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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 109 records · Page 6

Multiscale Models for Fibril Formation: Rare Events Methods, Microkinetic Models, and Population Balances

Amyloid fibrils are thought to grow by a two-step dock-lock mechanism. However, previous simulations of fibril formation (i) overlook the bi-molecular nature of the docking step and obtain rates with first-order units, or (ii) superimpose the docked and locked states when computing the potential of mean force for association and thereby muddle the docking and locking steps. Here, we developed a simple microkinetic model with separate locking and docking steps and with the appropriate concentration dependences for each step. We constructed a simple model comprised of chiral dumbbells that retains qualitative aspects of fibril formation. We used rare events methods to predict separate docking and locking rate constants for the model. The rate constants were embedded in the microkinetic model, with the microkinetic model embedded in a population balance model for “bottom-up” multiscale fibril growth rate predictions. These were compared to “top-down” results using simulation data with the same model and multiscale framework to obtain maximum likelihood estimates of the separate lock and dock rate constants. We used the same procedures to extract separate docking and locking rate constants from experimental fibril growth data. Our multiscale strategy, embedding rate theories, and kinetic models in conservation laws should help to extract docking and locking rate constants from experimental data or long molecular simulations with correct units and without compromising the molecular description.

Shayesteh Zadeh, Armin (ORCID:0000000299896710)↗

Elucidating the Role of Biofilm-Forming Microbial Communities in Fermentative Biohydrogen Process: An Overview

Amongst the biofuels described in the literature, biohydrogen has gained heightened attention over the past decade due to its remarkable properties. Biohydrogen is a renewable form of H 2 that can be produced under ambient conditions and at a low cost from biomass residues. Innovative approaches are continuously being applied to overcome the low process yields and pave the way for its scalability. Since the process primarily depends on the biohydrogen-producing bacteria, there is a need to acquire in-depth knowledge about the ecology of the various assemblages participating in the process, establishing effective bioaugmentation methods. This work provides an overview of the biofilm-forming communities during H 2 production by mixed cultures and the synergistic associations established by certain species during H 2 production. The strategies that enhance the growth of biofilms within the H 2 reactors are also discussed. A short section is also included, explaining techniques used for examining and studying these biofilm structures. The work concludes with some suggestions that could lead to breakthroughs in this area of research.

59 BASIC BIOLOGICAL SCIENCES↗

Photovoltaic mission analysis

Photovoltaic analysis was used to support the planning, development, and guidance of the National Photovoltaic program. The analysis identified and evaluated: (1) photovoltaic applications likely to have major energy impact; (2) appropriate strategies for stimulating the growth of photovoltaic markets; and (3) critical issues, define scope of subsequent examinations.

Leonard, S. L.↗

A perspective on CELSS control issues

Some issues of Closed Ecological Life Support System (CELSS) analysis and design are effectively addressed from a systems control perspective. CELSS system properties that may be elucidated using control theory in conjunction with mathematical and simulation modeling are enumerated. The approach that is being taken to the design of a control strategy for the Crop Growth Research Chamber (CGRC) and the relationship of that approach to CELSS plant growth unit subsystems control is described.

Blackwell, Ann L.↗

Rewarding Grid-Friendly Behavior: Estimating the Potential Bill Reduction and Load Shifting Benefits of Dynamic Prices

Shifting electric load from times of peak demand can be a key strategy to slow price growth as reducing peak demand avoids the cost of upgrading generation, transmission and distribution infrastructure. Utilities are releasing time-varying prices, such as time of use rates or dynamic prices, to incentivize grid-friendly load shifting. New dynamic price programs provide insight into the true cost of operating electricity grids and the potential economic benefits of load shifting. Program developers and device manufacturers need to understand the economic opportunities in terms of 1) the variation in prices across hours, days, and seasons; 2) the change in utility bills for customers who don’t shift load; and 3) the potential load shifted and economic value of different technologies if manufacturers or aggregators deploy price-responsive controls. This paper estimates possible impacts of dynamic price adoption and load shifting controls if customers paid the dynamic rate from one pilot program. Statistical analysis of historical prices identified annual and seasonal metrics as well as representative price curves for each circuit in the pilot. Simulations for residential technologies with price-responsive controls including unitary heat pump water heaters, central multifamily heat pump water heaters, heating & cooling + storage systems, and pool pumps estimated the potential impacts of highly dynamic prices both with and without load shifting controls. Results showed the potential to reduce electricity costs on representative days by 42-94% and reduce consumption during times of high electricity prices by 63-100% compared to baseline operation for those flex-friendly devices.

Grant, Peter↗

Charting a Path for Reliable, Resilient and Affordable Clean Energy: A Roadmap for Three Communities in Utah

The roadmap identifies strategies to align deployment of distributed energy resources with the continued growth of utility-scale solar. The strategies outlined in the roadmap have been developed through collaborative discussions with project partners, but may not represent the opinions of, or positions of, all partner organizations and parties involved in the "Renewable Energy Impacts and Solutions in Utah" project. Rather, the strategies outlined in this Roadmap represent a suite of tools and actions that Salt Lake City, Park City, and the City of Moab can consider as each city works towards their community renewable electricity goals. While this Roadmap was developed to inform three communities as they progress towards their specific community energy goals, much of the analysis presented in the roadmap was conducted for Utah as a whole. Other communities in Utah can use the scenarios and strategies outlined in the roadmap to leverage the full potential of distributed energy resources to provide benefits to the community.

100% renewable↗

A new efficient grain growth model using a random Gaussian-sampled mode filter

This paper presents the use of a Gaussian neighborhood mode filter for predicting grain growth in a manner similar to the solutions obtained by a Monte Carlo Potts model. This flexible grain growth model can quickly utilize modern, computationally optimized data science strategies on graphics processing units to simulate grain growth up to 100 times faster than the state-of-the-art, publicly available Monte Carlo Potts model. We show that, given the correct neighborhood, the mode filter can replicate normal grain growth in two or three dimensions. In addition, the paper briefly demonstrates the ability to model limited anisotropic in grain boundary energy and mobility. Anisotropic grain boundary energy is modeled by defining a weighted mode filter operation. Anisotropic grain boundary mobility is modeled by scaling and orienting the Gaussian neighborhood in a particular direction.

Anisotropy↗

3D Artificial Solid-Electrolyte Interphase for Lithium Metal Anodes Enabled by Insulator–Metal–Insulator Layered Heterostructures

Despite considerable efforts to prevent lithium (Li) dendrite growth, stable cycling of Li metal anodes with various structures remains extremely difficult due to the direct contact of the liquid electrolyte with Li. Rational design of solid-electrolyte interphase (SEI) for 3D electrodes is a promising but still challenging strategy for preventing Li dendrite growth and avoiding lithium–electrolyte side reactions in Li-metal batteries. Here, a 3D architecture is constructed with g-C 3 N 4 /graphene/g-C 3 N 4 insulator–metal–insulator sandwiched nanosheets to guide uniform Li plating/stripping in the van der Waals gap between the graphene and the g-C 3 N 4 , and the function of which can be regarded as a 3D artificial SEI. Li deposition on the surface of g-C 3 N 4 is suppressed due to its insulating nature. However, its uniform lithiophilic sites and nanopore channels enable homogeneous lithium plating between the graphene and the g-C 3 N 4 , prohibiting the direct contact of the electrolyte with the Li metal. The use of the g-C 3 N 4 -layer-modified 3D anode enables long-term Li deposition with a high Coulombic efficiency and stable cycling of full cells under high cathode loading, limited Li excess, and lean electrolyte conditions. The concept of a 3D artificial SEI will shed light on developing safe and stable Li-metal anodes.

25 ENERGY STORAGE↗

A Novel Framework for Multi-Path Data Fusion in Earth Observation and New Observing Strategies: Applications to Predicting Forest Canopy Height

Exponential growth of data from Earth Observation (EO) assets has necessitated the development of sophisticated methods for data interpretation and management. NASA’s New Observing Strategy (NOS) approach aims to coordinate operations among complex heterogenous systems of constellations, requiring advanced Artificial Intelligence and Machine Learning (AI/ML) techniques. Despite significant advancements in AI/ML across various domains, the EO and machine learning for satellite (SatML) fields remain fragmented, often relying on adapted techniques rather than domain-specific solutions. We present a novel end-to-end data fusion framework tailored specifically for EO and SatML, addressing this gap by facilitating rapid development of AI/ML applications. This framework, called, Multimodal Earth Observation Workflow for Machine Learning (MEOW-ML), sup- ports the entire AI/ML lifecycle, from dataset manipulation, to model training, evaluation, and logging, and is designed to expedite the development of next-generation NOS deployments and SOTA in EO. We apply our framework to predict canopy height model (CHM) derived from lidar data. We integrate multiple data modalities through a hierarchical, multi-path model architecture, effectively identifying and leveraging the unique strengths of each data source to enhance predictive accuracy. Our experiments demonstrate that the multi-path architecture outperforms traditional single-path models and provides significant advantages in both accuracy and computational efficiency.

Mark Moussa↗

Scale-up study of enhancing algal growth through bioaugmentation with the indole-3-acetic acid producing bacteria Azospirillum brasilense

Algae-based wastewater treatment technologies can recover nutrients while generating algal biomass with diverse application potentials. While numerous bacteria have demonstrated the ability to enhance algal growth through symbiotic relationships in laboratory settings, scaling this benefit to larger applications remains challenging due to complex wastewater conditions and microbe-algae dynamics. This study explores the effectiveness of bioaugmentation with Azospirillum brasilense, a plant growth-promoting bacterium known for producing the phytohormone indole-3-acetic acid (IAA), in boosting algal productivity within an Algaewheel wastewater treatment system. Through a series of experiments conducted at lab-, pilot-, and full-scale levels, we evaluated the impact of bioaugmentation on algal growth and developed a bioaugmentation strategy for an Algaewheel system. The results indicate that a biweekly dosing, achieving a final bioaugmenting cell density of 0.2–4 × 10 9 cells/L, effectively doubles the biomass productivity in a residential subdivision wastewater treatment plant in Northern Illinois. The bacterial production of IAA was the primary mechanism driving this enhancement, as demonstrated by the similar growth and yield improvements observed with chemically supplemented IAA and bioaugmentation across all experimental scales. High-throughput sequencing of 18S rRNA genes revealed that the algal community in the bioaugmented tank exhibited more stable biodiversity than the control. Additionally, bioaugmentation improved nutrient removal efficiency during winter, highlighting its potential to enhance the overall performance and sustainability of algae-based wastewater systems. The developed bioaugmentation and chemical treatment methods offer further operational solutions for managing yield, optimizing biochemical profiles, and enhancing biofuel production potential.

Algae-bacterial symbiotic relationship↗

PET-FBA: A lightweight enzyme allocation and thermodynamics-constrained flux analysis approach to explore Escherichia coli metabolic adaptation to intracellular acidification

Escherichia coli employs diverse strategies to adapt to acidic environments that disrupt enzyme activity and the thermodynamic feasibility of essential reactions. To understand the impact of pH stress on cell metabolism, we present the PET-FBA (pH-, Enzyme protein allocation-, and Thermodynamics-constrained Flux Balance Analysis) framework. PET-FBA extends genome-scale modeling by integrating enzyme protein costs and reaction Gibbs free energy changes. Additionally, by incorporating pH-dependent enzyme kinetics in response to intracellular acidification, this framework enables the simulation of E. coli's metabolic adjustments across varying external pH levels. The model's accuracy is validated by comparing in silico growth simulations with experimental measurements under both anaerobic and aerobic conditions, as well as in silico gene knockouts of essential genes. By explicitly incorporating pH effects, our model accurately replicates the metabolic shift towards lactate production as the primary fermentation product at low pH in anaerobic conditions. This shift is only predicted when enzyme kinetics are dynamically adjusted as a function of pH. Further analysis revealed that this shift can be attributed to the reduced protein efficiency of the acetyl-CoA branch compared to lactate dehydrogenase under acidic stress, which then becomes crucial for maintaining NAD regeneration and cell growth at low pH. Furthermore, we identified strategies for enhancing cell growth under acidic anaerobic conditions by improving the enzyme activity of lactate dehydrogenase and pyruvate formate lyase, which increases NAD production efficiency and reduces enzyme protein allocation costs. Designed as a lightweight yet versatile framework, PET-FBA enables efficient genome-scale metabolic analysis. Using E. coli as a model system, our framework provides a systematic approach to understanding metabolic responses to environmental stress, pinpointing key metabolic bottlenecks, and identifying potential targets for strain optimization.

42 ENGINEERING↗

Circumventing thermodynamic limitations in converting carbon dioxide into carbon nanotubes via tandem catalysis

Carbon nanotubes (CNTs) are important materials for electronics and structural composites, but their production still relies on hydrocarbon-based chemical vapor deposition, an energy-intensive and fossil-dependent process, limited by rapid catalyst deactivation. Using CO2 as a carbon feedstock offers a sustainable route for CNT synthesis, yet direct CO2 conversion to CNTs is thermodynamically unfavorable and existing CO2-to-carbon pathways mainly yield amorphous or weakly graphitized solids. Here, we demonstrate a tandem electrochemical–thermochemical (EC-TC) strategy that overcomes these limitations. CO2 is first electrochemically reduced to a tunable mixture of C2H4 and CO, which is directly fed into a thermochemical reactor and converted into CNTs with controllable morphology and high CNT-to-metal mass ratios (~200) over NiFe catalysts at 750 °C. In situ synchrotron-based characterization and density functional theory calculations reveal that CO dissociation and C2H4 decomposition on NiFe alloys cooperatively promote CNT nucleation and sustained growth. This EC-TC strategy establishes a modular route for converting CO2 into value-added carbon nanomaterials.

03 NATURAL GAS↗

Lithium–Metal Batteries via Suppressing Li Dendrite Growth and Improving Coulombic Efficiency

Lithium–metal batteries (LMB) are recognized as one of the most promising candidates for the next generation of batteries due to their high energy density. Extensive studies have been refocused on the field in the past decade to make the technology commercially viable. Unfortunately, despite exciting progress that has been made, the practical application of LMBs is still hampered by the uncontrollable Li plating morphology and inferior Coulombic efficiency (CE) during cycling. Herein, first, the relevant research that has been carried out in the past decade (2010–2021) is briefly summarized and then the Li plating behaviors, mechanistic understanding of these behaviors, and strategies to suppress Li dendrite growth are discussed. Finally, the methods and techniques to improve Coulombic efficiency (CE) is discussed, especially the design of liquid electrolytes, and possible research directions for the future development of LMBs.

25 ENERGY STORAGE↗

Bacterial Tradeoffs in Growth Rate and Extracellular Enzymes

Like larger organisms, bacteria possess traits, or phenotypic characteristics, that influence growth and impact ecosystem processes. Still, it remains unclear how these traits are organized across bacterial lineages. Using 49 bacterial strains isolated from leaf litter in Southern California, we tested the hypothesis that bacterial growth rates trade off against extracellular enzyme investment. We also tested for phylogenetic conservation of these traits under high and low resource conditions represented, respectively, by Luria broth (LB) and a monomer-dominated medium extracted from plant litter. In support of our hypotheses, we found a negative correlation between the maximum growth rate and the total activity of carbon-, nitrogen-, and phosphorus-degrading extracellular enzymes. However, this tradeoff was only observed under high resource conditions. We also found significant phylogenetic signal in maximum growth rate and extracellular enzyme investment under high and low resource conditions. Driven by our bacterial trait data, we proposed three potential life history strategies. Resource acquisition strategists invest heavily in extracellular enzyme production. Growth strategists invest in high growth rates. Bacteria in a third category showed lower potential for enzyme production and growth, so we tentatively classified them as maintenance strategists that may perform better under conditions we did not measure. These strategies were related to bacterial phylogeny, with most growth strategists belonging to the phylum Proteobacteria and most maintenance and resource acquisition strategists belonging to the phylum Actinobacteria. By accounting for extracellular enzyme investment, our proposed life history strategies complement existing frameworks, such as the copiotroph-oligotroph continuum and Grime’s competitorstress tolerator-ruderal triangle. Our results have biogeochemical implications because allocation to extracellular enzymes versus growth or stress tolerance can determine the fate and form of organic matter cycling through surface soil.

59 BASIC BIOLOGICAL SCIENCES↗

Lithium Deposition-Induced Fracture of Carbon Nanotubes and Its Implication to Solid-State Batteries

The increasing demand for safe and dense energy storage has shifted research focus from liquid electrolyte-based Li-ion batteries toward solid-state batteries (SSBs). However, the application of SSBs is impeded by uncontrollable Li dendrite growth and short circuiting, the mechanism of which remains elusive. Herein, we conceptualize a scheme to visualize Li deposition in the confined space inside carbon nanotubes (CNTs) to mimic Li deposition dynamics inside solid electrolyte (SE) cracks, where the high-strength CNT walls mimic the mechanically strong SEs. We observed that the deposited Li propagates as a creeping solid in the CNTs, presenting an effective pathway for stress relaxation. When the stress-relaxation pathway is blocked, the Li deposition-induced stress reaches the gigapascal level and causes CNT fracture. Mechanics analysis suggests that interfacial lithiophilicity critically governs Li deposition dynamics and stress relaxation. Furthermore, our study offers critical strategies for suppressing Li dendritic growth and constructing high-energy-density, electrochemically and mechanically robust SSBs.

25 ENERGY STORAGE↗

Understanding Environmental Barrier Coating Lifetimes and Performance for Industrial Gas Turbines

Hydrogen or hydrogen blend fuels are expected to replace natural gas in land-based industrial gas turbines (IGTs) to support a greener power economy. Silicon carbide (SiC) base ceramic matrix composites (CMCs) are considered for replacement of Ni-based superalloys to facilitate future efficiency improvements. SiC CMCs require environmental barrier coatings (EBCs) to mitigate volatilization from high-temperature steam, thus making the EBC lifetime critical information for identifying CMC component lifetimes. Here, the goal of this project is to determine the maximum bond coating temperature underneath the EBC for achieving an IGT component lifetime goal of 25,000 h, which is far greater than current CMC component lifetime requirements for aeroturbine applications. To provide data for the lifetime model, laboratory testing used atmospheric plasma-sprayed rare-earth silicate EBCs on monolithic SiC substrates with an intermediate Si bond coating. Specimens exposed to 1-h thermal cycles in flowing air–steam environments and reaction kinetics were assessed from 700 °C to 1350 °C by measuring the thickness of the thermally grown silica scales. The silica growth and phase transformation appear critical in predicting EBC lifetime and several strategies have been explored to reduce the oxide growth rate and improve EBC durability at elevated temperatures. Advanced characterization using Raman spectroscopy has helped clarify this system.

08 HYDROGEN↗

Understanding EBC Lifetimes and Performance for Industrial Gas Turbines

Hydrogen or hydrogen blend fuels are expected to replace natural gas in land-based industrial gas turbines (IGTs) to support a greener power economy. Silicon carbide (SiC) base ceramic matrix composites (CMCs) are considered for replacement of Ni-based superalloys to facilitate future efficiency improvements. SiC CMCs require environmental barrier coatings (EBCs) to mitigate volatilization from high-temperature steam, thus making the EBC lifetime critical information for identifying CMC component lifetimes. The goal of this project is to determine the maximum bond coating temperature underneath the EBC for achieving an IGT component lifetime goal of 25,000 h, which is far greater than current CMC component lifetime requirements for aero-turbine applications. To provide data for the lifetime model, laboratory testing used plasma-sprayed rare-earth silicate EBCs on monolithic SiC substrates with an intermediate Si bond coating. Specimens exposed to 1-h thermal cycles in flowing air-steam environments and reaction kinetics were assessed from 700°-1350°C by measuring the thickness of the thermally grown silica scales. The silica growth and phase transformation appear critical in predicting EBC lifetime and several strategies have been explored to reduce the oxide growth rate and improve EBC durability at elevated temperatures. Advanced characterization using Raman spectroscopy has helped clarify this system.

Ridley, Mackenzie↗

Optimized In Situ Doping Strategy Stabling Single-Crystal Ultrahigh-Nickel Layered Cathode Materials

Single-crystal Ni-rich cathodes offer promising prospects in mitigating intergranular microcracks and side reaction issues commonly encountered in conventional polycrystalline cathodes. However, the utilization of micrometer-sized single-crystal particles has raised concerns about sluggish Li + diffusion kinetics and unfavorable structural degradation, particularly in high Ni content cathodes. Herein, we present an innovative in situ doping strategy to regulate the dominant growth of characteristic planes in the singlecrystal precursor, leading to enhanced mechanical properties and effectively tackling the challenges posed by ultrahigh-nickel layered cathodes. Compared with the traditional dry-doping method, our in situ doping approach possesses a more homogeneous and consistent modifying effect from the inside out, ensuring the uniform distribution of doping ions with large radius (Nb, Zr, W, etc). Further, this mitigates the generally unsatisfactory substitution effect, thereby minimizing undesirable coating layers induced by different solubilities during the calcination process. Additionally, the uniformly dispersed ions from this in situ doping are beneficial for alleviating the two-phase coexistence of H2/H3 and optimizing the Li + concentration gradient during cycling, thus inhibiting the formation of intragranular cracks and interfacial deterioration. Consequently, the in situ doped cathodes demonstrate exceptional cycle retention and rate performance under various harsh testing conditions. Our optimized in situ doping strategy not only expands the application prospects of elemental doping but also offers a promising research direction for developing high-energy-density single-crystal cathodes with extended lifetime.

25 ENERGY STORAGE↗