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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

Multiallelic, Targeted Mutagenesis of Magnesium Chelatase With CRISPR/Cas9 Provides a Rapidly Scorable Phenotype in Highly Polyploid Sugarcane

Genome editing with sequence-specific nucleases, such as clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein 9 (Cas9), is revolutionizing crop improvement. Developing efficient genome-editing protocols for highly polyploid crops, including sugarcane ( x = 10–13), remains challenging due to the high level of genetic redundancy in these plants. Here, we report the efficient multiallelic editing of magnesium chelatase subunit I ( MgCh ) in sugarcane. Magnesium chelatase is a key enzyme for chlorophyll biosynthesis. CRISPR/Cas9-mediated targeted co-mutagenesis of 49 copies/alleles of magnesium chelatase was confirmed via Sanger sequencing of cloned PCR amplicons. This resulted in severely reduced chlorophyll contents, which was scorable at the time of plant regeneration in the tissue culture. Heat treatment following the delivery of genome editing reagents elevated the editing frequency 2-fold and drastically promoted co-editing of multiple alleles, which proved necessary to create a phenotype that was visibly distinguishable from the wild type. Despite their yellow leaf color, the edited plants were established well in the soil and did not show noticeable growth retardation. This approach will facilitate the establishment of genome editing protocols for recalcitrant crops and support further optimization, including the evaluation of alternative RNA-guided nucleases to overcome the limitations of the protospacer adjacent motif (PAM) site or to develop novel delivery strategies for genome editing reagents.

59 BASIC BIOLOGICAL SCIENCES↗

Using remote sensing to quantify the additional climate benefits of California forest carbon offset projects

Abstract Nature‐based climate solutions are a vital component of many climate mitigation strategies, including California's, which aims to achieve carbon neutrality by 2045. Most carbon offsets in California's cap‐and‐trade program come from improved forest management (IFM) projects. Since 2012, various landowners have set up IFM projects following the California Air Resources Board's IFM protocol. As many of these projects approach their 10th year, we now have the opportunity to assess their effectiveness, identify best practices, and suggest improvements toward future protocol revisions. In this study, we used remote sensing‐based datasets to evaluate the carbon trends and harvest histories of 37 IFM projects in California. Despite some current limitations and biases, these datasets can be used to quantify carbon accumulation and harvest rates in offset project lands relative to nearby similar “control” lands before and after the projects began. Five lines of evidence suggest that the carbon accumulated in offset projects to date has generally not been additional to what might have otherwise occurred: (1) most forests in northwestern California have been accumulating carbon since at least the mid‐1980s and continue to accumulate carbon, whether enrolled in offset projects or not; (2) harvest rates were high in large timber company project lands before IFM initiation, suggesting they are earning carbon credits for forests in recovery; (3) projects are often located on lands with higher densities of low‐timber‐value species; (4) carbon accumulation rates have not yet increased on lands that enroll as offset projects, relative to their pre‐enrollment levels; and (5) harvest rates have not decreased on most project lands since offset project initiation. These patterns suggest that the current protocol should be improved to robustly measure and reward additionality. In general, our framework of geospatial analyses offers an important and independent means to evaluate the effectiveness of the carbon offsets program, especially as these data products continue improving and as offsets receive attention as a climate mitigation strategy.

59 BASIC BIOLOGICAL SCIENCES↗

Chemical contributions to silicon anode calendar aging are dominant over mechanical contributions

Silicon (Si) anodes are a promising candidate for increasing the energy density of lithium (Li)-ion batteries for electric vehicles. However, they have recently been identified as having poor calendar life that is insufficient for commercial needs, in addition to the well-known issue of their poor cycle life resulting from large volume expansion. Here, a specially designed protocol with variable rest periods between intermittent cycling is used to evaluate the impact of the mechanical disruption of Si and solid electrolyte interphase (SEI) from cycling on calendar aging measurements. Si was found to undergo more mechanical degradation during calendar aging with intermittent cycling than graphite. However, Si anode capacity fade was still dominated by time, especially for rest periods greater than or equal to 1 month between cycling. Postmortem dQ/dV half-cell analysis indicated this was mainly due to Li inventory loss and an increase in electrode resistance. Isothermal microcalorimetry further demonstrated that Si passivation is more disrupted than graphite passivation with intermittent cycling and suggested that there may be a chemical buildup of a detrimental species in the electrolyte, leading to a large spike in heat after the Si and SEI are disrupted by cycling.

25 ENERGY STORAGE↗

Faster Randomized Dynamical Decoupling

We present a randomized dynamical decoupling (DD) protocol that can substantially improve the performance of any given deterministic DD scheme for suppressing coherent noise by using no more than two additional pulses. Our construction is implemented by probabilistically applying sequences of pulses, which, when combined, effectively eliminate the error terms that scale linearly with the system-environment coupling strength. As a result, we show that a randomized protocol using a few pulses can outperform deterministic DD protocols that require considerably more pulses. Furthermore, we prove that the randomized protocol provides an improvement compared to deterministic DD sequences that aim to reduce the error in the system’s Hilbert space, such as Uhrig DD, which had been previously regarded to be optimal. To rigorously evaluate the performance, we introduce new analytical methods suitable for analyzing higher-order DD protocols that might be of independent interest. Here, we also present numerical simulations confirming the significant advantage of using randomized protocols compared to widely used deterministic protocols.

Quantum algorithms & computation↗

Molten Salt Corrosion Tests of Additively Manufactured Stainless Steel 316H

Molten salt reactors (MSRs) have drawn considerable interest due to their favorable safety features, high thermal efficiency, and compatibility with different fuel cycles. Yet, the success of MSRs hinges critically on the performance of structural materials to be used in these aggressive molten salt environments, where corrosion and material compatibility remain primary challenges to long-term reliability. Additively manufactured (AM) nuclear structural materials prompt the use of novel geometries and compositions to enhance material performance and reduce costs of constructing MSRs. The rapid solidification conditions inherent to AM processing impart distinctive microstructural features, including cellular sub-structures, dislocation densities, residual stress, and oxide inclusions, which can influence material performance in MSR components. While the mechanical properties of AM stainless steels have been widely studied, their corrosion behavior, particularly in molten salt environments, has received far less attention. Addressing these needs, the Advanced Materials and Manufacturing Technologies (AMMT) program provides a framework for systematically evaluating how unique microstructures produced by AM processes influence the performance of these materials in these demanding environments and for developing reproducible testing workflows that can support future code qualification efforts and standards development. Bridging this knowledge gap is essential for assessing the viability of AM alloys in MSRs and informing qualification strategies. A further challenge is the absence of standardized protocols for molten salt corrosion testing. Accordingly, this report provides an account of the corrosion evaluation of AM 316H stainless steel in NaCl 2 -MgCl 2 molten salt at 550 °C, with exposure times of 100 and 500 hours. It documents the experimental procedures implemented under the AMMT program, including salt preparation, exposure protocols, and post-test characterization methods, to establish reproducibility and transparency. Importantly, the study examines AM 316H samples in the as-fabricated condition, directly reflecting the surface state most relevant to engineering applications, and compares their behavior to machine-cut surfaces. Overall, preliminary evaluations have noted that surface conditions (e.g. morphology, contamination, etc.) have a noticeable impact on the corrosion resiliency. The impact of the corrosion is difficult to detect at 100h, unless, in the case of AM 316H, the specimen surface is decontaminated. After 500 h, as-fabricated surfaces of AM and wrought 316H display evidence of general versus preferential corrosion attack, respectively. Both AM and wrought 316H machine-cut surfaces exhibit a continuous Cr depletion zone, evident of general corrosion. While the estimated extent of corrosion appears within the same order of magnitude regardless of the surface condition, it is apparent that more predictable behavior is observed on machine-cut surfaces. Nonetheless, further investigation is necessary to fully elucidate the corrosion mechanism under these conditions.

36 - MATERIALS SCIENCE↗

Influences of North Pacific Ocean Domain Extent on the Western U.S. Winter Hydroclimatology in Variable-Resolution CESM

Variable-resolution global climate models (VRGCMs) are a dynamical downscaling method that can reach spatiotemporal scales needed for regional climate assessments. Over the years, several users of VRGCMs have assumed where the location and extent of the refinement domain should be based on knowledge of the prevailing storm tracks and resolution dependence of important regional climate processes (e.g., atmospheric rivers [ARs] and orographic uplift), but the effect of high-resolution domain size and extent on the simulation of downstream hydroclimatic phenomena has not been systematically evaluated. Here, we use variable resolution in the Community Earth System Model (VR-CESM) to perform such a test. To do this, three VR-CESM grids were generated that span the entire, two thirds, and one third of the North Pacific and evaluated for a 30-year climatology using Atmospheric Model Intercomparison Project protocols. Simulations are compared with reanalysis products offshore (fifth-generation of the European Centre for Medium-Range Weather Forecasts atmospheric reanalysis [ERA5]) and onshore (Livneh, 2015, https://doi.org/10.1038/sdata.2015.42, and Parameter-elevation Regressions on Independent Slopes Model [PRISM]) of the western United States. The westward expansion of refinement domain influenced integrated vapor transport (IVT), which was generally high biased but minimally impacted AR characteristics. Due to slight differences in landfalling AR counts in the western United States, California winter precipitation generally improved with westward expansion of the refinement domain. Western U.S. mountain snowpack and surface temperatures were insensitive to refinement domain size and were more influenced by changes in topographic resolution and/or land surface model version. Here, given minimal dependence of simulated western U.S. hydroclimate on refinement domain size over the North Pacific, we advise future VR-CESM studies to focus grid resolution on better resolving land surface heterogeneity.

54 ENVIRONMENTAL SCIENCES↗

Next Generation Sensor Development (CRADA Final Report)

B. Project Scope This was a collaborative effort between Lawrence Livermore National Security, LLC (LLNS), as manager and operator of Lawrence Livermore National Laboratory (LLNL) and The Federal Reserve Bank of San Francisco ("FRBSF" or "Participant"), to research and develop advanced processing techniques to measure the fitness and authenticity of U.S. currency. The FRBSF previously partnered with LLNL to evaluate end-of-life predictions, review sensor requirements, develop communications protocols, and perform thermal analysis. These Strategic Partnership Projects (SPP) included SPP No. L20960 - Federal Reserve Currency Technology Office Studies, SPP No. L15900 - Development of a Common Detector Interface (CDI 2.0) Specification and Hardware Simulators, and SPP No. L15610 - Limited Design Review of a Second-Generation E-Material Authentication Sensor (EMAS2).

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Open Source Evaluation Framework for Solar Forecasting

The Solar Forecast Arbiter is an open-source evaluation framework for solar forecasting. The framework enables evaluations of solar irradiance, solar power, and net-load forecasts that are impartial, repeatable and auditable. The Solar Forecast Arbiter addresses stakeholder-informed use cases including evaluation of forecast skill, comparisons to reference data sets, private forecast trials, and evaluation of probabilistic forecast skill. The framework includes a data validation toolkit, reference data sources, data privacy protocols, and benchmark forecast capabilities for intra-hour and day ahead forecast horizons. Reports and metrics communicate the relative merits of the test and benchmark forecasts. The reports are created from standardized templates and include graphics for qualitatively evaluating deterministic and probabilistic forecasts and standard metrics for quantitatively evaluating forecasts. The Solar Forecast Arbiter is designed to support all solar forecasting stakeholders, including Solar Forecasting 2 Topic Area 2 and Topic Area 3 teams.

14 SOLAR ENERGY↗

IPv6 Tunneling and Translation Technologies Pilot

Based on the latest DOE (Department of Energy) milestones, Sandia needs to convert to IPv6 (Internet Protocol version 6)-only networks over the next 5 years. Our original IPv6 migration plan did not include migrating to IPv6-only networks at any point within the next 10 years, so it must necessarily change. To be successful in this endeavor, we need to evaluate technologies that will enable us to deploy IPv6-only networks early without creating system stability or security issues. We have set up a test environment using technology representative of our production network where we configured and evaluated industry standard translation technologies and techniques. Based on our results, bidirectional translation between IPv4 (Internet Protocol version 4) and IPv6 is achievable with our current equipment, but due to the complexity of the configuration, may not scale well to our production environment.

97 MATHEMATICS AND COMPUTING↗

Trocylation of 3-quinuclidinol, a key marker for the chemical warfare agent 3-quinuclidinyl benzilate, for its enhanced detection at low levels in complex soil matrices by electron ionization gas chromatography–mass spectrometry

Detection of 3-quinuclidinol (3Q), a marker for the chemical warfare agent 3-quinuclidinyl benzilate, is very difficult by gas chromatography–mass spectrometry (GC/MS), providing low, broad signals even when analyzed in isolated form. Therefore, a method that can convert 3Q into a substrate with enhanced detectability by GC/MS would be an important tool for its analysis. 2,2,2-Trichloroethoxycarbonyl chloride (TrocCl) was used in the derivatization of 3Q in three different soils of varying composition and total organic content (Virginia type A soil, Nebraska EPA standard soil and Ottawa sand) when present at a 10 μg g -1 concentration in each. A direct derivatization protocol and one involving the pre-extraction of the analyte were evaluated for their individual efficiencies and subsequent analysis using electron ionization GC/MS. The practical derivatization of 3Q, when present at low levels (10 μg g -1 ) in three different soil matrices, was found to be rapid (1 h) and to take place smoothly at ambient temperature (and as low as 4°C). The method detection limit was determined to be 30 ng mL -1 for the Virginia type A soil, 49 ng mL -1 for the Nebraska EPA standard soil and 72 ng mL -1 for the Ottawa sand sample. An expedient and practical derivatization method for 3Q, a chemical warfare degradation product difficult to detect by GC/MS, has been realized using trichloroethyl chloroformate. The reaction provides 3Q-Troc, a derivative with better detectability than 3Q by electron ionization GC/MS such as peak sharpness and a unique mass spectrum for its unambiguous identification.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Small-Molecule Models of Hydrogen-Evolving MX 2 (M = Mo, W; X = S, Se) Bulk Solids: Composition–Activity Relationships

Triangular metal chalcogenide clusters of the form [M 3 Q 7 L 3 ]An (M = Mo or W; Q = S or Se; L = i Bu 2 NCS 2 – , (CF 3 CH 2 ) 2 NCS 2 – , i Bu 2 NCSe 2 – , or i Bu 2 PS 2 – ; An = Cl – or I – ) have been investigated as molecular analogues of layered metal dichalcogenide (MX 2 ) H 2 -evolution catalysts. These clusters have been evaluated for their relative H 2 -evolving ability under a common photolysis protocol implementing [Ru(bpy) 3 ] 2+ as chromophore and Et 3 N as sacrificial electron donor. With M constant as Mo and with constant supporting ligand, clusters with an all-sulfide core enable greater H 2 -TON than clusters with an all-selenide core. A more active catalyst is produced by [Mo 3 S 7 (S 2 CN i Bu 2 ) 3 ] + I – than its W 3 analogue with the same core sulfide composition and supporting dithiocarbamate ligands. Dichalcogenocarbamate ligands provide more active catalysts than dialkyldithiophosphate ligated clusters, and within the dichalcogenocarbamate set, greater H 2 -turnovers correlate with more-electron-donating ligands (i.e., i Bu 2 NCS 2 – > (CF 3 CH 2 ) 2 NCS 2 – > i Bu 2 NCSe 2 – ). Cluster cations with Cl – as counteranion are very similar in activity H 2 -evolving levels to identical clusters with I – , ruling out any significant interfering effect by I – upon the electron transfer relay between Et 3 N and catalyst. In the aggregate, observations are consistent with a mechanism for H 2 evolution that involves reductive extrusion of H 2 from a metal hydride intermediate.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A Communication Testbed for Testing Power Electronic Agent Systems

Power electronic systems (PES) incorporate complex intra-system communication, which are of vital importance for the successful operation of these systems. This paper proposes and outlines a communication testbed that will help in the development and testing of the communications between the components of PES. It allows for the comparison and evaluation of different communication methods, such as MQTT, Modbus, or User Datagram Protocol (UDP), and for the characterization of how these communication protocols perform.

Dean, Ben↗

OmniFed: A Modular Framework for Configurable Federated Learning from Edge to HPC

Federated Learning (FL) is critical for edge and High Performance Computing (HPC) where data is not centralized and privacy is crucial. We present OmniFed, a modular framework designed around decoupling and clear separation of concerns for configuration, orchestration, communication, and training logic. Its architecture supports configuration-driven prototyping and code-level override-what-you-need customization. We also support different topologies, mixed communication protocols within a single deployment, and popular training algorithms. It also offers optional privacy mechanisms including Differential Privacy (DP), Homomorphic Encryption (HE), and Secure Aggregation (SA), as well as compression strategies. These capabilities are exposed through well-defined extension points, allowing users to customize topology and orchestration, learning logic, and privacy/compression plugins, all while preserving the integrity of the core system. We evaluate multiple models and algorithms to measure various performance metrics. By unifying topology configuration, mixed-protocol communication, and pluggable modules in one stack, OmniFed streamlines FL deployment across heterogeneous environments. Github repository is available at https://github.com/at-aaims/OmniFed.

Tyagi, Sahil [ORNL] (ORCID:0009000783144745)↗

The performance of ensemble-based free energy protocols in computing binding affinities to ROS1 kinase

Optimization of binding affinities for compounds to their target protein is a primary objective in drug discovery. Herein we report on a collaborative study that evaluates a set of compounds binding to ROS1 kinase. We use ESMACS (enhanced sampling of molecular dynamics with approximation of continuum solvent) and TIES (thermodynamic integration with enhanced sampling) protocols to rank the binding free energies. The predicted binding free energies from ESMACS simulations show good correlations with experimental data for subsets of the compounds. Consistent binding free energy differences are generated for TIES and ESMACS. Although an unexplained overestimation exists, we obtain excellent statistical rankings across the set of compounds from the TIES protocol, with a Pearson correlation coefficient of 0.90 between calculated and experimental activities.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Network Models of Active Degradation Mechanisms and Pathways for Service Life Prediction of Indoor and Outdoor PV Modules

ct: PV service lifetime prediction (SLP) enables accurate calculation of levelized cost of energy (LCOE), which is crucial to rationalizing PV investment and installation. However, SLP is challeging since PV reliability in the field is affected by many combined factors, including various environmental stresses and module quality. In order to map out the active degradation mechanisms and pathways that best resemble real world conditions, we introduce the framework of a study protocol and use network models fitted to data, to enable analysis and SLP of complex PV systems with multiple active degradation mechanisms. The study protocol is the experimental design, including module variants and different exposure conditions, selection of evaluation methods, time-series data acquisition and training of network models to these data. We present SLP of minimodules in the lab and PV systems in the field. For lab SLP, minimodules with 8 variants based on manufacturer, architecture, and encapsulation were prepared and aged in modified damp heat with or without full spectrum light exposure. Stepwise I-V and Suns-Voc data acquisition tracks changes in electrical properties including Rs,IV, Isc,IV, Vmp,PIV providing insights into power loss of minimodules. Network structural equation modeling (netSEM) was utilized to construct degradation pathway models that identify active degradation mechanisms and predict power loss over time. For field SLP, datastreams of Pmp values and I-V curve datastreams of two types of modules installed in three distinctly different Köppen-Geiger climate zones for 9 years were acquired. With power loss modes corresponding to uniform current loss (ΔPIsc), recombination (ΔPVoc), series resistance (ΔPRs), and current mismatch (ΔPImis) determined, the performance loss rates (PLR) were determined using PVplr. We show how to establish a study protocol framework to ensure appropriate parametric variations and valid data collection from the variants of your complex systems. Then the data-driven netSEM model fitting provides a comprehensive mapping of multiple active degradation mechanisms, and accurate service life prediction.

network model, degradation, photovoltaic, solar↗

Impact of cycling conditions on lithium-ion battery performance for electric vertical takeoff and landing applications

The development of better electrochemical energy storage systems has sparked significant interest in using Li-ion batteries for electric vertical takeoff and landing (eVTOL) applications. To ensure the optimal performance and safety of onboard batteries, their behavior under different charging/discharging protocols and environmental conditions must be understood. Here, this paper presents a comprehensive evaluation of commercial Li-ion batteries for eVTOL applications, focusing on their responses to varying charging/discharging strategies and mechanical vibrations experienced during flight. Through controlled experiments, the effects of rapid cycling on battery performance were investigated, including effects on lifespan, capacity, and internal resistance. Additionally, the impact of mechanical vibrations on battery behavior was assessed to identify potential challenges for onboard batteries. The results of this study revealed intriguing insights into the interplay between temperature, vibration, and battery performance. This work contributes to the broader adoption of electric aerial transportation, promising a greener and safer future for urban mobility.

18650 cells↗

Predicting Si-Anode Calendar Life Using Machine Learning: Correlating Electrolyte Properties and Electrochemical Signals

This study evaluates novel electrolytes tailored for Si-containing anodes to promote calendar-life. Drawing inspiration from advancements in electrolytes for Li-metal cells, the work investigates correlations between predicted electrolyte properties and measured electrochemical performance using several machine-learning models. By leveraging machine learning and advanced modeling techniques, this study aims to establish predictive frameworks that accelerate calendar-aging experiments and inform rational electrolyte design for Si-containing cells. In the present study, fifteen different electrolytes are evaluated in a Si-containing cell using an accelerated calendar-life protocol. For each electrolyte considered, 87 properties (features) from the Advanced Electrolyte Model were produced to identify key property/performance relationships. In this study, the best performing electrolytes were generally those formulations that included non-coordinating fluoroether solvents, and the most predictive features for long-term calendar-life were features related to salt concentration and electrolyte viscosity as well as early capacity, ionic conductivity, and Coulombic efficiency measurements. The framework developed in this study correlating electrolyte properties to measured electrochemical performance is expected to accelerate electrolyte design for Si-containing anodes and ultimately enable high-energy-density, long-life Li-ion batteries.

25 - ENERGY STORAGE↗