A CFD Validation Challenge for Transonic Shock-Induced Separated Flow: Experimental Characterization.
Abstract not provided.
Lynch, Kyle Patrick↗
SEARCH · Engineering Papers
Results for “characterization challenges”
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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Li-Ion Battery Thermal Characterization for Thermal Management Design
Battery design efforts often prioritize enhancing the energy density of the active materials and their utilization. However, optimizing thermal management systems at both the cell and pack levels is also key to achieving mission-relevant battery design. Battery thermal management systems, responsible for managing the thermal profile of battery cells, are crucial for balancing the trade-offs between battery performance and lifetime. Designing such systems requires accounting for the multitude of heat sources within battery cells and packs. This paper provides a summary of heat generation characterizations observed in several commercial Li-ion battery cells using isothermal battery calorimetry. The primary focus is on assessing the impact of temperatures, C-rates, and formation cycles. Moreover, a module-level characterization demonstrated the significant additional heat generated by module interconnects. Characterizing heat signatures at each level helps inform manufacturing at the design, production, and characterization phases that might otherwise go unaccounted for at the full pack level. Further testing of a 5 kWh battery pack revealed that a considerable temperature non-uniformity may arise due to inefficient cooling arrangements. To mitigate this type of challenge, a combined thermal characterization and multi-domain modeling approach is proposed, offering a solution without the need for constructing a costly module prototype.
25 ENERGY STORAGE↗
The Surface-Topography Challenge: A Multi-Laboratory Benchmark Study to Advance the Characterization of Topography
Surface performance is critically influenced by topography in virtually all real-world applications. The current standard practice is to describe topography using one of a few industry-standard parameters. The most commonly reported number is Ra, the average absolute deviation of the height from the mean line (at some, not necessarily known or specified, lateral length scale). However, other parameters, particularly those that are scale-dependent, influence surface and interfacial properties; for example the local surface slope is critical for visual appearance, friction, and wear. The present Surface-Topography Challenge was launched to raise awareness for the need of a multi-scale description, but also to assess the reliability of different metrology techniques. In the resulting international collaborative effort, 153 scientists and engineers from 64 research groups and companies across 20 countries characterized statistically equivalent samples from two different surfaces: a “rough” and a “smooth” surface. The results of the 2088 measurements constitute the most comprehensive surface description ever compiled. We find wide disagreement across measurements and techniques when the lateral scale of the measurement is ignored. Consensus is established through scale-dependent parameters while removing data that violates an established resolution criterion and deviates from the majority measurements at each length scale. Our findings suggest best practices for characterizing and specifying topography. The public release of the accumulated data and presented analyses enables global reuse for further scientific investigation and benchmarking.
42 ENGINEERING↗
Challenges of NDE Simulation Tool Challenges of NDE Simulation Tool
Realistic nondestructive evaluation (NDE) simulation tools enable inspection optimization and predictions of inspectability for new aerospace materials and designs. NDE simulation tools may someday aid in the design and certification of advanced aerospace components; potentially shortening the time from material development to implementation by industry and government. Furthermore, modeling and simulation are expected to play a significant future role in validating the capabilities and limitations of guided wave based structural health monitoring (SHM) systems. The current state-of-the-art in ultrasonic NDE/SHM simulation cannot rapidly simulate damage detection techniques for large scale, complex geometry composite components/vehicles with realistic damage types. This paper discusses some of the challenges of model development and validation for composites, such as the level of realism and scale of simulation needed for NASA' applications. Ongoing model development work is described along with examples of model validation studies. The paper will also discuss examples of the use of simulation tools at NASA to develop new damage characterization methods, and associated challenges of validating those methods.
Leckey, Cara A. C.↗
Atmospheric Variability and Measurement Uncertainty: Pitfalls in Averaging in situ Data
Satellite measurements and atmospheric models, two essential components of the integrated global observing system, provide crucial tools for monitoring and predicting regional and global foci, spanning numerous Earth Science fields. Unfortunately, models can lack the spatial and temporal resolution needed to resolve finer scale structure. Satellite measurements also have similar tempo-spatial restriction issues, but additionally can only measure certain species and can have biases that must be evaluated. Ground measurement networks are critical components of this system, by providing both independent inputs of species needed by models (including those that satellites do not provide) and assisting with investigation of biases in satellite products. Similarly, aircraft measurements play a vital role in closing the gaps between satellite measurements, model products, and ground monitoring networks by providing high accuracy, high-resolution data on local to regional spatial scales. Therefore, both ground-based and airborne observations are widely used to assess model predictions and satellite observations. One of the great challenges in using both ground and aircraft data in this fashion is matching the data temporally and spatially to the model/satellite data. A meaningful comparison with model or satellite requires a solid assessment of the variability of the in-situ measurements, which include both the instrument uncertainty and the statistical uncertainty due to atmospheric variability. While instrument uncertainty is generally more straightforwardly characterized, it can be challenging to accurately capture this variability uncertainty as it often presents in a non-Gaussian manner (e.g. emission plumes, frontal passages). We will present results examining spatial and temporal variability over a selection of scales relevant to satellite measurements and models of several in situ measurement species spanning both airborne and ground measurements. The extent of non-Gaussian variability will be quantified, and we will discuss additional statistical parameters that help assess the fitness of gaussian variability assumption when temporally or spatially averaging.
satellite validation↗
A Scalable & Non-Destructive Characterization Strategy to Study Semiconductor/Dielectric Interfaces and Predict Wafer-Level Device Performance
The defect density present at the dielectric-semiconductor interface in an MOS structure directly influences the channel carrier characteristics in semiconductor devices, especially in wide bandgap material systems used in power devices. While these trap defects are typically quantified through electrical characterization of MOS-capacitor test structures, this treatment offers very little insight into the physical nature of interface defects. Such shortcomings demand a physical characterization strategy to guide fabrication optimization. X-ray photoelectron spectroscopy (XPS) is suggested as a viable technique to determine chemical data for dielectric interfaces formed using atomic layer deposition (ALD) on GaN substrates. Previously, 1-D XPS characterization has confirmed the presence of a Ga x O y interlayer between ALD dielectrics and the GaN substrate. In this work, XPS data is serially collected to form 2-D images of an ALD-Al 2 O 3 /GaN interface as a proof-of-concept experiment for in-situ XPS quality monitoring during ALD processing. The information provided by this work reveals some of the challenges for incorporating XPS characterization as an in-situ strategy during fabrication of GaN-based devices. Separately, electrical mapping of a 2-D array of ALD-Al 2 O 3 /GaN MOS-capacitor devices provide a means to quantify the spatial variations in interface quality across a single wafer. Physical characterization techniques, such as time-of-flight secondary ion mass spectroscopy, provide additional chemical information about the Al 2 O 3 /Ga x O y /GaN structure that complement the electrical mapping results. This analysis shows that a higher Ga x O y content correlates with higher interface state defects for trap energies deep in the band gap.
42 ENGINEERING↗
Biomolecular condensates form spatially inhomogeneous network fluids
The functions of biomolecular condensates are thought to be influenced by their material properties, and these will be determined by the internal organization of molecules within condensates. However, structural characterizations of condensates are challenging, and rarely reported. Here, we deploy a combination of small angle neutron scattering, fluorescence recovery after photobleaching, and coarse-grained molecular dynamics simulations to provide structural descriptions of model condensates that are formed by macromolecules from nucleolar granular components (GCs). We show that these minimal facsimiles of GCs form condensates that are network fluids featuring spatial inhomogeneities across different length scales that reflect the contributions of distinct protein and peptide domains. The network-like inhomogeneous organization is characterized by a coexistence of liquid- and gas-like macromolecular densities that engenders bimodality of internal molecular dynamics. These insights suggest that condensates formed by multivalent proteins share features with network fluids formed by systems such as patchy or hairy colloids.
59 BASIC BIOLOGICAL SCIENCES↗
Synthesis and structural characterization of copper–cuprizone complexes
The chemistry of copper with cuprizone has challenged chemists for over 70 years. We characterize the classical ‘blue’ product, containing Cu( iii ) and hydrolyzed cuprizone, and a green multimeric Cu( ii ) product, containing unhydrolyzed cuprizone.
Chemistry↗
Modem Characterization Through a Wideband, Hard-Limited Ka-Band Satellite Channel
NASA is using a commercial customized TDMA/FDMA bandwidth on demand modem for use with the Advanced Communications Technology Satellite (ACTS) to highlight the numerous services and experiments that can be performed using small Ka-Band terminals. Characterizing the modems proved challenging due to the characteristics of the satellite transponder. The ACTS channel is hard-limited and up to 900 MHz wide. The channel has some unusual dynamic properties due to the satellite and antenna system, which make modem testing through the satellite challenging and the test requirements stringent. The satellite Multi-Beam Antenna (MBA) has a 1 hertz oscillation induced by the momentum wheel, which causes the transmit antenna pattern to move slightly. This results in a 1 hertz oscillation in the ground station receive power, with amplitude changes up to 1 dB depending on terminal location within a spot beam and associated gain slope. In addition, ACTS experiences a solar induced "thermal event" each day. This "thermal event" occurs when the sun heats the antenna support structure causing the transmit and receive reflectors to mispoint. This results in a slowly decreasing or increasing power density at the ground station receiver as the antenna pattern moves off bore-site. This paper describes the method used to fully characterize the TDMA/FDMA modem through the ACTS wideband, hard-limited transponder. In particular, techniques are discussed for conducting RF measurements on such a channel, the affect that the thermal characteristics and 1 hertz variations have on the accuracy of the results, and suggested means to minimize the error and provide useful and valuable data.
Reinhart, Richard C.↗
From Chaos to Clarity: Autonomous Materials Discovery for Extreme Environments [Slides]
The pursuit of advanced functional materials for energy applications demands an understanding of their behavior under the most challenging conditions. Extreme environments, characterized by intense radiation, high temperatures, and corrosive chemistries, push materials to their limits, often revealing unexpected behaviors and degradation pathways. Traditional materials research approaches, relying on trial-and-error experimentation, are often slow and resource-intensive, ill-suited to the complexities of extreme environments. This talk will explore the transformative potential of autonomous materials science in revolutionizing our understanding of materials synthesis and degradation in extreme environments. By integrating advanced microscopy techniques, artificial intelligence, and robotic experimentation, we can accelerate the discovery and design of resilient materials for a sustainable future. The presentation will highlight recent breakthroughs in autonomous microscopy, computer vision, and machine learning, showcasing their ability to unravel complex material transformations at the atomic scale. The talk will also delve into the challenges and opportunities associated with deploying autonomous systems to probe extreme environments, emphasizing the importance of robust algorithms, real-time data analysis, and adaptive experimentation. The ultimate goal is to empower scientists with unprecedented capabilities to explore, understand, and engineer materials that can withstand the harshest conditions, paving the way for innovations in energy, aerospace, and beyond.
14 SOLAR ENERGY↗
From Chaos to Clarity: Autonomous Materials Discovery for Extreme Environments
The pursuit of advanced functional materials for energy applications demands an understanding of their behavior under the most challenging conditions. Extreme environments, characterized by intense radiation, high temperatures, and corrosive chemistries, push materials to their limits, often revealing unexpected behaviors and degradation pathways. Traditional materials research approaches, relying on trial-and-error experimentation, are often slow and resource-intensive, ill-suited to the complexities of extreme environments. This talk will explore the transformative potential of autonomous materials science in revolutionizing our understanding of materials synthesis and degradation in extreme environments. By integrating advanced microscopy techniques, artificial intelligence, and robotic experimentation, we can accelerate the discovery and design of resilient materials for a sustainable future. The presentation will highlight recent breakthroughs in autonomous microscopy, computer vision, and machine learning, showcasing their ability to unravel complex material transformations at the atomic scale. The talk will also delve into the challenges and opportunities associated with deploying autonomous systems to probe extreme environments, emphasizing the importance of robust algorithms, real-time data analysis, and adaptive experimentation. Our ultimate goal is to empower scientists with unprecedented capabilities to explore, understand, and engineer materials that can withstand the harshest conditions, paving the way for innovations in energy, aerospace, and beyond.
artificial intelligence↗
Predicting receptor-ligand pairing preferences in plant-microbe interfaces via molecular dynamics and machine learning
Microbiome assembly, structure, and dynamics significantly influence plant health. Secreted microbial signaling molecules initiate and mediate symbiosis by binding to structurally compatible plant receptors. For example, lipo-chitooligosaccharides (LCOs), produced by nitrogen-fixing rhizobial bacteria and various fungi, are recognized by plant lysin motif receptor-like kinases (LysM-RLKs), which activate the common symbiotic pathway. Accurately predicting these molecular interactions could reveal complementary signatures underlying the initial stages of endosymbiosis. Despite the breakthrough in protein-ligand structure prediction with deep learning-based tools, such as AlphaFold3, the large size and highly flexible nature of signaling compounds like LCOs present major challenges for detailed structural characterization and binding-affinity prediction. Typical structure-/physics-based methods of ligand virtual screening are designed for small, drug-like molecules, often rely on high-resolution, experimentally determined structures of the protein receptors, and rarely achieve sufficient sampling to obtain converged thermodynamic quantities with large ligands. In this study, we developed a hybrid molecular dynamics/machine learning (MD/ML) approach capable of predicting binding affinity rankings with high accuracy in systems involving large, flexible ligands, despite limited experimental structural information. Using coarse initial structural models, the predictions using the MD/ML workflow achieved strong alignment with experimental trends, particularly in the top-affinity tier for four legume LysM-RLKs (LYR3) binding to LCOs and a chitooligosaccharide. Furthermore, the MD-based conformation selection protocol provided critical structural insights into substrate specificity and binding mechanisms. This study demonstrates a powerful method to screen for challenging cognate ligand-receptors and advance our understanding of the molecular basis of microbial colonization in plants.
Lipo-chitooligosaccharides↗
Human Systems Integration Relationships Between Deep Space and Deepwater Exploration Challenges
NASA pursuit of human missions Beyond Earth Orbit (BEO) to the moon and eventually Mars will pose many new challenges. These missions are characterized by increased risks to human performance due to stress, fatigue, radiation exposure, and isolation. Fundamental changes in spaceflight operations will be required as well. A very critical part of future missions will be assisting the crew with problem-solving and contingency resolution using next-generation smart spacecraft systems. Human Systems Integration (HSI) must be included as part of the systems engineering process. Gateway1 will serve as part of the proving ground for maturing technology such as autonomous systems and space operations procedures to help meet moon mission goals and prepare humans for missions to Mars. For deep space missions, risk factors affecting humans such as mission duration, distance, and physiological/psychological effects, must be considered. A human is not a simple component but rather a system in a systems-of-systems application-a system influenced by cognitive and biological factors that are difficult to model/analyze. System complexity will demand an integrated approach that requires multiple viewpoints, including the understanding of the astronauts' capabilities and limitations to enhance safety, performance, and satisfaction on the interaction between all system users in a variety of environments to achieve acceptable mission goals and performance. HSI will play a vital role in the development of these future missions. This paper provides a discussion of HSI used at NASA and the critical role human factors engineering will play in the HSI process for future missions along with the challenges. Industries such as oil and gas (O&G) could benefit from the content of this paper to help improve the safety and operations of deepwater/oil and gas exploration activities. NASA engineering and human systems subject-matter expert personnel reviewed challenges reported in space-related environments for long space duration missions and identified similarities with the challenges encountered in deepwater exploration. The researchers noted the space industry's current solutions and proposed a system development view to solve future deepwater exploration challenges using HSI principles. This paper discusses the results of the review.
George Salazar↗
Mapping Conductance and Switching Behavior of Graphene Devices In Situ
Graphene is proposed for use in various nanodevice designs, many of which harness emergent quantum properties for device functionality. However, visualization, measurement, and manipulation become nontrivial at nanometer and atomic scales, representing a significant challenge for device fabrication, characterization, and optimization at length scales where quantum effects emerge. Herein, proof of principle results at the crossroads between 2D nanoelectronic devices, e-beam-induced modulation, and imaging with secondary electron e-beam induced currents (SEEBIC) is presented. A device platform compatible with scanning transmission electron microscopy investigations is introduced. Then how the SEEBIC imaging technique can be used to visualize conductance and connectivity in single layer graphene nanodevices, even while supported on a thicker substrate (conditions under which conventional imaging fails) is shown. Finally, it is shown that the SEEBIC imaging technique can detect subtle differences in charge transport through time in nonohmic graphene nanoconstrictions indicating the potential to reveal dynamic electronic processes.
36 MATERIALS SCIENCE↗
Implementation of Ion Mobility Spectrometry-Based Separations in Structures for Lossless Ion Manipulations (SLIM)
Structures for Lossless Ion Manipulations (SLIM) is a powerful variant of traveling wave ion mobility spectrometry (TW-IMS) that uses a serpentine pattern of microelectrodes deposited onto printed circuit boards to achieve ultralong ion path lengths (13.5 m). Ions are propelled through SLIM platforms via arrays of TW electrodes while RF and DC electrodes provide radial confinement, establishing near lossless transmission. The recent ability to cycle ions multiple times through a SLIM has allowed ion path lengths to exceed 1000 m, providing unprecedented separation power and the ability to observe ion structural conformations unobtainable with other IMS technologies. The combination of high separation power, high signal intensity, and the ability to couple with mass spectrometry places SLIM in the unique position of being able to address longstanding proteomics and metabolomics challenges by allowing the characterization of isomeric mixtures containing low abundance analytes.
Hollerbach, Adam L.↗
Assessing factors that determine adatom migration and clustering on a thin film oxide; Pt 1 and Rh 1 on the “29” Cu x O/Cu(1 1 1) surface
The dynamical nature of single-site catalysts under non-equilibrium conditions poses significant challenges in the full characterization of their active sites. The “29” oxide is a thin Cu x O film grown on Cu(111) which provides a well-defined surface on which to study the structure and chemistry of atomically dispersed precious metals. A combination of experimental and first-principles approaches is used to investigate the factors that influence the mobility of metal adatoms and their clustering tendencies. Our work elucidates how a homogenous coordination environment of neutral single-atoms can be obtained when its tendency to break oxide bonds within its vicinity is low. Herein we demonstrate that this in turn affects the chemical atomically dispersed species on thin-film oxides, as defects on the oxide would in fact allow such species to be more accessible to CO. We thus highlight the importance of understanding the relationship between defects and atomically dispersed active sites upon designing single-site catalysts.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Resolving protein-mineral interfacial interactions during in vitro mineralization by atom probe tomography
Organic macromolecules exert remarkable control over the nucleation and growth of inorganic crystallites during (bio)mineralization, as exemplified during enamel formation where the protein amelogenin regulates the formation of hydroxyapatite (HAP). However, it is poorly understood how fundamental processes at the organic-inorganic interface, such as protein adsorption and/or incorporation into minerals, regulates nucleation and crystal growth due to technical challenges in observing and characterizing mineral-bound organics at high-resolution. Here, atom probe tomography techniques were developed and applied to characterize amelogenin-mineralized HAP particles in vitro, revealing distinct organic-inorganic interfacial structures and processes at the nanoscale. Specifically, visualization of amelogenin across the mineralized particulate demonstrates protein can become entrapped during HAP crystal aggregation and fusion. Identification of protein signatures and structural interpretations were further supported by standards analyses, i.e., defined HAP surfaces with and without amelogenin adsorbed. These findings represent a significant advance in the characterization of interfacial structures and, more so, interpretation of fundamental organic-inorganic processes and mechanisms influencing crystal growth. Ultimately, this approach can be broadly applied to inform how potentially unique and diverse organic-inorganic interactions at different stages regulates the growth and evolution of various biominerals.
36 MATERIALS SCIENCE↗
Modeling hyperbranched polymer formation via ATRP using dissipative particle dynamics
Hyperbranched polymers (HBPs) offer distinguishing, advantageous properties that arise from their distinctive complex topology. One of the effective approaches to the synthesis of hyperbranched structures involves the use of a branching initiator (inibramer) that is activated only after incorporation into a polymer chain. There remain, however, challenges in determining and characterizing the structures of the synthesized HBPs. Dissipative particle dynamics (DPD) was used to probe the effects of inibramer concentration, solvent concentration, and inibramer reactivity on the kinetics, molecular weight, and dispersity of HBPs. Additionally, DPD allows for direct observation of branched structures, which was not possible in previously reported Monte Carlo type simulations. It was found that higher inibramer concentrations led to faster monomer consumption while forming more dendritic structures with fewer defects. Additionally, high dispersities characteristic of HBP systems were found to originate from asymmetric propagation rates between inibramer-inibramer and inibramer-monomer reactions.
Biswas, Santidan↗