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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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DOE OSTI2025

Status and prospects for inertial fusion energy via lasers

Fusion energy is the ultimate clean and limitless energy source, but its development requires overcoming many scientific and technological challenges. For the first time in the 60-year long history of fusion research, ignition and target gain above unity (G>1) were demonstrated in the laboratory at the National Ignition Facility at the Lawrence Livermore National Laboratory in 2022. Turning laser fusion into an energy source requires that the results from single shot experiments be replicated at much higher repetition rates of many shots per second to produce high average power at relatively low cost. Furthermore, this requires the development of new laser technologies, mass production of suitable targets, accurate injection and tracking systems and new materials for the reactor chamber components and final optics. Ultra broadband and deep UV light are laser advances that can dramatically improve the laser energy coupling to the target thereby reducing the laser energy and power requirements.

Fusion energy↗

DOE OSTI2026

DOE EV Data Collection - Maintenance Data

Maintenance data includes information on maintenance performed on the electric vehicles, including preventive maintenance, service calls, and availability of the vehicles. The parameters collected, and their definitions, will vary due to the differences in maintenance tracking systems that exist between fleets. Parameter definitions are detailed in the data dictionary, and specific vehicle information is available in the vehicle attributes table. Vehicle ID can be used as a key between maintenance data and vehicle attribute tables. Data is being uploaded quarterly through 2023 and subject to change until the conclusion of the project.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2024

Performance of Pixel and Strip AC-LGAD Sensors with Different Design Parameter on a 120 GeV Proton Beam

We present the results of an extensive evaluation of strip and pixel AC-LGAD sensors tested with a 120 GeV proton beam, focusing on the influence of design parameters on the sensor temporal and spatial resolutions. Results show that reducing the thickness of pixel sensors significantly enhances their time resolution, with 20- μm-thick sensors achieving around 20 ps. Uniform performance is attainable with optimized sheet resistance, making these sensors ideal for future timing detectors. Conversely, 20-μm-thick strip sensors exhibit higher jitter than similar pixel sensors, negatively impacting time resolution, despite reduced Landau fluctuations with respect to the 50-μm-thick versions. Additionally, it is observed that a low resistivity in strip sensors limits signal size and time resolution, whereas higher resistivity improves performance. This study highlights the importance of tuning the n+ sheet resistance and suggests that further improvements should target specific applications like the Electron-Ion Collider or other future collider experiments. In addition, the detailed performance of four AC-LGADs sensor designs is reported as examples of possible candidates for specific detector applications. These advancements position AC-LGADs as promising candidates for future 4D tracking systems, pending the development of specialized readout electronics.

Lara, Carlos Pérez↗

DOE OSTI2025

Studies of Quark Transport and Hadronization in Nuclei

In this project, we conducted the first measurement of di‑hadron azimuthal correlations in deep inelastic scattering (DIS) off nuclei using the CLAS detector at Jefferson Lab. Using 5 GeV electron‑beam data collected on deuterium, carbon, iron, and lead targets, we extracted di‑pion correlation functions over a broad kinematic range. The results show a monotonic broadening of the correlation peak with increasing nuclear mass, along with pronounced dependencies on the pions’ kinematics. Separately, we implemented an algorithm based on the Kalman filter that achieved the first complete alignment of the CLAS12 central tracking system. In parallel, we developed simulations, algorithms, and performance studies that informed the conceptual designs of the forward hadronic calorimeter Insert and the Zero Degree Calorimeter, both of which are now included in the ePIC detector baseline for the forthcoming Electron Ion Collider.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2025

Reassessment of Dose Contributions from the Paducah Cask Special Waste Form Buried in the E-Area Low-Level Waste Facility

During a recent revision to the groundwater and inadvertent human intruder screening analysis report (Aleman and Hamm, 2023), weaknesses within the screening logic were observed resulting in the addition of U-235 being brought back into the list of radionuclides requiring inventory limits within the Paducah Cask special waste form (SWF). In addition, while reviewing the earlier vadose zone transport analysis efforts, an inconsistency was observed in the initial U-235P inventory that was supplied to the Consolidated Waste Tracking System (CWTS) back in 2009.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2025

Neutrally-buoyant balloons experiment – EMRTC 2025

This memo announces the successful execution of the neutrally-buoyant balloon experiment (EMRTC 2025), conducted at New Mexico Institute of Mining and Technology’s Energetic Materials Research and Testing Center (EMRTC) in Socorro, NM between April 3 and May 9, 2025. The experiment aimed to build on EMRTC 2022 balloon experiment through testing the effects of lateral and vertical displacement of release locations in a different terrain than EMRTC 2022. EMRTC 2025 employed dual GPS trackers on each balloon to provide both detailed near-source motion tracking in addition to the low-frequency long-distance trackers used in EMRTC 2022. A total of 156 neutrally-buoyant balloons were released over the week of May 5-9, which was approximately 2.5 times the number released in the EMRTC 2022 campaign. The dual tracking system will allow characterizing complex three-dimensional wind structures close to terrain features and diurnal wind patterns to validate wind and plume dispersion models for treaty verification.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2025

Towards High-Efficiency Particle Detection Using Superconducting Microwire Arrays

We present a detailed study of an 8-channel $1\times1$~mm$^{2}$ WSi superconducting microwire single photon detector (SMSPD) array exposed to 120~GeV hadron beam and 120~GeV muon beam at the CERN Super Proton Synchrotron H6 beamline. Following up on our first detailed characterization of the efficiency and response of an SMSPD fabricated on a 3~nm WSi film, we report measurements of enhanced particle detection efficiency using a sensor fabricated from a thicker 4.7~nm-thick WSi film. We also report the first SMSPD detection efficiency measurement made for muons. Measurements are enabled by a silicon tracking telescope providing 10~$\mu$m in situ spatial resolution. The results show a detection efficiency of 75\% and a time resolution of about 130~ps across pixels. These findings represent a significant advancement toward developing high-efficiency SMSPD charged particle tracking systems with simultaneous precision timing, with potential applications in future accelerator-based experiments such as the FCC-ee and Muon Collider.

Wang, Christina [Fermilab]↗

DOE OSTI2026

Bayesian Optimization of The Relativistic Heavy Ion Collider Luminosity via s * Control

A state-of-the-art jet detector named sPHENIX was proposed, commissioned, and operated at the Rel ativistic Heavy Ion Collider (RHIC) from 2023 to 2025. This detector featured precision tracking and calorime try that enable high-statistics studies of the Quark Gluon Plasma through jet modification, upsilon suppres sion, and open heavy flavor production. The innermost component of the three sPHENIX tracking systems is the Monolithic-Active-Pixel-Sensor-based Vertex Detec tor (MVTX) (Fig. 1), which has an acceptance within | s | < 0.1m of the interaction point (IP).

43 PARTICLE ACCELERATORS↗

DOE OSTI2025

Intelligent experiments through real-time AI: Fast Data Processing and Autonomous Detector Control for sPHENIX and future EIC detectors

This R&D project, initiated by the DOE Nuclear Physics AI-Machine Learning initiative in 2022, leverages AI to address data processing challenges in high-energy nuclear experiments (RHIC, LHC, and future EIC). Our focus is on developing a demonstrator for real-time processing of high-rate data streams from sPHENIX experiment tracking detectors. The limitations of a 15 kHz maximum trigger rate imposed by the calorimeters can be negated by intelligent use of streaming technology in the tracking system. The approach efficiently identifies low momentum rare heavy flavor events in high-rate p+p collisions (3MHz), using Graph Neural Network (GNN) and High Level Synthesis for Machine Learning (hls4ml). Success at sPHENIX promises immediate benefits, minimizing resources and accelerating the heavy-flavor measurements. The approach is transferable to other fields. For the EIC, we develop a DIS-electron tagger using Artificial Intelligence - Machine Learning (AI-ML) algorithms for real-time identification, showcasing the transformative potential of AI and FPGA technologies in high-energy nuclear and particle experiments real-time data processing pipelines.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

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

PV Fleet Performance Data Initiative 2026 Update

We provide an update on the PV Fleet Performance Data Initiative at the 2026 PV Reliability Workshop. Our latest runs incorporate additional data sources and an integrated analysis pipeline run on our Kestrel HPC cluster. Initial degradation findings suggest that single-axis tracked PV systems exhibit higher performance loss rates than fixed-tilt systems, an increase of 0.5 %/yr, almost double. We discuss multiple methods for identifying stuck tracker rows, which are suspected to be a contributor to the enhanced degradation. Through satellite image detection and data-driven approaches we address the topic of identifying when stuck trackers are occuring and to what extent the problem exists. Preliminary results suggest that the increased performance loss detected for the tracked systems would be consistent with stuck tracker rows affecting on the order of 5% - 10% of the system.

14 SOLAR ENERGY↗

DOE OSTI2025

Coupling Remote Sensing With a Process Model for the Simulation of Rangeland Carbon Dynamics

Rangelands provide significant environmental benefits through many ecosystem services, which may include soil organic carbon (SOC) sequestration. However, quantifying SOC stocks and monitoring carbon (C) fluxes in rangelands are challenging due to the considerable spatial and temporal variability tied to rangeland C dynamics as well as limited data availability. We developed the Rangeland Carbon Tracking and Management (RCTM) system to track long-term changes in SOC and ecosystem C fluxes by leveraging remote sensing inputs and environmental variable data sets with algorithms representing terrestrial C-cycle processes. Bayesian calibration was conducted using quality-controlled C flux data sets obtained from 61 Ameriflux and NEON flux tower sites from Western and Midwestern US rangelands to parameterize the model according to dominant vegetation classes (perennial and/or annual grass, grass-shrub mixture, and grass-tree mixture). The resulting RCTM system produced higher model accuracy for estimating annual cumulative gross primary productivity (GPP) (R 2 > 0.6, RMSE <390 g C m -2 ) relative to net ecosystem exchange of CO 2 (NEE) (R 2 > 0.4, RMSE <180 g C m -2 ). Model performance in estimating rangeland C fluxes varied by season and vegetation type. The RCTM captured the spatial variability of SOC stocks with R 2 = 0.6 when validated against SOC measurements across 13 NEON sites. Model simulations indicated slightly enhanced SOC stocks for the flux tower sites during the past decade, which is mainly driven by an increase in precipitation. Future efforts to refine the RCTM system will benefit from long-term network-based monitoring of vegetation biomass, C fluxes, and SOC stocks.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

Analysis of the elliptic integrable non-linear system in IOTA using tracking of a single electron

Integrable nonlinear lattices that can be realized in practical accelerators are of great interest, as they offer the potential to support high-intensity beams via Landau damping of collective instabilities. One such system, based on an elliptic potential, has been extensively studied at the IOTA storage ring at Fermilab. The analysis of strongly nonlinear dynamics with multi-particle bunches is challenging due to the rapid decoherence of kicked beams. IOTA has the capability to track single electrons using linear multi-anode photomultiplier tubes for simultaneously measuring transverse coordinates and arrival times of synchrotron-radiation pulses. This technology enables the full reconstruction of turn-by-turn positions and momenta in all three planes for a single particle. Using this apparatus, we measured the dependence of small-amplitude tunes on the strength of the nonlinear magnet, as well as tunes dependence on oscillations amplitudes.

Romanov, A. [Fermilab]↗

DOE OSTI2025

Analysis of the Elliptic Integrable Non-Linear System in IOTA Using Tracking of a Single Electron

Romanov, Aleksandr Leonidovich [Fermilab] (ORCID:0↗

DOE OSTI2025

Dynamic motion trajectory control with nanoradian accuracy for multi-element X-ray optical systems via laser interferometry

The past decades have witnessed the development of new X-ray beam sources with brightness growing at a rate surpassing Moore’s law. Current and upcoming diffraction limited and fully coherent X-ray beam sources, including multi-bend achromat based synchrotron sources and high repetition rate X-ray free electron lasers, puts increasingly stringent requirements on stability and accuracy of X-ray optics systems. Parasitic motion errors at sub-micro radian scale in beam transport and beam conditioning optics can lead to significant loss of coherence and brightness delivered from source to experiment. To address this challenge, we incorporated optical metrology based on interferometric length and angle sensing and real-time correction as part of the X-ray optics motion control system. A prototype X-ray optics system was constructed following the optical layout of a tunable X-ray cavity. On-line interferometric metrology enabled dynamical feedback to a motion control system to track and compensate for motion errors. The system achieved sub-microradian scale performance, as multiple optical elements are synchronously and continuously adjusted. This first proof of principle measurement demonstrated both the potential and necessity of incorporating optical metrology as part of the motion control architecture for large scale X-ray optical systems such as monochromators, delay lines, and in particular, X-ray cavity systems to enable the next generation cavity-based X-ray free electron lasers.

47 OTHER INSTRUMENTATION↗

DOE OSTI2025

yProv4ML: Effortless provenance tracking for machine learning systems

The rapid growth in interest in deep learning and foundation models (FMs) in particular, has attracted the attention of a diverse range of researchers thanks to their generalization ability. However, the advent of these techniques has also brought to light the lack of transparency and rigor in the way development is pursued. In particular, the inability to determine the number of epochs and other hyperparameters in advance presents challenges in identifying the best model. To address this challenge, machine learning frameworks such as MLFlow can automate the collection of this type of information. However, these tools capture data using proprietary formats and pose little attention to lineage. This paper proposes yProv4ML, a framework that captures provenance information generated during machine learning processes in PROV-JSON format, with minimal code modification.

Machine learning↗

DOE OSTI2025

Virtual sensing-enabled digital twin framework for real-time monitoring of nuclear systems leveraging deep neural operators

Abstract Real-time monitoring is a foundation of nuclear digital twin technology, crucial for detecting material degradation and maintaining nuclear system integrity. Traditional physical sensor systems face limitations, particularly in measuring critical parameters in hard-to-reach or harsh environments, often resulting in incomplete data coverage. Machine learning-driven virtual sensors offer a transformative solution by complementing physical sensors in monitoring critical degradation indicators. This paper introduces the use of Deep Operator Networks (DeepONet) to predict key thermal-hydraulic parameters in the hot leg of pressurized water reactor. DeepONet acts as a virtual sensor, mapping operational inputs to spatially distributed system behaviors without requiring frequent retraining. Our results show that DeepONet achieves low mean squared and Relative L2 error, making predictions 1400 times faster than traditional CFD simulations . These characteristics enable DeepONet to function as a real-time virtual sensor, synchronizing with the physical system to track degradation conditions and provide insights within the digital twin framework for nuclear systems.

Hossain, Raisa↗

DOE OSTI2025

A Cost-Effective Wave Energy Harvesting System with Maximum Power Point Tracking Capability

In this paper, we propose a low-cost bidirectional four-switch inverter that transfers three-phase energy between a permanent magnet synchronous generator (PMSG) driven by a wave energy collector and the power grid or a local ac load. To achieve high control performance, the machine-side inverter uses a high-gain observer for rotor position estimation and a Lyapunov-based approach for torque control. For the gridside inverter control, we estimate the filter capacitor voltage with a model reference adaptive system and control the dc-link voltage with a Lyapunov-based energy function. We also track the maximum power point from the sea waves with an integral control law that actively matches the generator impedance with that of the wave collection device. The proposed system supports both grid-following/forming modes. We validate our control design with simulation results on a 3-kW hardware setup.

wave energy, power systems integration, control de↗