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At least 721 records · Page 40
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Cold ion beam in a storage ring as a platform for large-scale quantum computers and simulators: Challenges and directions for research and development

The purpose of this paper is to evaluate the possibility of constructing a large-scale storage-ring-type ion-trap system capable of storing, cooling, and controlling a large number of ions as a platform for scalable quantum computing (QC) and quantum simulations. In such a trap, the ions form a crystalline beam moving along a circular path with a constant velocity determined by the frequency and intensity of the cooling lasers. In this paper, we consider a large leap forward in terms of the number of ions that serve as qubits in QC, from fewer than 100 available in state of the art linear ion-trap devices today to an order of 10 5 crystallized ions in the storage-ring setup. This new trap design unifies two different concepts: the storage rings of charged particles and the linear ion traps used for QC and mass spectrometry. In this paper, we use the language of particle accelerators to discuss the ion state and dynamics. We outline the differences between the above concepts, analyze challenges of the large ring with a revolving chain of ions, and propose goals for the research and development required to enable future quantum computers with 1000 times more qubits than available today. The challenge of creating such a large-scale quantum system while maintaining the necessary coherence of the qubits and the high fidelity of quantum logic operations is significant. Performing analog quantum simulations may be an achievable initial goal for such a device. Quantum calculations and simulations of complex quantum systems will move forward both the fundamental science and the applied research. Nuclear and particle physics, many-body quantum systems, lattice gauge theories, and nuclear structure calculations are just a few examples in which a large-scale quantum simulation system will become a very powerful tool to move forward our understanding of nature.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Leveraging Randomized Compiling for the QITE Algorithm

The success of the current generation of Noisy Intermediate-Scale Quantum (NISQ) hardware shows that quantum hardware may be able to tackle complex problems even without error correction. One outstanding issue is that of coherent errors arising from the increased complexity of these devices. These errors can accumulate through a circuit, making their impact on algorithms hard to predict and mitigate. Iterative algorithms like Quantum Imaginary Time Evolution are susceptible to these errors. This article presents the combination of both noise tailoring using Randomized Compiling and error mitigation with a purification. We also show that Cycle Benchmarking gives an estimate of the reliability of the purification. We apply this method to the Quantum Imaginary Time Evolution of a Transverse Field Ising Model and report an energy estimation and a ground state infidelity both below 1\%. Our methodology is general and can be used for other algorithms and platforms. We show how combining noise tailoring and error mitigation will push forward the performance of NISQ devices.

Ville, Jean-Loup↗
DOE OSTI2025

Growth and characterization of high-quality Zr doped AlN epilayers

AlN stands out for its remarkable figures of merit for electronic and photonic devices, attributed to its ultrawide bandgap of ∼6.1 eV and an exceptionally high critical field of ∼15 MV/cm. More recently, zirconium (Zr) doped AlN (AlN:Zr) has also been identified as a promising material platform for the exploration of solid-state qubits for quantum information and technology, high performance piezoelectric acoustic wave resonators, and optically triggered ultrafast power switching devices facilitated by optically activating Zr related impurities. Despite the significant potential, the ability for producing AlN:Zr epitaxial structures has yet to be established. In this study, we have achieved AlN:Zr epilayers with a high Zr doping level [NZr] of up to 1020 cm−3 using industrial standard metal-organic chemical vapor deposition growth technique. High crystalline quality of AlN:Zr was confirmed by x-ray diffraction, revealing a narrow full width at half maximum of the (002) rocking curve at 216 arcsec for 1.8 μm thick epilayers deposited on sapphire at [NZr]=1020 cm−3. Zr doping was observed to slightly increase the c-lattice constant to 4.992 Å for AlN:Zr (at [NZr]=1020 cm−3) compared to 4.980 Å for undoped AlN. X-ray photoelectron spectroscopy measurement results verified the substitution of Zr at the Al site (ZrAl). The formation of (ZrAl–VN) complexes, which are predicted to possess all the desired properties required by quantum qubits, was confirmed through optical absorption studies. The realization of high-quality AlN:Zr epilayers significantly broadens the scope of technologically significant device applications for AlN.

36 MATERIALS SCIENCE↗
DOE OSTI2022

OLEDs on planarized light outcoupling-enhancing structures in plastic

Light extraction from OLEDs remains a challenge. While consumer demand for OLEDs in display technology continues to grow as prices decline, commercial use of OLEDs in solid state lighting (SSL) applications is lagging due to low light extraction, which results in low efficiency. Previous studies have been directed toward increasing the light extraction factor η out , but cost effective approaches that will enable high throughput and potential upscaling, as well as elucidation of the extraction process, are still lagging. One promising approach is the use of buried light extraction enhancing patterns that are planarized with a high refractive index (RI) layer. When adding substrate mode extracting means, the highest external quantum efficiencies (EQEs) were achieved using a complex approach of planarized vacuum nano holes. Here we present η out -enhancing planarized extraction structures (PES) in plastic. While plastic substrates currently present long-term stability issues and other drawbacks, as we show, they provide a tool for simple, inexpensive, and rapid generation of various enhancing structures that importantly can be transferred to the preferred rigid and flexible glass substrates. Moreover, plastic substrates are attractive for biomedical applications. The successful structures we present are easily scalable periodic corrugations, e.g., with pitch a ~ 4.25 µm and pitch/depth ratio a/h ~2.4 planarized by a layer of RI ~1.9, resulting in maximal EQEs exceeding 60% for a green OLED and 48.5% for a white OLED. Comparable increased EQEs were achieved for structures with a ~ 15 and 16 µm, and a/h ~ 2.1 and 4, respectively. Enhanced extraction was also observed with a very simply fabricated quasiperiodic nanohole array, and surprisingly, with a random shallow design. The latter is at variance with simulations based on diffraction only. Results are discussed in terms of a, h, and structural parameters together with scattering matrix simulations to assess the effect of various PES parameters and the nanoparticle-embedded planarizing layer on η out . The experiments and simulations indicate contributions of diffraction, reflection, and scattering to EQE enhancement.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Constant Overhead Entanglement Distillation via Scrambling

High-fidelity quantum entanglement enables key quantum networking capabilities such as secure communication and distributed quantum computing, but long-distance entanglement distribution is limited by noise and loss. Entanglement distillation protocols address this problem by extracting high-fidelity Bell pairs from multiple noisy ones. The primary objective is minimizing the resource overhead: the number of noisy input pairs needed to distill each high-fidelity output pair. While protocols achieving optimal overhead are known in theory, they often require complex decoding operations that make practical implementation challenging. We circumvent this challenge by introducing protocols that use quantum scrambling—the spreading of quantum information under chaotic dynamics—through random Clifford operations. Based on this scrambling mechanism, our protocol maintains asymptotically constant overhead, independent of the desired output error rate $\bar{𝜖}$ , and can be implemented with shallow quantum circuits of depth 𝑂⁡(poly log log⁡ $\bar{𝜖}$ −1 ) and memory 𝑂⁡(poly log⁡ $\bar{𝜖}$ −1 ). Our protocol remains effective even with noisy quantum gates. By incorporating error correction, our protocol achieves state-of-the-art performance: starting with pairs of 10% initial infidelity, we require only seven noisy inputs per output pair to distill a single Bell pair with infidelity $\bar{𝜖}$ =10 −12 , substantially outperforming existing schemes. We demonstrate the utility of our protocols for quantum repeater networks.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Efficient Monte Carlo event generation for neutrino-nucleus exclusive cross sections

Modern neutrino-nucleus cross section computations need to incorporate sophisticated nuclear models to achieve greater predictive precision. However, the computational complexity of these advanced models often limits their practicality for experimental analyses. To address this challenge, we introduce a new Monte Carlo method utilizing normalizing flows to generate surrogate cross sections that closely approximate those of the original model while significantly reducing computational overhead. As a case study, we built a Monte Carlo event generator for the neutrino-nucleus cross section model developed by the Ghent group. This model employs a Hartree-Fock procedure to establish a quantum mechanical framework in which both the bound and scattering nucleon states are solutions to the mean-field nuclear potential. The surrogate cross sections generated by our method demonstrate excellent accuracy with a relative effective sample size of more than 98.4%, providing a computationally efficient alternative to traditional Monte Carlo sampling methods for differential cross sections.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Electron Sextets as Optically Addressable Molecular Qubits: Triplet Carbenes

There is a growing demand in quantum information science and sensing for electron spin purification and readout via a spin-optical interface. This technique, known as optically detected magnetic resonance (ODMR), has been applied to diamond-NV centers and transition-metal complexes. Metal-free counterparts of these optically addressable spin qubits promise to be cheaper, more sustainable color centers with prolonged polarization lifetimes. However, progress has been hindered by the low ODMR signals of carbon-based π-diradicals, partly due to the lack of a ground singlet-to-triplet intersystem crossing (ISC). In this work, we propose exploring organic systems that are even more electron-deficient: electron sextets. Using triplet carbenes as an example, we illustrate how the ground singlet-triplet gap can be widened beyond thermal energy with the associated singlet-to-triplet ISC made available by vibronic effects. Through careful molecular engineering, this ISC can occur at a rate similar to and with an opposite spin selectivity from the excited-state ISC well-established in π-diradicals, unlocking a new ODMR pathway with potential signal gains. Persistent triplet carbenes are a renascent field, with multiple stable molecules being isolated in the past five years. To motivate further development of its emissive properties, we illustrate our design in three realistic carbene candidates that incorporate existing strategies for carbene stabilization. Furthermore, we believe that a new realm of quantum materials can be uncovered by expanding our scope toward stable electron sextets.

Carbene compounds↗
DOE OSTI2025

Discovering nuclear models from symbolic machine learning

Numerous phenomenological nuclear models have been proposed to describe specific observables within different regions of the nuclear chart. However, developing a unified model that describes the complex behavior of all nuclei remains an open challenge. Here, we explore whether symbolic Machine Learning (ML) can rediscover traditional nuclear physics models or identify alternatives with improved simplicity, fidelity, and predictive power. To address this challenge, we developed a Multi-objective Iterated Symbolic Regression approach that handles symbolic regressions over multiple target observables, accounts for experimental uncertainties and is robust against high-dimensional problems. As a proof of principle, we applied this method to describe the nuclear binding energies and charge radii of light and medium mass nuclei. Our approach identified simple analytical relationships based on the number of protons and neutrons, providing interpretable models with precision comparable to state-of-the-art nuclear models. Additionally, we integrated this ML-discovered model with an existing complementary model to estimate the limits of nuclear stability. These results highlight the potential of symbolic ML to develop accurate nuclear models and guide our description of complex many-body problems.

Nuclear structure↗
DOE OSTI2021

Large-Scale, GPU-Enhanced DFTB Approaches for Probing Multi-Component Alloys

The major goals of the project are to develop and apply GPU-enhanced density functional theory tight binding (DFTB) calculations for efficient simulations of structural materials of alloy systems. The figure below depicts the GPU algorithmic developments on the left that will be carried out, and the solid-state structures on the right are representative of the complex alloys that can be computed with the GPU-enhanced DFTB approach. The methodology and tools developed in this project encompass accurate intermolecular potentials and GPU enhancements to the density functional tight binding (DFTB) approach for high-throughput ab initio molecular dynamics calculations of multi-component alloys at elevated temperatures. While classical molecular dynamics can handle hundreds of thousands of atoms, it cannot provide a first-principles based description of large, multi-component alloys at the predictive quantum level. At the other extreme, conventional Kohn-Sham DFT methods can probe the true quantum nature of chemical systems; however, these methods cannot tackle the large sizes relevant to these multi-component systems. The DFTB-based ab initio molecular dynamics approach (coupled with our in-house GPU capabilities for enhanced speed) used in this project provides a viable approach for probing these large systems at a quantum level of detail that is significantly faster than current first-principle methods Collectively, the capabilities developed in this project directly respond to DOE HBCU-OMI, AOI 2-1 initiatives by (1) enabling accurate and efficient predictions and (2) bringing a fundamental understanding of structural interactions in these complex systems at elevated temperatures.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2025

Reactions of Np(VI) and Pu(VI) with Phenanthroline Result in Bending the [NpVIO2]2+ Unit and a Reduced Pu(V) Species

Despite decades of actinyl chemistry, genuinely bent actinyl structures remain rare beyond uranium. We report the first crystallographic characterization of a bent neptunyl(VI) complex, NpO 2 Cl 2 (phen) 2, along with a linear plutonyl species that, unexpectedly, adopts the +V oxidation state. Coordination of two 1,10-phenanthroline ligands to NpO 2 2+ enforces pronounced bending of the O yl –Np–O yl unit to 162° through steric clashes with the axial phenathroline ligand, representing the sharpest angle reported for any neptunyl(VI) complex. In contrast, synthesis with PuO 2 2+ produces a reduced linear Pu(V) species, PuO 2 Cl(phen) 2, underscoring the redox lability and the reluctance of plutonium to distort. Raman and IR spectra yield the first experimental stretching and interaction force constants for plutonyl(V). Comparison with values for plutonyl(VI) and bent and linear uranyl(VI) and neptunyl(VI) compounds shows that reduction perturbs the actinyl bond more than bending within one oxidation state. Electrochemical and spectroscopic studies clarify phenanthroline binding to Pu(VI) and the system’s reactivity. Quantum chemical calculations indicate that bending is energetically favored in the U–Np–Pu series, but the stabilization energy decreases as the actinide atomic number increases. NBO and QTAIM analyses reveal systematic trends: increasing 5f occupancy and decreasing An–O yl bond covalency from U to Pu. These results demonstrate that ligand-induced bending in neptunyl(VI) species is not only electronically feasible but also synthetically achievable, though plutonyl(VI) is constrained by redox reactivity. This work expands the frontier of nonlinear actinyl chemistry and illuminates how structure, oxidation state, and electronic configuration interrelate across the actinyl series.

actinides↗
DOE OSTI2025

Quantum graph learning and algorithms applied in quantum computer sciences and image classification

Graph and network theory play a fundamental role in quantum computer sciences, including quantum information and computation. Random graphs and complex network theory are pivotal in predicting novel quantum phenomena, where entangled links are represented by edges. Quantum algorithms have been developed to enhance solutions for various network problems, giving rise to quantum graph computing and quantum graph learning (QGL). Here, in this review, we explore graph theory and graph learning methods as powerful tools for quantum computers to generate efficient solutions to problems beyond the reach of classical systems. We delve into the development of quantum complex network theory and its applications in quantum computation, materials discovery, and research. We also discuss quantum machine learning (QML) methodologies for effective image classification using qubits, quantum gates, and quantum circuits. Additionally, the paper addresses the challenges of QGL and algorithms, emphasizing the steps needed to develop flexible QGL solvers. This review presents a comprehensive overview of the fields of QGL and QML, highlights recent advancements, and identifies opportunities for future research.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Sustainable chemistry with plasmonic photocatalysts

There is a pressing global need to increase the use of renewable energy sources and limit greenhouse gas emissions. Towards this goal, highly efficient and molecularly selective chemical processes that operate under mild conditions are critical. Plasmonic photocatalysis uses optically resonant metallic nanoparticles and their resulting plasmonic, electronic, and phononic light-matter interactions to drive chemical reactions. The promise of simultaneous high-efficiency and product-selective reactions with plasmon photocatalysis provides a compelling opportunity to rethink how chemistry is achieved. Plasmonic nanoparticles serve as nanoscale ‘antennas’ that enable strong light–matter interactions, surpassing the light-harvesting capabilities one would expect purely from their size. Complex composite structures, combining engineered light harvesters with more chemically active components, are a focal point of current research endeavors. In this review, we provide an overview of recent advances in plasmonic catalysis. We start with a discussion of the relevant mechanisms in photochemical transformations and explain hot-carrier generation and distributions from several ubiquitous plasmonic antennae. Then we highlight three important types of catalytic processes for sustainable chemistry: ammonia synthesis, hydrogen production and CO 2 reduction. To help elucidate the reaction mechanism, both state-of-art electromagnetic calculations and quantum mechanistic calculations are discussed. This review provides insights to better understand the mechanism of plasmonic photocatalysis with a variety of metallic and composite nanostructures toward designing and controlling improved platforms for green chemistry in the future.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

CdSe Magic-Size Clusters Deviate from Nanocrystal-Size Scalings for Ultrafast Intraband Relaxation and Auger Recombination

The cluster regime of colloidal semiconductor quantum dots (QDs) occupies an interesting space on the continuum from molecule to bulk material and allow the study of QD properties at extreme quantum confinement limits. For typical QDs, several size-dependent property trends are well established including intraband relaxation rates and universal scaling of Auger recombination with particle volume. Advances in synthesis now allow isolation of atomically precise semiconductor magic-size clusters (MCs), which offer experimental insight regarding how electronic structure changes with particle size in the ultrasmall limit. Here, we report intraband cooling and Auger recombination for several stable CdSe MCs as a function of particle size and observe deviation from QD response in the cluster regime. We additionally show optical signatures ascribed to transient disordering 2 that appear in the single exciton regime for MCs, which point to complexities regarding their implementation.

Auger recombination↗
DOE OSTI2026

Chiral anomalies and Wilson fermions

The Wilson formulation of fermions in lattice gauge theory provides a unified description of the chiral anomalies in the standard model. The discrete Dirac operator diagonalizes into a series of 2 × 2 blocks. In each block the possible eigenvalues either form a complex pair or separate into two real eigenvalues that have specific chirality. The collision of these pairs of eigenvalues occurs outside the perturbative region and provides a path between topological sectors.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Durability of plasma sprayed Thermal Barrier Coatings with controlled properties part Ⅱ: Effects of geometrical curvature

The present investigation elucidates the effects of substrate curvature on the durability of Air Plasma Sprayed (APS) Thermal Barrier Coatings (TBCs). Traditionally, planar disk specimens are utilized in Furnace Cycle Testing (FCT). In most cases, delamination is initiated at the disk's free edge and then propagates along the TBC-bond coat interface. However, in turbine components (e.g., blades/vanes), they lack significant free edges and the coatings are deposited on non-flat surfaces of varying radii of curvature. These geometrical discrepancies imply significant differences in the stress states as compared to planar disk specimens. Therefore, the part geometry inevitably affects the TBC failure mechanisms in the turbine system, and consequently influences TBC durability. Nevertheless, these effects have not been fully explored in the past, despite the anecdotal knowledge which suggests the leading edge of turbine blades to be one of the most common failure/spallation locations. Here in this study, representative TBC systems were deposited onto superalloy disks with flat substrate and rods with curved substrate. The experimental results from FCT suggest TBC durability on rods is significantly lower than when sprayed on disks. Furthermore, the durability of TBCs on rods appears to increase with higher porosity, which is contradictory to reported trends for TBCs on disks. In addition, the effects of various bond coats are not consistent with those observed in disks. To clarify the underlying effects of curved geometries, detailed stress analyses were performed. They revealed a state of thermal stresses which is unique to curved geometries. It was found that TBC on rods experience tensile radial stresses as well as tensile hoop stresses during the cooling. These stresses result in a complex interplay in failure processes in rods, which explains the different observed trends in the durability from those obtained with disks.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Spin-flop-like transition as quantum critical point in Cs2⁢RuO4

We report thermodynamic, neutron diffraction, and inelastic neutron scattering measurements on Cs2⁢RuO4, a member of the celebrated family of frustrated magnets Cs2⁢𝑀⁢𝑋4 (𝑀 = Cu, Co, 𝑋 = Br, Cl). Unlike the previously studied members, it is based on 4⁢𝑑 transition metal ions with 𝑆=1. Mapping out the 𝐻−𝑇 magnetic phase diagram reveals an unusual continuous spin-flop-like phase transition associated with a quantum critical point within the antiferromagnetically ordered phase. A quantitative analysis of the complex magnetic excitation spectrum measured in zero field allows us to derive a model magnetic Hamiltonian for this compound. Its main feature is a frustration of magnetic anisotropy on a level that is much higher than in any of the previously studied species. This frustration naturally explains the peculiar phase transition observed.

Nabi, S [Laboratory for Solid State Physics, ETH Z↗
DOE OSTI2022

Majorana modes with side features in magnet-superconductor hybrid systems

Magnet-superconductor hybrid (MSH) systems represent promising platforms to host Majorana zero modes (MZMs), the elemental building blocks for fault-tolerant quantum computers. Theoretical description of such MSH structures is mostly based on simplified models, not accounting for the complexity of real materials. Here, based on density functional theory, we derive a superconducting 80-band model to study an MSH system consisting of a magnetic manganese chain on the s wave superconductor niobium. For a wide range of values of the superconducting order parameter, the system is a topological superconductor, with MZMs exhibiting non-universal spatial patterns and a drastic accumulation of spectral weight on both sides along the magnetic chain. These side feature states can be explained by an effective model which is guided by the ab initio results. Performing scanning tunneling spectroscopy experiments on the same system, we observe a spatial structure in the low-energy local density of states that is consistent with the theoretical findings. Our results open a first-principle approach to the discovery of topological superconductors.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Skyrmion-like Spin Textures Emerging in the Material Derived from Structural Frustration

Magnetic materials with complex spin textures present both fundamental and practical appeal. The complex patterns of magnetic moments emerging on underlying crystal lattices hold potential for robust information storage and processing, including the promise of topological quantum computing. The scope of materials that host such patterns, however, remains rather limited. Here, in this study, we report a discovery of a complex spin texture in a noncentrosymmetric material that emerges from the structural frustration at the boundary between centrosymmetric parent structures MnCoGe (the hexagonal Ni 2 In or the orthorhombic TiNiSi structure type) and MnCoAs (the TiNiSi structure type). Our findings demonstrate that such structural frustration provides a powerful handle for identifying compositional spaces where complex magnetic behavior and associated nontrivial magnetic structures are likely to emerge. Thus, the new phase MnCoGe 1/3 As 2/3 exhibits a modulated cycloidal antiferromagnetic arrangement of electron spins on a noncentrosymmetric lattice (of the hexagonal ZrNiAl type) that materializes in the space between centrosymmetric collinear ferromagnets. This work provides a pathway for discovering novel materials with exotic spin textures for next-generation spintronics and quantum technologies.

Wang, YiXu [Florida State University, Tallahassee,↗