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At least 163 records · Page 9

Vectorization of Dynamic Subgraphs via Generative Models (Final Report)

An important class of data analysis tasks stem from comparing subsets of connected records within massive sets of complex relational data. A common approach is to represent each set of connected records with a small graph, or set of data entities (graph vertices) and their relationships (graph edges), and efficient methods to gauge similarity for pairs of graphs are of high interest. This project concentrated on dynamic graphs, where each edge record has an associated timestamp denoting the time of observation. Pre-existing techniques for comparing dynamic graphs concentrate on either computing graph edit distance (number of vertex and edge deletion, addition, and timestamp modifications) or vectorizing the graph with counts of a limited set of dynamic graph motifs (tiny fundamental subgraphs) and computing distances between the vectors. These approaches are less able to see similarities in graphs that are fairly different in size but come from identical graph generation processes. The motif counting approach can be improved for graphs from the same process, but suffers from requiring many types of motifs meaning it is expensive. Moreover, many motifs are not present for small graphs, meaning realizing a a much larger graph came from the same process is difficult.

97 MATHEMATICS AND COMPUTING↗

Engineering approach to the prediction of shock patterns in bounded high-speed flows

A two-dimensional symmetric wedge configuration representative of a single high-speed intake in steady flow was investigated. The analysis presented here is intended as an engineering approach for estimating certain features of the internal shock system. The primary interest here is the prediction of the size and location of the almost-normal shock wave that develops when the leading-edge shocks intersect at angles above a certain critical value that is less than the wedge detachment angle. The almost-normal shock wave is frequently referred to as the 'Mach stem', Parametric studies enabled the sensitivity of the Mach stem height to various flowfield parameters to be examined, thus indicating how accurately these parameters must be measured in a given experiment. Results of these predictions were compared with those of a steady-flow experiment performed at nominal freestream Mach numbers from 2.8 to 5. The predicted stem heights were consistently lower than the mean experimental values, attributable both to experimental uncertainties and to certain simplifying assumptions used in the analysis. Modification of these assumptions to better represent the test environment improved the analytical results.

Azevedo, D. J.↗

Stochastic multiscale modeling for quantifying statistical and model errors with application to composite materials

This paper provides a coherent and efficient computational framework for stochastic multiscale analysis of material systems in the presence of parametric uncertainties and modeling errors. Uncertainty in those model parameters that are not deduced as upscaled quantities is attributed to an uncertainty “germ”. While such parameters can appear at any scale, they are predominant at the finest analysis scale. Additional uncertainties stemming from statistical estimation, attributed to lack of data and model error, are associated with each submodel contributing to the multiscale system. Here, a robust and efficient framework based on a generalized extended polynomial chaos expansion (gEPCE) is proposed to simultaneously propagate all these uncertainties in order to provide a probabilistic representation of specific quantities of interest (QoI). We characterize the full probability distribution of the QoI and the uncertainty in the failure probability pertaining to its tails. By combining gEPCE with kernel density estimation (KDE) and directional derivatives, we construct sensitivity measures that connect these statistical metrics of QoI to the various sources of uncertainty to assess their individual and combined impacts. An illustrative problem featuring three-point bending of a composite beam is investigated to demonstrate the presented approach.

36 MATERIALS SCIENCE↗

Large-eddy simulation of flow through a plane, asymmetric diffuser

A challenge for traditional turbulence modeling, based on the Reynolds averaged Navier-Stokes equations, remains the accurate prediction of 'mild', adverse pressure-gradient driven separation from a smooth surface. With this study we want to explore the capability of large-eddy simulation to predict the separation which occurs on the deflected wall of an asymmetric, plane diffuser with opening angle of 10 deg. The flow through the plane diffuser exhibits some additional interesting physical phenomena which make it a challenging test case. In addition to 'mild' separation about halfway down the deflected ramp, the flow is characterized by a small backflow zone with stalled fluid in the rear part of the expanding section. The turbulent flow entering the diffuser is subject to combined adverse and radial pressure gradients stemming from the convex curvature. Finally the flow recovers into a developed, turbulent channel flow in the outlet section. Obi et al. provide measurements of mean flow, Reynolds stresses, and pressure recovery, which were obtained by means of LDV in a wind tunnel. The objective of this study is to investigate whether LES with the standard dynamic model is able to accurately predict the flow in the one-sided diffuser and to explore the resolution requirements and associated costs.

Kaltenbach, Hans-Jakob↗

Sentiment analysis of the United States public support of nuclear power on social media using large language models

This study utilized large language models (LLMs) to analyze public sentiment in the United States (US) regarding nuclear power on social media, focusing on X/Twitter, considering climate change challenges and advancements in nuclear power technology. Approximately, 1.26 million nuclear tweets from 2008–2023 were examined to fine-tune LLMs for sentiment classification. We found the crucial role of accurate data labeling for model performance, with potential implications for a 15% improvement, achieved through high-confidence labels. LLMs demonstrated better performance compared to traditional machine learning classifiers, with reduced susceptibility to overfitting and up to 96% classification accuracy. LLMs are used to segment the US public tweets into policy and energy-related categories, revealing that 68% are politically themed. Policy tweets tended to convey negative sentiment, often reflecting opposing political perspectives and focusing on nuclear deals and international relations. Energy-related tweets covered diverse topics with predominantly neutral to positive sentiment, indicating broad support for nuclear power in 48 out of 50 US states. The US public positive sentiments toward nuclear power stemmed from its high power density, reliability regardless of weather conditions, environmental benefits, application versatility, and recent innovations and advancements in both fission and fusion technologies. Negative sentiments primarily focused on waste management, high capital costs, and safety concerns. The neutral campaign highlighted global nuclear facts and advancements, with varying tones leaning towards positivity or negativity. An interesting neutral theme was the advocacy for the combined use of renewable and nuclear energy to attain net-zero goals.

Energy & Fuels↗

Vacancy-induced suppression of charge density wave order and its impact on magnetic order in kagome antiferromagnet FeGe

Two-dimensional (2D) kagome lattice metals are interesting because their corner sharing triangle structure enables a wide array of electronic and magnetic phenomena. Recently, post-growth annealing is shown to both suppress charge density wave (CDW) order and establish long-range CDW with the ability to cycle between states repeatedly in the kagome antiferromagnet FeGe. Here we perform transport, neutron scattering, scanning transmission electron microscopy (STEM), and muon spin rotation (μSR) experiments to unveil the microscopic mechanism of the annealing process and its impact on magneto-transport, CDW, and magnetism in FeGe. Annealing at 560 °C creates uniformly distributed Ge vacancies, preventing the formation of Ge-Ge dimers and thus CDW, while 320 °C annealing concentrates vacancies into stoichiometric FeGe regions with long-range CDW. The presence of CDW order greatly affects the anomalous Hall effect, incommensurate magnetic order, and spin-lattice coupling in FeGe, placing FeGe as the only kagome lattice material with tunable CDW and magnetic order.

critical phenomena↗

Direct Characterization of Atomically Dispersed Catalysts: Nitrogen-Coordinated Ni Sites in Carbon-Based Materials for CO 2 Electroreduction

Metal, nitrogen-doped carbon materials have attracted interest as heterogenous catalysts that contain MN x active sites that are analogous to molecular catalysts. Of particular interest is Ni,N-doped carbon, a catalyst that is active for the electrochemical reduction of CO 2 to CO. Critical to the understanding of these materials is proof of single atomic sites and characterization of the environment surrounding the metal atom; however, directly probing this coordination remains challenging. This challenge is addressed in this study by combining scanning transmission electron microscopy (STEM), single atom electron energy loss spectroscopy (EELS), and time-of-flight secondary ion mass spectrometry (ToF-SIMS). Through STEM imaging, atomic dispersion of Ni in the carbon framework is confirmed and image analyses are utilized to give semiquantitative estimates of neighbor distance distributions and site densities of Ni atoms. Atomic resolution EELS demonstrates that N and Ni are colocated at the single Ni atom sites suggesting Ni–N coordination. ToF-SIMS reveals a distribution of NiN x C y - fragments that reflect the Ni–N bonding environments within Ni,N-doped carbon. The fragmentation from Ni,N-doped carbon is similar to Ni phthalocyanine, suggesting the existence of heterogenized, molecular-like NiN 4 active sites which motivates future studies that leverage insight from molecular catalysis design to develop next-generation heterogeneous catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Pumped Storage Hydropower (PSH) FAST Commissioning Prize Technical Analysis

The US energy landscape has undergone major changes over the past 10 years and will continue to see significant changes in future decades as the power grid increases its reliance on variable renewable energy resources. Because of the inherent variability of these resources, renewable energy growth may require additional energy storage capacity to provide flexible load-following capabilities and other grid services that can quickly adjust to changes in energy demand and generation. Pumped storage hydropower (PSH)—one such energy storage technology—uses pumps to convey water from a lower reservoir to an upper reservoir for energy storage and releases water back to the lower reservoir via a powerhouse for hydropower generation. PSH facility pump and generation cycling often follows economic and energy demand conditions. Across the United States, 43 PSH facilities are in operation and 55 projects are in various permitting or licensing stages. Altogether, the 43 operational projects provide the wide majority (95%) of utility-scale electricity storage in the United States. These facilities also provide significant power and nonpower grid benefits, including large-scale electrical system reserve capacity, grid reliability support, and electricity supply-demand balancing through quick-response capabilities and operational flexibility. PSH systems can accomplish these at a scale (e.g., size) and cost that makes these systems highly attractive from a technical standpoint. Although these research concepts are still in their infancy, they demonstrate promising potential as future PSH energy storage technologies. Although PSH has many advantages, development in the United States has effectively stalled since the 1990s, partially because of the magnitude of project costs and financing interest during development and construction, the length of time from project investment until project revenue begins, permitting challenges, construction risks, competition from other storage technologies (e.g., batteries, hydrogen storage), and electricity market evolution and uncertainty. In short, the time, cost, and risk associated with modern PSH development have resulted in limited growth in the United States recently, despite the growing energy storage demand stemming from increased wind and solar power deployment. Technology innovation is needed to help reduce PSH commissioning time, cost, and risk, particularly during the post-licensing phase of project development. To address challenges facing the PSH industry and to improve PSH commissioning timelines, the US Department of Energy (DOE) Water Power Technologies Office (WPTO) initiated the PSH Furthering Advancements to Shorten Time to (FAST) Commissioning Prize project.

13 HYDRO ENERGY↗

Multifrequency observations of dwarf novae outbursts

Studies using EXOSAT and IUE data combined with ground-based optical and IR photometry, spectroscopy and polarimetry of the transition timescales and physical properties of the high accretion rate states of the disks in cataclysmic variables are discussed. Implications for dwarf novae stem from comparison of the timing and amplitude of the optical and IR rise with that of the UV and X-ray; the development of the optical and UV line profile changes as the outburst develops; and the similarity of the outburst flux distributions in different systems and different types of outbursts (standstills and supermaxima). These features of dwarf novae outbursts present interesting comparisons with the outbursts of systems like TV Col and GK Per.

Szkody, P.↗

Looking around: 35 years of oculomotor modeling

Eye movements have attracted an unusually large number of researchers from many disparate fields, especially over the past 35 years. The lure of this system stemmed from its apparent simplicity of description, measurement, and analysis, as well as the promise of providing a "window in the mind." Investigators in areas ranging from biological control systems and neurological diagnosis to applications in advertising and flight simulation expected eye movements to provide clear indicators of what the sensory-motor system was accomplishing and what the brain found to be of interest. The parallels between compensatory eye movements and perception of spatial orientation have been a subject for active study in visual-vestibular interaction, where substantial knowledge has accumulated through experiments largely guided by the challenge of proving or disproving model predictions. Even though oculomotor control has arguably benefited more from systems theory than any other branch of motor control, many of the original goals remain largely unfulfilled. This paper considers some of the promising potential benefits of eye movement research and compares accomplishments with anticipated results. Four topics are considered in greater detail: (i) the definition of oculomotor system input and output, (ii) optimization of the eye movement system, (iii) the relationship between compensatory eye movements and spatial orientation through the "internal model," and (iv) the significance of eye movements as measured in (outer) space.

Flight Experiment↗

NASA MUREP-DEAP Institutes - Year 1 Updates on Capacity Building, Community Building and Research Initiatives

Through the Minority University Research and Education Project (MUREP), NASA engages underrepresented populations via various initiatives, including by means of three year competitive awards for Data Science Equity, Access, and Priority in Research and Education (DEAP) Institutes led by Historically Black Colleges and Universities (HBCUs). MUREP DEAP Institutes, multi-institutional consortia, conduct data science research and capacity building initiatives that aim to enhance the research, academic, and technological capabilities of the participating HBCUs while providing NASA-specific knowledge, skills and opportunities for students and faculty who have historically been underrepresented and underserved in the STEM workforce. Three MUREP DEAP Institutes, led by Bethune-Cookman University, North Carolina A&T University, and North Carolina Central University, are conducting data science and natural hazard related research utilizing remote sensing and earth observations, with mentorship for the Institutes provided by scientists from NASA’s Marshall Space Flight Center. Each Institute has unique capabilities, needs, and goals, but overlap in their common interest to conduct cutting edge data science and natural hazard related research and to build capacity, broaden participation, and increase retention of a diverse group of participating students and faculty​. Here, successes and challenges from the first year of activities at each MUREP DEAP institute are discussed, where activities focused primarily on the recruitment of a diverse group of students and the upskilling of students and faculty in data science and remote sensing concepts. The planned activities and goals of each DEAP Institute for the upcoming two years of activities will also be discussed, both from research and community-building perspectives.

Ronan Lucey↗

RELAP5-3D Modeling in the OECD-NEA HTTF Benchmark

Prismatic gas-cooled reactors are a technologically mature reactor concept of interest for near- to mid-term deployment. To accelerate the deployment of these reactors, the DOE's Advanced Reactor Technologies Gas-Cooled Reactor campaign is spearheading a thermal hydraulics code validation benchmark based on the High Temperature Test Facility at Oregon State University. This presentation provides an introduction to that benchmark and an overview of some of the RELAP5-3D validation activities stemming from that benchmark.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Carbon Isotope Characterization of Organic Intermediaries in Hydrothermal Hydrocarbon Synthesis by Pyrolysis-GC-MS-C-IRMS

We report results of experiments designed to characterize the carbon isotope composition of intermediate organic compounds produced as a result of mineral surface catalyzed reactions. The impetus for this work stems from recently reported detection of methane in the Martian atmosphere coupled with evidence showing extensive water-rock interaction during Martian history. Abiotic formation by Fischer-Tropsch-type (FTT) synthesis during serpentinization reactions may be one possible process responsible for methane generation on Mars, and measurement of carbon and hydrogen isotopes of intermediary organic compounds can help constrain the origin of this methane. Of particular interest within the context of this work is the isotopic composition of organic intermediaries produced on the surfaces of mineral catalysts (i.e. magnetite) during hydrothermal experiments, and the ability to make meaningful and reproducible isotope measurements. Our isotope measurements utilize a unique analytical technique combining Pyrolysis-Gas Chromatograph-Mass Spectrometry-Combustion-Isotope Ratio Mass Specrometry (Py-GC-MS-C-IRMS). Others have conducted similar pyrolysis-IRMS experiments on low molecular weight organic acids (Dias, et al, Organic Geochemistry, 33 [2002]). Our technique differs in that it carries a split of the pyrolyzed GC-separated product to a Thermo DSQ-II quadrupole mass spectrometer as a means of making qualitative and semi-quantitative compositional measurements of the organic compounds. A sample of carboxylic acid (mixture of C1 through C6) was pyrolyzed at 100 XC and passed through the GC-MS-C-IRMS (combusted at 940 XC). In order to test the reliability of our technique we compared the _13C composition of different molecular weight organic acids (from C1 through C6) extracted individually by the traditional sealed-tube cupric oxide combustion (940 XC) method with the _13C produced by our pyrolysis technique. Our data indicate that an average 4.3. +/-0.5. (V-PDB) apparent isotopic fractionation accompanies the pyrolysis extractions. We postulate that this isotope offset could be the result of incomplete thermal desorption during pyrolysis. We are continuing to investigate the reliability of this pyrolysis technique for correcting carbon isotope measurements of mineral surface catalyzed organic compounds.

Socki, Richard A.↗

2D-EFICACY: Control of Metastable 2D Carbide[1]Chalcogenide Heterolayers: Strain and Moire Engineering

The experimental isolation of graphene led to the discovery of an entirely new world of two-dimensional (2D) materials in which the 2D nature often leads to emergent behaviors not seen in bulk systems. 2D transition metal dichalcogenides (TMDs) exhibit physico-chemical properties that depend on the transition metal, polymorph, thickness, and presence and type of defects. Recently, a group of thin (10-100nm) transition metal carbides (TMCs), such as Mo2C, has been synthesized that exhibit a thickness-dependent superconducting critical temperature (Tc). These thin TMCs are different from MXenes, another class of 2D materials consisting of few layers of nitrides or carbides (<5nm) produced by chemical etching and delamination. The goal of this renewal proposal is to combine experiment and computation to synthesize and elucidate the guiding principles that control the growth, orientation and strain of heterostacks of thin TMCs and TMDs composed with Nb, Ti and W. We expect to stabilize metastable hybrid phases of TMCs sandwiched between TMDs (H-TMD/Cs) with unprecedented physico-chemical properties. As part of previous DOE-funded work by the Terrones/Sinnott groups, thin (10-100 nm thick) Mo2C flakes were successfully synthesized by chemical vapor deposition (CVD). By subsequently exposing Mo2C to H2S, partial chalcogenization was achieved, resulting in heterostacks of MoCx phases and MoS2. The formation of MoS2 led to a deficiency of Mo atoms in the underlying Mo2C, resulting in an inhomogeneous phase change from α-Mo2C to γ’-MoCx and then to γ-MoC. The γ’-MoCx is a strained metastable phase and the heterostack of all three phases demonstrated an increased Tc relative to that of α-Mo2C, from 4 to 6K; its interleaved layered structure consisting of superconducting and semiconducting phases is ideal for future studies of Josephson junction series arrays. Moiré patterns in these heterostacked systems could result in new phenomena, as moiré patterns in bilayer graphene showed unconventional superconductivity and moiré excitons have been observed in twisted TMD heterobilayers. The scientific hypothesis of the proposed synergistic computational and experimental research is that orientation and strain control within confined thin metastable TMCs, sandwiched by stable phases of TMCs and layered TMDs, will depend on kinetic and thermodynamic “knobs” that include fast temperature changes, chalcogen diffusion through preferred crystallographic planes, reaction times, pressure, reactive atmosphere, precursors, and surfactants, which will also tailor properties such as superconductivity, magnetism, ferroelectricity, piezoelectricity, and catalytic performance. We will develop the guiding principles for the synthesis and stabilization of metastable H-TMD/Cs based on Nb, Ti and W. In order to validate the hypothesis, four tasks are proposed: The first task will synthesize ultra-thin TMCs based on Nb, W and Ti, by: 1) adapting the CVD method used for Mo2C, 2) plasma assisted CVD, 3) defect-mediated CVD processes, and 4) cryo-milling of carbide powders. The second task will accomplish the synthesis and basic physico-chemical characterizations of H-TMD/Cs by chalcogenization of the materials synthesized in task one, and by carbonization of TMDs. H-TMD/Cs will also be investigated for their suitability in energy conversion applications such as supercapacitors, Li and multivalent ion batteries, and electrocatalysts, topics of interest to DoE. These tasks will be carried out in close conjunction with density functional theory (DFT) calculations with insights into energetics, lattice parameters, stability, phase diagrams, band structures, and density of states of H-TMD/Cs. The third task will characterize and evaluate strain and moiré patterns at the interfaces of different H-TMD/Cs by high-resolution scanning transmission electron microscopy (HR-STEM), scanning tunneling microscopy (STM), and conductive tip atomic force microscopy. Nudged elastic band calculations with DFT will be performed to understand the chalcogen diffusion process, which will provide insights into the interfaces between different phases of TMCs and TMDs. The fourth task aims at quantifying the stability and dynamics of H-TMD/Cs by in-situ TEM and Raman studies under heating, strain, and electrical biasing. Phonon calculations using DFT will provide a basis for interpreting Raman spectra. This coherent framework involving synthesis, characterization, and computation will result in a broad scientific impact for energy related applications. The ability to develop new H-TMD/Cs will enhance a range of applications that include batteries, catalysts, switches, sensors, quantum computing components and smart coatings.

2-Dimensional materials↗

2D-EFICACY: Control of Metastable 2D Carbide Chalcogenide Heterolayers: Strain and Moire Engineering

The experimental isolation of graphene led to the discovery of an entirely new world of two-dimensional (2D) materials in which the 2D nature often leads to emergent behaviors not seen in bulk systems. 2D transition metal dichalcogenides (TMDs) exhibit physico-chemical properties that depend on the transition metal, polymorph, thickness, and presence and type of defects. Recently, a group of thin (10-100nm) transition metal carbides (TMCs), such as Mo 2 C, has been synthesized that exhibit a thickness-dependent superconducting critical temperature (Tc). These thin TMCs are different from MXenes, another class of 2D materials consisting of few layers of nitrides or carbides (<5nm) produced by chemical etching and delamination. The goal of this renewal proposal is to combine experiment and computation to synthesize and elucidate the guiding principles that control the growth, orientation and strain of heterostacks of thin TMCs and TMDs composed with Nb, Ti and W. We expect to stabilize metastable hybrid phases of TMCs sandwiched between TMDs (H-TMD/Cs) with unprecedented physico-chemical properties. As part of previous DOE-funded work by the Terrones/Sinnott groups, thin (10-100 nm thick) Mo 2 C flakes were successfully synthesized by chemical vapor deposition (CVD). By subsequently exposing Mo 2 C to H 2 S, partial chalcogenization was achieved, resulting in heterostacks of MoCx phases and MoS 2 . The formation of MoS 2 led to a deficiency of Mo atoms in the underlying Mo 2 C, resulting in an inhomogeneous phase change from α-Mo 2 C to γ’-MoCx and then to γ-MoC. The γ’-MoCx is a strained metastable phase and the heterostack of all three phases demonstrated an increased Tc relative to that of α-Mo 2 C, from 4 to 6K; its interleaved layered structure consisting of superconducting and semiconducting phases is ideal for future studies of Josephson junction series arrays. Moiré patterns in these heterostacked systems could result in new phenomena, as moiré patterns in bilayer graphene showed unconventional superconductivity and moiré excitons have been observed in twisted TMD heterobilayers. The scientific hypothesis of the proposed synergistic computational and experimental research is that orientation and strain control within confined thin metastable TMCs, sandwiched by stable phases of TMCs and layered TMDs, will depend on kinetic and thermodynamic “knobs” that include fast temperature changes, chalcogen diffusion through preferred crystallographic planes, reaction times, pressure, reactive atmosphere, precursors, and surfactants, which will also tailor properties such as superconductivity, magnetism, ferroelectricity, piezoelectricity, and catalytic performance. We will develop the guiding principles for the synthesis and stabilization of metastable H-TMD/Cs based on Nb, Ti and W. In order to validate the hypothesis, four tasks are proposed: The first task will synthesize ultra-thin TMCs based on Nb, W and Ti, by: 1) adapting the CVD method used for Mo 2 C, 2) plasma assisted CVD, 3) defect-mediated CVD processes, and 4) cryo-milling of carbide powders. The second task will accomplish the synthesis and basic physico-chemical characterizations of H-TMD/Cs by chalcogenization of the materials synthesized in task one, and by carbonization of TMDs. H-TMD/Cs will also be investigated for their suitability in energy conversion applications such as supercapacitors, Li and multivalent ion batteries, and electrocatalysts, topics of interest to DoE. These tasks will be carried out in close conjunction with density functional theory (DFT) calculations with insights into energetics, lattice parameters, stability, phase diagrams, band structures, and density of states of H-TMD/Cs. The third task will characterize and evaluate strain and moiré patterns at the interfaces of different H-TMD/Cs by high-resolution scanning transmission electron microscopy (HR-STEM), scanning tunneling microscopy (STM), and conductive tip atomic force microscopy. Nudged elastic band calculations with DFT will be performed to understand the chalcogen diffusion process, which will provide insights into the interfaces between different phases of TMCs and TMDs. The fourth task aims at quantifying the stability and dynamics of H-TMD/Cs by in-situ TEM and Raman studies under heating, strain, and electrical biasing. Phonon calculations using DFT will provide a basis for interpreting Raman spectra. This coherent framework involving synthesis, characterization, and computation will result in a broad scientific impact for energy related applications. The ability to develop new H-TMD/Cs will enhance a range of applications that include batteries, catalysts, switches, sensors, quantum computing components and smart coatings.

2-Dimensional Materials↗

Inspiring the Next Generation of Explorers: Scientist Involvement in the Expedition Earth and Beyond Program

Scientists, science experts, graduate and even undergraduate student researchers have a unique ability to inspire the next generation of explorers. These science, technology, engineering, and mathematics (STEM) experts can serve as role models for students and can help inspire them to consider future STEM-related careers. They have an exceptional ability to instill a sense of curiosity and fascination in the minds of students as they bring science to life in the classroom. Students and teachers are hungry for opportunities to interact with scientists. They feel honored when these experts take time out of their busy day to share their science, their expertise, and their stories. The key for teachers is to be cognizant of opportunities to connect their students with scientists. For scientists, the key is to know how to get involved, to have options for participation that involve different levels of commitment, and to work with educational specialists who can help facilitate their involvement. The Expedition Earth and Beyond (EEAB) Program, facilitated by the Astromaterials Research and Exploration Science (ARES) Directorate at the NASA Johnson Space Center, is an Earth and planetary science education program designed to inspire, engage, and educate teachers and students by getting them actively involved with NASA exploration, discovery, and the process of science. One of the main goals of the program is to facilitate student research in the classroom. The program uses astronaut photographs, provided through the ARES Crew Earth Observations (CEO) payload on the International Space Station (ISS) as the hook to help students gain an interest in a research topic. Student investigations can focus on Earth or involve comparative planetology. Student teams are encouraged to use additional imagery and data from Earth or planetary orbital spacecraft, or ground-based data collection tools, to augment the astronaut photography dataset. A second goal of the program is to provide opportunities for meaningful connections between scientists and classrooms. To do this, EEAB offers multiple opportunities for scientist involvement. One opportunity involves having scientists work as mentors for student teams conducting research. These student teams, ranging from grades 4 through 12, are able to obtain guidance, suggestions, and input from STEM experts as they conduct a research investigation. Another opportunity for scientist involvement is participation in Classroom Connection Distance Learning (DL) events. These DL events entail interactive and engaging presentations that enable STEM experts to share their expertise with students and teachers (grades 3 through 12) from all across the nation. A third opportunity for scientist involvement involves participation in virtual student team science presentations. Student teams have the opportunity to share their research and results by presenting it to science experts through the use of WebEx, an easy-to-use online conferencing tool. The impact STEM experts have on students in today s classrooms is powerful. They serve as role models to these students, and they open students eyes to a potential career path they may not have known existed otherwise. The more scientists and STEM experts we can connect with students, the greater the impact we can make as we strive to inspire and prepare our nation s next generation of explorers.

Graff, Paige↗

Mapping structural heterogeneity at the nanoscale with scanning nano-structure electron microscopy (SNEM)

Here, in this work, we explore the use of scanning electron diffraction (also known as 4D-STEM) coupled with electron atomic pair distribution function analysis (ePDF) to understand the local order (structure and chemistry) as a function of position in a complex multicomponent system, a hot rolled, Ni-encapsulated, Zr 65 Cu 17.5 Ni 10 Al 7.5 bulk metallic glass (BMG), with a spatial resolution of 3 nm. We show that it is possible to gain insight into the chemistry and chemical clustering/ordering tendency in different regions of the sample, including in the vicinity of nano-scale crystallites that are identified from virtual dark field images and in heavily deformed regions at the edge of the BMG. In addition to simpler analysis, unsupervised machine learning was used to extract partial PDFs from the material, modeled as a quasi-binary alloy, and map them in space. These maps allowed key insights not only into the local average composition, as validated by EELS, but also a unique insight into chemical short-range ordering tendencies in different regions of the sample during formation. The experiments are straightforward and rapid and, unlike spectroscopic measurements, don’t require energy filters on the instrument. We spatially map different quantities of interest (QoI’s), defined as scalars that can be computed directly from positions and widths of ePDF peaks or parameters refined from fits to the patterns. We developed a flexible and rapid data reduction and analysis software framework that allows experimenters to rapidly explore images of the sample on the basis of different QoI’s. The power and flexibility of this approach are explored and described in detail. Because of the fact that we are getting spatially resolved images of the nanoscale structure obtained from ePDFs we call this approach scanning nano-structure electron microscopy (SNEM), and we believe that it will be powerful and useful extension of current 4D-STEM methods.

36 MATERIALS SCIENCE↗

Physics Discovery in Nanoplasmonic Systems via Autonomous Experiments in Scanning Transmission Electron Microscopy

Abstract Physics‐driven discovery in an autonomous experiment has emerged as a dream application of machine learning in physical sciences. Here, this work develops and experimentally implements a deep kernel learning (DKL) workflow combining the correlative prediction of the target functional response and its uncertainty from the structure, and physics‐based selection of acquisition function, which autonomously guides the navigation of the image space. Compared to classical Bayesian optimization (BO) methods, this approach allows to capture the complex spatial features present in the images of realistic materials, and dynamically learn structure–property relationships. In combination with the flexible scalarizer function that allows to ascribe the degree of physical interest to predicted spectra, this enables physical discovery in automated experiment. Here, this approach is illustrated for nanoplasmonic studies of nanoparticles and experimentally implemented in a truly autonomous fashion for bulk‐ and edge plasmon discovery in MnPS 3 , a lesser‐known beam‐sensitive layered 2D material. This approach is universal, can be directly used as‐is with any specimen, and is expected to be applicable to any probe‐based microscopic techniques including other STEM modalities, scanning probe microscopies, chemical, and optical imaging.

42 ENGINEERING↗