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Precipitation and Co-precipitation

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 Processes

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 Gravimetry

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...

Precipitation Titration: Endpoint Detection Methods

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...

Types of Coprecipitation

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 of Ions

Precipitation of Ions

Predicting Precipitation
The equation that describes the equilibrium between solid calcium carbonate and its solvated ions is:

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Related Experiment Video

Updated: Mar 21, 2026

Continuous Hydrologic and Water Quality Monitoring of Vernal Ponds

Continuous Hydrologic and Water Quality Monitoring of Vernal Ponds

Published on: November 13, 2017

Precipitation-aware sensor ecosystem modelling for performance-driven autonomous vehicle navigation.

Shruti Kalra¹, Ruby Beniwal¹, Narendra Singh Beniwal²

¹Department of Electronics and Communication Engineering, Jaypee Institute of Information Technology, Noida, Uttar Pradesh, 201307, India.

Scientific Reports

|March 20, 2026

Summary

This summary is machine-generated.

This study introduces a new framework for autonomous vehicle navigation in rain. It improves detection precision and reduces false positives by adapting sensors to weather conditions.

Keywords:

Adaptive probabilistic fusion Adverse weather perception Autonomous vehicles Multi-modal sensing Precipitation Severity Index (PSI)Precipitation nowcasting Sensor fusion Sensor reliability

Related Experiment Videos

Last Updated: Mar 21, 2026

Continuous Hydrologic and Water Quality Monitoring of Vernal Ponds

Continuous Hydrologic and Water Quality Monitoring of Vernal Ponds

Published on: November 13, 2017

Area of Science:

Robotics
Computer Vision
Artificial Intelligence

Background:

Autonomous vehicle (AV) navigation is challenged by adverse weather, particularly precipitation.
Current sensor fusion methods often lack adaptability to dynamic environmental conditions and sensor degradation.

Purpose of the Study:

To present a precipitation-aware sensor ecosystem modelling framework for enhanced AV navigation in adverse weather.
To dynamically adjust sensor inputs based on precipitation severity and sensor reliability.

Main Methods:

Integration of spatiotemporal radar-based precipitation nowcasting.
Deep neural network-based sensor degradation modelling.
Adaptive probabilistic sensor fusion for LiDAR, RADAR, and camera data.

Main Results:

Achieved a 31.2% increase in detection precision and a 27.8% reduction in false positives.
Reduced mean perception latency from 51 to 43 ms.
Radar-based rainfall estimation with a mean absolute error of 0.42 mm/h.

Conclusions:

The proposed framework significantly improves AV perception performance under precipitation.
Dynamic sensor adaptation enhances robustness and reliability in adverse weather conditions.
The framework offers a promising approach for all-weather autonomous driving.