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

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

3D Reconstruction of a High-Energy Diffraction Microscopy Sample Using Multi-modal Serial Sectioning with High-Precision EBSD and Surface Profilometry

High-energy diffraction microscopy (HEDM) combined with in situ mechanical testing is a powerful nondestructive technique for tracking the evolving microstructure within polycrystalline materials during deformation. This technique relies on a sophisticated analysis of X-ray diffraction patterns to produce a three-dimensional reconstruction of grains and other microstructural features within the interrogated volume. However, it is known that HEDM can fail to identify certain microstructural features, particularly smaller grains or twinned regions. Characterization of the identical sample volume using high-resolution surface-specific techniques, particularly electron backscatter diffraction (EBSD), can not only provide additional microstructure information about the interrogated volume but also highlight opportunities for improvement of the HEDM reconstruction algorithms. In this study, a sample fabricated from undeformed “low solvus, high refractory” nickel-based superalloy was scanned using HEDM. The volume interrogated by HEDM was then carefully characterized using a combination of surface-specific techniques, including epi-illumination optical microscopy, zero-tilt secondary and backscattered electron imaging, scanning white light interferometry, and high-precision EBSD. Custom data fusion protocols were developed to integrate and align the microstructure maps captured by these surface-specific techniques and HEDM. The raw and processed data from HEDM and serial sectioning have been made available via the Materials Data Facility (MDF) at https://doi.org/10.18126/4y0p-v604 for further investigation.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Neural Networks for Prediction of Complex Chemistry in Water Treatment Process Optimization

Water chemistry plays a critical role in the design and operation of water treatment processes. Detailed chemistry modeling tools use a combination of advanced thermodynamic models and extensive databases to predict phase equilibria and reaction phenomena. The complexity and formulation of these models preclude their direct integration in equation-oriented modeling platforms, making it difficult to use their capabilities for rigorous water treatment process optimization. Neural networks (NN) can provide a pathway for integrating the predictive capability of chemistry software into equation-oriented models and enable optimization of complex water treatment processes across a broad range of conditions and process designs. Herein, we assess how NN architecture and training data impact their accuracy and use in equation-oriented water treatment models. We generate training data using PhreeqC software and determine how data generation and sample size impact the accuracy of trained NNs. The effect of NN architecture on optimization is evaluated by optimizing hypothetical black-box desalination processes using a range of feed compositions from USGS brackish water data set, tracking the number of successful optimizations, and testing the impact of initial guess on the final solution. Our results clearly demonstrate that data generation and architecture impact NN accuracy and viability for use in equation-oriented optimization problems.

Dudchenko, Alexander V↗
DOE OSTI2025

Nucleon structure studies: DVCS on polarised protons with the CLAS12 experiment, and development of Micromegas detectors for EIC

The quark and gluon structure of nucleons is crucial for understanding the origin of their mass and spin. This information is encoded in structure function such as Generalised Parton Distributions (GPDs), which provide a three-dimensional picture of the nucleon in terms of its constituents. Deeply Virtual Compton Scattering (DVCS) offers the most direct access to GPDs, but their extraction requires high-precision measurements of multiple observables over a wide kinematic range. In 2022 and 2023 the CLAS12 experiment at Jefferson Lab (JLab) collected data from polarised electron scattering on a longitudinally polarised proton target, enabling the first measurement of polarised DVCS asymmetries at JLab 12GeV kinematics. This thesis will present preliminary measurement of the beam, target and double spin DVCS asymmetries from the CLAS12 polarised proton target data. Nucleon structure studies will also constitute a major part of the physics program at the future Electron Ion Collider (EIC). The development of the first detector at the EIC is ongoing and it requires light Micro-Pattern Gaseous Detectors (MPGDs) for its tracking system. This thesis further reports initial tests of Micromegas MPGDs with a two-dimensional readout developed for EIC.

Polcher, Samy [Univ. Paris-Saclay, Gif-sur-Yvette ↗
DOE OSTI2026

Near-field passive sensor for the monitoring of high-temperature oxidative corrosion of metals

This study reports on the development and testing of a passive wireless device designed to track temperature and corrosion behavior in SS304H stainless steel under elevated temperatures. The ANSYS HFSS software was utilized to model and optimize the design of an inductor-capacitor (LC) resonator passive wireless sensors fabricated using platinum designs printed onto an aluminum oxide support operating at frequencies between (50–190 MHz). The optimal LC wireless sensor designs were then fabricated using screen-printing and sintering methods. Here, the sensors were tested by placing the sensor onto polished SS304H flat substrates and heated to 900–1050 °C in air. Wireless acquisition of sensor data during heating, cooling, and isothermal stages was achieved through a Pt loop antenna connected to an RF signal generator and a network analyzer.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2024

Monitoring Helium Cryogen Usage with iFix Software at IB1 Test Facility

At the IB1 facility of the Applied Physics and Superconducting Technology Directorate within the Cryogenic Division at Fermilab, liquid helium is essential to the testing activities. The test stands used require large amounts of Helium to test the thermal and superconducting cavities and magnets. The liquid helium that enters the test stand is monitored through a series of valves and controls to determine the start and stop for monitoring time. There are 3 phases of cryogen usage that must be considered for each stand, cooldown, warming and overnight mode. With a new system in place, cold hour tracking will be more objective and precise within each test stand ensuring better calculations for user s fees that will provide funding for the replenishment of helium and continual operation at IB1.

Trillo, Angelica↗
DOE OSTI2024

Monitoring Helium Cryogen Usage with iFix Software at IB1 Test Facility

At the IB1 facility of the Applied Physics and Superconducting Technology Directorate within the Cryogenic Division at Fermilab, Liquid Helium is essential to the testing activities. The test stands require large amounts of Helium to test the thermal and superconducting cavities and magnets. The Liquid Helium that enters the test stand is monitored through a series of valves and controls to determine the start and stop for monitoring time. There are 3 phases of cryogen usage that must be considered for each stand, cooldown, warming and overnight mode. With a new system in place, cold hour tracking will be more objective and precise within each test stand ensuring better calculations for User s fees which are charged to various groups that employ the facility and aid replenishment of Helium and continual operation at IB1.

Trillo, Angelica↗
DOE OSTI2024

Beam test performance studies of CMS Phase-2 Outer Tracker module prototypes

A new tracking detector will be installed as part of thePhase-2 upgrade of the CMS detector for the high-luminosity LHC era.This tracking detector includes the Inner Tracker, equipped withsilicon pixel sensor modules, and the Outer Tracker, consisting ofmodules with two parallel stacked silicon sensors. The Outer Trackerfront-end ASICs will be able to correlate hits from chargedparticles in these two sensors to perform on-module discriminationof transverse momenta (p$_{T}$). The p$_{T}$information is generated at a frequency of 40 MHz and will be usedin the Level-1 trigger decision of CMS. Prototypes of theso-called 2S modules were tested at the Test Beam Facility at DESYHamburg between 2019 and 2020. These modules use the finalfront-end ASIC, the CMS Binary Chip (CBC), and for the firsttime the Concentrator Integrated Circuit (CIC), optical readoutand on-module power conversion. In total, seven modules were tested,one of which was assembled with sensors irradiated with protons. Animportant aspect was to show that it is possible to read out modulessynchronously. A cluster hit efficiency of about 99.75 % wasachieved for all modules. The CBC p$_{T}$ discriminationmechanism has been verified to work together with the CIC andoptical readout. The measured module performance meets therequirements for operation in the upgraded CMS tracking detector.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Central transcriptional regulator controls photosynthetic growth and carbon storage in response to high light

Carbon capture and biochemical storage are some of the primary drivers of photosynthetic yield and productivity. To elucidate the mechanisms governing carbon allocation, we designed a photosynthetic light response test system for genetic and metabolic carbon assimilation tracking, using microalgae as simplified plant models. The systems biology mapping of high light-responsive photophysiology and carbon utilization dynamics between two variants of the same Picochlorum celeri species, TG1 and TG2 elucidated metabolic bottlenecks and transport rates of intermediates using instationary 13 C-fluxomics. Simultaneous global gene expression dynamics showed 73% of the annotated genes responding within one hour, elucidating a singular, diel-responsive transcription factor, closely related to the CCA1/LHY clock genes in plants, with significantly altered expression in TG2. Transgenic P. celeri TG1 cells expressing the TG2 CCA1/LHY gene, showed 15% increase in growth rates and 25% increase in storage carbohydrate content, supporting a coordinating regulatory function for a single transcription factor.

09 BIOMASS FUELS↗
DOE OSTI2025

Superheating gold beyond the predicted entropy catastrophe threshold

In their landmark study, Fecht and Johnson unveiled a phenomenon that they termed the ‘entropy catastrophe’, a critical point where the entropy of superheated crystals equates to that of their liquid counterparts. This point marks the uppermost stability boundary for solids at temperatures typically around three times their melting point. Despite the theoretical prediction of this ultimate stability threshold, its practical exploration has been prevented by numerous intermediate destabilizing events, colloquially known as a hierarchy of catastrophes, which occur at far lower temperatures. Here we experimentally test this limit under ultrafast heating conditions, directly tracking the lattice temperature by using high-resolution inelastic X-ray scattering. Our gold samples are heated to temperatures over 14 times their melting point while retaining their crystalline structure, far surpassing the predicted threshold and suggesting a substantially higher or potentially no limit for superheating. We point to the inability of our samples to expand on these very short timescales as an important difference from previous estimates. These observations provide insights into the dynamics of melting under extreme conditions.

Laser-produced plasmas↗
DOE OSTI2025

Heat load measurements for the PIP-II pHB650 cryomodule

This study presents a brief overview of the 1st and 2nd phases and an in-depth analysis of the 3rd phase heat load testing performed on the pHB650 (prototype High Beta 650 MHz) cryomodule at PIP2IT (PIP-II Injector Test Facility), with a focus on both the results and the methodological advancements that have improved testing efficiency and accuracy. A key challenge identified in the testing campaign is the higher-than-expected heat loads observed in the first PIP-II (Proton Improvement Plan II) prototype cryomodules (pSSR1 and pHB650) tested at PIP2IT. Elevated heat loads are concerning given the fixed capacity of the PIP-II cryoplant that is currently being installed at Fermilab. However, understanding the sources of these elevated heat loads offers a critical opportunity to implement effective heat load mitigations on upcoming PIP-II cryomodules to stay within the available capacity of the PIP-II cryoplant. The study includes a summary of test results, descriptions of measurement procedures, and key observations on parameters directly and indirectly related to heat load measurements. Direct observations include measured heat loads and the effectiveness of JT heat exchanger under varying conditions, while indirect observation analyze factors such as the temperature distribution on the two-phase pipe and relief piping under varying conditions. Thermal acoustic oscillations (TAO) were identified during testing, which was mitigated by replacing the original G10 stem with a stainless steel stem equipped with wipers for the cryomodule cooldown valve. A major innovation during pHB650 Phase 3 testing was the development of an automated Python script to streamline data acquisition, analysis, and reporting of heat load results. This script automatically retrieved data from ACNET (Accelerator Control Network), performed heat load calculations, and generated detailed reports featuring plots and tables. This advancement significantly reduced manual labor and enhanced the thoroughness of data analysis compared to earlier campaigns. The heat load test reports were promptly uploaded to the electronic logbook shortly after each test, enabling rapid feedback and collaboration between the SRF and cryogenic teams. The heat load measurements included various components: HTTS (high-temperature thermal shield), LTTS (low-temperature thermal shield), 2K isothermal and non-isothermal heat loads. Results were recorded both within the cryomodule and between the bayonet can supply and return. Measurements were conducted under different operating conditions such as "standard", "linac", and "simulated dynamic". Additionally, HTTS and LTTS heat loads were calculated in real time, allowing for the tracking of thermal stability and identification of changes during testing, both in steady-state and transient conditions. The results of this testing campaign not only provide valuable insights into the performance of the pHB650 cryomodule but also highlight best practices and lessons learned that will inform future cryomodule testing at PIP2IT. These include adopting automated tools for data analysis, refining real-time measurement capabilities, and emphasizing detailed pre-test planning. The framework established in this campaign aims to set an improved standard for cryomodule testing and heat load reporting in future cryomodule test campaigns.

Porwisiak, D. [Fermilab; Wroclaw Tech. U.]↗
DOE OSTI2025

Geometric GNNs for charged particle tracking at GlueX

Nuclear physics experiments are aimed at uncovering the fundamental building blocks of matter. The experiments involve high-energy collisions that produce complex events with many particle trajectories. Tracking charged particles resulting from collisions in the presence of a strong magnetic field is critical to enable the reconstruction of particle trajectories and precise determination of interactions. It is traditionally achieved through combinatorial approaches that scale worse than linearly as the number of hits grows. Since particle hit data naturally form a point cloud and can be structured as graphs, graph neural networks (GNNs) emerge as an intuitive and effective choice for this task. In this study, we evaluate the GNN model for track finding on the data from the GlueX experiment at Jefferson Lab. We use simulation data to train the model and test on both simulation and real GlueX measurements. We demonstrate that GNN-based track finding outperforms the currently used traditional method at GlueX in terms of segment-based efficiency at a fixed purity while providing faster inferences. We show that the GNN model can achieve significant speedup by processing multiple events in batches, which exploits the parallel computation capability of graphical processing units (GPUs). Finally, we compare the GNN implementation on GPU and field-programmable gate array and describe the trade-off.

batched GNN pipeline↗
DOE OSTI2024

Performance of the first mechanically-coupled twisting heliostat: encircled energy vs angle of incidence, and closed loop tracking

The first automatic twisting heliostat, with 8 m2 reflector, was completed and tested on-sun in January 2024. It was set up on a target-oriented dual-axis mount, with the target-axis aimed at a target 113 m to the west. The shape-twisting is purely automatic, made by a mechanical cam coupling to the cross-axis, which turns as the angle of incidence of the sun’s rays on the reflector. Three unsaturated images taken at different times of day were recorded of the sun on the target, reflected at angles of incidence of 5°, 49° and 68°. The measured FWHM of three images is very similar, about 1.09 m or 9.5 mrad, only slightly larger than an ideal solar disc, indicating that the different twisted reflector shapes are close to the ideal biconics needed to image the sun. The encircled energy measured for all three images was similar, 87% within approximately 1.30 m diameter. We report here also on a novel, tracking camera that employs a semitransparent beamsplitter fixed perpendicular to the mirror surface and to the plane of incidence. Over 2.5 hours of measurement of closed loop tracking, errors were ≤ 0.36 mrad rms, in both tracking axes.

14 SOLAR ENERGY↗
DOE OSTI2025

Probing the PeV region in the astrophysical neutrino spectrum using 𝜈 𝜇 from the Southern sky

IceCube has observed a diffuse astrophysical neutrino flux over the energy region from a few TeV to a few PeV. At PeV energies, the spectral shape is not yet well measured due to the low statistics of the data. This analysis probes the gap between 1 and 10 PeV by using high-energy downgoing muon neutrinos. Here, to reject the large atmospheric muon background, two complementary techniques are combined. The first technique selects events with high stochasticity to reject atmospheric muon bundles whose stochastic energy losses are smoothed due to high muon multiplicity. The second technique vetoes atmospheric muons with the IceTop surface array. Using 9 yrs of data, we found two neutrino candidate events in the signal region, consistent with expectation from background, each with relatively high signal probabilities. A joint maximum likelihood estimation is performed using this sample and an independent 9.5-yr sample of tracks to measure the neutrino spectrum. A likelihood ratio test is done to compare the single power-law (SPL) vs SPL+cutoff hypothesis; the SPL+cutoff model is not significantly better than the SPL. High-energy astrophysical objects from four source catalogs are also checked around the direction of the two events. No significant coincidence was found.

Abbasi, R. [Loyola University Chicago] (ORCID:0000↗
DOE OSTI2024

Aerosol Envelope Sealing of Existing Residences

This report explores the best methods for aerosol envelope sealing of unoccupied, existing residences and documents typical leakage reductions. The project consisted of three distinct efforts: (1) scaled field demonstrations of the sealing process, tracking from setup to sealing and cleanup, (2) laboratory testing of new sealants that dry clear, making them more appropriate for retrofit applications, and (3) BEopt™ (Building Energy Optimization Tool) modeling of the energy implications of the measured reductions in leakage. Overall, aerosol sealing performance in existing homes was effective, with an average leakage reduction of 47% across all 34 sites. Conventional approaches typically only produce leakage reductions of 25%–30%. The aerosol sealing technology could provide a process for existing homes and multifamily units to gain the benefits of a well-sealed home at a reasonable cost with minimal disruption.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

An Educational Program on Concentrated Solar Power and Heliostats for Power Generation and Industrial Processes

The objective of this project was to design and implement a comprehensive educational and applied research program in Concentrated Solar Thermal Power (CSTP) and heliostat technologies at Northeastern University. In alignment with the U.S. Department of Energy's Heliostat Consortium (HelioCon) goals, the project aimed to expand student and public understanding of CSTP systems while simultaneously contributing to workforce development and the broader decarbonization strategy. A particular emphasis was placed on integrating hands-on student design projects and publicly disseminating educational content relevant to CSTP systems. The project addressed a critical gap in renewable energy education: CSTP and heliostats, despite their importance in utility-scale solar energy, are rarely included in standard mechanical engineering programs. This project established new pathways for students to engage with the topic through the creation of a 4-credit graduate/senior elective course, development of five industry-facing short courses, and the inclusion of CSTP-based capstone design projects. Over two academic years, 36 students across six senior design teams developed and tested technologies such as deformable heliostats, beacon-based tracking systems, and solar-powered pyrolizers for biomass-to-biochar conversion. Concurrently, 30 undergraduate and graduate students were enrolled in the new academic course centered around CSTP principles. To ensure the relevance and accessibility of the short course content, the project team engaged with industry professionals, technical policy stakeholders, and potential course participants through structured surveys and informal consultations. Feedback from 28 respondents guided the structure, length, and delivery format of the courses - resulting in a modular design broken into five workshops. The feedback emphasized the need for flexible, asynchronous delivery and practical case studies, particularly in areas such as heliostat control, thermal storage, and solar fuel production. This engagement helped align the courses with the evolving knowledge demands of the renewable energy workforce and ensured that participants from both technical and policy backgrounds could meaningfully benefit from the material. The research and educational activities advanced the understanding of heliostat control systems, optical performance under misalignment, and thermal system integration in solar-driven pyrolysis applications. Methods and designs explored in this project proved to be both technically effective and economically feasible at the lab scale. Prototypes were constructed using commercially available components and custom-fabricated elements, demonstrating that meaningful performance improvements can be achieved with modest material and fabrication costs, supporting the feasibility of student-led research in this field. The public benefit of this project is twofold. First, it cultivates a pipeline of engineers trained to be familiar with CSTP principles, an essential workforce need identified by the Department of Energy for achieving its 2030 cost and deployment targets. Second, it contributes openly accessible educational materials, course content, and experimental frameworks to the broader community, enabling other institutions to adopt or adapt similar programming. Through outreach activities, curriculum integration, and technical exposure, this project contributes to a more informed and capable renewable energy workforce while supporting innovation in heliostat and CSTP system design. A new technical report is being prepared to document the development of the course and its outcomes, with plans to publish it in the ASME Open Access Journal of Engineering to ensure global accessibility, free of cost.

14 SOLAR ENERGY↗
DOE OSTI2026

Beam test results of the Intermediate Silicon Tracker for sPHENIX

The Intermediate Silicon Tracker (INTT), a two-layer barrel silicon strip tracker, is a key component of the tracking system for sPHENIX at the Relativistic Heavy Ion Collider (RHIC) at Brookhaven National Laboratory. The INTT is designed to enable the association of reconstructed tracks with individual RHIC bunch crossings. To evaluate the performance of preproduction INTT ladders and the readout chain, a beam test was conducted at the Research Center for Accelerator and Radioisotope Science, Tohoku University, Japan. This paper presents the performance of the INTT evaluated through studies of the signal-to-noise ratio, residual distribution, spatial resolution, hit-detection efficiency, and multiple track reconstruction.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Optimal control of the electron temperature profile in DIII-D using machine learning surrogate models

The viability of the tokamak as a potential fusion reactor depends on the ability to keep the plasma in a stable regime while achieving temperatures, densities, and confinement times that are as high as possible. Tokamak scenario development attempts to find plasma regimes that achieve all of these conditions and are accessible with a given set of hardware constraints. This requires the ability to control plasma properties such as the normalized beta, the internal inductance, safety factor, rotation, etc. One property that has received less attention than some of the others, but is no less critical to achieving high performance, is the electron temperature (T e ) profile. In this work, Linear Quadratic Integral (LQI) control is used to develop a controller for the electron temperature profile in DIII-D. The controller is based on a linearized model derived from the transport equation that describes the evolution of the electron temperature, and includes contributions from the neural network surrogate models NubeamNet and MMMnet. Furthermore, the controller is tested in simulation using COTSIM, and is proven capable of tracking a target T e profile.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Performance and Durability Investigation of Thin, Low Crossover Proton Exchange Membranes for Water Electrolyzers

The goal of this project was to fabricate and study the performance and durability implications of thin, mechanically reinforced membranes containing gas recombination catalysts (GRCs) for advanced proton exchange membrane water electrolysis (PEMWE) systems. The thinner membranes, optimized for a PEMWE environment, dramatically reduced the proton transport resistance across the membrane, improving the overall efficiency of the PEMWE system. At the same time, the GRC technology was deployed to recombine crossover hydrogen from the cathode with oxygen from the anode to form water within the membrane. This reaction mitigated the buildup of hydrogen in the oxygen stream, ensuring safe operation of the PEMWE system. Capabilities to measure the gas crossover in both an ex-situ screening cell and in operando application testing were developed over the course of the project to track membrane progress and quantify deliverables. State of the art roll to roll manufacturing technologies were leveraged to fabricate the membranes on a commercial scale, where the membrane structure was precisely tuned and GRC distributed within the membrane structure.

08 HYDROGEN↗