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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 721 records · Page 40
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Shock compression of additively manufactured high solids loaded polymer composites with aligned porosity

The effects of aligned porosity on the shock-compression response of additively manufactured (AM) composite structures with collinear and log-cabin geometries are investigated. The composites contain two inorganic and two organic particle populations and a UV-curable polymer binder. X-ray phase contrast imaging (X-PCI) is used as an in-material diagnostic in plate-impact experiments performed at the Dynamic Compression Sector of the Advanced Photon Source at the Argonne National Laboratory. Macroscale shock and particle velocities and microscale pore collapse velocities are measured from X-PCI images obtained from samples impacted in various orientations relative to the AM build directions. The linear shock and particle velocity relation for the structures with collinear build geometry shows directional differences, with the build direction exhibiting the highest slope and the filament print direction having the shallowest slope. Composites with log-cabin geometry, due to their slightly lower porosity and smaller sized pores, show higher shock velocities than the collinear structures at the same particle velocity. Microscale directionality effects are also observed, with the pore collapse velocity dependent on the pore configuration. Specifically, the pore collapse velocity is highest for pores elongated along the impact direction which is the case for the colinear structures impacted in the filament print direction, which is consistent with the directionality trend observed in the data for the shock and particle velocity equation of state. The pore collapse velocity approaches ∼80 % of the shock velocity and is several times the average bulk particle velocity, suggesting a highly hydrodynamic mechanism of pore collapse. Overall, both the macroscale response as measured by the shock and particle velocity relationship, and the microscale response as measured by the pore collapse velocity, are found to be anisotropic and dependent on the AM composite structure.

Wagner, K. B. [Georgia Institute of Technology, At↗
DOE OSTI2020

Impact of acid site speciation and spatial gradients on zeolite catalysis

This mini-review provides an overview of the current state of acid site control in zeolite catalysts, including methods of synthesis, advanced characterization, and measured effects of acid properties (speciation, concentration, proximity, siting, and spatial distribution) on a variety of commerciallyrelevant reactions. The diversity of aluminum species is described with respect to their location at specific sites in zeolite crystals as well as mesoscopic gradients in elemental composition that give rise to zoned or core-shell architectures. Challenges in the identification of acid siting are highlighted within the context of trial-and-error synthesis methods for a range of aluminosilicate frameworks, which hinder a priori design of catalysts, and limitations in techniques to suitably characterize active sites. Emphasis is also placed on knowledge gaps in zeolite catalysis wherein broad development of structure-performance relationships relies on future advancement of synthesis and analytical methods in parallel with atomistic modeling.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Programmable Matter: The Nanoparticle Atom and DNA Bond

Colloidal crystal engineering with DNA has led to significant advances in bottom-up materials synthesis and a new way of thinking about fundamental concepts in chemistry. Here, programmable atom equivalents (PAEs), comprised of nanoparticles (the “atoms”) functionalized with DNA (the “bonding elements”), are assembled through DNA hybridization into crystalline lattices. Unlike atomic systems, the “atom” (e.g., the nanoparticle shape, size, and composition) and the “bond” (e.g., the DNA length and sequence) can be tuned independently, yielding designer materials with unique catalytic, optical, and biological properties. Here in this review, nearly three decades of work that have contributed to the evolution of this class of programmable matter is chronicled, starting from the earliest examples based on gold-core PAEs, and then delineating how advances in synthetic capabilities, DNA design, and fundamental understanding of PAE-PAE interactions have led to new classes of functional materials that, in several cases, have no natural equivalent.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Sensitivity and Uncertainty Quantification of Transition Scenario Simulations

This report documents the first collective attempt at developing and applying capabilities to quantify uncertainties, assess parametric sensitivities, and optimize multiple parameters and metrics in fuel cycle simulations generated by the SA&I Campaign. To do this, external codes that were designed to perform sensitivity analysis and uncertainty quantification (SA&UQ) needed to be coupled to the SA&I Campaign’s nuclear fuel cycle simulators (NFCS). In FY20, two approaches were pursued: 1) coupling Cyclus to an ORNL-internal code called MOT (Metaheuristic Optimization Tool) and 2) coupling DYMOND to the opensource SA&UQ tool kit Dakota. The primary objective of having these NFCS/SA&UQ coupled capabilities is to better inform DOE-NE and other stakeholders on the results generated from the NFCS. For a given set of fuel cycle strategies, policies, and technology assumptions that make up a fuel cycle scenario, these NFCS have traditionally been used by the SA&I Campaign to provide quantitative answers in terms of year-by-year mass flows, infrastructure requirements, costs, etc. With these newly developed coupled capabilities, the SA&I Campaign can now efficiently simulate hundreds or thousands of these scenarios, sample large ranges of parameters and assumptions, and use the unique features of the SA&UQ tools to process the data. This enables providing answers with known and propagated uncertainties, determining the sensitivity of important metrics to different parameters and assumptions, quantifying how much fuel cycle and technology parameters impact each other, and producing optimized fuel cycle strategies for single and multiple variables. To demonstrate these new capabilities, the Cyclus/MOT was used to model several scenarios ranging from simple fleet retirements to transitions to advanced reactors. Specifically, for a transition scenario from LWRs to SFRs and advanced LWRs, uncertainty quantification, sensitivity analysis, and optimization studies were applied to cases involving single and multiple parameter (input) and single and multiple metric (output) variations. In addition, a similar transition scenario was modeled to demonstrate how to optimize the reprocessing capacity parameter to minimize two performance metrics while taking into account uncertainties from two other parameters. Lastly, a depletion module based on SCALE/ORIGEN was added in Cyclus to simulate the third scenario that was designed to quantify the impact of the modeling assumption that all LWR used nuclear fuel have the same burnup. The newly developed DYMOND/Dakota capability was also applied to a transition scenario from the existing fleet to small modular reactors and fast reactors. This particular scenario involves not only explicit isotopic depletion via ORIGEN-2, but also includes multirecycling and utilizing the criticality search feature to determine the fresh fuel composition of recycled fuel, a feature unique to the DYMOND NFCS. A large database of simulations were run with 4 main parameters that were sampled: start date of reprocessing, reprocessing capacity, energy demand growth rate, and advanced reactor share of the fleet. The 4 main metrics were uranium consumption, enrichment requirements, waste generation, and levelized cost of electricity using data from the Cost Basis Report. The demonstrated SA&UQ results include those that inform on how to choose parameters to avoid “failed” scenarios, Sobol’ indices that inform on the importance of various parameters individually and synergistically, and Analysis of Variance (ANOVA) studies that decompose parameter ranges into groups and informs on whether variations are statistically significant.

Feng, B.↗
DOE OSTI2025

Artificial Intelligence and Multiscale Modeling for Sustainable Biopolymers and Bioinspired Materials

Abstract Biopolymers and bioinspired materials contribute to the construction of intricate hierarchical structures that exhibit advanced properties. The remarkable toughness and damage tolerance of such multilevel materials are conferred through the hierarchical assembly of their multiscale (i.e., atomistic to macroscale) components and architectures. Here, the functionality and mechanisms of biopolymers and bio‐inspired materials at multilength scales are explored and summarized, focusing on biopolymer nanofibril configurations, biocompatible synthetic biopolymers, and bio‐inspired composites. Their modeling methods with theoretical basis at multiple lengths and time scales are reviewed for biopolymer applications. Additionally, the exploration of artificial intelligence‐powered methodologies is emphasized to realize improvements in these biopolymers from functionality, biodegradability, and sustainability to their characterization, fabrication process, and superior designs. Ultimately, a promising future for these versatile materials in the manufacturing of advanced materials across wider applications and greater lifecycle impacts is foreseen.

Wang, Xing Quan [Department of Mechanical Engineer↗
DOE OSTI2020

Bio-treatment of poplar via amino acid for interface control in biocomposites

Advanced biocomposites reinforced by abundant biomass-derived fillers can add a revenue stream to enhance the economic viability of biofuel production chains and the energy efficiency of the composite industry. However, the low stiffness of biopolymers limits their use in structural applications. Poplar fibers (mesh size: <180 μm, Populus spp.), an abundant waste from the wood industry, were used as bio-filler to fabricate high-performance biocomposites based on polylactic acid (PLA), in which the poplar fibers were modified by an amino acid (l-lysine). As a benefit of the amino acid treatment, the tensile Young's moduli of the lysine/poplar/PLA composites increased by up to 68% with the addition of a small amount of lysine, compared with neat PLA. At the same time, the tensile strength, failure strain, and Young's modulus of the poplar/PLA composites all increased after adding only 0.1 wt % of lysine. It has been observed that the lysine content has a significant effect on the decomposition temperature, complex viscosity, storage modulus, crystallization temperature, and crystallinity of composites. The fracture surfaces of the composites with an optimum lysine content had fewer voids and were more compact compared with composites without any lysine. The pores on the surfaces of poplar fibers became more available for the penetration of PLA molecules as a result of lysine addition. Finally, this study presents a facile method for reinforcing biocomposites with extremely low-cost and environmentally friendly biofillers.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Architected mesoporous crystalline magnesium silicates with ordered pore structures

Novel approaches to harness earth abundant silicates as building blocks for carbon dioxide removal, capture, utilization, and storage are gaining increasing attention in the context of sustainable and low carbon energy and resource recovery. Advancing a calibrated understanding of these fluid-silicate interactions is essential for developing scalable processes. One of the challenges in developing predictive controls over these interactions is the compositional and morphological heterogeneity of naturally occurring, heterogeneous magnesium silicate minerals. To address this challenge, the synthesis of architected mesoporous crystalline magnesium silicate (Mg 2 SiO 4 ) is proposed. While synthesis routes for producing amorphous mesoporous magnesium silicates have been developed via sol-gel methods, approaches to synthesize crystalline magnesium silicates with well-controlled pore size distributions have not been explored. The conventional approaches of converting matter that is amorphous to crystalline states at elevated temperatures results in a heterogeneous pore size distribution. To develop controls on pore size distribution, amorphous mesoporous magnesium silicates are coated with carbon. This approach preserves the pore size distributions during the amorphous to crystalline transformations of Mg-silicates at elevated temperatures. The carbon coating is removed on heating. Magnesium silicate particles produced using this approach have highly ordered pores around 2.58 nm and a specific surface area of 124.25 m 2 /g. In this study, we report the chemical compositions, morphologies, phase transitions, and pore structures of the intermediate materials produced during the synthesis of crystalline mesoporous magnesium silicates. The transitions, and pore structures of the intermediate materials produced during the synthesis of crystalline mesoporous magnesium silicates. Furthermore, the synthesis routes discussed in this study can be applied translationally to produce metal silicates with ordered mesoporous structures.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Origin of Phase Separation in Ni-Rich Layered Oxide Cathode Materials During Electrochemical Cycling

In intercalation materials, the kinetics and uniformity of mass transport across the nanocrystalline domains dictate the structural reversibility and transport capability at the macroscopic level. (De)intercalation-induced interlayer disintegrations exhibit anisotropic crystallite size change. Due to the anisotropic mass transport mechanism, separated phases are inherently crystallographically oriented. One such material is LiNi $1–x–y$ Mn $x$ Co $y$ O 2 , which plays a pivotal role in advanced Li-ion batteries but suffers from severe phase inhomogeneities under fast charge or electrochemical aging. Here, using operando synchrotron techniques, we probe the mechanistic origins of the compositional and orientational-dependent phase separations during the electrochemical cycling of LiNi 0.8 Mn 0.1 Co 0.1 O 2 by comprehensive analysis of both in-plane and out-of-plane reflections. In the H2/H3 phase regime, in-plane domain propagation occurs due to increased covalency despite the severe decay of interlayer crystallographic order, resulting in the change of crystalline domain shape from 3D spheres to two-dimensional nanosheets. The crystallographically selective XRD line splitting is linked to the geometry of the facets as mass transfers along the ab plane. In conclusion, this work provides mechanistic insights into crystallographic orientation-dependent phase inhomogeneity under fast charge and extended cycling.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Li 2.9 Fe 0.9 Zr 0.1 Cl 6 as Redox-Active Catholyte for Solid-State Li-Ion Batteries

Solid electrolytes are one of the key challenges that hinder the commercialization of all-solid-state batteries. Most efforts have been made to advance the development of solid electrolytes as separators, while the development of catholytes, particularly redox-active catholytes, has been less extensively studied. The high loading of catholytes in composite cathodes, while facilitating ionic conduction, drastically decreases the energy density of the battery. Here, we report an alternative strategy to improve the energy density by using Li 2.9 Fe 0.9 Zr 0.1 Cl 6 as a redox-active catholyte. With a composite cathode containing uncoated LiCoO2 and Li 2.9 Fe 0.9 Zr 0.1 Cl 6 , the solid-state cell not only shows excellent rate capability and stable long-term cycling, benefiting from the high ionic conductivity of Li 2.9 Fe 0.9 Zr 0.1 Cl 6 , but also shows a high cathode specific capacity of ~153 mAh·g –1 . This study broadens the chemical space of the materials design for lithium-ion conductors with redox-active elements (e.g., Fe, Ti, V, and Cr), offering new opportunities to reduce the cost and improve the energy density for all-solid-state batteries.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Microstructure, Transport, and Mechanics of Compacted Clay Simulated at the 0.1 μm Scale (1400 Smectite Clay Particles) Using a Coarse-Grained Model with Explicit Counterions

Clay-rich geomaterials play a critical role in many subsurface systems. The macroscale properties of these materials (low permeability, high ionic conductivity, high swelling pressure, etc.) are sensitive to molecular-level adsorption and hydration interactions at clay−water interfaces. Efforts to develop multiscale simulation approaches to predict these properties reveal a scale gap between atomistic simulations (typically limited to systems smaller than 10 nm) and continuum-scale models (which use computational grid elements with dimensions ≳ 10 μm). In this study, we present a coarse-grained (CG) framework that partly bridges this gap by simulating compacted smectite clay assemblages with dimensions of 0.1 μm containing 1,400 clay particles across a range of dry densities (1,050 to 1,850 kg·m −3 ) and Na/Ca counterion compositions (Na fraction ranging from 0.2 to 1). The simulated systems, along with their reconstructed binary three-dimensional pore networks, are used to evaluate the microstructure, pore size distribution, tortuosity, ion diffusivity, and swelling pressure of compacted smectite clay. Results show that our approach captures important features of the mesoscale heterogeneity of compacted clays, including tactoid formation, hierarchical porosity, and anisotropic pore networks. Results also reveal how compaction and counterion composition govern emergent behaviors, including dominant pore sizes, directional transport, and electrochemical response. This work highlights the potential of CG simulations to bridge molecular and continuum scales and to advance geotechnical and environmental applications involving clay-rich materials as well as related nanoporous media such as geopolymers and calcium-silicate-hydrate. However, the results also suggest that accurate prediction of certain microstructural and mechanical properties (e.g., swelling pressure) may require even larger-scale systems on the order of 1 μm.

02 PETROLEUM↗
DOE OSTI2020

Dynamic Structure and Phase Behavior of a Block Copolymer Electrolyte under dc Polarization

There is an important consideration when designing lithium battery electrolytes for advanced applications is how the electrolyte facilitates ion transport at fast charge and discharge rates. Large current densities are accompanied by large salt concentration gradients across the electrolyte. Nanostructured composite electrolytes have been proposed to enable the use of high energy density lithium metal anodes, but many questions about the interplay between the electrolyte morphology and the salt concentration gradient that forms under dc polarization remain unanswered. To address these questions, we use an in situ small-angle X-ray scattering technique to examine the nanostructure of a polystyrene- block -poly(ethylene oxide) copolymer electrolyte under dc polarization with spatial and temporal resolution. In the quiescent state, the electrolyte exhibits a lamellar morphology. The passage of ionic current in a lithium symmetric cell leads to the formation of concurrent phases: a disordered morphology near the negative electrode, lamellae in the center of the cell, and coexisting lamellae and gyroid near the positive electrode. The most surprising result of this study was obtained after the applied electric field was turned off: a current-induced gyroid phase grows in volume for 6 h in spite of the absence of an obvious driving force. We show that this reflects the formation of localized pockets of salt-dense electrolyte, termed concentration hotspots, under dc polarization. Our methods may be applied to understand the dynamic structure of composite electrolytes at appreciable current densities.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

High-current, double-sided REBCO tapes by advanced MOCVD

Abstract An approach to fabricate double-sided, high-current RE-Ba 2 Cu 3 O 7− δ (REBCO) tapes for use in ultrahigh-field superconducting magnets operating at and above 20 T is demonstrated. In this work, we modified our advanced metal organic chemical vapor deposition (A-MOCVD) reactor to deposit REBCO films on each side of a double-sided buffer substrate in a single pass. The composition, thickness, and critical current ( I c ) of 1 µ m-thick REBCO films on each side of the double-sided tapes are compared. Double-sided REBCO tape with 2 µ m-thick films on each side showed self-field critical current density ( J c ) over 2.6 MA cm −2 at 77 K and 0 T. 15%-Zr-added double-sided REBCO tape showed I c over 530 A/4 mm at 20 K, 20 T.

Paidpilli, M.↗
DOE OSTI2023

Printing of electromagnetic interference shielding materials

Here, the proliferation of electronic devices has made electromagnetic interference (EMI) shielding an exponentially growing business. Regulatory requirements change constantly as new technologies continue to emerge. Innovations in materials and new advances in shielding implementation techniques are needed to pass regulatory compliance tests at an affordable cost. Here, we print various EMI shielding materials such as copper, silver and a composite of copper with Fe 3 O 4 using plasma jet printing. Printing enables shields only a few microns thick capable of high shielding effectiveness. Copper's EMI shielding performance is primarily contributed by reflection mechanism, as expected and this is known to cause secondary pollution. A Green Index for EMI shielding, given by the ratio of absorption and reflection contributions to shielding, indicates values lower than 0.1 for printed copper films.

36 MATERIALS SCIENCE↗
DOE OSTI2023

TRACER-Vertical Profile of Aerosol in Convective System (TRACER-VPACS) Field Campaign Report

We investigated physicochemical properties of aerosol at different altitudes during the U.S. Department of Energy (DOE)’s Atmospheric Radiation Measurement (ARM) user facility Tracking Aerosol Convection Interactions Experiment (TRACER). We used ARM’s tethered balloon system (TBS) and multi-modal offline analysis techniques available at DOE’s Environmental Molecular Sciences Laboratory (EMSL) at Pacific Northwest National Laboratory (PNNL) and at the Advanced Light Source (ALS) at the Lawrence Berkley National Laboratory (LBNL). The main scientific aim of this project was to understand the influence of the vertical profile of aerosol composition on the properties of deep convective clouds. The effect of aerosol properties on convective activity is still poorly understood and debated. For example, previous studies suggested that higher concentration of hygroscopic aerosol may lead to lower collection efficiency and eventually delay in onset of precipitation and total amount of precipitation. However, some observations suggested that increased aerosol concentration may result in vigorous convection and a higher amount of precipitation. In addition, the radiative forcing of the ambient aerosol is strongly influenced by the vertical distribution of aerosols and their chemical composition, and not well constrained in climate models. The estimation of the indirect effect of aerosol also has a significant uncertainty due to the spatial variation of the aerosol, especially at the cloud base. Detailed size-resolved chemical composition studies of aerosol and their microphysical properties, along with in situ measurements from ARM’s mobile facilities, help to improve our understanding of the role of aerosol in deep convective cloud formation over a broad range of environmental thermodynamic and aerosol conditions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

A Miniaturized Ignition Screening Rapid Compression Machine for probing low-to-intermediate temperature chemistry

With an objective to achieve net-zero emissions by no later than 2050, biofuels hold enormous potential as sustainable, renewable fuels that can be produced on a large scale. However, fuels of a similar type, derived from limited feedstock batch can dramatically vary in terms of their chemical structures and compositions, causing significant differences in physicochemical properties mainly influencing ignition-relevant properties. Rigorous prescreening and testing efforts are involved to evaluate fuels to comply with engines equipped with advanced combustion modes. The testing of some of these fuels implies low quantity fuel samples, access to relevant temperature and pressure conditions, high reproducibility, and a high throughput rate. In light of these considerations, a Miniaturized Ignition Screening Rapid Compression Machine (MISR) has been developed and built at the University of Illinois Chicago (UIC). Some design features include a smaller bellows-actuated driver section compared to other RCM designs, an adjustable brake section, and full optical access. The setup is designed to achieve reaction conditions (T > 600K and P < 100 bar with repetition rates of about 8 seconds per experiment). These conditions are relevant to low-to-intermediate temperature auto-ignition and can generate data for developing relevant chemical kinetics models or ignition maps. A brief insight into MISR design and its operating mechanism is shown. Also, to demonstrate the performance characteristics of the MISR, Ignition Delay (I.D) experiments for ethanol fuel at different equivalence ratios (Φ) are discussed in the context of plans with additional optical diagnostics, high-speed imaging, and gas sampling experiments.

Tomar, Mukul↗
DOE OSTI2020

Feasibility study of a compact neutron resonance transmission analysis instrument

Neutron Resonance Transmission Analysis (NRTA) uses resonant absorption of neutrons to infer the absolute isotopic composition of a target object, enabling applications in a broad range of fields such as archaeology, enrichment analysis of nuclear fuel, and arms control treaty verification. In the past, NRTA involved large user facilities and complex detector systems. However, recent advances in the intensity of compact neutron sources have made compact neutron imaging designs increasingly feasible. This work describes the Monte Carlo (MC) based design of a compact epithermal NRTA radiographic instrument which uses a moderated, compact deuterium-tritium (DT) neutron source and an epithermal neutron detector. Such an instrument would have a wide range of applications, and would be especially impactful for such scenarios as nuclear inspection and arms control verification exercises, where system complexity and mobility may be of critical importance. The MC simulations presented in this work demonstrate accurate time-of-flight (TOF) reconstructions for transmitted neutron energies, capable of differentiating isotopic compositions of nuclear material with high levels of accuracy. A new generation of miniaturized and increasingly more intense neutron sources will allow this technique to achieve measurements with greater precision and speed, with significant impact on a variety of engineering and societal problems.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Southwest Pacific tropical cyclone development classification utilizing machine learning and synoptic composites

This study evaluates the ability of machine learning algorithms to classify tropical depressions (TDs) and tropical storms (TSs) in the western region of the southwest Pacific Ocean (SWPO). Decision rules are generated to predict the environment required for a depression to fully develop into a mature storm, and the most influential predictors in the classification decision are ranked. TD and TS are discriminated based on a maximum sustained wind speed threshold (≥17 ms -1 ). Various aerosol, thermodynamic, and dynamic parameters are extracted closest to the initiation point of each non-developing and developing sample. The covariates associated with each labelled sample are used to train a decision tree and random forest model. Results using a testing dataset suggest the random forest approach more accurately distinguishes between non-developing and developing samples. The classification accuracy of the decision tree and random forest are 72% and 91%, respectively. Random forest outperformed the decision tree by providing higher accuracy in test data. The most important variables for binary classification are sea salt aerosol optical depth (AOD), 1,000 mb relative humidity, and sea surface temperature. AOD is a quantitative estimate of the aerosols presents in the air through the extinction of a ray of light as it passes through the atmosphere. Mean composite maps constructed in an unsupervised manner have been created for the most important variables identified by the random forest classifier during TD and TS events to highlight the difference in geophysical and aerosol variables' climatology during the two different classifications. This work will advance the risk management strategies for northeastern Australia and other SWPO basin islands to control their tropical cyclone related losses through prioritizing forecasting variables that are the strongest predictors of the strengthening of tropical depressions into tropical cyclones.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Advances in scientific literature mining for interpreting materials characterization

Abstract Using synchrotron light sources, such as the National Synchrotron Light Source II at Brookhaven National Laboratory, scientists in fields as diverse as physics, biology, and materials science, identify the atomic structure, chemical composition, or other important properties of varied specimens. x-ray spectroscopy from light sources is particularly valuable for materials research with vast information available about reference spectra in the scientific literature. However, as the technique is applicable to many science domains, searching for information about select x-ray spectroscopy spectra is impeded by the sheer number of publications. Moreover, useful information about the context of an experiment or figures presented in papers can be buried among the details, which takes time to assess. This work presents a scientific literature mining system that supports data acquisition, information extraction, and user interaction for referencing x-ray spectra identification and spectral interpretation. The goal is to provide efficient access to useful spectral data to researchers who may spend only a few days at a synchrotron light source. With this system, users browse a classification tree for papers arranged according to x-ray spectroscopic methods, chemical elements, and x-ray absorption spectroscopy edges. Relevant figures are extracted with sentences from the paper that explain them, known as ‘figure explanatory text.’ Notably, this system focuses on semantic aspects (logical analysis) to find figure explanatory text using deep contextualized word embeddings techniques and contains an interface to obtain labeled data from domain experts that is used to evaluate and improve the model.

Park, Gilchan (ORCID:0000000201536646)↗