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Inductively Coupled Plasma Atomic Emission Spectroscopy: Instrumentation01:26

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Inductively coupled plasma (ICP) is the common plasma source used in atomic emission spectroscopy (AES), a technique that detects and analyzes various elements in a sample. This method is often called inductively coupled plasma atomic emission spectroscopy (ICP-AES).
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Atomic Fluorescence Spectroscopy01:29

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Atomic fluorescence spectroscopy (AFS) is an analytical technique that involves the electronic transitions of atoms in a flame, furnace, or plasma being excited by electromagnetic (EM) radiation. When these atoms absorb energy, they become excited and subsequently release energy as they return to their original state. This emitted light, or "fluorescence," is observed at a right angle to the incident beam. Both absorption and emission processes transpire at distinct wavelengths, which...
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Atomic Absorption Spectroscopy: Instrumentation01:22

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An atomic absorption spectrophotometer (AAS) comprises several components: a radiation source, an atomizer, a monochromator, and a detector. The radiation source can be a hollow-cathode lamp (HCL) or an electrodeless-discharge lamp (EDL), both of which provide a narrow emission line of the required wavelength. However, some instruments use continuum sources and high-resolution monochromators to achieve a narrow range of radiation.
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AES is a powerful analytical technique, especially effective when used with plasma sources, producing abundant spectra in characteristic emission lines. The Inductively Coupled Plasma (ICP), in particular, yields superior quantitative analytical data due to its high stability, low noise, low background, and minimal interferences under optimal experimental conditions. However, newer air-operated microwave sources are emerging as promising alternatives that could be more cost-effective than...
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Atomic Absorption Spectroscopy: Overview01:27

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Atomic absorption spectroscopy (AAS) is a technique used to analyze elements by measuring electromagnetic radiation (EMR) absorbed by atoms, which causes them to transition to a higher-energy orbit. The most crucial step in AAS is atomization, where the analyte is converted into gas-phase atoms, typically through a flame or furnace. Some of these atoms become thermally excited in the flame, while most remain in the ground state.
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Atomic Absorption Spectroscopy: Lab01:21

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For AAS measurements, samples must be introduced as clear solutions, often requiring extensive preliminary treatment to dissolve materials like soils, animal tissues, and minerals. Common methods for sample preparation include treatment with hot mineral acids, wet ashing, combustion in closed containers, high-temperature ashing, or fusion with reagents.
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Spot Variation Fluorescence Correlation Spectroscopy for Analysis of Molecular Diffusion at the Plasma Membrane of Living Cells
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Diffuse Correlation Spectroscopy Analysis Implemented on a Field Programmable Gate Array.

Wei Lin1, David R Busch2, Chia Chieh Goh1

  • 1Stony Brook University, Stony Brook, NY 11794 USA.

IEEE Access : Practical Innovations, Open Solutions
|May 28, 2020
PubMed
Summary
This summary is machine-generated.

A new hardware analyzer using Field Programmable Gate Array (FPGA) technology significantly speeds up Diffusive Correlation Spectroscopy (DCS) analysis. This innovation overcomes computational barriers, enabling real-time blood perfusion measurements for clinical applications.

Keywords:
Diffuse Correlation SpectroscopyField Programmable Gate ArrayHigh Performance Computing

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Area of Science:

  • Biomedical Optics
  • Medical Instrumentation
  • Signal Processing

Background:

  • Diffusive Correlation Spectroscopy (DCS) is an optical technique for measuring deep tissue blood perfusion.
  • Current DCS analysis relies on computationally intensive non-linear curve fitting, hindering real-time clinical use.
  • Real-time processing, instrument size, and simplicity are crucial for clinical DCS deployment.

Purpose of the Study:

  • To mitigate the computational bottleneck in DCS analysis.
  • To develop a hardware analyzer for efficient DCS data processing.
  • To enable real-time DCS applications requiring mobility and speed.

Main Methods:

  • Developed a hardware analyzer using Field Programmable Gate Array (FPGA) technology.
  • Implemented the DCS non-linear curve fitting algorithm on digital logic circuits.
  • Integrated the FPGA analyzer with existing auto-correlator hardware for a complete solution.

Main Results:

  • The FPGA-based hardware analyzer significantly reduces computational load compared to software solutions.
  • The analyzer enables efficient, real-time processing of multiple DCS data channels.
  • Demonstrated utility in pre-clinical large animal studies of spinal cord ischemia.

Conclusions:

  • The FPGA hardware analyzer effectively addresses the computational challenges of DCS.
  • This development facilitates a device-on-a-chip solution for DCS signal processing.
  • The innovation paves the way for mobile and real-time DCS applications in clinical settings.