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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 757 records · Page 42

A Stochastic Reduced-Order Model for Statistical Microstructure Descriptors Evolution

Integrated computational materials engineering (ICME) models have been a crucial building block for modern materials development, relieving heavy reliance on experiments and significantly accelerating the materials design process. However, ICME models are also computationally expensive, particularly with respect to time integration for dynamics, which hinders the ability to study statistical ensembles and thermodynamic properties of large systems for long time scales. To alleviate the computational bottleneck, we propose to model the evolution of statistical microstructure descriptors as a continuous-time stochastic process using a non-linear Langevin equation, where the probability density function (PDF) of the statistical microstructure descriptors, which are also the quantities of interests (QoIs), is modeled by the Fokker–Planck equation. In this work, we discuss how to calibrate the drift and diffusion terms of the Fokker–Planck equation from the theoretical and computational perspectives. The calibrated Fokker–Planck equation can be used as a stochastic reduced-order model to simulate the microstructure evolution of statistical microstructure descriptors PDF. Considering statistical microstructure descriptors in the microstructure evolution as QoIs, we demonstrate our proposed methodology in three integrated computational materials engineering (ICME) models: kinetic Monte Carlo, phase field, and molecular dynamics simulations.

97 MATHEMATICS AND COMPUTING↗

OpenFerro v0.1.0

OpenFerro is a Python package for on-lattice atomistic dynamics simulation of ferroic materials. OpenFerro is based on JAX, a high-performance linear algebra package supporting auto-differentiation and GPU acceleration. OpenFerro is designed to minimize the effort required to build on-lattice Hamiltonian models, and to perform molecular dynamics (MD) and Landau-Lifshitz-Gilbert simulations. Unlike existing codes, OpenFerro provides a unified interface to model different types of local order parameters.

Xie, Pinchen [Lawrence Berkeley National Laborator↗

Putting error bars on density functional theory dataset

This dataset contains submission files and raw output files from high-throughput DFT simulations to analyze the systemic errors in lattice constant, bulk moduli and formation energy predictions for a range of binary and ternary oxides using four exchange correlation functionals (LDA, PBE, PBEsol and vdW-DF-C09). This data was then used as the basis for employing materials informatics methods to predict the expected errors in the lattice constants of the studied compounds. Predicted errors were also used to better the DFT-predicted lattice parameters. Our results emphasize the link between the computed errors and the electron density and hybridization errors of a functional. In essence, these results provide “error bars” for choosing a functional for the creation of high-accuracy, high-throughput datasets as well as avenues for the development of XC functionals with enhanced performance, thereby enabling the accelerated discovery and design of new materials.

36 MATERIALS SCIENCE↗

JLAB LLRF 3.0 Development and Tests

The Jefferson Lab LLRF 3.0 system is being developed to replace legacy LLRF systems in the CEBAF accelerator. The new design builds upon 25 years of design and operational RF control experience, and our recent collaboration in the design of the LCLSII LLRF system. The new cavity control algorithm is a fully functional phase and amplitude locked Self Exciting Loop (SEL). This paper discusses the progress of the LLRF 3.0 hardware design, FPGA firmware development, User Datagram Protocol (UDP) operation, and recent LLRF 3.0 system tests on the CEBAF Booster cryomodule in the Upgrade Injector Test Facility (UITF).

Plawski, T. E.↗

A Taxonomy for Classification and Comparison of Dataflows for GNN Accelerators

Recently, Graph Neural Networks (GNNs) have received a lot of interest because of their success in learning representations from graph structured data. However, GNNs exhibit different compute and memory characteristics compared to traditional Deep Neural Networks (DNNs). Graph convolutions require feature aggregations from neighboring nodes (known as the aggregation phase), which leads to highly irregular data accesses. GNNs also have a very regular compute phase that can be broken down to matrix multiplications (known as the combination phase). All recently proposed GNN accelerators utilize different dataflows and microarchitecture optimizations for these two phases. Different communication strategies between the two phases have been also used. However, as more custom GNN accelerators are proposed, the harder it is to qualitatively classify them and quantitatively contrast them. In this work, we present a taxonomy to describe several diverse dataflows for running GNN inference on accelerators. This provides a structured way to describe and compare the design-space of GNN accelerators.

97 MATHEMATICS AND COMPUTING↗

AI-enhanced Codesign for Next-Generation Neuromorphic Circuits and Systems

This report details work that was completed to address the Fiscal Year 2022 Advanced Science and Technology (AS&T) Laboratory Directed Research and Development (LDRD) call for “AI-enhanced Co-Design of Next Generation Microelectronics.” This project required concurrent contributions from the fields of 1) materials science, 2) devices and circuits, 3) physics of computing, and 4) algorithms and system architectures. During this project, we developed AI-enhanced circuit design methods that relied on reinforcement learning and evolutionary algorithms. The AI-enhanced design methods were tested on neuromorphic circuit design problems that have real-world applications related to Sandia’s mission needs. The developed methods enable the design of circuits, including circuits that are built from emerging devices, and they were also extended to enable novel device discovery. We expect that these AI-enhanced design methods will accelerate progress towards developing next-generation, high-performance neuromorphic computing systems.

42 ENGINEERING↗

Machine learning for optimizing the manufacture and operation of intermediate temperature fuel cells

The project developed machine learning and artificial intelligence (ML/AI) methodologies for guiding and accelerating the materials design and processing of new high temperature proton conducing electrode ionomer binders and reinforced membranes for high-temperature proton exchange membrane fuel cell (HT-PEMFC; aka intermediate-temperature polymer electrolyte membrane fuel cells).

08 HYDROGEN↗

Realizing Steady-State Microbunching with Optical Stochastic Crystallization

Optical Stochastic Cooling (OSC) is a state-of-the-art beam cooling technology first demonstrated in 2021 at the IOTA storage ring at Fermilab's FAST facility. A second phase of the research program is planned to run in 2026 and will incorporate an optical amplifier to enable significantly increased cooling rates and greater operational flexibility. In addition to beam cooling, an OSC system can be configured to enable advanced control over the phase space of the beam. An example operational mode could enable crystallization, where the particles in a bunch are locked into a self-reinforcing, regular microstructure at the OSC fundamental wavelength; we refer to this as Optical Stochastic Crystallization (OSX). OSX represents a new path toward Steady-State Microbunching (SSMB), which may enable light sources combining the high brightness of a free-electron laser with the high repetition rate of a storage ring. Such a source has applications from the terahertz to the extreme ultraviolet (EUV), including high-power EUV generation for semiconductor lithography. This contribution will discuss the integration of OSX development as part of the OSC program at IOTA. The design of an accelerator lattice to enable the mechanism and associated high fidelity simulations will be shown, and a path to realizing an experimental demonstration will be discussed.

Wallbank, Michael James [Fermilab]↗

Rheo–Electric Foundations and Engineering of Carbon Slurry Flow Electrodes

Flowable carbon slurry electrodes promise continuous, scalable electrochemical desalination and energy storage when their rheology (flow and stability) and electronic connectivity are jointly optimized. This report integrates six complementary thrusts that we executed under the Laboratory Directed Research and Development (LDRD) project: (i) a fast, ex situ, centrifuge-compatible method to quantify pellet (packed slurry) electronic conductivity, with a validated cell constant (“shape factor”) and quantitative structure–property insights for carbon mixtures; (ii) a controlled circulation study showing that peristaltic pumping can irreversibly alter particle size and morphology over laboratory-relevant durations; (iii) development of a miniature jet pump that preserves particle integrity while achieving entrainment ratios of 2–4 at practical flow rates; (iv) a comprehensive mapping of how a representative non-ionic surfactant (Tween 20) collapses the carbon gel network, separating network-percolation losses from intrinsic particle contact resistance; (v) in-situ visualization revealing how gravitational settling and flow-driven mixing compete to control charge transport, with dynamic bed layers preventing saturation while achieving 30-fold local concentration enhancement; and (vi) a simple, widely adoptable fabrication route to structured, gas-nitrided titanium nitride (TiN) titanium current collectors that dramatically lower interfacial losses and enable geometry-driven performance gains. Together, these results provide a coherent toolchain and design rules to accelerate formulation screening, de-risk device prototyping, and standardize characterization for carbon slurry electrodes in flow-electrode capacitive deionization (FCDI), electrochemical flow capacitor (EFC), and related systems.

25 ENERGY STORAGE↗

Update on PIP-II beam pattern generator upgrade

The beam pattern generator enables the transfer of beam pulses from the PIP-II linac to the Booster ring, the two RF systems being non-harmonically related. It is synchronized to the timing system to provide beam arrival information to the downstream accelerator subsystems. The design is being upgraded with COTS components and is being developed with a collaboration with SLAC.The pattern generation, digital signal processing and the user interface to an external EPICS server are integrated onto the ARM processor of the SOCFPGA. The progress of the system development is described.

Varghese, P. [Fermilab]↗

Superconducting qubits for particle detection and fundamental tests of quantum mechanics

Many fundamental questions at the interface of quantum mechanics, gravity, and measurement remain relatively unexplored in the laboratory. These include whether spatial superpositions experience gravitational redshift, how the quantum Zeno effect propagates through entangled systems, and whether quantum information is globally conserved or fundamentally lost during measurement-induced wavefunction collapse. In this colloquium, I will discuss how superconducting qubits—developed primarily for quantum computing—can be repurposed as ultra sensitive detectors to probe these questions and to search for low-energy particle interactions. I will describe my work at Fermilab on stabilizing these devices to the level required for next-generation qubit-based sensors. This includes mitigating decoherence from infrared radiation and cosmic rays, using machine-learning techniques to accelerate superconducting qubit design, and leveraging the quantum Zeno effect to improve coherence times and suppress qubit frequency fluctuations. Together, these advances point toward a new class of quantum sensors capable of testing fundamental physics.

Seidel, Olivia [Fermilab]↗

Steady-State Microbunching using Optical Stochastic Cooling

Optical Stochastic Cooling (OSC) is a state-of-the-art beam cooling technology first demonstrated in 2021 at the IOTA storage ring at Fermilab's FAST facility. A second phase of the research program is planned to run in 2026 and will incorporate an optical amplifier to enable significantly increased cooling rates and greater operational flexibility. In addition to beam cooling, an OSC system can be configured to enable advanced control over the phase space of the beam. An example operational mode could enable crystallization, where the particles in a bunch are locked into a self-reinforcing, regular microstructure at the OSC fundamental wavelength; we refer to this as Optical Stochastic Crystallization (OSX). OSX represents a new path toward Steady-State Microbunching (SSMB), which may enable light sources combining the high brightness of a free-electron laser with the high repetition rate of a storage ring. Such a source has applications from the terahertz to the extreme ultraviolet (EUV), including high-power EUV generation for semiconductor lithography. This contribution will discuss the integration of OSX development as part of the OSC program at IOTA. The design of an accelerator lattice to enable the mechanism and associated high fidelity simulations demonstrating the beam dynamics will be shown, and a path to realizing an experimental demonstration will be discussed.

Wallbank, Michael James [Fermilab]↗

Examples of State and Utility Actions on Proactive Planning and Investments

As states across the U.S. confront rising electricity demand, clean energy deployment, grid modernization imperatives, and the integration of large new loads, some regulators and utilities are shifting away from reactive, “just-in-time” investment approaches toward more proactive planning and investment frameworks. This report compiles examples of jurisdictional and utility actions that reshape planning processes, cost recovery mechanisms, and performance oversight to anticipate—rather than simply respond to—future grid needs. Several themes emerge from state actions examined in this report. First, legislatures and commissions are increasingly directing utilities to proactively upgrade their distribution and transmission systems, reflecting a shift toward a forward-looking system that aligns planning with state policy goals. Second, states are establishing long-term, iterative planning frameworks that often feature multi-year horizons, biannual or annual compliance reporting, structured opportunities for stakeholder engagement, and emphasis on collaboration among utilities, regulators, and stakeholders. Third, states are actively investigating innovative cost recovery mechanisms designed to support accelerated electrification and grid modernization, while balancing consumer advocates’ concerns regarding the ratepayer financial risks of premature investments. Fourth, performance metrics and reporting requirements are being developed to ensure transparency and accountability for proactive investments. Fifth, methodological improvements in planning—such as aligning load forecasting assumptions, incorporating sensitivities, and considering load management potential across building, vehicles, storage, and demand response—are recurring areas of stakeholder focus across jurisdictions. Overall, these developments signify a growing recognition among state regulators, utilities, and stakeholders that proactive planning—supported by clear definitions, consistent and transparent methodologies, robust performance metrics, and innovative cost recovery mechanisms—is a tool that can be used to address the scale and urgency of contemporary grid needs.

electricity market↗

Development and Validation of Low-Cost, High-Reflectance Composite CSP Facets: SIPS Final Report

This work investigates the various challenges associated with developing heliostat structural composite facets using 1 mm glass mirrors. Such facets are desirable for Concentrating Solar Power because 1 mm glass mirrors provide an absolute increase in reflectivity of 2-3 % over the industry standard of 4 mm glass mirrors. Prototypes of paraboloid composite facets with 1 mm glass mirrors were constructed that have a root mean square slope error on the order of 2 mrad while achieving greater than 96% reflectivity. These facets were constructed using a low-quality aluminum mold and a bill of materials that show potential to achieve cost parity with existing 4 mm glass mirrors supported by structural steel. The facets produced were able to survive up to 50 mm hail ball impacts and were robust against accelerated environmental cycling designed to expose durability concerns. Further work is needed to develop a scalable and cost-effective manufacturing process with a similar bill of materials.

14 SOLAR ENERGY↗

Results of the Low Speed Aeroelastic Buffet Test with a 0.046-scale Model (747-ax1322-d-3/orbiter 8-0) of the 747 Cam/orbiter in the University of Washington Wind Tunnel (CS 3)

A series of wind tunnel studies designed to assess the potential buffet problems resulting from orbiter wake characteristics with its tailcone removed are presented to provide design loads and acceleration environments, and to develop data on buffet sensitivity to various aerodynamic configurations and flight parameters. Data are intended to support subsequent analyses of structural fatigue life, crew efficiency, and equipment vibrations.

Gillins, R. L.↗

Lithium cell tests at Marshall Space Flight Center

Three 18 AH Li-CF batteries with a polypropylene separator and using dimethyl sulfite in Li as F6 for the electrolyte will be placed in each shuttle solid rocket booster for range safety and frustrum location aid. Mechanical vibration, acceleration, random and design vibration, and discharge evaluation tests are discussed.

Paschal, L. E.↗

Ion propulsion and Comet Halley rendezvous

Cometary rendezvous missions using ion propulsion is considered. The characteristics of the ion engine are discussed including the fuel efficiency and acceleration, and the design of the ion engine is described. The operation of the ion drive engine and an overview of its applications are presented.

Atkins, K. L.↗