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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 523 records · Page 29

eMosaic: Electrification Mosaic Platform for Grid Informed Smart Charging Management (Final Scientific/Technical Report)

ABB (Prime Contractor), in collaboration with its partners at the Utah State University (USU), Idaho National Laboratory, Rocky Mountain Power (RMP), and Electric Power Engineers (EPE), have performed research, development, and wide scale demonstration of a scalable and resilient Electrification Mosaic (eMosaic) platform for Smart Charge Management (SCM) for Electric Vehicle Infrastructure. Work was completed under DE EE0009194, titled “eMosaic Electrification Mosaic Platform for Grid Informed Smart Charging Management”, funded by the US Department of Energy. The project members developed algorithms that provide localized and bulk grid services and that reduce and stabilize costs all the way down the supply chain to the PEV owner through SCM. This platform aggregates telemetry from multiple data sources as pieces of the larger picture including personal, private fleet or transportation EVs, fast chargers and other supply equipment, weather service information, and geographically distributed charging sites such as public lots, garage and retail, and private or shared usage depots. ABB and the project team designed, tested, and improved a charging management system at local/edge and cloud levels. The ultimate objective of the project was to convincingly demonstrate that the developed secure eMosaic plat-form can be readily and favorably adopted by diverse utilities and site owners at scale. This was achieved through a demonstration plan with field deployment at several physical sites across 4 states and additional scalable simulation from high fidelity charging models.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Multi-task Parallelism for Robust Pre-training of Graph Foundation Models on Multi-source, Multi-fidelity Atomistic Modeling Data

Graph foundation models using graph neural networks promise sustainable, efficient atomistic modeling. To tackle challenges of processing multi-source, multi-fidelity data during pre-training, recent studies employ multi-task learning, in which shared message passing layers initially process input atomistic structures regardless of source, then route them to multiple decoding heads that predict data-specific outputs. This approach stabilizes pre-training and enhances a model’s transferability to unexplored chemical regions. Preliminary results on approximately four million structures are encouraging, yet questions remain about generalizability to larger, more diverse datasets and scalability on supercomputers. We propose a multi-task parallelism method that distributes each head across computing resources with GPU acceleration. Implemented in the open-source HydraGNN architecture, our method was trained on over 24 million structures from five datasets and tested on the Perlmutter, Aurora, and Frontier supercomputers, demonstrating efficient scaling on all three highly heterogeneous super-computing architectures.

Lupo Pasini, Massimiliano [ORNL] (ORCID:0000000249↗

Comparative Study of Zinc Cold-Spray Coating and Pre-treatments for Magnesium Alloys

Magnesium (Mg) alloys are appealing for automotive lightweighting owing to their high specific strength. However, their susceptibility to corrosion in harsh environments remains a major challenge. Conventional industrial pre-treatment coatings, including zinc phosphate, chromate conversion, and non-chromate conversion, often exhibit discontinuities and microcracks, leading to localized corrosion near fasteners and parting lines. Here, this study investigates cold-sprayed zinc (Zn) coatings as a novel pre-treatment alternative for high-pressure die cast (HPDC) AZ91 Mg alloys, demonstrating significant improvements in wear and corrosion performance. Cold spray produces uniform and robust coatings, reducing wear rate by over 50% and reducing corrosion rate by over 99.3%, as measured by evolved hydrogen release, compared to traditional pre-treatments. Multimodal corrosion testing reveals that Zn cold-spray coatings form a protective layer during exposure, minimizing general and filiform corrosion, and exhibiting corrosion potential (E corr ) that is nobler by ~ 400 mV than the surfaces of both pre-treated and uncoated AZ91. Scalability of cold spray for selective application around multimaterial joints further strengthens their industrial viability. This work establishes Zn cold-spray coatings as highly effective pre-treatment solutions for the advancement of corrosion resistant Mg alloy components in automotive applications.

multimodal corrosion↗

The DAQ system of the 12,000 channel CMS high granularity calorimeter prototype

The CMS experiment at the CERN LHC will be upgraded to accommodate the 5-fold increase in the instantaneous luminosity expected at the High-Luminosity LHC (HL-LHC). Concomitant with this increase will be an increase in the number of interactions in each bunch crossing and a significant increase in the total ionising dose and fluence. One part of this upgrade is the replacement of the current endcap calorimeters with a high granularity sampling calorimeter equipped with silicon sensors, designed to manage the high collision rates. As part of the development of this calorimeter, a series of beam tests have been conducted with different sampling configurations using prototype segmented silicon detectors. In the most recent of these tests, conducted in late 2018 at the CERN SPS, the performance of a prototype calorimeter equipped with ≈12,000 channels of silicon sensors was studied with beams of high-energy electrons, pions and muons. This paper describes the custom-built scalable data acquisition system that was built with readily available FPGA mezzanines and low-cost Raspberry Pi computers.

47 OTHER INSTRUMENTATION↗

Exploration of structure-activity relationships for the SARS-CoV-2 macrodomain from shape-based fragment linking and active learning

The macrodomain of severe acute respiratory syndrome coronavirus 2 nonstructural protein 3 is required for viral pathogenesis and is an emerging antiviral target. We previously performed an x-ray crystallography–based fragment screen and found submicromolar inhibitors by fragment linking. However, these compounds had poor membrane permeability and liabilities that complicated optimization. Here, we developed a shape-based virtual screening pipeline—FrankenROCS. We screened the Enamine high-throughput collection of 2.1 million compounds, selecting 39 compounds for testing, with the most potent binding with a 130 μM median inhibitory concentration (IC 50 ). We then paired FrankenROCS with an active learning algorithm (Thompson sampling) to efficiently search the Enamine REAL database of 22 billion molecules, testing 32 compounds with the most potent binding with a 220 μM IC 50 . Further optimization led to analogs with IC 50 values better than 10 μM. This lead series has improved membrane permeability and is poised for optimization. FrankenROCS is a scalable method for fragment linking to exploit synthesis-on-demand libraries.

Science & Technology - Other Topics↗

Automated Segmentation of Twin Boundaries in TRISO Silicon Carbide Using Deep Neural Networks

Coated particle fuels, such as the tristructural isotropic (TRISO) fuel particle, are essential for high-temperature gas reactor (HTGR) applications due to their efficiency and stability under normal and off-normal conditions. However, widespread commercialization and deployment of this technology for next-generation nuclear applications require robust quality assurance and quality control (QA/QC) methods linking fabrication, properties, and performance. Of the many important metrics for TRISO QA/QC, quantification of the silicon carbide (SiC) microstructure is critical because it correlates with fission product retention during irradiation. Previous work has shown extensive twinning of the SiC microstructure, which strongly affects microstructural metrics; however, twin grain boundaries are not expected play a significant role in fission product diffusion. This report summarizes the initial development, training, and testing of a machine learning image processing algorithm to detect twin grain boundaries in a backscattered electron image, which can be removed so that microstructural metrics can be recalculated for legacy data. Further development and deployment of this model will provide automated, scalable improvement of potential QA/QC methods for the SiC layer of TRISO particles.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

JGI Plant Transformation Workshop, May 20-21, 2025

Domestic biomass crops such as sorghum, switchgrass, Miscanthus, and poplar can provide United States industries with renewable feedstocks while also supporting low-input farming systems and strengthening supply chains for biofuels, biochemicals and biomaterials. The U.S. leads globally in biomass crop genomics, yet progress in engineering traits is constrained by slow, genotype-dependent transformation methods and lengthy Design-Build-Test-Learn (DBTL) cycles. At a May 2025 workshop, a panel of experts recommended establishing a DOE Plant Transformation Capability (PTC) to overcome these barriers. The PTC would unite two missions: advancing research to achieve genotype-independent, automated methods, and delivering scalable transformation services through a user-facility model. With expected gains of 10–100x in efficiency, including transformation and cost reduction, the PTC would accelerate the path from discovery to engineered plants, expand community access and training, and support downstream applications and workflows including field trials and regulatory navigation. By enabling rapid and predictable crop engineering, the PTC would strengthen U.S. supply chains, enhance industrial competitiveness, and ensure that DOE’s genomic investments deliver national impact.

09 BIOMASS FUELS↗

Helicopter Model Rotor-Blade Vortex Interaction Impulsive Noise: Scalability and Parametric Variations

Acoustic data taken in the anechoic Deutsch-Niederlaendischer Windkanal (DNW) have documented the blade-vortex interaction (BVI) impulsive noise radiated from a 1/7-scale model main rotor of the AH-1 series helicopter. Averaged model-scale data were compared with averaged full-scale, in-flight acoustic data under similar non-dimensional test conditions using an improved data analysis technique. At low advance ratios (mu = 0.164 - 0.194), the BVI impulsive noise data scale remarkably well in level, waveform, and directivity patterns. At moderate advance ratios (mu = 0.224 - 0.270), the scaling deteriorates, suggesting that the model-scale rotor is not adequately simulating the full-scale BVI noise. Presently, no proved explanation of this discrepancy exists. Measured BVI noise radiation is highly sensitive to all of the four governing nondimensional parameters--hover tip Mach number, advance ratio, local inflow ratio, and thrust coefficient.

Boxwell, D. A.↗

Net Shape Spin Formed Cryogenic Aluminum Lithium Cryogenic Tank Domes for Lower Cost Higher Performance Launch Vehicles

With the goal of lower cost (simplified manufacturing and lower part count) and higher performance (higher strength to weight alloys) the NASA Technical Maturation Program in 2006 funded a proposal to investigate spin forming of space launch vehicle cryogenic tank domes. The project funding continued under the NASA Exploration Technology Development Program through completion in FY12. The first phase of the project involved spin forming of eight, 1 meter diameter "path finder" domes. Half of these were processed using a concave spin form process (MT Aerospace, Augsburg Germany) and the other half using a convex process (Spincraft, Boston MA). The convex process has been used to produce the Ares Common Bulkhead and the concave process has been used to produce dome caps for the Space Shuttle light weight external tank and domes for the NASDA H2. Aluminum Lithium material was chosen because of its higher strength to weight ratio than the Aluminum 2219 baseline. Aluminum lithium, in order to obtain the desired temper (T8), requires a cold stretch after the solution heat treatment and quench. This requirement favors the concave spin form process which was selected for scale up. This paper describes the results of processing four, 5.5 meter diameter (upper stage scale) net shaped spin formed Aluminum Lithium domes. In order to allow scalability beyond the limits of foundry and rolling mills (about 12 foot width) the circular blank contained one friction stir weld (heavy lifter scales require a flat blank containing two welds). Mechanical properties data (tensile, fracture toughness, stress corrosion, and simulated service testing) for the parent metal and weld will also be discussed.

Curreri, Peter A.↗

Validation of Gas-Liquid Sharp Interface Model in Loci-Stream for Propellant Tank Self-pressurization under Normal Gravity

Deep space missions require advances in cryogenic fluid management (CFM) for long term storage of propellants. One of the important phenomena is self-pressurization due to heat leakages into the tank. Managing self-pressurization is one of the key technologies for deep space exploration and long-term space missions. The complex interactions involving natural convection, thermal gradients, turbulence, and phase change near the gas-liquid interface cannot be modeled using reduced order or nodal analysis models, and 3-D CFD analyses are necessary to fully characterize the dynamics. CFD analyses pose their own difficulties. The requisite CFD tool to tackle this problem need to be modular with the ability to incorporate various physics models, efficient, and computationally scalable for simulating flight size tanks. In this paper, we discuss modeling approach for self-pressurization in situations where the liquid interface is static and validate NASA MSFC’s Loci-Stream CFD solver for predicting self-pressurization in a test tank in normal gravity. This tank was designed to capture quantifiable and accurate data for understanding various two-phase fluid phenomena and to validate modeling tools. Specifically, we demonstrate the capability of the Loci-Stream solver with a two-phase sharp-interface treatment to predict self-pressurization of a tank with an unperturbed gas-liquid interface. This validation highlights the reliability of our modeling approach and our solver to serve as a design and analysis tool for NASA’s CFM application needs.

cryogenic fluid management↗

Validation of Gas-Liquid Sharp Interface Model in Loci-Stream for Propellant Tank Self-pressurization under Normal Gravity

Deep space missions require advances in cryogenic fluid management (CFM) for long term storage of propellants. One of the important phenomena is self-pressurization due to heat leakages into the tank. Managing self-pressurization is one of the key technologies for deep space exploration and long-term space missions. The complex interactions involving natural convection, thermal gradients, turbulence, and phase change near the gas-liquid interface cannot be modeled using reduced order or nodal analysis models, and 3-D CFD analyses are necessary to fully characterize the dynamics. CFD analyses pose their own difficulties. The requisite CFD tool to tackle this problem need to be modular with the ability to incorporate various physics models, efficient, and computationally scalable for simulating flight size tanks. In this paper, we discuss modeling approach for self-pressurization in situations where the liquid interface is static and validate NASA MSFC's Loci-Stream CFD solver for predicting self-pressurization in a test tank in normal gravity. This tank was designed to capture quantifiable and accurate data for understanding various two-phase fluid phenomena and to validate modeling tools. Specifically, we demonstrate the capability of the Loci-Stream solver with a two-phase sharp-interface treatment to predict self-pressurization of a tank with an unperturbed gas-liquid interface. This validation highlights the reliability of our modeling approach and our solver to serve as a design and analysis tool for NASA's CFM application needs.

cryogenic fluid management↗

Tailoring Corrosion Resistance of Additively Manufactured Metals with Atomic Layer Deposition

The goal of this work is to develop a scalable post-manufacturing capability at LANL that utilizes atomic layer deposition (ALD) for corrosion-resistant coatings onto additively manufactured (AM) metals. This will provide fundamentally new and essential capabilities towards the interchangeability of AM metals with traditionally wrought or machined material. This will be accomplished by (1) formulating novel ALD precursor doses and film thicknesses onto as-printed coupons of AM metals and (2) providing electrochemical characterization of corrosion susceptibility as a function of deposited film thickness. While ALD is well-established, the unique aspect (risk) of this work is application to rough AM surfaces. This risk is mitigated by repeating ALD deposition cycles, where thicker coatings laterally branch, resulting in a uniform coating. This risk will be assessed in the phase 1 feasibility study, wherein the application of ALD coatings to small AM coupon surfaces will be demonstrated using existing hardware and characterization tools at Sigma. This study alone will provide ground-breaking insight on the compatibility of ALD coating techniques with AM metals. Going beyond the phase 1 study, a standalone deposition chamber will be built, so full AM components can be coated and tested. While this MFR investment is focused on corrosion mitigation, it is critical to highlight external benefits of this technique outside the scope of this proposed study. ALD has extraordinary universality, whereby almost any material can be given almost any coating or graded density coating with atomic precision; and, the only limiting factors to scalability is the size of the dosing chamber. The self-limiting reactions intrinsic to ALD offers high conformity to part geometry and tolerance, even for internal surfaces where electroplating or conventional chemical vapor deposition falls short due to differential diffusion. This uniquely positions ALD at the forefront of post-manufacturing strategies for AM components, especially for those with complex geometry and internal surfaces.

36 MATERIALS SCIENCE↗

Asymptotic-preserving semi-implicit finite volume scheme for extended magnetohydrodynamics

A Finite Volume (FV) scheme is developed for solving the extended magnetohydrodynamic (XMHD) equations, yielding accurate results in the ideal, resistive, and Hall MHD limits. This is accomplished by first re-writing the XMHD equations such that it allows the algorithm to retain the use of ideal MHD Riemann solvers and the constrained transport method to preserve divergence-free magnetic fields. Incorporation of electron inertia and displacement current introduces additional numerical stiffness which motivates a semi-implicit FV scheme that re-formulates the XMHD model as a relaxation system. The equations are then advanced in time using an explicit 2nd-order Runge–Kutta scheme with operator splitting applied to the implicit source term updates at each sub-stage. For additional numerical stability, a density-dependent slope limiter is implemented to increase flux diffusivity at low density regions where non-ideal effects become significant. The algorithm is subsequently implemented in a scalable adaptive mesh refinement (AMR) framework. As the new algorithm retains many aspects of the ideal MHD formulations, it asymptotes naturally to the ideal MHD limit. Moreover, it shows promising results at the resistive and Hall MHD limits. This is verified against reference test problems for ideal, resistive and Hall MHD.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Antimicrobial properties of a multi-component alloy

High traffic touch surfaces such as doorknobs, countertops, and handrails can be transmission points for the spread of pathogens, emphasizing the need to develop materials that actively self-sanitize. Metals are frequently used for these surfaces due to their durability, but many metals also possess antimicrobial properties which function through a variety of mechanisms. This work investigates metallic alloys comprised of several metals which individually possess antimicrobial properties, with the target of achieving broad-spectrum, rapid sanitation through synergistic activity. An entropy-motivated stabilization paradigm is proposed to prepare scalable alloys of copper, silver, nickel and cobalt. Using combinatorial sputtering, thin-film alloys were prepared on 100 mm wafers with ≈50% compositional grading of each element across the wafer. The films were then annealed and investigated for alloy stability. Antimicrobial activity testing was performed on both the as-grown alloys and the annealed films using four microorganisms—Phi6, MS2, Bacillus subtilis and Escherichia coli —as surrogates for human viral and bacterial pathogens. Testing showed that after 30 s of contact with some of the test alloys, Phi6, an enveloped, single-stranded RNA bacteriophage that serves as a SARS-CoV-2 surrogate, was reduced up to 6.9 orders of magnitude (> 99.9999%). Additionally, the non-enveloped, double-stranded DNA bacteriophage MS2, and the Gram-negative E. coli and Gram-positive B. subtilis bacterial strains showed a 5.0, 6.4, and 5.7 log reduction in activity after 30, 20 and 10 min, respectively. Antimicrobial activity in the alloy samples showed a strong dependence on the composition, with the log reduction scaling directly with the Cu content. Concentration of Cu by phase separation after annealing improved activity in some of the samples. The results motivate a variety of themes which can be leveraged to design ideal antimicrobial surfaces.

36 MATERIALS SCIENCE↗

CO 2 Mineralization Using Porous Carbon and Industrial Wastes to Make Multifunctional Concrete

Along with substantial benefits and promises of carbon capture and storage (CCS) technologies, significant challenges exist in developing scalable materials and methods for capture and of CO 2 . The overarching objective of this project is to provide a system approach for developing a new CO 2 capture and utilization technology using porous carbon and industrial wastes to make a low-cost, scalable and multifunctional concrete product. The objective of Phase I of this project is to develop and fine-tune activated carbons from different wastes such as plastic wastes to offer a cheap, abundant and scalable feedstock for CO 2 uptake. The objective of Phase 2 is creating a facile protocol to develop a concrete prototype comprising CO 2 adsorbed activated carbon (e.g. from plastic wastes), followed by product validation, life-cycle analysis, and bench-scale testing. The project objectives are designed to specifically obtain a final product and technology that directly addresses the main goals of the DOE’s CCS programs.

01 COAL, LIGNITE, AND PEAT↗

NRC Multiphysics Analysis Capability Deployment (FY2020--Part 3)

This report details progress and activities of Idaho National Laboratory (INL) on the NRC project ”Development and Modeling Support for Advanced Non-Light Water Reactors.” The tasks completed for this report are as follows: First, Task 2c: Explicit modeling of pebble transient temperature response. In this simulation, the PBMR-400 reactor experiences a 20 second power ramp from 100% to 150% power. This is followed by a similar reduction in the power back to 100%. Several multiscale pebble coupling approaches are tested with one pebble per mesh element in the active core region. The results show good conservation behavior and the stability of the coupling. Next, Extended scope part 1: An assessment of the computational efficiency of the DFEM heat transfer solver shows good scalability. The DFEM solver is a factor of 4 more expensive in solution time than the FEM solver for heat transfer problems due to the increased number of degrees of freedom. Nonetheless, the DFEM approach provides the user with the flexibility to model gap heat transfer problems. Then Extended scope part 2: the GapHeatTransferInterfaceMaterial was improved to give the user increased flexibility with the modeling of heat transfer through gaps with the DFEM solver. A number of gap parameters can now be coupled both through functions and variables. Finally, Extended scope part 3: demonstration of how the gap width between hexagonal fuel cells can be calculated during a heat up transient and used in the GapHeat- TransferInterface model. A full domain DFEM model with gap expansion is coupled to a SubApp that models the thermal expansion of the base plate. The results show the expected physical behavior, although have not been fully bench- marked at this point in time.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Novel Approaches to the Isolation of Glucaric Acid from Fermentation Broth. Final report

Kalion has successfully demonstrated a fermentation route using glucose as the feedstock. This game-changing technology allows Kalion to economically produce large-scale quantities of high-purity glucaric acid products. Kalion has also developed a novel downstream processing strategy for isolating and purifying glucaric acid forms, including the free acid, monoammonium glucarate, and monopotassium glucarate. Despite the low solubility of these products, significant water removal is needed prior to crystallization, requiring energy intensive evaporation or reverse osmosis. Here, we work in collaboration with the Separations Consortium to develop novel, low-cost means of water removal in Kalion’s glucarate/glucaric acid purification process. This proposed CRADA project with national labs (ORNL, ANL, and NREL) evaluated various technologies developed by the Separations Consortium as applied to glucaric acid purification, intended to generate a scalable, cost-effective, energy-efficient process. Four approaches were evaluated with mock aqueous solutions of glucaric acid or glucarate, and the results analyzed with respect to separation effectiveness and potential cost savings. The leading technology will then be further developed and tested with actual clarified or non-clarified broth (depending on the approach) obtained from 20L fermentations provided by Kalion, that will contain inorganic ions, byproducts, and residual sugars in addition to the product.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

High Resolution Aerospace Applications using the NASA Columbia Supercomputer

This paper focuses on the parallel performance of two high-performance aerodynamic simulation packages on the newly installed NASA Columbia supercomputer. These packages include both a high-fidelity, unstructured, Reynolds-averaged Navier-Stokes solver, and a fully-automated inviscid flow package for cut-cell Cartesian grids. The complementary combination of these two simulation codes enables high-fidelity characterization of aerospace vehicle design performance over the entire flight envelope through extensive parametric analysis and detailed simulation of critical regions of the flight envelope. Both packages. are industrial-level codes designed for complex geometry and incorpor.ats. CuStomized multigrid solution algorithms. The performance of these codes on Columbia is examined using both MPI and OpenMP and using both the NUMAlink and InfiniBand interconnect fabrics. Numerical results demonstrate good scalability on up to 2016 CPUs using the NUMAIink4 interconnect, with measured computational rates in the vicinity of 3 TFLOP/s, while InfiniBand showed some performance degradation at high CPU counts, particularly with multigrid. Nonetheless, the results are encouraging enough to indicate that larger test cases using combined MPI/OpenMP communication should scale well on even more processors.

Mavriplis, Dimitri J.↗