Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Atomic Absorption Spectroscopy: Lab01:21

Atomic Absorption Spectroscopy: Lab

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.
 Solutions containing organic solvents, such as low-molecular-mass alcohols, esters, or ketones, enhance absorbances by increasing nebulizer...
Atomic Emission Spectroscopy: Overview01:20

Atomic Emission Spectroscopy: Overview

Atomic emission spectroscopy (AES) is an analytical technique used to determine the elemental composition of a sample by analyzing the light emitted from excited atoms. In AES, atoms in a sample are excited to higher energy levels by thermal energy from high-temperature sources, such as plasma, arcs, or sparks. When these excited atoms return to lower energy states, they emit light at specific wavelengths characteristic of each element. The resulting atomic emission spectrum, which consists of...
Atomic Absorption Spectroscopy: Atomization Methods01:25

Atomic Absorption Spectroscopy: Atomization Methods

Atomic Absorption Spectroscopy (AAS) atomizes samples through flame atomization or electrothermal atomization. Flame atomization typically involves a nebulizer and spray chamber assembly to combine the sample with a fuel–oxidant mixture, creating a fine aerosol mist that enters a burner. Typically, the fuel and oxidant are combined in an approximately stoichiometric ratio. However, for atoms that are easily oxidized, a fuel-rich mixture may be more advantageous. Only about 5% of the aerosol...
Atomic Emission Spectroscopy: Lab01:29

Atomic Emission Spectroscopy: Lab

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...
Physical Properties of Amines01:26

Physical Properties of Amines

Amines with low molecular weight are usually gaseous at room temperature, while those with high molecular weight are liquid or solids in nature. Usually, low molecular weight amines have a rotten fish-like smell. Diamines typically have a pungent smell. For instance, cadaverine and putrescine, depicted in Figure 1, are two molecules responsible for decaying tissue.
EDTA: Indirect and Alkalimetric Titration01:23

EDTA: Indirect and Alkalimetric Titration

Unlike direct titration, back-titration, and displacement titration, indirect titration is an EDTA titration method for quantifying anions. In the indirect titration method, anions are precipitated as their insoluble salts with excess metal ions. The filtrate containing the excess metal ions is directly titrated with standard EDTA until the endpoint is achieved. Another approach involves extracting the metal ion and back-titrating with standard EDTA to obtain the endpoint. In this way, the...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Dual-Mode Fluorescence Modulation Using Ferrocene-Dithienylethene-Pyromellitic Diimide-Based Photoswitchable Material: Applications in Cascaded Molecular Logic and in Deciphering Secret Codes.

Chemistry (Weinheim an der Bergstrasse, Germany)·2026
Same author

ψ-BCN monolayers as emerging 2D materials: effects of hydrogen passivation on structure, stability, and functionality.

Physical chemistry chemical physics : PCCP·2026
Same author

Copper-Catalyzed Selective Mononitration of Unbiased <i>ortho</i>-C-H Bonds in Arenes Using a Ball Mill in Air: Excellent Compatibility with Heterocycles.

Organic letters·2026
Same author

Mechanistic Insights Into CO<sub>2</sub> Activation via Phosphorus-Boron Frustrated Lewis Pairs: A Density Functional Theory Study.

Chemphyschem : a European journal of chemical physics and physical chemistry·2026
Same author

NiS<sub>2</sub> nanoparticles: structural, spectroscopic and significant antibacterial properties against series of pathogenic strains.

Preparative biochemistry & biotechnology·2025
Same author

Decarbonative routes to generate <i>N</i>-acyliminium ion intermediates for the synthesis of 3-substituted isoindolinones <i>via</i> an intermolecular amidoalkylation reaction.

Organic & biomolecular chemistry·2025

Related Experiment Video

Updated: Jun 24, 2026

Removal of Arsenic Using a Cationic Polymer Gel Impregnated with Iron Hydroxide
08:01

Removal of Arsenic Using a Cationic Polymer Gel Impregnated with Iron Hydroxide

Published on: June 28, 2019

Arsenic toxicity: an atom counting and electrophilicity-based protocol.

Debesh R Roy1, Santanab Giri, Pratim K Chattaraj

  • 1Department of Chemistry and Centre for Theoretical Studies, Indian Institute of Technology, Kharagpur, India.

Molecular Diversity
|March 28, 2009
PubMed
Summary

This study uses atomic properties like electrophilicity to predict arsenic toxicity. These models can forecast the harmful effects of unknown arsenic compounds.

More Related Videos

Determination of Inorganic Arsenic in a Wide Range of Food Matrices using Hydride Generation - Atomic Absorption Spectrometry.
08:21

Determination of Inorganic Arsenic in a Wide Range of Food Matrices using Hydride Generation - Atomic Absorption Spectrometry.

Published on: September 1, 2017

TD-DFT Guided Advanced E-Eye Sensing Technique for On-site Quantification of Fe, Cr, F, and As in the Environmental, Biological, and Food Samples
09:51

TD-DFT Guided Advanced E-Eye Sensing Technique for On-site Quantification of Fe, Cr, F, and As in the Environmental, Biological, and Food Samples

Published on: September 19, 2025

Related Experiment Videos

Last Updated: Jun 24, 2026

Removal of Arsenic Using a Cationic Polymer Gel Impregnated with Iron Hydroxide
08:01

Removal of Arsenic Using a Cationic Polymer Gel Impregnated with Iron Hydroxide

Published on: June 28, 2019

Determination of Inorganic Arsenic in a Wide Range of Food Matrices using Hydride Generation - Atomic Absorption Spectrometry.
08:21

Determination of Inorganic Arsenic in a Wide Range of Food Matrices using Hydride Generation - Atomic Absorption Spectrometry.

Published on: September 1, 2017

TD-DFT Guided Advanced E-Eye Sensing Technique for On-site Quantification of Fe, Cr, F, and As in the Environmental, Biological, and Food Samples
09:51

TD-DFT Guided Advanced E-Eye Sensing Technique for On-site Quantification of Fe, Cr, F, and As in the Environmental, Biological, and Food Samples

Published on: September 19, 2025

Area of Science:

  • * Computational chemistry and toxicology.
  • * Quantitative Structure-Activity Relationship (QSAR) studies.

Background:

  • * Atomic number (Z) and electrophilicity index (omega) are established toxicity predictors for metal ions.
  • * Arsenic compounds exhibit significant toxicity, necessitating predictive models for risk assessment.

Purpose of the Study:

  • * To utilize global electrophilicity (omega) and atomic properties to explain and predict arsenic derivative toxicity.
  • * To develop regression models for forecasting the toxicity of novel arsenic compounds.

Main Methods:

  • * Employed global electrophilicity (omega), number of nonhydrogenic atoms (N (NH)), local philicity (omega(As)+), and atomic charge (Q (As)) for two arsenic derivative training sets.
  • * Developed and applied regression models based on these descriptors.

Main Results:

  • * Established correlations between electrophilicity, atomic charge, and arsenic toxicity.
  • * Successfully predicted the toxicity of previously uncharacterized arsenic derivatives using the developed models.

Conclusions:

  • * Global and local electrophilicity indices, along with atomic charge, are effective parameters for predicting arsenic toxicity.
  • * The developed QSAR models provide a valuable tool for assessing the toxicological risks of arsenic compounds.