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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 1,729 records · Page 96
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Experimental investigation of laser ablation of stone polycrystalline targets

We report the results of an experimental investigation of ablation of stone polycrystalline targets of complex multicomponent composition, which imitate the substance of asteroids. The targets were irradiated by nanosecond pulses of a neodymium laser at an energy density Φ{sub L} of up to 5 × 10{sup 4} J cm{sup −2}. The experiments demonstrated the existence of two ablation regimes, with the boundary between them lying at Φ{sub L} ≈ 4000 J cm{sup −2}. The regime change is characterised by a change in the form of the dependence of the surface mass density of removed target material on the laser energy density and by the appearance of a minimum in the dependence of specific energy of destruction on Φ{sub L}. This is supposedly related to the passage from a one-dimensional plasma plume expansion to the three-dimensional one and the corresponding decrease in the efficiency of energy transfer from the laser beam to the target due to a lowering of laser-produced plasma density. Our experiments also showed the existence of a maximum in impulse coupling coefficient C{sub m} as a function of laser energy density (C{sub m} ≈ 6.3 × 10{sup −5} N W{sup −1} for Φ{sub L} = Φ{sub opt} ≈ 25 J cm{sup −2}). Maxima were also recorded in the dependences of the ablation efficiency and average ablation flow velocity on Φ{sub L}. For Φ{sub L} > Φ{sub opt}, the decrease in the function C{sub m}(Φ{sub L}) turns out to be much steeper than for metals and polymer materials. The difference is supposedly due to the lower strength and lower plasticity of the polycrystalline stone targets. (paper)

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Probing the Kitaev honeycomb model on a neutral-atom quantum computer

Quantum simulations of many-body systems are among the most promising applications of quantum computers. In particular, models based on strongly correlated fermions are central to our understanding of quantum chemistry and materials problems, and can lead to exotic, topological phases of matter. However, owing to the non-local nature of fermions, such models are challenging to simulate with qubit devices. Here we realize a digital quantum simulation architecture for two-dimensional fermionic systems based on reconfigurable atom arrays. We utilize a fermion-to-qubit mapping based on Kitaev’s model on a honeycomb lattice, in which fermionic statistics are encoded using long-range entangled states. We prepare these states efficiently using measurement and feedforward, realize subsequent fermionic evolution through Floquet engineering with tunable entangling gates interspersed with atom rearrangement, and improve results with built-in error detection. Leveraging this fermion description of the Kitaev spin model, we efficiently prepare topological states across its complex phase diagram and verify the non-Abelian spin-liquid phase by evaluating an odd Chern number. We further explore this two-dimensional fermion system by realizing tunable dynamics and directly probing fermion exchange statistics. Finally, we simulate strong interactions and study the dynamics of the Fermi–Hubbard model on a square lattice. These results pave the way for digital quantum simulations of complex fermionic systems for materials science, chemistry and high-energy physics.

atomic and molecular physics↗
DOE OSTI2020

Acousto-optic modulators of high-power laser radiation on the basis of KGW and KYW crystals

Different modifications of acousto-optic modulators (AOMs) based on KG(WO{sub 4}){sub 2} (KGW) and KY(WO{sub 4}){sub 2} (KYW) crystals, designed for Q switching of high-power pulsed lasers, is developed and investigated. It is shown that AOMs based on these crystals are universal, can be combined with different lasers in the wavelength range of 1 – 3 μm, and have a high radiation resistance in the absence of antireflection coatings and light input at Brewster’s angle. The operation efficiency of KGW-based AOMs is experimentally demonstrated. Solid-state lasers based on Cr : Er : YSGG (λ = 2.78 μm), Cr : Yb : Ho : YSGG (λ = 2.87 μm), Cr : Tm : Ho : YSGG (λ = 2.09 μm), and Nd : YAG (λ = 1.064 μm) crystals with active acousto-optic Q switching, operating in the repetitively pulsed regime with a high beam quality and without surface destruction, are investigated. Lasing pulses (30 – 60)-ns long with energy up to 32 mJ at a repetition rate from 1 to 1000 Hz are obtained. (paper)

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Solar Spectrum Conversion for an Algae Bioreactor (CRADA Final Report)

This project focused on developing advanced optical coatings to improve solar energy utilization. The research aimed to create lanthanide-doped upconversion nanoparticles (UCNPs) capable of capturing unused near-infrared (NIR) light from the sun and converting it into visible light (blue and red photons) that can be used for photosynthesis. The primary goal was to identify, synthesize, and integrate highly efficient UCNPs into a transparent thin-film device. Through a comprehensive workflow involving computer simulations, high-throughput robotic synthesis, and detailed optical characterization, the project successfully developed a high-performance material. The key technical achievement was the creation of a core-shell UCNP (NaYF₄:20%Yb³⁺, 2%Er³⁺ coated with a 10 nm NaYF₄ shell) that demonstrated a quantum yield of 3.2% for converting 980 nm NIR light into visible light. Transparent thin films fabricated from these nanoparticles showed excellent optical properties, confirming their potential for practical applications. This research adds to the scientific understanding of energy transfer in lanthanide materials and demonstrates a technically effective method for creating efficient light-converting coatings. The primary benefit to the public lies in the potential for these coatings to enhance the efficiency of solar-driven processes, such as boosting the growth of algae in photobioreactors for biofuel production.

14 SOLAR ENERGY↗
DOE OSTI2022

Solving nuclear structure problems with the adaptive variational quantum algorithm

Here we use the Lipkin-Meshkov-Glick (LMG) model and the valence-space nuclear shell model to examine the likely performance of variational quantum eigensolvers in nuclear-structure theory. The LMG model exhibits both a phase transition and spontaneous symmetry breaking at the mean-field level in one of the phases, features that characterize collective dynamics in medium-mass and heavy nuclei. We show that with appropriate modifications, the ADAPT-VQE algorithm, a particularly flexible and accurate variational approach, is not troubled by these complications. We treat up to 12 particles and show that the number of quantum operations needed to approach the ground-state energy scales linearly with the number of qubits. We find similar scaling when the algorithm is applied to the nuclear shell model with realistic interactions in the sd and pf shells. Although most of these simulations contain no noise, we use a noise model from real IBM hardware to show that for the LMG model with four particles, weak noise has no effect on the efficiency of the algorithm.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Ligand Control of Structural Diversity in Luminescent Hybrid Copper(I) Iodides

Copper(I) iodide hybrids are of interest for next-generation lighting technologies because of their efficient luminescence in the absence of rare-earth elements. Here, we report 10 structurally diverse hybrid copper(I) iodides that emit in the green–red region with quantum yields reaching 67%. The compounds display a diversity of structures including ones with one-dimensional (1D) Cu–1 chains, Cu 2 I 2 rhomboid dimers, and structures with two different arrangements of Cu 4 I 4 tetramers. The compounds with Cu 2 I 2 rhomboid dimers or Cu 4 I 4 cubane tetramers have higher photoluminescence quantum yields than those with Cu–I 1D chains and octahedral Cu 4 I 4 tetramers, owing to the optimal degree of condensation of the inorganic motifs, which suppresses nonradiative processes. Electronic structure calculations on these compounds point out the critical influence of the inorganic motif and organic ligand on the nature of the band gaps and thus the excitation characteristics. Temperature-dependent photoluminescence spectra are presented to better understand the nature of luminescence in compounds with different inorganic motifs. Here. the emerging understanding of composition–structure–property correlations in this family provides inspiration for the rational design of hybrid phosphors for general lighting applications.

36 MATERIALS SCIENCE↗
DOE OSTI2020

A framework for quantitative analysis of spectral data in two channels

Simultaneous acquisition of emission intensity from two channels in dual-color fluorescence measurements can be used to determine the spectral properties of an emitter. We detail a method to extract quantitative information from dual-color measurements by considering two models: a single spectral component model for peak wavelength determination and a dual spectral component model for relative strength determination. The former model is useful for spectral characterization and establishing heterogeneity within an emitter species, while the latter model is useful for analyzing energy transfer efficiency. Both models are formalized to yield probability distributions that reflect uncertainties due to shot noise. We applied these analysis tools to single-particle measurements of CdSe/CdS quantum dots. Isolated emitters had narrow spectral-intensity distributions that reflected their static emission profiles and fluorescence stability. Small assemblies of mixed donor/acceptor particles exhibited dynamic behavior where emission configuration changes reveal different spectral characteristics due to energy transfer.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Stabilization of magnetic bubbles in [Ni/Co]n multilayers on an oxygen-reconstructed Nb(110) surface via an ultra-thin Cu interlayer

Magnetic thin films hosting topological spin textures, such as magnetic skyrmions, hold high potential for breakthroughs in the field of spintronics, due to good scalability and energy efficiency. Novel computational architectures such as memory-in-logic devices rely on material platforms able to host those topological spin textures. Furthermore, recently proposed designs of novel quantum information technologies are based on heterostructures where topological spin textures are in direct proximity to a superconducting layer. Here, we demonstrate the stabilization of out-of-plane magnetic bubbles in highly ordered [Ni/Co]n multilayers on a Nb(110) single crystal. This is achieved without the need for the removal of the well-known Nb(110)-oxide surface reconstruction, due to the introduction of an ultra-thin Cu interlayer in between the Nb substrate and the magnetic multilayer. The Cu interlayer generates a well-ordered hexagonal surface, which is key for the epitaxial growth of the [Ni/Co]n multilayers hosting the desired out-of-plane anisotropy. The magnetic ground state of the prepared material stacks is directly imaged via spin-polarized low-energy electron microscopy, revealing the presence of magnetic bubble domains with lateral sizes as small as 450 nm.

Dibajeh, Ahmad↗
DOE OSTI2021

Dynamic properties of a polaron coupled to dispersive optical phonons

We study static and dynamic properties of an electron coupled to dispersive quantum optical phonons in the framework of the Holstein model defined on a one-dimensional lattice. Calculations are performed using the Lanczos algorithm based on a highly efficient construction of the variational Hilbert space. Even small phonon dispersion has a profound effect on the low-energy optical response. While the upward phonon dispersion broadens the optical spectra due to single-phonon excitations, the downward dispersion has the opposite effect. With increasing dispersion, a multiphonon excitation (MPE) state becomes the lowest excited state of the system at zero momentum and determines the low-frequency response of the optical conductivity where the threshold for optical absorption moves below the single-phonon frequency. Multiphonon states form a well-defined bandlike feature just above the polaron band as clearly seen in the electron spectral function. Low-energy MPEs should be observable in systems with strong optical phonon dispersion in optical as well as angle-resolved photoemission experiments.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Biochemical Process Modeling and Simulation (BPMS)

The Biochemical Process Modeling and Simulation project aims to reduce the cost and time of research by applying theory, modeling, and simulation to the most relevant bottlenecks in the biochemical process. We use molecular modeling, quantum mechanics, metabolic modeling, fluid dynamics, and reaction-diffusion methods in close collaboration with pretreatment, hydrolysis, upgrading, and TEA. The project's outcomes are increased yields and efficiency of the biochemical process, added value to products, and reduced price of fuels by specifically targeting catalytic efficiency, reactor design, enzyme efficiency, and microbial design. We work closely with experimental projects to identify problems and iterate with experiments to find and refine solutions. By working with experimentalists, we decide on problems that can be solved with simulation that could otherwise not be solved or would take too long with experiment alone to reach BETO's targets. Over the years, we have produced solutions that have resulted in determining the most likely fatty-acid derivative for passive transport out of bacteria that upgrade biomass, and we have also designed enzyme mutations for enhanced lignin upgrading. Metabolic models have been developed to tune the activity of 2,3 butanediol production for the 2030 target. A computational method to deliver understanding of how complex omics data can be interpreted in the metabolic pathways of organisms used in the Agile Biofoundry. We have found methods to overcome specific barriers and continue to develop those methods. Our reactor studies have guided the design of both the microbes and reactors for aerobic and micro-aerobic production at all scales and have been instrumental in improving the accuracy of techno-economic analysis models. This project is essential in the process of selecting the final processes for 2030 SAF production targets. More specifically, recently, we have: 1) Predicted the strength of the basic structural interactions in commodity plastics to provide guidance for plastics upcycling strategies. 2) Developed computational tool to improve the characterization of lignin-derived compounds 3) Developed new methodologies to enable Machine Learning-based Directed Evolution for protein engineering. 4) Developed Machine Learning methods to predict protein promiscuity and mutations to further improve microbial and enzymatic driven processes and demonstrated the utility of ML approaches to engineering proteins from sparse experimental datasets. 5) Developed new methods to enable high-fidelity simulation of aerobic fermentation at industrial scale and resolving mismatch of time scales through subcycling/operator splitting 7) Identified the difficulty in preventing local high-oxygen conditions in industrial bubble columns, which leads to less-desirable acetoin production, suggesting future research directions in alternative reactor configurations (e.g loop reactors, shallow-channel reactors).

BIOMASS FUELS↗
DOE OSTI2021

QBTNs - Quantum Boolean Tensor Networks

We develop algorithms and software that uses the D-Wave 2000Q quantum annealer to solve several types of Boolean tensor factorization problems. Boolean tensor factorization refers to the problem of representing a high-dimensional tensor filled with Boolean values as a product of smaller Boolean core tensors and Boolean matrices. We consider different tensor factorization models, including Boolean Tensor Train, Boolean Tucker, and Boolean Hierarchical Tucker. As an exact decomposition of a given type may not exist in the general case, the objective is to minimize the difference between the input high-dimensional tensor and the product of the lower-dimensional tensors of the proposed factorization, using a specified tensor norm. In our approach, we reduce the Boolean tensor factorization problem to a sequence of quadratic unconstrained binary optimization problems suitable for the D-Wave 2000Q quantum annealer. Although current quantum technology is still fairly restricted in the problems it can tackle, we show that complex tensor factorization problems as the ones addressed by us can be solved efficiently and accurately.

Alexandrov, Boian↗
DOE OSTI2025

Classical Preoptimization Approach for ADAPT-VQE: Maximizing the Potential of High-Performance Computing Resources to Improve Quantum Simulation of Chemical Applications

The ADAPT-VQE algorithm is a promising method for generating a compact ansatz based on derivatives of the underlying cost function, and it yields accurate predictions of electronic energies for molecules. In this work, we report the implementation and performance of ADAPT-VQE with our recently developed sparse wave function circuit solver (SWCS) in terms of accuracy and efficiency for molecular systems with up to 52 spin orbitals. The SWCS can be tuned to balance computational cost and accuracy, which extends the application of ADAPT-VQE for molecular electronic structure calculations to larger basis sets and a larger number of qubits. Using this tunable feature of the SWCS, we propose an alternative optimization procedure for ADAPT-VQE to reduce the computational cost of the optimization. Furthermore, by preoptimizing a quantum simulation with a parametrized ansatz generated with ADAPT-VQE/SWCS, we aim to utilize the power of classical high-performance computing in order to minimize the work required on noisy intermediate-scale quantum hardware, which offers a promising path toward demonstrating quantum advantage for chemical applications.

ADAPT-VQE↗
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 OSTI2023

Quantum-enhanced Imaging and Spectroscopy and their Relevance to International Safeguards

As a follow-up to our previous report on quantum sensing for safeguards, here we delve deeper into quantum-enhanced imaging & spectroscopy and address their relevance to international safeguards. Much of the approaches rely on entangled photons, a quantum phenomenon not possible with classical physics, although just correlated photons will work for some applications, such as ghost imaging. We provide a comprehensive survey of quantum approaches, including multiple entangled photon ghost imaging and spectroscopy techniques. Entangled photons for noise reduction are also described, as well as Non-Line-Of-Sight imaging, compressive techniques, and squeezed light. Of particular interest is the generation of entangled photons with large wavelength separation, such as infrared/visible entangled photon pairs. Such entangled pairs would allow interaction with objects in the IR, such as in the molecular “fingerprint” wavelength region, while the recording device captures the visible photons, thus leveraging the high efficiency and lower cost of visible detectors. Unfortunately, entangled x-ray photons are not practical, which would have been useful for safeguards to interrogate shielded materials. Entangled gamma rays are even further beyond reason. We provide our assessment for application of quantum-enhanced imaging & spectroscopy for international safeguards, including suggested improvements to existing IAEA instruments and destructive assay measurements that are done at IAEA lab facilities.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Data from: "Colonisation of the alpine tundra by trees: alpine neighbours assist late-seral but not early-seral conifer seedlings"

This archive contains data used to support conclusions made in “Colonisation of the alpine tundra by trees: alpine neighbours assist late-seral but not early-seral conifer seedlings”, by Jabis et al., 2020. Data were collected in the alpine field location of the Alpine Treeline Warming Experiment (ATWE), on Niwot Ridge, in the Front Range of the Colorado Rocky Mountains, USA.This package includes survivorship and physiology data for limber pine (Pinus flexilis), Engelmann spruce (Picea engelmannii), and Rocky Mountain snowlover (Chionophila jamesii). Site climate data such as soil moisture and temperature are also included. This data package contains ten comma-separated-values (.csv) files, and two rich-text-format (.rtf) files all compressed within one folder named “Neighbor_data_repository.zip”. Both file types can be opened by text-edit softwares such as TextEdit (Mac) and Notepad (Windows). The files are also compatible with analyses softwares such as R. .csv files can also be opened by Microsoft Excel. Two geospatial datasets are also included in this archive: one keyhole markup language (.kml) file with four points marking the corners of the study site, and a compressed file containing two ESRI shapefiles (.shp). The .kml files can be opened with Google Earth or Google Maps, and the shapefiles can be opened using any geographic information system applications, including the entire ArcGIS suite, and QGIS. -------------------------------------------------------------------------------------------------------------------------------------------------------The elevation mountain treeline is expected to shift upward with climate warming, and seed germination and seedling survival are critical local controls on treeline expansion. Neighboring alpine plants, either through competition for resources or through altering the microclimate, can also affect seedling emergence and survival. We asked whether establishing tree seedlings and an alpine herb are similarly sensitive to alpine plant neighbours under ambient and altered climate. We imposed active heating, watering, and neighbor removal experiments for emerging conifer seedlings and an alpine herb.We compared target plant survival, photosynthetic efficiency, and water use efficiency under ambient and experimental conditions. Picea engelmannii seedlings showed lower survival compared with Pinus flexilis three weeks following neighbour removal, and after 1 year only survived in watered plots. Pinus seedlings responded to neighbour removal by lowering the quantum yield of photosynthesis (ϕPSII). Contrary to expectations from the stress gradient hypothesis, survival was reduced without neighbours near the low-elevation range limit of Chionophila jamesii.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Single-hole physics in GaAs/AlGaAs double quantum dot system with strong spin–orbit interaction

There is rapidly expanding interest in exploiting the spin of valence-band holes rather than conduction-band electrons for spin qubit semiconductor circuits composed of coupled quantum dots. The hole platform offers stronger spin–orbit interaction (SOI), large difference between in-dot-plane and out-of-dot-plane g-factors, i.e. g-factor anisotropy, and a significantly reduced hyperfine coupling to nuclei in the host material. These attributes collectively can deliver fast all-electric coherent spin manipulation, efficient spin-flip inter-dot tunneling channels, a voltage tunable effective g-factor, a g-factor adjustable to nearly zero in an appropriately oriented external magnetic field, and long spin relaxation and coherence times. In this work, we review our recent work on the physics of heavy holes confined in a planar GaAs/AlGaAs double quantum dot system with strong SOI. For a single-hole, we have performed resonant tunneling magneto-spectroscopy to extract spin-flip and spin-conserving tunneling strengths, implemented spin-flip Landau–Zener–Stückelberg–Majorana (LZSM) interferometry, determined the spin relaxation time T 1 as a function of magnetic field using a fast single-shot latched charge technique, electrically tuned the effective g-factor revealed by electric dipole spin resonance, and found signatures of the hyperfine interaction and dynamic nuclear polarization with holes. For two-holes, we have measured the energy spectrum in the presence of strong SOI (and so not limited by Pauli spin blockade), quantified the heavy-hole (HH) g-factor anisotropy on tilting the magnetic field, described a scheme to employ HHs whose g-factor is tunable to nearly zero for an in-plane magnetic field for a coherent photon-to-spin interface, and observed a well-defined LZSM interference pattern at small magnetic fields on pulsing through the singlet-triplet anti-crossing.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2025

Factorization Machine‐Based Active Learning for Functional Materials Design with Optimal Initial Data

The optimization of functional materials is important to enhance their properties, but their complex geometries pose great challenges to optimization. Data-driven algorithms efficiently navigate such complex design spaces by learning relationships between material structures and performance metrics to discover high-performance functional materials. Surrogate-based active learning, continually improving its surrogate model by iteratively including high-quality data points, has emerged as a cost-effective data-driven approach. Furthermore, it can be coupled with quantum computing to enhance optimization processes, especially when paired with a special form of surrogate model (i.e., quadratic unconstrained binary optimization), formulated by factorization machine (FM). However, current practices often overlook the variability in design space sizes when determining the initial data size for optimization. In this work, we investigate the optimal initial data sizes required for efficient convergence across various design space sizes. By employing averaged piecewise linear regression, we identify initiation points where convergence begins, highlighting the crucial role of employing adequate initial data in achieving efficient optimization. These results contribute to the efficient optimization of functional materials by ensuring faster convergence and reducing computational costs in FM-based active learning.

active learning↗
DOE OSTI2021

Leading-color two-loop QCD corrections for three-jet production at hadron colliders

We present the complete set of leading-color two-loop contributions required to obtain next-to-next-to-leading-order (NNLO) QCD corrections to three-jet production at hadron colliders. We obtain analytic expressions for a generating set of finite remainders, valid in the physical region for three-jet production. The analytic continuation of the known Euclidean-region results is determined from a small set of numerical evaluations of the amplitudes. We obtain analytic expressions that are suitable for phenomenological applications and we present a C++ library for their efficient and stable numerical evaluation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗