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Related Concept Videos

Precipitation and Co-precipitation01:17

Precipitation and Co-precipitation

Precipitation and coprecipitation methods can be used to separate a mixture of ions in a solution. In qualitative inorganic analysis, ions that form sparingly soluble precipitates with the same reagent are separated based on the differences in solubility products. For example, consider the separation of Cu(II) and Fe(II) ions by precipitation as insoluble sulfides. First, copper(II) sulfide is precipitated by the addition of acidic H2S, where the dissociation of H2S is suppressed. Adding H2S...
Precipitation Processes01:12

Precipitation Processes

The experimental conditions in a gravimetric analysis should be optimized to maximize the particle size and purity of the obtained precipitate. Ideally, the concentration of the precipitating reagent should be low with effective stirring to maintain low relative supersaturation for the growth of large crystals. In homogeneous precipitation, the precipitant is slowly generated by a chemical reaction in the solution to avoid local reagent excesses. For example, urea decomposes gradually to...
Precipitation Gravimetry01:03

Precipitation Gravimetry

Precipitation gravimetry is based on converting an analyte into a sparingly soluble precipitate, which is separated by filtration and weighed. An ideal precipitate should be pure, insoluble, of known composition, and easily filtered from the reaction mixture.
In determining nickel by gravimetric analysis, a precipitant of ethanolic dimethylglyoxime is added to a hot nickel salt solution. This is quickly followed by the dropwise addition of dilute ammonia solution until precipitation occurs. A...
Types of Coprecipitation01:10

Types of Coprecipitation

Coprecipitation is the contamination of a precipitate by otherwise soluble species and occurs via different processes. In colloidal precipitates, coprecipitation occurs via surface adsorption. For instance, barium sulfate has a primary layer of adsorbed barium ions and a secondary layer of nitrate counterions. This results in contamination of the precipitate by barium nitrate.
Sometimes, ions in a crystal lattice can undergo isomorphous replacement by inclusions of similar charge and size. For...
Precipitation Titration: Endpoint Detection Methods01:19

Precipitation Titration: Endpoint Detection Methods

In argentometric precipitation titrations, endpoints can be detected visually by the Mohr, Volhard, and Fajans methods. In the Mohr method, adding a soluble chromate indicator gives an initial yellow color to the analyte solution. As the titrant is added, the first excess of silver ions forms a red silver chromate precipitate, marking the endpoint. The solution pH should be maintained at about 8 by adding solid CaCO3.
In the Volhard method, a standard excess of AgNO3 is first added to the...
Insensitive Nuclei Enhanced by Polarization Transfer (INEPT)01:15

Insensitive Nuclei Enhanced by Polarization Transfer (INEPT)

Insensitive Nuclei Enhanced by Polarization Transfer (INEPT) is an advanced Nuclear Magnetic Resonance (NMR) technique specifically designed to detect and enhance the signals of low-abundance nuclei, such as carbon-13 and nitrogen-15, in small molecules. The fundamental principle behind INEPT is the transfer of polarization from a more abundant and highly polarizable nucleus, typically hydrogen-1, to the low-abundance nucleus of interest. This process effectively boosts the NMR signal of the...

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Related Experiment Video

Updated: May 10, 2026

Investigating the Relationship between Sea Surface Chlorophyll and Major Features of the South China Sea with Satellite Information
10:28

Investigating the Relationship between Sea Surface Chlorophyll and Major Features of the South China Sea with Satellite Information

Published on: June 13, 2020

Improved El Nino forecasting by cooperativity detection.

Josef Ludescher1, Avi Gozolchiani, Mikhail I Bogachev

  • 1Institut für Theoretische Physik, Justus-Liebig-Universität Giessen, 35392 Giessen, Germany.

Proceedings of the National Academy of Sciences of the United States of America
|July 3, 2013
PubMed
Summary
This summary is machine-generated.

This study introduces a new El Niño prediction method using network analysis. It enables a 12-month forecast, doubling the current early-warning time for this major climate event.

Keywords:
ENSOclimatecross-correlationsdynamic networksspring barrier

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Measurement of the Directional Information Flow in fNIRS-Hyperscanning Data using the Partial Wavelet Transform Coherence Method
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Measurement of the Directional Information Flow in fNIRS-Hyperscanning Data using the Partial Wavelet Transform Coherence Method

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Related Experiment Videos

Last Updated: May 10, 2026

Investigating the Relationship between Sea Surface Chlorophyll and Major Features of the South China Sea with Satellite Information
10:28

Investigating the Relationship between Sea Surface Chlorophyll and Major Features of the South China Sea with Satellite Information

Published on: June 13, 2020

Measurement of the Directional Information Flow in fNIRS-Hyperscanning Data using the Partial Wavelet Transform Coherence Method
08:42

Measurement of the Directional Information Flow in fNIRS-Hyperscanning Data using the Partial Wavelet Transform Coherence Method

Published on: September 3, 2021

Area of Science:

  • Climate Science
  • Oceanography
  • Network Analysis

Background:

  • El Niño events in the eastern equatorial Pacific cause global impacts.
  • Current El Niño forecasting is limited to approximately 6 months.
  • Extended prewarning times are crucial for mitigating damages like harvest failures.

Purpose of the Study:

  • To develop an extended El Niño forecasting scheme.
  • To double the current early-warning period for El Niño events.

Main Methods:

  • Utilizing network methods to analyze emerging teleconnections.
  • Identifying a large-scale cooperative mode linking the El Niño basin and the wider ocean.
  • Employing high-quality observational data from 1950 onwards.

Main Results:

  • A cooperative mode builds up in the year preceding an El Niño event.
  • An efficient 12-month El Niño forecasting scheme was developed.
  • The method achieved hit rates above 0.5 with false-alarm rates below 0.1.

Conclusions:

  • Network analysis provides a novel approach to El Niño prediction.
  • The developed method significantly extends the El Niño early-warning period.
  • This advancement aids in mitigating the global impacts of El Niño events.