1,721,024 research outputs found
A Physics-Informed Bayesian Method for Quantitative X-Ray Diffraction Analysis: Case Study on the Quantification of Ordering in a Proxy TaTi for Compositionally Complex Alloys
Full text linkStructural characterization is vital for understanding microstructure and establishing processing-structure-property relationships. The diffraction pattern produced by X-ray diffraction (XRD) not only helps to classify the structure but also contains the quantitative information of structure that are not fully employed. However, XRD analysis is a time-consuming human endeavor, heavily relying on the expertise of individuals in diffraction and material systems. To address this, we develop AutoXRD, a Bayesian framework incorporating Rietveld refinement for quantitative diffraction analysis. AutoXRD demonstrated its ability on a simulated TaTi alloy system to quantify the ordering in the presence of grain size and microstrain effects. AutoXRD provides both point estimations and uncertainty measurements for ordering, grain size, and microstrain. The sensitivity analysis quantitatively assesses AutoXRD’s ability to identify and quantify ordering. This generalizable framework has been demonstrated to extract quantitative knowledge from diffraction data and could be extensible for integration into automated materials discovery workflow.M.A.S.2025-11-07 00:00:0
Materials Datasets with 273 compositional and structural features extracted from Matminer
No full text<p>Materials Datasets with 273 compositional and structural features extracted from <a href="https://github.com/hackingmaterials/matminer">Matminer</a>. Materials datasets are retrieved using the python package <a href="https://github.com/usnistgov/jarvis">jarvis-tools</a>.</p>
The Materials Super Highway: Integrating High-Throughput Experimentation into the Catalysis MGI
No full textSynthesis of Mono-Disperse CoFe Alloy Nanoparticles with High Activity toward NaBH\u3csub\u3e4\u3c/sub\u3e Hydrolysis
No full textTraditionally, the synthesis of CoFe nanoparticles with tunable particle sizes and narrow particle size-distributions is accomplished via the use of expensive and air sensitive precursors and strong non-polar capping agents. Such strong capping agents can be difficult to remove from the nanoparticles and thus render them catalytically inactive. We report a novel solution-based methodology to synthesize CoFe alloy nanoparticles with narrow size-distributions using a combination of robust and inexpensive metal precursors and an easily removable polar capping agent. High resolution transmission electron microscope images show that the CoFe alloy nanoparticles are well crystallized, and the particle size is tunable from 9 to 24 nm while keeping a particle size standard deviation of 10%. The CoFe alloy nanoparticles show superior activity for NaBH4 hydrolysis compared with the best-known CoFe catalysts. This work represents a substantial improvement in the synthesis of transition metal nanoparticles, opening the pathway for their application to a number of technologically important catalytic applications
One-Step Production of Long-Chain Hydrocarbons from Waste-Biomass-Derived Chemicals using Bi-Functional Heterogeneous Catalysts
Full text linkn this study, we demonstrate the production of long-chain hydrocarbons (C8+) from 2-methylfuran (2MF) and butanal in a single step reactive process by utilizing a bi-functional catalyst with both acid and metallic sites. Our approach utilizes a solid acid for the hydroalkylation function and as a support as well as a transition metal as hydrodeoxygenation catalyst. A series of solid acids was screened, among which MCM-41 demonstrated the best combination of activity and stability. Platinum nanoparticles were then incorporated into the MCM-41. The Pt/MCM-41 catalyst showed 96% yield for C8+ hydrocarbons and the catalytic performance was stable over four reaction cycles of 20 hour each. The reaction pathways for the production of long-chain hydrocarbons is probed with a combination of infrared spectroscopy and steady-state reaction experiments. It is proposed that 2MF and butanal go through hydroalkylation first on the acid site followed by hydrodeoxygenation to produce the hydrocarbon fuels
A High Throughput Aqueous Passivation Testing Methodology for Compositionally Complex Alloys using Scanning Droplet Cell
Full text linkCompositionally complex alloy systems containing more than five principal
elements allow exploring a wide range of compositions, processing, and
structural variables with the hope for identifying unique properties. Such
opportunities also apply to designing materials for improved corrosion
resistance, regulated by a self-healing passive film. Such a rich landscape in
reactivity and protectivity demands the search for high-throughput experimental
testing workflows to uncover key metrics, indicative of superior properties. In
this communication, one such methodology is demonstrated for evaluating
passivation performance of a combinatorial library of
Al0.7-x-yCoxCryFe0.15Ni0.15 thin film alloys in deaerated 0.1 mol/L H2SO4(aq),
using a scanning droplet cell
A Semi-Empirical Model for Tilted-Gun Planar Magnetron Sputtering Accounting for Chimney Shadowing
No full textApplications of High Throughput (Combinatorial) Methodologies to Electronic, Magnetic, Optical, and Energy-Related Materials
Full text linkHigh throughput (combinatorial) materials science methodology is a relatively new research paradigm that offers the promise of rapid and efficient materials screening, optimization, and discovery. The paradigm started in the pharmaceutical industry but was rapidly adopted to accelerate materials research in a wide variety of areas. High throughput experiments are characterized by synthesis of a “library” sample that contains the materials variation of interest (typically composition), and rapid and localized measurement schemes that result in massive data sets. Because the data are collected at the same time on the same “library” sample, they can be highly uniform with respect to fixed processing parameters. This article critically reviews the literature pertaining to applications of combinatorial materials science for electronic, magnetic, optical, and energy-related materials. It is expected that high throughput methodologies will facilitate commercialization of novel materials for these critically important applications. Despite the overwhelming evidence presented in this paper that high throughput studies can effectively inform commercial practice, in our perception, it remains an underutilized research and development tool. Part of this perception may be due to the inaccessibility of proprietary industrial research and development practices, but clearly the initial cost and availability of high throughput laboratory equipment plays a role. Combinatorialmaterials science has traditionally been focused on materials discovery, screening, and optimization to combat the extremely high cost and long development times for new materialsand their introduction into commerce. Going forward, combinatorial materials science will also be driven by other needs such as materials substitution and experimental verification ofmaterials properties predicted by modeling and simulation, which have recently received much attention with the advent of the Materials Genome Initiative. Thus, the challenge for combinatorial methodology will be the effective coupling of synthesis, characterization and theory, and the ability to rapidly manage large amounts of data in a variety of formats
Development of Combined Optical Cell and Sieverts-type Apparats for in-situ Measurement of Hydrogen Storage Materials
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