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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 523 records · Page 29

Low quantum efficiency of μ-oxo iron bisporphyrin photocatalysts explained with femtosecond M-edge XANES

Bridged μ-oxo iron porphyrins serve as photocatalysts for oxidative organic transformations, but suffer from low photon-to-product efficiency. This low photochemical quantum yield is most commonly attributed to the short lifetime of a disproportionated TPPFe(II)/TPPFe(IV)=O state, but an alternate hypothesis suggests that the majority photoproduct is a catalytically inactive ligand-centered TPPFe(III)+/TPPFe(III)–O – ion pair. We use femtosecond optical and extreme ultraviolet (XUV) spectroscopy to investigate the early photodynamics of the μ-oxo iron bisporphyrin (TPPFe) 2 O and identify the primary loss mechanism. XUV spectroscopy probes 3p → 3d transitions, corresponding to M 2,3 -edge XANES spectra, and is a distinctive probe of the metal oxidation state. Excitation of the mixed π–π*/ligand-to-metal charge transfer (LMCT) band results in the formation of an iron(II)/iron(III) LMCT state in tens of femtoseconds. This state decays on a subpicosecond timescale to the ligand-centred iron(III) ion pair state, and no TPPFe(IV)=O species is observed within the sensitivity of the measurement. Finally, the lack of an iron(II)/iron(IV) XANES spectrum suggests that preferential formation of the inactive iron(III) ion pair state is a main cause of the low quantum yield of this and similar bisporphyrins.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Analysis of Power-Maximizing Region 2 Controllers for Wind and Marine Turbines

Wind and marine energy are rapidly growing and complementary technologies that share some techniques for simplified modeling and control, particularly in below-rated flow speeds. A turbine operator has several choices of controller for maximizing power in Region 2. The simple and ubiquitous KΩ 2 control law is often effective but limited in its flexibility. Alternative controllers use reference tracking to split the control objectives into a low-bandwidth optimal tip-speed ratio tracking loop to maximize steady-state power and a higher-bandwidth proportional-integral control loop to reject inflow turbulence. Several options exist for identifying the slowly varying optimal set point during operation, based on estimating the inflow velocity or filtering the power or torque signals. This study compares the trade-offs between performance and other design priorities for a few choices of reference-tracking controller in the literature for reference wind and marine turbines. Analysis is performed in the frequency domain using the linearization of each controller, and the impact of turbulent disturbances on the closed-loop system is described. The controllers are simulated in OpenFAST to analyze their performance with higher-order nonlinear turbine dynamics.

17 WIND ENERGY↗

Current-based metrology with two-terminal mesoscopic conductors

The traditional approach to quantum parameter estimation focuses on the quantum state, deriving fundamental bounds on precision through the quantum Fisher information. In most experimental settings, however, performing arbitrary quantum measurements is highly unfeasible. In open quantum systems, an alternative approach to metrology involves the measurement of stochastic currents flowing from the system to its environment. However, the present understanding of current-based metrology is mostly limited to Markovian master equations. Considering a parameter estimation problem in a two-terminal mesoscopic conductor, we identify the key elements that determine estimation precision within the Landauer-Büttiker formalism. Crucially, this approach allows us to address arbitrary coupling and temperature regimes. Furthermore, we obtain analytical results for the precision in linear-response and zero-temperature regimes. For the specific parameter estimation task that we consider, we demonstrate that the boxcar transmission function is optimal for current-based metrology in all parameter regimes.

Landauer formula↗

Anomaly Detection and Identification Using a Leave-One-Variable-Out Method

At nuclear power plants (NPPs), anomaly detection and identification (i.e., determining the causes of anomalies) are important tasks for ensuring the safe and efficient operation of NPPs. These tasks are currently labor-intensive and costly, and are made more difficult by the size and complexity of NPP systems. An alternative approach to conducting these tasks is to automate them, such as via the reconstruction-based contribution method, which is a well-researched unsupervised machine learning method that uses a data-driven model of anomaly-free behavior to detect events and then identify each variable’s contributions to those events. The present effort developed a novel contribution approach that utilized a leave-one-variable-out (LOVO) model, with which each variable is predicted using all the other variables. The novelty lay in transforming this model into a reconstruction model and modifying the identification algorithm to work with the new reconstruction model. To evaluate this method in a controlled environment, a synthetic dataset based on spring-mass-damper (SMD) systems (commonly found in mechanical engineering references) was used, with known anomalies introduced into the system. The proposed method successfully detected the anomalies and afforded insights into their causes, thus enabling the appropriate identifications to be made.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Northstar Accelerator Based Mo99 Production Facility Design Support

Facility design support in FY20 centered on transfer of the target insertion and design details to MBraun and Springs, the companies under contract via Northstar to do the hot cell, target insertion and the local target shielding. A significant number of changes have been introduced by these vendors which have been reviewed and critiqued. In addition, the company contracted to produce the Mo100 disks announced that the tolerance on the thickness of 0.5 mm would be ±25%. An alternative design of the target holder was proposed. Bulk shielding and local target shielding design work has continued also and will be reported. Ongoing design and cooling issues continue to arise as the facility takes shape and moves toward completion. LANL is part of the team identifying, analyzing and designing solutions to these issues. Many of these are covered in this report.

43 PARTICLE ACCELERATORS↗

SB10 Frit Recommendation, and Evaluations of the Glass Variability Study and Cs-137 Concentrations in Strip Effluent Based on May 2021 Projections

The Defense Waste Processing Facility (DWPF) is currently preparing to initiate processing of Sludge Batch 10 (SB10), which is comprised of material from Tanks 11H, 13H, 15H, and 26F, Alternate Feed Stock-2 (AFS-2) and Sodium Reactor Experiment (SRE) material from H-Canyon. In support of SB10 qualification, frit development using 2020 Tank 40 blend projections and experimental work for the glass variability study were previously conducted. Frit 473 and Frit 209 were identified as candidate frits and both were included in the development of the variability study test matrix; however, a final frit recommendation was postponed until more information could be determined about the composition of SB10 after washing. In May 2021, Savannah River Remediation (SRR) reprojected SB10 based on the analytical results from the Tank 51 qualification sample that was washed in the Savannah River National Laboratory (SRNL) Shielded Cells Facility.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

PHASM: A Toolkit for Creating AI Surrogate Models within Legacy Codebases

PHASM (“Parallel Hardware viA Surrogate Models”) is a software toolkit for creating AI-based surrogate models of scientific code. AI-based surrogate models are widely used for creating fast and inverse simulations. PHASM anticipates an additional future use case: adapting legacy code to modern hardware. While data centers are investing in heterogeneous hardware such as GPUs and FPGAs, many established scientific codebases remain unable to take advantage of the hardware’s higher parallelism without undergoing a costly rewrite. An alternative is to train a AI-based surrogate model to mimic computationally intensive functions in the code, and run the surrogate instead. PHASM formalizes a development lifecycle for such surrogate models, including discovering functions amenable to replacement with a surrogate model, predicting the resulting performance, identifying the function’s space of inputs and outputs, binding the model to the code, and managing model versions. A suite of software tools for facilitating these steps was written and validated against a set of model problems.

97 MATHEMATICS AND COMPUTING↗

Hierarchical Optimal Power Flow with Improved Gradient Evaluation

Existing algorithms to solve alternating-current optimal power flow (AC-OPF) often exploit linear approximations to simplify system models and accelerate computations. In this paper, we improve a recent hierarchical OPF algorithm, which rested on primal-dual gradients evaluated in a linearized distribution power flow model. Specifically, we identify a risk of voltage violation arising from the model linearization, and propose a more accurate gradient evaluation method to eliminate that risk. We further develop a hierarchical primal-dual algorithm to solve OPF based on the proposed gradient evaluation method. Numerical results on IEEE networks show that our algorithm can enhance voltage safety with satisfactory computational efficiency.

distributed algorithm↗

Assessing the levelized cost of energy in South Korea

This study evaluates the levelized cost of energy (LCOE) for various energy technologies in the Republic of Korea (Korea) from 2023 to 2050, highlighting cost trajectories and potential crossovers among competing technologies. The analysis projects that, based on our set of assumptions, utility-scale photovoltaic systems achieve lower LCOEs than nuclear by 2030, while fixed offshore wind is expected to become cost-competitive with coal-fired generation around the same time. Floating offshore wind is projected to reach cost parity with coal in the late 2030s. Co-firing with natural gas and green hydrogen is identified as the highest-cost generation option due to high natural gas and green fuel costs and declining capacity utilization. This study further examines the potential for hybrid systems that integrate renewable energy with energy storage to serve as flexible, cost-effective, zero-emission alternatives to green hydrogen-based generation. Spatial LCOE assessments indicate that near-shore offshore wind sites may achieve lower costs despite modest capacity factors, contingent on site-specific factors such as grid integration and social acceptance. The findings indicate that renewable energy technologies are expected to experience continued cost declines, with solar photovoltaic becoming the most competitive energy source in Korea by 2030–2035. Incorporating social costs accelerates this shift from conventional alternatives.

Green hydrogen↗

Novel Class of Rhenium Borides Based on Hexagonal Boron Networks Interconnected by Short B 2 Dumbbells

Transition metal borides are known due to their attractive mechanical, electronic, refractive, and other properties. A new class of rhenium borides was identified by synchrotron single-crystal X-ray diffraction experiments in laser-heated diamond anvil cells between 26 and 75 GPa. Recoverable to ambient conditions, compounds rhenium triboride (ReB 3 ) and rhenium tetraboride (ReB 4 ) consist of close-packed single layers of rhenium atoms alternating with boron networks built from puckered hexagonal layers, which link short bonded (~ 1.7 angstrom) axially oriented B 2 dumbbells. The short and incompressible Re-B and B-B bonds oriented along the hexagonal c-axis contribute to low axial compressibility comparable with the linear compressibility of diamond. Sub-millimeter samples of ReB 3 and ReB 4 were synthesized in a large-volume press at pressures as low as 33 GPa and used for material characterization. Crystals of both compounds are metallic and hard (Vickers hardness, H V = 34(3) GPa). Geometrical, crystal-chemical, and theoretical analysis considerations suggest that potential ReB x compounds with x > 4 can be based on the same principle of structural organization as in ReB 3 and ReB 4 and possess similar mechanical and electronic properties.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Chemistry of Materials Underpinning Photoelectrochemical Solar Fuel Production

Since its inception, photoelectrochemistry has sought to power the generation of fuels, particularly hydrogen, using energy from sunlight. Efficient and durable photoelectrodes, however, remain elusive. Here we review the current state of the art, focusing our discussion on advances in photoelectrodes made in the past decade. We open by briefly discussing fundamental photoelectrochemical concepts and implications for photoelectrode function. We next review a broad range of semiconductor photoelectrodes broken down by material class (oxides, nitrides, chalcogenides, and mature photovoltaic semiconductors), identifying intrinsic properties and discussing their influence on performance. We then identify innovative in situ and operando techniques to directly probe the photoelectrode|electrolyte interface, enabling direct assessment of structure–property relationships for catalytic surfaces in active reaction environments. We close by considering more complex photoelectrochemical fuel-forming reactions (carbon dioxide and nitrogen reduction, as well as alternative oxidation reactions), where product selectivity imposes additional criteria on electrochemical driving force and photoelectrode architecture. By contextualizing recent literature within a fundamental framework, we seek to provide direction for continued progress toward achieving efficient and stable fuel-forming photoelectrodes.

08 HYDROGEN↗

Chemical and electrochemical pathways to low-carbon iron and steel

Currently, the iron and steel industry is responsible for 7% of global CO 2 emissions. In this review, we summarize the operational principles of current emissions-intensive steelmaking technologies and review emerging low- and zero-carbon technologies that could substantially reduce emissions. Current technologies that are discussed include blast furnaces, electric arc furnaces, and smelting. Promising low-carbon routes include use of alternative reductants for ore processing (hydrogen direct reduction, hydrogen plasma-smelting, hydrogen smelting, and ammonia-based reduction), electrolytic iron production (with aqueous and molten oxide electrolytes) and biocarbon-based electric arc furnace operation. Advantages of each approach are presented, and remaining research hurdles are identified.

36 MATERIALS SCIENCE↗

A robust plasma-based laser amplifier via stimulated Brillouin scattering

Brillouin amplification in plasma is more resilient to fluctuations in the laser and plasma parameters than Raman amplification, making it an attractive alternative to Raman amplification. In this work, we focus on high plasma densities, n 0 > n cr /4, where stimulated Raman scattering is not possible and laser beam filamentation is the dominant competing process. Through analytic theory and multi-dimensional particle-in-cell simulations, we identify a parameter regime for which Brillouin amplification can be efficient while maintaining filamentation of the probe at a controlled level. We demonstrate pump-to-probe compression ratios of up to 72 and peak amplified probe fluences over 1 kJ cm -2 with ≃50% efficiency. High pulse quality is maintained through control of parasitic filamentation, enabling operation at large beam diameters. Provided the pump and probe pulse diameters can be increased to 1 mm, our results suggest that Brillouin amplification can be used to produce sub-picosecond pulses of petawatt power.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Engineering long-lived entanglement through dissipation in quantum hybrid solid-state platforms

Spin squeezing, a form of many-body entanglement, is a crucial resource in quantum metrology and information processing. While experimentally viable protocols for generating stable spin squeezing have been proposed in quantum optics setups, there is growing interest in quantum hybrid solid-state systems as alternative platforms for both engineering and exploring many-body quantum phenomena. In this work, we propose a scheme to generate long-lived spin squeezing in an ensemble of solid-state qubits interacting with electromagnetic noise emitted by a squeezed solid-state bath. We identify the conditions under which quantum correlations within the bath can be transferred to the qubit array, driving it into an entangled state independently of its initial configuration. To assess the experimental feasibility of our approach, we analyze the dynamics of an array of solid-state spin defects coupled to a common ferromagnetic bath, which is driven into a non-equilibrium squeezed state through its interaction with a surface acoustic wave mode. Our results demonstrate that the ensemble can exhibit steady-state spin squeezing under suitable conditions, opening new pathways for the generation of robust many-body entanglement in solid-state spin ensembles.

NV centers↗

Validation of the DESI 2024 Lyman alpha forest BAL masking strategy

Broad absorption line quasars (BALs) exhibit blueshifted absorption relative to a number of their prominent broad emission features. These absorption features can contribute to quasar redshift errors and add absorption to the Lyman-α (Lyα) forest that is unrelated to large-scale structure. We present a detailed analysis of the impact of BALs on the Baryon Acoustic Oscillation (BAO) results with the Lyα forest from the first year of data from the Dark Energy Spectroscopic Instrument (DESI). The baseline strategy for the first year analysis is to mask all pixels associated with all BAL absorption features that fall within the wavelength region used to measure the forest. We explore a range of alternate masking strategies and demonstrate that these changes have minimal impact on the BAO measurements with both DESI data and synthetic data. This includes when we mask the BAL features associated with emission lines outside of the forest region to minimize their contribution to redshift errors. We identify differences in the properties of BALs in the synthetic datasets relative to the observational data, as well as use the synthetic observations to characterize the completeness of the BAL identification algorithm, and demonstrate that incompleteness and differences in the BALs between real and synthetic data also do not impact the BAO results for the Lyα forest.

Lyman alpha forest↗

Asymmetric response of Amazon forest water and energy fluxes to wet and dry hydrological extremes reveals onset of a local drought-induced tipping point

Understanding the effects of intensification of Amazon basin hydrological cycling—manifest as increasingly frequent floods and droughts—on water and energy cycles of tropical forests is essential to meeting the challenge of predicting ecosystem responses to climate change, including forest “tipping points”. Here, we investigated the impacts of hydrological extremes on forest function using 12+ years of observations (between 2001–2020) of water and energy fluxes from eddy covariance, along with associated ecological dynamics from biometry, at the Tapajós National Forest. Measurements encompass the strong 2015–2016 El Niño drought and La Niña 2008–2009 wet events. We found that the forest responded strongly to El Niño-Southern Oscillation (ENSO): Drought reduced water availability for evapotranspiration ( ET ) leading to large increases in sensible heat fluxes ( H ). Partitioning ET by an approach that assumes transpiration ( T ) is proportional to photosynthesis, we found that water stress-induced reductions in canopy conductance ( G s ) drove T declines partly compensated by higher evaporation ( E ). By contrast, the abnormally wet La Niña period gave higher T and lower E , with little change in seasonal ET . Both El Niño-Southern Oscillation (ENSO) events resulted in changes in forest structure, manifested as lower wet-season leaf area index. However, only during El Niño 2015–2016, we observed a breakdown in the strong meteorological control of transpiration fluxes (via energy availability and atmospheric demand) because of slowing vegetation functions (via shutdown of G s and significant leaf shedding). Drought-reduced T and G s , higher H and E , amplified by feedbacks with higher temperatures and vapor pressure deficits, signaled that forest function had crossed a threshold, from which it recovered slowly, with delay, post-drought. In conclusion, identifying such tipping point onsets (beyond which future irreversible processes may occur) at local scale is crucial for predicting basin-scale threshold-crossing changes in forest energy and water cycling, leading to slow-down in forest function, potentially resulting in Amazon forests shifting into alternate degraded states.

54 ENVIRONMENTAL SCIENCES↗

Biopower: Impact of Biofuels Deployment to Replace Petroleum Liquids in Stationary Power Applications

Petroleum-based liquids are used in a portion of power generation applications in the United States, predominantly in the New England, Middle Atlantic, South Atlantic, and Pacific-Noncontiguous regions. Power plants that burn petroleum liquids, such as distillate or residual fuel oils, are generally used for short periods to accommodate peak electricity demands. The Energy Information Administration (EIA) estimated the U.S. consumption of petroleum liquids for electricity generation at 27 million barrels in 2018, representing a cost of $2.4 billion annually. This study assesses the potential to displace all or part of the petroleum liquids in U.S. power generation with biofuels. The biofuels for this application are assumed to be derived from terrestrial feedstocks, with conversion routes of both fast pyrolysis (bio-oil) and hydrothermal liquefaction (bio-crude). Regional models were used to assess the availability and cost of three different base materials: clean wood, forest residues, and corn stover; each was evaluated in the laboratory at small or experimental scales for conversion to bio-oil or bio-crude. The estimated biofuel production quantities depend on equivalent heating versus the current heavy fuel. In this report, the availability of each type of biomass for each section of the U.S. Census division is estimated using a conservative broker price (in each case) of $ 80 per dry tonne. The results show that the petroleum-liquid power generation in each of the Census Divisions could be supplied by one or more of the feedstocks evaluated. For all regions, clean wood supplies (only) could provide ample supply. For all but two regions (Middle Atlantic and New England), forest residues alone are sufficient. Finally, for all regions but three (Middle Atlantic, New England, and South Atlantic), corn stover alone is adequate. The Minimum Fuel Selling Price (MFSP) of bio-oil and bio-crude were also estimated for each feedstock type and Census Division. This analysis showed that fast pyrolysis bio-oil projections to be lower (14% on average) than current wholesale petroleum-based heating oil prices in each of the regions, assuming 100 dry tonnes/day processing capacity. However, bio-crude predictions were significantly higher (2X) in all cases. The effect of biorefinery size was also quantified. Based on the preliminary results in this study, it is apparent the biofuels could be an economical alternative for current petroleum liquids in U.S. power generation. However, additional research is needed to determine the necessary biofuel characteristics to support existing generation equipment. It is recommended that both power generation and biofuel production stakeholders to be engaged to outline the research and testing needed to identify the technical hurdles to enable the opportunity.

02 PETROLEUM↗

Multi-scale Simulation, Calibration, and Optimization of Calcium Carbonate Precipitation in Microbial Communities

Ensuring the efficient engineering of microbially induced calcium carbonate precipitation (MICP) is crucial for a variety of environmental and civil engineering applications, such as soil stabilization and carbon sequestration. Addressing this need, we present a comprehensive multi-scale workflow that begins with the isolation of calcium carbonate-producing microbes from soil samples, followed by metagenomic sequencing and metabolic reconstruction. We then characterize microbial growth phenotypes under diverse nutrient conditions, compare observed growth with metabolic model predictions, and apply the Consistent Reproduction of Phenotype (CROP) algorithm to refine these models. Furthermore, we analyze metabolite consumption and production, and develop a consumer-resource model that is calibrated using time-series measurements of growth rates, pH levels, and calcium carbonate precipitation. The primary benefit of our approach lies in its ability to predict and control MICP outcomes, facilitated by a Bayesian methodology that incorporates priors on initial conditions and parameters. This allows us to compute posteriors by integrating experimental data, and to solve a risk optimization problem under uncertainty to identify nutrient conditions that maximize calcium carbonate production. In contrast to non-Bayesian methods, which fail to quantify uncertainty accurately, our approach provides a more reliable pathway to optimizing nutrient conditions, enhancing the likelihood of achieving desired MICP outcomes. This positions our method as a superior alternative in the quest to improve MICP through engineered microbial consortia.

54 ENVIRONMENTAL SCIENCES↗