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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Catalytic CO Oxidation on MgAl 2 O 4 -Supported Iridium Single Atoms: Ligand Configuration and Site Geometry

Probing and understanding the local chemical environment of an active site is essential for designing high-performance single-atom catalysts (SACs). Density functional theory (DFT) calculations were performed to investigate the ligand configuration and site geometry of MgAl 2 O 4 -supported iridium single atoms (Ir-1) toward catalytic carbon monoxide (CO) oxidation. We employed MgAl 2 O 4 (111) and MgAl 2 O 4 (211) as the model substrates with adsorbed Ir single atoms of different site geometries. DFT calculations revealed that the Mg-site on MgAl 2 O 4 (111) and the step site on MgAl 2 O 4 (211) are the most stable adsorption sites for Ir single atoms. Irrespective of site choices, CO oxidation on supported Ir single atoms follows the Eley-Rideal (E-R) mechanism, in which the surface oxygen vacancies close to the Ir single atoms activate molecular O 2 with a negligible barrier and the rate-limiting step is the gas-phase CO directly attacking the O-Ir species that is modulated by a CO ligand. Furthermore, first-principles X-ray absorption near-edge spectra of reaction intermediates along with in situ/operando X-ray absorption spectroscopy (XAS) suggest that Ir single atoms adsorb primarily on the step sites of MgAl 2 O 4 . However, microkinetic modeling predicts that a higher activity can be attained on the equally stable Mg-site, maximizing the population of which in catalyst synthesis might prove fruitful in future studies. Electronic structure analysis indicates that the CO ligand increases the reactivity of adsorbed oxygen atoms bound to Ir single atoms by increasing the antibonding nature of the O-Ir bond.

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

The Role of Co-ZSM-5 Catalysts in Aerobic Oxidation of Ethylbenzene

Various forms of cobalt catalysts have been studied extensively for selective aerobic oxidation of hydrocarbons. However, it remains unclear whether cobalt can directly activate molecular oxygen under mild reaction conditions. Here we investigated the catalytic roles of cobalt in ethylbenzene oxidation with and without a hydroperoxide initiator. The contribution of different cobalt species was studied by varying the metal loading on Co-impregnated ZSM-5 samples. Quantitative EPR was used to determine the impact of cobalt catalysts on the free radical concentrations. Furthermore, this work provided strong evidence that cobalt, in several different forms, catalyzes hydrocarbon oxidation by facilitating peroxy bond cleavage, instead of direct oxygen activation.

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

PDB ‐101: Educational resources supporting molecular explorations through biology and medicine

Abstract The Protein Data Bank (PDB) archive is a rich source of information in the form of atomic‐level three‐dimensional (3D) structures of biomolecules experimentally determined using macromolecular crystallography, nuclear magnetic resonance (NMR) spectroscopy, and electron microscopy (3DEM). Originally established in 1971 as a resource for protein crystallographers to freely exchange data, today PDB data drive research and education across scientific disciplines. In 2011, the online portal PDB‐101 was launched to support teachers, students, and the general public in PDB archive exploration ( pdb101.rcsb.org ). Maintained by the Research Collaboratory for Structural Bioinformatics PDB, PDB‐101 aims to help train the next generation of PDB users and to promote the overall importance of structural biology and protein science to nonexperts. Regularly published features include the highly popular Molecule of the Month series, 3D model activities, molecular animation videos, and educational curricula. Materials are organized into various categories (Health and Disease, Molecules of Life, Biotech and Nanotech, and Structures and Structure Determination) and searchable by keyword. A biennial health focus frames new resource creation and provides topics for annual video challenges for high school students. Web analytics document that PDB‐101 materials relating to fundamental topics (e.g., hemoglobin, catalase) are highly accessed year‐on‐year. In addition, PDB‐101 materials created in response to topical health matters (e.g., Zika, measles, coronavirus) are well received. PDB‐101 shows how learning about the diverse shapes and functions of PDB structures promotes understanding of all aspects of biology, from the central dogma of biology to health and disease to biological energy.

Zardecki, Christine↗
NASA NTRS1986

Intramolecular interactions in aminoacyl nucleotides: Implications regarding the origin of genetic coding and protein synthesis

Cellular organisms store information as sequences of nucleotides in double stranded DNA. This information is useless unless it can be converted into the active molecular species, protein. This is done in contemporary creatures first by transcription of one strand to give a complementary strand of mRNA. The sequence of nucleotides is then translated into a specific sequence of amino acids in a protein. Translation is made possible by a genetic coding system in which a sequence of three nucleotides codes for a specific amino acid. The origin and evolution of any chemical system can be understood through elucidation of the properties of the chemical entities which make up the system. There is an underlying logic to the coding system revealed by a correlation of the hydrophobicities of amino acids and their anticodonic nucleotides (i.e., the complement of the codon). Its importance lies in the fact that every amino acid going into protein synthesis must first be activated. This is universally accomplished with ATP. Past studies have concentrated on the chemistry of the adenylates, but more recently we have found, through the use of NMR, that we can observe intramolecular interactions even at low concentrations, between amino acid side chains and nucleotide base rings in these adenylates. The use of this type of compound thus affords a novel way of elucidating the manner in which amino acids and nucleotides interact with each other. In aqueous solution, when a hydrophobic amino acid is attached to the most hydrophobic nucleotide, AMP, a hydrophobic interaction takes place between the amino acid side chain and the adenine ring. The studies to be reported concern these hydrophobic interactions.

Lacey, J. C., Jr.↗
DOE OSTI2024

Investigations of atomic and molecular processes of NBI-heated discharges in the MAST Upgrade Super-X divertor with implications for reactors

This experimental study presents an in-depth investigation of the performance of the MAST-U Super-X divertor during NBI-heated operation (up to 2.5 MW) focussing on volumetric ion sources and sinks as well as power losses during detachment. The particle balance and power loss analysis revealed the crucial role of Molecular Activated Recombination and Dissociation (MAR and MAD) ion sinks in divertor particle and power balance, which remain pronounced in the change from ohmic to higher power (NBI heated) L-mode conditions. The importance of MAR and MAD remains with double the absorbed NBI heating. MAD results in significant power dissipation (up to ${\sim} 20\%$ of $P_\textrm{SOL}$), mostly in the cold ($T_e \lt 5$ eV) detached region. Theoretical and experimental evidence is found for the potential contribution of $D^-$ to MAR and MAD, which warrants further study. These results suggest that MAR and MAD can be relevant in higher power conditions than the ohmic conditions studied previously. Post-processing reactor-scale simulations suggests that MAR and MAD can play a significant role in divertor physics and synthetic diagnostic signals of reactor-scale devices, which are currently underestimated in exhaust simulations. This raises implications for the accuracy of reactor-scale divertor simulations of particularly tightly baffled (alternative) divertor configurations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Insights into substrate coordination and glycosyl transfer of poplar cellulose synthase-8

Cellulose is an abundant cell wall component of land plants. It is synthesized from UDP-activated glucose molecules by cellulose synthase, a membrane-integrated processive glycosyltransferase. Cellulose synthase couples the elongation of the cellulose polymer with its translocation across the plasma membrane. Here, we present substrate- and product-bound cryogenic electron microscopy structures of the homotrimeric cellulose synthase isoform-8 (CesA8) from hybrid aspen (poplar). UDP-glucose binds to a conserved catalytic pocket adjacent to the entrance to a transmembrane channel. The substrate’s glucosyl unit is coordinated by conserved residues of the glycosyltransferase domain and amphipathic interface helices. Site-directed mutagenesis of a conserved gating loop capping the active site reveals its critical function for catalytic activity. Molecular dynamics simulations reveal prolonged interactions of the gating loop with the substrate molecule, particularly across its central conserved region. These transient interactions likely facilitate the proper positioning of the substrate molecule for glycosyl transfer and cellulose translocation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Water-Soluble Copper(I) Hydroxide Catalyst and Its Formation in Ligand-Free Suzuki–Miyaura Cross-Coupling Reactions

Copper has emerged as an alternative metal for metal-catalyzed cross-coupling reactions due to its low cost, readily availability, and low toxicity. Here this article reports a water-soluble active molecular catalyst and its formation in the ligand-free Suzuki–Miyaura (SM) cross-coupling reactions with copper iodide as the precatalyst in aqueous solutions. The SM coupling is homogeneous in nature, and the molecular catalyst is Cu(OH) in its singlet electronic state as identified by experimental and computational UV–vis absorption spectroscopy. The Cu(OH) catalyst is generated through the leaching of oval-shaped Cu 2 O nanoparticles, which are characterized with X-ray Auger electron spectroscopy, X-ray absorption spectroscopy, and transmission electron microscopy. The soluble Cu(OH) species is stable for at least 4 weeks under ambient conditions.

cross-coupling↗
DOE OSTI2025

Using supervised machine-learning approaches to understand abiotic stress tolerance and design resilient crops

Abiotic stresses such as drought, heat, cold, salinity and flooding significantly impact plant growth, development and productivity. As the planet has warmed, these abiotic stresses have increased in frequency and intensity, affecting the global food supply and making it imperative to develop stress-resilient crops. In the past 20 years, the development of omics technologies has contributed to the growth of datasets for plants grown under a wide range of abiotic environments. Integration of these rapidly growing data using machine-learning (ML) approaches can complement existing breeding efforts by providing insights into the mechanisms underlying plant responses to stressful conditions, which can be used to guide the design of resilient crops. In this review, we introduce ML approaches and provide examples of how researchers use these approaches to predict molecular activities, gene functions and genotype responses under stressful conditions. Finally, we consider the potential and challenges of using such approaches to enable the design of crops that are better suited to a changing environment. This article is part of the theme issue ‘Crops under stress: can we mitigate the impacts of climate change on agriculture and launch the ‘Resilience Revolution’?’.

abiotic stress↗
DOE OSTI2025

Nickel promotes selective ethylene epoxidation on silver

Over the last 80 years, chlorine (Cl) has been the primary promoter of the ethylene epoxidation reaction valued at ~40 billion USD per year, providing a ~25% selectivity increase over unpromoted silver (Ag) (~55%). Promoters such as cesium, rhenium, and molybdenum each add a few percent of selectivity enhancements to achieve 90% overall, but their codependence on Cl makes optimizing and understanding their function complex. Here, we took a theory-guided, single-atom alloy approach to identify nickel (Ni) as a dopant in Ag that can facilitate selective oxidation by activating molecular oxygen (O 2 ) without binding oxygen (O) too strongly. Surface science experiments confirmed the facile adsorption/desorption of O 2 on NiAg, as well as demonstrating that Ni serves to stabilize unselective nucleophilic oxygen. Supported Ag catalyst studies revealed that the addition of Ni in a 1:200 Ni to Ag atomic ratio provides a ~25% selectivity increase without the need for Cl co-flow and acts cooperatively with Cl, resulting in a further 10% initial increase in selectivity.

36 MATERIALS SCIENCE↗
NASA NTRS2003

Gene Expression Dynamics Inspector (GEDI): for integrative analysis of expression profiles

Genome-wide expression profiles contain global patterns that evade visual detection in current gene clustering analysis. Here, a Gene Expression Dynamics Inspector (GEDI) is described that uses self-organizing maps to translate high-dimensional expression profiles of time courses or sample classes into animated, coherent and robust mosaics images. GEDI facilitates identification of interesting patterns of molecular activity simultaneously across gene, time and sample space without prior assumption of any structure in the data, and then permits the user to retrieve genes of interest. Important changes in genome-wide activities may be quickly identified based on 'Gestalt' recognition and hence, GEDI may be especially useful for non-specialist end users, such as physicians. AVAILABILITY: GEDI v1.0 is written in Matlab, and binary Matlab.dll files which require Matlab to run can be downloaded for free by academic institutions at http://www.chip.org/~ge/gedihome.html Supplementary information: http://www.chip.org/~ge/gedihome.html.

Database Management Systems↗
DOE OSTI2022

Model Choice Metrics to Optimize Profile-QSAR Performance

Predicting molecular activity against protein targets is difficult because of the paucity of experimental data. Approaches like multitask modeling and collaborative filtering seek to improve model accuracy by leveraging results from multiple targets, but are limited because different compounds are measured with different assays, leading to sparse data matrices. Profile-QSAR (pQSAR) 2.0 addresses this problem by fitting a series of partial least squares models for each target, using as features the predictions from single-task models on the remaining targets. Here, this method has been shown to produce better results than single task and multitask models. However, the factors determining the success of pQSAR 2.0 have as yet not been characterized. In this paper we examine the experimental conditions that lead to better pQSAR models. We limit the amount of data available to the method by retraining with decreasing amounts of data and explore the model’s ability to generalize to compounds that have never been assayed. Finally, we look at the properties of training data needed to demonstrate pQSAR improvement.

Biological and medical sciences, Computer science↗
DOE OSTI2023

Molecular redox-active organic materials for electrochemical carbon capture

Abstract This prospective is a forward-looking outlook for researchers investigating electrochemical carbon capture utilizing molecular redox-active organic materials, with the following objectives: (1) identifying the essential components of an electrochemical carbon capture system, (2) introducing design principles for the system utilizing redox-active organic materials, encompassing their physicochemical properties and other critical factors, (3) presenting representative examples, and (4) promoting further experimental and theoretical studies on the application of redox-active organic materials for electrochemical carbon capture. Graphical abstract

Seo, Hyowon (ORCID:0000000295691902)↗
DOE OSTI2022

Molecular mechanism of active Cas7-11 in processing CRISPR RNA and interfering target RNA

Cas7-11 is a Type III-E CRISPR Cas effector that confers programmable RNA cleavage and has potential applications in RNA interference. Cas7-11 encodes a single polypeptide containing four Cas7- and one Cas11-like segments that obscures the distinction between the multi-subunit Class 1 and the single-subunit Class-2 CRISPR Cas systems. We report a cryo-EM (cryo-electron microscopy) structure of the active Cas7-11 from Desulfonema ishimotonii (DiCas7-11) that reveals the molecular basis for RNA processing and interference activities. DiCas7-11 arranges its Cas7- and Cas11-like domains in an extended form that resembles the backbone made up by four Cas7 and one Cas11 subunits in the multi-subunit enzymes. Unlike the multi-subunit enzymes, however, the backbone of DiCas7-11 contains evolutionarily different Cas7 and Cas11 domains, giving rise to their unique functionality. The first Cas7-like domain nearly engulfs the last 15 direct repeat nucleotides in processing and recognition of the CRISPR RNA, and its free-standing fragment retains most of the activity. Both the second and the third Cas7-like domains mediate target RNA cleavage in a metal-dependent manner. The structure and mutational data indicate that the long variable insertion to the fourth Cas7 domain has little impact on RNA processing or targeting, suggesting the possibility for engineering a compact and programmable RNA interference tool.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Magnetic Field Perturbations to a Soft X-ray-Activated Fe (II) Molecular Spin State Transition

The X-ray-induced spin crossover transition of an Fe (II) molecular thin film in the presence and absence of a magnetic field has been investigated. The thermal activation energy barrier in the soft X-ray activation of the spin crossover transition for [Fe{H2B(pz)2}2(bipy)] molecular thin films is reduced in the presence of an applied magnetic field, as measured through X-ray absorption spectroscopy at various temperatures. The influence of a 1.8 T magnetic field is sufficient to cause deviations from the expected exponential spin state transition behavior which is measured in the field free case. We find that orbital moment diminishes with increasing temperature, relative to the spin moment in the vicinity of room temperature.

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

Do Molecular Fingerprints Identify Diverse Active Drugs in Large-Scale Virtual Screening? (No)

Computational approaches for small-molecule drug discovery now regularly scale to the consideration of libraries containing billions of candidate small molecules. One promising approach to increased the speed of evaluating billion-molecule libraries is to develop succinct representations of each molecule that enable the rapid identification of molecules with similar properties. Molecular fingerprints are thought to provide a mechanism for producing such representations. Here, we explore the utility of commonly used fingerprints in the context of predicting similar molecular activity. We show that fingerprint similarity provides little discriminative power between active and inactive molecules for a target protein based on a known active—while they may sometimes provide some enrichment for active molecules in a drug screen, a screened data set will still be dominated by inactive molecules. We also demonstrate that high-similarity actives appear to share a scaffold with the query active, meaning that they could more easily be identified by structural enumeration. Furthermore, even when limited to only active molecules, fingerprint similarity values do not correlate with compound potency. In sum, these results highlight the need for a new wave of molecular representations that will improve the capacity to detect biologically active molecules based on their similarity to other such molecules.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Determination of Infinite Dilution Activity Coefficients of Molecular Solutes in Ionic Liquids and Deep Eutectic Solvents by Factorization-Machine-Based Neural Networks

Widely known as “green solvents,” ionic liquids (ILs) and deep eutectic solvents (DESs) have been used as substitutes for traditional organic solvents in separation science. To achieve better separations using ILs and DESs, this work aimed to predict the infinite dilution activity coefficients (IDACs) of molecular solutes in these solvents with the state-of-the-art factorization-machine-based neural network (DeepFM). DeepFM combines the benefits of factorization machines and deep neural networks to learn both low-order and high-order interactions among features. The IDAC prediction model was established with 52,372 experimental IDAC datapoints including 260 solvents (252 ILs and 8 DESs) and 112 molecular solutes collected at various temperatures from 288.15 to 428.15 K. Chemical information describing the ILs, DESs, and molecular solutes was included in the IDAC prediction model, including chemical functional groups, molecular weights, and Abraham solvation parameters. The IDAC prediction model showed an improved accuracy compared with alternative models; additionally, DESs were included in the IDAC prediction model for the first time. Here, the model will reduce the energy and resources needed to optimize the selection of ILs and DESs for specific separations, which will promote the development of these green solvents for sustainable chemical processes.

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

Discovery of Self-Assembling π-Conjugated Peptides by Active Learning-Directed Coarse-Grained Molecular Simulation

Electronically active organic molecules have demonstrated great promise as novel soft materials for energy harvesting and transport. Self-assembled nanoaggregates formed from π-conjugated oligopeptides composed of an aromatic core flanked by oligopeptide wings offer emergent optoelectronic properties within a water-soluble and biocompatible substrate. Nanoaggregate properties can be controlled by tuning core chemistry and peptide composition, but the sequence–structure–function relations remain poorly characterized. Here, we employ coarse-grained molecular dynamics simulations within an active learning protocol employing deep representational learning and Bayesian optimization to efficiently identify molecules capable of assembling pseudo-1D nanoaggregates with good stacking of the electronically active π-cores. We consider the DXXX-OPV3-XXXD oligopeptide family, where D is an Asp residue and OPV3 is an oligophenylenevinylene oligomer (1,4-distyrylbenzene), to identify the top performing XXX tripeptides within all 20 3 = 8000 possible sequences. By direct simulation of only 2.3% of this space, we identify molecules predicted to exhibit superior assembly relative to those reported in prior work. Spectral clustering of the top candidates reveals new design rules governing assembly. This work establishes new understanding of DXXX-OPV3-XXXD assembly, identifies promising new candidates for experimental testing, and presents a computational design platform that can be generically extended to other peptide-based and peptide-like systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗