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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Identification of 2-Hydroxyacyl-CoA Synthases with High Acyloin Condensation Activity for Orthogonal One-Carbon Bioconversion

One-carbon (C1) compounds are emerging as cost-effective and potentially carbon-negative feedstocks for biomanufacturing, which require efficient, versatile metabolic platforms for the synthesis of value-added products. Synthetic formyl-CoA elongation (FORCE) pathways allow diverse product synthesis from C1 compounds via iterative C1 elongation, operating independently from the host metabolism with reduced engineering complexity and improved theoretical yields. However, a major bottleneck was identified as the suboptimal kinetics of the core C1–C1 condensation enzyme, 2-hydroxyacyl-CoA synthase (HACS), catalyzing the acyloin condensation reaction between formaldehyde and formyl-CoA. Furthermore, we used a combinatorial approach of bioprospecting and rational protein engineering to identify multiple HACS variants with significantly improved activities toward C1 substrates. Sequence and structure alignment of the active variants elucidated the key regions for the catalytic function, which were targeted for mutagenesis, leading to improved catalytic efficiency. In parallel, a consecutive round of bioprospecting for homologs with high similarity with active variants revealed a highly active HACS variant exhibiting up to 7-fold improvement in catalytic efficiency (k cat /K M ) and 14-fold improvement in the FORCE pathway flux in vivo compared to the previous reports. Upon further optimization of the downstream pathway, the orthogonal C1-to-product bioconversion system showed a metabolic flux of up to 700 μM glycolate OD –1 h –1 (2.1 mmol gDCW –1 h –1 ) and an industrially relevant glycolate titer, rate, and yield of 5.2 g L –1 (67.8 mM), 0.22 g L –1 h –1 , and 94% carbon yield, respectively.

2-hydroxyacyl-CoA synthase↗
DOE OSTI2016

Quinone 1 e – and 2 e – /2 H + Reduction Potentials: Identification and Analysis of Deviations from Systematic Scaling Relationships

Quinones participate in diverse electron transfer and proton-coupled electron transfer processes in chemistry and biology. To understand the relationship between these redox processes, an experimental study was carried out to probe the 1 e – and 2 e – /2 H + reduction potentials of a number of common quinones. The results reveal a non-linear correlation between the 1 e – and 2 e – /2 H + reduction potentials. This unexpected observation prompted a computational study of 134 different quinones, probing their 1 e – reduction potentials, p K a values, and 2 e – /2 H + reduction potentials. We report the density functional theory calculations reveal an approximately linear correlation between these three properties and an effective Hammett constant associated with the quinone substituent(s). However, deviations from this linear scaling relationship are evident for quinones that feature intramolecular hydrogen bonding, halogen substituents, charged substituents, and/or sterically bulky substituents. These results, particularly the different substituent effects on the 1 e – versus 2 e – /2 H + reduction potentials, have important implications for designing quinones with tailored redox properties.

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

Performance enhancement and degradation mechanism identification of a single-atom Co–N–C catalyst for proton exchange membrane fuel cells

Development of platinum group metal (PGM)-free catalysts for oxygen reduction reaction (ORR) has been a strategic research topic for proton exchange membrane (PEM) fuel cells. Present state-of-art PGM-free ORR catalysts are Fe, N co-doped carbon (Fe-N-C) catalysts, which unfortunately exhibit instability concerns. Herein, we report a stable atomically dispersed Co, N co-doped carbon (Co-N-C) catalyst with high Co content of 1.0 at% and the active site, i.e., the coordination of Co, is CoN2+2 in nature. The Co-N-C catalyst demonstrated high ORR activity comparable to, and high stability over 3 times better than, that of the Fe-N-C catalyst. It also achieved a high activity of 22 mA cm2 at 0.9 ViR-free and a power density of 0.61 W cm-2 under 1.0 bar H2/O2. Further, we identify two main degradation mechanisms of the PGM-free catalysts: catalyst oxidation by H2O2/radicals and demetalation. The improved stability of Co-N-C relative to Fe-N-C is attributed to less Fenton-reactive nature of Co and significantly enhanced resistance to demetalation of Co-N-C.

Xie, Xiaohong↗
DOE OSTI2015

Atomic-scale identification of Pd leaching in nanoparticle catalyzed C–C coupling: Effects of particle surface disorder

C–C coupling reactions are of great importance in the synthesis of numerous organic compounds, where Pd nanoparticle catalyzed systems represent new materials to efficiently drive these reactions. Despite their pervasive utility, the catalytic mechanism of these particle-based reactions remains highly contested. Herein we present evidence of an atom leaching mechanism for Stille coupling under aqueous conditions using peptide-capped Pd nanoparticles. EXAFS analysis revealed Pd coordination changes in the nanoparticle consistent with Pd atom abstraction, where sizing analysis by SAXS confirmed particle size changes associated with a leaching process. It is likely that recently discovered highly disordered surface Pd atoms are the favored catalytic active sites and are leached during oxidative addition, resulting in smaller particles. Thus, probing the mechanism of nanoparticle-driven C–C coupling reactions through structural analyses provides fundamental information concerning these active sites and their reactivity at the atomic-scale, which can be used to improve catalytic performance to meet important sustainability goals.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2015

Identification of an organic semiconductor superlattice structure of pentacene and perfluoro-pentacene through resonant and non-resonant X-ray scattering

Highly crystalline and stable molecular superlattices are grown with the smallest possible stacking period using monolayers (MLs) of the organic semiconductors pentacene (PEN) and perfluoro-pentacene (PFP). Superlattice reflections in X-ray reflectivity and their energy dependence in resonant soft X-ray reflectivity measurements show that PFP and PEN MLs indeed alternate even though the coherent ordering is lost after ~ 4 ML. The observed lattice spacing of 15.9 Å in the superlattice is larger than in pure PEN and PFP films, presumably because of more upright standing molecules and lack of interdigitation between the incommensurate crystalline PEN and PFP layers. The findings are important for the development of novel organic quantum optoelectronic devices.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Breakup of a liquid rivulet falling over an inclined plate: Identification of a critical Weber number

Here, we have numerically investigated the breakup of a rivulet falling over a smooth inclined plate using the volume of fluid method. The breakup the rivulet is a complex phenomenon that is dictated by many factors, such as solvent properties, contact angle, inertia, plate inclination, etc. An extensive simulation campaign was conducted wherein these factors were systematically investigated. Regimes for a stable rivulet and an unstable rivulet that leads to the breakup and formation of a droplet are examined in terms of a critical value of the Weber number (We cr ) that delineates these regimes. The effect of plate inclination on the breakup of the rivulet shows that the critical Weber number decreases with increased inclination angle (θ) owing to higher liquid velocity. However, the effect is negligible beyond θ > 60°. The impact of solvent properties is characterized using the Kapitza number (Ka). Variation of We cr with Ka shows two trends depending on the Ka value of the solvent. Solvents with lower Ka values, corresponding to high viscosities and/or low surface tensions, show smaller values of the critical Weber number and the variation is linear. While solvents with higher Ka values exhibit higher values of the We cr and the variation in We cr is steep. This behavior is more pronounced with increasing contact angle. Higher contact angles promote rivulet breakup so that inertia must be higher to the breakup. As a result, a phenomenological scaling for a critical Weber number with the Kapitza number and contact angle is presented that can offer insight into rivulet breakup.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

DeepMerge – II. Building robust deep learning algorithms for merging galaxy identification across domains

In astronomy, neural networks are often trained on simulation data with the prospect of being used on telescope observations. Unfortunately, training a model on simulation data and then applying it to instrument data leads to a substantial and potentially even detrimental decrease in model accuracy on the new target dataset. Simulated and instrument data represent different data domains, and for an algorithm to work in both, domain-invariant learning is necessary. Here we employ domain adaptation techniques— Maximum Mean Discrepancy (MMD) as an additional transfer loss and Domain Adversarial Neural Networks (DANNs)— and demonstrate their viability to extract domain-invariant features within the astronomical context of classifying merging and non-merging galaxies. Additionally, we explore the use of Fisher loss and entropy minimization to enforce better in-domain class discriminability. We show that the addition of each domain adaptation technique improves the performance of a classifier when compared to conventional deep learning algorithms. We demonstrate this on two examples: between two Illustris-1 simulated datasets of distant merging galaxies, and between Illustris-1 simulated data of nearby merging galaxies and observed data from the Sloan Digital Sky Survey. The use of domain adaptation techniques in our experiments leads to an increase of target domain classification accuracy of up to ~20%. With further development, these techniques will allow astronomers to successfully implement neural network models trained on simulation data to efficiently detect and study astrophysical objects in current and future large-scale astronomical surveys.

galaxies: interactions↗