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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 289 records · Page 16

Seamless Hybrid-integrated Interconnect NEtwork (SHINE)

Large-scale date centers are becoming increasingly limited by the capacity of interconnects due to the rapid increasing power consumption and bandwidth demands driven by the rigorous down scaling of CMOS critical dimensions in according with the Moore’s Law. As a result of the continuing bandwidth scaling, optical interconnects based on parallel optics, where data are simultaneously transmitted along more than one lane, have becoming a preferred interconnected solution over copper cables. To building an efficient optical interconnect system, optical coupling between different elements, such as optical fibers, photonics chips, is a critical step, which is challenging due to the mode mismatch of varies optical ports. In this project, we proposed and demonstrated an optical interfacing scheme, which provided a light coupling approach with low energy loss, broadband operation, high alignment tolerance and compatible with scalable fabrication and testing. Here, the mode transformation is achieved by a total internal reflection from a chip integrated microscale freefrom surface. Due to the enormous light wavefront manipulating ability associated with the gigantic design space, the freeform couplers platform is universally applicable to a wide range of optical coupling scenarios, such as the interfacing between a waveguide to a fiber, another waveguide, surface normal device, or free space.

42 ENGINEERING↗

The DESI Bright Galaxy Survey: Final Target Selection, Design, and Validation

Over the next 5 yr, the Dark Energy Spectroscopic Instrument (DESI) will use 10 spectrographs with 5000 fibers on the 4 m Mayall Telescope at Kitt Peak National Observatory to conduct the first Stage IV dark energy galaxy survey. At z < 0.6, the DESI Bright Galaxy Survey (BGS) will produce the most detailed map of the universe during the dark-energy-dominated epoch with redshifts of >10 million galaxies spanning 14,000 deg 2 . In this work, we present and validate the final BGS target selection and survey design. From the Legacy Surveys, BGS will target an r < 19.5 mag limited sample (BGS Bright), a fainter 19.5 < r < 20.175 color-selected sample (BGS Faint), and a smaller low-z quasar sample. BGS will observe these targets using exposure times scaled to achieve homogeneous completeness and cover the footprint three times. We use observations from the Survey Validation programs conducted prior to the main survey along with simulations to show that BGS can complete its strategy and make optimal use of "bright" time. BGS targets have stellar contamination <1%, and their densities do not depend strongly on imaging properties. BGS Bright will achieve >80% fiber assignment efficiency. Finally, BGS Bright and BGS Faint will achieve >95% redshift success over any observing condition. BGS meets the requirements for an extensive range of scientific applications. BGS will yield the most precise baryon acoustic oscillation and redshift-space distortion measurements at z < 0.4. It presents opportunities for new methods that require highly complete and dense samples (e.g., N-point statistics, multitracers). BGS further provides a powerful tool to study galaxy populations and the relations between galaxies and dark matter.

79 ASTRONOMY AND ASTROPHYSICS↗

Tussock tundra surface temperatures, ambient air and incoming photosynthetically active radiation measured at the NGEE Arctic Council site, 2021 - 2023

This dataset contains temperature measurements carried out along two fiber optics cables/lines (150 m each) laid out along the ground at the Next Generation Ecosystem Experiment (NGEE) Arctic site near Council, Alaska. The lines traverse an heterogeneous part of the tussock tundra site including thermokarst features and lichen dominated sections of the tundra. Measurements were done using a Sensornet Oryx DTS, a Distributed Temperature sensor that was installed in September 2021 and taken down in August 2023. The sensor was powered by solar power with data being collected every 30 minutes at 1 m resolution. In addition to these measurements air temperature and incoming photosynthetically active radiation (PAR) are provided. These measurements are co-located with the NGEE Arctic Council eddy flux and meteorological station (AmeriFlux ID US-NGC). Included are six *.csv files (four data files and two reporting format files) and two *.kml files. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

Air temperature↗

Optimizing the Heisenberg Vortex Tube for Hydrogen Cooling (Final Technical Report)

Hydrogen utilization at Plug Power sites ranges between 70-93% with the remainder vented and lost to the atmosphere. The goal of this project was to improve hydrogen utilization at Plug Power fulfillment centers via the patented Heisenberg vortex tube (HVT). The HVT combines conventional counterflow vortex tubes with para-orthohydrogen conversion catalyst to allow the cooling of hydrogen flows with no moving parts or external energy inputs. In year 1 of this project the HVT was evaluated to improve hydrogen utilization via the following concepts: 1) increasing liquid hydrogen pump volumetric efficiency by 20% through vapor separation and subcooling of the liquid, 2) reducing liquid hydrogen storage tank boil-off losses by 20% through thermal vapor shielding (TVS), and 3) increase isentropic efficiency of supercritical hydrogen expansion at 40-50 K, from 31% to over 40%. The TVS concept was selected as the most favorable application for further development. While the conceptual analysis was underway, the cryocatalysis hydrogen experiment facility (CHEF) was retrofitted with a new cryocooler, higher pressure condenser tanks, and in-situ fiber-optic Raman probes for ortho-parahydrogen composition analysis at the inlets and outlets of the HVT. To our knowledge this is the first in-situ implementation of cryogenic Raman probes for ortho-parahydrogen analysis. Subsequent testing of catalyzed and non-catalyzed HVT identified a low flow rate, high-conversion efficacy regime well suited for TVS development. Computational fluid dynamics (CFD), Reduced order modeling (ROM), and quantum Monte Carlo atomistic simulations were applied to optimize the design of the HVT implemented for TVS. The simulations and analysis identified a ruthenium-based catalyst as the most optimal for high conversion with little pressure losses and was matched to experimental measurements. These results indicated the design could achieve the 20% boil-off reduction target. An HVT field-trial was designed and constructed by Plug Power and implemented at a customer site. However, budget limitations reduced the amount of catalyst that could be applied to the HVT. With the reduced amount of catalyst, CFD analysis estimated about 3% reduction in boil-off. A similar amount of boil-off reduction was observed during preliminary measurements during tank commissioning. However, the results have a large margin for error and were operated at relatively low tank temperatures when the HVT has the lowest potential for improvement. This project demonstrated the use of para-orthohydrogen catalysis for reducing liquid hydrogen tank boil-off losses. The field trial system is anticipated to provide long-term experimental measurements on tank operational performance that will allow Plug Power to instrument additional tanks in the future. Recommendations for future work include the development of higher activity, lower cost para-orthohydrogen conversion catalyst for use in the HVT. Tank process optimizations could maximize the efficacy of the HVT and further improve hydrogen utilization.

08 HYDROGEN↗

Bayesian optimization scheme for the design of a nanofibrous high power target

High Power Targetry (HPT) R&D is critical in the context of increasing beam intensity and energy for next generation accelerators. Many target concepts and novel materials are being developed and tested for their ability to withstand extreme beam environments; the HPT R&D Group at Fermilab is developing an electrospun nanofiber material for this purpose. The performance of these nanofiber targets is sensitive to their construction parameters, such as the packing density of the fibers. Lowering the density improves the survival of the target, but reduces the secondary particle yield. Optimizing the lifetime and production efficiency of the target poses an interesting design problem, and in this paper we study the applicability of Bayesian optimization to its solution. We first describe how to encode the nanofiber target design problem as the optimization of an objective function, and how to evaluate that function with computer simulations. We then explain the optimization loop setup. Thereafter, we present the optimal design parameters suggested by the algorithm, and close with discussions of limitations and future refinements.

43 PARTICLE ACCELERATORS↗

Bayesian Optimization Scheme for the Design of a Nanofibrous High Power Target

High Power Targetry (HPT) R\&D is critical in the context of increasing beam intensity and energy for next generation accelerators. Many target concepts and novel materials are being developed and tested for their ability to withstand extreme beam environments; the HPT R\&D Group at Fermilab is developing an electrospun nanofiber material for this purpose. The performance of these nanofiber targets is sensitive to their construction parameters, such as the packing density of the fibers. Lowering the density improves the survival of the target, but reduces the secondary particle yield. Optimizing the lifetime and production efficiency of the target poses an interesting design problem, and in this paper we study the applicability of Bayesian optimization to its solution. We first describe how to encode the nanofiber target design problem as the optimization of an objective function, and how to evaluate that function with computer simulations. We then explain the optimization loop setup. Thereafter, we present the optimal design parameters suggested by the algorithm, and close with discussions of limitations and future refinements.

43 PARTICLE ACCELERATORS↗

Development of Novel Materials for Direct Air Capture of CO 2 : MIL-101(Cr)-Amine Sorbents Evaluation Under Realistic Direct Air Capture Conditions (Final Report)

The overarching goal of this project is to evaluate the CO 2 adsorption properties of a small family of metal-organic framework (MOFs) materials functionalized with amines at sub-ambient conditions. Our goal is to develop capabilities to measure CO 2 adsorption at conditions more relevant to the weather of the planet. For this purpose, Georgia Tech is constructing a “sub-ambient adsorption facility” in partnership with ZCP Sorbent Development, LLC, aimed specifically at rapidly and deeply characterizing the performance of DAC candidate materials in this important operational range (adsorption at -20 to 20 °C and RH of 0-100%). Here, we use the sub-ambient lab instrumentation designed or adapted to study the behavior of the pristine metal organic framework (MOF) MIL-101(Cr) and the MOF in the presence of amines ranging from small molecules (e.g. TREN, tris(2-aminoethylamine)) to oligomers (e.g. PEI, poly(ethyleneimine)). Any DAC sorbent must be amenable to deployment in practical contactors for gas-solid contacting (traditional pellet-based fixed beds are impossible at scale). To this end, we developed and tested these DAC materials in the forms of composite polymer/MOF fibers and custom 3D-printed monolith structures containing MOF DAC sorbents. The proposed studies advance these materials from technology readiness level (TRL) 2 to TRL 3.

01 COAL, LIGNITE, AND PEAT↗

Collective optical Thomson scattering in pulsed-power driven high energy density physics experiments (invited)

Optical collective Thomson scattering is used to diagnose magnetized high energy density physics experiments at the Magpie pulsed-power generator at Imperial College London. The system uses an amplified pulse from the 2nd harmonic of a Nd:YAG laser (3 J, 8 ns, 532 nm) to probe a wide diversity of hightemperature plasma objects; with densities in the range of 10 17 -10 19 cm -3 and temperatures between 10 eV and a few keV. The scattered light is collected from 100 μm-scale volumes within the plasmas, which are imaged onto optical fiber arrays. Multiple collection systems observe these volumes from different directions, providing simultaneous probing with different scattering K-vectors (and different associated α-parameters, typically in the range 0.5 – 3) allowing independent measurements of separate velocity components of the bulk plasma flow. The fiber arrays are coupled to an imaging spectrometer with a gated ICCD. The spectrometer is configured to view the ion-acoustic waves (IAWs) of the collective Thomson scattered spectrum. Fits to the spectra with the theoretical spectral density function S(K,ω) yield measurements of the local plasma temperatures and velocities. Fitting is constrained by independent measurements of the electron density from laser interferometry, and the corresponding spectra for different scattering vectors. Furthermore, this TS diagnostic has been successfully implemented on a wide range of experiments, revealing temperature and flow velocity transitions across magnetized shocks, inside rotating plasma jets and imploding wire arrays, as well as providing direct measurements of drift velocities inside a magnetic reconnection current sheet.

47 OTHER INSTRUMENTATION↗

Membrane Carbonation for 100% Efficient Delivery of Industrial CO 2 Gases

Industrial processes generate about one quarter of all greenhouse gases emissions in the US, about 80% of which is carbon dioxide (CO 2 ). Biological processes are one of the largest natural sinks for atmospheric CO 2 , but the rate of capture is limited by the low concentration in air (~0.04%). Industrial emissions have significantly higher CO 2 concentrations, ranging from 5–80% CO 2 , which can significantly increase the rate of biological CO 2 capture, including many-fold improvements for cultivating microalgae to produce food, fertilizer, and renewable fuel. However, traditional methods for delivering CO 2 to microalgae using bubbling is < 40% efficient, leading to significant residual CO 2 emissions and increased cost. This project developed the Membrane Carbonation (MC) technology to significantly improve the CO 2 delivery efficiency to microalgae from power plant flue gas, wastewater treatment plant anaerobic digesters biogas (Figure 1), and other CO 2 -containing industrial sources.

09 BIOMASS FUELS↗

High‐Speed Slot‐Die Coating with Donor‐Priority Rapid Aggregation Kinetics for Improved Morphology and Efficiency in Ecofriendly Organic Solar Cells

Abstract Solution‐processable organic solar cells (OSCs) represent a promising renewable photovoltaic technology with significant potential for eco‐compatible production. While high power conversion efficiencies (PCEs) have been achieved in OSCs, scaling this technology for high‐throughput manufacturing remains challenging. Key reason lies in the lack of efficient control strategies for the complex and long‐duration morphology evolution during high‐speed coating process with ecofriendly solvents. Here, a donor‐priority rapid aggregation process (DP‐RAP) scheme is proposed to solve this issue by adjusting the aggregation kinetics of donor and acceptor components. DP‐RAP enables blends with a nanoscale fiber network structure and favorable crystallinity, which contributes to balanced carrier transport and reduced recombination losses. As a result, the PCE is improved from 14.3% (reference) to 17.4% (DP‐RAP) for ultra‐high speed coated PM6:BTP‐eC9 devices in atmosphere, which is one of the highest values for non‐halogenated solvent‐processed solar cells at coating speeds of 500 mm s −1 . Moreover, the DP‐RAP based devices remain a stable PCE of approximately 17.4% across a broad range of coating speeds (20–500 mm s −1 ), illustrating its tolerance to the varied manufacturing conditions. This work highlights a promising avenue for the high‐speed, ecofriendly production of efficient OSCs, pushing the boundaries of practical manufacturing in renewable energy technologies.

Chemistry↗

Distributed sensing of electromagnetic components using optical fiber based methods

An OFDR based fiber-optics sensor for distributed real-time temperature rise monitoring of a transformer in operation has been disclosed. The fiber-optic sensor provides an effective solution to monitoring the physical structures of the transformer core, as well as accurately detecting the non-uniform temperature distribution inside the transformer, and thus provides innovative feedback to the transformer design by minimizing the core losses. Additionally, the method may be responsive to the presence of magnetic and electric fields, as well as responsive to various chemical species. The method allows novel approaches to real-time asset monitoring of power transformers while operational.

Ohodnicki, Paul R.↗

Synthetic Scientific Image Generation with VAE, GAN, and Diffusion Model Architectures

Generative AI (genAI) has emerged as a powerful tool for synthesizing diverse and complex image data, offering new possibilities for scientific imaging applications. This review presents a comprehensive comparative analysis of leading generative architectures, ranging from Variational Autoencoders (VAEs) to Generative Adversarial Networks (GANs) on through to Diffusion Models, in the context of scientific image synthesis. We examine each model's foundational principles, recent architectural advancements, and practical trade-offs. Our evaluation, conducted on domain-specific datasets including microCT scans of rocks and composite fibers, as well as high-resolution images of plant roots, integrates both quantitative metrics (SSIM, LPIPS, FID, CLIPScore) and expert-driven qualitative assessments. Results show that GANs, particularly StyleGAN, produce images with high perceptual quality and structural coherence. Diffusion-based models for inpainting and image variation, such as DALL-E 2, delivered high realism and semantic alignment but generally struggled in balancing visual fidelity with scientific accuracy. Importantly, our findings reveal limitations of standard quantitative metrics in capturing scientific relevance, underscoring the need for domain-expert validation. We conclude by discussing key challenges such as model interpretability, computational cost, and verification protocols, and discuss future directions where generative AI can drive innovation in data augmentation, simulation, and hypothesis generation in scientific research.

Generative Adversarial Networks↗

TuFF internal WRAP for Rapid Pipeline Repair (TuFF iWRAP)

The goal of “TuFF internal WRAP for Rapid Pipeline Repair” (TuFF iWRAP) program was to develop a novel material system and placement process to fabricate structural pipe within the existing deteriorated pipelines without disruption of gas delivery. The team (University of Delaware – Center for Composite Materials (UD-CCM) and Plitzie Inc.) addressed this challenge by developing a new material feedstock and pipe in pipe (PIP) repair strategy. This allows the potential for significant cost reduction and has minimum operational impact on gas customers. The new robotic based placement design allows discontinuous placement of pipe sections creating a stand-alone structural liner within the legacy pipeline without the need for pipe shutdown. Here, the material is supplied using a tethered material feeding system and is placed and UV cured with the internal Wound Rapid Automated Placement (iWRAP) system. This provides maximum placement efficiency capable of traversing 90 angle bends in 12-inch pipe and overall design customization to meet pipe repair requirements (e.g., variable wall thickness, bridging gaps, etc.). UV-curable fiber reinforced composite material has been optimized to meet structural performance and placement/cure times. Superior strength and fatigue life has been demonstrated by improving fiber-matrix adhesion using new fiber sizing for UV resins. Rapid cure approaches using new liner and resins have been evaluated with industry. The appropriate design of the section joints has been developed and tested. We estimate coating time to be ~100 hours per mile enabling typical pipe repair within 1 week.

03 NATURAL GAS↗

Non-planar platinum group metal-free fuel cell cathodes for enhanced oxygen transport and water rejection

Proton exchange membrane fuel cells (PEMFC) with cathodes using platinum group metal-free (PGM-free) catalysts could significantly reduce costs, but the lower volumetric oxygen reduction reaction (ORR) activity requires thick electrodes that suffer from liquid water flooding and increased oxygen transport resistance. To address these challenges, we developed a 3D gas diffusion electrode (GDE) architecture to enhance liquid water removal through the diffusion media and reduce cathode saturation. The cathode features a uniform catalyst layer adjacent to the membrane for high ORR activity and then pillars of the hydrophilic catalyst layer that pass through the microporous layer (MPL), providing a low capillary pressure barrier pathway to the carbon fiber paper layer and channel. The non-planar cathode also increases the interfacial area between the catalyst layer and hydrophobic MPL for a greater fraction of the cathode with high O 2 concentration. Our studies included parametric experimental study of the pillar density to identify the optimum pitch between pillars. Our measurements show significant improvements in the mass transport region of the polarization curve with 3D structured electrodes leading to an 8% increase in maximum current density, 19% increase in maximum power density, and 16% increase in current density at 0.67 V with air.

25 ENERGY STORAGE↗

User defined intensity profile laser beam

A high-power laser beam with an arbitrary intensity profile is produced. Such beam has a variety of uses including for laser materials processing such as powder bed fusion additive manufacturing. Several challenges in additive manufacturing are mitigated with the present non-uniform intensity laser profiles. Nonuniform shapes include a set of intensity pixels in a line that could print a wide stripe area instead of just a single line. One example uses the multimode interference pattern from the output of a ribbon fiber which is imaged onto a work piece. The interference pattern is controlled to allow turning on or off of ‘pixels’ along a line which can be used to shape the beam and form the additively manufactured part.

Drachenberg, Derrek R.↗

Pilot Test of a Nanoporous, Super-hydrophobic Membrane Contactor Process for Post-combustion CO 2 Capture

GTI Energy and Air Liquide Advanced Separations (ALaS) have been developing a novel hollow fiber membrane contactor (HFMC) technology for post-combustion CO 2 capture. The process combines advantageous features of both absorption and membrane-based separation processes to separate CO 2 from flue gas cost-effectively. The key component of the HFMC technology is the super-hydrophobic, porous hollow fiber, which is made from polyether ether ketone (PEEK). Compared to conventional absorption/desorption technologies, the critical advantage of the HFMC process is the high contact surface area provided by the hollow fibers enabling an increased volumetric mass-transfer rate. In the PEEK HFMC process, the specific surface area has been increased by an order of magnitude over structurally packed or trayed columns, resulting in compact systems with small footprints.

20 FOSSIL-FUELED POWER PLANTS↗

Fiber-optic bolometer with low detection limit fabricated using thermal release tape and precise laser heating

Fiber-optic bolometers (FOBs) based on a fiber-tipped silicon Fabry–Perot (FP) interferometric temperature sensor and a gold disk absorber have been shown to be an attractive alternative to conventional resistive bolometers for plasma radiation measurement in fusion devices. Either a high-finesse FP or a low-finesse FP can be used, each with trade-offs between noise performance and fabrication complexity. In this paper, we present an FOB design that overcomes these limitations by combining a low-finesse long silicon FP cavity with a large gold disk absorber to achieve enhanced sensitivity and noise performance without increasing the fabrication complexity and the time constant. We also demonstrated a fabrication method for the sensor head facilitated by thermal release tape and precise laser heating. Our FOB demonstrates a temperature resolution of 0.08 mK, a cooling time constant of 230 ms, and a noise equivalent power density of 0.015 W m −2 . This represents an eightfold improvement over previous high-finesse FOBs and 26-fold improvement over previous low-finesse FOBs with similar demodulation bandwidths and similar cooling time constants.

Fabry–Perot interferometer↗

Explainable machine learning for incipient anomaly detection in compact molten salt heat exchanger with overlapping feature distributions

High-temperature molten salt-cooled reactors (MSCRs) are a promising next-generation nuclear technology option, offering efficient power conversion and inherent safety features. However, the reliability of these systems depends on the robust operation of heat exchangers (HXs), which are susceptible to failure due to temperature gradients and channel plugging caused by fluid freezing. Conventional monitoring methods, relying on inlet and outlet measurements, lack the spatial resolution needed to detect early-stage faults. We propose a novel design of a compact salt-to-salt matrix-type HX design consisting of interleaved arrays of parallel tubes, with integrated synthetic fiber optic distributed temperature sensing (DTS) to enable localized detection of incipient faults. To evaluate performance of this design, we generate high-fidelity synthetic data using heat transfer computational modeling to simulate channel plugging, and introduce sensor noise for realistic modeling of measurements. The dataset comprises of 97% normal operation and 3% anomaly cases, with each anomaly class representing 1% of the data. These early anomalies result in overlapping temperature profiles between normal and faulty channels, producing a non-separable dataset that challenges traditional classification techniques. We benchmark eight supervised machine learning (ML) models and demonstrate that XGBoost achieves the highest performance. To improve transparency, we develop an explainability framework combining Shapley values and partially ordered sets (POSETs) to quantify and structurally analyze feature importance. This approach identifies both dominant predictors and ambiguous feature relationships, enhancing trust and interpretability. Our results highlight the potential of combining DTS and explainable ML with intelligent feature selection to improve predictive maintenance and ensure operational resilience in advanced nuclear systems.

Prantikos, Konstantinos [Argonne National Laborato↗