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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 91 records · Page 5

Bioinspired Catalyst Design Principles: Progress in Emulating Properties of Enzymes in Synthetic Catalysts

Catalysis enables many aspects of modern life, including fuels, products, plastics, and medicines. Recent advances in catalysis have enabled us to realize higher efficiencies and new processes. Ideally, we seek to achieve high rates of selective conversions using catalysts derived from abundantly available elements and operating under mild conditions, specifically lower reaction temperatures and pressures. Such catalysts could enable decentralized, on-demand synthesis of chemicals and energy carriers. Nature has demonstrated the feasibility of this approach with enzymes, which showcase catalytic processes at low temperatures and pressures with nonprecious metals. Current thinking holds that in addition to the active site, the complexity of the enzyme structure, specifically the protein scaffold, is also critical to achieving this performance. Recreating this environment has been a long-standing scientific goal. However, we still understand the functions of enzymes better than we understand the de novo design of catalysts that mimic enzymes features, while also retaining their activity and selectivity under more demanding conditions. Here, in this Perspective, we will critically examine four key areas of catalyst design that incorporate the chemical and structural properties of enzymes into synthetic catalysts: (i) the use of confinement to enhance catalytic activity, (ii) tailoring the environment around the active site, (iii) proton transport, and (iv) bifunctionality and cooperativity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

An extended focused assessment with sonography in trauma ultrasound tissue-mimicking phantom for developing automated diagnostic technologies

Medical imaging-based triage is critical for ensuring medical treatment is timely and prioritized. However, without proper image collection and interpretation, triage decisions can be hard to make. While automation approaches can enhance these triage applications, tissue phantoms must be developed to train and mature these novel technologies. Here, we have developed a tissue phantom modeling the ultrasound views imaged during the enhanced focused assessment with sonography in trauma exam (eFAST). The tissue phantom utilized synthetic clear ballistic gel with carveouts in the abdomen and rib cage corresponding to the various eFAST scan points. Various approaches were taken to simulate proper physiology without injuries present or to mimic pneumothorax, hemothorax, or abdominal hemorrhage at multiple locations in the torso. Multiple ultrasound imaging systems were used to acquire ultrasound scans with or without injury present and were used to train deep learning image classification predictive models. Performance of the artificial intelligent (AI) models trained in this study achieved over 97% accuracy for each eFAST scan site. We used a previously trained AI model for pneumothorax which achieved 74% accuracy in blind predictions for images collected with the novel eFAST tissue phantom. Grad-CAM heat map overlays for the predictions identified that the AI models were tracking the area of interest for each scan point in the tissue phantom. Overall, the eFAST tissue phantom ultrasound scans resembled human images and were successful in training AI models. Tissue phantoms are critical first steps in troubleshooting and developing medical imaging automation technologies for this application that can accelerate the widespread use of ultrasound imaging for emergency triage.

60 APPLIED LIFE SCIENCES↗

Dynamic Oscillation and Motion of Oil‐in‐Water Emulsion Droplets

Abstract The interplay of interfacial tensions on droplets results in a range of self‐powered motions that mimic those of living systems and serve as a tunable model to understand their complex non‐equilibrium behavior. Spontaneous shape deformations and oscillations are crucial features observed in nature but difficult to incorporate in synthetic artificial systems. Here, we report sessile oil‐in‐water emulsions that exhibit rapid oscillating behavior. The oscillations depend on the nature and concentration of the surfactant, the chemical composition of the oil, and the wettability of the solid substrate. The rapid changes in the contact angle per oscillation are observed using side‐view optical microscopy. We propose that the changes in the interfacial tension of the oil droplets is due to the partitioning of the surfactant into the oil phase and the movement of self‐emulsified oil out of the parent droplets giving rise to the rhythmic variation in droplet contact‐line. The ability to control and understand droplet oscillation can help model similar oscillations in out‐of‐equilibrium systems in nature and reproduce biomimetic behavior in artificial systems for various applications, such as microfluidic lab‐on‐a‐chip and adaptive materials.

Krishna Mani, Sanjana↗

Dynamic Oscillation and Motion of Oil‐in‐Water Emulsion Droplets

The interplay of interfacial tensions on droplets results in a range of self‐powered motions that mimic those of living systems and serve as a tunable model to understand their complex non‐equilibrium behavior. Spontaneous shape deformations and oscillations are crucial features observed in nature but difficult to incorporate in synthetic artificial systems. Here, we report sessile oil‐in‐water emulsions that exhibit rapid oscillating behavior. The oscillations depend on the nature and concentration of the surfactant, the chemical composition of the oil, and the wettability of the solid substrate. The rapid changes in the contact angle per oscillation are observed using side‐view optical microscopy. We propose that the changes in the interfacial tension of the oil droplets is due to the partitioning of the surfactant into the oil phase and the movement of self‐emulsified oil out of the parent droplets giving rise to the rhythmic variation in droplet contact‐line. The ability to control and understand droplet oscillation can help model similar oscillations in out‐of‐equilibrium systems in nature and reproduce biomimetic behavior in artificial systems for various applications, such as microfluidic lab‐on‐a‐chip and adaptive materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Biomimetic Catalysts Based on Au@ZnO–Graphene Composites for the Generation of Hydrogen by Water Splitting

For some decades, the scientific community has been looking for alternatives to the use of fossil fuels that allow for the planet’s sustainable and environmentally-friendly development. To do this, attempts have been made to mimic some processes that occur in nature, among which the photosystem-II stands out, which allows water splitting operating with different steps to generate oxygen and hydrogen. This research presents promising results using synthetic catalysts, which try to simulate some natural processes, and which are based on Au@ZnO–graphene compounds. These catalysts were prepared by incorporating different amounts of gold nanoparticles (1 wt.%, 3 wt.%, 5 wt.%, 10 wt.%) and graphene (1 wt.%) on the surface of synthesized zinc oxide nanowires (ZnO NWs), and zinc oxide nanoparticles (ZnO NPs), along with a commercial form (commercial ZnO) for comparison purposes. The highest amount of hydrogen (1127 μmol/hg) was reported by ZnO NWs with a gold and graphene loadings of 10 wt.% and 1 wt.%, respectively, under irradiation at 400 nm. Quantities of 759 μmol/hg and 709 μmol/hg were obtained with catalysts based on ZnO NPs and commercial ZnO, respectively. The photocatalytic activity of all composites increased with respect to the bare semiconductors, being 2.5 times higher in ZnO NWs, 8.8 times higher for ZnO NPs, and 7.5 times higher for commercial ZnO. The high photocatalytic activity of the catalysts is attributed, mainly, to the synergism between the different amount of gold and graphene incorporated, and the surface area of the composites.

Machín, Abniel (ORCID:0000000341343344)↗

Sequence Design of Random Heteropolymers as Protein Mimics

Random heteropolymers (RHPs) have been computationally designed and experimentally shown to recapitulate protein-like phase behavior and function. However, unlike proteins, RHP sequences are only statistically defined and cannot be sequenced. Recent developments in reversible-deactivation radical polymerization allowed simulated polymer sequences based on the well-established Mayo–Lewis equation to more accurately reflect ground-truth sequences that are experimentally synthesized. This led to opportunities to perform bioinformatics-inspired analysis on simulated sequences to guide the design, synthesis, and interpretation of RHPs. We compared batches on the order of 10000 simulated RHP sequences that vary by synthetically controllable and measurable RHP characteristics such as chemical heterogeneity and average degree of polymerization. Our analysis spans across 3 levels: segments along a single chain, sequences within a batch, and batch-averaged statistics. We discuss simulator fidelity and highlight the importance of robust segment definition. Examples are presented that demonstrate the use of simulated sequence analysis for in-silico iterative design to mimic protein hydrophobic/hydrophilic segment distributions in RHPs and compare RHP and protein sequence segments to explain experimental results of RHPs that mimic protein function. To facilitate the community use of this workflow, the simulator and analysis modules have been made available through an open source toolkit, the RHPapp.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Whole-cell biocomputing

The ability to manipulate systems on the molecular scale naturally leads to speculation about the rational design of molecular-scale machines. Cells might be the ultimate molecular-scale machines and our ability to engineer them is relatively advanced when compared with our ability to control the synthesis and direct the assembly of man-made materials. Indeed, engineered whole cells deployed in biosensors can be considered one of the practical successes of molecular-scale devices. However, these devices explore only a small portion of cellular functionality. Individual cells or self-organized groups of cells perform extremely complex functions that include sensing, communication, navigation, cooperation and even fabrication of synthetic nanoscopic materials. In natural systems, these capabilities are controlled by complex genetic regulatory circuits, which are only partially understood and not readily accessible for use in engineered systems. Here, we focus on efforts to mimic the functionality of man-made information-processing systems within whole cells.

Non-NASA Center↗

TwinMe4AD: WGAN-based Digital Twins for Anomaly Detection

SAND2024-08373O TwinMe4AD is a Python-based software tool designed for anomaly detection using digital twins that closely mimic real, wearable healthcare datasets. The tool is invaluable for scenarios where collecting data is either expensive or impractical, serving as a privacy-preserving solution. Sensitive information is protected by training deep learning models on synthetic data derived from real datasets. One of TwinMe4AD's key features is its anomaly detection capability, which is based on fourth-order moments of parameters. This versatile approach can be applied across a range of datasets, from univariate to multivariate, making it compatible with various types of data. It also generates synthetic twins using Wasserstein Generative Adversarial Networks (WGANs), allowing users to create a small cohort of a population similar to that of a village population. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Poorey, Kunal↗

Preface to the special issue: photosynthesis-inspired biohybrid and biomimetic systems

Research of Photosynthetic-Inspired Biohybrid and Biomimetic Systems has gained significant momentum in recent years as an approach to both study and use solar energy in new photon-to-fuels schemes that mimic photosynthesis. This intense interest arises from the incredible opportunity that photosynthetic-inspired biohybrids provide, which is to harness the optimal qualities of both artificial and natural photosynthetic systems byusing evolvedprotein architectures from biology to address synthetic challenges,and by incorporatingsynthetic molecules to creatively probe and utilize Nature’s mechanisms.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Developing a Model-based Capability to Analyze Requirements for the Climate Observing System

Models are foundational for estimating states of the earth's climate system, both as tools to extrapolate information in time and space, and as observation 'operators' used to relate what is analyzed and predicted to what is observed. Expanding the simulation approach further, observing system simulation experiments (OSSEs) are designed to mimic the complete process of analyzing the climate state by replacing real observations with entirely simulated ones determined from a model-based depiction of nature. OSSEs provide a framework to 'fly' simulated satellite instruments through a synthetic atmosphere and investigate the trade-spaces of measurements for various satellite configurations and sampling strategies, and assess their measurement impact on modeling and forecasting capabilities. Such a tool is a crucial but as yet unfulfilled need for future mission selection and design. The components of a state-of-the-art OSSE system are being assembled at the Global Modeling and Assimilation Office (GMAO, Code 610.1) at NASA/GSFC, leveraging on the GMAO's existing modeling and data assimilation infrastructure for numerical weather prediction (NWP). The OSSE framework is based on the GMAO's Goddard Earth Observing System atmospheric general circulation model, version 5 (GEOS-5) and the Gridpoint Statistical Interpolation (GSI) observational analysis scheme, combined with the Goddard Chemistry, Aerosol, Radiation, and Transport (GOCART) model developed by the Atmospheric Chemistry and Dynamics Branch (Code 613.3). This system is an evolving, key component of Goddard's planned development of an Integrated Earth System Analysis (IESA) capability, which will bring together into a single, fully interactive system Goddard's modeling and assimilation efforts in atmosphere, ocean and chemistry and aerosols to provide a comprehensive analysis and prediction system for weather and climate In addition to providing a state-of-the-art capability for assimilating current observation types, GEOS-5, and the future IESA, provide the capability to identify the need for, and assess the potential impact of, future observing systems under consideration for improving weather and climate prediction.

Gelaro, Ronald↗

A comparison of effective field theory models of redshift space galaxy power spectra for DESI 2024 and future surveys

In preparation for the next generation of galaxy redshift surveys, and in particular the year-one data release from the Dark Energy Spectroscopic Instrument (DESI), we investigate the consistency of a variety of effective field theory models that describe the galaxy-galaxy power spectra in redshift space into the quasi-linear regime using 1-loop perturbation theory. These models are employed in the pipelines velocileptors, PyBird, and Folpsν. While these models have been validated independently, a detailed comparison with consistent choices has not been attempted. After briefly discussing the theoretical differences between the models we describe how to provide a more apples-to-apples comparison between them. We present the results of fitting mock spectra from the AbacusSummit suite of N-body simulations provided in three redshift bins to mimic the types of dark time tracers targeted by the DESI survey. We show that the theories behave similarly and give consistent constraints in both the forward-modeling and ShapeFit compressed fitting approaches. We additionally generate (noiseless) synthetic data from each pipeline to be fit by the others, varying the scale cuts in order to show that the models agree within the range of scales for which we expect 1-loop perturbation theory to be applicable. Finally, this work lays the foundation of Full-Shape analysis with DESI Y1 galaxy samples where in the tests we performed, we found no systematic error associated with the modeling of the galaxy redshift space power spectrum for this volume.

79 ASTRONOMY AND ASTROPHYSICS↗

Advances in supramolecular host-mediated reactivity

Since the trailblazing discoveries of Lehn, Cram and Pedersen, supramolecular chemistry has established itself as a cornerstone of organic chemistry. Supramolecular hosts offer defined microenvironments that mimic the active sites of enzymes, utilizing specific host–guest interactions to enable remarkable rate enhancements and product selectivity. The development of a diverse array of self-assembled hosts, coupled with the increased demand for shorter and greener synthetic routes, have spurred significant progress in the field of supramolecular catalysis. This Review Article covers recent advances in the field, ranging from novel organic reactivity aided by supramolecular hosts to catalytic cooperation between hosts and organometallic compounds or metal nanoparticles. Furthermore, strides have also been made in the synthetic application of these hosts in site-selective substrate modifications and challenging photochemical reactions. These efforts have enabled the incorporation of non-covalent macromolecular catalysis in natural product syntheses, evidencing their unique advantages as a synthetic tool, and their powerful potential for practical applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Population-based heteropolymer design to mimic protein mixtures

Biological fluids, the most complex blends, have compositions that constantly vary and cannot be molecularly defined. Despite these uncertainties, proteins fluctuate, fold, function and evolve as programmed. We propose that in addition to the known monomeric sequence requirements, protein sequences encode multi-pair interactions at the segmental level to navigate random encounters; synthetic heteropolymers capable of emulating such interactions can replicate how proteins behave in biological fluids individually and collectively. Here, we extracted the chemical characteristics and sequential arrangement along a protein chain at the segmental level from natural protein libraries and used the information to design heteropolymer ensembles as mixtures of disordered, partially folded and folded proteins. For each heteropolymer ensemble, the level of segmental similarity to that of natural proteins determines its ability to replicate many functions of biological fluids including assisting protein folding during translation, preserving the viability of fetal bovine serum without refrigeration, enhancing the thermal stability of proteins and behaving like synthetic cytosol under biologically relevant conditions. Molecular studies further translated protein sequence information at the segmental level into intermolecular interactions with a defined range, degree of diversity and temporal and spatial availability. This framework provides valuable guiding principles to synthetically realize protein properties, engineer bio/abiotic hybrid materials and, ultimately, realize matter-to-life transformations.

59 BASIC BIOLOGICAL SCIENCES↗

Can the Rate of a Catalytic Turnover Be Altered by Ligands in the Absence of Direct Binding Interactions?

Second sphere coordination effects ubiquitous in enzymatic catalysis occur through direct interactions, either covalent or non-covalent, with reaction intermediates and transition states. Here, we present herein evidence of indirect second sphere coordination effects in which ligation of water/alkanols far removed from the primary coordination sphere of the active site nevertheless alter energetic landscapes within catalytic redox cycles in the absence of direct physicochemical interactions with surface species mediating catalytic turnovers. Density functional theory, in situ X-ray absorption and infrared spectroscopy, and a wide array of steady-state and transient CO oxidation rate data suggest that the presence of peripheral water renders oxidation half-cycles within two-electron redox cycles over μ m -oxo-bridged trimers in MIL-100(M) more kinetically demanding. Communication between ligated water and the active site appears to occur through the Fe-O-Fe backbone, as inferred from spin density variations on the central μ m -oxygen 'junction'. Evidence is provided for the generality of these second sphere effects in that they influence different types of redox half-cycles or metals, and can be amplified or attenuated through choice of coordinating ligand. Specifically in the case of MIL-100(M) materials, the Cr isostructure can be made to kinetically mimic the Fe variant by disproportionately hindering oxidation half-cycles relative to the reduction half-cycles. Kinetic and spectroscopic inferences presented here significantly expand both the conceptual definition of second sphere effects as well as the palette of synthetic levers available for tuning catalytic redox performance through chemical ligation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Functional and Multifunctional Polymers: Materials for Smart Structures

The ultimate goal of the research in smart structures and smart materials is the development of a new generation of products/devices which will perform better than products/devices built from passive materials. There are a few examples of multilayer polymer systems which function as smart structures, e.g. a synthetic muscle which is a multilayer assembly of a poly(ethylene) layer, a gold layer, and a poly(pyrrole) layer immersed in a liquid electrolyte. Oxidation and reductions of the active pyrrole layer causes the assembly to reversibly deflect and mimic biological muscles. The drawback of such a setup is slow response times and the use of a liquid electrolyte. We have developed multifunctional polymers which will eliminate the use of a liquid electrolyte, and also because the functionalities of the polymers are within a few hundred angstroms, an improved response time to changes in the external field should be possible. Such multifunctional polymers may be classified as the futuristic 'smart materials.' These materials are composed of a number of different functionalities which work in a synergistic fashion to function as a device. The device performs on the application of an external field and such multifunctional polymers may be scientifically labeled as 'field responsive polymers.' Our group has undertaken a systematic approach to develop functional and multifunctional polymers capable of functioning as field responsive polymers. Our approach utilizes multicomponent polymer systems (block copolymers and graft copolymers), the strategy involves the preparation of block or graft copolymers where the functionalities are limited to different phases in a microphase separated system. Depending on the weight (or volume) fractions of each of the components, different microstructures are possible. And, because of the intimate contact between the functional components, an increase in the synergism between the functionalities may be observed. In this presentation, three examples of multifunctional polymers developed in our labs will be reported. The first class of multifunctional polymers are the microphase separated mixed (ionic and electronic) conducting or MIEC block copolymers. The second class being developed in our labs are the biocompatible conductive materials and the conductive fluids. The final class may be considered microwave active smart polymers.

Arnold, S.↗

Direct structural retrieval from gas-phase ultrafast diffraction data using a genetic algorithm

Ultrafast scattering techniques such as ultrafast electron diffraction and ultrafast x-ray diffraction have been utilized to elucidate the structural dynamics, reaction intermediates, and final products in molecular reactions following photoexcitation. The time-dependent structures are typically not directly retrieved from the experimental data, but they rely on comparison with calculations. The genetic algorithm (GA), a global optimization strategy, can be used to retrieve the molecular structures directly from diffraction patterns without any theoretical input. However, the robustness of the GA with respect to real experimental conditions such as a limited momentum transfer range, noise, and artifacts has not been studied in detail. In this work, we characterize the performance of the GA with simulated data that mimic realistic experimental conditions. We have developed and implemented a variant of the GA specific to diffraction measurements which performs better in the presence of imperfect data compared to the standard implementation of the GA. We demonstrate this method with both synthetic data and experimental ultrafast electron diffraction data on the UV-induced photodissociation of trifluoroiodomethane (C⁢F 3⁡ I) molecules.

74 ATOMIC AND MOLECULAR PHYSICS↗

The Influence of Ecological Isolation on the Structural and Functional Stability of Complex Microbial Communities

To help understand how the behavior of microorganisms and microbial communities in insular space habitats may differ from the behavior of these groups on Earth, long-term incubations (100+ days) were conducting using wastewater bioreactors (batch fed) designed to mimic "closed" and "open" ecological systems. The issue of immigration was considered, and the goal of the research was to determine whether the stability of microbial communities in space is reduced due to their prolonged isolation. Bioreactors were established by inoculating flasks of sterile synthetic wastewater with the microbial community obtained from a local treatment facility; each day, one-third of the medium in the flask was replaced with an equal volume of sterile artificial wastewater. Flasks were divided into two treatments: "closed" and "open" to recruitment of additional microorganisms. "Closed" flasks were maintained as described above, while the medium used to feed the "open" flasks was supplemented daily with a small amount of raw sewage (which provided a continuous source of new potential community members). Significant differences in microbial community structure and function developed in the two sets of communities, and the results suggest that the open community was more stable and better able to adjust to changing environmental conditions. Each community's resistance to environmental (temperature fluctuations) and biological stresses (starvation and invasion by an opportunistic pathogen Pseudomonas aeruginosa) was monitored. Experiments were also conducted to determine whether the effect of isolation changes depending on the microbial communities' initial diversity or composition; communities with a low(er) initial diversity were less stable. Overall, the results indicate that isolation will be an important factor influencing the activity of microbial communities on board spacecraft. A possible way of mitigating these effects would be to include communities with high initial diversity or to periodically re-inoculate the systems using diverse inocula transported from Earth.

Franklin, R. B.↗

Leveraging Observing System Simulation Experiments for Satellite Instrument Design: Advancements and Challenges

This abstract highlights NASA's OSSE framework, developed at the Global Modeling and Assimilation Office, which has become a widely adopted tool for evaluating the impact of new observations on weather forecasts. The framework involves simulating realistic observations by introducing errors to mimic real-world scenarios. By utilizing advanced radiative transfer modeling, the accuracy of simulated observations is significantly improved, enhancing the reliability of experimental outcomes. The talk focuses on recent progress and challenges in three key areas. Firstly, it explores the techniques used to simulate synthetic observations, a crucial aspect of OSSE experiments. Secondly, the presentation also discusses the challenges of examining the observation errors that need to be added to the perfect observations to generate realistic simulated observations. Lastly, the assimilation of synthetic observations and their impact on forecast skills is evaluated, providing valuable insights for optimizing current and future observing systems for improving the weather forecasts. By sharing recent advancements and acknowledging challenges, this presentation seeks to inspire researchers to leverage the OSSE framework in weather forecasting. NASA's OSSE techniques hold promise for a better understanding of the atmosphere and the development of more accurate and reliable weather predictions.

Isaac Moradi↗