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Related Concept Videos

Precipitation Gravimetry01:03

Precipitation Gravimetry

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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...
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The moisture content of aggregates is a crucial factor in construction, particularly in concrete mixing, as it influences the total water required in the mix. Moisture content represents the water coated on the exterior surface of the aggregate existing in a saturated and surface-dry condition. The total water content of a moist aggregate is the sum of its moisture content and water absorption.
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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...
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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...
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Related Experiment Video

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In Situ Soil Moisture Sensors in Undisturbed Soils
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A global long-term daily multilayer soil moisture dataset derived from machine learning.

Zeyang Wei1,2, Lifei Wei3,4, Ting Wang5

  • 1Faculty of Resources and Environmental Science, Hubei University, Wuhan, 430062, China.

Scientific Data
|December 15, 2025
PubMed
Summary

A new global soil moisture dataset (SWSM) provides daily, high-resolution estimates for deep soil layers. This valuable resource aids hydrologic modeling and agricultural water management.

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Area of Science:

  • Earth Science
  • Hydrology
  • Data Science

Background:

  • Soil moisture is crucial for Earth's energy and water cycles.
  • Existing soil moisture products often lack continuous, high-resolution data for deeper soil layers.

Purpose of the Study:

  • To generate a global, daily, seamless multilayer soil moisture dataset (SWSM) covering 2002-2021.
  • To provide estimates for three distinct soil depth horizons (0-10 cm, 10-30 cm, 30-60 cm) at a 0.05° spatial resolution.

Main Methods:

  • Utilized a machine learning approach (XGBoost) to create the SWSM dataset.
  • Leveraged in situ observations for rigorous validation of the generated data.

Main Results:

  • The SWSM dataset demonstrates high accuracy, with Pearson correlation coefficients > 0.90 and RMSE < 0.05 across all depths.
  • Feature importance analysis confirmed the dataset's physical consistency and depth-dependent hydrological patterns.

Conclusions:

  • The SWSM dataset offers long-term temporal coverage, fine spatial resolution, and a multi-layer structure.
  • This dataset is a valuable resource for hydrologic modeling, agricultural water management, and climate change studies.