Model-independent particle species disentanglement by X-ray cross-correlation scattering

Pedrini, Bill; Menzel, Andreas; Guzenko, Vitaliy A.; Dávid, Christian; Gutt, Christian

doi:10.1038/srep45618

Cited by 4 publications

(1 citation statement)

References 44 publications

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“…The extraction of three-point and higher correlations from crystals in x-ray experiments is still an active area of study. [36][37][38][39] Impressive strides have been made in energy-resolved scanning tunneling electron microscopy to directly measure SRO domains in alloys, but atomic-level chemical ordering across multiple points in alloy systems is still challenging to quantify. [3,40] Simulation and theory could be used to directly evaluate multi-point chemical ordering to support experimental findings, but it can be challenging to obtain meaningful statistics in substitutional/alloy systems with many degrees of freedom.…”

Section: B)mentioning

confidence: 99%

Quantifying multi-point ordering in alloys

Goff,

Li,

Sinnott

et al. 2021

Preprint

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A central problem in multicomponent lattice systems is to systematically quantify multi-point ordering. Ordering in such systems is often described in terms of pair correlations, even though this is not sufficient when three-point and higher-order interactions are significant. Current models and parameters for multi-point ordering are often only applicable for very specific cases and/or require approximating a subset of correlated occupational variables on a lattice as being uncorrelated. In this work, a multi-point cluster order parameter is introduced to quantify arbitrary multi-point ordering motifs in substitutional systems through direct calculations of normalized cluster probabilities. These parameters can describe multi-point chemical ordering in crystal systems with multiple sublattices, multiple components, and systems with reduced symmetry. These are defined within and applied to quantify four-point chemical ordering motifs in platinum/palladium alloy nanoparticles that are practical interest to the synthesis of catalytic nanocages. Impacts of chemical ordering on alloy nanocage stability are discussed. It is demonstrated that approximating multi-point order parameters from combinations of low-order correlations is not sufficient in cases where multi-point energetics are significant. Conclusions about the formation mechanisms of nanocages may change significantly when using common low-order approximations.

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Section: B)mentioning

confidence: 99%

Quantifying multi-point ordering in alloys

Goff,

Li,

Sinnott

et al. 2021

Preprint

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Latest Insights and Methods in Analyzing Liquid Dense Clusters and Crystal Nucleation

Brognaro

Betzel

2018

Encyclopedia of Analytical Chemistry

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Liquid dense clusters (LDCs) are distinct membrane‐less microcompartments of molecules in aqueous solution, which arise in the process of liquid–liquid phase separation. LDC formation is observed most frequently in vivo during cell development, in neurodegenerative diseases and stress signaling, as well as in vitro, in liquid–solid phase transition. LDCs emerge spaciotemporally depending on the physicochemical environment, surface properties, and conformational flexibility of the molecules involved. Knowledge about structural and dynamic properties of growth and division of different macromolecule LDCs and other clustering phenomena, such as gels and fibers, is till now incomplete and only simplified thermodynamic models are available to predict some aspects of clustering so far. For example, for crystal growth a multistep mechanism is today most commonly accepted, starting with the early formation of LDCs, followed by a self‐organization within this LDCs and initial nucleation of an ordered crystal lattice. Therefore, insights about the LDCs formation and stability will also support directed optimization of macromolecule crystallization and will shed light on physiological LDC processes as well. Furthermore, it will support the establishment of new sample preparation and imaging techniques in structural biology utilizing latest and upcoming X‐ray imaging methods at high‐intensity radiation sources.

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Construction of three-dimensional temperature distribution using a network of ultrasonic transducers

Shen

Chen

Shih

et al. 2019

Sci Rep

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Although the ultrasonic technique for measuring temperature distributions has drawn much attention in recent years, most studies that adopt this technique focus on two-dimensional (2D) systems. Mathematically, extending from 2D to 3D requires higher construction-performing algorithms, as well as more complicated, but extremely crucial, designs of ultrasonic transducer layouts. Otherwise the ill condition of governing-equation matrices will become more serious. Here, we aim at constructing 3D temperature distributions by using a network of properly-installed ultrasonic transducers that can be controlled to transmit and receive ultrasound. In addition, the proposed method is capable of performing this construction procedure in real time, thus monitoring transient temperature distributions and guarantee the safety of operations related to heating or burning. Numerical simulations include constructions for four kinds of temperature distributions, as well as corresponding qualitative and quantitative analyses. Finally, our study offers a guide in developing non-intrusive experimental methods that measure 3D temperature distributions in real time.

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Model-independent particle species disentanglement by X-ray cross-correlation scattering

Cited by 4 publications

References 44 publications

Quantifying multi-point ordering in alloys

Quantifying multi-point ordering in alloys

Latest Insights and Methods in Analyzing Liquid Dense Clusters and Crystal Nucleation

Construction of three-dimensional temperature distribution using a network of ultrasonic transducers

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