple drop-off locations. Since the formulated mixed-integer nonlinear programming (MINLP) problem is non-deterministic polynomial-time (NP) hard, a heuristic algorithm called "rolling horizon with k-position search (KPS)" is used to compute the departure sequence and scheduled time of departure (STD) of each UAS at a depot, considering temporal constraints at en-route crossing waypoints and depots for strategic deconfliction. The simulation studies show that an increase in the value of k (local neighborhood search) in the KPS reduces the average ground delay at the cost of an increase in the computation time for a given number of UAS, size of the rolling horizon window, and number of depots involved in the local neighborhood search. The studies also show that for a given rolling horizon window, the computation time increases exponentially with an increase in the total number of UAS flights when serial processing the local neighborhood search of KPS (with k > 1) and drops by an order of magnitude upon performing the local neighborhood search of KPS using parallel processing instead of serial processing. The computation time drops with the reduction in air traffic complexity of a scenario for a given number of flights, k (local neighborhood search), and rolling horizon window.

UTM↗

DOE OSTI2024

Importance of gas heating in capacitively coupled radiofrequency plasma-assisted synthesis of carbon nanomaterials

In pursuit of diamond nanoparticles, a capacitively-coupled radio frequency flow-through plasma reactor was operated with methane-argon gas mixtures. Signatures of the final product obtained microscopically and spectroscopically indicated that the product was an amorphous form of graphite. This result was consistent irrespective of combinations of the macroscopic reactor settings. To explain the observed synthesis output, measurements of C 2 and gas properties were carried out by laser-induced fluorescence and optical emission spectroscopy. Strikingly, the results indicated a strong gas temperature gradient of 100 K per mm from the center of the reactor to the wall. Based on additional plasma imaging, a model of hot constricted region (filamentation region) was then formulated. It illustrated that, while the hot constricted region was present, the bulk of the gas was not hot enough to facilitate diamond sp 3 formation: characterized by much lower reaction rates, when compared to sp 2 , sp 3 formation kinetics are expected to become exponentially slow. This result was further confirmed by experiments under identical conditions but with a H 2 /CH 4 mixture, where no output material was detected: if graphitic sp 2 formation was expected as the main output material from the methane feedstock, atomic hydrogen would then be expected to etch it away in situ, such that the net production of that sp 2 -hybridized solid material is nearly a zero. Finally, the crucial importance of gas heating was corroborated by replacing RF with microwave source whereby facile sp 3 production was attained with H 2 /CH 4 gas mixture.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Dynamic Cooling on Contemporary Quantum Computers

We study the problem of dynamic cooling whereby a target qubit is cooled at the expense of heating up N − 1 further identical qubits by means of a global unitary operation. A standard back-of-the-envelope high-temperature estimate establishes that the target qubit temperature can be dynamically cooled by at most a factor of 1 / N . Here we provide the exact expression for the minimum temperature to which the target qubit can be cooled and reveal that there is a crossover from the high initial temperature regime, where the scaling is 1 / N , to a low initial temperature regime, where a much faster scaling of 1 / N occurs. This slow, 1 / N scaling, which was relevant for early high-temperature NMR quantum computers, is the reason dynamic cooling was dismissed as ineffectual around 20 years ago; the fact that current low-temperature quantum computers fall in the fast, 1 / N scaling regime, reinstates the appeal of dynamic cooling today. We further show that the associated work cost of cooling is exponentially more advantageous in the low-temperature regime. We discuss the implementation of dynamic cooling in terms of quantum circuits and examine the effects of hardware noise. We successfully demonstrate dynamic cooling in a three-qubit system on a real quantum processor. Since the circuit size grows quickly with N , scaling dynamic cooling to larger systems on noisy devices poses a challenge. We therefore propose a suboptimal cooling algorithm, whereby relinquishing a small amount of cooling capability results in a drastically reduced circuit complexity, greatly facilitating the implementation of dynamic cooling on near-future quantum computers. Published by the American Physical Society2024

Physics↗

DOE OSTI2017

Self-Shielding Of Transmission Lines

The use of shielding to contend with noise or harmful EMI/EMR energy is not a new concept. An inevitable trade that must be made for shielding is physical space and weight. Space was often not as much of a painful design trade in older larger systems as they are in today’s smaller systems. Today we are packing in an exponentially growing number of functionality within the same or smaller volumes. As systems become smaller and space within systems become more restricted, the implementation of shielding becomes more problematic. Often, space that was used to design a more mechanically robust component must be used for shielding. As the system gets smaller and space is at more of a premium, the trades starts to result in defects, designs with inadequate margin in other performance areas, and designs that are sensitive to manufacturing variability. With these challenges in mind, it would be ideal to maximize attenuation of harmful fields as they inevitably couple onto transmission lines without the use of traditional shielding. Dr. Tom Van Doren proposed a design concept for transmission lines to a class of engineers while visiting New Mexico. This design concept works by maximizing Electric field (E) and Magnetic Field (H) field containment between operating transmission lines to achieve what he called “Self-Shielding”. By making the geometric centroid of the outgoing current coincident with the return current, maximum field containment is achieved. The reciprocal should be true as well, resulting in greater attenuation of incident fields. Figure’s 1(a)-1(b) are examples of designs where the current centroids are coincident. Coax cables are good examples of transmission lines with co-located centroids but they demonstrate excellent field attenuation for other reasons and can’t be used to test this design concept. Figure 1(b) is a flex circuit design that demonstrate the implementation of self-shielding vs a standard conductor layout.

42 ENGINEERING↗

NASA NTRS2000

Langmuir Probe Measurements in an Inductively Coupled Ar/CF4 Plasmas

Technological advancement in the microelectronics industry requires an understanding of the physical and chemical processes occurring in plasmas of fluorocarbon gases, such as carbon tetrafluoride (CF4) which is commonly used as an etchant, and their mixtures to optimize various operating parameters. In this paper we report data on electron number density (ne), electron temperature'(Te), electron energy distribution function (EEDF), mean electron energy, ion number density (ni), and plasma potential (Vp) measured by using Langmuir probe in an inductively coupled 13.56 MHz radio frequency plasmas generated in 50%Ar:50%CF4 mixture in the GEC cell. The probe data were recorded at various radial positions providing radial profiles of these plasma parameters at 10-50 mTorr pressures and 200 W and 300 W of RF power. Present measurements indicate that the electron and ion number densities increase with increase in pressure and power. Whereas the plasma potential and electron temperature decrease with increase in pressure, and they weakly depend on RF power. The radial profiles exhibit that the electron and ion number densities and the plasma potential peak at the center of the plasma with an exponential fall away from it, while the electron temperature has a minimum at the center and it increases steadily towards the electrode edge. The EEDFs have a characteristic drop near the low energy end at all pressures and pressures and their shapes represent non-Maxwellian plasma and exhibit more like Druyvesteyn energy distribution.v

Rao, M. V. V. S.↗