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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Improving Peptide-Level Mass Spectrometry Analysis via Double Competition

A critical statistical task in the analysis of shotgun proteomics data involves controlling the false discovery rate (FDR) among the reported set of discoveries. This task is most commonly solved at the peptide-spectrum match (PSM) level by using target-decoy competition (TDC), in which a set of observed spectra are searched against a database containing a mixture of real (target) and decoy peptides. The PSM-level procedure can be adapted to the peptide level by selecting the top-scoring PSM per peptide prior to FDR estimation. Here, we investigate both PSM-level and peptide-level FDR control methods and come to two conclusions. First, although the TDC procedure is provably correct under certain assumptions, we observe that one of these assumptions - that incorrect PSMs are independent of one another - is frequently violated. Hence, we empirically demonstrate that TDC-based PSM-level FDR estimates can be liberally biased. Further, we propose that researchers avoid PSM-level results and instead focus on peptide-level analysis. Second, we investigate three ways to carry out peptide level TDC and show that the most common method ("PSM-only") offers the lowest statistical power in practice. The most powerful method, peptide-level FDR with PSM competition ("PSM-and-peptide"), carries out competition first at the PSM level and then again at the peptide level. In our experiments, this approach yields an average increase of 17% more discovered peptides at a1% FDR threshold relative to the PSM-only method.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Simultaneously Enhanced Hydrophilicity and Stability of a Metal‐Organic Framework via Post‐Synthetic Modification for Water Vapor Sorption/Desorption

Abstract With increasing demands for high‐performance water sorption materials, metal‐organic frameworks (MOFs) have gained considerable attention due to their high maximum uptake capacities. In many cases, however, high overall capacity is not necessarily accomplishing high working capacity under operating conditions, due to insufficient hydrophilicity and/or water stability. Herein, we present a post‐synthetic modification (PSM) of MOF‐808, with di‐sulfonic acids enhancing simultaneously its hydrophilicity and water stability without sacrificing its uptake capacity of ≈30 mmol g −1 . Di‐sulfonic acid PSM enabled a shift of the relative humidity (RH) associated with a sharp step in water vapor sorption from 35–40 % RH in MOF‐808 to below 25 % RH. While MOF‐808 lost uptake capacity and crystallinity over multiple sorption/desorption cycles, the di‐sulfonic acid PSM MOF‐808 retained >80 % of the original capacity. PSM MOF‐808 exhibited good hydrothermal stability up to 60 °C and high swing capacity.

Luo, Tian‐Yi↗
DOE OSTI2022

Simultaneously Enhanced Hydrophilicity and Stability of a Metal-Organic Framework via Post-Synthetic Modification for Water Vapor Sorption/Desorption

With increasing demands for high-performance water sorption materials, metal-organic frameworks (MOFs) have gained considerable attention due to their high maximum uptake capacities. In many cases, however, high overall capacity is not necessarily accomplishing high working capacity under operating conditions, due to insufficient hydrophilicity and/or water stability. Herein, we present a post-synthetic modification (PSM) of MOF-808, with di-sulfonic acids enhancing simultaneously its hydrophilicity and water stability without sacrificing its uptake capacity of ≈30 mmol g -1 . Further, di-sulfonic acid PSM enabled a shift of the relative humidity (RH) associated with a sharp step in water vapor sorption from 35–40 % RH in MOF-808 to below 25 % RH. While MOF-808 lost uptake capacity and crystallinity over multiple sorption/desorption cycles, the di-sulfonic acid PSM MOF-808 retained >80 % of the original capacity. PSM MOF-808 exhibited good hydrothermal stability up to 60 °C and high swing capacity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Postsynthetic Oxidation of the Coordination Site in a Heterometallic Metal-Organic Framework: Tuning Catalytic Behaviors

Postsynthetic modification (PSM) in metal-organic frameworks (MOFs) can introduce multiple functionalities and alter the structural function for the desired application. However, the PSM of the coordination site faces the challenges of structural collapse or incompatibility between the original metal site and the newly formed coordination group. Herein, we developed a novel concept of introducing “primary” and “secondary” nodes, coexisting in a water-stable, Zr-based heterometallic MOF, [Zr6(µ3-OH)8(OH)8][CuI4(L1)4]2 (1-SH-a, H2L1 = 6-mercaptopyridine-3-carboxylic acid). The post-synthetic oxidation at the coordination site was successfully achieved in the “secondary” nodes [CuI4(L1)4]4-, while the robust “primary” nodes [Zr6(µ3-OH)8(OH)8]8+ stabilized the whole framework to form [Zr6(µ3-OH)8(OH)8][(CuI0.44CuII0.56(OH)0.56)4(L2)4]2 (1-SO3H, H2L2 = 6-sulfonicotinic acid). PSM of 1-SH-a to form 1-SO3H dramatically tuned the catalytic properties toward the styrene oxide ring-opening reaction to give a regioselectivity of primary alcohol (A) of ~99% compared with 1-SH-a (~71%).

Han, Yi↗
DOE OSTI2026

Challenging conventional assumptions in PV: a high-throughput open-air approach to low-cost perovskite module production

Perovskite solar modules (PSMs) offer a promising pathway to low-cost photovoltaics, yet their commercialization is challenged by manufacturing scalability, device uniformity, additive costs, interlayer complexity, and module stability. This study introduces a comprehensive technoeconomic analysis of single junction PSM's and projections for tandem perovskite-Si modules that integrate all materials and manufacturing steps, module performances, projected lifetimes, and manufacturing costs across scales. Here, we highlight an open-air manufacturing approach to fabricate all active layers of serially interconnected PSMs, including electrodes and charge transport layers, enabling high-throughput production without inert or vacuum environments. The analysis reveals two orders of magnitude throughput enhancement and cost reductions of 24% in all-open-air production, escalating to over 60% at 1 GW factory capacity compared to conventional methods. Levelized cost of energy (LCOE) projections for utility-scale installations over 30 years, accounting for module replacement and recycling, demonstrate the potential to achieve the 2030 US target of $0.03 per kWh with realistic 7–11-year PSM lifetimes, outperforming incumbent silicon-based modules. Neither four terminal (4T) nor two terminal (2T) tandem-Si PSMs improve over single junction perovskite or silicon LCOE regardless of higher efficiencies at any modeled lifetime. Addressing PSM technical challenges with a cost-modeling framework guides commercialization efforts and provides a convincing pathway for challenging incumbent Si-based PV.

14 SOLAR ENERGY↗
DOE OSTI2020

Structural insight into the Staphylococcus aureus ATP-driven exporter of virulent peptide toxins

Staphylococcus aureus is a major human pathogen that has acquired alarming broad-spectrum antibiotic resistance. One group of secreted toxins with key roles during infection is the phenol-soluble modulins (PSMs). PSMs are amphipathic, membrane-destructive cytolytic peptides that are exported to the host-cell environment by a designated adenosine 5'-triphosphate (ATP)–binding cassette (ABC) transporter, the PSM transporter (PmtABCD). Here, we demonstrate that the minimal Pmt unit necessary for PSM export is PmtCD and provide its first atomic characterization by single-particle cryo-EM and x-ray crystallography. We have captured the transporter in the ATP-bound state at near atomic resolution, revealing a type II ABC exporter fold, with an additional cytosolic domain. Comparison to a lower-resolution nucleotide-free map displaying an “open” conformation and putative hydrophobic inner chamber of a size able to accommodate the binding of two PSM peptides provides mechanistic insight and sets the foundation for therapeutic design.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Physics-guided machine learning for improved accuracy of the National Solar Radiation Database

The National Solar Radiation Database (NSRDB) provides high-resolution spatiotemporal solar irradiance data for the entire globe. The NSRDB uses a two-step Physical Solar Model (PSM) to compute the effects of clouds and other atmospheric variables on the solar radiation reaching the surface of the Earth. Physical and optical cloud properties are fundamental inputs to the PSM and are derived from the National Oceanic and Atmospheric Administration's Geostationary Operational Environmental Satellites. This paper describes recent improvements to the NSRDB driven by physics-guided machine learning methods for cloud property retrieval. The impacts of these new methods on the NSRDB irradiance data are validated using an extensive set of ground measurement sites, showing significant improvement for all sites. We report on average, the mean absolute percentage error for global horizontal irradiance and direct normal irradiance show reductions of 2.16 and 3.95 percentage points respectively for all daylight conditions, 5.92 and 17.39 percentage points respectively for cloudy conditions, and 9.00 and 22.59 percentage points respectively for gap-filled cloudy conditions. These new methods will help improve the quality and accuracy of the irradiance and cloud data in the NSRDB.

14 SOLAR ENERGY↗
DOE OSTI2020

Molecular Structure of Sphingomyelin in Fluid Phase Bilayers Determined by the Joint Analysis of Small-Angle Neutron and X-ray Scattering Data

In this work, we have determined the fluid bilayer structure of palmitoyl sphingomyelin (PSM) and stearoyl sphingomyelin (SSM) by simultaneously analyzing small-angle neutron and X-ray scattering data. Using a newly developed scattering density profile (SDP) model for sphingomyelin lipids, we report structural parameters including the area per lipid, total bilayer thickness, and hydrocarbon thickness, in addition to lipid volumes determined by densitometry. Unconstrained all-atom simulations of PSM bilayers at 55 °C using the C36 CHARMM force field produced a lipid area of 56 Å 2 , a value that is 10% lower than the one determined experimentally by SDP analysis (61.9 Å2). Furthermore, scattering form factors calculated from the unconstrained simulations were in poor agreement with experimental form factors, even though segmental order parameter (S CD ) profiles calculated from the simulations were in relatively good agreement with S CD profiles obtained from NMR experiments. Conversely, constrained area simulations at 61.9 Å 2 resulted in good agreement between the simulation and experimental scattering form factors, but not with S CD profiles from NMR. We discuss possible reasons for the discrepancies between these two types of data that are frequently used as validation metrics for molecular dynamics force fields.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Using Grazing-Incidence Small-Angle Neutron Scattering to Study the Orientation of Block Copolymer Morphologies in Thin Films

Here, we used grazing-incidence small-angle neutron scattering (GISANS) to probe the depth-dependent orientation of self-assembled morphologies of block copolymers. A hydrophobic–hydrophobic block copolymer, poly(solketal methacrylate)-block-polystyrene (PSM-b-PS), was synthesized and spin-coated into films tens of nanometers in thickness where the polymers adopted a disordered state. PSM-b-PS was then hydrolyzed by exposing the polymer thin film to trifluoroacetic acid vapor or embedding a photoacid generator in the film during spin coating, followed by exposure to UV light. The hydrolysis converted the block copolymer into a hydrophilic–hydrophobic block copolymer, poly(glycerol monomethacrylate)-block-polystyrene (PGM-b-PS), significantly increasing the segmental interaction parameter (χ) and causing microphase separation of the copolymers. GISANS was used to study the depth-dependent structure of the films and revealed that the orientation of the microphase-separated structure differed at the polymer–air and polymer–substrate interfaces. In the regions where the lamellae were parallel to the interfaces, the orientation propagated into the film from the interfaces. However, in the areas where the lamellae were perpendicular to the interfaces, the orientation did not persist with increasing distance from the interfaces.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Hydrolysis-Induced Morphology Evolution of Linear and Bottlebrush Block Copolymers in Thin Films with Acid Vapor or Photoacid Generators

The self-assembly of high-χ low-N block copolymers (BCPs) can give patterns with sub-10 nm full pitch, serving as a promising alternative to photolithographic methods. Here, in this work, we synthesized poly(solketal methacrylate)-block-polystyrene copolymers, PSM-b-PS, with various volume ratios of the two blocks. After hydrolysis of the PSM block into poly(glycerol monomethacrylate), PGM, the BCPs had both lamellar and cylindrical microdomain morphologies in the bulk phase and in thin films. In addition to our previously developed solid-state hydrolysis strategy involving trifluoroacetic acid vapor, we developed a new photoinduced solid-state hydrolysis using photoacid generators, PAGs, embedded within the polymer films. After exposure to UV followed by a postexposure baking or solvent vapor annealing, the BCPs transitioned from the disordered, phase-mixed state into laterally ordered cylindrical patterns. In comparison to linear BCPs that rely on a random copolymer layer to modify interfacial interactions with the substrate to promote an orientation of the microdomains normal to the interface, we found that the microdomains in bottlebrush multiblock copolymers oriented normal to the interface absent substrate modification due to the chain architecture.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Designing metal halide perovskite solar modules for thermomechanical reliability

There is a significant deficiency in perovskite solar module (PSM) stability under thermomechanical stressors which is not well-understood. In this perspective, common issues seen with perovskite solar cell device fabrication related to thermomechanical reliability of PSM processing are discussed, with a focus on how the robustness of device layers and interlayer adhesion can be improved. Film stresses, adhesion of charge transport layers, and instability under light and heat are discussed with the purpose of providing insight on designing PSMs for durability. Processing conditions of encapsulation of PSMs and critical parameters to consider are also examined, and accelerated testing protocols for PSMs are discussed that probe mechanical degradation modes and ensure reliability of devices in the field.

14 SOLAR ENERGY↗
DOE OSTI2023

A series of cation-modified robust zirconium-based metal–organic frameworks for carbon dioxide capture

Metal–organic frameworks (MOFs) represent one of the most promising porous solids for possible use as sorbents to control and reduce the greenhouse gas emission. Studies have shown that open metal sites (OMS) interact strongly with carbon dioxide and thus, serve as efficient binding sites for CO 2 capture. However, many OMS-bearing MOFs are lack of framework stability and often have high regeneration temperature. To seek ways to solve the stability issue, we designed a series of isoreticular MOFs, Zr-tcpb-COOM (M = alkali/alkaline earth metal), by exchange of protons with metal ions on Zr-tcpb-COOH via post-synthetic modification (PSM). The pristine MOF (Zr-tcpb-COOH) has a very robust framework. The PSM process does not deteriorate the framework stability but creates metal binding sites that form strong bonds with carbon dioxide. The results show that at low CO 2 pressure, the uptake amount is enhanced considerably using Zr-tcpb-COOM and is in trend of increasing atomic number (Li + < Na + < K + < Ca 2+ ). High adsorption selectivity (CO 2 /N 2 IAST selectivity (15 : 85) = 539.5) is also achieved for CO 2 over N 2 at room temperature. This approach offers a feasible method to improve CO 2 capture capacity, especially at low concentrations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Accounting for linkages between wildfire-driven shifts in plant-microbial interactions and soil carbon dynamics in Arctic tundra

Increasing wildfire regimes in the rapidly changing Arctic tundra are altering the soil carbon budget through increased permafrost degradation, shrubs expansion, and shifts in microbial activities. Whether future arctic wildfires will result in net C losses or gains in the future will depend on complex biotic and abiotic interactions that regulate belowground C biogeochemical processes, including linkages among biotic communities. One important linkage is plant-microbe interactions. While these interactions are likely shaped or altered by wildfires, they remain little explored in the context of successional trajectories. Yet, incorporating plant-microbe interactions in frameworks for defining and understanding post-fire soil C trajectories is critical to predict belowground C responses to future tundra wildfires. Here, we provide examples of and discuss how fire-mediated changes in plant-soil-microbe (PSM) interactions can impact soil C dynamics in the Arctic tundra. We consider different impacts of wildfires on PSM interactions and their implications to soil C dynamics, as well as the nuances associated with particular wildfire regimes (severity and intensity) and successional timescales. We suggest that accounting for plant-microbial linkages in future wildfire-succession interactions frameworks can inform future experimental designs and reduce uncertainties in our ability to predict the net effect of Arctic wildfires on ecosystem C.

fungi, bacteria↗
DOE OSTI2021

Physics-Guided Machine Learning for Prediction of Cloud Properties in Satellite-Derived Solar Data

With over 20 years of high-resolution surface irradiance data covering most of the western hemisphere, the National Solar Radiation Database (NSRDB) is a vital public data asset. The NSRDB uses a two-step Physical Solar Model (PSM) that explicitly considers the effects of clouds and other atmospheric variables on radiative transfer. High-quality physical and optical cloud properties derived from satellite imagery are perhaps the most important data inputs to the PSM, representing the greatest source of radiation attenuation and scattering. However, traditional methods for cloud property retrieval have their own limitations and are unable to accurately predict cloud properties outside of nominal conditions. We introduce a physics-guided neural network that can accurately predict cloud properties when traditional methods fail or are inaccurate. Using this framework, we show reductions in relative Root Mean Square Error (RMSE) for Global Horizontal Irradiance (GHI) up to 13 percentage points for timesteps that previously had missing or low-quality cloud property data. We expect that this methodology will be effective in improving the quality of cloud property and solar irradiance data in the NSRDB.

cloud properties↗
DOE OSTI2021

Wood-to-Fuel Demonstration Project for California's Transportation Sector using Autothermal Pyrolysis (Non-Proprietary Summary Process Hazard Assessment)

Frontline has prioritized personnel safety, equipment preservation, and environmental protection throughout the design process of the autothermal pyrolysis unit. To facilitate a safe design, Frontline completed an informal hazards and operability (HAZOP) study and a formal HAZOP study, and employ management of change procedures. The result of these safety procedures is a plant that will function in a safe manner with a limited and acceptable amount of risk. Frontline took an approach it used in previous projects to execute a preliminary, internally facilitated hazards and operability (HAZOP) study. While this HAZOP study was performed without any subsequent change tracking, it enables a group of well-trained engineers to consider the safety implications of each part of the plant in a thorough and methodical manner. Frontline chose to bring in a pyrolysis consultant (Daren Daugaard of Burning Oak Energy) to participate in the review. Following the preliminary HAZOP and once the detailed design work was nearing completion, Frontline performed a formal HAZOP with a third-party facilitator, Jason Stittleburg of Novetus Engineering. Although the plant is not subject to process safety management (PSM) requirements, this formal HAZOP was performed in accordance with OSHA regulations deemed reasonable for PSM. Finally, after the formal HAZOP was conducted, Frontline maintained a safe system by implementing and following management of change procedures on each substantial change to the process. Frontline has kept a record of each subsequent change made to the formal HAZOP P&IDs. The process hazard assessment process allowed Frontline to find and correct several unacceptable configurations within the plant.

09 BIOMASS FUELS↗
DOE OSTI2021

Estimating Surface Solar Irradiance Using Meteosat-8 Satellite for India and Surrounding Regions (2017-2019)

Using the Physical Solar Model, Version 3 (PSM V3), the National Renewable Energy Laboratory—in collaboration with the University of Wisconsin, the National Oceanic and Atmospheric Administration, and Solar Consulting Services—produced modeled surface solar irradiance based on Meteosat-8 satellite cloud information. PSM V3 implements a physics-based radiative transfer approach to model surface solar irradiance using cloud properties processed from raw satellite data and ancillary data such as aerosol optical depth and precipitable water vapor from the Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2). Further, the modeled surface solar irradiance was validated using 10 high-quality ground measurement data from the Baseline Surface Radiation Network. The modeled data showed good correlation with the ground measurement, and the overall uncertainty is less than 35% for all validation locations. Because of the satellite viewing geometry, the Indian and European locations demonstrated higher uncertainties than the African locations, where the Meteosat-8 satellite has a more nadir viewing geometry. Further, instruction on how to access the data is provided.

14 SOLAR ENERGY↗
DOE OSTI2023

Simulation of a rapid compression machine for evaluation of ignition chemistry and soot formation using gasoline/ethanol blends

Due to the projected decline of demand for gasoline in light duty engines and the advent of ethanol as a green fuel, the use of gasoline/ethanol blend fuels in heavy duty applications are being investigated as they are projected to have lower cost and lower lifecycle green house gas (GHG) emissions. In heavy duty engines, the primary mode of combustion is mixing controlled combustion where wide range of mixture conditions (equivalence ratio) exist. Soot emissions of these fuels in richer conditions are not well understood. The goal of this research is to evaluate some commercially available soot modeling codes for the particulate matter emissions from gasoline/ethanol fuel blends, especially at fuel rich conditions. A Rapid Compression Machine (RCM) is modeled in a three-dimensional numerical simulation using CONVERGE computational software using a reduced chemical kinetic mechanism with SAGE chemistry solver and a RANS k-ϵturbulence model with a sector model including the creviced piston. The creviced piston is used in the experimental setup to reduce boundary layer effects and to maintain a homogeneous core in the reaction cylinder. Computational fluid dynamics simulations are conducted for different gasoline-ethanol fuel blends from E10 (10% ethanol v/v) to E100. The fuel blend is modeled as a surrogate mixture of toluene, iso-octane, n-heptane for gasoline content, and ethanol. The computational results were validated against experimental results using pressure measurements and laser extinction diagnostics. Different soot models are investigated to evaluate their capability of predicting the sooting tendencies of fuel blends, especially in richer conditions experienced during mixing-controlled combustion. The experimental combustion characteristics such as the ignition delay of different blends of fuel are reasonably well predicted. The Particulate Size Mimic (PSM) model accurately predicts the soot generation characteristics of the different fuels, but the Hiroyasu-NSC model falls short in this regard. For accurate prediction of soot with the PSM model, the thermodynamic conditions during combustion must be accurately modeled. While the current computational modeling tools can produce accurate results for the prediction of particulate matter emissions, there is much work to be done in improving our understanding of the underlying fundamental processes.

Energy & Fuels↗
DOE OSTI2021

Physics-Guided Machine Learning for Prediction of Cloud Properties in Satellite-Derived Solar Data: Preprint

With over 20 years of high-resolution surface irradiance data covering most of the western hemisphere, the National Solar Radiation Database (NSRDB) is a vital public data asset. The NSRDB uses a two-step Physical Solar Model (PSM) that explicitly considers the effects of clouds and other atmospheric variables on radiative transfer. High-quality physical and optical cloud properties derived from satellite imagery are perhaps the most important data input to the PSM, representing the greatest source of radiation attenuation and scattering. However, traditional methods for cloud property retrieval have their own limitations and are unable to accurately predict cloud properties outside of nominal conditions. We introduce a physics-guided neural network that can accurately predict cloud properties when traditional methods fail or are inaccurate. Using this framework, we show reductions in relative Root Mean Square Error (RMSE) for Global Horizontal Irradiance (GHI) up to 13 percentage points for timesteps that previously had missing or low-quality cloud property data. We expect that this methodology will be effective in improving the quality of cloud property and solar irradiance data in the NSRDB.

41 EE - Solar Energy Technologies Office (EE-4S)↗