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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Unraveling Fundamental Activity–Stability Relationships in Rutile Oxides

The oxygen evolution reaction (OER) is a key anodic half-cell reaction that accompanies several critical electrochemical reduction reactions of interest to a variety of applications. Despite steady advances in understanding and qualitatively predicting OER activity and selectivity trends, a comprehensive description or prediction of material aqueous (in)stability and degradation mechanisms remains elusive, even though these processes critically influence device lifetime and economic feasibility. In this work, we investigate the interplay, or lack thereof, between OER activity and material aqueous stability across rutile oxides, with a particular focus on iridium oxide (IrO 2 ). By applying a Born–Haber cycle, we calculate the thermodynamic driving force for metal dissolution as a function of the applied bias and electrolyte conditions. We apply interpretable machine learning techniques, including principal component analysis and symbolic regression, to analyze trends across rutile oxides and find that key thermodynamic descriptors for OER activity and surface stability are only very weakly correlated. Instead, the local atomic environment─especially electronic structure signatures for interactions between the active site and its neighbors─plays a more important role in predicting material stability. Leveraging these insights, we investigate the impact of doping IrO 2 with a range of transition metals and show that the stability of Ir active sites can be tuned largely independently of its predicted OER activity. These insights lay the foundation for material design to improve stability with respect to corrosion, with the ultimate aim to enhance long-term stability without sacrificing catalytic performance in the OER.

evolution reactions↗
DOE OSTI2020

Engineering Active Fe Sites on Nickel–Iron Layered Double Hydroxide through Component Segregation for Oxygen Evolution Reaction

Nickel-iron layered double hydroxide (NiFe LDH) is a promising oxygen evolution reaction (OER) electrocatalyst under alkaline conditions. Much research has been performed to understand the structure-activity relationship of NiFe LDH under OER conditions. However, the specific role of the Fe species remains unclear and under debate. Herein, based on DFT calculations, it was discovered that the edge Fe sites show higher activity towards OER than either the edge Ni sites or lattice sites. Therefore, a facile acid-etching method was proposed to controllably induce the formation of edge Fe sites in NiFe LDH, and the obtained sample exhibited higher OER activity. X-ray absorption near edge structure and extended X-ray absorption fine structure analyses further revealed that the interaction of the edge Fe species with Ni is believed to contribute to the enhancement of the OER performance. This work provides a new understanding of the structure-activity relationship in NiFe LDH and offers a facile method for the design of efficient electrocatalysts in an alkaline environment.

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

Acidic Oxygen Evolution Reaction Activity–Stability Relationships in Ru-Based Pyrochlores

Ru-based oxygen evolution reaction (OER) catalysts show significant promise for efficient water electrolysis, but rapid degradation poses a major challenge for commercial applications. In this work, we explore several Ru-based pyrochlores (A 2 Ru 2 O 7 , A = Y, Nd, Gd, Bi) as OER catalysts and demonstrate improved activity and stability of catalytic Ru sites relative to RuO 2 . Furthermore, we combine complementary experimental and theoretical analysis to understand how the A-site element impacts activity and stability under acidic OER conditions. Among the A 2 Ru 2 O 7 studied herein, we find that a longer Ru–O bond and a weaker interaction of the Ru 4d and O 2p orbitals compared with RuO 2 results in enhanced initial activity. We observe that the OER activity of the catalysts changes over time and is accompanied by both A-site and Ru dissolution at different relative rates depending on the identity of the A-site. Pourbaix diagrams constructed using density functional theory (DFT) calculations reveal a driving force for this experimentally observed dissolution, indicating that all compositions studied herein are thermodynamically unstable in acidic OER conditions. Theoretical activity predictions show consistent trends between A-site cation leaching and OER activity. These trends coupled with Bader charge analysis suggest that dissolution exposes highly oxidized Ru sites that exhibit enhanced activity. Overall, using the stability number (molO2 evolved/molRu dissolved) as a comparative metric, the A 2 Ru 2 O 7 materials studied in this work show substantially greater stability than a standard RuO2 and commensurate stability to some Ir mixed metal oxides. Finally, the insights described herein provide a pathway to enhanced Ru catalyst activity and durability, ultimately improving the efficiency of water electrolyzers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1983

A study of solar activity-ozone relationship from Nimbus-4 BUV data

The total O3 and the O3 mixing ratio at various pressure levels in the stratosphere measured from the Nimbus-4 BUV experiment over a 7-yr period (1970 to 1977) comprises a comprehensive data base available to study the possible effects of solar variability on stratospheric O3. It is shown that with the decrease in solar activity from 1970 to 1976, the globally averaged O3 inferred from Nimbus-4 data decreases from about 10 to 12 percent in the upper stratosphere to about 1 to 3 percent in the lower stratosphere. The systematic decrease in O3 seems to be correlated with the conventional indices of solar activity; however, it is difficult to account for the observed changes at various pressure levels with the current understanding of the photochemical models and the solar UV flux variations over a solar cycle.

Chandra, S.↗
DOE OSTI2021

Engineering Second Sphere Interactions in a Host–Guest Multicomponent Catalyst System for the Hydrogenation of Carbon Dioxide to Methanol

Many enzymes utilize interactions extending beyond the primary coordination sphere to enhance catalyst activity and/or selectivity. Such interactions could improve the efficacy of synthetic catalyst systems, but the supramolecular assemblies employed by biology to incorporate second sphere interactions are challenging to replicate in synthetic catalysts. Herein, a strategy is reported for efficiently manipulating outer sphere influence on catalyst reactivity by modulating host–guest interactions between a noncovalently encapsulated transitionmetal-based catalyst guest and a metal–organic framework (MOF) host. This composite consists of a ruthenium PNP pincer complex encapsulated in the MOF UiO-66 that is used in tandem with the zirconium oxide nodes of UiO-66 and a ruthenium PNN pincer complex to hydrogenate carbon dioxide to methanol. Due to the method used to incorporate the complexes in UiO-66, structure–activity relationships could be efficiently determined using a variety of functionalized UiO-66-X hosts. These investigations uncovered the beneficial effects of the ammonium functional group (i.e., UiO-66-NH 3 + ). Mechanistic experiments revealed that the ammonium functionality improved efficiency in the hydrogenation of carbon dioxide to formic acid, the first step in the cascade. Isotope effects and structure–activity relationships suggested that the primary role of the ammonium functionality is to serve as a general Brønsted acid. Importantly, the cooperative influence from the host was effective only with the functional group in close proximity to the encapsulated catalyst. Here, reactions carried out in the presence of molecular sieves to remove water highlighted the beneficial effects of the ammonium functional group in UiO-66-NH 3 + and resulted in a 4-fold increase in activity. As a result of the modular nature of the catalyst system, the highest reported turnover number (TON) (19 000) and turnover frequency (TOF) (9100 h –1 ) for the hydrogenation of carbon dioxide to methanol are obtained. Moreover, the reaction was readily recyclable, leading to a cumulative TON of 100 000 after 10 reaction cycles.

08 HYDROGEN↗
NASA NTRS1991

Radius-luminosity and mass-luminosity relationships for active galactic nuclei

Broad-line region (BLR) sizes derived from spectral variability and BLR line widths are used to directly derive the mass (M) of the central objects of ten active galactic nuclei (AGNs) in a uniform manner. It is shown that the luminosity-weighted C IV 1549-emitting BLR radius (R) correlates with the bolometric luminosity L(Bol) and is consistent with R about sq rt L(Bol). The measurements also permit a verification of the Dibai mass-luminosity (M-L) relationship (previously derived indirectly). It is found that L(Bol) is proportional to M exp (1.1 + or - 0.3). It is found that the efficiency factor epsilon, defined as the ratio of L(Bol) to the Eddington luminosity increases from 0.03 in the low-luminosity Seyferts up to 0.06 in the most luminous objects in the sample.

Koratkar, Anuradha P.↗
DOE OSTI2023

Anti-fungal bioactive terpenoids in the bioenergy crop switchgrass (Panicum virgatum) may contribute to ecotype-specific microbiome composition

Abstract Plant derived bioactive small molecules have attracted attention of scientists across fundamental and applied scientific disciplines. We seek to understand the influence of these phytochemicals on rhizosphere and root-associated fungi. We hypothesize that – consistent with accumulating evidence that switchgrass genotype impacts microbiome assembly – differential terpenoid accumulation contributes to switchgrass ecotype-specific microbiome composition. An initial in vitro Petri plate-based disc diffusion screen of 18 switchgrass root derived fungal isolates revealed differential responses to upland- and lowland-isolated metabolites. To identify specific fungal growth-modulating metabolites, we tested fractions from root extracts on three ecologically important fungal isolates – Linnemania elongata, Trichoderma sp. and Fusarium sp. Saponins and diterpenoids were identified as the most prominent antifungal metabolites. Finally, analysis of liquid chromatography-purified terpenoids revealed fungal inhibition structure – activity relationships (SAR). Saponin antifungal activity was primarily determined by the number of sugar moieties – saponins glycosylated at a single core position were inhibitory whereas saponins glycosylated at two core positions were inactive. Saponin core hydroxylation and acetylation were also associated with reduced activity. Diterpenoid activity required the presence of an intact furan ring for strong fungal growth inhibition. These results inform future breeding and biotechnology strategies for crop protection with reduced pesticide application.

09 BIOMASS FUELS↗
NASA NTRS1973

The evolution of prominences and their relationship to active centers /A Review/

A necessary condition for the formation of prominences is established where components of the magnetic field of opposite sign lie juxtaposed. This condition is sometimes recognizable prior to the formation of prominences in active centers and between adjacent active centers in H-alpha by paths of fibrils aligned nearly end to end. Prominences are usually not found in active regions until they are about 4 days old. After this time, the number of prominences appears to be a function of the large-scale complexities in the magnetic field pattern whether these are a result of emerging flux, the merging of adjacent active centers, or the coalescing of remnant fields of active centers. Prominences may disappear by the slow or rapid flow of mass into the chromosphere or by the more violent eruptives. The formation of new active centers has been associated with the eruption of some filaments related to weak chromospheric fields.

Martin, S. F.↗
NASA NTRS1987

The relationship of active comets, 'extinct' comets, and dark asteroids

The possibility of distinguishing between outer solar system asteroids and dark cometary objects is discussed. Planetesimals that could be comets in various evolutionary phases have been detected at distances greater than about 3 AU. Comparisons are made among observed planetesimal and cometary albedos and spectra. It is noted that carbonaceous material, assumed to originate from comets, has been captured in the stratosphere. The data indicate that extinct or dormant comets have loose aggregate surface structures consisting of reddish organic compounds. A protoplanetary nebular condensation scenario is discussed which would have produced the dark cometary bodies.

Hartmann, William K.↗
DOE OSTI2023

Integrated data-driven and experimental approaches to accelerate lead optimization targeting SARS-CoV- 2 main protease

Identification of potential therapeutic candidates can be expedited by integrating computational modeling with domain aware machine learning (ML) approaches followed by experimental validation. Generative deep learning models have been recently developed that can generate thousands of new candidates, but their physiochemical properties are typically not optimized. Using our deep learning models and a scaffold as a starting point, we generated tens of thousands of compounds for SARS-CoV-2 M pro that preserve the core scaffold. Here we utilized and implemented several computational tools such as structural alert and toxicity analysis, high throughput virtual screening, ML-based 3D quantitative structure–activity relationships, multi-parameter optimization, and graph neural networks on libraries of generated candidates to predict biological activity and binding affinity a priori. From these collective computational results, eight promising candidates were identified and tested experimentally using Native Mass Spectrometry (MS) and FRET-based functional assays. Two compounds, with quinazoline-2-thiol and acetylpiperidine core moiety showed IC 50 values in the low micromolar range: 2.95±0.0017 µM and 3.41±0.0015 µM, respectively. The molecular dynamics simulations further highlight that binding of these compounds results in allosteric modulations in the chain B and the interface domains of the M pro . The key fragments from these top hits can be used as input for closed loop lead optimization in the integrated pipeline.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Dynamic control and quantification of active sites on ceria for CO activation and hydrogenation

Ceria (CeO 2 ) is a widely used oxide catalyst, yet the nature of its active sites remains elusive. This study combines model and powder catalyst studies to elucidate the structure-activity relationships in ceria-catalyzed CO activation and hydrogenation. Well-defined ceria clusters are synthesized on planar CeO 2 (111) and exhibit dynamic and tunable ranges of Ce coordination numbers, which enhance their interaction with CO. Reduced ceria clusters (e.g., Ce 3 O 3 ) bind CO strongly and facilitate its dissociation, while near-stoichiometric clusters (e.g., Ce 3 O 7 ) adsorb CO weakly and promote oxidation via carbonate formation. Unlike planar ceria surfaces, supported ceria clusters exhibit dynamic properties and enhanced catalytic activity, that mimic those of powder ceria catalysts. Insight from model studies provide a method to quantify active sites on powder ceria and guide further optimization of ceria catalysts for syngas conversion. This work marks a leap toward model-guided catalyst design and highlights the importance of site-specific catalysis.

03 NATURAL GAS↗
DOE OSTI2025

Biosynthesis of bioprivileged, linear molecules via novel carboligase reactions

Over the award period, we made progress on the three aims. We screened twenty-five carboligases for activity coupling twenty-one possible -keto acids (Aim 1). The carboligases were selected across a diverse set of protein sequences. Using Q-Exactive UHPLC-MS, we tested a total of 210 coupled products per enzyme and generated a dataset of 5250 enzyme-substrate activity relationships. We identified multiple enzymes that had activity for synthesizing suberic acid and heptanoic acid (Aim 2). We built a random forest model for predicting the activity of each enzyme toward substrates on which it was not tested using the data from Aim 1. Finally, we evaluated growth defects that occurred due to expression of different carboligases in E. coli (Aim 3). We were able to identify specific metabolites and putative pathways that, when supplemented in the media, recovered the growth defect associated with the presence of specific carboligases. We are in the process of publishing two manuscript describing the methods for high-throughput screening of enzyme promiscuity, using machine learning to predict activity on untested substrates, and enzyme activity data we collected. This project has produced enabling data for biosynthesis of a range of new-to-nature compounds to support biomanufacturing.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Bacterial Resistance Toward Antimicrobial Ionic Liquids Mediated by Multidrug Efflux Pumps

The effective elimination of foodborne pathogens through cleaning and disinfection measures is of great importance to the food processing industry. As food producers rely heavily on disinfectants to control pathogenic bacteria in their facilities, the increasing spread of tolerant, often even multidrug resistant, strains is of particular concern. In addition to efforts to prevent or at least reduce development and spread of strains resistant to disinfectants and sanitizers, there is an urgent need for new and effective antimicrobials. One new class of promising antimicrobials is ionic liquids (ILs), which have been reported to be effective against resistant strains as they interact with bacterial cells in multiple ways, but investigations of their effectivity against MDR bacteria or specific defense mechanisms are still limited. This study investigates the role of multidrug efflux pumps of the Resistance Nodulation-Division family (RND) on the resistance of bacterial pathogens Escherichia coli and Salmonella enterica serovar Typhimurium toward 10 antimicrobial active ILs. Results reveal that, while known structure–activity relationships (SARs), such as the side-chain effect, were found for all strains, antimicrobial ILs with one elongated alkyl side chain were significantly affected by the RND efflux pump, highlighting the importance of efflux pumps for future IL toxicity studies. In case of antimicrobial ILs with multiple side chains and different cationic head groups, two ILs were identified that were highly active against all investigated strains with little to no effect of the efflux pump. The results obtained in this study for RND efflux pumps can serve as a starting point for identifying and designing antimicrobial ILs as effective biocides against MDR bacteria.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Engineering a Self-Grown TiO 2 /Ti-MOF Heterojunction with Selectively Anchored High-Density Pt Single-Atomic Cocatalysts for Efficient Visible-Light-Driven Hydrogen Evolution

A photocatalyst TiO 2 /Ti-BPDC-Pt is developed with a self-grown TiO 2 /Ti-metal–organic framework (MOF) heterojunction, i.e., TiO 2 /Ti-BPDC, and selectively anchored high-density Pt single-atomic cocatalysts on Ti-BPDC for photocatalytic hydrogen evolution. This intimate heterojunction, growing from the surface pyrolytic reconstruction of Ti-BPDC, works in a direct Z-scheme, efficiently separating electrons and holes. Pt is selectively anchored on Ti-BPDC by ligands and is found in the form of single atoms with loading up to 1.8 wt %. The selective location of Pt is the electron-enriched domain of the heterojunction, which further enhances the utilization of the separated electrons. This tailored TiO 2 /Ti-BPDC-Pt shows a significantly enhanced activity of 12.4 mmol g -1 h -1 compared to other TiO 2 - or MOF-based catalysts. In conclusion, the structure-activity relationship further proves the balance of two simultaneously exposed domains of heterojunctions is critical to fulfilling this kind of catalyst.

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

Fingerprinting Interactions between Proteins and Ligands for Facilitating Machine Learning in Drug Discovery

Molecular recognition is fundamental in biology, underpinning intricate processes through specific protein–ligand interactions. This understanding is pivotal in drug discovery, yet traditional experimental methods face limitations in exploring the vast chemical space. Computational approaches, notably quantitative structure–activity/property relationship analysis, have gained prominence. Molecular fingerprints encode molecular structures and serve as property profiles, which are essential in drug discovery. While two-dimensional (2D) fingerprints are commonly used, three-dimensional (3D) structural interaction fingerprints offer enhanced structural features specific to target proteins. Machine learning models trained on interaction fingerprints enable precise binding prediction. Recent focus has shifted to structure-based predictive modeling, with machine-learning scoring functions excelling due to feature engineering guided by key interactions. Notably, 3D interaction fingerprints are gaining ground due to their robustness. Various structural interaction fingerprints have been developed and used in drug discovery, each with unique capabilities. This review recapitulates the developed structural interaction fingerprints and provides two case studies to illustrate the power of interaction fingerprint-driven machine learning. The first elucidates structure–activity relationships in β2 adrenoceptor ligands, demonstrating the ability to differentiate agonists and antagonists. The second employs a retrosynthesis-based pre-trained molecular representation to predict protein–ligand dissociation rates, offering insights into binding kinetics. Despite remarkable progress, challenges persist in interpreting complex machine learning models built on 3D fingerprints, emphasizing the need for strategies to make predictions interpretable. Binding site plasticity and induced fit effects pose additional complexities. Interaction fingerprints are promising but require continued research to harness their full potential.

3D structural interaction fingerprints↗
DOE OSTI2020

Exploring the Effects of Node Topology, Connectivity, and Metal Identity on the Binding of Nerve Agents and Their Hydrolysis Products in Metal–Organic Frameworks

Recent studies have shown that metal–organic frameworks (MOFs) built from hexanuclear M(IV) oxide cluster nodes are effective catalysts for nerve agent hydrolysis, where the properties of the active sites on the nodes can strongly influence the reaction energetics. The connectivity and metal identity of these M6 nodes can be easily tuned, offering extensive opportunities for computational screening to predict promising new materials. Thus, we used density functional theory (DFT) to examine the effects of node topology, connectivity, and metal identity on the binding energies of multiple nerve agents and their corresponding hydrolysis products. By computing an optimization metric based on the relative binding strengths of key hydrolysis reaction species (water, agent, and bidentate-bound products), we predicted optimal M6 nodes for hydrolyzing specific nerve agent and simulant molecules, where our results are in qualitative agreement with observed experimental trends. This analysis highlighted the notion that no single metal or node topology is optimal for all possible organophosphates, suggesting that MOFs should be selected based on the agent of interest. Using the large amount of data generated from our DFT calculations, we then derived quantitative structure–activity relationship (QSAR) models to help explain the complex trends observed in the binding energies. Through linear regression, we identified the most important descriptors for describing the binding of nerve agents and their hydrolysis products to M6 nodes. These results suggested that both molecular and node properties, including both structural and chemical features, collectively contribute to the binding energetics. By performing a thorough statistical analysis, we showed that our QSAR models are capable of making quantitatively accurate binding energy predictions for nerve agents and their hydrolysis products in a wide variety of M(IV)-MOFs. In conclusion, the insights gained herein can be used to guide future experiments for the synthesis of MOFs with enhanced catalytic activity for organophosphate hydrolysis.

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

Potent Inhibition of E. coli DXP Synthase by a gem -Diaryl Bisubstrate Analog

New antimicrobial strategies are needed to address pathogen resistance to currently used antibiotics. Bacterial central metabolism is a promising target space for the development of agents that selectively target bacterial pathogens. 1-Deoxy- D -xylulose 5-phosphate synthase (DXPS) converts pyruvate and d-glyceraldehyde 3-phosphate ( D -GAP) to DXP, which is required for synthesis of essential vitamins and isoprenoids in bacterial pathogens. Thus, DXPS is a promising antimicrobial target. Toward this goal, our lab has demonstrated selective inhibition of Escherichia coli DXPS by alkyl acetylphosphonate (alkylAP)-based bisubstrate analogs that exploit the requirement for ternary complex formation in the DXPS mechanism. Here, we present the first DXPS structure with a bisubstrate analog bound in the active site. Insights gained from this cocrystal structure guided structure–activity relationship studies of the bisubstrate scaffold. A low nanomolar inhibitor (compound 8) bearing a gem-dibenzyl glycine moiety conjugated to the acetylphosphonate pyruvate mimic via a triazole-based linker emerged from this study. Compound 8 was found to exhibit slow, tight-binding inhibition, with contacts to E. coli DXPS residues R99 and R478 demonstrated to be important for this behavior. This work has discovered the most potent DXPS inhibitor to date and highlights a new role of R99 that can be exploited in future inhibitor designs toward the development of a novel class of antimicrobial agents.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗