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Results for “EXPERIMENT”
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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Contributions to improving small ester combustion chemistry: Theory, model and experiments
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Drained coastal peatlands: A potential nitrogen source to marine ecosystems under prolonged drought and heavy storm events—A microcosm experiment
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The antimony sorption and transport mechanisms in removal experiment by Mn-coated biochar
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A Differentially Pumped Dual Linear Quadrupole Ion Trap (DLQIT) Mass Spectrometer: A Mass Spectrometer Capable of Clean MSn Experiments
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Experiments and Simulations Probing Local Domain Bulge and String Assembly of Aligned Nanoplates in a Lamellar Diblock Copolymer
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The quantum coherent mechanism for singlet fission: experiment and theory
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Mechanism of O2 Activation and Methanol Production by (Di(2-pyridyl)methanesulfonate)PtIIMe(OHn)(2-n)- Complex from Theory with Validation from Experiment
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Rectification of Ion Current in Nanopores Depends on the Type of Monovalent Cations: Experiments and Modeling
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Highly parameterized inverse estimation of hydraulic conductivity and porosity in a three-dimensional, heterogeneous transport experiment: HIGHLY PARAMETERIZED INVERSE ESTIMATION IN 3-D
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On-the-fly machine-learning for high-throughput experiments: search for rare-earth-free permanent magnets
Advanced materials characterization techniques with ever-growing data acquisition speed and storage capabilities represent a challenge in modern materials science, and new procedures to quickly assess and analyze the data are needed. Machine learning approaches are effective in reducing the complexity of data and rapidly homing in on the underlying trend in multi-dimensional data. Here, we show that by employing an algorithm called the mean shift theory to a large amount of diffraction data in high-throughput experimentation, one can streamline the process of delineating the structural evolution across compositional variations mapped on combinatorial libraries with minimal computational cost. Data collected at a synchrotron beamline are analyzed on the fly, and by integrating experimental data with the inorganic crystal structure database (ICSD), we can substantially enhance the accuracy in classifying the structural phases across ternary phase spaces. We have used this approach to identify a novel magnetic phase with enhanced magnetic anisotropy which is a candidate for rare-earth free permanent magnet.