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Related Concept Videos

Raman Spectroscopy Instrumentation: Overview01:26

Raman Spectroscopy Instrumentation: Overview

587
A conventional Raman spectrophotometer includes a laser source, a sample holding system, a wavelength selector, and a detector.
The monochromatic laser source, typically using visible or near-infrared radiation, generates a highly focused beam of light. This light interacts with the molecules of the sample, scattering some of the light. Liquid and gaseous samples are usually tested in ordinary glass capillaries, while solids can be analyzed as powders packed in capillaries or as potassium...
587
Raman Spectroscopy: Overview01:20

Raman Spectroscopy: Overview

765
The underlying principle of Raman spectroscopy is based on the interaction between light and matter, specifically molecules' inelastic scattering of photons. When a monochromatic beam of light, typically from a laser source, interacts with a sample, most scattered light has the same frequency as the incident light. This is known as Rayleigh scattering.
However, a small fraction of the scattered light exhibits a frequency shift due to the exchange of energy between the incident photons and...
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Response Surface Methodology01:16

Response Surface Methodology

319
Response Surface Methodology (RSM) is a collection of statistical and mathematical techniques used to develop, improve, and optimize processes. It is particularly valuable when many input variables or factors potentially influence a response variable.
The process of RSM involves several key steps:
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Analysis Methods of Pharmacokinetic Data: Model and Model-Independent Approaches01:14

Analysis Methods of Pharmacokinetic Data: Model and Model-Independent Approaches

252
Drug disposition in the body is a complex process and can be studied using two major approaches: the model and the model-independent approaches.
The model approach uses mathematical models to describe changes in drug concentration over time. Pharmacokinetic models help characterize drug behavior in patients, predict drug concentration in the body fluids, calculate optimum dosage regimens, and evaluate the risk of toxicity. However, ensuring that the model fits the experimental data accurately...
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Mechanistic Models: Compartment Models in Individual and Population Analysis01:23

Mechanistic Models: Compartment Models in Individual and Population Analysis

108
Mechanistic models are utilized in individual analysis using single-source data, but imperfections arise due to data collection errors, preventing perfect prediction of observed data. The mathematical equation involves known values (Xi), observed concentrations (Ci), measurement errors (εi), model parameters (ϕj), and the related function (ƒi) for i number of values. Different least-squares metrics quantify differences between predicted and observed values. The ordinary least...
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Classification of Titrimetric Analysis Based on Reaction Types01:01

Classification of Titrimetric Analysis Based on Reaction Types

913
Titrimetric analysis in solution chemistry involves measuring the volume of solutions and is often called volumetric analysis. The standard solution of known concentration in the burette is called the titrant, whereas the solution of unknown concentration in the flask is called the analyte, or titrand. Titrimetric analyses can be classified into four types based on the reactions between the titrant and analyte.
Titrations between an acid and a base lead to neutralization reactions that form...
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Related Experiment Video

Updated: Oct 14, 2025

An Integrated Raman Spectroscopy and Mass Spectrometry Platform to Study Single-Cell Drug Uptake, Metabolism, and Effects
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Chemometric analysis in Raman spectroscopy from experimental design to machine learning-based modeling.

Shuxia Guo1,2,3, Jürgen Popp2,3, Thomas Bocklitz4,5

  • 1Institute for Brain and Intelligence, Southeast University, Nanjing, China.

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|November 6, 2021
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Summary

This study provides a protocol for Raman spectral analysis, a technique used in biology and diagnostics. It guides users to avoid pitfalls and move Raman spectroscopy from research to real-world applications.

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Area of Science:

  • Analytical Chemistry
  • Spectroscopy
  • Biotechnology

Background:

  • Raman spectroscopy is gaining traction in diverse fields like biology, forensics, and pharmaceutics.
  • Advancements in computational/experimental setups and chemometrics drive this growth.
  • Chemometric techniques analyze subtle spectral differences for sample differentiation.

Purpose of the Study:

  • To provide a standardized protocol for Raman spectral analysis.
  • To guide users in avoiding common pitfalls in Raman spectral data analysis.
  • To facilitate the transition of Raman spectroscopy from proof-of-concept to practical applications.

Main Methods:

  • The protocol covers experimental design, data preprocessing, data learning, and model transfer.
  • It includes strategies for spectral processing and statistical analysis of Raman data.
  • Exemplified using single-cell and spectral imaging datasets from cell and tissue samples.

Main Results:

  • The protocol addresses challenges in Raman spectral analysis, offering solutions for problematic issues.
  • It aims to standardize the analysis process, which is currently not well-defined.
  • Demonstrates a workflow applicable to various Raman spectroscopy applications.

Conclusions:

  • This protocol aims to enhance the reliability and reproducibility of Raman spectral analysis.
  • It empowers researchers to overcome analytical challenges and implement Raman spectroscopy in real-world scenarios.
  • Standardized Raman spectral analysis will accelerate its adoption across scientific and industrial fields.