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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 1,657 records · Page 92

Accelerating Time Integration for the Shallow Water Equations on the Sphere Using GPUs

The push towards larger and larger computational platforms has made it possible for climate simulations to resolve climate dynamics across multiple spatial and temporal scales. This direction in climate simulation has created a strong need to develop scalable time-stepping methods capable of accelerating throughput on high performance computing. This work details the recent advances in the implementation of implicit time stepping on a spectral element cube-sphere grid using graphical processing units (GPU) based machines. We demonstrate how solvers in the Trilinos project are interfaced with ACME and GPU kernels can significantly increase computational speed of the residual calculations in the implicit time stepping method for the shallow water equations on the sphere. We show the optimization gains and data structure reorganization that facilitates the performance improvements.

54 ENVIRONMENTAL SCIENCES↗

Sustainable Lactic Acid Production from Lignocellulosic Biomass

Lignocellulosic biomass is a promising feedstock for sustainable biofuels and bioproducts. Among emerging bioproducts, lactic acid has attracted significant interest because of its growing application in many industries (e.g., packaging, medical, and pharmaceutical). In this study, BioSTEAM—an open-source platform—was leveraged for the design, simulation, and evaluation (via techno-economic analysis, TEA, and life cycle assessment, LCA) of lignocellulosic lactic acid biorefineries. With a minimum product selling price (MPSP) between 1.38 and 1.91 kg –1 (5th–95th percentiles, baseline at 1.57 kg –1 ), the biorefinery was capable of producing market-competitive lactic acid (market price between 1.7 and 2.1 kg –1 ), and its performance could be further enhanced (e.g., MPSP down to 1.09 kg –1 , global warming potential of 2.79 kg CO 2 -eq·kg –1 , and fossil energy consumption of 31.7 MJ·kg –1 ) with advancements in key technological parameters (fermentation yield and separation process conversions) and optimization in process operation. Sensitivity analyses focused on the fermentation unit (across titer, yield, and productivity; neutral vs low-pH fermentation) and feedstock characteristics (carbohydrate content and price) were also included to quantify their impact on the sustainability of the biorefinery. Overall, this research highlights the ability of agile TEA/LCA to screen promising biorefinery designs, prioritize research needs, and establish a road map for the continued development of bioproducts and biofuels.

09 BIOMASS FUELS↗

Discovery of two-dimensional binary nanoparticle superlattices using global Monte Carlo optimization

Binary nanoparticle (NP) superlattices exhibit distinct collective plasmonic, magnetic, optical, and electronic properties. Here, we computationally demonstrate how fluid-fluid interfaces could be used to self-assemble binary systems of NPs into 2D superlattices when the NP species exhibit different miscibility with the fluids forming the interface. We develop a basin-hopping Monte Carlo (BHMC) algorithm tailored for interface-trapped structures to rapidly determine the ground-state configuration of NPs, allowing us to explore the repertoire of binary NP architectures formed at the interface. By varying the NP size ratio, interparticle interaction strength, and difference in NP miscibility with the two fluids, we demonstrate the assembly of an array of exquisite 2D periodic architectures, including AB-, AB 2 -, and AB 3 -type monolayer superlattices as well as AB-, AB 2 -, A 3 B 5 -, and A 4 B 6 -type bilayer superlattices. Our results suggest that the interfacial assembly approach could be a versatile platform for fabricating 2D colloidal superlattices with tunable structure and properties.

36 MATERIALS SCIENCE↗

Electrifying Airport GSE: Monte Carlo Grid Impacts

Airports globally are shifting from ICE-powered to electric Ground Support Equipment (eGSE) to enhance efficiency, reduce operational costs, and improve operator health. Leveraging predictable routes, flat terrain, and low operational speeds, airports provide ideal conditions for electrification. This study evaluates freight GSE electrification at Dallas-Fort Worth International Airport (DFW), USA, using the Agile@ platform, which integrates three analytical methods: Freight Facility Model (FFM), Activity-Structure-Intensity-Fuel (ASIF), and Monte Carlo simulations. Results from 10,000 simulations indicate modest but critical increases in electricity demand and significant variability in GSE energy consumption. These insights emphasize the importance of data-driven scheduling, targeted maintenance, and strategic infrastructure planning. For high-uncertainty scenarios, airports are advised to deploy buffer energy storage systems (battery banks), implement demand-response charging strategies, schedule flexible workforce shifts, and prioritize proactive maintenance-particularly for equipment with higher operational uncertainty, such as tug tractors with trailers. Agile@ thus offers a robust, scalable, and data-driven framework to optimize long-term GSE planning and enhance reliability across diverse airport environments.

Bose, Ranjan [ORNL] (ORCID:0009000791026327)↗

An Aminotransferase is Responsible for the Deamination of the N-terminal Leucine and Required for Formation of Oxazolone Ring A in Methanobactin of Methylosinus trichosporium OB3b

Gene expression in methanotrophs has been shown to be affected by the availability of a variety of metals, most notably copper regulating expression of alternative forms of methane monooxygenase. A copper-binding compound or chalkophore called methanobactin plays a key role in copper uptake in methanotrophs. Methanobactin is a ribosomally synthesized and post-translationally modified peptide (RiPP) with two heterocyclic rings with an associated thioamide for each ring, formed from X-Cys dipeptide sequences that bind copper. The gene encoding for the precursor polypeptide of methanobactin, mbnA , is part of a gene cluster, but the role of other genes in methanobactin biosynthesis is unclear. To begin to elucidate the function of these genes, we constructed an unmarked deletion of mbnABCMN in Methylosinus trichosporium OB3b, and then homologously expressed mbnABCM off a broad host range cloning vector to determine the function of mbnN , annotated as encoding for an aminotransferase. Methanobactin produced by this strain was found to be substantially different from wildtype methanobactin in that the C-terminal methionine was missing, and only one of the two oxazolone rings was formed. Rather, in the place of the N-terminal 3-methylbutanoyl-oxazolone-thioamide group, a leucine and thioamide-containing glycine (Gly-Ψ) were found, indicating that MbnN is used for deamination of the N-terminal leucine of methanobactin, and that this post-translational modification is critical for closure of the N-terminal oxazolone ring in M. trichosporium OB3b. These studies provide new insights into methanobactin biosynthesis, and also provide a platform for understanding the function of other genes in the methanobactin gene cluster. Methanotrophs, microbes that play a critical role in the carbon cycle, are influenced by copper, with gene expression and enzyme activity changing as copper levels change. Methanotrophs produce a copper-binding compound, or chalkophore called methanobactin for copper uptake, and methanobactin plays a key role in controlling methanotrophic activity. Methanobactin has also been shown to be effective in the treatment of Wilson Disease, an autosomal recessive disorder where the human body cannot correctly assimilate copper. It is important that the biosynthetic pathway of methanobactin be characterized to understand how methanotrophs respond to their environment as well as to optimize the use of methanobactin for the treatment of copper-related diseases such as Wilson Disease. Here we show that mbnN , encoding an aminotransferase, is involved in the deamination of the N-terminal leucine and necessary for the formation of one but not both heterocyclic rings in methanobactin that are responsible for copper binding.

59 BASIC BIOLOGICAL SCIENCES↗

HERO WEC V1: Design and Experimental Data Collection Efforts

The Hydraulic and Electric Reverse Osmosis Wave Energy Converter (HERO WEC) is a research platform aimed at developing a modular, small-scale wave-powered desalination system for remote and disaster-response applications. Funded by the Department of Energy (DOE)'s Water Power Technologies Office (WPTO), the project aims to advance wave-powered desalination by developing and testing a small-scale, modular wave energy converter (WEC). The insights gained from this project will help guide the design and development of larger-scale wave energy devices as well as the integration of marine energy and reverse osmosis (RO) desalination. The HERO WEC was initially developed to derisk the Waves to Water prize, enabling the staff to practice WEC deployment and recovery, while optimizing installation protocols ologies, aiming to advance the broader fields of marine energy and water treatment.

13 HYDRO ENERGY↗

Vacuum-assisted extrusion to reduce internal porosity in large-format additive manufacturing

Large-scale 3D printing of polymer composite structures has gained popularity and seen extensive use over the last decade. Much of the research related to improving the mechanical properties of 3D-printed parts has focused on exploring new materials and optimizing print parameters to improve geometric control and minimize voids between printed beads. However, porosity at the microstructural level (within the printed bead) has been much less studied although it is almost universally observed at levels of 4 %-10 % when using fiber reinforced materials. This study introduces a vacuum-assist approach that minimizes internal porosity by removing ambient air from the interstitial space between pellets in the hopper and acts as a negative pressure vent for gases that evolve during the initial stages of single-screw extrusion. Vacuum-assisted extrusion was able to reduce porosity below 2 % across a wide range of processing parameters, moisture content, fiber reinforcements, and printing platforms. Specifically, when printing on a large-format extruder (Strangpresse Model-30), the vacuum-assisted extrusion reduced internal porosity by 35–75 % compared to conventional non-vacuum extrusion, and only pores with length scale > 2 microns are affected. The success of this approach prompted the design of a patent-pending continuous vacuum hopper relevant for large-scale 3D printing on commercial systems.

36 MATERIALS SCIENCE↗

Interfacial electroneutrality controls transport of asymmetric salts through charge-patterned mosaic membranes

Membranes that selectively enhance target solute permeation while rejecting competing species are essential for precision separations. This study introduces charge-patterned mosaic membranes (CMMs) that selectively transport divalent asymmetric salts by leveraging a net-neutral membrane–solution interface. This mechanism, dictated by the charge ratio of positive and negative domains on the membrane surface and the balance of cations and anions in the salt, is supported by analytical, numerical, and experimental results. Analytical solutions identified cationic domain coverages (f + ) of 33%, 50%, and 66% as optimal for the selective transport of +2:−1 salts, +1:−1 salts, and +1:−2 salts, respectively, under conditions where the pattern size (L) is significantly larger than the Debye length. Numerical simulations and experiments using CMMs with alternating charged-stripes inkjet-printed onto nanostructure copolymer substrates confirmed these findings. By varying stripe widths to control f + , pressure-driven filtration experiments demonstrated selective enrichment of MgCl 2 and K 2 SO 4 at the predicted f + values, with deviations from these values leading to salt rejection. These results highlight the pivotal role of a net-neutral interface in enabling asymmetric salt enrichment. This study positions CMMs as a versatile platform for tuning ion selectivity, addressing challenges in resource recovery, water treatment, and precision separations.

additive manufacturing↗

Trace-gas sensing using the compliance voltage of an external cavity quantum cascade laser

Quantum cascade lasers (QCLs) are increasingly being used to detect, identify, and measure levels of trace gases in the air. External cavity QCLs (ECQCLs) provide a broadly-tunable infrared source to measure absorption spectra of chemicals and provide high detection sensitivity and identification confidence. Applications include detecting chemical warfare agents and toxic industrial chemicals, monitoring building air quality, measuring greenhouse gases for atmospheric research, monitoring and controlling industrial processes, analyzing chemicals in exhaled breath for medical diagnostics, and many more. Compact, portable trace gas sensors enable in-field operation in a wide range of platforms, including handheld units for use by first responders, fixed installations for monitoring air quality, and lightweight sensors for deployment in unmanned aerial vehicles (UAVs). We present experimental demonstration of a new chemical sensing technique based on intracavity absorption in an external cavity quantum cascade laser (ECQCL). This new technique eliminates the need for an infrared photodetector and gas cell by detecting the intracavity absorption spectrum in the compliance voltage of the laser device itself. To demonstrate and characterize the technique, we measure infrared absorption spectra of chemicals including water vapor and Freon-134a. Sub-ppm detection limits in one second are achieved, with the potential for increased sensitivity after further optimization. The technique enables development of handheld, high-sensitivity, and high-accuracy trace gas sensors for in-field use.

infrared spectroscopy, quantum cascade laser, trac↗

Poster - 01: LabPET II Pixelated APD-Based PET Scanner for High-Resolution Preclinical Imaging

Purpose: LabPET II is a new generation APD-based PET scanner designed to achieve sub-mm spatial resolution using truly pixelated detectors and highly integrated parallel front-end processing electronics. Methods: The basic element uses a 4×8 array of 1.12×1.12 mm{sup 2} Lu{sub 1.9}Y{sub 0.1}SiO{sub 5}:Ce (LYSO) scintillator pixels with one-to-one coupling to a 4×8 pixelated monolithic APD array mounted on a ceramic carrier. Four detector arrays are mounted on a daughter board carrying two flip-chip, 64-channel, mixed-signal, application-specific integrated circuits (ASIC) on the backside interfacing to two detector arrays each. Fully parallel signal processing was implemented in silico by encoding time and energy information using a dual-threshold Time-over-Threshold (ToT) scheme. The self-contained 128-channel detector module was designed as a generic component for ultra-high resolution PET imaging of small to medium-size animals. Results: Energy and timing performance were optimized by carefully setting ToT thresholds to minimize the noise/slope ratio. ToT spectra clearly show resolved 511 keV photopeak and Compton edge with ToT resolution well below 10%. After correction for nonlinear ToT response, energy resolution is typically 24±2% FWHM. Coincidence time resolution between opposing 128-channel modules is below 4 ns FWHM. Initial imaging results demonstrate that 0.8 mm hot spots of a Derenzo phantom can be resolved. Conclusion: A new generation PET scanner featuring truly pixelated detectors was developed and shown to achieve a spatial resolution approaching the physical limit of PET. Future plans are to integrate a small-bore dedicated mouse version of the scanner within a PET/CT platform.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

A high-throughput experimentation platform for data-driven discovery in electrochemistry

Automating electrochemical analyses combined with artificial intelligence is poised to accelerate discoveries in renewable energy sciences and technologies. This study presents an automated high-throughput electrochemical characterization (AHTech) platform as a cost-effective and versatile tool for rapidly assessing liquid analytes. The Python-controlled platform combines a liquid handling robot, potentiostat, and customizable microelectrode bundles for diverse, reproducible electrochemical measurements in microtiter plates, minimizing chemical consumption and manual effort. To showcase the capability of AHTech, we screened a library of 180 small molecules as electrolyte additives for aqueous zinc metal batteries, generating data for training machine learning models to predict Coulombic efficiencies. Key molecular features governing additive performance were elucidated using Shapley Additive exPlanations and Spearman’s correlation, pinpointing high-performance candidates like cis-4-hydroxy-d-proline, which achieved an average Coulombic efficiency of 99.52% over 200 cycles. The workflow established herein is highly adaptable, offering a powerful framework for accelerating the exploration and optimization of extensive chemical spaces across diverse energy storage and conversion fields.

Lin, Dian-Zhao [Johns Hopkins University, Baltimor↗

A Sensitive Electrochemical Cholinesterase-Inhibiting Biosensor for Organophosphorus Pesticides Based on Ti 3 C 2 TX MXene Quantum Dots

Organophosphorus pesticides (OPs) pose significant environmental and health risks due to their widespread use and toxicity, primarily by inhibiting acetylcholinesterase. Traditional detection methods are often slow and costly, highlighting the urgent need for advanced, sensitive, and accessible technologies. This study developed a highly sensitive electrochemical cholinesterase-inhibiting biosensor for OP pesticides, utilizing Ti 3 C 2 T x MXene Quantum Dots (MQDs), which was synthesized via a hydrothermal method. The biosensor’s performance was characterized using electrochemical impedance spectroscopy, differential pulse voltammetry (DPV), and cyclic voltammetry. DPV proved to be the optimal technique, exhibiting an ultralow detection limit of 1 × 10 −17 M and a wide linear range (10 −14 –10 −8 M) for chlorpyrifos (a model OP) with an estimated inhibition constant of 62 nM. The biosensor demonstrated high selectivity for OPs (chlorpyrifos, acephate, glyphosate) over a non-target pyrethroid (permethrin), confirmed by distinct electrochemical signatures and compared to in vitro cholinergic activity assays in bean beetle homogenates. The enhanced performance is attributed to the high surface-to-volume ratio, quantum confinement effects, and superior conductivity of the MQDs, as well as the robust enzyme immobilization facilitated by glutaraldehyde cross-linking and a chitosan matrix. This work presents a promising platform for rapid, sensitive, and selective detection of OP pesticides, with potential applications in environmental monitoring and public health protection.

Chemistry↗

Metabolic engineering for the high-yield production of isoprenoid-based C 5 alcohols in E. coli

Branched five carbon (C 5 ) alcohols are attractive targets for microbial production due to their desirable fuel properties and importance as platform chemicals. In this study, we engineered a heterologous isoprenoid pathway in E. coli for the high-yield production of 3-methyl-3-buten-1-ol, 3-methyl-2-buten-1-ol, and 3-methyl-1-butanol, three C 5 alcohols that serve as potential biofuels. We first constructed a pathway for 3-methyl-3-buten-1-ol, where metabolite profiling identified NudB, a promiscuous phosphatase, as a likely pathway bottleneck. We achieved a 60% increase in the yield of 3-methyl-3-buten-1-ol by engineering the Shine-Dalgarno sequence of nudB, which increased protein levels by 9-fold and reduced isopentenyl diphosphate (IPP) accumulation by 4-fold. To further optimize the pathway, we adjusted mevalonate kinase (MK) expression and investigated MK enzymes from alternative microbes such as Methanosarcina mazei. Next, we expressed a fusion protein of IPP isomerase and the phosphatase (Idi1~NudB) along with a reductase (NemA) to diversify production to 3-methyl-2-buten-1-ol and 3-methyl-1-butanol. Lastly, we used an oleyl alcohol overlay to improve alcohol recovery, achieving final titers of 2.23 g/L of 3-methyl-3-buten-1-ol (~70% of pathway-dependent theoretical yield), 150 mg/L of 3-methyl-2-buten-1-ol, and 300 mg/L of 3-methyl-1-butanol.

59 BASIC BIOLOGICAL SCIENCES↗

Overview of Wendelstein 7-X high-performance operation

The Wendelstein 7-X (W7-X) stellarator has completed two consecutive experimental campaigns OP 2.2 (Sep.-Dec. 2024) and OP 2.3 (Feb.-May 2025) under a new operational strategy enabling more than one year of uninterrupted device availability. This approach, supported by exceptionally high subsystem reliability, allowed sustained high-efficiency plasma operations with up to 80–100 discharges per day across a broad range of magnetic configurations. Several key technical upgrades-most notably the first operation of a 1.5 MW class steady-state gyrotron, a new steady-state pellet injector, and advanced real-time feedback control systems significantly enhanced heating, fueling, and plasma control capabilities. Together, these improvements enabled major advances in long-pulse performance, high-β operation, and confinement optimization. Long-pulse discharges achieved 1.8 GJ of injected energy under fully detached divertor conditions, while reduced-field scenarios facilitated record volume-averaged β values approaching 3%. High-performance plasmas with centrally peaked density profiles, created via neutral beam injection (NBI) or sustained pellet fueling, demonstrated strongly reduced turbulent transport and stellarator-record fusion triple products. Complementary studies of power exhaust and divertor heat loads revealed the role of scrape-off-layer drift physics in shaping strike-line patterns under attached conditions. Together, the results from OP 2.2 and OP 2.3 significantly expand the operational space of W7-X and strengthen its role as a leading platform for steady-state stellarator research and reactor-relevant plasma scenarios.

Wendelstein 7-X↗

User-oriented Improvements in the MOOSE Framework in Support of Multiphysics Simulation

The Multiphysics Object-Oriented Simulation Environment (MOOSE) framework is a foundational capability used by the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program to create over 15 different simulation tools for advanced nuclear reactors. Due to this ubiquity, improvements to the framework in support of modeling and simulation goals are critical to the program. These improvements can take many forms, including optimization, improved user experience, streamlined application programming interfaces (APIs), parallelism, and new capabilities. The work transcribed in this report was conducted in direct support of the simulation tools and has already been deployed or will be deployed in the coming months. The capabilities were implemented in the same order as they are covered in this report: chainable execution objects or executors, support for transfers between same-level applications in a coupling scheme, support for boundary/subdomain restricted transfers, support for transfers between applications with different coordinate or unit systems, support for MOOSE applications in the NEAMS Workbench, deployment of the MOOSE application of the Idaho National Laboratory (INL) high-performance computing (HPC) OnDemand platform, the addition of a triangular meshing library in libMesh, and increased support of face variables.

97 MATHEMATICS AND COMPUTING↗

Advanced Laboratory and Field Arrays (ALFA)/Lab Collaboration Project (LCP) for Marine Energy (Final Scientific/Technical Report)

The objective of the Advanced Laboratory and Field Arrays (ALFA) project was to reduce the Levelized Cost of Energy (LCOE) of Marine and Hydrokinetic (MHK) energy by leveraging research, development, and testing capabilities at Oregon State University, University of Washington, and the University of Alaska, Fairbanks. ALFA is a project within the Pacific Marine Energy Center (PMEC; formerly NNMREC), a multi-institution entity with a diverse funding base that focuses on research and development for marine renewables. The ALFA project aimed to accelerate the development of next-generation arrays of wave energy conversion (WEC) and tidal energy conversion (TEC) devices through a suite of field-focused R&D activities spanning a broad range of strategic opportunity areas identified in the Funding Opportunity Announcement: • Device and/or array operation and maintenance (O&M) logistics development; • High-fidelity resource characterization and/or modeling technique development and validation; • Array-specific component technology development (e.g. moorings and foundations, transmission, and other offshore grid components); • Array performance testing and evaluation; and • Novel cost-effective environmental monitoring techniques and instrumentation testing and evaluation. The objective of the Lab Collaboration Project (LCP) was to accelerate the development of next-generation marine energy conversion systems. The LCP aimed to achieve these project objectives in collaboration with the national laboratories by: • Developing concept generation and assessment tools; • Improving access to existing testing resources; • Validating collision risk models between fish and turbines; and • Advancing analysis and simulation capabilities for wave-WEC interactions and PTO analysis in nonlinear ocean waves. The ALFA portion of the project was comprised of six overarching technical tasks: • Task 1: Debris Modeling, Detection and Mitigation; • Task 2: Autonomous Monitoring & Intervention; • Task 3: Resource Characterization for Extreme Conditions; • Task 4: Robust Models for Design of Offshore Anchoring and Mooring Systems; • Task 5: Performance Enhancement for Marine Energy Converter (MEC) Arrays; and • Task 6: Evaluating Sampling Techniques for MHK Biological Monitoring. The LCP was divided into four overarching technical tasks: • Task 7: Project Management and Reporting • Task 8: Novel Design and Assessment Methodologies for Wave Energy Converter Design (Wave- SPARC) • Task 9: Testing Access for Commercial Marine Renewable Energy Technology Developers • Task 10: Quantifying Collision Risk for Fish and Turbines • Task 11: Nonlinear Ocean Waves and PTO Control Strategy Each ALFA/LCP task listed above functioned as a separate and discreet project. A final Technical Report was written for each individual task and these reports were uploaded to OSTI, after receiving DOE approval. The following document is a compilation of each of these final, approved reports arranged as individual chapters.

13 HYDRO ENERGY↗

Development of High-Fidelity and Efficient Modeling Capabilities for Enabling Co-Optimization of Fuels and Multi-Mode Engines

The objective of this closely coordinated research project is to develop improved physical sub-models and innovative numerical algorithms to enable accurate and efficient predictions of multi-mode combustion to support EERE’s Co-Optima program. To this end, a research pro-gram is proposed that seeks • to develop accurate submodels for predicting multi-mode combustion regimes, wall-heat transfer, non-equilibrium plasma ignition, and combustion-mode transition, • to develop dynamic load-rebalancing algorithms and efficient semi-implicit time-integration schemes for enabling exascale computing, • to validate the computational submodels against experiments and direct numerical simulation (DNS) data in conjunction with sensitivity analysis, and • to support the direct transition of the resulting sub-models into other engine-simulation tools through the development of self-contained modules. All sub-models will be integrated into the open-source exascale engine-simulation platform Nek5000.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗