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At least 1,459 records · Page 81
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Slow magnetic relaxation in a europium(II) complex

Single-ion anisotropy is vital for the observation of Single-Molecule Magnet (SMM) properties (i.e., a slow dynamics of the magnetization) in lanthanide-based systems. In the case of europium, the occurrence of this phenomenon has been inhibited by the spin and orbital quantum numbers that give way to J = 0 in the trivalent state and the half-filled population of the 4f orbitals in the divalent state. Herein, by optimizing the local crystal field of a quasi-linear bis(silylamido) Eu II complex, the [Eu II (N{SiMePh 2 } 2 ) 2 ] SMM is described, providing an example of a europium complex exhibiting slow relaxation of its magnetization. This behavior is dominated by a thermally activated (Orbach-like) mechanism, with an effective energy barrier of approximately 8 K, determined by bulk magnetometry and electron paramagnetic resonance. Ab initio calculations confirm second-order spin-orbit coupling effects lead to non-negligible axial magnetic anisotropy, splitting the ground state multiplet into four Kramers doublets, thereby allowing for the observation of an Orbach-like relaxation at low temperatures.

36 MATERIALS SCIENCE↗
DOE OSTI2023

The role of electron correlations in the electronic structure of putative Chern magnet TbMn6Sn6

Abstract A member of the RMn 6 Sn 6 rare-earth family materials, TbMn 6 Sn 6 , recently showed experimental signatures of the realization of a quantum-limit Chern magnet. In this work, we use quantum Monte Carlo (QMC) and density functional theory with Hubbard U (DFT + U ) calculations to examine the electronic structure of TbMn 6 Sn 6 . To do so, we optimize accurate, correlation-consistent pseudopotentials for Tb and Sn using coupled-cluster and configuration–interaction (CI) methods. We find that DFT + U and single-reference QMC calculations suffer from the same overestimation of the magnetic moments as meta-GGA and hybrid density functional approximations. Our findings point to the need for improved orbitals/wavefunctions for this class of materials, such as natural orbitals from CI, or for the inclusion of multi-reference effects that capture the static correlations for an accurate prediction of magnetic properties. DFT + U with Mn magnetic moments adjusted to the experiment predict the Dirac crossing in bulk to be close to the Fermi level, within ~120 meV, in agreement with the experiments. Our non-stoichiometric slab calculations show that the Dirac crossing approaches even closer to the Fermi level, suggesting the possible realization of Chern magnetism in this limit.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Low-temperature synthesis of all-inorganic perovskite nanocrystals for UV-photodetectors

Controllable synthesis of tin-doped all-inorganic perovskite (e.g. CsPb 1-X Sn X Br 3 ) nanocrystals while maintaining tin at the divalent state is of great importance for tuning their optoelectronic properties by changing the chemical composition and geometrical size; however, this remains a non-negligible challenge. In contrast to the conventional high-temperature (>150 °C) synthesis reaction that would more likely facilitate oxidation of divalent Sn 2+ to quadrivalent Sn 4+ , this work demonstrates a facile low-temperature (105–150 °C) hot-injection method to synthesize quantum-confined Sn 2+ -doped CsPb 1-X Sn X Br 3 nanocrystals with sizes ranging from ~6.2 nm to ~8.3 nm depending on the reaction temperature. The optimized reaction temperature of 135 °C led to a Sn 2+ -doping ratio of 3.4% in CsPb 1-X Sn X Br 3 nanocrystals which exhibited uniform nanoplatelets with an average lateral size of ~7.4 nm. Furthermore, for the first time, we show that the perovskite nanocrystals are promising for the development of low-cost and trap-assisted photomultiplication UV-photodetectors, and the photodetectors based on CsPb 0.966 Sn 0.034 Br 3 nanocrystals exhibited wavelength-dependent detectivities in the magnitude of 1011 Jones for UV light extending from 310 nm to 400 nm at a reverse bias of -7 V. Finally, the high EQE of ~1940% at around 340 nm indicates that the devices had a gain at the large reverse bias condition, which is attributed to the formation of interfacial traps by CsPb 0.966 Sn 0.034 Br 3 nanocrystals that can make the electron injection barrier thin enough to allow electron tunneling in the photodetectors for photomultiplication.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Soft X-ray spectroscopy with transition-edge sensors at Stanford Synchrotron Radiation Lightsource beamline 10-1

We present results obtained with a new soft X-ray spectrometer based on transition-edge sensors (TESs) composed of Mo/Cu bilayers coupled to bismuth absorbers. This spectrometer simultaneously provides excellent energy resolution, high detection efficiency, and broadband spectral coverage. The new spectrometer is optimized for incident X-ray energies below 2 keV. Each pixel serves as both a highly sensitive calorimeter and an X-ray absorber with near unity quantum efficiency. We have commissioned this 240-pixel TES spectrometer at the Stanford Synchrotron Radiation Lightsource beamline 10-1 (BL 10-1) and used it to probe the local electronic structure of sample materials with unprecedented sensitivity in the soft X-ray regime. As mounted, the TES spectrometer has a maximum detection solid angle of 2 × 10 –3 sr. The energy resolution of all pixels combined is 1.5 eV full width at half maximum at 500 eV. We describe the performance of the TES spectrometer in terms of its energy resolution and count-rate capability and demonstrate its utility as a high throughput detector for synchrotron-based X-ray spectroscopy. Here, the results from initial X-ray emission spectroscopy and resonant inelastic X-ray scattering experiments obtained with the spectrometer are presented.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Quantum stabilization and flat hydrogen-based bands of nitrogen-doped lutetium hydride

We explore the electronic and structural properties of Lu-H-N structures with specific N,H ordering due to their remarkably narrow hydrogen-based bands at the Fermi level. Although exhibits a classical instability persisting up to 17 GPa, it is anharmonically stable near ambient pressure when accounting for quantum nuclear effects. The presence of flat bands near is understood to arise from destructive quantum interference between and surrounding orbitals, with certain types of defects leaving the flat bands unaffected. The results suggest that if this system is superconducting, there is an optimal pressure near ambient where the superconducting is maximized by anharmonically stabilized low-frequency and nonadiabatically coupled high-frequency hydrogen modes. Despite the metastability of this structure, its dynamical stability when modeled beyond a classical harmonic approach suggests the narrow bands near do not cause structural distortions in certain Lu-H-N stoichiometries.

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

Quantum simulations of nuclear resonances with variational methods

Background: The many-body nature of nuclear physics problems poses significant computational challenges. These challenges become even more pronounced when studying the resonance states of nuclear systems, which are governed by the non-Hermitian Hamiltonian. Quantum computing, particularly for quantum many-body systems, offers a promising alternative, especially within the constraints of current noisy intermediate-scale quantum (NISQ) devices. Purpose: This work aims to simulate nuclear resonances using quantum algorithms by developing a variational framework compatible with non-Hermitian Hamiltonians and implementing it fully on a quantum simulator. Methods: We employ the complex scaling technique to extract resonance positions classically and adapt it for quantum simulations using a two-step algorithm. First, we transform the non-Hermitian Hamiltonian into a Hermitian form by using the energy variance as a cost function within a variational framework. Second, we perform 𝜃-trajectory calculations to determine optimal resonance positions in the complex energy plane. To address resource constraints on NISQ devices, we utilize Gray code (GC) encoding to reduce qubit requirements. Results: We first validate our approach using a schematic potential model that mimics a nuclear potential, successfully reproducing known resonance energies with high fidelity. We then extend the method to a more realistic 𝛼−𝛼 nuclear potential and compute the 𝐷- and 𝐺-wave resonance energies with a basis size of 𝑁=16, using only four qubits. The quantum simulation results closely match the classical values, demonstrating the feasibility of our approach. Conclusions: This study demonstrates, for the first time, that the complete 𝜃-trajectory method can be implemented on a quantum computer without relying on any classical input beyond the Hamiltonian. The results establish a scalable and efficient quantum framework for simulating resonance phenomena in nuclear systems. This work represents a significant step toward quantum simulations of open quantum systems and lays the foundation for future investigations into resonance structures in nuclear, atomic, and molecular physics.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Inference, Prediction, & Entropy-Rate Estimation of Continuous-Time, Discrete-Event Processes

Inferring models, predicting the future, and estimating the entropy rate of discrete-time, discrete-event processes is well-worn ground. However, a much broader class of discrete-event processes operates in continuous-time. Here, we provide new methods for inferring, predicting, and estimating them. The methods rely on an extension of Bayesian structural inference that takes advantage of neural network’s universal approximation power. Based on experiments with complex synthetic data, the methods are competitive with the state-of-the-art for prediction and entropy-rate estimation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS1990

Resonant tunneling IR detectors

Researchers propose a novel semiconductor heterojunction photodetector which would have a very low dark current and would be voltage tunable. A schematic diagram of the device and its band structure are shown. The two crucial components of the device are a cathode (InGaAs) whose condition band edge is below the conduction band edge of the quantum wells and a resonant tunneling filter (GaAs-AlGaAs). In a standard resonant tunneling device the electrodes are made of the same material as the quantum wells, and this device becomes highly conducting when the quantum levels in the wells are aligned with the Fermi level in the negatively biased electrode. In contrast, the researchers device is essentially non-conducting under the same bias conditions. This is because the Fermi Level of the cathode (InGaAs) is still well below the quantum levels so that no resonant transport occurs and the barriers (AlGaAs) effectively block current flow through the device. However, if light with the same photon energy as the conduction-band discontinuity between the cathode and the quantum wells, E sub c3-E sub c1, is shone on the sample, free carriers will be excited to an energy corresponding to the lowest quantum level in the well closest to the cathode (hv plue E sub c1 = E sub o). These electrons will resonantly tunnel through the quantum wells and be collected as a photocurrent in the anode (GaAs). To improve the quantum efficiency, the cathode (InGaAs) should be very heavily doped and capped with a highly reflective metal ohmic contact. The thickness of the device should be tailored to optimize thin film interference effects and afford the maximum absorption of light. Because the device relies on resonant tunneling, its response should be very fast, and the small voltages needed to change the responsivity should allow for very high frequency modulation of the photocurrent. In addition, the device is tuned to a specific photon energy so that it can be designed to detect a fairly narrow range of wavelengths. This selectivity is important for reducing the photocurrent due to spurious light sources.

Woodall, Jerry M.↗
NASA NTRS2004

Application of Simulated Annealing and Related Algorithms to TWTA Design

Simulated Annealing (SA) is a stochastic optimization algorithm used to search for global minima in complex design surfaces where exhaustive searches are not computationally feasible. The algorithm is derived by simulating the annealing process, whereby a solid is heated to a liquid state and then cooled slowly to reach thermodynamic equilibrium at each temperature. The idea is that atoms in the solid continually bond and re-bond at various quantum energy levels, and with sufficient cooling time they will rearrange at the minimum energy state to form a perfect crystal. The distribution of energy levels is given by the Boltzmann distribution: as temperature drops, the probability of the presence of high-energy bonds decreases. In searching for an optimal design, local minima and discontinuities are often present in a design surface. SA presents a distinct advantage over other optimization algorithms in its ability to escape from these local minima. Just as high-energy atomic configurations are visited in the actual annealing process in order to eventually reach the minimum energy state, in SA highly non-optimal configurations are visited in order to find otherwise inaccessible global minima. The SA algorithm produces a Markov chain of points in the design space at each temperature, with a monotonically decreasing temperature. A random point is started upon, and the objective function is evaluated at that point. A stochastic perturbation is then made to the parameters of the point to arrive at a proposed new point in the design space, at which the objection function is evaluated as well. If the change in objective function values (Delta)E is negative, the proposed new point is accepted. If (Delta)E is positive, the proposed new point is accepted according to the Metropolis criterion: rho((Delta)f) = exp((-Delta)E/T), where T is the temperature for the current Markov chain. The process then repeats for the remainder of the Markov chain, after which the temperature is decremented and the process repeats. Eventually (and hopefully), a near-globally optimal solution is attained as T approaches zero. Several exciting variants of SA have recently emerged, including Discrete-State Simulated Annealing (DSSA) and Simulated Tempering (ST). The DSSA algorithm takes the thermodynamic analogy one step further by categorizing objective function evaluations into discrete states. In doing so, many of the case-specific problems associated with fine-tuning the SA algorithm can be avoided; for example, theoretical approximations for the initial and final temperature can be derived independently of the case. In this manner, DSSA provides a scheme that is more robust with respect to widely differing design surfaces. ST differs from SA in that the temperature T becomes an additional random variable in the optimization. The system is also kept in equilibrium as the temperature changes, as opposed to the system being driven out of equilibrium as temperature changes in SA. ST is designed to overcome obstacles in design surfaces where numerous local minima are separated by high barriers. These algorithms are incorporated into the optimal design of the traveling-wave tube amplifier (TWTA). The area under scrutiny is the collector, in which it would be ideal to use negative potential to decelerate the spent electron beam to zero kinetic energy just as it reaches the collector surface. In reality this is not plausible due to a number of physical limitations, including repulsion and differing levels of kinetic energy among individual electrons. Instead, the collector is designed with multiple stages depressed below ground potential. The design of this multiple-stage collector is the optimization problem of interest. One remaining problem in SA and DSSA is the difficulty in determining when equilibrium has been reached so that the current Markov chain can be terminated. It has been suggested in recent literature that simulating the thermodynamic properties opecific heat, entropy, and internal energy from the Boltzmann distribution can provide good indicators of having reached equilibrium at a certain temperature. These properties are tested for their efficacy and implemented in SA and DSSA code with respect to TWTA collector optimization.

Radke, Eric M.↗
DOE OSTI2025

3D-printed micro ion trap technology for quantum information applications

Trapped-ion applications, such as in quantum information processing1, precision measurements, optical clocks and mass spectrometry, rely on specialized high-performance ion traps. The last three of these applications typically use traditional machining to customize macroscopic 3D Paul traps, whereas quantum information processing experiments usually rely on photolithographic techniques to miniaturize the traps and meet scalability requirements. Using photolithography, however, it is challenging to fabricate the complex 3D electrode structures required for optimal confinement. Here, in this work, we demonstrate a high-resolution 3D printing technology based on two-photon polymerization (2PP) that is capable of fabricating large arrays of high-performance miniaturized 3D traps. We show that 3D-printed ion traps combine the advantages, such as strong radial confinement, of traditionally machined 3D traps with on-chip miniaturization. We trap calcium ions in 3D-printed ion traps with radial trap frequencies ranging from 2 MHz to 24 MHz. The tight confinement eases ion cooling requirements and allows us to implement high-quality Rabi oscillations with Doppler cooling only. Also, we demonstrate a two-qubit gate with a Bell-state fidelity of 0.978 ± 0.012. With 3D printing technology, the design freedom is greatly expanded without sacrificing scalability and precision, so that ion trap geometries can be optimized for higher performance and better functionality.

quantum information↗
DOE OSTI2021

Quantum process tomography of a Mølmer-Sørensen gate via a global beam

Here, we present a framework for quantum process tomography of two-ion interactions that leverages modulations of the trapping potential and composite pulses from a global laser beam to achieve individual-ion addressing. Tomographic analysis of identity and delay processes reveals dominant error contributions from laser decoherence and slow qubit frequency drift during the tomography experiment. We use this framework on two co-trapped 40 Ca + ions to analyze both an optimized and an overpowered Mølmer–Sørensen gate and to compare the results of this analysis to a less informative Bell-state tomography measurement and to predictions based on a simplified noise model. These results show that the technique is effective for the characterization of two-ion quantum processes and for the extraction of meaningful information about the errors present in the system. The experimental convenience of this method will allow for more widespread use of process tomography for characterizing entangling gates in trapped-ion systems.

quantum computing↗
DOE OSTI2019

Color optimization of red OLEDs via periodic and gradient deposition rate of fluorescent dopants

We have investigated a method to enhance the light emission efficiency and color tuning for mixture of dyes with varying the growth parameters, during Alq{sub 3}:Nile Red deposition. We used solvent bath and green laser (532 nm) for improvement of the performance of devices. This paper presents two kind of evaporation method, periodic and gradient. We observed that periodic emission layers can greatly improve the device performances such as electroluminescence, chromaticity coordinates, luminance, and reduced the turn on voltage. The periodic 3 structure with evaporation rate of (0.1 → 3 → 2 → 3 → 2 → 0.1 A°/s) has a luminance of 3000 cd/m{sup 2} and maximum efficiency of 1.8 cd/A at 18 V which are the highest values among devices.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Analytical gradients for molecular-orbital-based machine learning

We report molecular-orbital-based machine learning (MOB-ML) enables the prediction of accurate correlation energies at the cost of obtaining molecular orbitals. Here, we present the derivation, implementation, and numerical demonstration of MOB-ML analytical nuclear gradients, which are formulated in a general Lagrangian framework to enforce orthogonality, localization, and Brillouin constraints on the molecular orbitals. The MOB-ML gradient framework is general with respect to the regression technique (e.g., Gaussian process regression or neural networks) and the MOB feature design. We show that MOB-ML gradients are highly accurate compared to other ML methods on the ISO17 dataset while only being trained on energies for hundreds of molecules compared to energies and gradients for hundreds of thousands of molecules for the other ML methods. The MOB-ML gradients are also shown to yield accurate optimized structures at a computational cost for the gradient evaluation that is comparable to a density-corrected density functional theory calculation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Surf-Deformer: Mitigating Dynamic Defects on Surface Code via Adaptive Deformation

In this paper, we introduce Surf-Deformer, a code deformation framework that seamlessly integrates adaptive defect mitigation functionality into the current surface code workflow. It crafts several basic deformation instructions based on fundamental gauge transformations, which can be combined to explore a larger design space than previous methods. This enables more optimized deformation processes tailored to specific defect situations, restoring the QEC capability of deformed codes more efficiently with minimal qubit resources. Additionally, we design an adaptive code layout that accommodates our defect mitigation strategy while ensuring efficient execution of logical operations. Our evaluation shows that Surf-Deformer outperforms previous methods by significantly reducing the end-to-end failure rate of various quantum programs by 35× to 70×, while requiring only about 50% of the qubit resources compared to the previous method to achieve the same level of failure rate. Ablation studies show that Surf-Deformer surpasses previous defect removal methods in preserving QEC capability and facilitates surface code communication by achieving nearly optimal throughput.

Yin, Keyi↗
DOE OSTI2020

PANNA: Properties from Artificial Neural Network Architectures

We report prediction of material properties from first principles is often a computationally expensive task. Recently, artificial neural networks and other machine learning approaches have been successfully employed to obtain accurate models at a low computational cost by leveraging existing example data. Here, we present a software package “Properties from Artificial Neural Network Architectures” (PANNA) that provides a comprehensive toolkit for creating neural network models for atomistic systems following the Behler–Parrinello topology. Besides the core routines for neural network training, it includes data parser, descriptor builder for Behler–Parrinello class of symmetry functions and force-field generator suitable for integration within molecular dynamics packages. PANNA offers a variety of activation and cost functions, regularization methods, as well as the possibility of using fully-connected networks with custom size for each atomic species. PANNA benefits from the optimization and hardware-flexibility of the underlying TensorFlow engine which allows it to be used on multiple CPU/GPU/TPU systems, making it possible to develop and optimize neural network models based on large datasets.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

A numerical analysis of a magnetocaloric refrigerator with a 16-layer regenerator

A numerical analysis was conducted to study a room temperature magnetocaloric refrigerator with a 16-layer parallel plates active magnetic regenerator (AMR). Sixteen layers of LaFeMnSiH having different Curie temperatures were employed as magnetocaloric material (MCM) in the regenerator. Measured properties data was used. A transient one dimensional (1D) model was employed, in which a unique numerical method was developed to significantly accelerate the simulation speed of the multi-layer AMR system. As a result, the computation speed of a multi-layer AMR case was very close to the single-layer configuration. The performance of the 16-layer AMR system in different frequencies and utilizations has been investigated using this model. To optimize the layer length distribution of the 16-layer MCMs in the regenerator, a set of 137 simulations with different MCM distributions based on the Design of Experiments (DoE) method was conducted and the results were analyzed. The results show that the 16-layer AMR system can operate up to 84% of Carnot cycle COP at a temperature span of 41 K, which cannot be obtained using an AMR with fewer layers. Here, the DoE results indicate that for a 16-layer AMR system, the uniform distribution is very close to the optimized design.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Characterization of Low Gain Avalanche Detector Prototypes’ Response to Gamma Radiation

Motivated by the need for fast timing detectors to withstand up to 2 MGy of ionizing dose at the High Luminosity Large Hadron Collider, prototype low gain avalanche detectors (LGADs) have been fabricated in a single pad configuration, 2 × 2 arrays, and related p-i-n diodes, and exposed to Co-60 sources for study. Devices were fabricated with a range of dopant layer concentrations, and for the arrays, a variety of inter-pad distances and distances from the active area to the edge. Measurements of capacitance versus voltage and leakage current versus voltage have been made to compare pre- and post-irradiation characteristics in gain layer depletion voltage, full bulk depletion voltage, and breakdown voltage. Conclusions are drawn regarding the effects of the gammas on both surface and interface states and on their contribution to acceptor removal through non-ionizing energy loss from Compton electrons or photoelectrons. Comparison of the performances of members of the set of devices can be used to optimize gain layer parameters.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

The Global Optimization of Pt{sub 13} Cluster Using the First-Principle Molecular Dynamics with the Quenching Technique

The high-temperature first-principle molecular dynamics method used to obtain the low energy configurations of clusters [L. L. Wang and D. D. Johnson, PRB 75, 235405 (2007)] is extended to a considerably large temperature range by combination with the quenching technique. Our results show that there are strong correlations between the possibilities for obtaining the ground-state structure and the temperatures. Larger possibilities can be obtained at relatively low temperatures (as corresponds to the pre-melting temperature range). Details of the structural correlation with the temperature are investigated by taking the Pt{sub 13} cluster as an example, which suggests a quite efficient method to obtain the lowest-energy geometries of metal clusters.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗