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DOE OSTI2022

Li x (C 5 H 5 N) y Fe 2– z Se 2 : A Defect-Resilient Expanded-Lattice High-Temperature Superconductor

Two-dimensional iron chalcogenide intercalates display a remarkable correlation of the interlayer spacing with enhancement of the superconducting critical temperature (T c ). In this work, synchrotron X-ray absorption (XAS; at the Fe and Se K-edges) and emission (XES; at the Fe Κβ) spectroscopies allow one to discuss how the important rise of T c (~44 K) in the molecule-intercalated Li x (C 5 H 5 N) y Fe 2-z Se 2 relates to the electronic and local structural changes felt by the inorganic host upon doping (x). XES shows that widely separated layers of edge-sharing FeSe 4 tetrahedra carry low-spin moieties, with a local Fe magnetic moment slightly reduced compared to the parent β-Fe 2-z Se 2 . Pre-edge XAS expresses the progressively reduced mixing of metal 3d-4p states upon lithiation. Doping-mediated local lattice modifications, probed by conventional T c optimization measures (cf. the anion height and FeSe 4 tetrahedra regularity), become less relevant when layers are spaced far away. On the basis of extended X-ray absorption fine structure, such distortions are compensated by a softer Fe network that relates to Fe-site vacancies, alleviating electron-lattice correlations and superconductivity. Density functional theory (DFT) guided modification of the isolated Fe 2-z Se 2 (z, vacant sites) planes, resembling the host layers, identify that Fe-site deficiency occurs at low energy cost, giving rise to stretched Fe sheets, in accordance with experiments. Here, the robust high-T c in Li x (C 5 H 5 N) y Fe 2-z Se 2 , arises from the interplay of electron-donating spacers and the iron selenide layer's tolerance to defect chemistry, a tool to favorably tune its Fermi surface properties.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2019

Update on the JLEIC Electron Collider Ring Design

The design concept of electron collider ring in the Jefferson Lab Electron-Ion Collider (JLEIC) is based on a small beam size at the interaction point (IP) to boost the luminosity. With a chosen beta-star at the IP, electron beam size is determined by the equilibrium emittance obtained by the linear optics design. In this paper, we present an update on the lattice design of the electron ring considering not only preservation of low beam emittance, but also optimization of geometric arrangement. In particular, recently development of the lattice design has been focused on incorporating the vertical dogleg, which brings the electron beam to the ion beam plane for collisions, in the spin rotator design. The vertical dogleg is designed with no horizontal emittance growth, controlled vertical emittance and no first-order effect on the electron polarization. Single particle nonlinear beam dynamics study is also performed to explore the momentum acceptance and dynamic aperture in this updated design.

Lin, F.↗

NASA NTRSDate not supplied

Exploring Quantum State Preparation Using Tensor Networks and Sparse Wavefunction Simulations

The variational quantum eigenvalue solver is a powerful hybrid quantum-classical approach that has been suggested as a candidate method to run on near-term quantum hardware for computing ground state electronic energies of molecular systems. However, even for small molecules, the number of variational parameters and qubits required to minimize the electronic energy is beyond the reach of current quantum computers except for small basis sets. We explore a new paradigm for state preparation where we test how much of the optimization can be approximately prepared with classical computers to reduce the number of optimization steps performed using a quantum device. By adapting a recent algorithm for the factorized form of the UCC ansatz, we can study molecular electronic structure problems with up to 64 qubits. In addition, we also test a related approach of using tensor networks to optimize quantum circuits in order to benchmark various lattice models. We present results using these approaches and discuss strategies for incorporating these ideas into variational algorithms involving near-term quantum computers. Our results help demonstrate the strength of the UCC ansatz and address pressing questions about optimal initial parameterizations and circuit construction.

quantum computing↗

DOE OSTI2021

Online Optimization of NSLS-II Dynamic Aperture and Injection Transient (Facility Improvement Project)

The Facility Improvement Project (FIP) “Methods of online optimization of NSLS-II storage ring concurrent with user operations” proposed and approved in 2018 is now complete. The first goal is the online optimization of nonlinear beam dynamics to increase the beam lifetime and injection efficiency. We have developed a model-independent optimization technique using advanced algorithms. Using this technique, we increased the NSLS-II dynamic aperture by 20% and reduced the amplitude-dependent tune shift by a factor of two. We applied sextupole optimization to the new high-chromaticity lattice, which has been developed to improve the beam stability and to increase the single-bunch beam intensity. We were able to double the injection efficiency and exceed 90%. The second goal of this project is to provide the top-off injection with minimized perturbations of the beamline user operations. To achieve the transparent injection, we optimize the matching of four storage ring injection kickers reducing the perturbation of the stored beam orbit. The first application of the online optimization resulted in a reduction of the amplitude of residual beam oscillation by a factor of six, from 1300 μm down to 200 μm. Further improvement was limited by the timing jitter of the trigger boards. Then, we replaced all trigger boards with a new design and reduced the timing jitter by a factor of five, from 5 ns down to 1 ns. This upgrade resulted in the injection transient reduction from 200 μm to 120 μm. To optimize the full set of kicker parameters, including the trigger timing, amplitude, and pulse width, we upgraded all kicker power supplies with the capability of tunable waveform width. As a result, we have reduced the injection transient to the limit of 60 μm.

43 PARTICLE ACCELERATORS↗

DOE OSTI2022

Physics makes the difference: Bayesian optimization and active learning via augmented Gaussian process

Abstract Both experimental and computational methods for the exploration of structure, functionality, and properties of materials often necessitate the search across broad parameter spaces to discover optimal experimental conditions and regions of interest in the image space or parameter space of computational models. The direct grid search of the parameter space tends to be extremely time-consuming, leading to the development of strategies balancing exploration of unknown parameter spaces and exploitation towards required performance metrics. However, classical Bayesian optimization (BO) strategies based on the Gaussian process (GP) do not readily allow for the incorporation of the known physical behaviors or past knowledge. Here we explore a hybrid optimization/exploration algorithm created by augmenting the standard GP with a structured probabilistic model of the expected system’s behavior. This approach balances the flexibility of the non-parametric GP approach with a rigid structure of physical knowledge encoded into the parametric model. The fully Bayesian treatment of the latter allows additional control over the optimization via the selection of priors for the model parameters. The method is demonstrated for a noisy version of a standard univariate test function used to evaluate optimization algorithms and further extended to physical lattice models. This methodology is expected to be universally suitable for injecting prior knowledge in the form of physical models and past data in the BO framework.

42 ENGINEERING↗

NASA NTRS2020

Additive Manufactured Ultra-Fine Lattice Structures for Propulsion Catalysts

Traditional mono-propulsion catalysts consist of coated ceramic or graphite foams that possess anisotropic mechanical and fluid properties limiting design, cost, availability, and operational use. Ultra-fine lattice structures are repeating unit cells with ligament thickness as small as 100 μm produced via Additive manufacture (AM). These lattice structures have the potential to replace coated foams used in a mono-propellant system catalysts. AM ultrafine lattice structures are designed to mimic the operational intent of coated foams but with improved design flexibility, compressive strength, and flow behavior printed from into a single part directly from the preferred platinum metal alloy. The investigation objective was to conduct feasibility studies of AM ultra-fine lattice structures capable of replacing coated foams with superior functionality. NASA MSFC identified desired lattice characteristics and created designs while EOS developed optimized laser powder bed fusion AM parameters to manufacture Ti6Al4V and tungsten specimens. Optimized designs, computational tools, AM parameters, and post-process methods were developed. Specimens underwent x-ray microfocus CT, metallographic inspection, compression testing, and flow testing. Results demonstrate that AM ultra-fine lattices improved geometric and performance repeatability with the potential for significantly increased availability while decreasing cost and lead time.

Omar R Mireles↗

NASA NTRSDate not supplied

Additive Manufacture of Ultra-Fine Lattice Structures of Green Propulsion Catalysts

Omar Mireles↗

NASA NTRSDate not supplied

Additive Manufactured Ultra-Fine Lattice Structures for Propulsion Catalysts

Traditional mono-propulsion catalysts consist of coated ceramic or graphite foams that possess anisotropic mechanical and fluid properties limiting design, cost, availability, and operational use. Ultra-fine lattice structures are repeating unit cells with ligament thickness as small as 100 μm produced via Additive manufacture (AM). These lattice structures have the potential to replace coated foams used in a mono-propellant system catalysts. AM ultra-fine lattice structures are designed to mimic the operational intent of coated foams but with improved design flexibility, compressive strength, and flow behavior printed from into a single part directly from the preferred platinum metal alloy. The investigation objective was to conduct feasibility studies of AM ultra-fine lattice structures capable of replacing coated foams with superior functionality. NASA MSFC identified desired lattice characteristics and created designs while EOS developed optimized laser powder bed fusion AM parameters to manufacture Ti6Al4V and tungsten specimens. Optimized designs, computational tools, AM parameters, and post-process methods were developed. Specimens underwent x-ray micro-focus CT, metallographic inspection, compression testing, and flow testing. Results demonstrate that AM ultra-fine lattices improved geometric and performance repeatability with the potential for significantly increased availability while decreasing cost and lead time.

Omar R Mireles↗

DOE OSTI2018

Ultrahigh Power Factor in Thermoelectric System Nb 0.95 M 0.05 FeSb (M = Hf, Zr, and Ti)

Abstract Conversion efficiency and output power are crucial parameters for thermoelectric power generation that highly rely on figure of merit ZT and power factor (PF), respectively. Therefore, the synergistic optimization of electrical and thermal properties is imperative instead of optimizing just ZT by thermal conductivity reduction or just PF by electron transport enhancement. Here, it is demonstrated that Nb 0.95 Hf 0.05 FeSb has not only ultrahigh PF over ≈100 µW cm −1 K −2 at room temperature but also the highest ZT in a material system Nb 0.95 M 0.05 FeSb (M = Hf, Zr, Ti). It is found that Hf dopant is capable to simultaneously supply carriers for mobility optimization and introduce atomic disorder for reducing lattice thermal conductivity. As a result, Nb 0.95 Hf 0.05 FeSb distinguishes itself from other outstanding NbFeSb‐based materials in both the PF and ZT . Additionally, a large output power density of ≈21.6 W cm −2 is achieved based on a single‐leg device under a temperature difference of ≈560 K, showing the realistic prospect of the ultrahigh PF for power generation.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2017

Improving superconductivity in BaFe 2 As 2 -based crystals by cobalt clustering and electronic uniformity

Quantum materials such as antiferromagnets or superconductors are complex in that chemical, electronic, and spin phenomena at atomic scales can manifest in their collective properties. Although there are some clues for designing such materials, they remain mainly unpredictable. In this work, we find that enhancement of transition temperatures in BaFe 2 As 2 -based crystals are caused by removing local-lattice strain and electronic-structure disorder by thermal annealing. While annealing improves Neel-ordering temperature in BaFe 2 As 2 crystal (T N =132K to 136K) by improving in-plane electronic defects and reducing overall a-lattice parameter, it increases superconducting-ordering temperature in optimally cobalt-doped BaFe 2 As 2 crystal (T c =23 to 25K) by precipitating-out the cobalt dopants and giving larger overall a-lattice parameter. And while annealing improves local chemical and electronic uniformity resulting in higher T N in the parent, it also promotes nanoscale phase separation in the superconductor resulting in lower disparity and strong superconducting band gaps in the dominant crystal regions, which lead to both higher overall T c and critical-current-density, J c

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2016

TRITON11 - Westinghouse 11*11 BWR fuel design

Westinghouse has developed an 11*11 BWR fuel design referred to as the TRITON11 fuel design. Given the current economic pressure on the utilities, the key development objective was to significantly reduce the fuel cycle costs. Careful considerations were also made to meet the varying requirements between the different BWR utilities. In particular, the fuel was optimized for both short and long cycle operation, as well as for the up-rated cores and higher burnups. In addition to these advances, careful considerations were given to the overall reliability of the new design to further reduce the risk of fuel failures. Further improved fuel economy requires improved thermal margins since both SVEA-96 Optima2 and Optima3 are already highly optimized for reactivity performance at the fuel lattice level. It was realized that better thermal margins must come from adding more fuel rods, thereby reducing the linear heat generation rate and surface heat flux. This requires going beyond the 10*10 fuel lattice. An 11*11 fuel design was chosen as optimum, considering benefits versus manufacturing cost and added complexity. The numbers, dimensions and positioning of fuel rods and internal water channels (passing non-boiling water) were analyzed intensively. The resulting TRITON11 design has 109 fuel rods and 3 central water rods for improved moderation. The paper presents the TRITON11 fuel design. The development objectives are laid out and the resulting performance and reliability improvements are described. The development is in the final phase of testing and validation. Examples of recent tests are presented. The advances in BWR core analysis codes in support of TRITON11 fuel are briefly summarized. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

NASA NTRS2019

How Certain Physical Considerations Impact Aerostructural Wing Optimization

Wing design optimization has been studied extensively and is of continued interest as optimization tools are developed and become more accessible. In each of these studies, certain assumptions and simplifications are made to make the design problem tractable. However, it is difficult to find systematic studies in which several considerations are added or removed one at a time to study how much impact they have. In this work, we examine how certain physical considerations (viscous drag, wave drag, thrust loads, and inertial relief from structural, fuel, and engine masses), impact the aerostructural optimization results for three distinct aircraft wings. The goal is to help develop a rough idea of how important these physical considerations are. We do this using gradient-based optimization and a multidisciplinary design optimization framework, OpenMDAO. We use the open-source tool OpenAeroStruct that couples a vortex lattice method to a finite element method. We establish a baseline aerostructural design optimization problem then perform a series of optimizations, each with one physical consideration removed from the baseline case. We find that depending on the size of the aircraft and flight conditions, the importance of some of these physical considerations varies considerably whereas the importance of others do not. Specifically, the optimal designs change radically without proper viscous and wave drag considerations and smaller aircraft with more distributed propulsion are more affected by the inclusion of engine loads.

Aeropropulsion↗

DOE OSTI2017

A methodology to determine the elastic moduli of crystals by matching experimental and simulated lattice strain pole figures using discrete harmonics

Determining reliable single crystal material parameters for complex polycrystalline materials is a significant challenge for the materials community. In this work, a novel methodology for determining those parameters is outlined and successfully applied to the titanium alloy, Ti-6Al-4V. Utilizing the results from a lattice strain pole figure experiment conducted at the Cornell High Energy Synchrotron Source, an iterative approach is used to optimize the single crystal elastic moduli by comparing experimental and simulated lattice strain pole figures at discrete load steps during a uniaxial tensile test. Due to the large number of unique measurements taken during the experiments, comparisons were made by using the discrete spherical harmonic modes of both the experimental and simulated lattice strain pole figures, allowing the complete pole figures to be used to determine the single crystal elastic moduli. (C) 2016 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Wielewski, Euan↗

DOE OSTI2026

AI-Ready Semantic Infrastructure for CEBAF: From CED to PALS Knowledge Graphs

JLab and PNNL are jointly developing an AI-ready data ecosystem that exposes the Continuous Electron Beam Acceleration Facility’s (CEBAF’s) operational configuration, lattice description, and control-system channels to agentic optimization frameworks through a standards-based semantic layer. The effort integrates the existing facility-specific CEBAF Element Database (CED) with extensions of the emerging facility-agnostic Particle Accelerator Lattice Standard (PALS) to produce a knowledge graph (KG) containing coherent, machine-interpretable views of devices, signals, and regions. With this KG, CEBAF’s setpoints, readbacks, and device hierarchies become queryable using a uniform declarative graph query language (e.g., Neo4j Cypher), providing intents and inspectable semantics suitable for agentic control. The resulting graph-backed interfaces will allow autonomous agents to retrieve authoritative machine configurations, reason over device- and signal-level relationships, and execute tuning and diagnostic workflows without bespoke CEBAF-specific logic, thereby delivering a scalable pathway from operational data to trustworthy agentic accelerator tuning frameworks.

Zhang, He [Thomas Jefferson National Accelerator F↗

DOE OSTI2016

Microstructural and micromechanical characterization of IN718 theta shaped specimens built with electron beam melting

Theta-shaped specimens were additively manufactured out of Inconel 718 powders using an electron beam melting technique, as a model complex load bearing structure. We employed two different build strategies; producing two sets of specimens. Microstructural and micro-mechanical characterizations were performed using electron back-scatter, synchrotron x-ray and in-situ neutron diffraction techniques. In particular, the cross-members of the specimens were the focus of the synchrotron x-ray and in-situ neutron diffraction measurements. The build strategies employed resulted in the formation of distinct microstructures and crystallographic textures, signifying the importance of build-parameter manipulation for microstructural optimization. Large strain anisotropy of the different lattice planes was observed during in-situ loading. Texture was concluded to have a distinct effect upon both the axial and transverse strain responses of the cross-members. In particular, the (200), (220) and (420) transverse lattice strains all showed unexpected overlapping trends in both builds. This was related to the strong {200} textures along the build/loading direction, providing agreement between the experimental and calculated results.

36 MATERIALS SCIENCE↗

DOE OSTI2017

Lattice Matched Carbide–Phosphide Composites with Superior Electrocatalytic Activity and Stability

Composites of electrocatalytically active transition-metal compounds present an intriguing opportunity toward enhanced activity and stability. Here, to identify potentially scalable pairs of a catalytically active family of compounds, we demonstrate that phosphides of iron, nickel, and cobalt can be deposited on molybdenum carbide to generate nanocrystalline heterostructures. Composites synthesized via solvothermal decomposition of metal acetylacetonate salts in the presence of highly dispersed carbide nanoparticles show hydrogen evolution activities comparable to those of state-of-the-art non-noble metal catalysts. Investigation of the spent catalyst using high resolution microscopy and elemental analysis reveals that formation of carbide–phosphide composite prevents catalyst dissolution in acid electrolyte. Lattice mismatch between the two constituent electrocatalysts can be used to rationally improve electrochemical stability. Among the composites of iron, nickel, and cobalt phosphide, iron phosphide displays the lowest degree of lattice mismatch with molybdenum carbide and shows optimal electrochemical stability. Turnover rates of the composites are higher than that of the carbide substrate and compare favorably to other electrocatalysts based on earth-abundant elements. Lastly, our findings will inspire further investigation into composite nanocrystalline electrocatalysts that use molybdenum carbide as a stable catalyst support.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Machine Learning an Ab-Initio Based Bond-Order Potential for Bismuthene

Bismuthene is a heavy 2D material whose strong spin–orbit coupling and recently observed single-element ferroelectricity have intensified interest in its structural, vibrational, and transport properties. Accurate modeling of these behaviors requires a short-range interatomic potential that can reproduce the underlying bonding physics at a fraction of the computational cost of first-principles methods. However, such a potential is currently unavailable. Here, in this work, we construct a Tersoff bond-order potential for β-bismuthene using a reinforcement-learning framework that integrates a continuous Monte Carlo Tree Search with a simplex-based local optimizer. The optimized parameter sets reproduce first-principles lattice constants, cohesive energy, the equation of state, elastic constants, and phonon dispersion. We validate the models by performing thermal-conductivity calculations and uniaxial fracture simulations our findings confirm the reliability of the resulting models across multiple thermomechanical regimes. Comparison of the three best solutions reveals how differences in pairwise interactions, angular terms, and bond-order behavior govern phonon features and mechanical responses. We demonstrate an interpretable and computationally efficient potential for bismuthene and demonstrate a general reinforcement-learning strategy for developing bond-order models in emerging 2D materials.

deformation↗

DOE OSTI2025

Nanoscopic strain evolution in single-crystal battery positive electrodes

Single-crystal Ni-rich layered oxides (SC-NMC) with a grain-boundary-free configuration have effectively addressed the long-standing cracking issue of conventional polycrystalline Ni-rich materials (PC-NMC) in lithium-ion batteries, prompting a shift in optimization strategies. However, continued reliance on anisotropic lattice volume change—a well-established failure indicator in PC-NMC—as a metric for understanding strain and guiding compositional design for SC-NMC becomes controversial. Here, in this study, by leveraging multiscale diagnostic techniques, we unravelled the distinct nanoscopic strain evolution in SC-NMC during battery operation, challenging the conventional composition-driven strategies and mechanical degradation indicators used for PC-NMC. Through particle-level chemomechanical analysis, we reveal a decoupling between mechanical stability and lattice volume change in SC-NMC, identifying that structural instability in SC materials is primarily driven by multidimensional lattice distortions induced by kinetics-driven reaction heterogeneity and progressively deactivating chemical phases. Using this mechanical failure mode, we redefine the roles of cobalt and manganese in maintaining mechanical stability. Unlike cobalt’s detrimental role in PC-NMC, we find cobalt to be critical in enhancing the longevity of SC-NMC by mitigating localized strain along the extended diffusion pathway, whereas manganese exacerbates mechanical degradation.

36 MATERIALS SCIENCE↗