Analyzing the Intensities of K-Edge Transitions in X 2 Molecules (X = F, Cl, Br) for Use in Ligand K-Edge X-ray Absorption Spectroscopy
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37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
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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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Using Diffusion Maps to Analyze Reaction Dynamics for a Hydrogen Combustion Benchmark Dataset
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37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Analyzing Stabilities of Metal–Organic Frameworks: Correlation of Stability with Node Coordination to Linkers and Degree of Node Metal Hydrolysis
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37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
ClipsMS: An Algorithm for Analyzing Internal Fragments Resulting from Top-Down Mass Spectrometry
Not provided.
Biochemistry & Molecular Biology↗
A Curated Experimental Compilation Analyzed by Theory Is More than a Review
Macromolecules is an exceptional resource in the field of polymer science and now publishes more than 1000 original articles a year that set the standard for scientific rigor and creative insights. Over the years, these individual contributions have combined to build the foundation of polymer science, broadly and inclusively defined. In addition to the individual articles, many of which are being celebrated in this series of editorials, Macromolecules has published invaluable reviews and perspectives. These scholarly contributions integrate the insights and results from numerous sources into a unified whole and often recommend future directions for the field. Novices and experts alike benefit from these works that capture topics from emerging discoveries to long-pondered topics and everything in between. To explore the importance of Macromolecules’ reviews and perspectives, we considered their influence on the field and found the 1994 review by Fetters et al. entitled “Connection between Polymer Molecular Weight, Density, Chain Dimensions, and Melt Viscoelastic Properties”1 to be a singularity. This review expertly curates and compiles a trove of data to build robust correlations between molecular characteristics and macroscopic viscoelastic properties of polymer melts, in the context of the tube model of entanglements.
36 MATERIALS SCIENCE↗
Differentiating Double-Layer, Psuedocapacitance, and Battery-like Mechanisms by Analyzing Impedance Measurements in Three Dimensions
Electrochemical energy storage arises from processes that are broadly categorized as capacitive, pseudocapacitive, or battery-like. Advanced charge-storing materials that are designed to deliver high capacity at a high rate often exhibit a multiplicity of such mechanisms, which complicates the understanding of their charge-storage behavior. In this paper, we apply a “3D Bode analysis” technique to identify key descriptors for fast Li-ion storage processes, where AC impedance data, such as the real capacitance ($C'$) or phase angle ($Φ$), are represented versus the frequency ($f$) and a third independent variable, the applied DC cell voltage. For double-layer processes, a near-constant $C'$ or $Φ$ is supported across the entire voltage range, and the decrease in these values shows a near-linear decrease at higher $f$. For pseudocapacitance, an increase in $C'$ is delivered, accompanied by high $C'$ retention at higher $f$ compared to double-layer processes. Interestingly, the lower $Φ$ values, where $C'$ is highest, suggest that this is a key descriptor for pseudocapacitance, where high-rate charge storage is still facilitated within a kinetically limited regime. For battery-like processes, a high $C'$ is only observed at the voltage at which the material stores charge, while outside that voltage, $C'$ is negligible. The three-dimensional (3D) Bode analysis allows charge-storage dynamics to be mapped out in great detail with more delineation between mechanisms compared to the more frequently deployed kinetic analyses derived from cyclic voltammetry.
25 ENERGY STORAGE↗
Analyzing Production Rate and Carbon Utilization Trade-offs in CO 2 RR Electrolyzers
Carbon utilization is a crucially important performance characteristic of CO 2 electrolyzers; however, applications of simple and accurate descriptive models to experimental data on this topic are currently lacking. Here, we apply a simple analytical reactor model to parameterize single-pass conversion as a function of feed-gas flow rate and show that it captures a wide body of experimental data in the literature exceptionally well. In doing so, we demonstrate that this simple conceptual approach can characterize progress and capture recent innovations in reactor design. To validate the extracted parameters, we employ a well-established comprehensive model to confirm that the results agree with physical expectations. Lastly, we explore the implications of the descriptive model by examining the inherent trade-off between single-pass conversion efficiency and reactor productivity. Understanding such trade-offs is crucially important for advancing this electrolyzer technology toward commercial applications.
36 MATERIALS SCIENCE↗
A Flexible Open Source Mass Transport Framework for Analyzing Dynamic Outgassing Experiments
Explore the source record for details and available documents.
Materials science↗
In Situ Velocity‐Strain Sensitivity Near the San Jacinto Fault Zone Analyzed Through Train Tremors
Abstract We utilize train tremors as P‐wave seismic sources to investigate velocity‐strain sensitivity near the San Jacinto Fault Zone. A dense nodal array deployed at the Piñon Flat Observatory is used to detect and identify repeating train energy emitted from a railway in the Coachella valley. We construct P‐wave correlation functions across the fault zone and estimate the spatially averaged dt / t versus strain sensitivity to be 6.25 × 10 4 . Through numerical simulations, we explore how the sensitivity decays exponentially with depth. The optimal solution reveals a subsurface sensitivity of 1.2 × 10 5 and a depth decay rate of 0.05 km −1 . This sensitivity aligns with previous findings but is toward the higher end, likely due to the fractured fault‐zone rocks. The depth decay rate, previously unreported, is notably smaller than assumed in empirical models. This raises the necessity of further investigations of this parameter, which is crucial to study stress and velocity variations at seismogenic depth.
Geology↗
Design, construction, and validation of an in-situ groundwater trace element analyzer with applications in carbon storage
Abstract It is estimated that carbon emissions should reach net-zero by 2050 to meet important climate targets. Carbon capture is likely necessary to reach these targets, requiring a long-term storage solution such as geological carbon sequestration. However, as with any subsurface activity, leakage can occur, potentially impacting groundwater quality near the storage site. Rapid detection is essential to mitigate damage to this resource. Since CO 2 will acidify groundwater, the concentrations of acid soluble minerals and associated cations will increase. Thus, an in-situ, real-time element analysis system based on laser-induced breakdown spectroscopy (LIBS) is under development to monitor these elements. The system splits the traditional LIBS system into a miniature, all-optical sensor head built around a passively Q-switch laser fiber coupled to a control unit. Previous work has validated the LIBS technique for use at high pressure as well as the split system design. In this work, a fieldable prototype sensor is developed and tested in an onsite monitoring well where trace elements concentrations (approx. 0–3 ppm) were tracked over 20 days. These concentrations varied in response to local rainfall, diluting with increased rain, demonstrating the ability of a LIBS-based sensor to track trace elements under real-world conditions.
54 ENVIRONMENTAL SCIENCES↗
A machine learning approach to robustly determine director fields and analyze defects in active nematics
A machine learning model for reliable director fields calculation from raw experimental images of active nematics. The model is accurate, robust to noise and generalizable, enhancing analysis such as the detection and tracking of topological defects.
97 MATHEMATICS AND COMPUTING↗
Machine learning for analyzing atomic force microscopy (AFM) images generated from polymer blends
In this paper, we present a new machine learning (ML) workflow with unsupervised learning techniques to identify domains within atomic force microscopy (AFM) images obtained from polymer films.
Paruchuri, Aanish [Master of Science in Data Scien↗
A super-resolution technique to analyze single-crystal inelastic neutron scattering measurements using direct-geometry chopper spectrometers
Direct-geometry time-of-flight chopper neutron spectroscopy is instrumental in studying dynamics in liquid, powder, and single crystal systems. We report here that real-space techniques in optical imagery can be adapted to obtain reciprocal-space super resolution dispersion for phonon or magnetic excitations from single-crystal neutron spectroscopy measurements. The procedure to reconstruct super-resolution energy dispersion of excitations relies on an accurate determination of the momentum and energy-dependent point spread function and a dispersion correction technique inspired by an image disparity calculation technique commonly used in stereo imaging. Here by, applying these methods to spinwave dispersion data from a virtual neutron experiment demonstrates ~5-fold improvement over nominal energy resolution.
47 OTHER INSTRUMENTATION↗
PyLRO: A Python calculator for analyzing long-range structural order
We present PyLRO, an open-source Python calculator designed to detect, quantify, and display long-range order in periodic structures. The program’s design methodology, workflow, and approach to order quantification are described and demonstrated using a simple toy model. Additionally, we apply PyLRO to a series of metastable AlPO 4 structural intermediates from a prior high-pressure study, demonstrating how to compute and visualize structural order in all directions on a Miller sphere. We further highlight the program’s capabilities through a high-throughput analysis of structural patterns in the pressure-induced amorphization of AlPO 4 , revealing atomistic insights into specific energy regions of massive amorphous structures. These results suggest that PyLRO can be a valuable tool for investigating crystal–amorphous transition in materials research.
36 MATERIALS SCIENCE↗
Analyzing the effect of misalignment on single-filament carbon fiber tensile testing via stereoscopic computer vision imaging
An understanding of the constitutive properties of carbon fibers (CF) is critical to the accuracy of high-resolution composite simulations and to the development of CF derived from low-cost alternative precursor materials. Single-fiber tensile testing is a capable tool to measure CF properties and is well suited to research efforts where only a small number of fibers may be available. However, single-fiber tensile tests are challenging to conduct due to the difficulty in handling small diameter fibers (5-15 μm), the brittleness of single fibers, and the required nanoscale/microscale resolution of testing equipment. The accuracy of the measured properties depends on several factors, but a critical factor is fiber misalignment, especially at short gauge lengths. Current standards do not address the effect of tensile specimen misalignment on measured properties. Furthermore, this work presents a robust method of fiber alignment using stereoscopic computer vision that enables users to align fibers vertically for tensile testing to improve the accuracy of resulting mechanical properties. Additionally, an analytical relationship between fiber misalignment angle and measured properties is developed and validated against the experimental results. As a result, new best practices for single-fiber tensile testing of CF are recommended.
47 OTHER INSTRUMENTATION↗