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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 973 records · Page 54
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Xylose Assimilation for the Efficient Production of Biofuels and Chemicals by Engineered Saccharomyces cerevisiae

Microbial conversion of plant biomass into fuels and chemicals offers a practical solution to global concerns over limited natural resources, environmental pollution, and climate change. Pursuant to these goals, researchers have put tremendous efforts and resources towards engineering the yeast Saccharomyces cerevisiae to efficiently convert xylose, the second most abundant sugar in lignocellulosic biomass, into various fuels and chemicals. Here, we summarize recent advances in metabolic engineering of yeast to address bottlenecks on xylose assimilation, and to enable simultaneous co-utilization of xylose and other carbon sources in lignocellulosic hydrolysates. We also highlight distinct characteristics of xylose metabolism that can be harnessed to produce advanced biofuels and chemicals. Although many challenges remain, recent research investments have facilitated efficient fermentation of xylose and simultaneous co-consumption of xylose and glucose. In particular, understanding of xylose-induced metabolic rewiring in engineered yeast has encouraged use of xylose as a carbon source for producing various non-ethanol bioproducts. Furthermore, to boost the lignocellulosic biomass-based bioeconomy, much attention is expected to promote xylose-utilizing efficiency via reprogramming cellular regulatory networks, to attain robust co-fermentation of xylose and other cellulosic carbon sources under industrial conditions, and to exploit the advantageous traits of yeast xylose metabolism for producing diverse fuels and chemicals.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Metabolic Engineering of Nonmodel Yeast Issatchenkia orientalis SD108 for 5–Aminolevulinic Acid Production

Biological production of 5-aminolevulinic acid (5-ALA) has received growing attention over the years. However, there is the tradeoff between 5-ALA biosynthesis and cell growth because the fermentation broth will become acidic due to the production of 5-ALA. To address this limitation, we engineered an acid-tolerant yeast, Issatchenkia orientalis SD108, for 5-ALA production. We first discovered that the cell growth rate of I. orientalis SD108 was boosted by 5-ALA and its endogenous ALA synthetase (ALAS) showed higher activity than those homologs from other yeasts. The titer of 5-ALA was improved from 28 mg/L to 120-, 150-, and 300 mg/L, by optimizing plasmid design, overexpressing a transporter, and increasing gene copy number, respectively. After redirecting the metabolic flux using the pyruvate decarboxylase (PDC) knockout strain (SD108ΔPDC) and culturing with urea, we increased the titer of 5-ALA to 510 mg/L, a 13-fold enhancement, proving the importance of the newly identified IoALAS with higher activity and the strategic selection of nitrogen sources for knockout strains. This study demonstrates the acid-tolerant I. orientalis SD108ΔPDC has a high potential for 5-ALA production at a large scale in the future.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Highly Stable and Conductive 1,3‐Dioxolane/Hydrocarbon Based Electrolyte Solvent for Advanced Lithium‐Sulfur Batteries

Abstract Developing effective electrolytes is crucial for boosting the performance of Lithium‐Sulfur (LiS) rechargeable battery. Recent improvements in electrolyte formulations have enhanced cyclability by increasing electrochemical stability at the electrode interfaces. However, achieving both high ionic conductivity (σ) and stability at these interfaces simultaneously remains a significant challenge. In this study, we utilized a strategy to suppress polysulfide dissolution by employing a mixture of 1,3‐dioxolane (DOL) and hydrocarbon solvents with lithium bis(trifluoromethanesulfonyl)imide (LiTFSI) electrolyte salt. Compared to the conventional electrolyte solution, which is 1 M LiTFSI salt in a 50/50 vol % mixture of DOL and dimethoxy ethane (DME), the LiTFSI electrolyte with DOL/hydrocarbon solvents demonstrate better cycling stability, compatibility with the Li‐metal anode, and a high specific discharge capacity (Csp). Among the various DOL/hydrocarbon and LiTFSI electrolyte salts, the combination of DOL and n‐hexane, a linear hydrocarbon, with LiTFSI electrolyte salt, (DnH40LiTFSI) exhibits remarkable σ (6.5×10 −3 S/cm at 30 °C), compatibility with the Li‐metal anode, an initial Csp of ca. 1264 mAh/g, cycling stability (Csp and Coulombic efficiency are 811 mAh/g and 98.09 % after 120 cycles) at 0.1 C by forming a good protective layer on the Li‐metal surface and preventing polysulfide dissolution.

Ahmed, Faiz↗
DOE OSTI2022

Concurrent Enhancement of Acetylene Uptake Capacity and Selectivity by Progressive Core Expansion and Extra–Framework Anions in Pore–Space–Partitioned Metal–Organic Frameworks

A multi-stage core-expansion method is proposed here as one component of the integrative binding-site/extender/core-expansion (BEC) strategy. The conceptual deconstruction of the partitioning ligand into three editable parts draws our focus onto progressive core expansion and allows the optimization of both acetylene uptake and selectivity. Herein the effectiveness of this strategy is shown through a family of eight cationic pore-partitioned materials containing three different partitioning ligands and various counter anions. The optimized structure, Co 3 -cpt-tph-Cl (Hcpt=4-(p-carboxyphenyl)-1,2,4-triazole, H-tph=(2,5,8-tri-(4-pyridyl)-1,3,4,6,7,9-hexaazaphenalene) with the largest surface area and highest C 2 H 2 uptake capacity (200 cm 3 /g at 298 K), also exhibits (desirably) the lowest CO 2 uptake and hence the highest C 2 H 2 /CO 2 selectivity. The successful boost in both C 2 H 2 capacity and IAST selectivity allows Co 3 -cpt-tph-Cl to rank among the best crystalline porous materials, ionic MOFs in particular, for C 2 H 2 uptake and C 2 H 2 /CO 2 experimental breakthrough separation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Indirectly Detected DNP-Enhanced 17 O NMR Spectroscopy: Observation of Non-Protonated Near-Surface Oxygen at Naturally Abundant Silica and Silica-Alumina

Recent studies have shown that dynamic nuclear polarization (DNP) can be used to detect 17 O solid-state NMR spectra of naturally abundant samples within a reasonable experimental time. Observations using indirect DNP, which relies on 1 H mediation in transferring electron hyperpolarization to 17 O, are currently limited mostly to hydroxyls. Direct DNP schemes can hyperpolarize non-protonated oxygen near the radicals; however, they generally offer much lower signal enhancements. In this study, we demonstrate the detection of signals from non-protonated 17 O in materials containing silicon. The sensitivity boost that made the experiment possible originates from three sources: indirect DNP excitation of 29 Si via protons, indirect detection of 17 O through 29 Si nuclei using two-dimensional 29 Si{ 17 O} D-HMQC, and Carr-Purcell-Meiboom-Gill refocusing of 29 Si magnetization during acquisition. This 29 Si-detected scheme enabled, for the first time, 2D 17 O– 29 Si heteronuclear correlation spectroscopy in mesoporous silica and silica-alumina surfaces at natural abundance. In contrast to the silanols showing motion-averaged 17 O signals, the framework oxygens exhibit unperturbed powder patterns as unambiguous fingerprints of surface sites. Furthermore, along with hydroxyl oxygens, detection of these moieties will help in gaining more atomistic-scale insights into surface chemistry.

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

Singlet Fission in Thin Solid Films of Bis(thienyl)diketopyrrolopyrroles

The singlet fission (SF) process discovered in bis(thienyl)diketopyrrolopyrroles (TDPPs) can boost their potential for photovoltaics (PV). The crystal structures of TDPP analogs carrying n-hexyl, n-butyl, or 2-(adamant-1-yl)ethyl substituents are similar, but contain increasingly slipped stacked neighbor molecules. The observed SF rate constants, k SF , (7±4), (9±3) and (5.6±1.9) ns –1 for thin films of the three compounds, respectively, are roughly equal, but the triplet quantum yields vary strongly: (120±40), (160±40) and (70±16), respectively. The recent molecular pair model reproduces the near equality of all three k SF at the crystal geometries and identifies all possible pair arrangements in which SF is predicted to be faster, by up to two orders of magnitude. Furthermore, it is also clear that the presently non-existent ability to predict the rates of processes competing with SF is pivotal for providing a guide for efforts to optimize the materials for PV.

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

Predictive analytics of selections of russet potatoes

We explore the application of machine learning algorithms specifically to enhance the selection process of Russet potato (Solanum tuberosum L.) clones in breeding trials by predicting their suitability for advancement. This study addresses the challenge of efficiently identifying high-yield, disease-resistant, and climate-resilient potato varieties that meet processing industry standards. Leveraging manually collected data from trials in the state of Oregon, we investigate the potential of a wide variety of state-of-the-art binary classification models. The dataset includes 1086 clones, with data on 38 attributes recorded for each clone, focusing on yield, size, appearance, and frying characteristics, with several control varieties planted consistently across four Oregon regions from 2013 to 2021. We conduct a comprehensive analysis of the dataset that includes preprocessing, feature engineering, and imputation to address missing values. We focus on several key metrics such as accuracy, F1-score, and Matthews correlation coefficient (MCC) for model evaluation. The top-performing models, namely a feedforward neural network classifier (Neural Net), a histogram-based gradient boosting classifier (HGBC), and a support vector machine classifier (SVM), demonstrate consistent and significant results. To further validate our findings, we conducted a simulation study using the aims, data-generating mechanisms, estimands, methods, and performance measures (ADEMP) framework, simulating different data-generating scenarios to assess model robustness and performance through true positive, true negative, false positive, and false negative distributions, area under the receiver operating characteristic curve (AUC-ROC) and MCC. The simulation results highlight that non-linear models like SVM and HGBC consistently show higher AUC-ROC and MCC than logistic regression, thus outperforming the traditional linear model across various distributions, and emphasizing the importance of model selection and tuning in agricultural trials. Variable selection further enhances model performance and identifies influential features in predicting trial outcomes. The findings emphasize the potential of machine learning in streamlining the selection process for potato varieties, offering benefits such as increased efficiency, substantial cost savings, and judicious resource utilization. Our study contributes insights into precision agriculture and showcases the relevance of advanced technologies for informed decision-making in breeding programs.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Sustainble dropwise condensation enabled ultraefficient heat pipes

Heat pipes play a critical role in determining the operations, safety, and energy efficiency of electronics. The main focus to improve the heat pipe performance is on the evaporator design or wicking structures. However, the intrinsic limitation comes from the condenser, which is fundamentally constrained by inefficient filmwise condensation (FWC). In this study, we successfully achieved a peak effective thermal conductivity (k eff ) of ~140 kW/(m·K) on widely used groove heat pipes by implementing sustainable dropwise condensation (DWC) and integrating with enhanced evaporator. To better understand the working mechanisms of the ultraefficient heat pipe, both the evaporator and condenser of the heat pipes have been modified accordingly. Our results show that up to 296% enhancements on the k eff can be achieved under various inclination angles by only inducing DWC in the condenser section. The drawback of temperature fluctuations induced by DWC in smooth heat pipes appears to be effectively solved using the grooves-wicking structure. Furthermore, by integrating the nanostructured evaporator, the k eff of the heat pipe can be boosted up to 517% compared to conventional groove heat pipes. This study, for the first time, demonstrates the huge potential of engineering both the condenser and evaporator simultaneously in developing ultraefficient heat pipes.

42 ENGINEERING↗
DOE OSTI2024

Ventenata dubia projected to expand in the western United States despite future novel conditions

Abstract Distributions of both native and invasive species are expected to shift under future climate. Species distribution models (SDMs) are often used to explore future habitats, but sources of uncertainty including novel climate conditions may reduce the reliability of future projections. We explore the potential spread of the invasive annual grass ventenata ( Ventenata dubia ) in the western United States under both current and future climate scenarios using boosted regression tree models and 30 global climate models (GCMs). We quantify novel climate conditions, prediction variability arising from both the SDMs and GCMs, and the agreement among GCMs. Results demonstrate that currently suitable habitat is concentrated inside the invaded range of the northwest, but substantial habitat exists outside the invaded range in the Southern Rockies and southwestern US mountains. Future suitability projections vary greatly among GCMs, but GCMs commonly projected decreased suitability in the invaded range and increased suitability along higher elevations of interior mountainous areas. Climate novelty did not appear to undermine the prediction reliability in many cases where the climate–species relationship was fully represented by the occurrence data. GCM‐derived variability resulting from variation in future cool season precipitation and temperature seasonality was greatest in the Rocky Mountains. SDM‐derived variability was higher in currently suitable habitat, and few GCMs projections agreed that these areas would contain future suitable habitat. However, while prediction variability was high, many GCM projections agreed that parts of the Rocky, Wasatch, and Uinta Mountains would contain highly suitable habitat in the future. As disturbances in the interior mountains occur in coming decades, reducing some natural barriers to invasion, land managers, and conservationists will need to monitor for ventenata in post‐disturbance environments. Changes to invasion potential may not play out for several decades, but results related to current potential may have applications for early detection and rapid response planning.

Environmental Sciences & Ecology↗
DOE OSTI2024

Tailoring Binder Molecular Weight to Enhance Slurry-Cast NMC Cathodes for Sulfide Solid-State Batteries

We demonstrate for the first time the critical influence of binder molecular weight on the performance of slurry-cast lithium nickel manganese cobalt oxide (NMC) cathodes in sulfide-based all-solid-state batteries (SSBs). SSBs are increasingly recognized as a safer and potentially more efficient alternative to traditional Li-ion batteries, owing to the superior ionic conductivities and inherent safety features of sulfide solid electrolytes. However, the integration of high-voltage NMC cathodes with sheet-type sulfide solid electrolytes presents significant fabrication challenges. Our findings reveal that higher molecular weight binders not only enhance the discharge capacity and cycle life of these cathodes but also ensure robust adhesion and structural integrity. By optimizing binder molecular weights, we effectively shield the active materials from degradation and mechanical stress, significantly boosting the functionality and longevity of SSBs. These results underscore the paramount importance of binder properties in advancing the practical application of high-performance all-solid-state batteries.

25 ENERGY STORAGE↗
DOE OSTI2021

Reusable Catalysts for Hydroformylation‐Based Reactions

Abstract Catalytic hydroformylation is an important reaction, widely studied by academics and applied in the chemical industry, and it is a paradigmatic example of a chemical reaction that is aligned with most of the Green Chemistry principles. In the last years, the global requirement for more sustainable chemical processes has boosted the development of more active, selective, and reusable hydroformylation catalysts. In this review, we highlight the most recent advances regarding the creation and expansion of reusable catalysts for hydroformylation and sequential processes that use hydroformylation as central reaction. The most relevant strategies for immobilization of hydroformylation catalysts are discussed, along with a critical analysis of their application in synthesis, based on catalytic activity, selectivity, and reusability.

Rodrigues, Fábio M. S.↗
DOE OSTI2021

Structure-Property Relationships and Idiosyncrasies of Bulk, 2D Hybrid Lead Bromide Perovskites

Bulk, 2D hybrid lead bromide perovskites comprise a robust family of halide perovskites with a rich structural and photophysical chemistry witnessed thus far. In an attempt to boost focus on systematically charting the phase space of 2D lead bromide perovskites, it is timely and critical to review the structure-property relationships that are emerging in this family of materials. In this review, we assess the multitude of (100)-orientated lead bromide perovskites, as well as the idiosyncratic (110)-orientated members. We examine the underpopulated phase space of bulk, thick-layer (n>1) lead bromide perovskites, highlighting several examples of structures violating Goldschmidt's tolerance factor with large organic spacers in the cuboctahedral perovskite cages. The narrow and broadband emission is discussed, along with the developed optoelectronic profile of bulk, lead bromide perovskites, as yet. Lastly, we summarize the integration of 2D lead bromide perovskites in optoelectronic devices.

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

Machine learning for accuracy in density functional approximations

Machine learning techniques have found their way into computational chemistry as indispensable tools to accelerate atomistic simulations and materials design. In addition, machine learning approaches hold the potential to boost the predictive power of computationally efficient electronic structure methods, such as density functional theory, to chemical accuracy and to correct for fundamental errors in density functional approaches. In this paper, recent progress in applying machine learning to improve the accuracy of density functional and related approximations is reviewed. Promises and challenges in devising machine learning models transferable between different chemistries and materials classes are discussed with the help of examples applying promising models to systems far outside their training sets.

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

Surface Functionalization of Carbon Black for PEM Fuel Cell Electrodes

Abstract Carbon‐based materials are extensively used in fuel cell applications due to their crucial role in maintaining high performance. Particularly, carbon black (CB) stands out as a preferred electrode material for fuel cells, owing to its high electrical conductivity and large surface area. This review focuses on the functionalization of CB and its use as a support for Pt‐based catalysts in proton exchange membrane fuel cells. Functionalization strategies include oxidation, covalent functionalization, as well as polymer grafting or impregnation. Various approaches to functionalize the CB surface are discussed that effectively tailor the surface properties of electrodes, leading to improved fuel cell performance. The improvements are seen in enhanced dispersibility of catalyst particles, better ionomer distribution, increased catalyst stability, and reduced carbon corrosion. This review provides an overview of various modifications applied to CB to enhance their structural and electrochemical properties, thereby boosting fuel cell performance.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2022

Efficacy of a Short-Term Captive Broodstock Program Compared with Hatchery-Origin Spring Chinook Salmon Derived from the Same Population

Abstract We examined the efficacy of a one-generation (five brood years: 1997–2001) captive broodstock program for spring Chinook Salmon Oncorhynchus tshawytscha by comparing survival rates of captive broodstock progeny (CBP; F2) with that of hatchery-origin fish (HOR) from a conservation hatchery supplementation program in which both groups were derived from the Tucannon River (Washington State) population for the 2000–2006 brood years. Survival rates compared were egg to fry, fry to smolt, egg to smolt, total (ages 3–5) and adult (ages 4+) smolt-to-adult-return (SAR) survival, and total (ages 3–5) and adult (ages 4+) progeny-to-parent (P:P) ratio. Total escapement and adult P:P ratios were also examined to determine if observed demographic benefits to the population continued after the captive broodstock program ended. The CBP group had lower within-hatchery survival than the HOR group, with significant differences in survival at the egg-to-fry and egg-to-smolt stages due to poor egg viability. Mean untransformed total and adult SARs for the CBP were half those of the HOR group; however, SARs did not differ significantly. The CBP also had significantly lower total and adult P:P ratios than the HOR group and were below replacement for six of the seven brood years. While the captive broodstock provided additional fish for release that would not have been available otherwise, overall the CBP performed poorly and below expectations compared with the HOR group, both within the hatchery and after release. The captive broodstock program provided a short-term demographic boost, most notable in the 2008–2010 return years, but the benefit did not carry over after the program ended.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Enhanced detection of paramagnetic fluorine-19 magnetic resonance imaging agents using zero echo time sequence and compressed sensing

Fluorine-19 ( 19 F) magnetic resonance imaging (MRI) is an emerging technique offering specific detection of labeled cells in vivo. Lengthy acquisition times and modest signal-to-noise ratio (SNR) makes three-dimensional spin-density–weighted 19 F imaging challenging. Recent advances in tracer paramagnetic metallo-perfluorocarbon (MPFC) nanoemulsion probes have shown multifold SNR improvements due to an accelerated 19 F T 1 relaxation rate and a commensurate gain in imaging speed and averages. However, 19 F T 2 -reduction and increased linewidth limit the amount of metal additive in MPFC probes, thus constraining the ultimate SNR. To overcome these barriers, we describe a compressed sampling (CS) scheme, implemented using a “zero” echo time (ZTE) sequence, with data reconstructed via a sparsity-promoting algorithm. Our CS-ZTE scheme acquires k-space data using an undersampled spherical radial pattern and signal averaging. Image reconstruction employs off-the-shelf sparse solvers to solve a joint total variation and -norm regularized least square problem. To evaluate CS-ZTE, we performed simulations and acquired 19 F MRI data at 11.7 T in phantoms and mice receiving MPFC-labeled dendritic cells. For MPFC-labeled cells in vivo, we show SNR gains of ~6.3 × with 8-fold undersampling. We show that this enhancement is due to three mechanisms including undersampling and commensurate increase in signal averaging in a fixed scan time, denoising attributes from the CS algorithm, and paramagnetic reduction of T 1 . Importantly, 19 F image intensity analyses yield accurate estimates of absolute quantification of 19 F spins. Overall, the CS-ZTE method using MPFC probes achieves ultrafast imaging, a substantial boost in detection sensitivity, accurate 19 F spin quantification, and minimal image artifacts.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

A comprehensive review on valorization of chestnut processing wastes into bio‐based composites and bioplastics

Abstract This review examines the characterization and utilization of chestnut processing wastes (35%) in the production of bioplastics and biocomposites. In this review, a Web of Science search without any publishing year restriction on the biochemical compositions of all the components of Castanea sativa . The obtaining of bioplastics and biocomposites based on C. sativa was reviewed. First, it highlights the biochemical composition and antioxidant properties of chestnut fruit, shell, burrs, leaves, flowers, and wood focusing on the most important compounds, such as phenolic acids, flavonoids, carbohydrates, Klason lignin, cellulose, and glucan, which can enhance the properties of these materials. Then the review covers using several chestnut extracts and fillers in bioplastics production through solvent casting technique. The mechanical, structural, bioactive properties, and moisture content were optimized through the composition and production. The color, UV absorption, antioxidant, and antimicrobial activity were also discussed. Biocomposites reinforced with chestnut burs, shells, or wood flour increased the intended properties. The enhancements in tensile strength, elastic modulus, and the effects of a pre‐treatment were evaluated. Additionally, it discusses material recovery, recycling, and reuse, particularly how it affects the biodegradability of composites incorporating chestnut waste residues. Highlights Chestnut fruit, shells, and burrs are rich in starch, lignin, and cellulose. The waste of chestnut processing can be used in bioplastics and biocomposites. Chestnut‐based films and biocomposites exhibit promising mechanical properties. The antimicrobial activity, making films, and composites proper for food packaging. New techniques boost performance, offering alternatives to conventional plastics.

Silva, Simão B. [REQUIMTE/LAQV, ISEP, Polytechnic ↗
DOE OSTI2022

AlInP-passivated III–V solar cells grown by dynamic hydride vapor-phase epitaxy

We report the development of AlInP-passivated solar cells grown by dynamic hydride vapor-phase epitaxy (D-HVPE) with AM1.5G efficiencies of 26.0% for single-junction (1J) GaAs cells and 28.0% for GaInP/GaAs (2J) tandems. We compare the device performance of solar cells passivated with AlInP versus control cells passivated with GaInP, which has already enabled near-unity carrier collection in GaAs solar cells. 1J devices passivated with either AlInP or GaInP have an identical open-circuit voltage (V OC ) of 1.06 V and long-wavelength current collection near 95%, indicating that both window materials provide a similar degree of passivation. Adding AlInP passivation to each solar cell structure improves the current collection by 1.3 and 1 mA/cm 2 for the 1J and 2J, respectively. The AlInP also results in a top cell V OC boost of ~40 mV relative to a tandem device passivated only by a thin, highly doped GaInP emitter. Secondary-ion mass spectrometry measurements indicate that although O and Si both incorporate in the AlInP window, they do not appear in the subsequently grown absorber layers and do not impact its ability to passivate the front surface. We expect that these achievements, along with continued optimization, will enable parity of hydride vapor-phase epitaxy (HVPE)-grown device efficiencies with state-of-the-art devices grown by other epitaxial methods in the near future.

14 SOLAR ENERGY↗