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相关概念视频

Inductively Coupled Plasma Atomic Emission Spectroscopy: Instrumentation01:26

Inductively Coupled Plasma Atomic Emission Spectroscopy: Instrumentation

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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).
There are three main types of inductively coupled plasma atomic emission spectroscopy  (ICP-AES) instruments: sequential, simultaneous multichannel, and Fourier transform instruments, with the latter being less commonly used....
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Aliasing01:18

Aliasing

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Accurate signal sampling and reconstruction are crucial in various signal-processing applications. A time-domain signal's spectrum can be revealed using its Fourier transform. When this signal is sampled at a specific frequency, it results in multiple scaled replicas of the original spectrum in the frequency domain. The spacing of these replicas is determined by the sampling frequency.
If the sampling frequency is below the Nyquist rate, these replicas overlap, preventing the original...
133
¹H NMR: Interpreting Distorted and Overlapping Signals01:02

¹H NMR: Interpreting Distorted and Overlapping Signals

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Spin systems where the difference in chemical shifts of the coupled nuclei is greater than ten times J are called first-order spin systems. These nuclei are weakly coupled, and their chemical shifts and coupling constant can generally be estimated from the well-separated signals in the spectrum.
As Δν decreases and the signals move closer, the doublets appear increasingly distorted. The intensities of the inner lines increase at the cost of those of the outer lines as the signals are...
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Upsampling01:22

Upsampling

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Managing signal sampling rates is essential in digital signal processing to maintain signal integrity. A decimated signal, characterized by a reduced frequency range due to its lower sampling rate, can be upsampled by inserting zeros between each sample. This upsampling process expands the original spectrum and introduces repeated spectral replicas at intervals dictated by the new Nyquist frequency. To refine this zero-inserted sequence, it is passed through a lowpass filter with a cutoff...
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Atomic Emission Spectroscopy: Instrumentation01:22

Atomic Emission Spectroscopy: Instrumentation

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The instrumentation of atomic emission spectrometry (AES) involves various components, including atomization devices that convert samples into gas-phase atoms and ions. There are two main types of atomization devices: continuous and discrete atomizers.  Continuous atomizers, like plasmas and flames, introduce samples in a constant stream, while discrete atomizers inject individual samples using syringes or autosamplers. The most common discrete atomizer is the electrothermal atomizer.
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Bandpass Sampling01:17

Bandpass Sampling

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In signal processing, bandpass sampling is an effective technique for sampling signals that have most of their energy concentrated within a narrow frequency band. This type of signal is known as a bandpass signal. The key principle of bandpass sampling involves sampling the signal at a rate that is greater than twice the signal's bandwidth to prevent aliasing.
A bandpass signal has a spectrum with a lower frequency limit, denoted as ω1, and an upper frequency limit, denoted as ω2....
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相关实验视频

Updated: Jun 29, 2025

ARL Spectral Fitting as an Application to Augment Spectral Data via Franck-Condon Lineshape Analysis and Color Analysis
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代优化技术的开发:使用小规模的料框架模拟器选择纯组件光谱.

Samuel Henson1, Adam J Rish1, Md Anik Alam2

  • 1Duquesne University Graduate School for Pharmaceutical Sciences, Pittsburgh, PA 15282, USA.

International journal of pharmaceutics
|April 4, 2024
PubMed
概括

代优化技术 (IOT) 为在制药制造中使用近红外 (NIR) 频谱预测API功效提供了较低的校准负担. 这项研究通过确保纯成分光谱条件代表混合物光谱来证明准确的预测.

关键词:
代优化技术 (IOT) 是一种最小的校准最小校准在NIR中,NIR是NIR.这就是PATAT PATAT.纯元件模型 纯元件模型一个小规模的模拟器.

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科学领域:

  • 制药制造业 制药制造业 制药制造业
  • 光谱过程分析技术 (PAT)
  • 化学测量 化学测量 化学测量

背景情况:

  • 光谱PAT可在制药生产中进行线上数据收集.
  • 部分最小平方 (PLS) 模型用于从PAT数据中预测API功率是常见的,但其校准负担很高.
  • 纯组件方法,如代优化技术 (IOT),可以减少校准负担.

研究的目的:

  • 为了解决IOT算法的假设,关于PAT应用的光谱收集条件.
  • 为了评估IOT在预测API功效中的有效性,从线式NIR频谱中进行预测.
  • 通过仔细选择纯成分光谱集来优化IOT模型性能.

主要方法:

  • 利用代优化技术 (IOT) 来从近红外线 (NIR) 光谱中预测API功率.
  • 采用了停滞和动态纯成分光谱的组合.
  • 使用了一组混合样本的开发集来指导代表性纯成分光谱集的选择.
  • 使用开发和测试集的指标评估模型性能.

主要成果:

  • 通过将IOT与用于光谱选择的开发集相结合,可以实现准确的API功效预测.
  • 通过开发集上的模型性能指标确定了最佳的纯成分光谱集.
  • 该研究表明,纯成分光谱收集条件需要代表混合光谱,不一定是相同的.

结论:

  • 物联网和开发集的结合有效地预测了制药制造中的API功效.
  • 关于光谱收集条件的IOT假设应该被视为代表性要求,而不是严格协调.
  • 这种方法增强了IOT在具有挑战性的制药制造环境中的应用.