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Quantifying X-Ray Fluorescence Data Using MAPS14:58

Quantifying X-Ray Fluorescence Data Using MAPS

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Here, we demonstrate the use of the X-ray fluorescence fitting software, MAPS, created by Argonne National Laboratory for the quantification of fluorescence microscopy data. The quantified data that results is useful for understanding the elemental distribution and stoichiometric ratios within a sample of interest.
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Using modern plastic extrusion and printing technologies, it is now possible to quickly and inexpensively produce physical models of X-ray CT data taken in a laboratory. The three -dimensional printing of tomographic data is a powerful visualization, research, and educational tool that may now be accessed by the preclinical imaging...
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How Data are Classified: Numerical Data00:59

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Data that are countable or measurable in specific units are called numerical or quantitative data. Quantitative data are always numbers. Quantitative data are the result of counting or measuring the attributes of a population. Amount of money, pulse rate, weight, number of people living in a town, and number of students who opt for statistics are examples of quantitative data.
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How Data are Classified: Categorical Data01:11

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A variable, usually notated by capital letters such as X and Y, is a characteristic or measurement that can be determined for each member of a population. Data are the actual values of variables. They may be numbers, or they may be words. Datum is a single value.
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Fixed Target Serial Data Collection at Diamond Light Source06:19

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We present a comprehensive guide to fixed target sample preparation, data collection, and data processing for serial synchrotron crystallography at Diamond beamline I24.
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Video Experimental Relacionado

Updated: Jan 20, 2026

Quantifying X-Ray Fluorescence Data Using MAPS
14:58

Quantifying X-Ray Fluorescence Data Using MAPS

Published on: February 17, 2018

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Reconstrucción de datos de rayos X a partir de muestreo de datos incompleto

Kárel García Medina1,2, Ernesto Estevez Rams2, Reinhard B Neder1

  • 1Lehrstuhl für Kristallographie und Strukturphysik, Friedrich-Alexander-Universität Erlangen-Nürnberg, Germany.

Journal of applied crystallography
|January 19, 2026
PubMed
Resumen
Este resumen es generado por máquina.

Este estudio presenta un método novedoso para reconstruir datos faltantes en patrones de difracción, crucial para experimentos que utilizan múltiples detectores. El algoritmo modificado de Papoulis-Gerchberg rellena eficazmente las lagunas, mejorando la integridad de los datos en el análisis de difracción.

Palabras clave:
Papoulis-Gerchbergdifracción de rayos Xmuestreo

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Área de la Ciencia:

  • Física de la difracción
  • Reconstrucción de imágenes
  • Procesamiento de señales

Sus antecedentes:

  • Los patrones de difracción pueden tener datos faltantes debido a configuraciones experimentales, como huecos entre detectores.
  • Los datos de difracción incompletos limitan la precisión y la integridad del análisis estructural.

Objetivo del estudio:

  • Proponer y validar un procedimiento novedoso para reconstruir información de señal faltante en patrones de difracción.
  • Adaptar el algoritmo de Papoulis-Gerchberg para la reconstrucción de datos de difracción.

Principales métodos:

  • Desarrollo de un algoritmo modificado de Papoulis-Gerchberg adaptado a patrones de difracción.
  • Formulación matemática del algoritmo de reconstrucción.
  • Prueba del algoritmo utilizando datos de difracción simulados y experimentales.

Principales resultados:

  • El algoritmo propuesto reconstruye con éxito la señal faltante en los patrones de difracción.
  • Demostró robustez y rendimiento en varios casos simulados y experimentales.
  • Manejo eficaz de las características del patrón de difracción sin pérdida de generalidad.

Conclusiones:

  • El algoritmo modificado de Papoulis-Gerchberg proporciona una solución fiable para reconstruir datos de difracción faltantes.
  • Este método mejora la utilidad de los experimentos de difracción con cobertura angular incompleta.
  • El procedimiento validado mejora la integridad de los análisis basados en difracción.