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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 307 records · Page 17

Logic-based analysis of gene expression data predicts association between TNF, TGFB1 and EGF pathways in basal-like breast cancer

For breast cancer, clinically important subtypes are well characterized at the molecular level in terms of gene expression profiles. In addition, signaling pathways in breast cancer have been extensively studied as therapeutic targets due to their roles in tumor growth and metastasis. However, it is challenging to put signaling pathways and gene expression profiles together to characterize biological mechanisms of breast cancer subtypes since many signaling events result from post-translational modifications, rather than gene expression differences. We designed a logic-based computational framework to explain the differences in gene expression profiles among breast cancer subtypes using Pathway Logic and transcriptional network information. Pathway Logic is a rewriting-logic-based formal system for modeling biological pathways including post-translational modifications. Our method demonstrated its utility by constructing subtype-specific path from key receptors (TNFR, TGFBR1 and EGFR) to key transcription factor (TF) regulators (RELA, ATF2, SMAD3 and ELK1) and identifying potential association between pathways via TFs in basal-specific paths, which could provide a novel insight on aggressive breast cancer subtypes. Lastly, codes and results are available at http://epigenomics.snu.ac.kr/PL/.

59 BASIC BIOLOGICAL SCIENCES↗

Evaluating CO 2 mitigation strategies in SAF biorefineries: Techno-economic and life cycle analysis

The aviation sector requires scalable decarbonization strategies, and lignocellulosic sustainable aviation fuel (SAF) represents a promising pathway. This study comparatively evaluates the techno-economic analysis and life cycle assessment (LCA) of three CO 2 management strategies integrated within a U.S.-based gasification–Fischer–Tropsch SAF biorefinery: (i) catalytic hydrogenation of captured CO 2 to methanol, (ii) geological CO 2 sequestration, and (iii) mineralization to sodium bicarbonate (NaHCO 3 ). Techno-economic analysis indicates that methanol synthesis requires approximately 26% higher capital investment and 33% higher operating costs than mineralization. Although methanol co-production generates the highest gross revenue, NaHCO 3 production reduces the SAF minimum selling price by approximately 38% relative to both methanol synthesis and geological sequestration pathways, reflecting a more balanced cost allocation through mineral co-product valorization. Geological sequestration lowers operating costs by nearly 50% compared with methanol synthesis but remains highly dependent on carbon credit mechanisms. LCA reveals substantial divergence in climate performance. Relative to methanol synthesis, sequestration improves net greenhouse gas performance by approximately 163%, transitioning the system from net-positive to net-negative emissions. Mineralization further enhances carbon mitigation, achieving roughly 85% greater carbon reduction than sequestration and over sixfold improvement relative to methanol synthesis within the defined system boundary. Sensitivity analysis identified hydrogen price, co-product market value, and process emissions as dominant drivers. Under baseline assumptions, CO 2 mineralization is found to offer the most balanced pathway.

Carbon capture and storage↗

Hanford Site Composite Analysis Data Package: Exposure Scenarios and Radionuclide Specific Dose Conversion Factors.

This data package summarizes the exposure assumptions, equations, and methods used to calculate radionuclide-specific unit dose factors and the radiological doses for both groundwater and atmospheric pathways as a part of the revised Hanford Site Composite Analysis. An All-Pathways Representative Person exposure scenario is considered to evaluate exposure via both groundwater and atmospheric transport pathways. The radiological dose assessments for both groundwater and atmospheric pathways are included in the performance assessments for various Waste Management Areas at the Hanford Site. This data package calculates exposure route-specific and total unit dose factors for composite-analysis-specific radionuclides of concern based on the exposure assumptions used in the composite analysis and performance assessments. This data package presents the results and comparison of the radionuclide-specific unit dose factors based on the exposure assumptions used in the revised composite analysis and various performance assessments.

61 RADIATION PROTECTION AND DOSIMETRY↗

Time-resolved relaxation and fragmentation of polycyclic aromatic hydrocarbons investigated in the ultrafast $\mathrm{XUV}$-$\mathrm{IR}$ regime

Polycyclic aromatic hydrocarbons (PAHs) play an important role in interstellar chemistry and are subject to high energy photons that can induce excitation, ionization, and fragmentation. Previous studies have demonstrated electronic relaxation of parent PAH monocations over 10–100 femtoseconds as a result of beyond-Born-Oppenheimer coupling between the electronic and nuclear dynamics. Here, we investigate three PAH molecules: fluorene, phenanthrene, and pyrene, using ultrafast XUV and IR laser pulses. Simultaneous measurements of the ion yields, ion momenta, and electron momenta as a function of laser pulse delay allow a detailed insight into the various molecular processes. We report relaxation times for the electronically excited PAH * , PAH +* and PAH 2+* states, and show the time-dependent conversion between fragmentation pathways. Additionally, using recoil-frame covariance analysis between ion images, we demonstrate that the dissociation of the PAH 2+ ions favors reaction pathways involving two-body breakup and/or loss of neutral fragments totaling an even number of carbon atoms.

79 ASTRONOMY AND ASTROPHYSICS↗

Techno-Economic Assessment for the Production of Hydrocarbon Fuels via Catalytic Upgrading of Furans

This technical report documents the techno-economic analysis (TEA) implications of a biochemical/catalytic pathway for the production of long-chain hydrocarbon fuels in support to the multi-lab Catalytic Upgrading of Biochemical Intermediates (CUBI) project within the Chemical Catalysis for Bioenergy Consortium (ChemCatBio). Two distinct conceptual biorefineries centered around the process encompassing sugar dehydration to furans, aldol condensation between furans and a ketone (methyl ethyl ketone [MEK]), and a final step of hydrotreating to obtain hydrocarbons in the C 14 -C 16 range are considered: an integrated plant that simultaneously produces both furans (furfural and HMF) and ketone (MEK via 2,3-butanediol [BDO]) from sugars and a dedicated facility focused on producing furans from corn stover hydrolysate and procuring the ketone externally. In either plant, the main coproducts are adipic acid (derived from lignin) and sodium sulfate. The results from the assessment are quite comparable to those reported in previous design case focused on biological conversion of sugars to fermentation intermediates with subsequent catalytic upgrading of those intermediates to hydrocarbon fuels, thus presenting another viable alternative pathway to achieve similar fuel cost targets through purely catalytic upgrading of sugars. Since this study considers long-term performance targets for the full pathway dedicated to sugar upgrading to fuels, the critical remaining research points needed to achieve future cost goals are also discussed. Finally, this report presents a single-point sensitivity analysis around selected parameters to identify the major cost drivers of the biorefineries and provides a qualitative discussion on additional opportunities for cost reduction within the proposed concepts, namely through adding value to furans, to coproducts that may be obtained following BDO dehydration, and to lignin through alternative pathways.

09 BIOMASS FUELS↗

Data, Modeling, & Analysis

The project goal includes developing model pathways to improve sustainability of feedstock supply chains to reduce access costs and the environmental footprint. The project aims to harness synergies of production and collection practices and current systems to improve economic and environmental outcomes.

09 BIOMASS FUELS↗

Uncovering electronic and geometric descriptors of chemical activity for metal alloys and oxides using unsupervised machine learning

Here, we show that unsupervised machine learning (ML) using principal component analysis (PCA) provides a straightforward pathway for developing accurate and interpretable electronic-structure descriptors of the chemical and catalytic properties of materials. We demonstrate the approach by finding chemisorption descriptors for metal alloys and surface oxygens on metals and metal oxides. In both cases, the principal component (PC) descriptors yield ML models that predict the material’s chemical properties with competitive accuracy compared to ML models built using established descriptors. Importantly, interpreting the electronic-structure patterns captured by each PC descriptor via signal reconstruction suggests potential design motifs for future electronic-structure descriptor design and allows us to identify links between a material’s geometric and catalytic properties. Ultimately, we show that the unsupervised ML approach provides a route to find electronic-structure descriptors of the catalytic properties of materials that readily connect to geometric structure and composition.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Life-cycle analysis of microalgae-based polyurethane foams

Polyurethane plastics are essential in many consumer and commercial products such as insulation, furniture, automotive interiors, and clothing. Pathways for producing polyurethane from microalgae offer an opportunity to reduce greenhouse gas emissions and other environmental impacts and can incorporate processes that avoid the use of toxic isocyanates typically used in conventional polyurethane production processes. In this study, the greenhouse gas emissions, fossil energy, and water consumption of biobased polyurethane and biobased non-isocyanate polyurethane were evaluated via life-cycle analysis using the R&D Greenhouse Gases, Regulated Emissions, and Energy Use in Technologies model. Microalgae-based polyurethane foam was found to achieve greenhouse gas emission reductions of up to 79% compared with conventional polyurethane foam production. The greenhouse gas reductions for the non-isocyanate microalgae polyurethane pathway are slightly lower at 58% compared with conventional polyurethane foam. However, it offers additional benefits by reducing toxicity potential compared to the isocyanate polyurethane pathway. The analysis also included a biorefinery-level analysis to evaluate the impact of incorporating polyurethane production into fuel-processing microalgae biorefineries. The sensitivity analyses conducted in this study reveal that improved algae cultivation strategies can lead to decreases of up to 127% and 80% in GHG emissions from the baseline process of Bio-PU and Bio-NIPU, respectively. Likewise, implementation of renewable electricity can result in up to 128% and 74% lower GHG emissions compared to the baseline production of Bio-PU and Bio-NIPU, respectively. Finally, the analysis evaluated different coproduct handling methods including displacement and allocation (based on mass, energy, and market-value). The results suggest that it is important to consider both the displacement and allocation methods as these led to significant differences in the environmental impacts.

36 MATERIALS SCIENCE↗

Evaluating the contribution of plant metabolic pathways in the light to the ATP:NADPH demand using a meta-analysis of isotopically non-stationary metabolic flux analyses

Abstract Balancing the ATP: NADPH demand from plant metabolism with supply from photosynthesis is essential for preventing photodamage and operating efficiently, so understanding its drivers is important for integrating metabolism with the light reactions of photosynthesis and for bioengineering efforts that may radically change this demand. It is often assumed that the C3 cycle and photorespiration consume the largest amount of ATP and reductant in illuminated leaves and as a result mostly determine the ATP: NADPH demand. However, the quantitative extent to which other energy consuming metabolic processes contribute in large ways to overall ATP: NADPH demand remains unknown. Here, we used the metabolic flux networks of numerous recently published isotopically non-stationary metabolic flux analyses (INST-MFA) to evaluate flux through the C3 cycle, photorespiration, the oxidative pentose phosphate pathway, the tricarboxylic acid cycle, and starch/sucrose synthesis and characterize broad trends in the demand of energy across different pathways and compartments as well as in the overall ATP:NADPH demand. These data sets include a variety of species including Arabidopsis thaliana , Nicotiana tabacum , and Camelina sativa as well as varying environmental factors including high/low light, day length, and photorespiratory levels. Examining these datasets in aggregate reveals that ultimately the bulk of the energy flux occurred in the C3 cycle and photorespiration, however, the energy demand from these pathways did not determine the ATP: NADPH demand alone. Instead, a notable contribution was revealed from starch and sucrose synthesis which might counterbalance photorespiratory demand and result in fewer adjustments in mechanisms which balance the ATP deficit.

59 BASIC BIOLOGICAL SCIENCES↗

Hanford Site Composite Analysis Data Package: Exposure Scenarios and Radionuclide Specific Dose Conversion Factors

This data package summarizes the exposure assumptions, equations, and methods used to calculate radionuclide-specific unit dose factors and the radiological doses for both groundwater and atmospheric pathways as a part of the updated Hanford Site Composite Analysis (CA). An All Pathways Representative Person exposure scenario is considered to evaluate exposure via both groundwater and atmospheric transport pathways. The radiological dose assessments for both groundwater and atmospheric pathways are included in the performance assessments (PAs) for various Waste Management Areas at the Hanford Site. This data package calculates exposure route-specific and total unit dose factors for CA-specific radionuclides of concern based on the exposure assumptions used in the CA and PAs. This data package also presents the results and comparison of the radionuclide-specific unit dose factors based on the exposure assumptions used in the revised Hanford Site Composite Analysis and Hanford Site performance assessments for low-level waste disposal facilities.

61 RADIATION PROTECTION AND DOSIMETRY↗

Tailoring Ion Transport in Li 3‐3y Ho 1+y Cl 6‐x Br x via Transition‐Metal Free Structural Planes and Charge Carrier Distribution

Abstract Localized atomistic disorder in halide‐based solid electrolytes (SEs) can be leveraged to boost Li + mobility. In this study, Li + transport in structurally modified Li 3 HoCl 6 , via Br − introduction and Li + deficiency, is explored. The optimized Li 3‐3 y Ho 1+ y Cl 6‐ x Br x achieves an ionic conductivity of 3.8 mS cm −1 at 25 °C, the highest reported for holmium halide materials. 6,7 Li nuclear magnetic resonance and relaxometry investigations unveil enhanced ion dynamics with bromination, attaining a Li + motional rate neighboring 116 MHz. X‐ray diffraction analyses reveal mixed‐anion‐induced phase transitions with disproportionate octahedral expansions and distortions, creating Ho‐free planes with favorable energetics for Li + migration. Bond valence site energy analysis highlights preferred Li + transport pathways, particularly in structural planes devoid of Ho 3+ blocking effects. Molecular dynamics simulations corroborate enhanced Li + diffusion with Br − introduction into Li 3 HoCl 6 . Li‐Ho electrostatic repulsions in the (001) plane presumably drive Li + diffusion into the Ho‐free (002) layer, enabling rapid intraplanar Li + motion and exchange between the 2d and 4h sites. Li 3‐3 y Ho 1+ y Cl 6‐ x Br x also demonstrates good battery cycling stability. These findings offer valuable insights into the intricate correlations between structure and ion transport and will help guide the design of high‐performance fast ion conductors for all‐solid‐state batteries.

Chemistry↗

Fuel‐Driven π‐Conjugated Superstructures to Form Transient Conductive Hydrogels

Despite advances in creating dissipative materials with transient properties, such as hydrogels and active droplets, their application remains confined to temporal changes in structural properties. Developing out-of-equilibrium materials whose electronic functions are parameterized by a chemical reaction cycle is challenging. Yet, this class of materials is required to construct biomimetic materials. In contrast to traditional chemical reaction cycles that exploit molecularly dissolved building blocks at thermodynamic equilibrium, we show that fiber structures derived from reactive naphthalene diimide (NDI) building blocks can be used as resting states to form far-from-equilibrium conductive hydrogels after the addition of chemical fuels. Upon fueling the NDI-derived fibers, a dual-component activation and deactivation pathway is deduced by kinetic analysis and is absent when using a molecularly dissolved resting state. Investigating the solid-state morphologies of the structures formed throughout the fuel-driven reaction cycle using cryo-EM reveals that the resting thermodynamic fibers evolve to transient thicker fibrils and layered superstructures. We show that the transient redox-active hydrogels exhibit a nearly threefold increase in electrical conductivity upon fuel consumption before reverting to their original value over hours. In conclusion, these far-from-equilibrium materials are potential candidates in applications such as programmable biorobotics and chemical computing.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Photon management in silicon photovoltaic cells: A critical review

With the practical efficiency of the silicon photovoltaic (PV) cell approaching its theoretical limit, pushing conversion efficiencies even higher now relies on reducing every type of power loss that can occur within the device. Limiting optical losses is therefore critical and requires effective management of incident photons in terms of how they interact with the device. Ultimately, photon management within a PV cell means engineering the device and constituent materials to maximize photon absorption within the active semiconductor and therefore reduce the number of photons lost through other means, most notably reflection and parasitic absorption. There have been great advancements in the front and the rear side photon management techniques in recent years. This review aims to discuss these advancements and compare the various approaches, not only in terms of increases in photogenerated current, but also their compatibility with different PV cell architectures and potential trade-offs, like increased surface recombination or scalability for high-volume manufacturing. In this review, a comprehensive discussion of a wide variety of the front and the rear side photon management structures are presented with suggestions to improve the already achieved performance further. Here, this review is unique because it not only presents the recent development in photon management techniques, but also offers through analysis of these techniques and pathways to improve further.

14 SOLAR ENERGY↗

Orientation-Dependent Distortion of Lamellae in a Block Copolymer Electrolyte under DC Polarization

Lithium-salt-doped block copolymers have the potential to serve as solid electrolytes in rechargeable batteries with lithium metal anodes. In this work, we use small-angle X-ray scattering (SAXS) to study the structure of polystyrene-block-poly(ethylene oxide) (PS-b-PEO) doped with bis-(trifluoromethylsulfonyl)amine lithium salt (LiTFSI) during direct current (dc) polarization experiments in lithiu-lithium symmetric cells. The block copolymer studied is nearly symmetric in composition, has a total molecular weight of 39 kg mol -1 , and exhibits a lamellar morphology at all studied salt concentrations. When ionic current is passed through the electrolyte, a salt concentration gradient forms that induces a spatial gradient in the domain spacing, d. The dependence of d on distance from the positive electrode, x, was determined experimentally by scanning the incident X-ray beam from one lithium electrode to the other. By studying the two-dimensional (2D) SAXS patterns as a function of azimuthal scattering angle, we find that lamellae with PS/PEO interfaces oriented perpendicular to the flow of ionic current (LAM ⟂ ) swell and contract to a greater degree than those with interfaces oriented parallel to the current direction (LAM || ). While domains with the LAM ⟂ do not provide direct conducting pathways between the electrodes, our analysis suggests that they play an important role in establishing the salt concentration gradient necessary for sustaining a large ionic current through greater expansion and contraction.

25 ENERGY STORAGE↗

An exploration of machine learning models for the determination of reaction coordinates associated with conformational transitions

Determining collective variables (CVs) for conformational transitions is crucial to understanding their dynamics and targeting them in enhanced sampling simulations. Often, CVs are proposed based on intuition or prior knowledge of a system. However, the problem of systematically determining a proper reaction coordinate (RC) for a specific process in terms of a set of putative CVs can be achieved using committor analysis (CA). Identifying essential degrees of freedom that govern such transitions using CA remains elusive because of the high dimensionality of the conformational space. Various schemes exist to leverage the power of machine learning (ML) to extract an RC from CA. Here, we extend these studies and compare the ability of 17 different ML schemes to identify accurate RCs associated with conformational transitions. We tested these methods on an alanine dipeptide in vacuum and on a sarcosine dipeptoid in an implicit solvent. Our comparison revealed that the light gradient boosting machine method outperforms other methods. In order to extract key features from the models, we employed Shapley Additive exPlanations analysis and compared its interpretation with the “feature importance” approach. For the alanine dipeptide, our methodology identifies ϕ and θ dihedrals as essential degrees of freedom in the C7ax to C7eq transition. For the sarcosine dipeptoid system, the dihedrals ψ and ω are the most important for the cisαD to transαD transition. We further argue that analysis of the full dynamical pathway, and not just endpoint states, is essential for identifying key degrees of freedom governing transitions.

Chemistry↗

Bacterium-enabled transient gene activation by artificial transcription factors for resolving gene regulation in maize

Abstract Understanding gene regulatory networks is essential to elucidate developmental processes and environmental responses. Here, we studied regulation of a maize (Zea mays) transcription factor gene using designer transcription activator-like effectors (dTALes), which are synthetic Type III TALes of the bacterial genus Xanthomonas and serve as inducers of disease susceptibility gene transcription in host cells. The maize pathogen Xanthomonas vasicola pv. vasculorum was used to introduce 2 independent dTALes into maize cells to induced expression of the gene glossy3 (gl3), which encodes a MYB transcription factor involved in biosynthesis of cuticular wax. RNA-seq analysis of leaf samples identified, in addition to gl3, 146 genes altered in expression by the 2 dTALes. Nine of the 10 genes known to be involved in cuticular wax biosynthesis were upregulated by at least 1 of the 2 dTALes. A gene previously unknown to be associated with gl3, Zm00001d017418, which encodes aldehyde dehydrogenase, was also expressed in a dTALe-dependent manner. A chemically induced mutant and a CRISPR-Cas9 mutant of Zm00001d017418 both exhibited glossy leaf phenotypes, indicating that Zm00001d017418 is involved in biosynthesis of cuticular waxes. Bacterial protein delivery of dTALes proved to be a straightforward and practical approach for the analysis and discovery of pathway-specific genes in maize.

59 BASIC BIOLOGICAL SCIENCES↗

Decarbonizing the US Energy System

Recent rapid and unexpected cost reductions in decarbonization technologies have accelerated the cost-effective decarbonization of the US economy, with greenhouse gas (GHG) emissions falling by 20% from 2005 to 2020. The literature on US economy-wide decarbonization focuses on maximizing long-term GHG emissions reduction strategies that rely mostly on renewable energy expansion, electrification, and efficiency improvements to achieve net-zero GHG emissions by 2050. While these studies provide a valuable foundation, further research is needed to properly support decarbonization policy development and implementation. In this review, we identify key decarbonization analysis gaps and opportunities, including issues related to cross-sectoral linkages, spatial and temporal granularity, consumer behavior, emerging technologies, equity and environmental justice, and political economy. We conclude by discussing the implications of these analysis gaps for US decarbonization pathways and how they relate to challenges facing major global emitters.

08 HYDROGEN↗

Predictive Contaminant Transport Simulation with the P2R Model for the Composite Analysis Base Case

In order to meet the requirements of U.S. Department of Energy (DOE) in DOE O 435.1 Chg. 1, Radioactive Waste Management, a composite analysis (CA) must be completed for the Central Plateau at the Hanford Site. The updated Hanford Site CA requires estimates of fate and transport of radionuclides in the groundwater from multiple sources within and downgradient of the Central Plateau. Numerical simulations using the MT3D-MST computer code were conducted to evaluate the fate and transport of existing distributions of 16 radionuclides as identified in CP-62184, Hanford Site Composite Analysis: Radionuclide Selection for Groundwater Pathway Evaluation: tritium (H-3), carbon-14 (C-14), chloride- 36 (Cl-36), strontium-90 (Sr-90), technetium-99 (Tc-99), rhenium-187 (Re-187), radium-226 (Ra-226), thorium-230 (Th-230), uranium-232 (U-232), uranium-232 (U-232), uranium-233 (U-233), uranium-234 (U-234), uranium-235 (U-235), uranium-236 (U-236), neptunium-237 (Np-237), and uranium-238 (U- 238). This document details the application of the P2R Model version 8.3 to predict the fate and transport of contaminants in groundwater on the Central Plateau for the 10,052 year simulation to support the CA. The simulation of fate and transport of contaminants reported in this environmental calculation file (ECF) will support dose predictions as part of the updated Hanford Site CA.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗