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DOE OSTI2024

Electromagnetic Design Optimization Integrated with Mechanical Stress Analysis of PM-Assisted Synchronous Reluctance Machine Topologies Enabled with a Blend of Magnets

Permanent Magnet-Assisted Synchronous Reluctance Machines (PMASynRM) provide a low-cost alternative to Surface PM Machines due to the use of relatively lower grades of rare-earth (RE) or RE-free magnets, as the performance degradation due to weaker magnets is compensated by the presence of reluctance torque. However, the weaker magnets suffer from a high risk of demagnetization, leading to unreliable motor operation. Using a blend of RE and RE-free magnets has the potential to overcome this issue. This paper proposes to blend different grades of various rare-earth (RE) and rare-earth-free (RE-free) magnets in six different combinations and utilizes them in two-layer and three-layer U-shaped PMASynRM topologies with both eight-pole and six-pole variations. The rotor of the various designs is then optimized using a differential evolution (DE) based optimization algorithm to obtain low-cost designs with reduced RE magnet volume and minimum demagnetization risk. The optimization of each design is also integrated with the evaluation of mechanical stresses in the rotor laminations so as to maintain the stresses below the material yield strength. Furthermore, the various performance metrics, such as toque–speed/power–speed characteristics, demagnetization, and efficiency maps, are evaluated for each of the optimized and mechanically feasible designs. A quantitative comparison of the various optimized designs is also obtained to highlight the various trade-offs. The results indicate the feasibility of meeting the baseline torque requirement across the entire speed range, even with a 100% reduction in RE magnet volume and less than 5% demagnetization risk, while achieving a cost reduction exceeding 50%. Moreover, the two-layer, eight-pole designs exhibit relatively higher performance, whereas the three-layer, eight-pole designs are found to be the most economical option.

design optimization↗

DOE OSTI2025

Assessment of Benefits of Solid-State Advanced Manufacturing Processes for Nuclear Energy Products

The Advanced Materials and Manufacturing Technology (AMMT) program develops cross cutting technologies in support of a broad range of nuclear reactor technologies and maintains U.S. leadership in materials and manufacturing technologies for nuclear energy applications. This overall project provides the U.S. Department of Energy a critical feasibility study comparison of three solid-state processes to other AM processes, thereby providing the feasibility of the solid-state processes examined to manufacture 316H SS and ODS steel components: • Fused-filament fabrication (FFF): This work provides an initial evaluation of the impact of powder morphology and sizes on the FFF process, and the feasibility and adaptability for different material systems, to use FFF for ODS steels and 316 SS. • Shear-assisted processing and extrusion (ShAPE): Specifically for this portion of the project on ShAPE tube forming, the objectives will be to determine the feasibility to direct tube forming of high tensile strength steel tubing, specifically for ODS steel to determine the effect of the patented extrusion process on the dispersoids of the ODS material. Additionally, as often ODS powders are mechanically alloyed and therefore more platelike or angular, this feasibility was to explore the impact on the optimization process and initial feasibility of direct tube forming. • Cold spray and friction stir additive manufacturing as a stretch goal: Bulk and near net shape manufacturing processes for high-temperature, high-strength alloys are needed. Additionally, cold spray techniques can be applied in-situ at the operational level for repair and can provide multiple benefits to the nuclear industry. These tasks aim to provide information to show benefits of cold spray during the full life cycle, namely research and development, product manufacturing, and repair to mention a few key points.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2014

Numerical design of SiC bulk crystal growth for electronic applications

Presented study concerns numerical simulation of Physical Vapor Transport (PVT) growth of bulk Silicon Carbide (SiC) crystals. Silicon Carbide is a wide band gap semiconductor, with numerous applications due to its unique properties. Wider application of SiC is limited by high price and insufficient quality of the product. Those problems can be overcame by optimizing SiC production methods. Experimental optimization of SiC production is expensive because it is time consuming and requires large amounts of energy. Numerical modeling allows to learn more about conditions inside the reactor and helps to optimize the process at much lower cost. In this study several simulations of processes with different reactor geometries were presented along with discussion of reactor geometry influence on obtained monocrystal shape and size.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2023

SHAPER: can you hear the shape of a jet?

The identification of interesting substructures within jets is an important tool for searching for new physics and probing the Standard Model at colliders. Many of these substructure tools have previously been shown to take the form of optimal transport problems, in particular the Energy Mover’s Distance (EMD). In this work, we show that the EMD is in fact the natural structure for comparing collider events, which accounts for its recent success in understanding event and jet substructure. We then present a Shape Hunting Algorithm using Parameterized Energy Reconstruction (SHAPER), which is a general framework for defining and computing shape-based observables. SHAPER generalizes N-jettiness from point clusters to any extended, parametrizable shape. This is accomplished by efficiently minimizing the EMD between events and parameterized manifolds of energy flows representing idealized shapes, implemented using the dual-potential Sinkhorn approximation of the Wasserstein metric. We show how the geometric language of observables as manifolds can be used to define novel observables with built-in infrared-and-collinear safety. We demonstrate the efficacy of the SHAPER framework by performing empirical jet substructure studies using several examples of new shape-based observables.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2023

Saddle-Shaped Third Component with Out-of-Plane Electrostatic Dipole for Realizing High-Performance Photovoltaic Donor Terpolymers

Terpolymer fabrication is an effective methodology for molecular engineering and generating high-performance organic photovoltaic materials to construct highly efficient polymer solar cells. Modification of the polymer PM6 by incorporating a third component resulting in the formation of a ternary copolymer is reported to outperform PM6 in achieving enhanced device performances. However, one of the major challenges in constructing high-performance terpolymers is to counter the molecular disorder caused by the backbone entropy induced by the third moiety. Here, in this work, double B←N bridged bipyridine (BNBP) is used as the third component, which possesses a strong out-of-plane electrostatic dipole owing to the saddle-shaped B←N fused ring structure. The out-of-plane dipole moment introduced in the modified PM6 terpolymer can be used as a means for tuning and optimizing the nanostructures of the blended films. The prepared PM6-BNBP-4 blend polymer with 4% of the benzodithiophene dione monomers replaced by BNBP results in excellent power conversion efficiency of 19.13%. This work demonstrates that the out-of-plane electrostatic dipole moment in saddle-shaped molecules is valuable for achieving high-performance organic photovoltaic donor materials.

36 MATERIALS SCIENCE↗

DOE OSTI2016

A Highly Resolved Large-Eddy Simulation of a Wind Turbine using an Actuator Line Model with Optimal Body Force Projection

When representing the blade aerodynamics with rotating actuator lines, the computed forces have to be projected back to the CFD flow field as a volumetric body force. That has been done in the past with a geometrically simple uniform three-dimensional Gaussian at each point along the blade. Here, we argue that the body force can be shaped in a way that better predicts the blade local flow field, the blade load distribution, and the formation of the tip/root vortices. In previous work, we have determined the optimal scales of circular and elliptical Gaussian kernels that best reproduce the local flow field in two-dimensions. Lastly, in this work we extend the analysis and applications by considering the full three-dimensional blade to test our hypothesis in a highly resolved Large Eddy Simulation.

17 WIND ENERGY↗

DOE OSTI2023

Neural network-based control of an ultrafast laser

With the recent advances in machine learning (ML) and data science (DS), the control, modeling, and analysis of these complex systems continues to improve. In this work, we report on the optimization of the intensity of a femtosecond laser using feedforward neural networks (FFNN) that model the input–output relationships of the data. The input parameters of the system were optimized to achieve the required performance of the femtosecond laser. We propose a neural network-based control system to model the relationship between the spectral amplitude and phase of the input laser pulse at the amplifier input and the shape of the output pulse. Low-jitter laser parameter inputs and the resulting laser pulse duration were modeled, and the resulting correlation between the input and output data was used to optimize the laser pulse. Here, we demonstrate improved processing and laser control performance.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2020

Extending XACC for Quantum Optimal Control

Quantum computing vendors are beginning to open up application programming interfaces for direct pulse-level quantum control. With this, programmers can begin to describe quantum kernels of execution via sequences of arbitrary pulse shapes. This opens new avenues of research and development with regards to smart quantum compilation routines that enable direct translation of higher-level digital assembly representations to these native pulse instructions. In this work, we present an extension to the XACC system-level quantum-classical software framework that directly enables this compilation lowering phase via user-specified quantum optimal control techniques. This extension enables the translation of digital quantum circuit representations to equivalent pulse sequences that are optimal with respect to the backend system dynamics. Our work is modular and extensible, enabling third party optimal control techniques and strategies in both C++ and Python. We demonstrate this extension with familiar gradient-based methods like gradient ascent pulse engineering (GRAPE), gradient optimization of analytic controls (GOAT), and Krotov's method. Our work serves as a foundational component of future quantum-classical compiler designs that lower high-level programmatic representations to low-level machine instructions.

Nguyen, Thien↗

DOE OSTI2023

Freeform thermoelectrics in single-step manufacturing: additive manufacturing of bismuth-telluride thermoelectrics

The project succeeded in producing crack-free Bismuth Telluride thermoelectric parts with density exceeding 98% through laser powder bed fusion (LPBF) additive manufacturing (AM). This greatly exceeded the highest previously reported density of 88% and is the highest among all semiconducting materials processed by LPBF. The additively manufactured material shows comparable Seebeck coefficient as conventional form and can be made into complex geometries with reduced material loss. On the other hand, measured properties are dramatically sensitive to the AM process parameters used, such that with identical composition, the Seebeck coefficient can be controllably tuned from +120 µV/K to -207 µV/K, which means the material switches between an n-type to a p-type semiconductor depending on processing. These changes are accompanied by significant differences in the as-processed microstructure due to rapid solidification. A machine learning protocol was developed and greatly reduced the experimental burden of the project, reducing the typical process optimization period of 2 years to 6 months. The project was fully successful in the objective of producing defect-free, complex geometry of bismuth-telluride parts through LPBF, but only partially successful in achieving performance goals. First, cost reduction of manufacturing, as measured by material waste, was successfully reduced by up to 70% compared to conventional manufacturing methods. This exceeded the proposed 30% reduction in materials waste needed to reach the 20% cost reduction goal of the project. On the other hand, the device performance, as measured by Seebeck coefficient, failed to reach the 40% improvement in efficiency. Rather, we observe comparable Seebeck coefficient between AM samples and conventionally processed counterparts. The device-level efficiency improvement does exceed 40% for complex geometry samples due to shape-induced increase in temperature gradients, but this was not the originally proposed metric. The machine learning approach developed in this project greatly accelerated the process optimization and can be adopted for fast development of AM processing parameters for other brittle and otherwise difficult-to-print materials. For the public, we deliver an efficient and widely adoptable process for incorporating waste-heat harvesting thermoelectric devices in both industrial and commercial heat exchangers. The geometric flexibility allows the capturing device to conform to the shape of the heat source to improve the system-level conversion efficiency. The technique can be deployed on any commercial LBPF systems with zero modifications, thus poses minimal adoption barrier for any manufacturer that already employed AM technology. Beyond bismuth-telluride, the machine-learning guided optimization protocol can be used in the future to reduce both the time and cost of process development for AM of other energy conversion and harvesting materials.

36 MATERIALS SCIENCE↗

DOE OSTI2025

3D Printing of Highly Porous Polypropylene Separators for Lithium‐Ion Batteries Using Fused Deposition Modeling and Thermally Induced Phase Separation

Appearing as one of the key-components of lithium-ion batteries (LIBs), this work specifically focuses on the additive manufacturing (AM) of custom-shape separators, facilitated by the filament material extrusion process, also called fused deposition modeling (FDM). The development and optimization of composite thermoplastic filament feedstocks combining polypropylene and paraffin wax, followed by the 3D printing of the separator membranes is shown. A post-processing step, based on thermal induced phase separation (TIPS), is introduced to promote porosity formation through removal of the paraffin wax sacrificial phase within the 3D printed items. Separators with different polypropylene/paraffin wax ratios are developed and the impact on printability, mechanical strength, porosity, and electrochemical performances, is thoroughly discussed. X-ray micro-computed tomography is employed to assess the geometric fidelity and to detect printing defects in a complex 3D lattice structure. The performance of the 3D printed porous separators is also compared to a commercial separator. This pioneering research establishes a foundation for the creation of porous separators that can adapt to and conform into 3D printed battery architectures with novel form factors, and also creates opportunities for the use of FDM and TIPS for a wide range of applications that employ porous structures beyond the energy storage field.

3D printing↗

DOE OSTI2018

Enhanced Light Extraction from OLEDs Fabricated on Patterned Plastic Substrates

A key scientific and technological challenge in organic light-emitting diodes (OLEDs) is enhancing the light outcoupling factor η out , which is typically <20%. This paper reports experimental and modeling results of a promising approach to strongly increase η out by fabricating OLEDs on novel flexible nanopatterned substrates that result in a >2× enhancement in green phosphorescent OLEDs (PhOLEDs) fabricated on corrugated polycarbonate (PC). The external quantum efficiency (EQE) reaches 50% (meaning ηout ≥50%); it increases 2.6x relative to a glass/ITO device and 2× relative to devices on glass/poly(3,4-ethylenedioxythiophene):polystyrene sulfonate (PEDOT:PSS) or flat PC/PEDOT:PSS. A significant enhancement is also observed for blue PhOLEDs with EQE 1.7× relative to flat PC. The corrugated PC substrates are fabricated efficiently and cost-effectively by direct room-temperature molding. These substrates successfully reduce photon losses due to trapping/waveguiding in the organic+anode layers and possibly substrate, and losses to plasmons at the metal cathode. Focused ion beam gauged the conformality of the OLEDs. Dome-shaped convex nanopatterns with height of ~280–400 nm and pitch ~750–800 nm were found to be optimal. Lastly, substrate design and layer thickness simulations, reported first for patterned devices, agree with the experimental results that present a promising method to mitigate photon loss paths in OLEDs.

36 MATERIALS SCIENCE↗

DOE OSTI2017

Evaluation of a Bioabsorbable Self-Expandable Vein Stent-Base Made of Poly(l-lactide) In Vitro and In Vivo

PurposeThis study was designed to evaluate performance and tissue response to a self-expandable bioabsorbable vein stent-base cut from a tube with enhanced stiffness and strength in vitro and in vivo.MethodsA diamond-shaped stent-base was cut from a sequential biaxially strained poly(l-lactide) (PLLA) tube for optimized performance. The performance of the stent-base was evaluated in a finite element analysis model, and validation was attempted in vitro through a cyclic flat-plate compression and radial force measurement. The performance of the stent-base was tested in vivo using 3 sheep with 2 implants each for 2 and 3½ weeks, respectively.ResultsIn vitro the stent-base showed an elliptical deformation but no fractures. In vivo the stent-base showed adequate radial force and no migration. All implanted stent-bases showed multiple fractures not only at the predicted stress zones but at all connecting points. Fragments of the caudal stent-base stayed in the vein wall indicating sufficient tissue coverage to avoid embolization of the fractured stent pieces, whereas fragments from the cranial device remaining were few. Neointima formation was confirmed histologically at 2 and 3½ weeks.ConclusionA bioabsorbable self-expandable stent-base made from PLLA for large veins seems feasible, but over time, the PLLA used in this study appears too stiff and lacks the sufficient flexibility to move with the vena cava, causing multiple fractures.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2021

Evaluation of Force Fields for Molecular Dynamics Simulations of Platinum in Bulk and Nanoparticle Forms

Here, understanding the size- and shape-dependent properties of platinum nanoparticles is critical for enabling the design of nanoparticle-based applications with optimal and potentially tunable functionality. Toward this goal, we evaluated nine different empirical potentials with the purpose of accurately modeling faceted platinum nanoparticles using molecular dynamics simulation. First, the potentials were evaluated by computing bulk and surface properties - surface energy, lattice constant, stiffness constants, and the equation of state - and comparing these to prior experimental measurements and quantum mechanics calculations. Then, the potentials were assessed in terms of the stability of cubic and icosahedral nanoparticles with faces in the {100} and {111} planes, respectively. Although none of the force fields predicts all the evaluated properties with perfect accuracy, one potential - the embedded atom method formalism with a specific parameter set - was identified as best able to model platinum in both bulk and nanoparticle forms.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2015

Identifying the Atomic-Level Effects of Metal Composition on the Structure and Catalytic Activity of Peptide-Templated Materials

Bioinspired approaches for the formation of metallic nanomaterials have been extensively employed for a diverse range of applications including diagnostics and catalysis. These materials can often be used under sustainable conditions; however, it is challenging to control the material size, morphology, and composition simultaneously. Here we have employed the R5 peptide, which forms a 3D scaffold to direct the size and linear shape of bimetallic PdAu nanomaterials for catalysis. The materials were prepared at varying Pd:Au ratios to probe optimal compositions to achieve maximal catalytic efficiency. These materials were extensively characterized at the atomic level using transmission electron microscopy, extended X-ray absorption fine structure spectroscopy, and atomic pair distribution function analysis derived from high-energy X-ray diffraction patterns to provide highly resolved structural information. The results confirmed PdAu alloy formation, but also demonstrated that significant surface structural disorder was present. The catalytic activity of the materials was studied for olefin hydrogenation, which demonstrated enhanced reactivity from the bimetallic structures.These results present a pathway to the bioinspired production of multimetallic materials with enhanced properties, which can be assessed via a suite of characterization methods to fully ascertain structure/function relationships.

36 MATERIALS SCIENCE↗

DOE OSTI2019

Origin of High Activity and Durability of Twisty Nanowire Alloy Catalysts under Oxygen Reduction and Fuel Cell Operating Conditions

The ability to control the surface composition and morphology of alloy catalysts is critical for achieving high activity and durability of catalysts for oxygen reduction reaction (ORR) and fuel cells. Here, this report describes an efficient surfactant-free synthesis route for producing a twisty nanowire (TNW) shaped platinum–iron (PtFe) alloy catalyst (denoted as PtFe TNWs) with controllable bimetallic compositions. PtFe TNWs with an optimal initial composition of ~24% Pt are shown to exhibit the highest mass activity (3.4 A/mg Pt , ~20 times higher than that of commercial Pt catalyst) and the highest durability (<2% loss of activity after 40000 cycles and <30% loss after 120000 cycles) among all PtFe-based nanocatalysts under ORR or fuel cell operating conditions reported so far. Using ex situ and in situ synchrotron X-ray diffraction coupled with atomic pair distribution function (PDF) analysis and 3D modeling, the PtFe TNWs are shown to exhibit mixed face-centered cubic (fcc)-body-centered cubic (bcc) alloy structure and a significant lattice strain. A striking finding is that the activity strongly depends on the composition of the as-synthesized catalysts and this dependence remains unchanged despite the evolution of the composition of the different catalysts and their lattice constants under ORR or fuel cell operating conditions. Notably, dealloying under fuel cell operating condition starts at phase-segregated domain sites leading to a final fcc alloy structure with subtle differences in surface morphology. Due to a subsequent realloying and the morphology of TNWs, the surface lattice strain observed with the as-synthesized catalysts is largely preserved. This strain and the particular facets exhibited by the TNWs are believed to be responsible for the observed activity and durability enhancements. These findings provide new insights into the correlation between the structure, activity, and durability of nanoalloy catalysts and are expected to energize the ongoing effort to develop highly active and durable low-Pt-content nanowire catalysts by controlling their alloy structure and morphology.

25 ENERGY STORAGE↗

DOE OSTI2018

Retrievals of Riming and Snow Density From Vertically Pointing Doppler Radars

Retrievals of ice and snow are made from Ka- and W-band zenith-pointing Doppler radars at Hyytiälä, Finland, during the snow experiment component of the Biogenic Aerosols: Effects on Clouds and Climate (2014) field campaign. In a novel optimal estimation retrieval, mean Doppler velocity is exploited to retrieve a density factor parameter, which modulates the mass, shape, terminal velocity, and backscatter cross sections of ice particles. In a case study including aggregate snow and graupel we find that snow rate and ensemble mean ice density can be retrieved to within 50% of in situ measurements at the surface using dual-frequency Doppler radar retrievals. While Doppler measurements are essential to the retrieval of particle density, the dual-frequency ratio provides a strong constraint on particle size. The retrieved density factor is strongly correlated with liquid water path, indicating that riming is the primary process by which the density factor is modulated. Using liquid water path as a proxy for riming, profiles classified as unrimed snow, rimed snow, and graupel exhibit distinct features characteristic of aggregation and riming processes, suggesting the potential to make estimates of process rates from these retrievals. We discuss the potential application of the technique to future satellite missions.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2015

The effect of morphology and confinement on the high-pressure phase transition in ZnO nanostructure

The transition pressure (P{sub t}) of the B4-to-B1 phase transformation of zinc oxide nanoparticle (n-ZnO) structures was investigated in terms of their size and morphology. Nanorods, nanopencils, nanopyramids, nanowires, and nanotubes of the B4 phase in various sizes were directly built up by accounting for the atomic basis of the core and surface regions. The previously proposed transformation path was performed for constructing shapes and sizes compatible with B1 phases. Using systematic density functional theory, the surfaces were cleaved from the optimized crystal structures at different pressures in both the B4 and B1 phases. A method for calculating the surface energy at different pressures is proposed using an asymmetric slab model. Using the proposed model, the transition pressure of n-ZnO structures was found to significantly depend on their morphology and size, which is in good agreement with the available experimental reports.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2014

TH-C-17A-07: Visualizing and Quantifying Radiation Therapy in Real-Time Using a Novel Beam Imaging Technique

Purpose: Radiation therapy uses invisible high energy X-rays to treat an invisible tumor. Proper positioning of the treatment beam relative to the patient's anatomy during dose delivery is critically important to the success of treatment. We develop and characterize a novel radiation therapy beam visualization technique for real-time monitoring of patient treatment. Methods: Custom made flexible scintillator sheets were fabricated from gadolinium oxysulfide (GOS) particles that had been doped with terbium within a silicone elastomer matrix. Sheets of several thicknesses ranging from 0.3 to 1mm were prepared and tested. Sheets were exposed to megavoltage X-ray and electron beams from a Varian linac and the resulting optical signal was collected by multiple CMOS cameras placed in the treatment room. Real-time images were collected for different beam energies and dose rates. Signal intensity and SNR were calculated by processing the acquired images. Results: All signals were detectable in the presence of full room lighting and at an integration time of 45ms. Average signal intensity and SNR increased with both sheet thickness and dose rate and decreased with beam energy and incident light. For a given sheet thickness and beam energy the correlation between dose rate and signal intensity was highly linear. Increased sheet thickness or dose rate results in a linear increase in the detected signal. All results are consistent with analytical approximations. Conclusion: The technique offers a means of accurately visualizing a radiation therapy beam shape and fluence in real time. The effects of salient parameters have been characterized and will enable further optimization of the technique as it is implemented into the clinical workflow. The project described was supported by the National Center for Advancing Translational Sciences of the National Institutes of Health through UL1 TR001085.

60 APPLIED LIFE SCIENCES↗