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At least 1,765 records · Page 98

Space Shuttle Main Engine - The Relentless Pursuit of Improvement

The Space Shuttle Main Engine (SSME) is the only reusable large liquid rocket engine ever developed. The specific impulse delivered by the staged combustion cycle, substantially higher than previous rocket engines, minimized volume and weight for the integrated vehicle. The dual pre-burner configuration permitted precise mixture ratio and thrust control while the fully redundant controller and avionics provided a very high degree of system reliability and health diagnosis. The main engine controller design was the first rocket engine application to incorporate digital processing. The engine was required to operate at a high chamber pressure to minimize engine volume and weight. Power level throttling was required to minimize structural loads on the vehicle early in flight and acceleration levels on the crew late in ascent. Fatigue capability, strength, ease of assembly and disassembly, inspectability, and materials compatibility were all major considerations in achieving a fully reusable design. During the multi-decade program the design evolved substantially using a series of block upgrades. A number of materials and manufacturing challenges were encountered throughout SSME s history. Significant development was required for the final configuration of the high pressure turbopumps. Fracture control was implemented to assess life limits of critical materials and components. Survival in the hydrogen environment required assessment of hydrogen embrittlement. Instrumentation systems were a challenge due to the harsh thermal and dynamic environments within the engine. Extensive inspection procedures were developed to assess the engine components between flights. The Space Shuttle Main Engine achieved a remarkable flight performance record. All flights were successful with only one mission requiring an ascent abort condition, which still resulted in an acceptable orbit and mission. This was achieved in large part via extensive ground testing to fully characterize performance and to establish acceptable life limits. During the program over a million seconds of accumulated test and flight time was achieved. Post flight inspection and assessment was a key part of assuring proper performance of the flight hardware. By the end of the program the predicted reliability had improved by a factor of four. These unique challenges, evolution of the design, and the resulting reliability will be discussed in this paper.

VanHooser, Katherine P.↗

Helicopter Flight Test of 3-D Imaging Flash LIDAR Technology for Safe, Autonomous, and Precise Planetary Landing

Two flash lidars, integrated from a number of cutting-edge components from industry and NASA, are lab characterized and flight tested for determination of maximum operational range under the Autonomous Landing and Hazard Avoidance Technology (ALHAT) project (in its fourth development and field test cycle) which is seeking to develop a guidance, navigation, and control (GN&C) and sensing system based on lidar technology capable of enabling safe, precise crewed or robotic landings in challenging terrain on planetary bodies under any ambient lighting conditions. The flash lidars incorporate pioneering 3-D imaging cameras based on Indium-Gallium-Arsenide Avalanche Photo Diode (InGaAs APD) and novel micro-electronic technology for a 128 x 128 pixel array operating at 30 Hz, high pulse-energy 1.06 micrometer Nd:YAG lasers, and high performance transmitter and receiver fixed and zoom optics. The two flash lidars are characterized on the NASA-Langley Research Center (LaRC) Sensor Test Range, integrated with other portions of the ALHAT GN&C system from partner organizations into an instrument pod at NASA-JPL, integrated onto an Erickson Aircrane Helicopter at NASA-Dryden, and flight tested at the Edwards AFB Rogers dry lakebed over a field of human-made geometric hazards during the summer of 2010. Results show that the maximum operational range goal of 1 km is met and exceeded up to a value of 1.2 km. In addition, calibrated 3-D images of several hazards are acquired in real-time for later reconstruction into Digital Elevation Maps (DEM's).

Roback, Vincent↗

Characterization of a novel epigenetic effect of ionizing radiation: the death-inducing effect

The detrimental effects associated with exposure to ionizing radiation have long been thought to result from the direct targeting of the nucleus leading to DNA damage; however, the emergence of concepts such as radiation-induced genomic instability and bystander effects have challenged this dogma. After cellular exposure to ionizing radiation, we have isolated a number of clones of Chinese hamster-human hybrid GM10115 cells that demonstrate genomic instability as measured by chromosomal destabilization. These clones show dynamic and persistent generation of chromosomal rearrangements multiple generations after the original insult. We hypothesize that these unstable clones maintain this delayed instability phenotype by secreting factors into the culture medium. To test this hypothesis we transferred filtered medium from unstable cells to unirradiated GM10115 cells. No GM10115 cells were able to survive this medium. This phenomenon by which GM10115 cells die when cultured in medium from chromosomally unstable GM10115 clones is the death-inducing effect. Medium transfer experiments indicate that a factor or factors is/are secreted by unstable cells within 8 h of growth in fresh medium and result in cell killing within 24 h. These factors are stable at ambient temperature but do not survive heating or freezing, and are biologically active when diluted with fresh medium. We present the initial description and characterization of the death-inducing effect. This novel epigenetic effect of radiation has implications for radiation risk assessment and for health risks associated with radiation exposure.

Non-NASA Center↗

Heat Transfer Characteristics of Particle and Air Flow Through Additively Manufactured Lattice Frame Material Based on Octet-Shape Topology

Particle-to-supercritical carbon dioxide (sCO 2 ) heat exchanger is a critical component in next-generation concentrating solar power (CSP) plants. The inherently low heat transfer between falling particles and sCO 2 imposes a challenge toward economic justification of levelized cost of electricity produced through solar energy. Introduction of integrated porous media with the walls bounding particle flow has the potential to enhance the overall particle-to-sCO 2 heat exchanger performance. Here, this paper presents an experimental study on heat transfer characterization of additively manufactured lattice frame material based on Octet-shaped unit cell with particles and air as working fluids. The lattice structures were additively manufactured in stainless steel (SS) 316L and SS420 (with 40% bronze infiltration) via Binder jetting process, where the lattice porosities were varied between 0.75 and 0.9. The mean particle diameters were varied from 266 μm to 966 μm. The effective thermal conductivity and averaged heat transfer coefficient were determined through steady-state experiments. It was found that the presence of lattice enhances the effective thermal conductivity by 2–4 times when compared to packed bed of particles alone. Furthermore, for gravity-assisted particle flow through lattice panel, significantly high convective heat transfer coefficients ranging from 200 W/m2K to 400 W/m2K were obtained for the range of particle diameters tested. The superior thermal transport properties of Octet-shape-based lattice frame for particle flow makes it a very promising candidate for particle-to-sCO 2 heat exchanger for CSP application.

14 SOLAR ENERGY↗

Dual Tunability for Uncatalyzed N‐Alkylation of Primary Amines Enabled by Plasma‐Microdroplet Fusion

Abstract The fusion of non‐thermal plasma with charged microdroplets facilitates catalyst‐free N‐alkylation for a variety of primary amines, without halide salt biproduct generation. Significant reaction enhancement (up to >200×) is observed over microdroplet reactions generated from electrospray. This enhancement for the plasma‐microdroplet system is attributed to the combined effects of energetic collisions and the presence of reactive oxygen species (ROS). The ROS (e.g., O 2 ⋅ − ) act as a proton sink to increase abundance of free neutral amines in the charged microdroplet environment. The effect of ROS on N‐alkylation is confirmed through three unique experiments: (i) utilization of radical scavenging reagent, (ii) characterization of internal energy distribution, and (iii) controls performed without plasma, which lacked reaction acceleration. Establishing plasma discharge in the wake of charged microdroplets as a green synthetic methodology overcomes two major challenges within conventional gas‐phase plasma chemistry, including the lack of selectivity and product scale‐up. Both limitations are overcome here, where dual tunability is achieved by controlling reagent concentration and residence time in the microdroplet environment, affording single or double N‐alkylated products. Products are readily collected yielding milligram quantities in eight hours. These results showcase a novel synthetic strategy that represents a straightforward and sustainable C−N bond‐forming process.

Chemistry↗

Genesis of Active Pt/CeO 2 Catalyst for Dry Reforming of Methane by Reduction and Aggregation of Isolated Platinum Atoms into Clusters

Atomically dispersed metal catalysts offer the advantages of efficient metal utilization and high selectivities for reactions of technological importance. Such catalysts have been suggested to be strong candidates for dry reforming of methane (DRM), offering prospects of high selectivity for synthesis gas without coke formation, which requires ensembles of metal sites and is a challenge to overcome in DRM catalysis. However, investigations of the structures of isolated metal sites on metal oxide supports under DRM conditions are lacking, and the catalytically active sites remain undetermined. Data characterizing the DRM reaction-driven structural evolution of a cerium oxide- supported catalyst, initially incorporating atomically dispersed platinum, and the corresponding changes in catalyst performance are reported. X-ray absorption and infrared spectra show that the reduction and agglomeration of isolated cationic platinum atoms to form small platinum clusters/nanoparticles are necessary for DRM activity. Density functional theory calculations of the energy barriers for methane dissociation on atomically dispersed platinum and on platinum clusters support these observations. Here the results emphasize the need for in-operando experiments to assess the active sites in such catalysts. The inferences about the catalytically active species are suggested to pertain to a broad class of catalytic conversions involving the rate-limiting dissociation of light alkanes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Phage therapy: From biological mechanisms to future directions

Increasing antimicrobial resistance rates have revitalized bacteriophage (phage) research, the natural predators of bacteria discovered over 100 years ago. In order to use phages therapeutically, they should (1) preferably be lytic, (2) kill the bacterial host efficiently, and (3) be fully characterized to exclude side effects. Developing therapeutic phages takes a coordinated effort of multiple stakeholders. Herein, we review the state of the art in phage therapy, covering biological mechanisms, clinical applications, remaining challenges, and future directions involving naturally occurring and genetically modified or synthetic phages.

59 BASIC BIOLOGICAL SCIENCES↗

Recent progress toward catalyst properties, performance, and prediction with data-driven methods

Herein, data-driven approaches are currently renovating the field of heterogenous catalysis and open a door to advance catalyst design. Their success depends heavily on the synergy among machine learning (ML), experimental data, and quantum mechanical (QM) calculations. In this brief survey of recent progress, we examine catalysis informatics in the context of (1) ML-aided catalyst characterizations, (2) knowledge extractions from experimental data, (3) predictions of catalytic properties and constructions of reaction networks, and (4) ML-enabled large-scale QM simulations. An outlook on the current challenges of this rapidly evolving field is also provided.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A comprehensive review of diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) techniques in protonic ceramic cells (PCCs): Current status and future perspective

Protonic ceramic cells (PCCs) have emerged as a promising technology for power generation, energy storage, and value-added chemical synthesis, offering benefits such as fuel flexibility, low emissions, and efficient operation at intermediate temperatures (300–600 ​°C). Recently, significant breakthroughs in materials and manufacturing methods have markedly enhanced the performance of PCCs. However, establishing a fundamental understanding of their electrocatalytic reactions has gained less attention. As a fast and cost-effective method for physicochemical fingerprinting, diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) has proven to be a surface-sensitive analytical tool for structural and functional studies. This review critically examines the most up-to-date applications of DRIFTS for characterizing key components of PCCs, including oxygen electrodes, protonic electrolytes, and hydrogen electrodes for different applications, with a focus on revealing hydration properties and catalytic reactions, and guiding rational material design. The challenges for advancing DRIFTS, including quantitative capabilities and operando applications for PCC investigations, are highlighted and strategies to tackle these challenges are discussed. Ultimately, this review underscores the critical role of DRIFTS in accelerating the development of high-performance and durable PCCs for next-generation energy solutions, offering methodologies and insights broadly applicable to a wide range of electrochemical energy conversion and storage technologies.

Diffuse Reflectance Infrared Fourier Transform Spe↗

Challenges and opportunities in plasma-activated reactions of CO 2 with light alkanes

We present upgrading CO 2 with surplus light alkanes to value-added chemicals using one-step plasma-activated processes under mild conditions, where opportunities and challenges for improving product selectivity focus on understanding reaction pathways, decoupling and benchmarking plasma and catalyst roles in reactions, tuning catalyst structural and electronic properties under plasma activation, and developing in situ characterization techniques.

03 NATURAL GAS↗

Machine learning prediction on the fractional free volume of polymer membranes

Fractional free volume (FFV) characterizes the microstructural level features of polymers and affects their properties including thermal, mechanical, and separation performance. Experimental measurements and theoretical analyses have been used to quantify the FFV of polymers, but challenges remain because of their limitations. Experimental measurements are laborious and based on semi empirical equations, while Bondi’s group contribution theory involves ambiguities like the determination of van der Waals volume and the choice of factor values in the theoretical equation. To efficiently evaluate the FFV of polymers, this study utilizes high-throughput molecular dynamics (MD) simulations to build a large dataset regarding polymer’s FFV. Based on this large dataset, we further build machine learning (ML) models to establish the composition-structure relation. Inspired by group contribution theory which correlates polymer’s functional groups to FFV, our ML models correlate polymer’s substructures or physico-chemical indexes to FFV. Here, our study first benchmarks the MD simulation protocol to obtain reliable FFV of polymers and then carries out high-throughput MD simulations for more than 6,500 homopolymers and 1,400 polyamides. Such a large and diverse dataset makes the well-trained ML models more generalizable, compared with the group contribution theory. The efficiency of a feed forward neural network model is further demonstrated by applying it to a hypothetical polyimide dataset of more than 8 million chemical structures. The predicted FFVs of hypothetical polyimides are further validated by MD simulations. The obtained FFVs of the 8 million polymers, plus their previously reported gas separation performances, demonstrate the promising capability of ML virtual screening for the discovery of polymer membranes with exceptional permeability/selectivity.

36 MATERIALS SCIENCE↗

Self-Driving Laboratory for Polymer Electronics

Owing to the chemical pluripotency and viscoelastic nature of electronic polymers, polymer electronics have shown unique advances in many emerging applications such as skin-like electronics, large-area printed energy devices, and neuromorphic computing devices, but their development period is years-long. Recent advancements in automation, robotics, and learning algorithms have led to a growing number of self-driving (autonomous) laboratories that have begun to revolutionize the development and accelerated discovery of materials. In this perspective, we first introduce the current state of autonomous laboratories. Then we analyze why it is challenging to conduct polymer electronics research by an autonomous laboratory and highlight the needs. Here, we further discuss our efforts in building an autonomous laboratory, namely Polybot, for the automated synthesis and characterization of electronic polymers and their processing and fabrication into electronic devices. Finally, we share our vision in using a self-driving laboratory for different types of polymer electronics research.

36 MATERIALS SCIENCE↗

Using Knowledge-Guided Machine Learning To Assess Patterns of Areal Change in Waterbodies across the Contiguous United States

Lake and reservoir surface areas are an important proxy for freshwater availability. Advancements in machine learning (ML) techniques and increased accessibility of remote sensing data products have enabled the analysis of waterbody surface area dynamics on broad spatial scales. However, interpreting the ML results remains a challenge. While ML provides important tools for identifying patterns, the resultant models do not include mechanisms. Thus, the “black-box” nature of ML techniques often lacks ecological meaning. Using ML, we characterized temporal patterns in lake and reservoir surface area change from 1984 to 2016 for 103,930 waterbodies in the contiguous United States. We then employed knowledge-guided machine learning (KGML) to classify all waterbodies into seven ecologically interpretable groups representing distinct patterns of surface area change over time. Many waterbodies were classified as having “no change” (43%), whereas the remaining 57% of waterbodies fell into other groups representing both linear and nonlinear patterns. This analysis demonstrates the potential of KGML not only for identifying ecologically relevant patterns of change across time but also for unraveling complex processes that underpin those changes.

54 ENVIRONMENTAL SCIENCES↗

Leveraging Multiple Raman Excitation Wavelength Systems for Process Monitoring of Nuclear Waste Streams

Processing nuclear waste from sites such as Hanford is a significant environmental cleanup need while being a significant logistical challenge. Integration of process monitoring tools, that can provide in situ and real-time feedback about the process, can significantly alleviate needs to collect grab samples for process control and product characterization. Raman spectroscopy paired with chemometric analysis is one process monitoring tool that can provide chemical composition information on a large number of chemical targets in nuclear waste streams. However, methods to improve limits of detection as well as drop uncertainty in quantification are needed. Optimizing instrument specifications can achieve this, here this is demonstrated by comparing limits of detection for key analytes when using Raman systems with 671 nm, 532 nm, and 405 nm excitation wavelengths. Generally, limits of detection decease (allowing the measurement of lower salt concentrations) with decreasing wavelength. Similarly, data collection times and averaging were optimized. Finally, multiple chemometric modeling approaches were leveraged, including multiblock methods that combined data from all three Raman systems to simultaneously quantify targets with improved sensitivity.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Nonintuitive Surface Self-Assembly of Functionalized Molecules on Ag(111)

The fabrication of nanomaterials involves selfordering processes of functional molecules on inorganic surfaces. To obtain specific molecular arrangements, a common strategy is to equip molecules with functional groups. However, focusing on the functional groups alone does not provide a comprehensive picture. Especially at interfaces, processes that govern self-ordering are complex and involve various physical and chemical effects, often leading to unexpected structures, as we showcase here on the example of a homologous series of quinones on Ag(111). Naively, one could expect that such quinones, which all bear the same functionalization, form similar motifs. In salient contrast, our joint theoretical and experimental study shows that profoundly different structures are formed. Using a machine-learning-based structure search algorithm, we find that this is due to a shift of the balance of three antagonizing driving forces: adsorbate-substrate interactions governing adsorption sites, adsorbate-adsorbate interactions favoring close packing, and steric hindrance inhibiting certain otherwise energetically beneficial molecular arrangements. The theoretical structures show excellent agreement with our experimental characterizations of the organic/ inorganic interfaces, both for the unit cell sizes and the orientations of the molecules within. The nonintuitive interplay of similarly important interaction mechanisms will continue to be a challenging aspect for the design of functional interfaces. With a detailed examination of all driving forces, we are, however, still able to devise a design principle for self-assembly of functionalized molecules.

structure prediction↗

Recent Widespread Deceleration of Global Surface Urban Heat Islands Unveiled by Satellites

Tracking the temporal dynamics of urban heat island (UHI) is critical for urban heat adaptation and mitigation strategies. However, whether UHI trends have shifted recently and their underlying drivers remain unknown. Here we investigate the variabilities in surface UHI trends and their associated determinants in 2,104 cities worldwide from 2000 to 2022. Our findings reveal that approximately half of the world's cities have experienced notable shifts in surface UHI trends, predominantly characterized by UHI deceleration. These shifts can be primarily attributed to alterations in vegetation trends during the day and to modifications in surface albedo and local warming trends at night. Our study challenges the conventional linear models commonly employed to estimate surface UHI trends, suggesting potential biases in such estimates. Our findings underscore the need for nuanced policies to curtail UHI growth by considering changes in urban underlying surfaces and background climate, particularly from a nonlinear perspective.

54 ENVIRONMENTAL SCIENCES↗

Rapid and efficient hydrogen clathrate hydrate formation in confined nanospace

Clathrate hydrates are crystalline solids characterized by their ability to accommodate large quantities of guest molecules. Although CH 4 and CO 2 are the traditional guests found in natural systems, incorporating smaller molecules (e.g., H 2 ) is challenging due to the need to apply higher pressures to stabilize the hydrogen-bonded network. Another critical limitation of hydrates is the slow nucleation and growth kinetics. Here, we show that specially designed activated carbon materials can surpass these obstacles by acting as nanoreactors promoting the nucleation and growth of H 2 hydrates. The confinement effects in the inner cavities promote the massive growth of hydrogen hydrates at moderate temperatures, using pure water, with extremely fast kinetics and much lower pressures than the bulk system.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Rapid atom-efficient polyolefin plastics hydrogenolysis mediated by a well-defined single-site electrophilic/cationic organo-zirconium catalyst

Polyolefins comprise a major fraction of single-use plastics, yet their catalytic deconstruction/recycling has proven challenging due to their inert saturated hydrocarbon connectivities. Here a very electrophilic, formally cationic earth-abundant single-site organozirconium catalyst chemisorbed on a highly Brønsted acidic sulfated alumina support and characterized by a broad array of experimental and theoretical techniques, is shown to mediate the rapid hydrogenolytic cleavage of molecular and macromolecular saturated hydrocarbons under mild conditions, with catalytic onset as low as 90 °C/0.5 atm H 2 with 0.02 mol% catalyst loading. For polyethylene, quantitative hydrogenolysis to light hydrocarbons proceeds within 48 min with an activity of > 4000 mol(CH 2 units)·mol(Zr) –1 ·h –1 at 200 °C/2 atm H 2 pressure. Under similar solventless conditions, polyethylene-co–1-octene, isotactic polypropylene, and a post-consumer food container cap are rapidly hydrogenolyzed to low molecular mass hydrocarbons. Regarding mechanism, theory and experiment identify a turnover-limiting C-C scission pathway involving ß-alkyl transfer rather than the more common σ-bond metathesis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗