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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
DOE OSTI2020

From Long-distance Entanglement to Building a Nationwide Quantum Internet: Report of the DOE Quantum Internet Blueprint Workshop

A Quantum Path Forward. Today, many scientific experts recognize that building and scaling quantum-protected and enhanced communication networks are among the most important technological frontiers of the 21st century. The international research community perceives the construction of a first prototype global quantum network-the Quantum Internet-to be within reach over the next decade. In February 2020, the U.S. Department of Energy (DOE)'s Office of Advanced Scientific Computing Research hosted the Quantum Internet Blueprint workshop to define a potential roadmap toward building the first nationwide quantum Internet. The workshop participants included representatives from DOE national laboratories, universities, industry, and other U.S. agencies with serious interests in quantum networking. The goal was to provide an outline of the essential research needed, detail any engineering and design barriers, and suggest a path forward to move from today's limited local network experiments to a viable, secure quantum Internet.

Peters, Nicholas↗
DOE OSTI2022

On the Viability of Quantum Annealers to Solve Fluid Flows

This paper explores the suitability of upcoming novel computing technologies, particularly adiabatic annealing based quantum computers, to solve fluid dynamics problems that form a critical component of several science and engineering applications. For our experiments, we start with a well-studied one-dimensional simple flow problem, and provide a framework to convert such problems in continuum to a form amenable for deployment on such quantum annealers. Since the DWave annealer returns multiple states sampling the energy landscape of the problem, we explore multiple solution selection strategies to approximate the solution of the problem. We analyze the continuum solutions obtained both qualitatively and quantitatively as well as their sensitivities to the particular solution selection scheme.

42 ENGINEERING↗
DOE OSTI2022

Nonlocal subpicosecond delay metrology using spectral quantum interference

Precise knowledge of position and timing information is critical to support elementary protocols such as entanglement swapping on quantum networks. While approaches have been devised to use quantum light for such metrology, they largely rely on time-of-flight (ToF) measurements with single-photon detectors and, therefore, are limited to picosecond-scale resolution owing to detector jitter. In this work, we demonstrate an approach to distributed sensing that leverages phase modulation to map changes in the spectral phase to coincidence probability, thereby overcoming the limits imposed by single-photon detection. By extracting information about the joint biphoton phase, we measure a generalized delay—the difference in signal–idler arrival, relative to local radio frequency (RF) phase modulation. For nonlocal ranging measurements, we achieve (2$σ$) precision of ±0.04 ps and for measurements of the relative RF phase, (2$σ$) precision of ±0.7°. We complement this fine timing information with ToF data from single-photon time-tagging to demonstrate absolute measurement of time delay. By relying on off-the-shelf telecommunications equipment and standard quantum resources, this approach has the potential to reduce overhead in practical quantum networks.

42 ENGINEERING↗
DOE OSTI2025

Orbital Engineering Band Degeneracy in a Dual-Square Carbon-Oxide Framework

Electron band degeneracies in momentum space give rise to exotic quantum phenomena that have sparked intense interest in condensed matter physics and materials science. Nodal-lines─isolines in k-space formed by the incidental touching of two bands that share the same energy but belong to discrete eigenstates─arise in the presence of symmetries that preclude effective hybridization. Despite recent advances in the design, bottom-up assembly, and engineering of exotic electronic states in graphene nanomaterials, the extension of this approach to access synthetic two-dimensional (2D) quantum materials derived from metal- or covalent-organic frameworks (COFs) has lagged behind. Here we present a molecular orbital engineering approach for designing and fabricating an edge-centered dual square lattice within a π-conjugated 2D-tetraoxa[8]circulene (2D-TOC) COF. First-principles calculations and scanning tunnelling spectroscopy reveal the emergence of Frontier states at the center of a 3 × 3 lattice that give rise to Dirac nodal-lines in 2D-TOC. Our findings not only provide a general guide for the design of conjugated COFs with custom tailored electronic properties from molecular fragments but enable the exploration of emergent topological phenomena in synthetic 2D materials with potential application for high-speed, low-power data processing, transmission, and storage.

Dirac nodal line semimetal↗
DOE OSTI2022

Quantum Photon Sources in WSe 2 Monolayers Induced by Weakly Localized Strain Fields

Quantum emitters in semiconductor transition metal dichalcogenide (TMD) monolayers hold great promise for many quantum optics applications due to the intriguing properties afforded by the host materials. The creation of localized excitonic states in two-dimensional semiconductors is also fundamentally interesting. Local strain engineering of TMD monolayers has been attested to be a viable approach for creating quantum emitters. However, despite the ubiquitous existence of local topography variations in the structures used to create strain gradients in the TMD monolayers, an understanding of their influence on the strain fields and exciton trapping is notably lacking, especially on the nanoscale. In this study, we investigate WSe 2 monolayers deposited on the edges of asfabricated trenches, which are deemed to induce 1D delocalized strain profiles in the monolayers, and observe optical signatures of weakly confined excitonic states supporting biexciton emission. Here, our numerical simulations of the strain distributions suggest that the quantum emitters originate from quasi-1D like localized strain profiles induced by local topography variations at the trench edges. These findings have strong implications toward the controlled creation of quantum emitters in TMD monolayers and their efficient coupling to photonic structures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Optimizing thermodynamic trajectories using evolutionary and gradient-based reinforcement learning

Here using a model heat engine, we show that neural-network-based reinforcement learning can identify thermodynamic trajectories of maximal efficiency. We consider both gradient and gradient-free reinforcement learning. We use an evolutionary learning algorithm to evolve a population of neural networks, subject to a directive to maximize the efficiency of a trajectory composed of a set of elementary thermodynamic processes; the resulting networks learn to carry out the maximally efficient Carnot, Stirling, or Otto cycles. When given an additional irreversible process, this evolutionary scheme learns a previously unknown thermodynamic cycle. Gradient-based reinforcement learning is able to learn the Stirling cycle, whereas an evolutionary approach achieves the optimal Carnot cycle. Our results show how the reinforcement learning strategies developed for game playing can be applied to solve physical problems conditioned upon path-extensive order parameters.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Sub-1 Volt and high-bandwidth visible to near-infrared electro-optic modulators

Abstract Integrated electro-optic (EO) modulators are fundamental photonics components with utility in domains ranging from digital communications to quantum information processing. At telecommunication wavelengths, thin-film lithium niobate modulators exhibit state-of-the-art performance in voltage-length product ( V π L ), optical loss, and EO bandwidth. However, applications in optical imaging, optogenetics, and quantum science generally require devices operating in the visible-to-near-infrared (VNIR) wavelength range. Here, we realize VNIR amplitude and phase modulators featuring V π L ’s of sub-1 V ⋅ cm, low optical loss, and high bandwidth EO response. Our Mach-Zehnder modulators exhibit a V π L as low as 0.55 V ⋅ cm at 738 nm, on-chip optical loss of ~0.7 dB/cm, and EO bandwidths in excess of 35 GHz. Furthermore, we highlight the opportunities these high-performance modulators offer by demonstrating integrated EO frequency combs operating at VNIR wavelengths, with over 50 lines and tunable spacing, and frequency shifting of pulsed light beyond its intrinsic bandwidth (up to 7x Fourier limit) by an EO shearing method.

42 ENGINEERING↗
DOE OSTI2022

Role of p-GaN layer thickness in the degradation of InGaN-GaN MQW solar cells under 405 nm laser excitation

GaN-based solar cells with InGaN multiple quantum wells (MQWs) are promising devices for application in space environment, concentrator solar systems, wireless power transmission and multi-junction solar cells. It is therefore important to understand their degradation kinetics when submitted to high-temperature and high-intensity stress. We submitted three samples of GaN-InGaN MQW solar cells with p-AlGaN electron-blocking-layer with different thickness of the p-GaN layer to constant power stress at 310 W/cm 2 , 175 °C for several hundred hours. The main degradation modes are a reduction of open-circuit voltage, short-circuit current, external quantum efficiency, power conversion efficiency and electroluminescence. In particular, we observed that a thinner p-GaN layer results in a stronger degradation observed on the cell operating parameters. The analysis of the dark I-V characteristics showed an increase in low-forward bias current and the analysis of electroluminescence showed a decrease in the electroluminescene emitted by the (forward biased) cell, as a consequence of stress. This work highlights that the cause of degradation is possibly related to a diffusion mechanism, which results in an increase of defect density in the active region. Finally, the impurities involved in the diffusion processes possibly originate from the p-side of the devices, therefore a thicker p-GaN layer reduces the amount of defects reaching the active region.

14 SOLAR ENERGY↗
DOE OSTI2022

Membrane potential sensing: Material design and method development for single particle optical electrophysiology

We review the development of “single” nanoparticle-based inorganic and organic voltage sensors, which can eventually become a viable tool for “non-genetic optogenetics.” The voltage sensing is accomplished with optical imaging at the fast temporal response and high spatial resolutions in a large field of view. Inorganic voltage nanosensors utilize the Quantum Confined Stark Effect (QCSE) to sense local electric fields. Engineered nanoparticles achieve substantial single-particle voltage sensitivity (~2% Δλ spectral Stark shift up to ~30% ΔF/F per 160 mV) at room temperature due to enhanced charge separation. A dedicated home-built fluorescence microscope records spectrally resolved images to measure the QCSE induced spectral shift at the single-particle level. Biomaterial based surface ligands are designed and developed based on theoretical simulations. The hybrid nanobiomaterials satisfy anisotropic facet-selective coating, enabling effective compartmentalization beyond non-specific staining. Self-spiking- and patched-HEK293 cells and cortical neurons, when stained with hybrid nanobiomaterials, show clear photoluminescence intensity changes in response to membrane potential (MP) changes. Organic voltage nanosensors based on polystyrene beads and nanodisk technology utilize Fluorescence (Förster) Resonance Energy Transfer (FRET) to sense local electric fields. Voltage sensing FRET pairs achieve voltage sensitivity up to ~35% ΔF/F per 120 mV in cultures. Non-invasive MP recording from individual targeted sites (synapses and spines) with nanodisks has been realized. However, both of these QCSE- and FRET-based voltage nanosensors yet need to reach the milestone of recording individual action potentials from individual targeted sites.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Strongly coupled edge states in a graphene quantum Hall interferometer

Electronic interferometers using the chiral, one-dimensional (1D) edge channels of the quantum Hall effect (QHE) can demonstrate a wealth of fundamental phenomena. The recent observation of phase jumps in a Fabry-Pérot (FP) interferometer revealed anyonic quasiparticle exchange statistics in the fractional QHE. When multiple integer edge channels are involved, FP interferometers have exhibited anomalous Aharonov-Bohm (AB) interference frequency doubling, suggesting putative pairing of electrons into 2e quasiparticles. Here, we use a highly tunable graphene-based QHE FP interferometer to observe the connection between interference phase jumps and AB frequency doubling, unveiling how strong repulsive interaction between edge channels leads to the apparent pairing phenomena. By tuning electron density in-situ from filling factor v < 2 to v > 7, we tune the interaction strength and observe periodic interference phase jumps leading to AB frequency doubling. Our observations demonstrate that the combination of repulsive interaction between the spin-split v = 2 edge channels and charge quantization is sufficient to explain the frequency doubling, through a near-perfect charge screening between the localized and extended edge channels. Our results show that interferometers are sensitive probes of microscopic interactions and enable future experiments studying correlated electrons in 1D channels using density-tunable graphene.

42 ENGINEERING↗
DOE OSTI2020

Lidar-based remote infrared gas sensor for monitoring anthropogenic pollution: a proof of concept

We propose using wavelength-modulation laser absorption spectroscopy in combination with quadrature detection of scattered light for remote industrial pollution monitoring in the atmosphere with a compact lidar-based gas sensor, which can be mounted on board an unmanned aerial vehicle. The instrument can be used for detecting leaks in product pipe lines; monitoring toxic gases near landfill sites, waste incineration plants, and other hazardous man-made facilities; analysing the gas atmosphere in industrial buildings and structures; and monitoring engineering processes at a sensitivity level of tens of ppm m in gas concentration measurements at characteristic distances of tens of metres. (laser applications and other issues in quantum electronics)

42 ENGINEERING↗
DOE OSTI2022

Stabilizing and Improving Qubit Coherence by Engineering the Noise Spectrum of Two-Level Systems

Superconducting circuits are a leading platform for quantum computing. However, their coherence times are still limited and exhibit temporal fluctuations. Those phenomena are often attributed to the coupling between qubits and material defects that can be well described as an ensemble of two-level systems (TLSs). Among them, charge fluctuators inside amorphous oxide layers contribute to both low-frequency 1 / f charge noise and high-frequency dielectric loss, causing fast qubit dephasing and relaxation. Moreover, spectral diffusion from mutual TLS interactions varies the noise amplitude over time, fluctuating the qubit lifetime. Here, we propose to mitigate those harmful effects by engineering the relevant TLS noise spectral densities. Specifically, our protocols smooth the high-frequency noise spectrum and suppress the low-frequency noise amplitude via depolarizing and dephasing the TLSs, respectively. As a result, we predict a drastic stabilization in qubit lifetime and an increase in qubit pure dephasing time. Our detailed analysis of feasible experimental implementations shows that the improvement is not compromised by spurious coupling from the applied noise to the qubit.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Quantum Computing and Visualization: A Disruptive Technological Change Ahead

The focus of this Visualization Viewpoints article is to provide some background on quantum computing (QC), to explore ideas related to how visualization helps in understanding QC, and examine how QC might be useful for visualization with the growth and maturation of both technologies in the future. In a quickly evolving technology landscape, QC is emerging as a promising pathway to overcome the growth limits in classical computing. In some cases, QC platforms offer the potential to vastly outperform the familiar classical computer by solving problems more quickly or that may be intractable on any known classical platform. As further performance gains for classical computing platforms are limited by diminishing Moore’s Law scaling, QC platforms might be viewed as a potential successor to the current field of exascale-class platforms. Importantly, while present-day QC hardware platforms are still limited in scale, the field of quantum computing is robust and rapidly advancing in terms of hardware capabilities, software environments for developing quantum algorithms, and educational programs for training the next generation of scientists and engineers. After a brief introduction to QC concepts, the focus of this article is to explore the interplay between the fields of visualization and QC. First, visualization has played a role in QC by providing the means to show representations of the quantum state of single-qubits in superposition states and multiple-qubits in entangled states. Second, there are a number of ways in which the field of visual data exploration and analysis may potentially benefit from this disruptive new technology though there are challenges going forward.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Reshaping the Quantum Arrow of Time

While the microscopic laws of physics are often symmetric under time reversal, most natural processes that we observe are not. The emergent asymmetry between typical and time-reversed processes is referred to as the arrow of time. In quantum physics, an arrow of time emerges when a sequence of measurements is performed on a system. We introduce quantum control tools that can yield dynamics more consistent with time flowing backward than forward. The control tools are based on the explicit construction of a Hamiltonian that can replicate the stochastic trajectories of a monitored quantum system. Such a Hamiltonian can reverse the effect of monitoring and, via a feedback process, generate trajectories consistent with a reversed arrow of time. It can also be used to simulate the backward-in-time dynamics of an open quantum system. Finally, we design a feedback-driven continuous measurement engine powered by the energy pumped into the system by the monitoring process. We show that the engine can operate under experimentally realizable conditions with feedback delay and finite-efficiency measurements.

Entropy production↗
DOE OSTI2022

Electronic Structure of InAs and InSb Surfaces: Density Functional Theory and Angle-Resolved Photoemission Spectroscopy

The electronic structure of surfaces plays a key role in the properties of quantum devices. However, surfaces are also the most challenging to simulate and engineer. Here, in this work, the electronic structure of InAs(001), InAs(111), and InSb(110) surfaces is studied using a combination of density functional theory (DFT) and angle-resolved photoemission spectroscopy (ARPES). Large-scale first principles simulations are enabled by using DFT calculations with a machine-learned Hubbard U correction [npj Comput. Mater. 6, 180 (2020)]. To facilitate direct comparison with ARPES results, a “bulk unfolding” scheme is implemented by projecting the calculated band structure of a supercell surface slab model onto the bulk primitive cell. For all three surfaces, a good agreement is found between DFT calculations and ARPES. For InAs(001), the simulations clarify the effect of the surface reconstruction. Different reconstructions are found to produce distinctive surface states, which may be detected by ARPES with low photon energies. For InAs(111) and InSb(110), the simulations help elucidate the effect of oxidation. Owing to larger charge transfer from As to O than from Sb to O, oxidation of InAs(111) leads to significant band bending and produces an electron pocket, whereas oxidation of InSb(110) does not. The combined theoretical and experimental results may inform the design of quantum devices based on InAs and InSb semiconductors, for example, topological qubits utilizing the Majorana zero modes.

42 ENGINEERING↗
DOE OSTI2021

Interfacial and Confinement-Mediated Organization of Gas Hydrates, Water, Organic Fluids, and Nanoparticles for the Utilization of Subsurface Energy and Geological Resources

Harnessing the subsurface geologic environments in an efficient and environmentally sustainable manner is challenged by uncertainties associated with predicting the fate of fluids and sustaining porosity and permeability in subsurface geologic environments. Some of these uncertainties arise from confined and interfacially induced structures of fluids in subsurface geologic environments. The formation of gas hydrates, phase transitions of confined fluids, assembly and deposition of heavy hydrocarbons, and the agglomeration and fate of nanoparticles in confined environments are summarized in this review. Nanoscale confinement contributes to anisotropic structures and dynamics of fluids, which is the basis for anomalous phase transition thermodynamics, reactivity, transport, and geomechanical behavior. In this review, we discuss the structures of confined fluids and deviation in observed properties from bulk fluids. The factors influencing the structures of confined fluids can be generally divided into two groups: (a) pore characteristics including pore size, pore surface chemistry, and pore geometry and (b) confined fluid/solid characteristics such as molecular structure, concentrations, charges, pore filling, and presence of additives. Scientific advancements and knowledge gaps in our understanding of the structures of confined fluids and the associated differences in observed properties compared to bulk fluids are discussed. Here, the phenomena discussed in this review are of particular relevance to our efforts in harnessing the subsurface environments for a low carbon future by increasing the utilization of geothermal energy, using CO 2 as a working fluid, and storing CO 2 in subsurface geologic environments.

42 ENGINEERING↗
DOE OSTI2020

Consistency-Enhanced Evolution for Variable Selection Can Identify Key Chemical Information from Spectroscopic Data

In the last few decades, spectroscopic techniques such as near-infrared (NIR) spectroscopy have gained wide applications in several industries, such as the pharmaceutical, agricultural, oil, and gas industries. As a result, various soft sensors have been developed to predict sample properties from spectroscopic readings. Because the spectroscopic readings at different wavelengths, especially at the adjacent wavelengths, are highly correlated, it has been shown that variable selection could significantly improve a soft sensor’s prediction performance while reducing the model complexity. To improve the prediction performance, most variable selection methods focus on identifying the variables (i.e., wavelengths or wavelength segments) that are strongly correlated with the dependent variable. Although many successful applications have been reported, these variable selection methods do have their limitations. Specifically, the selected wavelengths sometimes show little connection to the chemical bounds or functional groups presenting in the sample. In addition, the selected variables can be quite sensitive to the choice of the training samples. In this work, we address these limitations from a different perspective: if a variable selection algorithm can identify the truly relevant input variables, it should consistently identify the same subset of variables regardless of the choice of the training samples. Therefore, we propose a variable selection method that aims to improve the consistency of variable selection resulting from different training samples. Furthermore, the new algorithm is termed consistency-enhanced evolution for variable selection (CEEVS). To demonstrate the performance and robustness of CEEVS, we compare the proposed method with three representative variable selection methods using five published NIR data sets. These case studies clearly demonstrate that by improving the variable selection consistency, we can not only achieve improved prediction performance, but also identify key chemical information from spectroscopic data.

42 ENGINEERING↗