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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 649 records · Page 36
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

The sodium channel Na X : Possible player in excitation–contraction coupling

Abstract The sodium channel Na X (encoded by the SCN7A gene) was originally identified in the heart and skeletal muscle and is structurally similar to the other voltage‐gated sodium channels but does not appear to be voltage gated. Although Na X is expressed at high levels in cardiac and skeletal muscle, little information exists on the function of Na X in these tissues. Transcriptional profiling of ion channels in the heart in a subset of patients with Brugada syndrome revealed an inverse relationship between the expression of Na X and Na V 1.5 suggesting that, in cardiac myocytes, the expression of these channels may be linked. We propose that Na X plays a role in excitation–contraction coupling based on our experimental observations. Here we show that in cardiac myocytes, Na X is expressed in a striated pattern on the sarcolemma in regions corresponding to the sarcomeric M‐line. Knocking down Na X expression decreased Na V 1.5 mRNA and protein and reduced the inward sodium current ( I Na+ ) following cell depolarization. When the expression of Na V 1.5 was knocked down, ~85% of the I Na+ was reduced consistent with the observations that Na V 1.5 is the main voltage‐gated sodium channel in cardiac muscle and that Na X likely does not directly participate in mediating the I Na+ following depolarization. Silencing Na V 1.5 expression led to significant upregulation of Na X mRNA. Similar to Na V 1.5, Na X protein levels were rapidly downregulated when the intracellular [Ca 2+ ] was increased either by CaCl 2 or caffeine. These data suggest that a relationship exists between Na X and Na V 1.5 and that Na X may play a role in excitation–contraction coupling.

Bogdanovic, Elena↗
DOE OSTI2025

Machine learning for arbitrary single-qubit rotations on an embedded device

Here, in this study, we present a technique for using machine learning (ML) for single-qubit gate synthesis on field-programmable logic for a superconducting transmon-based quantum computer based on simulated studies. Our approach is multi-stage. We first “bootstrap” a model based on simulation with access to the full state vector for measuring gate fidelity. We next present an algorithm, named adapted randomized benchmarking (ARB), for fine-tuning the gate on hardware based on measurements of the devices. We also present techniques for deploying the model on programmable devices with care to reduce the required resources. While the techniques here are applied to a transmon-based computer, many of them are portable to other architectures.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Life cycle analysis of hydrogen production via methane pyrolysis using plasma arc

Steam methane reforming of natural gas is the primary method of producing hydrogen in the United States, accounting for 95% of all hydrogen produced there. Methane pyrolysis, an alternative production pathway that decomposes natural gas into solid carbon and hydrogen, both eliminates CO 2 emissions associated with methane reforming and allows for additional income from carbon black. A life-cycle inventory of this process has been developed using ASPEN Plus to model the methane pyrolysis (plasma arc) process. From well to gate, hydrogen production via methane pyrolysis produces 2.78 kg CO 2 e/kg H 2 of greenhouse gas emissions using mass allocation of emissions between hydrogen and carbon black coproducts. The well-to-gate emissions are mainly driven by electricity consumption (∼38 kW h/kg H 2 ), which accounts for 81% of the emissions; if renewable electricity is used, well-to-gate emissions can be reduced to −0.448 kg CO 2 e/kg H 2 .

08 HYDROGEN↗
DOE OSTI2025

A time-parallel multiple-shooting method for large-scale quantum optimal control

Quantum optimal control plays a crucial role in quantum computing by providing the interface between compiler and hardware. Solving the optimal control problem is particularly challenging for multi-qubit gates, due to the exponential growth in computational complexity with the system's dimensionality and the deterioration of optimization convergence. To ameliorate the computational complexity of time-integration, this paper introduces a multiple-shooting approach in which the time domain is divided into multiple windows and the intermediate states at window boundaries are treated as additional optimization variables. Further, this enables parallel computation of state evolution across time-windows, significantly accelerating objective function and gradient evaluations. Since the initial state matrix in each window is only guaranteed to be unitary upon convergence of the optimization algorithm, the conventional gate trace infidelity is replaced by a generalized infidelity that is convex for non-unitary state matrices. Continuity of the state across window boundaries is enforced by equality constraints. A quadratic penalty optimization method is used to solve the constrained optimal control problem, and an efficient adjoint technique is employed to calculate the gradients in each iteration. We demonstrate the effectiveness of the proposed method through numerical experiments on quantum Fourier transform gates in systems with 2, 3, and 4 qubits, noting a speedup of 80x for evaluating the gradient in the 4-qubit case, highlighting the method's potential for optimizing control pulses in multi-qubit quantum systems.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Quantum Computing with Exciton Qubits in Colloidal Semiconductor Nanocrystals

The present work evaluates the feasibility of quantum computing with exciton qubits in coupled colloidal semiconductor nanocrystals (NCs). A strategy for manipulating two-qubit states of colloidal NC hetero-dimers is described. We show that a sequence of laser pulses with the same photon energy can bring excitonic states of a nanocrystal hetero-dimer into entanglement and perform arbitrary qubit rotations (quantum gates). Our simulations of a realistic two-particle assembly of CdSe/CdS core/shell NCs demonstrate that such two-qubit gate operations can be driven by optical parametric oscillators with a theoretical error of 0.1%. Furthermore, a strategy for upscaling two-qubit hetero-dimers to N-qubit exciton gates in semiconductor NC assemblies is discussed.

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

Distinguishing Potassium Channel Resting State Conformations in Live Cells with Environment-Sensitive Fluorescence

Ion channels are polymorphic membrane proteins whose high-resolution structures offer images of individual conformations, giving us starting points for identifying the complex and transient allosteric changes that give rise to channel physiology. Here, we report live-cell imaging of voltage-dependent structural changes of voltage-gated Kv2.1 channels using peptidyl tarantula toxins labeled with an environment-sensitive fluorophore, whose spectral shifts enable identification of voltage-dependent conformation changes in the resting voltage sensing domain (VSD) of the channel. We synthesize a new environment-sensitive, far-red fluorophore, julolidine phenoxazone (JP) azide, and conjugate it to tarantula toxin GxTX to characterize Kv2.1 VSD allostery during membrane depolarization. JP has an inherent response to the polarity of its immediate surroundings, offering site-specific structural insight into each channel conformation. Using voltage-clamp spectroscopy to collect emission spectra as a function of membrane potential, we find that they vary with toxin labeling site, the presence of Kv2 channels, and changes in membrane potential. With a high-affinity conjugate in which the fluorophore itself interacts closely with the channel, the emission shift midpoint is 50 mV more negative than the Kv2.1 gating current midpoint. This suggests that substantial conformational changes at the toxin-channel interface are associated with early gating charge transitions and these are not concerted with VSD motions at more depolarized potentials. These fluorescent probes enable study of conformational changes that can be correlated with electrophysiology, putting channel structures and models into a context of live-cell membranes and physiological states.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Electroluminescence from Single-Walled Carbon Nanotubes with Quantum Defects

Individual single-walled carbon nanotubes with covalent sidewall defects have emerged as a class of photon sources whose photoluminescence spectra can be tailored by the carbon nanotube chirality and the attached functional group/molecule. Here we present electroluminescence spectroscopy data from single-tube devices based on (7, 5) carbon nanotubes, functionalized with dichlorobenzene molecules, and wired to graphene electrodes. We observe electrically generated, defect-induced emissions that are controllable by electrostatic gating and strongly red-shifted compared to emissions from pristine nanotubes. The defect-induced emissions are assigned to excitonic and trionic recombination processes by correlating electroluminescence excitation maps with electrical transport and photoluminescence data. At cryogenic conditions, additional gate-dependent emission lines appear, which are assigned to phonon-assisted hot-exciton electroluminescence from quasi-levels. Similar results were obtained with functionalized (6, 5) nanotubes. We also compare functionalized (7, 5) electroluminescence data with photoluminescence of pristine and functionalized (7, 5) nanotubes redox-doped using gold(III) chloride solution. This work shows that electroluminescence excitation is selective toward neutral defect-state configurations with the lowest transition energy, which in combination with gate-control over neutral versus charged defect-state emission leads to high spectral purity.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Accumulation of Large Ion Populations with High Ion Densities and Effects Due to Space Charge in Traveling Wave-Based Structures for Lossless Ion Manipulations (SLIM) IMS-MS

The accumulation of very large ion populations in traveling wave (TW)-based Structures for Lossless ion Manipulations (SLIM) has been studied to better understand aspects of ‘in-SLIM’ ion accumulation, and particularly its use in conjunction with ion mobility spectrometry (IMS). A linear SLIM ion path was implemented that had a ‘gate’ for blocking and accumulating ions for arbitrary time periods. Removing the gate potential caused ions to exit and the spatial distributions of accumulated ions were examined. The ion populations for a set of peptides were observed to increase with increased accumulation times until space change effects became significant, after which the peptide precursor ion populations decreased due to growing space charge-related ion activation, reactions, and losses. Ions closest to the gate were preferentially activated, and increasingly so with added storage times, TW amplitude, and the size of the total ion population. For analytical applications, we found that relatively weak TWs in the accumulation/storage region should be utilized to prevent or minimize ion losses and/or ion heating effects that can also lead to fragmentation. Our results further indicate that an accumulation region close to the SLIM entrance is advantageous for both speeding accumulation, minimizing ion heating, and avoiding ion population profiles that result in IMS peak tailing. Importantly, space charge-driven separations were observed for large populations of accumulated species and attributed to the opposing effects of space charge and the TW. In these separations, ion species form distributions or peaks, sometimes moving against the TW, and ordered in the SLIM based on their mobilities. Such separations may offer utility for ion pre-fractionation of ions and increasing the dynamic range measurements, increasing the resolving power of IMS separations by decreasing peak widths for accumulated ion populations, and other purposes benefitting from separations of extremely large ion populations.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Lithium-ion electrolytic substrates for sub-1V high-performance transition metal dichalcogenide transistors and amplifiers

Electrostatic gating of two-dimensional (2D) materials with ionic liquids (ILs), leading to the accumulation of high surface charge carrier densities, has been often exploited in 2D devices. However, the intrinsic liquid nature of ILs, their sensitivity to humidity, and the stress induced in frozen liquids inhibit ILs from constituting an ideal platform for electrostatic gating. Here we report a lithium-ion solid electrolyte substrate, demonstrating its application in high-performance back-gated n-type MoS 2 and p-type WSe 2 transistors with sub-threshold values approaching the ideal limit of 60 mV/dec and complementary inverter amplifier gain of 34, the highest among comparable amplifiers. Remarkably, these outstanding values were obtained under 1 V power supply. Microscopic studies of the transistor channel using microwave impedance microscopy reveal a homogeneous channel formation, indicative of a smooth interface between the TMD and underlying electrolytic substrate. These results establish lithium-ion substrates as a promising alternative to ILs for advanced thin-film devices.

42 ENGINEERING↗
DOE OSTI2022

Generalization in quantum machine learning from few training data

Modern quantum machine learning (QML) methods involve variationally optimizing a parameterized quantum circuit on a training data set, and subsequently making predictions on a testing data set (i.e., generalizing). In this work, we provide a comprehensive study of generalization performance in QML after training on a limited number N of training data points. We show that the generalization error of a quantum machine learning model with T trainable gates scales at worst as $\sqrt{T/N}$. When only K$\ll$T gates have undergone substantial change in the optimization process, we prove that the generalization error improves to $\sqrt{K/N}$. Our results imply that the compiling of unitaries into a polynomial number of native gates, a crucial application for the quantum computing industry that typically uses exponential-size training data, can be sped up significantly. We also show that classification of quantum states across a phase transition with a quantum convolutional neural network requires only a very small training data set. Other potential applications include learning quantum error correcting codes or quantum dynamical simulation. Our work injects new hope into the field of QML, as good generalization is guaranteed from few training data.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Harmonic to anharmonic tuning of moiré potential leading to unconventional Stark effect and giant dipolar repulsion in WS 2 /WSe 2 heterobilayer

Excitonic states trapped in harmonic moiré wells of twisted heterobilayers is an intriguing testbed for exploring many-body physics. However, the moiré potential is primarily governed by the twist angle, and its dynamic tuning remains a challenge. Here we demonstrate anharmonic tuning of moiré potential in a WS 2 /WSe 2 heterobilayer through gate voltage and optical power. A gate voltage can result in a local in-plane perturbing field with odd parity around the high-symmetry points. This allows us to simultaneously observe the first (linear) and second (parabolic) order Stark shift for the ground state and first excited state, respectively, of the moiré trapped exciton - an effect opposite to conventional quantum-confined Stark shift. Depending on the degree of confinement, these excitons exhibit up to twenty-fold gate-tunability in the lifetime (100 to 5 ns). Also, exciton localization dependent dipolar repulsion leads to an optical power-induced blueshift of ~ 1 meV/μW - a five-fold enhancement over previous reports.

42 ENGINEERING↗
DOE OSTI2024

Dual receptor-sites reveal the structural basis for hyperactivation of sodium channels by poison-dart toxin batrachotoxin

The poison dart toxin batrachotoxin is exceptional for its high potency and toxicity, and for its multifaceted modification of the function of voltage-gated sodium channels. By using cryogenic electron microscopy, we identify two homologous, but nonidentical receptor sites that simultaneously bind two molecules of toxin, one at the interface between Domains I and IV, and the other at the interface between Domains III and IV of the cardiac sodium channel. Together, these two bound toxin molecules stabilize α/π helical conformation in the S6 segments that gate the pore, and one of the bound BTX-B molecules interacts with the crucial Lys1421 residue that is essential for sodium conductance and selectivity via an apparent water-bridged hydrogen bond. Overall, our structure provides insight into batrachotoxin’s potency, efficacy, and multifaceted functional effects on voltage-gated sodium channels via a dual receptor site mechanism.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Tomography of entangling two-qubit logic operations in exchange-coupled donor electron spin qubits

Scalable quantum processors require high-fidelity universal quantum logic operations in a manufacturable physical platform. Donors in silicon provide atomic size, excellent quantum coherence and compatibility with standard semiconductor processing, but no entanglement between donor-bound electron spins has been demonstrated to date. Here we present the experimental demonstration and tomography of universal one- and two-qubit gates in a system of two weakly exchange-coupled electrons, bound to single phosphorus donors introduced in silicon by ion implantation. We observe that the exchange interaction has no effect on the qubit coherence. We quantify the fidelity of the quantum operations using gate set tomography (GST), and we use the universal gate set to create entangled Bell states of the electrons spins, with fidelity 91.3 ± 3.0%, and concurrence 0.87 ± 0.05. These results form the necessary basis for scaling up donor-based quantum computers.

42 ENGINEERING↗
DOE OSTI2022

Demonstration of universal control between non-interacting qubits using the Quantum Zeno effect

The Zeno effect occurs in quantum systems when a very strong measurement is applied, which can alter the dynamics in non-trivial ways. Despite being dissipative, the dynamics stay coherent within any degenerate subspaces of the measurement. Here we show that such a measurement can turn a single-qubit operation into a two- or multi-qubit entangling gate, even in a non-interacting system. We demonstrate this gate between two effectively non-interacting transmon qubits. Our Zeno gate works by imparting a geometric phase on the system, conditioned on it lying within a particular non-local subspace. These results show how universality can be generated not only by coherent interactions as is typically employed in quantum information platforms, but also by Zeno measurements.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

High-fidelity trapped-ion qubit operations with scalable photonic modulators

Abstract Experiments with trapped ions and neutral atoms typically employ optical modulators in order to control the phase, frequency, and amplitude of light directed to individual atoms. These elements are expensive, bulky, consume substantial power, and often rely on free-space I/O channels, all of which pose scaling challenges. To support many-ion systems like trapped-ion quantum computers or miniaturized deployable devices like clocks and sensors, these elements must ultimately be microfabricated, ideally monolithically with the trap to avoid losses associated with optical coupling between physically separate components. In this work we design, fabricate, and test an optical modulator capable of monolithic integration with a surface-electrode ion trap. These devices consist of piezo-optomechanical photonic integrated circuits configured as multi-stage Mach-Zehnder modulators that are used to control the intensity of light delivered to a single trapped ion on a separate chip. We use quantum tomography employing hundreds of multi-gate sequences to enhance the sensitivity of the fidelity to the types and magnitudes of gate errors relevant to quantum computing and better characterize the performance of the modulators, ultimately measuring single qubit gate fidelities that exceed 99.7%.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Efficient sparse state preparation via quantum walks

Continuous-time quantum walks (CTQWs) on dynamic graphs, referred to as dynamic CTQWs, are a recently introduced universal model of computation that offers a new paradigm in which to envision quantum algorithms. In this work, we develop an algorithm that converts single-edge and self-loop dynamic CTQWs to the gate model of computation. We use this mapping to introduce an efficient sparse quantum state preparation framework based on dynamic CTQWs. Our approach utilizes combinatorics techniques such as minimal hitting sets, minimum spanning trees, and shortest Hamiltonian paths to reduce the number of controlled gates required to prepare sparse states. We show that our framework encompasses the current state of the art ancilla-free sparse state preparation method by reformulating this method as a CTQW. This CTQW-based framework offers an alternative to the uniformly controlled rotation method used by Qiskit by requiring fewer CX gates when the target state has a polynomial number of non-zero amplitudes.

dynamic continuous time quantum walks↗
DOE OSTI2026

Distributed quantum approximate optimization algorithm on a quantum-centric supercomputing architecture

Quantum approximate optimization algorithm (QAOA) has shown promise in solving combinatorial optimization problems by providing quantum speedup on near-term gate-based quantum computing systems. However, QAOA faces challenges for high-dimensional problems due to the large number of qubits required and the complexity of deep circuits, limiting its scalability for real-world applications. In this study, we present a distributed QAOA (DQAOA), which leverages distributed computing strategies to decompose a large computational workload into smaller tasks that require fewer qubits and shallower circuits than are necessary to solve the original problem. These sub-problems are processed using a combination of high-performance and quantum computing resources. The global solution is iteratively updated by aggregating sub-solutions, allowing convergence toward the optimal solution. We demonstrate that DQAOA can handle considerably large-scale optimization problems (e.g., 1000-bit problem), achieving a high solution quality and short time-to-solution, outperforming existing strategies. Furthermore, we realize DQAOA on a quantum-centric supercomputing architecture, paving the way for practical applications of gate-based quantum computers in real-world optimization tasks. To extend DQAOA’s applicability to materials science, we further develop an active learning algorithm integrated with our DQAOA (AL-DQAOA), which involves machine learning, DQAOA, and active data production in an iterative loop. We successfully optimize photonic structures using AL-DQAOA, indicating that solving real-world optimization problems using gate-based quantum computing is feasible. We expect the proposed DQAOA to be applicable to a wide range of optimization problems and AL-DQAOA to find broader applications in material design.

Kim, Seongmin [ORNL] (ORCID:0000000159063004)↗
DOE OSTI2020

Highly skewed current–phase relation in superconductor–topological insulator–superconductor Josephson junctions

Three-dimensional topological insulators (TIs) in proximity with superconductors are expected to exhibit exotic phenomena, such as topological superconductivity (TSC) and Majorana-bound states (MBS), which may have applications in topological quantum computation. In superconductor–TI–superconductor Josephson junctions, the supercurrent versus the phase difference between the superconductors, referred to as the current–phase relation (CPR), reveals important information including the nature of the superconducting transport. Here, we study the induced superconductivity in gate-tunable Josephson junctions (JJs) made from topological insulator BiSbTeSe 2 with superconducting Nb electrodes. We observe highly skewed (non-sinusoidal) CPR in these junctions. The critical current, or the magnitude of the CPR, increases with decreasing temperature down to the lowest accessible temperature ( T ~ 20 mK), revealing the existence of low-energy modes in our junctions. The gate dependence shows that close to the Dirac point the CPR becomes less skewed, indicating the transport is more diffusive, most likely due to the presence of electron/hole puddles and charge inhomogeneity. Our experiments provide strong evidence that superconductivity is induced in the highly ballistic topological surface states (TSS) in our gate-tunable TI-based JJs. Furthermore, the measured CPR is in good agreement with the prediction of a model which calculates the phase-dependent eigenstate energies in our system, considering the finite width of the electrodes, as well as the TSS wave functions extending over the entire circumference of the TI.

36 MATERIALS SCIENCE↗