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At least 1,099 records · Page 61
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Artificial intelligence for materials research at extremes

Abstract Materials development is slow and expensive, taking decades from inception to fielding. For materials research at extremes, the situation is even more demanding, as the desired property combinations such as strength and oxidation resistance can have complex interactions. Here, we explore the role of AI and autonomous experimentation (AE) in the process of understanding and developing materials for extreme and coupled environments. AI is important in understanding materials under extremes due to the highly demanding and unique cases these environments represent. Materials are pushed to their limits in ways that, for example, equilibrium phase diagrams cannot describe. Often, multiple physical phenomena compete to determine the material response. Further, validation is often difficult or impossible. AI can help bridge these gaps, providing heuristic but valuable links between materials properties and performance under extreme conditions. We explore the potential advantages of AE along with decision strategies. In particular, we consider the problem of deciding between low-fidelity, inexpensive experiments and high-fidelity, expensive experiments. The cost of experiments is described in terms of the speed and throughput of automated experiments, contrasted with the human resources needed to execute manual experiments. We also consider the cost and benefits of modeling and simulation to further materials understanding, along with characterization of materials under extreme environments in the AE loop. Graphical abstract AI sequential decision-making methods for materials research: Active learning, which focuses on exploration by sampling uncertain regions, Bayesian and bandit optimization as well as reinforcement learning (RL), which trades off exploration of uncertain regions with exploitation of optimum function value. Bayesian and bandit optimization focus on finding the optimal value of the function at each step or cumulatively over the entire steps, respectively, whereas RL considers cumulative value of the labeling function, where the latter can change depending on the state of the system (blue, orange, or green).

36 MATERIALS SCIENCE↗
NASA NTRS2012

Plant Atrium System for Food Production in NASA's Deep Space Habitat Tests

In preparation for future human exploration missions to space, human habitat designs and concepts need to be tested to assess integration issues, power requirements, crew operations, and technology I subsystem performance. One potential subsystem for early habitats is supplemental food production. Fresh foods, such as vegetables and small fruits, could be harvested on a continuous basis to improve the diet and quality of life. The system would need to fit conveniently into the habitat and not interfere with other components or operations. To test this concept, a plant growing "atrium" was designed to surround the lift between the lower and upper modules of the Deep Space Habitat and deployed at NASA DRA TS test site in 2011 and at NASA's JSC in 20I2. With this approach, un-utilized volume provided an area for vegetable growth. For the 20 II test, mizuna, lettuce, basil, radish and sweetpotato plants were grown in trays using commercially available red I blue LED light fixtures. Seedlings were transplanted into the atrium and cared for by the crew. Plants were then harvested two weeks later following completion of the test. In 20I2, mizuna, lettuce, and radish plants were grown similarly but under flat panel banks of white LEDs. In 20 I2, the crew went through plant harvesting, including sanitizing the leafy greens and radishes, which were then consumed. Each test demonstrated successful production of vegetables within a functional hab module. The round red I blue LEDs for the 20Il test lighting cast a purple light in the hab, and were less uniformly distributed over the plant trays. The white LED panels provided broad spectrum light with more uniform distribution. Post-test questionnaires showed that the crew enjoyed tending and consuming the plants, and that the white LED light in 2012 provided welcome extra light for the main hab area.

Massa, Gioia↗
NASA NTRS2013

Plant Atrium System for Food Production in NASA's Deep Space Habitat Tests

In preparation for future human exploration missions to space, NASA evaluates habitat concepts to assess integration issues, power requirements, crew operations, technology, and system performance. The concept of a Food Production System utilizes fresh foods, such as vegetables and small fruits, harvested on a continuous basis, to improve the crew's diet and quality of life. The system would need to fit conveniently into the habitat and not interfere with other components or operations. To test this concept, a plant growing "atrium" was designed to surround the lift between the lower and upper modules of the Deep Space Habitat and deployed at NASA Desert Research and Technology Studies (DRATS) test site in 2011 and at NASA Johnson Space Center in 2012. With this approach, no-utilized volume provided an area for vegetable growth. For the 2011 test, mizuna, lettuce, basil, radish and sweetpotato plants were grown in trays using commercially available red I blue LED light fixtures. Seedlings were transplanted into the atrium and cared for by the. crew. Plants were then harvested two weeks later following completion of the test. In 2012, mizuna, lettuce, and radish plants were grown similarly but under flat panel banks of white LEDs. In 2012, the crew went through plant harvesting, including sanitizing tlie leafy greens and radishes, which were then consumed. Each test demonstrated successful production of vegetables within a functional hab module. The round red I blue LEDs for the 2011 test lighting cast a purple light in the hab, and were less uniformly distributed over the plant trays. The white LED panels provided broad spectrum light with more uniform distribution. Post-test questionnaires showed that the crew enjoyed tending and consuming the plants and that the white LED light in 2012 provided welcome extra light for the main HAB AREA.

Massa, Gioia D.↗
NASA NTRS2015

Pioneering a Biobased UAS

With the exponential growth of interest in unmanned aerial vehicles (UAVs) and their vast array of applications in both space exploration and terrestrial uses such as the delivery of medicine and monitoring the environment, the 2014 Stanford-Brown-Spelman iGEM team is pioneering the development of a fully biological UAV for scientific and humanitarian missions. The prospect of a biologically-produced UAV presents numerous advantages over the current manufacturing paradigm. First, a foundational architecture built by cells allows for construction or repair in locations where it would be difficult to bring traditional tools of production. Second, a major limitation of current research with UAVs is the size and high power consumption of analytical instruments, which require bulky electrical components and large fuselages to support their weight. By moving these functions into cells with biosensing capabilities - for example, a series of cells engineered to report GFP, green fluorescent protein, when conditions exceed a certain threshold concentration of a compound of interest, enabling their detection post-flight - these problems of scale can be avoided. To this end, we are working to engineer cells to synthesize cellulose acetate as a novel bioplastic, characterize biological methods of waterproofing the material, and program this material's systemic biodegradation. In addition, we aim to use an "amberless" system to prevent horizontal gene transfer from live cells on the material to microorganisms in the flight environment. So far, we have: successfully transformed Gluconacetobacter hansenii, a cellulose-producing bacterium, with a series of promoters to test transformation efficiency before adding the acetylation genes; isolated protein bands present in the wasp nest material; transformed the cellulose-degrading genes into Escherichia coli; and we have confirmed that the amberless construct prevents protein expression in wild-type cells. In addition, as part of our human outreach project, we have been in touch with leaders in the fields of UAVs, synthetic biology, and earth sciences, and it is clear that biodegradable UAVs could have a significant impact on the industry.

Escherichia↗
NASA NTRS2014

Towards a Biosynthetic UAV

We are currently working on a series of projects towards the construction of a fully biological unmanned aerial vehicle (UAV) for use in scientific and humanitarian missions. The prospect of a biologically-produced UAV presents numerous advantages over the current manufacturing paradigm. First, a foundational architecture built by cells allows for construction or repair in locations where it would be difficult to bring traditional tools of production. Second, a major limitation of current research with UAVs is the size and high power consumption of analytical instruments, which require bulky electrical components and large fuselages to support their weight. By moving these functions into cells with biosensing capabilities - for example, a series of cells engineered to report GFP, green fluorescent protein, when conditions exceed a certain threshold concentration of a compound of interest, enabling their detection post-flight - these problems of scale can be avoided. To this end, we are working to engineer cells to synthesize cellulose acetate as a novel bioplastic, characterize biological methods of waterproofing the material, and program this material's systemic biodegradation. In addition, we aim to use an "amberless" system to prevent horizontal gene transfer from live cells on the material to microorganisms in the flight environment.

Biological↗
NASA NTRS2015

Pioneering a Biobased UAS

With the exponential growth of interest in unmanned aerial vehicles (UAVs) and their vast array of applications in both space exploration and terrestrial uses such as the delivery of medicine and monitoring the environment, the 2014 Stanford-Brown-Spelman iGEM team is pioneering the development of a fully biological UAV for scientific and humanitarian missions. The prospect of a biologically-produced UAV presents numerous advantages over the current manufacturing paradigm. First, a foundational architecture built by cells allows for construction or repair in locations where it would be difficult to bring traditional tools of production. Second, a major limitation of current research with UAVs is the size and high power consumption of analytical instruments, which require bulky electrical components and large fuselages to support their weight. By moving these functions into cells with biosensing capabilities – for example, a series of cells engineered to report GFP, green fluorescent protein, when conditions exceed a certain threshold concentration of a compound of interest, enabling their detection post-flight – these problems of scale can be avoided. To this end, we are working to engineer cells to synthesize cellulose acetate as a novel bioplastic, characterize biological methods of waterproofing the material, and program this material’s systemic biodegradation. In addition, we aim to use an “amberless” system to prevent horizontal gene transfer from live cells on the material to microorganisms in the flight environment. So far, we have: successfully transformed Gluconacetobacter hansenii, a cellulose-producing bacterium, with a series of promoters to test transformation efficiency before adding the acetylation genes; isolated protein bands present in the wasp nest material; transformed the cellulose-degrading genes into Escherichia coli; and we have confirmed that the amberless construct prevents protein expression in wild-type cells. In addition, as part of our human outreach project, we have been in touch with leaders in the fields of UAVs, synthetic biology, and earth sciences, and it is clear that biodegradable UAVs could have a significant impact on the industry.

Escherichia↗
DOE OSTI2022

Role of defects in ultra-high gain in fast planar tin gallium oxide UV-C photodetector by MBE

Here we report ultra-high responsivity of epitaxial (Sn x Ga 1–x ) 2 O 3 (TGO) Schottky UV-C photodetectors and experimentally identified the source of gain as deep-level defects, supported by first principles calculations. Epitaxial TGO films were grown by plasma-assisted molecular beam epitaxy on (–201) oriented n-type β-Ga 2 O 3 substrates. Fabricated vertical Schottky devices exhibited peak responsivities as high as 3.5 ×10 4 A/W at –5 V applied bias under 250 nm illumination with sharp cutoff shorter than 280 nm and fast rise/fall time in milliseconds order. Hyperspectral imaging cathodoluminescence (CL) spectra were examined to find the mid-bandgap defects, the source of this high gain. Irrespective of different tin mole fractions, the TGO epilayer exhibited extra CL peaks at the green band (~2.20 eV) not seen in β-Ga 2 O 3 along with enhancement of the blue emission-band (~2.64 eV) and suppression of the UV emission-band. Based on hybrid functional calculations of the optical emission expected for defects involving Sn in β-Ga 2 O 3 , V Ga –Sn complexes are proposed as potential defect origins of the observed green and blue emission-bands. Such complexes behave as acceptors that can efficiently trap photogenerated holes and are predicted to be predominantly responsible for the ultra-high photoconductive gain in the Sn-alloyed Ga 2 O 3 devices by means of thermionic emission and electron tunneling. Regenerating the V Ga –Sn defect complexes by optimizing the growth techniques, we have demonstrated a planar Schottky UV-C photodetector of the highest peak responsivity.

36 MATERIALS SCIENCE↗
DOE OSTI2020

SpackDev: Multi-Package Development with Spack

High Energy Physics (HEP) software environments often involve ~ hundreds of external packages and libraries, and similar numbers of experiment-specific, science-critical packages—many under continuous development. Managing coherent releases of the external software stack is challenging enough, but managing the highly-collaborative—and distributed—development of a large body of code against such a stack adds even more complexity and room for error. Spack is a popular Python-based package management tool with a specific focus on the needs of High Performance Computing (HPC) systems and system administrators whose strength is orchestrating the discrete download, build, testing, and installation of pre-packaged or tagged third-party software against similarly stable dependencies. As such it is becoming increasingly popular within HEP as that community makes increasing use of HPC facilities, and as efforts to develop future HPC systems utilize Spack to provide scientific software on those platforms. SpackDev is a system to facilitate the simultaneous development of interconnected sets of packages. Intended to handle packages without restriction to one internal build system, SpackDev is integrated with Spack as a command extension in order to leverage features such as dependency calculations and build system configuration, and is generally applicable outside HEP. We describe SpackDev’s features and development over the last two years, initial experience using SpackDev in the context of the LArSoft liquid argon detector toolkit, and work remaining before it can be considered a fully-functional multi-package build system for HEP experiments utilizing Spack.

Green, Chris↗
NASA NTRS1987

User's guide to programming fault injection and data acquisition in the SIFT environment

Described are the features, command language, and functional design of the SIFT (Software Implemented Fault Tolerance) fault injection and data acquisition interface software. The document is also intended to assist and guide the SIFT user in defining, developing, and executing SIFT fault injection experiments and the subsequent collection and reduction of that fault injection data. It is also intended to be used in conjunction with the SIFT User's Guide (NASA Technical Memorandum 86289) for reference to SIFT system commands, procedures and functions, and overall guidance in SIFT system programming.

Elks, Carl R.↗
NASA NTRS1994

Radiative transfer in shrub savanna sites in Niger: Preliminary results from HAPEX-Sahel. Part 3: Optical dynamics and vegetation index sensitivity to biomass and plant cover

A shrub savannah landscape in Niger was optically characterized utilizing blue, green, red and near-infrared wavelengths. Selected vegetation indices were evaluated for their performance and sensitivity to describe the complex Sahelian soil/vegetation canopies. Bidirectional reflectance factors (BRF) of plants and soils were measured at several view angles, and used as input to various vegetation indices. Both soil and vegetation targets had strong anisotropic reflectance properties, rendering all vegetation index (6) responses to be a direct function of sun and view geometry. Soil background influences were shown to alter the response of most vegetation indices. N-space greenness had the smallest dynamic range in VI response, but the n-space brightness index provided additional useful information. The global environmental monitoring index (GEMI) showed a large 6 dynamic range for bare soils, which was undesirable for a vegetation index. The view angle response of the normalized difference vegetation index (NDVI), atmosphere resistant vegetation index (ARVI) and soil atmosphere resistant vegetation index (SARVI) were asymmetric about nadir for multiple view angles, and were, except for the SARVI, altered seriously by soil moisture and/or soil brightness effects. The soil adjusted vegetation index (SAVI) was least affected by surface soil moisture and was symmetric about nadir for grass vegetation covers. Overall the SAVI, SARVI and the n-space vegetation index performed best under all adverse conditions and were recommended to monitor vegetation growth in the sparsely vegetated Sahelian zone.

vanLeeuwen, W. J. D.↗
DOE OSTI2025

Investigation of the Cyanothece nitrogenase cluster in Synechocystis : a blueprint for engineering nitrogen-fixing photoautotrophs

ABSTRACT The nitrogenase gene cluster of unicellular diazotrophic cyanobacteria, such asCyanothece, is frequently selected by nature for nitrogen-fixing partnerships with eukaryotic phototrophs. The essential cluster components that confer an advantage in such partnerships remain underexplored. To use this cluster for the development of synthetic, phototrophic nitrogen-fixing systems, a thorough and systematic analysis of its constituent genes is necessary. An initial effort to assess the possibility of engineering this cluster into non-diazotrophic phototrophs led to the generation of aSynechocystis6803 strain with significant nitrogenase activity. In the current study, a refactoring approach was taken to determine the dispensability of the non-structural genes in the cluster and define a minimal gene set for constructing a functional nitrogenase for phototrophs. Using a bottom-up strategy, thenifgenes fromCyanothece51142 were re-organized to form new operons. The genes were then seamlessly removed to determine their essentiality in the nitrogen fixation process. We demonstrate that besides the structural genesnifHDK,nifBSUENPVZTXW, as well ashesAB, are important for optimal nitrogenase function in a phototroph. We also show that optimal expression of these genes is crucial for efficient nitrogenase activity. Our findings provide a solid foundation for generating synthetic systems that will facilitate solar-powered conversion of atmospheric nitrogen into nitrogen-rich compounds, a stride toward a greener world. IMPORTANCE Integrating nitrogen fixation genes into various photosynthetic organisms is an exciting strategy for converting atmospheric nitrogen into nitrogen-rich products in a green and energy-efficient way. In order to facilitate this process, it is essential that we understand the fundamentals of the functioning of a prokaryotic nitrogen-fixing machinery in a non-diazotrophic, photoautotrophic cell. This study examines a nitrogenase gene cluster that has been naturally selected on multiple occasions for a nitrogen-fixing partnership by eukaryotic photoautotrophs and provides a basic blueprint for designing a photosynthetic organism with nitrogen-fixing ability.

Microbiology↗
NASA NTRS1986

Lens collimation and testing using a Twyman-Green interferometer with a self-pumped phase-conjugating mirror

Ordinarily Twyman-Green interferometers are employed testing optical elements. In a modification of the basic configuration, the ordinary mirror in the test arm is replaced with a self-pumped phase-conjugating mirror using a barium titanate crystal. It is shown that, with a redefinition of components, the new configuration permits retention and improvement of the optical element testing function while simultaneously serving as a sensitive test for collimation. The optical path difference resulting from the double pass in the original Twyman-Green interferometer approximately equals that of the single pass and phase conjugation in the modification.

Howes, W. L.↗
DOE OSTI2021

Urban Forests as Main Regulator of the Evaporative Cooling Effect in Cities

Abstract Higher temperatures in urban areas expose a large fraction of the human population to potentially dangerous heat stress. Green spaces are promoted worldwide as local and city‐scale cooling strategies but the amount, type, and functioning of vegetation in cities lack quantification and their interaction with urban climate in different settings remains a matter of debate. Here we use state‐of‐the‐art remote sensing data from 145 city clusters to disentangle the drivers of surface urban heat islands (SUHI) intensity and quantify urban‐rural differences in vegetation cover, species composition, and evaporative cooling. We show that nighttime SUHIs are affected mostly by abiotic factors, while daytime SUHIs are highly correlated with vegetation characteristics and the wetness of the background climate. Magnitude and seasonality of daytime SUHIs are controlled by urban‐rural differences in plant transpiration and leaf area, which explain the dependence of SUHIs on wetness conditions. Leaf area differences are caused primarily by changes in vegetation type and a loss of in‐city forested areas, highlighting the importance of maintaining “natural reserves” as a sustainable heat mitigation policy.

Paschalis, Athanasios↗
DOE OSTI2024

Thermal stability and coalescence dynamics of exsolved metal nanoparticles at charged perovskite surfaces

Exsolution reactions enable the synthesis of oxide-supported metal nanoparticles, which are desirable as catalysts in green energy conversion technologies. It is crucial to precisely tailor the nanoparticle characteristics to optimize the catalysts’ functionality, and to maintain the catalytic performance under operation conditions. We use chemical (co)-doping to modify the defect chemistry of exsolution-active perovskite oxides and examine its influence on the mass transfer kinetics of Ni dopants towards the oxide surface and on the subsequent coalescence behavior of the exsolved nanoparticles during a continuous thermal reduction treatment. Nanoparticles that exsolve at the surface of the acceptor-type fast-oxygen-ion-conductor SrTi 0.95 Ni 0.05 O 3–δ (STNi) show a high surface mobility leading to a very low thermal stability compared to nanoparticles that exsolve at the surface of donor-type SrTi 0.9 Nb 0.05 Ni 0.05 O 3–δ (STNNi). Our analysis indicates that the low thermal stability of exsolved nanoparticles at the acceptor-doped perovskite surface is linked to a high oxygen vacancy concentration at the nanoparticle-oxide interface. For catalysts that require fast oxygen exchange kinetics, exsolution synthesis routes in dry hydrogen conditions may hence lead to accelerated degradation, while humid reaction conditions may mitigate this failure mechanism.

25 ENERGY STORAGE↗
DOE OSTI2022

Viscosity in water from first-principles and deep-neural-network simulations

Abstract We report on an extensive study of the viscosity of liquid water at near-ambient conditions, performed within the Green-Kubo theory of linear response and equilibrium ab initio molecular dynamics (AIMD), based on density-functional theory (DFT). In order to cope with the long simulation times necessary to achieve an acceptable statistical accuracy, our ab initio approach is enhanced with deep-neural-network potentials (NNP). This approach is first validated against AIMD results, obtained by using the Perdew–Burke–Ernzerhof (PBE) exchange-correlation functional and paying careful attention to crucial, yet often overlooked, aspects of the statistical data analysis. Then, we train a second NNP to a dataset generated from the Strongly Constrained and Appropriately Normed (SCAN) functional. Once the error resulting from the imperfect prediction of the melting line is offset by referring the simulated temperature to the theoretical melting one, our SCAN predictions of the shear viscosity of water are in very good agreement with experiments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗