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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 163 records · Page 9

Software for High-Resolution Flood Mapping With Sentinel-1 and Sentinel-2 via Misalignment-Robust Cross-Sensor Learning and Generative Despeckling

SF-26-078 This software provides a high-level workflow for satellite-based flood and surface-water mapping using Sentinel-1 SAR and Sentinel-2 multispectral imagery. It supports preparation of remote-sensing data, training and evaluation of deep-learning models, and generation of high-resolution water extent predictions, including methods to improve robustness to SAR speckle noise and cross-sensor image misalignment.

Feinstein, Jeremy [Argonne National Laboratory (AN↗

Towards robust laser beam propagation in atmospheric turbulence

High-fidelity optical propagation through the atmosphere is essential for free-space optical technologies, including laser-based remote sensing and optical communication. However, atmospheric turbulence severely distorts beams and compromises system performance. In this work, we employ hypergeometric-Gaussian (HyGG) vortex beams as probes to characterize and mitigate atmospheric turbulence. Using over 250,000 experimental and simulated frames, we show that refining the power spectrum density (PSD) can reduce numerical prediction errors by up to 79.8%. Concurrently, experimental observations supported by numerical simulations demonstrate that HyGG beams exhibit superior turbulence resilience across multiple metrics compared to conventional Gaussian beams, particularly in their ability to withstand over 5 times stronger turbulence while maintaining similar intensity fluctuations. These dual investigations, on both turbulence mitigation and robust beam solutions, converge to form a unified strategy for enhancing free-space optical system performance. Collectively, our findings provide new insights into light–turbulence interactions and highlight the practical utility of vortex beams under atmospheric conditions.

Zhang, Boyu↗

Design and fabrication of robust hybrid photonic crystal cavities

Abstract Heterogeneously integrated hybrid photonic crystal cavities enable strong light–matter interactions with solid state, optically addressable quantum memories. A key challenge to realizing high quality factor ( Q ) hybrid photonic crystals is the reduced index contrast on the substrate compared to suspended devices in air. This challenge is particularly acute for color centers in diamond because of diamond’s high refractive index, which leads to increased scattering loss into the substrate. Here, we develop a design methodology for hybrid photonic crystals utilizing a detailed understanding of substrate-mediated loss, which incorporates sensitivity to fabrication errors as a critical parameter. Using this methodology, we design robust, high-Q, GaAs-on-diamond photonic crystal cavities, and by optimizing our fabrication procedure, we experimentally realize cavities with Q approaching 30,000 at a resonance wavelength of 955 nm.

Abulnaga, Alex↗

Innovations in Direct Air Capture: Unveiling a Simple and Robust Synthesized Fibrous Amine-functionalized Matrix (FAM) Sorbent for Commercial Scale-up

The escalating challenge of climate change necessitates innovative solutions in the realm of carbon management, particularly in mitigating the impact of fossil fuel emissions. Direct Air Capture (DAC) technology emerged as a critical component within the spectrum of Carbon Capture and Sequestration (CCS) solutions, offering the distinct advantage of directly removing CO2 from the atmosphere irrespective of the source. This attribute grants DAC systems unparalleled flexibility in deployment locations and the potential to make substantial contributions to lowing atmospheric CO2 levels. The success of DAC technologies significantly depends on the development of an efficient, economical sorbent capable of selective and durable CO2 capture from ambient air. Recent advancements in material science have led to the exploration of amine-functionalized sorbents, hollow fiber sorbents and membranes, and other novel materials designed to meet these criteria. This study explores a novel Fibrous Amine-functionalized Matrix (FAM) sorbent. The FAM sorbent distinguished itself through its mechanical robustness, a streamlined synthesis process, and the capability for low-temperature regeneration (is 90 oC really low temperature?). FAM’s exceptional adsorption-desorption kinetics enable swift CO2 capture and release, crucial for the viability of DAC on a commercial scale. The synthesis process involves a simple dip-coating technique, allowing crosslinked amines to coat glass substrates.

Wang, Qiuming↗

Advancements in Direct Air Capture: Unveiling a Simple and Robust Synthesized Fibrous Amine-functionalized Matrix (FAM) Sorbent for Commercial Scale-up

The escalating challenge of climate change necessitates innovative solutions in the realm of carbon management, particularly in mitigating the impact of fossil fuel emissions. Direct Air Capture (DAC) technology emerges as a critical component within the spectrum of Carbon Capture and Sequestration (CCS) solutions, offering the distinct advantage of directly removing CO2 from the atmosphere irrespective of the source. This attribute grants DAC systems unparalleled flexibility in deployment location sand the potential to make substantial contributions to lowing atmospheric CO2 levels. The success of DAC technologies significantly depends on the development of efficient, economical sorbent capable of selective and durable CO2 capture from ambient air. Recent advancements in material science have led to the exploration of amine-functionalized sorbents, hollow fiber sorbents and membranes, and other novel materials designed to meet these criteria. This study introduces a significant advancement in DAC technology with the development of a Fibrous Amine-functionalized Matrix (FAM) sorbent. The FAM sorbent distinguished itself through its mechanical robustness, a streamlined synthesis process, and the capability for low-temperature regeneration. Its exceptional adsorption-desorption kinetics enable swift CO2 capture and release, crucial for the viability of DAC on a commercial scale.

Wang, Qiuming↗

Robust Size-Effects Compensation Through Regularized Lever-Arm Estimation

Size effects are an unavoidable nuisance in inertial navigation using sensors which are not co-located at the navigational point of interest. When estimating transforms between the navigation point and sensor locations, some trajectories preclude observation of all model parameters. Regularization is proposed to avoid over-fitting size-effects models. The result yields robust size effects compensation in other regions of flight.

42 ENGINEERING↗

Robust resonator-assisted ZZ cancellation in superconducting quantum processors

Strong qubit interactions are essential for faster two-qubit gates, but they often come with undesirable ZZ interactions that limit gate fidelity. Existing methods to mitigate these interactions, such as flux-tunable couplers, can introduce additional noise and complexity. In contrast, our work presents a simpler, more robust approach using a driven resonator to cancel the static ZZ interaction between qubits [1]. The experiment was performed on a revised 9-qubit quantum processing unit from Rigetti, developed in collaboration with SQMS scientists. We validate the resonator-induced-phase (RIP) interaction, where an off-resonant drive on the resonator dynamically cancels ZZ coupling. This marks an important step toward high gate fidelities. We also explore the entangling gates enabled by this coupling scheme, focusing on minimizing gate duration and qubit decoherence while maintaining effective ZZ cancellation.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

SMART SiC Power ICs: Scalable, Manufacturable, and Robust Technology for SiC Power Integrated Circuits (Final Technical Report)

This collaborative project was initiated with the goal of developing Scalable, Manufacturable, and Robust Technology for SiC Power Integrated Circuits (SMART SiC Power ICs). In pursuit of this objective, innovative designs and fabrication processes were implemented, enabling the development of large-scale (>1 cm²) SiC Complementary Metal-Oxide-Semiconductor (CMOS) integrated circuits and high-voltage (400–600 V) lateral power MOSFETs (HV-LDMOS) on 150 mm 4H-SiC substrates. The resulting SMART SiC Power ICs are tailored to support a wide range of applications requiring diverse voltage and power levels, including automotive systems, industrial equipment, electronic data processing, energy harvesting, and power conditioning. To achieve the proposed ‘SMART’ technology for SiC ICs, the team focused on 1) the Development of highly scalable CMOS (with high channel mobilities for n-type and p-type MOSFETs), LDMOS (~600V, 10A rated), and IC technologies, 2) Establishment of a manufacturable process baseline in a production-grade-, 150mm, SiC fabrication facility, and 3) Demonstration of SMART SiC ICs. The project initially comprised of fabricating 5 lots. In lot 1 monolithic integration using a single process was achieved. Here, we were able to successfully accomplish Integrated HV NMOSFET with LV CMOS on N-epi/N+ Substrate. The HV NMOS demonstrated a Breakdown Voltage (BV) more than 600V. Circuit demonstration of CMOS was also another achievement from this lot. In lot 2, priority was in place for isolation and integration. Here we addressed the isolation concerns and integrated the HV NMOS and LV CMOS using the N-epi/P-epi/N+ substrate. Similar to the lot 1, we were able to achieve a BV of 600 V for HV NMOS. Optimized gate oxide process with high channel mobilities, better gate oxide reliability, development of SPICE models, successful ohmic process development, novel wafer area saving design layouts, P+ isolation schemes with channeling implantations and high temperature operational circuits demonstrations are some of the key highlights from lot 1 and lot2. In lot 3, discrete device performances of HV NMOS with a BV ~700V and reliable LV CMOS performances were achieved. Also, novel architectural solutions were successfully implemented to suppress the electric field crowding at the gate oxide for reliable operations. In lot 4, half bridge power driver ICs with a conversion efficiency of (target 90% to 95%) in the 1-5MHz switching frequency range for output power between 25 W to 3 kW have been included in. However, due to the unfortunate events of sudden foundry shutdown (SiCamore Semi) the processing of lot 4 wafers came to a complete stop (January 2024). Arrangements have recently been made to shift the fabrication to another foundry, General Electric Aerospace. The fabrication process now on course (as of December 2024). Characterizations are delayed due to this unfortunate circumstance. The proposed trench architectural-based devices and ICs (lot 5) underwent modifications from the original project proposal. This change was necessitated by limitations in the availability of trench-based processes at commercial production-grade fabrication facilities in the US. Apart from above achievements, a Process Development Kit (PDK) was successfully developed for planar type SiC CMOS/LDMOS.

42 ENGINEERING↗

INTEGRATE – Inverse Network Transformations for Efficient Generation of Robust Airfoil and Turbine Enhancements

The INTEGRATE (Inverse Network Transformations for Efficient Generation of Robust Airfoil and Turbine Enhancements) project developed a new inverse-design capability for the aerodynamic design of wind turbine rotors using invertible neural networks. Training data was obtained from improved turbulence and transition models for RANS and hybrid RANS/LES solvers with machine-learned physics-based data-augmented corrections and then using the resulting neural-network(s) augmented RANS model to run thousands of 2-D and 3-D CFD simulations.

17 WIND ENERGY↗

Robustness and printed sensor qualification

A limiting factor of additive manufactured (AM) sensors for in-pile applications is the development of appropriate interconnection and packaging strategies that can maintain reliable performance in extreme environments. Failure mechanisms in these harsh conditions could include, but not limited to, materials interaction (i.e., intermetallic formation) and coefficient of thermal expansion (CTE) mismatch between the individual components of the sensors. To mitigate premature failure and enable the successful sustained operation of AM sensors, non-destructive qualification tests are used as an intermediate process control step used for verifying robustness and reliability of the sensor before they are deployed. A materials system of interest is the use of barium strontium titanium oxide (BST) films on stainless steel 316L (SS316L) substrate. Due to BST’s high dielectric constant and tunable dielectric properties, there is an interest for its application as an insulation/encapsulation layer for capacitive strain gauges when printed on structural materials. Previous work on the BST/SS316L material system, however, showed that the BST cracks when exposed to temperatures up to 600 °C due to CTE mismatch between the printed BST film and the metallic substrate. When comparing different fabrication techniques, less surface cracking was observed in the samples that deposited thinner (i.e., 2-20 μm) than samples that were thicker (i.e., 135 µm – 300 µm). The objective of this report is to establish a qualification process that will determine and address any challenges (i.e., mechanical failure of thick prints) of the AM sensor prior to its application in experimental tests. To demonstrate the qualification process in this report, laser spallation and uniaxial tensile tests using dynamic and quasi-static loading, respectively, will be discussed.

36 - MATERIALS SCIENCE↗

Development of Calcined Clay/Calcium Sulfate Blends for Robust Performance of LC3 Concrete

This report documents the development of robust blends of calcined clays (CCs) with calcium sulfate (gypsum) for application in limestone calcined clay cement (LC3) systems. The U.S. cement industry faces supply chain constraints and high energy intensity, motivating the need for alternative supplementary cementitious materials. Calcined clays are abundant and highly reactive when properly processed, but their variable physical and chemical characteristics can negatively impact hydration balance, rheology, and admixture demand in LC3 concretes. To address this, five calcined clays, two Portland cements, ground limestone, gypsum, and a polycarboxylate dispersant were procured. Isothermal calorimetry and mini-cone flow tests were used to determine sulfate and dispersant demand. Results show that the addition of approximately 6.7% gypsum, relative to the calcined clay weight, consistently balanced sulfate consumption across the LC3 systems studied. Dispersant demand, however, varied significantly with clay source, demonstrating the need for tailored admixture strategies. These findings confirm that supplying CC–gypsum blends directly to concrete producers is a viable approach to overcoming current manufacturing constraints, enabling reliable fresh and hardened performance of LC3 concretes, and supporting broader adoption of calcined clays in the U.S. market.

36 MATERIALS SCIENCE↗

Robust Dark Energy Constraints with the Dark Energy Spectroscopic Survey (Final Technical Report)

This project developed and applied advanced theoretical, computational, and data-analysis methodologies to extract robust and precise cosmological constraints from the Dark Energy Spectroscopic Instrument (DESI). The work focused on maximizing the scientific return of DESI through optimized survey strategy, novel higher-order clustering statistics, improved modeling of small-scale structure, and rigorous mitigation of observational systematics. Over the award period, the project made substantial contributions to DESI science planning, produced new methods for bispectrum and three-point correlation function analyses, advanced constraints on primordial non-Gaussianity, and delivered widely used software tools. The project also played a major role in training graduate students and a postdoctoral researcher who contributed directly to DESI key projects. The results have significantly enhanced the cosmological reach of DESI and provide a strong foundation for future surveys such as DESI-II and Stage-V experiments.

79 ASTRONOMY AND ASTROPHYSICS↗

Final Technical Report: Testing the robustness of CMB-S4 inflation measurements to foreground models

This report summarizes the research activities for DOE award SC0024462, which focused on enhancing the robustness of CMB-S4 inflation measurements by characterizing and mitigating Galactic foreground interference. The project grounded foreground models in the physical processes of the Interstellar Medium with MHD and semi-analytic filament models, and developed analysis pipelines, such as Needlet Internal Linear Combination (NILC) techniques, to isolate faint cosmological signals.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

AI in Astrophysics: Tackling Domain Shift, Model Robustness and Uncertainty

Artificial Intelligence (AI) is revolutionizing physics research from probing the large-scale structure of the Universe to modeling subatomic interactions and fundamental forces. Yet, a major challenge persists: AI models trained on simulations or old experiment / astronomical survey often perform poorly when applied to new data exposing issues of dataset (domain) shift, model robustness, and uncertainty in predictions. This talk will introduce common challenges in applying AI across domains and present solutions based on domain adaptation a set of techniques designed to improve model generalization under domain shift. We will cover foundational ideas, practical strategies, and current research frontiers in this area. Through examples in astrophysics, we'll explore how domain adaptation can help bridge the gap between synthetic and real-world data, improve trust in model outputs, and advance scientific discovery.

Ciprijanvoic, Aleksandra [Fermilab] (ORCID:0000000↗

Robust Heat-Flux Sensors for Coal-Fired Boiler Extreme Environments

In this project, robust heat-flux measurement systems were developed. The heat-flux sensors utilize thermoelectric effects to directly transduce the heat-flux inputs to analog electrical voltage signals. They were constructed from dedicated materials that can withstand temperatures of at least 1000°C and maintain adequate performance at these conditions for prolonged periods of time. The proposed approaches took into account numerous considerations, including system cost, sensor head resilience, sensor footprint, data accuracy, response time, and maintenance requirements. Through modern thermoelectric materials design, methodical materials selection and rigorous testing in materials characterization labs and medium-scale fire research facilities, we have demonstrated functioning laboratory prototypes, upon which one could base industrial heat-flux sensing platforms capable of operating in the challenging high-temperature, corrosive environments of the boilers of coal-fired power plants. A distributed sensor array for heat-flux measurements throughout the furnace water-wall, the superheater area and the economizer coils can provide critical data for the power plant control systems to increase efficiency, improve safety and reduce down times. For example, the combined heat-flux sensor/control systems can contribute to the optimization of burner and boiler operations under flexible loads, the optimization of heat-exchange conditions and overall reduction of heat rate and emissions, the prediction of imminent overheating conditions, and the optimization of the soot-blowing protocols.

20 FOSSIL-FUELED POWER PLANTS↗

Towards a Robust Adaptive Digital Twin for Fusion Applications

The development of a digital twin system for fusion applications is essential for enhancing the prediction, analysis, and optimization of complex plasma processes. Machine learning (ML), particularly deep learning has demonstrated strong capabilities in modeling such highly nonlinear and intricate systems. However, two critical challenges limit the deployment of deep learning-based digital twins: Uncertainty Quantification (UQ) and data drift. UQ is vital for ensuring trustworthy predictions, especially in decision-support scenarios. Additionally, data-driven models are often sensitive to changes in the underlying data distribution, such as shot-to-shot variations in fusion experiments, which can lead to performance degradation over time. To address these challenges, we are developing an uncertainty-aware, adaptive digital twin framework. Our approach incorporates deep learning models enhanced with Gaussian Process approximations for predictive uncertainty estimation, coupled with an online learning mechanism that enables continuous model adaptation to new experimental data. This adaptive capability allows the data driven models to respond effectively to evolving plasma behaviors and equipment conditions. Specifically, to mitigate the effects of shot-to-shot drift, our system updates itself incrementally as new data becomes available, improving both robustness and fidelity. Our vision is to evolve this data driven model into a self-sustaining digital twin system that leverages UQ based feedback to continuously refine itself and potentially support real-time decision making. This presentation will cover a brief background on uncertainty quantification for ML, our ongoing effort on development of UQ capabilities for ML, our data science pipeline from data collection to model development and analysis and online learning framework for modeling coil deflection at DIII-D. I will also briefly touch upon opportunities and challenges in development of digital twin framework.

Sammuli, Brian [General Atomics]↗

ExaWorks software development kit: a robust and scalable collection of interoperable workflows technologies

Scientific discovery increasingly requires executing heterogeneous scientific workflows on high-performance computing (HPC) platforms. Heterogeneous workflows contain different types of tasks (e.g., simulation, analysis, and learning) that need to be mapped, scheduled, and launched on different computing. That requires a software stack that enables users to code their workflows and automate resource management and workflow execution. Currently, there are many workflow technologies with diverse levels of robustness and capabilities, and users face difficult choices of software that can effectively and efficiently support their use cases on HPC machines, especially when considering the latest exascale platforms. We contributed to addressing this issue by developing the ExaWorks Software Development Kit (SDK). The SDK is a curated collection of workflow technologies engineered following current best practices and specifically designed to work on HPC platforms. We present our experience with (1) curating those technologies, (2) integrating them to provide users with new capabilities, (3) developing a continuous integration platform to test the SDK on DOE HPC platforms, (4) designing a dashboard to publish the results of those tests, and (5) devising an innovative documentation platform to help users to use those technologies. Our experience details the requirements and the best practices needed to curate workflow technologies, and it also serves as a blueprint for the capabilities and services that DOE will have to offer to support a variety of scientific heterogeneous workflows on the newly available exascale HPC platforms.

97 MATHEMATICS AND COMPUTING↗