Search Results - "Anker, Andy S."

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    Simple Setup Miniaturization with Multiple Benefits for Green Chemistry in Nanoparticle Synthesis by Mathiesen, Jette K, Cooper, Susan R, Anker, Andy S, Kinnibrugh, Tiffany L, Jensen, Kirsten M. Ø, Quinson, Jonathan

    Published in ACS omega (08-02-2022)
    “…The development of nanomaterials often relies on wet-chemical synthesis performed in reflux setups using round-bottom flasks. Here, an alternative approach to…”
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    Journal Article
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    Machine learning for analysis of experimental scattering and spectroscopy data in materials chemistry by Anker, Andy S, Butler, Keith T, Selvan, Raghavendra, Jensen, Kirsten M. Ø

    Published in Chemical science (Cambridge) (13-12-2023)
    “…The rapid growth of materials chemistry data, driven by advancements in large-scale radiation facilities as well as laboratory instruments, has outpaced…”
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    POMFinder : identifying polyoxometallate cluster structures from pair distribution function data using explainable machine learning by Anker, Andy S, Kjær, Emil T S, Juelsholt, Mikkel, Jensen, Kirsten M Ø

    Published in Journal of applied crystallography (01-02-2024)
    “…Characterization of a material structure with pair distribution function (PDF) analysis typically involves refining a structure model against an experimental…”
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    ClusterFinder: a fast tool to find cluster structures from pair distribution function data by Anker, Andy S., Friis-Jensen, Ulrik, Johansen, Frederik L., Billinge, Simon J. L, Jensen, Kirsten M. Ø.

    “…A novel automated high‐throughput screening approach, ClusterFinder, is reported for finding candidate structures for atomic pair distribution function (PDF)…”
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    Atomic structural changes in the formation of transition metal tungstates: the role of polyoxometalate structures in material crystallization by Skjærvø, Susanne Linn, Anker, Andy S, Wied, Magnus C, Kjær, Emil T. S, Juelsholt, Mikkel, Christiansen, Troels Lindahl, Ø. Jensen, Kirsten M

    Published in Chemical science (Cambridge) (10-05-2023)
    “…Material nucleation processes are poorly understood; nevertheless, an atomistic understanding of material formation would aid in the design of material…”
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    Using generative adversarial networks to match experimental and simulated inelastic neutron scattering data by Anker, Andy S, Butler, Keith T, Le, Manh Duc, Perring, Toby G, Thiyagalingam, Jeyan

    Published in Digital discovery (12-06-2023)
    “…Supervised machine learning (ML) models are frequently trained on large datasets of physics-based simulations with the aim of being applied to experimental…”
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    Effect of solvothermal synthesis parameters on the crystallite size and atomic structure of cobalt iron oxide nanoparticles by Aalling-Frederiksen, Olivia, Pittkowski, Rebecca K, Anker, Andy S, Quinson, Jonathan, Klemeyer, Lars, Frandsen, Benjamin A, Koziej, Dorota, Jensen, Kirsten M Ø

    Published in Nanoscale advances (16-09-2024)
    “…We here investigate how the synthesis method affects the crystallite size and atomic structure of cobalt iron oxide nanoparticles. By using a simple…”
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    DeepStruc: towards structure solution from pair distribution function data using deep generative models by Kjær, Emil T S, Anker, Andy S, Weng, Marcus N, Billinge, Simon J L, Selvan, Raghavendra, Jensen, Kirsten M Ø

    Published in Digital discovery (13-02-2023)
    “…Structure solution of nanostructured materials that have limited long-range order remains a bottleneck in materials development. We present a deep learning…”
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    MLstructureMining: a machine learning tool for structure identification from X-ray pair distribution functions by Kjær, Emil T. S, Anker, Andy S, Kirsch, Andrea, Lajer, Joakim, Aalling-Frederiksen, Olivia, Billinge, Simon J. L, Jensen, Kirsten M. Ø

    Published in Digital discovery (15-05-2024)
    “…Synchrotron X-ray techniques are essential for studies of the intrinsic relationship between synthesis, structure, and properties of materials. Modern…”
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    Breaking with the Principles of Coreduction to Form Stoichiometric Intermetallic PdCu Nanoparticles by Mathiesen, Jette K., Bøjesen, Espen D., Pedersen, Jack K., Kjær, Emil T. S., Juelsholt, Mikkel, Cooper, Susan, Quinson, Jonathan, Anker, Andy S., Cutts, Geoff, Keeble, Dean S., Thomsen, Maria S., Rossmeisl, Jan, Jensen, Kirsten M. Ø.

    Published in Small methods (01-06-2022)
    “…Intermetallic nanoparticles (NPs) have shown enhanced catalytic properties as compared to their disordered alloy counterparts. To advance their use in green…”
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    Exploring the Composition Space of High-Entropy Alloy Nanoparticles for the Electrocatalytic H2/CO Oxidation with Bayesian Optimization by Mints, Vladislav A., Pedersen, Jack K., Bagger, Alexander, Quinson, Jonathan, Anker, Andy S., Jensen, Kirsten M. Ø., Rossmeisl, Jan, Arenz, Matthias

    Published in ACS catalysis (16-09-2022)
    “…High-entropy alloy (HEA) electrocatalysts offer a vast composition space that awaits exploration to identify interesting materials for energy conversion…”
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