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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 217 records · Page 12

Regulatory interventions improve the biosynthesis of limiting amino acids from methanol carbon to improve synthetic methylotrophy in Escherichia coli

Synthetic methylotrophy aims to engineer methane and methanol utilization pathways in platform hosts like Escherichia coli for industrial bioprocessing of natural gas and biogas. While recent attempts to engineer synthetic methylotrophs have proved successful, autonomous methylotrophy, that is, the ability to utilize methane or methanol as sole carbon and energy substrates, has not yet been realized. Here, we address an important limitation of autonomous methylotrophy in E. coli: the inability of the organism to synthesize several amino acids when grown on methanol. We targeted global and local amino acid regulatory networks. Those include removal of amino acid allosteric feedback inhibition (argA H15Y , ilvA L447F , hisG E271K , leuA G462D , proB D107N , thrA S345F, trpE S40F ), knockouts of transcriptional repressors (ihfA, metJ); and overexpression of amino acid biosynthetic operons (hisGDCBHAFI, leuABCD, thrABC, trpEDCBA) and transcriptional regulators (crp, purR). Compared to the parent methylotrophic E. coli strain that was unable to synthesize these amino acids from methanol carbon, these strategies resulted in improved biosynthesis of limiting proteinogenic amino acids (histidine, leucine, lysine, methionine, phenylalanine, threonine, tyrosine) from methanol carbon. In several cases, improved amino acid biosynthesis from methanol carbon led to improvements in methylotrophic growth in methanol minimal medium supplemented with a small amount of yeast extract. Here, this study addresses a key limitation currently preventing autonomous methylotrophy in E. coli and possibly other synthetic methylotrophs and provides insight as to how this limitation can be alleviated via global and local regulatory modifications.

60 APPLIED LIFE SCIENCES↗

Genome‐wide CRISPR‐Cas9 screen reveals a persistent null‐hyphal phenotype that maintains high carotenoid production in Yarrowia lipolytica

Abstract Yarrowia lipolytica is a metabolic engineering host of growing industrial interest due to its ability to metabolize hydrocarbons, fatty acids, glycerol, and other renewable carbon sources. This dimorphic yeast undergoes a stress‐induced transition to a multicellular hyphal state, which can negatively impact biosynthetic activity, reduce oxygen and nutrient mass transfer in cell cultures, and increase culture viscosity. Identifying mutations that prevent the formation of hyphae would help alleviate the bioprocess challenges that they create. To this end, we conducted a genome‐wide CRISPR screen to identify genetic knockouts that prevent the transition to hyphal morphology. The screen identified five mutants with a null‐hyphal phenotype— ΔRAS2 , ΔRHO5 , ΔSFL1 , ΔSNF2 , and ΔPAXIP1 . Of these hits, only ΔRAS2 suppressed hyphal formation in an engineered lycopene production strain over a multiday culture. The RAS2 knockout was also the only genetic disruption characterized that did not affect lycopene production, producing more than 5 mg L −1 OD −1 from a heterologous pathway with enhanced carbon flux through the mevalonate pathway. These data suggest that a ΔRAS2 mutant of Y. lipolytica could prove useful in engineering a metabolic engineering host of the production of carotenoids and other biochemicals.

59 BASIC BIOLOGICAL SCIENCES↗

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↗

Effects of processing on the efficacy and metabolites of Cistanche tubulosa using ultra‐performance liquid chromatography coupled with quadrupole time‐of‐flight mass spectrometry

Abstract Cistanche tubulosa (CT), a well‐known traditional Chinese medicine, has always been processed with rice wine for the treatment of kidney‐yang deficiency syndrome (KYDS) since time immemorial. To explore the effect of processing on the efficacy and metabolites of CT in vivo , a comprehensive method using ultra‐performance liquid chromatography coupled with quadrupole time‐of‐flight mass spectrometry was established for the analysis of the altered endogenous metabolites in response to the intervention of the raw and processed CT in KYDS model and the metabolites of the absorbed compounds in rats after gastric perfusion. It was shown that CT could improve KYDS, and the effect of the processed product was more significant. A total of 47 differential metabolites were identified in urine. Pathway analysis proved that purine metabolism; alanine, aspartate, and glutamate metabolism; and citrate cycle were the main pathways. Furthermore, 53 prototypes and 48 metabolites have been detected in rats. This was the first systematic research focus on the metabolites of raw and processed CT in vivo , which could provide a scientific basis for explaining the increasing efficiency of the processed CT. Moreover, it provides a valuable strategy for analyzing the chemical components and metabolites of other TCM prescriptions.

Lei, Huibo↗

A Hybrid Structural Method for Investigating Low Molecular Weight Oligomeric Structures of Amyloid Beta

Spurred in part by the failure of recent therapeutics targeting amyloid β plaques in Alzheimer's Disease (AD), attention is increasingly turning to the oligomeric forms of this peptide that form early in the aggregation process. However, while numerous amyloid β fibril structures have been characterized, primarily by NMR spectroscopy and cryo-EM, obtaining structural information on the low molecular weight forms of amyloid β that presumably precede and/or seed fibril formation has proved challenging. Furthermore, these transient forms are heterogeneous, and depend heavily on experimental conditions such as buffer, temperature, concentration, and degree of quiescence during measurement. Here, we present the concept for a new approach to delineating structural features of early-stage low molecular weight amyloid β oligomers, using a solvent accessibility assay in conjunction with simultaneous fluorescence measurements.

60 APPLIED LIFE SCIENCES↗

Light‐Driven Metabolic Pathways in Non‐Photosynthetic Biohybrid Bacteria

Biomanufacturing via microorganisms relies on carbon substrates for molecular feedstocks and a source of energy to carry out enzymatic reactions. This creates metabolic bottlenecks and lowers the efficiency for substrate conversion. Nanoparticle biohybridization with proteins and whole cell surfaces can bypass the need for redox cofactor regeneration for improved secondary metabolite production in a non-specific manner. Here we propose using nanobiohybrid organisms (Nanorgs), intracellular protein-nanoparticle hybrids formed through the spontaneous coupling of core-shell quantum dots (QDs) with histidine-tagged enzymes in non-photosynthetic bacteria, for light-mediated control of bacterial metabolism. Furthermore, this proved to eliminate metabolic constrictions and replace glucose with light as the source of energy in Escherichia coli, with an increase in growth by 1.7-fold in 75 % reduced nutrient media. Metabolomic tracking through carbon isotope labeling confirmed flux shunting through targeted pathways, with accumulation of metabolites downstream of respective targets. Finally, application of Nanorgs with the Ehrlich pathway improved isobutanol titers/yield by 3.9-fold in 75 % less sugar from E. coli strains with no genetic alterations. These results demonstrate the promise of Nanorgs for metabolic engineering and low-cost biomanufacturing.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Generalized Brønsted‐Evans‐Polanyi Relationships for Reactions on Metal Surfaces from Machine Learning

Abstract Brønsted‐Evans‐Polanyi (BEP) relationships, i. e., a linear scaling between reaction and activation energies, lie at the core of computational design of heterogeneous catalysts. However, BEPs are not general and often require reparameterization for each class of reactions. Here we construct generalized BEPs (gBEPs), which can predict activation energies for a diverse dataset of reactions of C, O, N and H containing molecules on metal surfaces. In a first step we develop a set of descriptors based on scaling relationships that can capture the change in chemical identity of reactants during the reaction. Subsequently, we use the reaction energy, these descriptors and a single descriptor for the surface structure to parameterize machine learning based regression approaches for the prediction of activation energies. The best approach we developed shows a Mean Absolute Error (MAE) of 0.11 eV for the training set (80 % of the data set) and 0.23 eV for the test set (20 % of the data set). The methodology presented here allows to calculate activation energies within fractions of seconds on a typical personal computer and due to its generality, accuracy and simplicity in application it might prove to be useful in transition metal catalyst design.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Electrocatalytic Oxidative Coupling of Methane on NiFe Exsolved Perovskite Anode: Effect of Water

Oxidative coupling of methane (OCM) can be performed electrocatalytically by utilizing solid oxide cells, which provide a readily controlled oxygen supply through dense electrolytes. La 0.7 Sr 0.2 Ni 0.2 Fe 0.8 O 3 (LSNF) perovskite is an effective anode for OCM. Its surface characteristics and electrocatalytic activity can be improved by reduction and the resultant exsolution of bimetallic NiFe nanoparticles from its bulk. X-ray diffraction (XRD) and environmental transmission electron microscopy proved that the evolution of hetero-phases under reducing environment resulted in bimetallic NiFe nanoparticles being formed on the surface. Further, a 36 % improvement in C 2+ hydrocarbon production rate was achieved due to the reduction of LSNF with the exsolved NiFe nanoparticles. Co-feeding of H 2 O enhanced selective conversion of CH 4 resulting in the production rate of C 2+ hydrocarbons being increased by 56 %. Analysis of impedance spectra and in-situ DRIFTS under a CH 4 +H 2 O atmosphere provided an understanding for the enhancement on the electrocatalytic OCM.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Data‐Driven Analysis of Amine‐Based Sorbents for CO 2 Removal from the Atmosphere

Available data on amine-based sorbents used for the direct air capture (DAC) process were gathered and analyzed to identify the correlations between various aspects of these sorbents and the operating conditions they are used in. It is demonstrated that a moderately high temperature (∼ 50 °C) can help with higher CO 2 capture capacity. Furthermore, the effect of sorbent preparation method on its activity and stability was studied. Also, the influence of amine groups and support choice on amine efficiency and CO 2 capture capacity was discussed. The DAC process conditions proved to play a major role in determining the optimal sorbent. An outlook for characteristics to be sought for in future DAC sorbents for CO 2 removal is proposed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Photoredox Organic Synthesis Employing Heterogeneous Photocatalysts with Emphasis on Halide Perovskite

Abstract Lately, heterogeneous semiconductor materials have been explored as an emerging type of efficient photocatalyst for photoredox organic synthesis. Among these semiconductors, lead halide perovskite materials demonstrate unique properties towards excellent charge separation and charge transfer, extremely long charge carrier migration, high efficiency in visible light absorption, and long excited states lifetimes, etc., as proved in ground‐breaking solar cell applications, garnering necessary merits for an efficient catalytic system for photoredox organic reactions. Here, the latest progress in heterogeneous semiconductor materials towards this endeavor is examined, with particular emphasis on lead halide perovskite nanocrystals (NCs) in photocatalytic organic synthesis.

Lin, Yixiong↗

Iodide Double Perovskites and the Limits of their Structural Stability

AbstractWhile halide double perovskites A2M(I)M(III)X6 have attracted significant attention, examples involving iodides are rare. We examine the limits of the structural stability of iodide double perovskites, presenting the synthesis and single‐crystal structures of Cs2NaScI6 and Cs2NaYI6. Bypassing the common expectation that iodides have small band gaps, these compounds display optical gaps of 3.10 eV [M(III) = Sc] and 3.65 eV [M(III) = Y]. Cs2NaScI6 is the only iodide double perovskite to exhibit a cubic crystal structure at room temperature. Density functional theory‐based electronic structure calculations help understand the role of competing Cs3M(III)2I9 (3 : 2 : 9) phases and provide possible reasons for why iodide double perovskites based around In(III), Sb(III) and Bi(III) cations have proved elusive. We confirm design rules for halide double perovskites based around concepts of the tolerance factor and the radius ratio of the smaller, trivalent ion, but also point to situations such as what is observed for Cs2NaScI6 where a double perovskite can be trapped in a metastable structure.

Mulligan, Anya S.↗

Shock Formation and Vorticity Creation for 3d Euler

Abstract We analyze the shock formation process for the 3D nonisentropic Euler equations with the ideal gas law, in which sound waves interact with entropy waves to produce vorticity. Building on our theory for isentropic flows in [3, 4], we give a constructive proof of shock formation from smooth initial data. Specifically, we prove that there exist smooth solutions to the nonisentropic Euler equations which form a generic stable shock with explicitly computable blowup time, location, and direction. This is achieved by establishing the asymptotic stability of a generic shock profile in modulated self‐similar variables, controlling the interaction of wave families via: (i) pointwise bounds along Lagrangian trajectories, (ii) geometric vorticity structure, and (iii) high‐order energy estimates in Sobolev spaces. © 2022 Wiley Periodicals LLC.

Mathematics↗

Formation of Point Shocks for 3D Compressible Euler

We consider the 3D isentropic compressible Euler equations with the ideal gas law. We provide a constructive proof of the formation of the first point shock from smooth initial datum of finite energy, with no vacuum regions, with nontrivial vorticity present at the shock, and under no symmetry assumptions . We prove that for an open set of Sobolev‐class initial data that are a small L ∞ perturbation of a constant state, there exist smooth solutions to the Euler equations which form a generic stable shock in finite time. The blowup time and location can be explicitly computed, and solutions at the blowup time are smooth except for a single point , where they are of cusp‐type with Hölder C 1/3 regularity. Our proof is based on the use of modulated self‐similar variables that are used to enforce a number of constraints on the blowup profile, necessary to establish global existence and asymptotic stability in self‐similar variables. © 2022 Wiley Periodicals LLC.

Mathematics↗

Quantum optimization algorithms: Energetic implications

Since the dawn of quantum computing (QC), theoretical developments like Shor's algorithm proved the conceptual superiority of QC over traditional computing. However, such quantum supremacy claims are difficult to achieve in practice because of the technical challenges of realizing noiseless qubits. In the near future, QC applications will need to rely on noisy quantum devices that offload part of their work to classical devices. One way to achieve this is by using parameterized quantum circuits in optimization or even in machine learning tasks. The energy requirements of quantum algorithms have not yet been studied extensively. Here in this article, we explore several optimization algorithms using both theoretical insights and numerical experiments to understand their impact on energy consumption. Specifically, we highlight why and how algorithms like quantum natural gradient descent, simultaneous perturbation stochastic approximations or circuit learning methods, are at least 2x to 4x more energy efficient than their classical counterparts; why feedback-based quantum optimization is energy-inefficient; and how techniques like Rosalin can improve the energy efficiency of other algorithms by a factor of ≥2 0 x. Finally, we use the NchooseK high-level programming model to run optimization problems on both gate-based quantum computers and quantum annealers. Empirical data indicate that these optimization problems run faster, have better success rates, and consume less energy on quantum annealers than on their gate-based counterparts.

97 MATHEMATICS AND COMPUTING↗

Accelerating the Structure Exploration of Diverse Bi–Pt Nanoclusters via Physics‐Informed Machine Learning Potential and Particle Swarm Optimization

Bimetallic Bi–Pt nanoclusters exhibit diverse structural motifs, including core-shell, Janus, and mixed alloy configurations, due to the unique bonding characteristics between Bi and Pt atoms. Using density functional theory refinements from ChIMES physically machine-learned potential and CALYPSO particle swarm optimization global searches, 34 Bi20-Pt20 nanoclusters are systematically classified. The results reveal that Bi atoms predominantly occupy surface sites, driven by charge transfer effects. Cohesive energy trends alone prove insufficient for structure differentiation, necessitating a data-driven approach employing principal component analysis and K-means clustering. Furthermore, vibrational, electronic, and infrared spectral analyses provide additional insights into structure-property relationships. The findings offer an original framework for the automated classification and analysis of bimetallic nanoclusters, enhancing the understanding of their stability and functional properties.

bimetallic nanoparticles↗

Quantitative Low-Field 19 F Nuclear Magnetic Resonance Analysis of Carbonyl Groups in Pyrolysis Oils

Pyrolysis bio-oils, one of the products of lignocellulosic biomass pyrolysis, have the potential to be widely used as fuels. The chemical composition of bio-oils is very complicated as they contain hundreds, if not thousands, of different, mostly oxygen-containing, compounds with a wide distribution of physical properties, chemical structures, and concentrations. Detailed knowledge of bio-oil composition is crucial for optimizing both the pyrolysis processes and for any subsequent upgrading into a more viable fuel resource. Here we report the successful use of low-field, or benchtop, nuclear magnetic resonance (NMR) spectrometers in the analysis of pyrolysis oils. Pyrolysis oils from four different feedstocks were derivatized and analyzed using 19 F NMR techniques. The NMR results compare favorably with titrations for total carbonyl content. In addition, the benchtop NMR spectrometer proves able to reveal key spectral features, thus allowing the quantification of different carbonyl groups, such as aldehydes, ketones and quinones. Benchtop NMR spectrometers are typically compact, cheaper than their superconducting counterparts and do not require cryogens. Their use will make NMR analysis of pyrolysis oils easier and more accessible to a wide range of different potential users.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Allylation and Thermosetting of Acetosolv Wheat Straw Lignin

Abstract The acetosolv extraction, allylation and subsequent cross‐linking of wheat straw lignin to thermoset biomaterials is herein described. The extraction temperature proved to be of great importance for the quality of the resulting lignin, with moderate temperature being key for preservation of β‐O‐4’ linkages. The allylation of the acetosolv lignin was carried out using three different synthetic strategies, resulting in selective installation of either benzylic or phenolic allyl ethers, or unselective allylation of various hydroxyl groups via etherification and carboxyallylation. The different allylation protocols employed either allyl alcohol, allyl chloride, or diallylcarbonate as allyl precursors, with the latter resulting in the highest degree of functionalization. Selected allylated acetosolv lignins were cross‐linked using a thiol‐ene approach and the lignin with the highest density of allyl groups was found to form a cross‐linked thermoset material with properties comparable to kraft lignin‐based analogues.

Chemistry↗

Climate warming threatens the persistence of a community of disturbance-adapted native annual plants

With ongoing climate change, populations are expected to exhibit shifts in demographic performance that will alter where a species can persist. This presents unique challenges for managing plant populations and may require ongoing interventions, including in situ management or introduction into new locations. However, few studies have examined how climate change may affect plant demographic performance for a suite of species, or how effective management actions could be in mitigating climate change effects. Over the course of two experiments spanning 6 yr and four sites across a latitudinal gradient in the Pacific Northwest, United States, here we manipulated temperature, precipitation, and disturbance intensity, and quantified effects on the demography of eight native annual prairie species. Each year we planted seeds and monitored germination, survival, and reproduction. We found that disturbance strongly influenced demographic performance and that seven of the eight species had increasingly poor performance with warmer conditions. Across species and sites, we observed 11% recruitment (the proportion of seeds planted that survived to reproduction) following high disturbance, but just 3.9% and 2.3% under intermediate and low disturbance, respectively. Moreover, mean seed production following high disturbance was often more than tenfold greater than under intermediate and low disturbance. Importantly, most species exhibited precipitous declines in their population growth rates (λ) under warmer-than-ambient experimental conditions and may require more frequent disturbance intervention to sustain populations. Aristida oligantha, a C4 grass, was the only species to have λ increase with warmer conditions. These results suggest that rising temperatures may cause many native annual plant species to decline, highlighting the urgency for adaptive management practices that facilitate their restoration or introduction to newly suitable locations. Frequent and intense disturbances are critical to reduce competitors and promote native annuals’ persistence, but even such efforts may prove futile under future climate regimes.

54 ENVIRONMENTAL SCIENCES↗