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

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Quantum adiabatic machine learning by zooming into a region of the energy surface

Recent work has shown that quantum annealing for machine learning, referred to as QAML, can perform comparably to state-of-the-art machine learning methods with a specific application to Higgs boson classification. Here, we propose QAML-Z, an algorithm that iteratively zooms in on a region of the energy surface by mapping the problem to a continuous space and sequentially applying quantum annealing to an augmented set of weak classifiers. Results on a programmable quantum annealer show that QAML-Z matches classical deep neural network performance at small training set sizes and reduces the performance margin between QAML and classical deep neural networks by almost 50% at large training set sizes, as measured by area under the receiver operating characteristic curve. The significant improvement of quantum annealing algorithms for machine learning and the use of a discrete quantum algorithm on a continuous optimization problem both opens a class of problems that can be solved by quantum annealers and suggests the approach in performance of near-term quantum machine learning towards classical benchmarks.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Scaling adaptive quantum simulation algorithms via operator pool tiling

Adaptive variational quantum simulation algorithms use information from a quantum computer to dynamically create optimal trial wave functions for a given problem Hamiltonian. A key ingredient in these algorithms is a predefined operator pool from which trial wave functions are constructed. Finding suitable pools is critical for the efficiency of the algorithm as the problem size increases. Here, we present a technique called operator pool tiling that facilitates the construction of problem-tailored pools for arbitrarily large problem instances. By first performing an Adaptive Derivative-Assembled Problem-Tailored Ansatz Variational Quantum Eigensolver (ADAPT-VQE) calculation on a smaller instance of the problem using a large, but computationally inefficient, operator pool, we extract the most relevant operators and use them to design more efficient pools for larger instances. We demonstrate the method here on strongly correlated quantum spin models in one and two dimensions, finding that ADAPT automatically finds a highly effective ansatz for these systems. Given that many problems, such as those arising in condensed matter physics, have a naturally repeating lattice structure, we expect the pool tiling method to be a widely applicable technique apt for such systems. Published by the American Physical Society 2024

Van Dyke, John S. (ORCID:0000000167815480)↗
DOE OSTI2020

Decentralized Schemes with Overlap for Solving Graph-Structured Optimization Problems

We present a new algorithmic paradigm for the decentralized solution of graph-structured optimization problems that arise in the estimation and control of network systems. A key and novel design concept of the proposed approach is that it uses overlapping subdomains to promote and accelerate convergence. We show that the algorithm converges if the size of the overlap is sufficiently large and that the convergence rate improves exponentially with the size of the overlap. The proposed approach provides a bridge between fully decentralized and centralized architectures and is flexible in that it enables the implementation of asynchronous schemes, handling of constraints, and balancing of computing, communication, and data privacy needs. The proposed scheme is tested in an estimation problem for a 9241-node power network and we show that it outperforms the alternating direction method of multipliers.

asynchronous↗
DOE OSTI2016

SU-F-J-86: Method to Include Tissue Dose Response Effect in Deformable Image Registration

Purpose: Organ changes shape and size during radiation treatment due to both mechanical stress and radiation dose response. However, the dose response induced deformation has not been considered in conventional deformable image registration (DIR). A novel DIR approach is proposed to include both tissue elasticity and radiation dose induced organ deformation. Methods: Assuming that organ sub-volume shrinkage was proportional to the radiation dose induced cell killing/absorption, the dose induced organ volume change was simulated applying virtual temperature on each sub-volume. Hence, both stress and heterogeneity temperature induced organ deformation. Thermal stress finite element method with organ surface boundary condition was used to solve deformation. Initial boundary correspondence on organ surface was created from conventional DIR. Boundary condition was updated by an iterative optimization scheme to minimize elastic deformation energy. The registration was validated on a numerical phantom. Treatment dose was constructed applying both the conventional DIR and the proposed method using daily CBCT image obtained from HN treatment. Results: Phantom study showed 2.7% maximal discrepancy with respect to the actual displacement. Compared with conventional DIR, subvolume displacement difference in a right parotid had the mean±SD (Min, Max) to be 1.1±0.9(−0.4∼4.8), −0.1±0.9(−2.9∼2.4) and −0.1±0.9(−3.4∼1.9)mm in RL/PA/SI directions respectively. Mean parotid dose and V30 constructed including the dose response induced shrinkage were 6.3% and 12.0% higher than those from the conventional DIR. Conclusion: Heterogeneous dose distribution in normal organ causes non-uniform sub-volume shrinkage. Sub-volume in high dose region has a larger shrinkage than the one in low dose region, therefore causing more sub-volumes to move into the high dose area during the treatment course. This leads to an unfavorable dose-volume relationship for the normal organ. Without including this effect in DIR, treatment dose in normal organ could be underestimated affecting treatment evaluation and planning modification. Acknowledgement: Partially Supported by Elekta Research Grant.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Optimal Spatial Separation of High-Order Harmonics from Infrared Driving Lasers with an Annular Beam in the Overdriven Regime

We study high-order harmonic generation (HHG) with an annularly shaped high-power, high-repetition-rate laser. In this work we investigate how the spatial separation (or divergence) of the incident laser and the generated high-order harmonics depends on the gas pressure when the laser intensity is in the overdriven regime. It is shown that, when the cone size of the incident annular beam is relatively large, the resulting harmonics are highly collimated along the propagation axis and are spatially separated from the incident beam. Under the overdriven condition, dynamic phase matching favors HHG emissions from short-trajectory electrons that are efficiently built up in the second half of the gas medium. We verify that using an annular beam is a simple and effective method for separating the intense incident infrared laser from the generated high harmonics. Such high-flux and low-divergence light pulses are expected to be powerful sources in the laboratory for ultrafast probing of electron dynamics.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Latest Developments in PM Systems and Methods and their Application to WM Projects - 20364

How do you improve on an industry that is well established yet often misses the mark on key metrics demonstrating effective planning and execution of project scope, schedule and budget? With the increased complexity of DOE projects relative to either poorly kept records of what wastes are stored or the lack of specific knowledge relative to the waste concentrations/quantities, this is a question continually asked and investigated by many. In fact, in 2017, the GAO's report to Congress indicated that although the DOE has made some progress on its monitoring effectiveness and demonstrating progress criteria, these goals were not met and there needs to be more improvement and monitoring. This paper will offer some insights into the latest developments in project management methodologies and the possible application of these to waste management projects. Traditional data generated via a project schedule that utilizes critical path methodology (CPM) and additional earned value management (EVM) data needs to be accurate and enable the project manager to better understand the probability of project success. Although this data has readily been available on most large-scale projects, success as measured by various stakeholder groups including the client, project team, regulators, etc. is less than optimal. Therefore, an urgent need exists to explore how traditional project data (CPM and EVM) coupled with new methodologies allows for better planning and execution by the project team. Many new approaches/methodologies can even be used to predict the success of options prior to full implementation on the actual project. Three approaches/methodologies will be discussed: - Artificial Intelligence; - Change Management; - Blend of Traditional Management (Gantt chart) and Agile Methodologies. As market forces change, so will the direction of project management. The days of 'one size fits all' are no longer valid. A combination of predictive and adaptive approaches in the management of projects is essential to enable execution of project deliverables on time, under budget, and within the contractual scope. This paper is intended to provide the reader with insight to the close relationship of project management trends and business management trends, and to provoke critical thinking about what it means to align project management strategy with an environment of non-stop innovation. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2018

Flux growth and magneto-transport properties of cubic antiperovskite Ca3PbO single crystals

Highlights: • Antiperovskite Ca{sub 3}PbO is predicted to be a three-dimensional Dirac fermion system. • Cubic crystals, 1 mm in size, were obtained by a Ca-self-flux method. • The crucible and sealing method were critical factors to reduce carrier density. • Shubnikov-de Haas oscillations were clearly observed, indicating its high purity. - Abstract: We report the single crystal growth of cubic antiperovskite Ca{sub 3}PbO by a Ca-self-flux method. Cubic crystals, 1 mm in size, were successfully obtained through the use of iron crucibles sealed in stainless steel capsules. The crucible material and sealing method were found to be critical factors for achieving large crystals with low carrier density. The crystals were subsequently characterized by powder and single-crystal x-ray diffraction experiments, electron-probe microanalysis, and Hall effect measurements. Through the use of short stainless steel rods as tight caps for the crucible and fillers to occupy extra space in the capsule, the Ca evaporation loss of the flux, which contributes to Ca vacancy formation, was effectively reduced. Hence, the hole carrier density in the single crystal was reduced to 4.0 × 10{sup 19} cm{sup −3}. The crystal synthesized under optimized growth conditions showed clear Shubnikov-de Haas oscillations, indicating its high purity and homogeneity.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
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 OSTI2019

Optimized illumination for high-throughput ptychography

As a scanning version of coherent diffraction imaging (CDI), X-ray ptychography has become a popular and very successful method for high-resolution quantitative imaging of extended specimens. The requirements of mostly coherent illumination and the scanning mechanism limit the throughput of ptychographic imaging. In this paper, we will introduce the methods we use at the Advanced Photon Source (APS) to achieve high-throughput ptychography by optimizing the parameters of the illumination beam. One work we have done is increasing the illumination flux by using a double-multilayer monochromator (DMM) optics with about 0.8% bandwidth. Compared with our double-crystal monochromator (DCM) optics with 0.01% bandwidth, this DMM optics provides around 20 times more flux. A multi-wavelength reconstruction method has been implemented to deal with the consequential degraded temporal coherence from such an illumination to ensure high-quality reconstruction. In the other work, we adopt a novel use of flat-top focusing optics to generate a flat-top beam with the diameter of about 1.5 µm on the focal plane. The better uniformity of the probe and the large beam size allow one to significantly increase the step size in ptychography scans and thereby the imaging efficiency.

Broad bandwidth↗
DOE OSTI2025

Processability and Material Behavior of NiTi Shape Memory Alloys Using Wire Laser-Directed Energy Deposition (WL-DED)

Utilizing additive manufacturing (AM) techniques with shape memory alloys (SMAs) like NiTi shows great promise for fabricating highly flexible and functionally superior 3D metallic structures. Compared to methods relying on powder feedstocks, wire-based additive manufacturing processes provide a viable alternative, addressing challenges such as chemical composition instability, material availability, higher feedstock costs, and limitations on part size while simplifying process development. This study presented a novel approach by thoroughly assessing the printability of Ni-rich Ni55.94Ti (Wt. %) SMA using the wire laser-directed energy deposition (WL-DED) technique, addressing the existing knowledge gap regarding the laser wire-feed metal additive manufacturing of NiTi alloys. For the first time, the impact of processing parameters—specifically laser power (400–1000 W) and transverse speed (300–900 mm/min)—on single-track fabrication using NiTi wires in the WL-DED process was examined. An optimal range of process parameters was determined to achieve high-quality prints with minimal defects, such as wire dripping, stubbing, and overfilling. Building upon these findings, we printed five distinct cubes, demonstrating the feasibility of producing nearly porosity-free specimens. Notably, this study investigated the effect of energy density on the printed part density, impurity pick-up, transformation temperature, and hardness of the manufactured NiTi cubes. The results from the cube study demonstrated that varying energy densities (46.66–70 J/mm3) significantly affected the quality of the deposits. Lower to intermediate energy densities achieved high relative densities (>99%) and favorable phase transformation temperatures. In contrast, higher energy densities led to instability in melt pool shape, increased porosity, and discrepancies in phase transformation temperatures. These findings highlighted the critical role of precise parameter control in achieving functional NiTi parts and offer valuable insights for advancing AM techniques in fabricating larger high-quality NiTi components. Additionally, our research highlighted important considerations for civil engineering applications, particularly in the development of seismic dampers for energy dissipation in structures, offering a promising solution for enhancing structural performance and energy management in critical infrastructure.

Dabbaghi, Hediyeh↗
DOE OSTI2024

Dyn$\mathrm{AMO}$: Multi-agent reinforcement learning for dynamic anticipatory mesh optimization with applications to hyperbolic conservation laws

Here we introduce DynAMO, a reinforcement learning paradigm for Dynamic Anticipatory Mesh Optimization. Adaptive mesh refinement is an effective tool for optimizing computational cost and solution accuracy in numerical methods for partial differential equations. However, traditional adaptive mesh refinement approaches for time-dependent problems typically rely only on instantaneous error indicators to guide adaptivity. As a result, standard strategies often require frequent remeshing to maintain accuracy. In the DynAMO approach, multi-agent reinforcement learning is used to discover new local refinement policies that can anticipate and respond to future solution states by producing meshes that deliver more accurate solutions for longer time intervals. By applying DynAMO to discontinuous Galerkin methods for the linear advection and compressible Euler equations in two dimensions, we demonstrate that this new mesh refinement paradigm can outperform conventional threshold-based strategies while also generalizing to different mesh sizes, remeshing and simulation times, and initial conditions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

On the application of the MARTINI coarse-grained model to immersion of a protein in a phospholipid bilayer

An important step in the simulation of a membrane protein in a phospholipid bilayer is the correct immersion of the protein in the bilayer. Crystal structures are determined without the bilayer. Particularly for proteins with monotopic domains, it can be unclear how deeply and in which orientation the protein is being inserted in the membrane. We have previously developed a procedure combining coarse-grain (CG) with all-atom (AA) molecular dynamics (MD) simulations to insert and simulate a cytochrome P450 (CYP) possessing an N-terminal transmembrane helix connected by a flexible linker region to a globular domain that dips into the membrane. The CG simulations provide a computationally efficient means to explore different orientations and conformations of the CYP in the membrane. Converged configurations obtained in the CG simulations are then refined in AA simulations. Here, we tested different variants of the MARTINI CG model, differing in the water model, the treatment of long-range non-bonded interactions, and the implementation (GROMACS 4.5.5 vs 5.0.4), for this purpose. We examined the behavior of the models for simulating a 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC) bilayer in water and for the immersion of CYP3A4 in a POPC bilayer, and compared the CG-MD results with the previously reported experimental and simulation results. We also tested the methodology on a set of four other CYPs. Finally, we propose an optimized protocol for modeling such protein-membrane systems that provides the most plausible configurations and is computationally efficient; this incorporates the standard non-polar water model and the GROMACS 5.0.4 implementation with a reaction field treatment of long-range interactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Improved Productivity with Multilaser Rotary Powder Bed Fusion Additive Manufacturing

Laser powder bed fusion (LPBF) enables the fabrication of intricate, geometrically complex structures with a sufficiently fine surface finish for many engineering applications with a diversity of available feedstock metals. However, the production rate of LPBF systems is not well suited for mass production in comparison to traditional manufacturing methods. LPBF systems measure their deposition rates in 100's of grams per hour, while other processes measure in kilograms per hour or even in the case of processes such as forming, stamping, and casting, 100's of kilograms per hour. To be widely adopted in industry for mass production, LPBF requires a new scalable architecture that enables many orders of magnitude improvement in deposition rate, while maintaining the geometry freedom of additive manufacturing. This article explores concepts that could achieve as much as four orders of magnitude increase in the production rate through the application of (1) rotary table kinematic arrangements; (2) a dramatic number of simultaneously operating lasers; (3) reductions of laser optic size; (4) improved scanning techniques; and (5) an optimization of toroidal build plate size. To theoretically demonstrate the possibilities of production improvements, a productivity analysis is proposed for synchronous reluctance motors with relevance to the electric vehicle industry, given the recent increase in the diversity of printable soft magnetic alloys. The analysis provides insights into the impact of the architecture and process parameters necessary to optimize rotary powder bed fusion for mass production.

36 MATERIALS SCIENCE↗
DOE OSTI2015

A Preliminary Comparison of Three Dimensional Particle Tracking and Sizing using Plenoptic Imaging and Digital In-line Holography

Digital in-line holography and plenoptic photography are two techniques for single-shot, volumetric measurement of 3D particle fields. Here we present a preliminary comparison of the two methods by applying plenoptic imaging to experimental configurations that have been previously investigated with digital in-line holography. These experiments include the tracking of secondary droplets from the impact of a water drop on a thin film of water and tracking of pellets from a shotgun. Both plenoptic imaging and digital in-line holography successfully quantify the 3D nature of these particle fields. This includes measurement of the 3D particle position, individual particle sizes, and three-component velocity vectors. For the initial processing methods presented here, both techniques give out-of-plane positional accuracy of approximately 1-2 particle diameters. For a fixed image sensor, digital holography achieves higher effective in-plane spatial resolutions. However, collimated and coherent illumination makes holography susceptible to image distortion through index of refraction gradients, as demonstrated in the shotgun experiments. On the other hand, plenotpic imaging allows for a simpler experimental configuration. Furthermore, due to the use of diffuse, white-light illumination, plenoptic imaging is less susceptible to image distortion in the shotgun experiments. Additional work is needed to better quantify sources of uncertainty, particularly in the plenoptic experiments, as well as develop data processing methodologies optimized for the plenoptic measurement.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2015

A Preliminary Comparison of Three Dimensional Particle Tracking and Sizing using Plenoptic Imaging and Digital In-line Holography [PowerPoint]

Digital in-line holography and plenoptic photography are two techniques for single-shot, volumetric measurement of 3D particle fields. Here we present a preliminary comparison of the two methods by applying plenoptic imaging to experimental configurations that have been previously investigated with digital in-line holography. These experiments include the tracking of secondary droplets from the impact of a water drop on a thin film of water and tracking of pellets from a shotgun. Both plenoptic imaging and digital in-line holography successfully quantify the 3D nature of these particle fields. This includes measurement of the 3D particle position, individual particle sizes, and three-component velocity vectors. For the initial processing methods presented here, both techniques give out-of-plane positional accuracy of approximately 1-2 particle diameters. For a fixed image sensor, digital holography achieves higher effective in-plane spatial resolutions. However, collimated and coherent illumination makes holography susceptible to image distortion through index of refraction gradients, as demonstrated in the shotgun experiments. On the other hand, plenotpic imaging allows for a simpler experimental configuration. Furthermore, due to the use of diffuse, white-light illumination, plenoptic imaging is less susceptible to image distortion in the shotgun experiments. Additional work is needed to better quantify sources of uncertainty, particularly in the plenoptic experiments, as well as develop data processing methodologies optimized for the plenoptic measurement.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2015

WE-EF-BRA-04: Evaluation of Dosimetric Uncertainties in Individualized Targeted Radionuclide Therapy (TRT) Treatment Planning Using Pre-Clinical Data

Purpose: Dosimetry for targeted radionuclide therapy (TRT) is moving away from conventional model-based methods towards patient-specific approaches. To address this need, a Monte Carlo (MC) dosimetry platform was developed to estimate patient-specific therapeutic 3D dose distributions based on pre-treatment imaging. However, because a standard practice for patient-specific internal dosimetry has not yet been established, there are many sources of dosimetric uncertainties. The goal of this work was to quantify the sensitivity of various parameters on MC dose estimations. Methods: The ‘diapeutic’ agent, CLR1404, was used as a proof-of-principle compound in this work. CLR1404 can be radiolabeled with either {sup 124}I for PET imaging or {sup 131}I for radiotherapy or SPECT imaging. PET/CT images of 5 mice were acquired out to 240 hrs post-injection of {sup 124}I-CLR1404. The therapeutic {sup 131}I-CLR1404 absorbed dose (AD) distribution was calculated using a Geant4-based MC dosimetry platform. A series of sensitivity studies were performed. The variables that were investigated included the PET/CT voxel resolution, partial volume corrections (PVC), material segmentation, inter-observer contouring variability, and the pre-treatment image acquisition frequency. Results: Resampling the PET/CT voxel size between 0.2–0.8 mm resulted in up to a 13% variation in the mean AD. Application of the PVC increased the mean AD by 0.5–11.2%. Less than 1% differences in ROI mean AD were observed between the tissue segmentation schemes using 4 and 27 different material compositions. Inter-observer contouring variability led to up to a 20% CoV (stdev/mean) in the mean AD between the users. Varying the number and frequency of pre-treatment images used resulted in changes in mean AD up to 176% compared to the case using all 12 images. Conclusion: Voxel resolution, contour segmentation, the image acquisition protocol most significantly impacted patient-specific TRT dosimetry. Further work is needed to develop a standard protocol that optimizes accuracy and efficiency for patient-specific internal dosimetry. BT and JG are affiliated with Cellectar Biosciences which owns the licensing rights to CLR1404 and related compounds.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

Spinel high-entropy oxides (FeNiCrMnZnX) 3 O 4 (X = Al, mg) as anode materials for high-performance lithium-ion batteries

To address the high cost, cobalt dependency, and resource constraints typical of conventional high-entropy oxide (HEO) anodes, this study reports the successful synthesis of two Co-free, six-component spinel-type HEOs(FeNiCrMnZnAl) 3 O 4 (HEO-Al) and (FeNiCrMnZnMg) 3 O 4 (HEO-Mg), via a sol-gel method. The distinct effects of Al 3+ and Mg 2+ incorporation on the electrochemical performance and lithium storage kinetics were systematically investigated. XRD, Raman, and TEM characterizations confirm that both materials possess a pure spinel phase, uniform particle size, and homogeneous elemental distribution. Notably, electrochemical evaluations reveal that HEO-Al delivers a superior reversible capacity of 480.7 mAh g −1 after 100 cycles at 0.1 A g −1 , and maintains 354.5 mAh g −1 after 1000 long-term cycles at 1 A g −1 , significantly outperforming HEO-Mg. Kinetic analysis indicates that HEO-Al exhibits lower charge transfer resistance, a higher Li + diffusion coefficient, and a pseudocapacitive contribution of up to 82%. Furthermore, these findings demonstrate that Al substitution effectively optimizes the structural stability and lithium storage kinetics of Co-free HEOs, providing a viable strategy for designing low-cost, highly stable HEO anode systems.

Anode materials↗