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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 541 records · Page 30

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↗

FINETUNA: fine-tuning accelerated molecular simulations

Abstract Progress towards the energy breakthroughs needed to combat climate change can be significantly accelerated through the efficient simulation of atomistic systems. However, simulation techniques based on first principles, such as density functional theory (DFT), are limited in their practical use due to their high computational expense. Machine learning approaches have the potential to approximate DFT in a computationally efficient manner, which could dramatically increase the impact of computational simulations on real-world problems. However, they are limited by their accuracy and the cost of generating labeled data. Here, we present an online active learning framework for accelerating the simulation of atomic systems efficiently and accurately by incorporating prior physical information learned by large-scale pre-trained graph neural network models from the Open Catalyst Project. Accelerating these simulations enables useful data to be generated more cheaply, allowing better models to be trained and more atomistic systems to be screened. We also present a method of comparing local optimization techniques on the basis of both their speed and accuracy. Experiments on 30 benchmark adsorbate-catalyst systems show that our method of transfer learning to incorporate prior information from pre-trained models accelerates simulations by reducing the number of DFT calculations by 91%, while meeting an accuracy threshold of 0.02 eV 93% of the time. Finally, we demonstrate a technique for leveraging the interactive functionality built in to Vienna ab initio Simulation Package (VASP) to efficiently compute single point calculations within our online active learning framework without the significant startup costs. This allows VASP to work in tandem with our framework while requiring 75% fewer self-consistent cycles than conventional single point calculations. The online active learning implementation, and examples using the VASP interactive code, are available in the open source FINETUNA package on Github.

97 MATHEMATICS AND COMPUTING↗

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↗

C−H Activation of Inert Arenes using a Photochemically Activated Guanidinato‐Magnesium(I) Compound

Abstract UV irradiation of solutions of a guanidinate coordinated dimagnesium(I) compound, [{(Priso)Mg} 2 ] 3 (Priso=[(DipN) 2 CNPr i 2 ] − , Dip=2,6‐diisopropylphenyl), in either benzene, toluene, the three isomers of xylene, or mesitylene, leads to facile activation of an aromatic C−H bond of the solvent in all cases, and formation of aryl/hydride bridged magnesium(II) products, [{(Priso)Mg} 2 (μ‐H)(μ‐Ar)] 4 – 9 . In contrast to similar reactions reported for β‐diketiminate coordinated counterparts of 3 , these C−H activations proceed with little regioselectivity, though they are considerably faster. Reaction of 3 with an excess of the pyridine, p ‐NC 5 H 4 Bu t (py Bu t ), gave [(Priso)Mg(py Bu t H)(py Bu t ) 2 ] 10 , presumably via reduction of the pyridine to yield a radical intermediate, [(Priso)Mg(py Bu t ⋅)(py Bu t ) 2 ] 11 , which then abstracts a proton from the reaction solvent or a reactant. DFT calculations suggest two possible pathways to the observed arene C−H activations. One of these involves photochemical cleavage of the Mg−Mg bond of 3 , generating magnesium(I) doublet radicals, (Priso)Mg⋅. These then doubly reduce the arene substrate to give “Birch‐like” products, which subsequently rearrange via C−H activation of the arene. Circumstantial evidence for the photochemical generation of transient magnesium radical species includes the fact that irradiation of a cyclohexane solution of 3 leads to an intramolecular aliphatic C−H activation process and formation of an alkyl‐bridged magnesium(II) species, [{Mg(μ‐Priso −H )} 2 ] 12 . Furthermore, irradiation of a 1 : 1 mixture of 3 and the β‐diketiminato dimagnesium(I) compound, [{( Dip Nacnac)Mg} 2 ] ( Dip Nacnac=[HC(MeCNDip) 2 ] − ), effects a “scrambling” reaction, and the near quantitative formation of an unsymmetrical dimagnesium(I) compound, [(Priso)Mg−Mg( Dip Nacnac)] 13 . Finally, the EPR spectrum (77 K) of a glassed solution of UV irradiated 3 is dominated by a broad featureless signal, indicating the presence of a doublet radical species.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A Flexible Operation of Distributed Generation in Distribution Networks With Dynamic Boundaries

Distributed generators performing black start to form isolated microgrids offer a flexible and resilient solution to service restoration in distribution systems. Employing the dynamic microgrid concept, distributed generators can form isolated microgrids by changing their physical boundaries through smart switches and conventional circuit breakers. However, the flexibility of distributed generators has not been thoroughly investigated and utilised in existing works. To address this issue, this letter presents a new model to the reconfiguration formulation in active distribution networks considering different operation modes of distributed generators. Compared with the existing models, this study provides a new formulation supporting different DGs' operation modes and fully making use of their flexibility. Illustrative results on IEEE 34-test systems verify the effectiveness of the proposed model.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Design of a bifunctional TEMPO-tertiary amine mesoporous silica catalyst for the three-step cascade synthesis of a chromene derivative

A key challenge is design of materials and processes whereby competing reagents or conditions do not harm the multi-step sequence, thus allowing for more efficient chemical synthesis with elimination of work-up and separation steps. In this work, a three-step reaction cascade is performed using a porous bifunctional dimethylpropylamine-TEMPO-MCM41 catalyst, converting the commodity chemicals benzyl alcohol, sodium hypochlorite, and malononitrile to a biologically active anti-cancer, and anti-malarial 2-amino-chromene derivative. The cascade first utilizes a TEMPO-catalyzed oxidation of benzyl alcohol to benzaldehyde with NaOCl as the terminal oxidant. This is followed by a two-step, dual base catalyzed Knoevenagel condensation with malononitrile followed by a Michael addition with lawsone. Optimal conditions converting benzyl alcohol to 2-amino-5,10-dioxo-4-phenyl-5,10-dihydro-4H-benzo[g]chromene-3-carbonitrile include the delayed addition of malononitrile and lawsone during the three-step reaction sequence, which results in a 2-amino-chromene yield of over 80%. The importance of stepwise reagent addition is rationalized due to the unfavorable adsorption of acidic lawsone on the surface-grafted base catalyst. Tertiary Brønsted base sites of dimethylpropylamine outperform the more Lewis basic primary propylamine functionalized catalyst. This work outlines a simple and effective method for generating mesoporous materials with two types of active sites via co-condensation and thiol-ene coupling procedures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Temporal multi-omic analysis uncovers sex-biased molecular programs underlying skeletal muscle adaptation to endurance training

Background. Exercise training is known to benefit health and reduce disease risk. While adaptations in skeletal muscles are fundamental to many of the health benefits of exercise training, the common and sex-specific molecular regulators that mediate these adaptations remain to be fully elucidated. Methods. To this end, we leveraged skeletal muscle multi-omics data generated by the Molecular Transducers of Physical Activity Consortium (MoTrPAC), where 6 month-old male and female rats endurance trained for 1, 2, 4, or 8 weeks. Our objective was to identify shared and sex-specific multi-omic molecular responses to endurance training in skeletal muscle, and relate them to phenotypic adaptations. Results. We identified largely sexually-conserved transcriptomic and proteomic enrichments in the gastrocnemius, which correlated with skeletal muscle responses from a published exercise study in humans. We uncovered sex-consistent post-translational modifications, including decreased oxidation of MYH2 and deacetylation of the ß-oxidation enzyme HADHA. Pathway enrichment analyses revealed sex-specific remodeling across the acetylome, redox proteome, and phosphoproteome; females decreased mitochondrial protein oxidation and increased mitochondrial cristae proteins, indicative of enhanced redox buffering and mitochondrial efficiency. Despite observed decreases in the oxidation of key mitochondrial proteins, females displayed increases in the oxidation of proteins involved in glucose catabolism relative to males after 8 weeks of training, suggestive of sex-biased subcellular reactive oxygen species generation. Conclusions. This work shows a large portion of the adaptive response to endurance training in skeletal muscle is shared between females and males, while there are distinct and nuanced sex-specific adaptations that are evident, particularly at the level of post-translational regulation.

Many, Gina M.↗

Site-Selective Probes of Mixed-Node Metal Organic Frameworks for Photocatalytic Hydrogen Generation

Metal organic frameworks (MOFs) have emerged as a novel platform offering new promise for photocatalytic applications. In this work, we report a mixed-node MOF (MOF-74) based on earth-abundant metals (i.e., Co and Fe) as highly active and robust photocatalysts for visible light-driven H 2 generation. Using in situ X-ray absorption spectroscopy which allows us to selectively probe the individual metal node in MOFs, we unambiguously identified the catalytic active sites and captured the key intermediate species under the standard catalytic conditions. We show that both Co and Fe centers in MOF-74 are the reversible active sites, and the accumulation of their reduced states is responsible for the observed induction period for H 2 generation. Moreover, we captured the key intermediate species formed when the reaction reaches equilibrium, which is featured by an elongated Co–O bond at the Co center and a more distorted octahedral geometry at the Fe center with respect to their original geometry. These results not only demonstrate the potential of MOF-74 as a single site catalyst for H 2 generation but also provide new insight into the catalytic mechanism for further development.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Ni/Photoredox-Catalyzed C(sp 3 )–C(sp 3 ) Coupling between Aziridines and Acetals as Alcohol-Derived Alkyl Radical Precursors

Aziridines are readily available C(sp 3 ) precursors that afford valuable β-functionalized amines upon ring opening. In this article, we report a Ni/photoredox methodology for C(sp 3 )–C(sp 3 ) cross-coupling between aziridines and methyl/1°/2° aliphatic alcohols activated as benzaldehyde dialkyl acetals. Orthogonal activation modes of each alkyl coupling partner facilitate cross-selectivity in the C(sp 3 )–C(sp 3 ) bond-forming reaction: the benzaldehyde dialkyl acetal is activated via hydrogen atom abstraction and β-scission via a bromine radical (generated in situ from single-electron oxidation of bromide), whereas the aziridine is activated at the Ni center via reduction. Here, we demonstrate that an Ni(II) azametallacycle, conventionally proposed in aziridine cross-coupling, is not an intermediate in the productive cross-coupling. Rather, stoichiometric organometallic and linear free energy relationship studies indicate that aziridine activation proceeds via Ni(I) oxidative addition, a previously unexplored elementary step.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Multifunctional Coatings on Sulfide‐Based Solid Electrolyte Powders with Enhanced Processability, Stability, and Performance for Solid‐State Batteries

Abstract Sulfide‐based solid‐state electrolytes (SSEs) exhibit many tantalizing properties including high ionic conductivity and favorable mechanical properties for next‐generation solid‐state batteries. Widespread adoption of these materials is hindered by their intrinsic instability under ambient conditions, which makes them difficult to process at scale, and instability at the Li||SSE and cathode||SSE interfaces, which limits cell performance and lifetime. Atomic layer deposition is leveraged to grow thin Al 2 O 3 coatings on Li 6 PS 5 Cl powders to address both issues simultaneously. These coatings can be directly grown onto Li 6 PS 5 Cl particles with negligible chemical modification of the underlying material and enable exposure of powders to pure and H 2 O‐saturated oxygen environments for ≥4 h with minimal reactivity, compared with significant degradation of the uncoated powder. Pellets fabricated from coated powders exhibit ionic conductivities up to 2× higher than those made from uncoated material, with a simultaneous decrease in electronic conductivity and significant suppression of chemical reactivity at the Li‐SSE interface. These benefits result in significantly improved room temperature cycle life at high capacity and current density. It is hypothesized that this enhanced performance derives from improved intergranular properties and improved Li metal adhesion. This work points to a completely new framework for designing active, stable, and scalable materials for next‐generation solid‐state batteries.

36 MATERIALS SCIENCE↗

Incorporation and Assembly of a Light-Emitting Enzymatic Reaction into Model Protein Condensates

Eukaryotic cells partition enzymes and other cellular components into distinct subcellular compartments to generate specialized biochemical niches. A subclass of these compartments form in the absence of lipid membranes, via liquid-liquid phase separation of proteins to form biomolecular condensates or “membraneless organelles” such as nucleoli, stress granules, and P-bodies. Because of their ability to form compartments from simple starting materials, membraneless organelles are an attractive target for engineering new functionalities in both living cells and protocells. In this work, we demonstrate incorporation of novel enzymatic activity in protein coacervates with a light-generating enzyme, NanoLuc, to produce bioluminescence. Using condensates comprised of the disordered RGG domain of C. elegans LAF-1, we show functionalization of condensates with enzymatic activity in vitro and that localization to protein coacervates enhances the assembly and activity of split enzymes. To build condensates that function as light emitting reactors, we designed a NanoLuc enzyme flanked by RGG domains. Furthermore, the resulting condensates concentrated NanoLuc by 10-fold over bulk solution and display significantly increased net reaction rates. We further show that condensate viscosity impacts light emission due to diffusion-limited behavior. By splitting NanoLuc enzyme into its constituent components, we demonstrate that NanoLuc activity can be reconstituted via co-condensation. Further, we demonstrate control of the spatial localization of enzyme within condensates by targettng NanoLuc to the surface of in vitro condensates. Collectively, this work demonstrates that membraneless organelles can be endowed with localized enzymatic activity, and that this activity can be spatially and temporally controlled via enzyme reconstitution and design of protein surfactants.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Low-temperature hydroformylation of ethylene by phosphorous stabilized Rh sites in a one-pot synthesized Rh-(O)-P-MFI zeolite

Zeolites containing Rh single sites stabilized by phosphorous were prepared through a one-pot synthesis method and are shown to have superior activity and selectivity for ethylene hydroformylation at low temperature (50°C). Catalytic activity is ascribed to confined Rh 2 O 3 clusters in the zeolite which evolve under reaction conditions into single Rh 3+ sites. These Rh 3+ sites are effectively stabilized in a Rh-(O)-P structure by using tetraethylphosphonium hydroxide as a template, which generates in situ phosphate species after H 2 activation. In contrast to Rh 2 O 3 , confined Rh0 clusters appear less active in propanal production and ultimately transform into Rh(I)(CO) 2 under similar reaction conditions. As a result, we show that it is possible to reduce the temperature of ethylene hydroformylation with a solid catalyst down to 50°C, with good activity and high selectivity, by controlling the electronic and morphological properties of Rh species and the reaction conditions.

Catalysis↗

Optically controlled single-valley exciton doublet states with tunable internal spin structures and spin magnetization generation

Manipulating quantum states through light–matter interactions has been actively pursued in two-dimensional materials research. Significant progress has been made toward the optical control of the valley degrees of freedom in semiconducting monolayer transition-metal dichalcogenides, based on doubly degenerate excitons from their two distinct valleys in reciprocal space. Here, we introduce a type of optically controllable doubly degenerate exciton states that come from a single valley, dubbed as single-valley exciton doublet (SVXD) states. They are unique in that their constituent holes originate from the same valence band, making possible the direct optical control of the spin structure of the excited constituent electrons. Combining ab initio GW plus Bethe–Salpeter equation ( GW -BSE) calculations and a theoretical analysis method, we demonstrate such SVXD in substrate-supported monolayer bismuthene—which has been successfully grown using molecular beam epitaxy. In each of the two distinct valleys in the Brillouin zone, strong spin–orbit coupling and C 3 v symmetry lead to a pair of degenerate 1s exciton states (the SVXD states) with opposite spin configurations. Any coherent linear combinations of the SVXD in a single valley can be excited by light with a specific polarization, enabling full manipulation of their internal spin configurations. In particular, a controllable net spin magnetization can be generated through light excitation. Our findings open routes to control quantum degrees of freedom, paving the way for applications in spintronics and quantum information science.

2D materials↗

Characterization of SETD3 methyltransferase–mediated protein methionine methylation

Most characterized protein methylation events encompass arginine and lysine N-methylation, and only a few cases of protein methionine thiomethylation have been reported. Newly discovered oncohistone mutations include lysine-to-methionine substitutions at positions 27 and 36 of histone H3.3. In these cases, the methionine substitution localizes to the active-site pocket of the corresponding histone lysine methyltransferase, thereby inhibiting the respective transmethylation activity. SET domain–containing 3 (SETD3) is a protein (i.e. actin) histidine methyltransferase. Here, we generated an actin variant in which the histidine target of SETD3 was substituted with methionine. As for previously characterized histone SET domain proteins, the methionine substitution substantially (76-fold) increased binding affinity for SETD3 and inhibited SETD3 activity on histidine. Unexpectedly, SETD3 was active on the substituted methionine, generating S-methylmethionine in the context of actin peptide. The ternary structure of SETD3 in complex with the methionine-containing actin peptide at 1.9 Å resolution revealed that the hydrophobic thioether side chain is packed by the aromatic rings of Tyr 312 and Trp 273 , as well as the hydrocarbon side chain of Ile 310 . Our results suggest that placing methionine properly in the active site—within close proximity to and in line with the incoming methyl group of SAM—would allow some SET domain proteins to selectively methylate methionine in proteins.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Multiscale maps of Active Layer Depth for Teller site Mile Marker 27 and Kougarok Mile Marker 80, Seward Peninsula, AK

Remote sensing maps of active layer depth derived from Unmanned Areal System (UAS) data. The UAS datasets were stepwise scaled until matching the AVIRIS-NG (Airborne Visible / Infrared Imaging Spectrometer - Next Generation) and Sentinel-2 spatial resolutions. Using the field observed Active Layer Depth (ALD) measurement in combination with spectral and topographic predictors derivatives from DJI UAS imagery, we used a spatially explicit RF regression model to predict and map ALD across our study landscapes. This package includes maps for Next-Generation Ecosystem Experiment Arctic (NGEE Arctic)’s Teller Mile Marker (MM) 27, and Kougarok MM80 (aka Mile 80) watersheds. The field, map data, and metadata are provided as geoTIF and text (*.csv) formats. These datasets are provided in support of Hantson et al., 2024 (accepted) “Scaling Arctic landscape and permafrost features improves active layer depth modeling”

54 ENVIRONMENTAL SCIENCES↗

Predicting Solar Plant Generation with Machine Learning Techniques

Accurately predicting power generation for PV sites is critical for prioritizing relevant operations & maintenance activities, thereby extending the lifetime of a system and improving profit margins. A number of factors influence power generation at PV sites, including local weather, shading and soiling losses, design of modules, DC mismatches, and degradation over time. Other external factors such as curtailment and grid outages can also have a notable impact on power generation. Machine learning techniques can be used to provide more accurate predictions of PV power production by accounting for important weather and climate information neglected by current industry methods. This article will cover the deficiencies of those methods and will show how machine learning can dramatically improve power generation predictions.

14 SOLAR ENERGY↗

Emulation Modeling for Development of Cyber-Defense Capabilities for Satellite Systems

The objective of this project was to develop a novel capability to generate synthetic data sets for the purpose of training Machine Learning (ML) algorithms for the detection of malicious activities on satellite systems. The approach experimented with was to a) generate sparse data sets using emulation modeling and b) enlarge the sparse data using Generative Adversarial Networks (GANs). We based our emulation modeling on the Open Source NASA Operational Simulator for Small Satellites (NOS3) developed by the Katherine Johnson Independent Verification and Validation (IV&V) program in West Virginia. Significant new capabilities on NOS3 had to be developed for our data set generation needs. To expand these data sets for the purpose of training ML, we experimented with a) Extreme Learning Machines (ELMs) and b) Wasserstein-GANs (WGAN-GP).

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Accessing the Subsurface Biosphere Within Rocks Undergoing Active Low-Temperature Serpentinization in the Samail Ophiolite (Oman Drilling Project)

The Oman Drilling Project established an “Active Alteration” multi-borehole observatory in peridotites undergoing low-temperature serpentinization in the Samail Ophiolite. The highly serpentinized rocks are in contact with strongly reducing fluids. Distinct hydrological regimes, governed by differences in rock porosity and fracture density, give rise to steep redox (Eh +200 to –750 mV) and pH (pH range 8.5–11.2) gradients within the 300–400 m deep boreholes. The serpentinites and fluids host an active subsurface ecosystem. Microbial cell abundances in serpentinite vary at least six orders of magnitude, from ≤3.5 × 10 1 to 2.9 × 10 7 cells/g. Low levels of biological sulfate reduction (2–1,000 fmol/cm 3 /day) can be detected in rock cores, particularly in rocks in contact with reduced groundwaters with pH < 10.5. Thermodesulfovibrio is the predominant sulfate reducer identified via metagenomic sequencing of adjacent groundwater communities. Here, we infer that transport and reaction of microbially generated sulfide with the serpentine and brucite assemblages gives rise to optical darkening and sulfide overprinting, including the formation of tochilinite-vallerite group minerals, potentially serving as an indicator that this system is inhabited by microbial life. Olivine mesh-cores replaced with ferroan brucite and minor awaruite, abundant veins containing hydroandradite garnet and polyhedral serpentine, and late-stage carbonate veins are suggested as targets for future spatially resolved life-detection investigations. The high-quality whole-round core samples that have been preserved can be further probed to define how life distributes itself and functions within a system where chemical disequilibria are sustained by low-temperature water/rock interaction, and how biosignatures of in situ microbial activity are generated.

58 GEOSCIENCES↗