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

Key Elements for Plant Nutrition02:35

Key Elements for Plant Nutrition

22.0K
Like all living organisms, plants require organic and inorganic nutrients to survive, reproduce, grow and maintain homeostasis. To identify nutrients that are essential for plant functioning, researchers have leveraged a technique called hydroponics. In hydroponic culture systems, plants are grown—without soil—in water-based solutions containing nutrients. At least 17 nutrients have been identified as essential elements required by plants. Plants acquire these elements from the...
22.0K

You might also read

Related Articles

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

Sort by
Same author

Interfacial Engineering of Ru/Ni Hetero-Nanoparticles Embedded in N-Doped Hollow Carbon Polyhedron/Nanotubes Integrated Hierarchical Structures for pH-Universal Hydrogen Evolution.

Chemistry, an Asian journal·2026
Same author

Leveraging large language models and embedding representations for enhanced word similarity computation.

Scientific reports·2025
Same author

Radical-Net: A chemistry-enhanced transformer for elementary radical reactions in pollutant chemistry.

Journal of hazardous materials·2025
Same author

Enhanced tetracycline hydrochloride removal by ultra-microporous phosphorus-doped KOH-activated microalgal biochar: Adsorption performance and mechanistic insights.

Environmental research·2025
Same author

Long-term aging-driven evolution of microplastic ecological risks: New insights from rooftop-deposited microplastics on urban buildings of varying ages.

Journal of hazardous materials·2025
Same author

Placement of an elastic, biohybrid patch in a model of right heart failure with pulmonary artery banding.

Frontiers in bioengineering and biotechnology·2025

Related Experiment Video

Updated: Sep 18, 2025

Two-way Valorization of Blast Furnace Slag: Synthesis of Precipitated Calcium Carbonate and Zeolitic Heavy Metal Adsorbent
11:14

Two-way Valorization of Blast Furnace Slag: Synthesis of Precipitated Calcium Carbonate and Zeolitic Heavy Metal Adsorbent

Published on: February 21, 2017

12.5K

Multi-factor interaction perspective: machine learning-based analysis of Ni2⁺ adsorption onto soil.

Yingdong Wu1,2, Jiang Yu3,4,5, Zixin Zeng1,2

  • 1Department, of Environmental Science and Engineering, College of Architecture and Environment, Sichuan University, 610065, Chengdu, People's Republic of China.

Environmental Geochemistry and Health
|June 19, 2025
PubMed
Summary

Machine learning models revealed that initial nickel (Ni2+) concentration is key to soil adsorption. Interactions between nickel, soil properties, and ionic strength influence its environmental fate and remediation strategies.

Keywords:
Interaction effectMachine learningNickel (Ni2+) adsorptionSoil adsorption

More Related Videos

Two-Dimensional Visualization and Quantification of Labile, Inorganic Plant Nutrients and Contaminants in Soil
12:03

Two-Dimensional Visualization and Quantification of Labile, Inorganic Plant Nutrients and Contaminants in Soil

Published on: September 1, 2020

6.3K
Improving Infrared Spectroscopy Characterization of Soil Organic Matter with Spectral Subtractions
08:57

Improving Infrared Spectroscopy Characterization of Soil Organic Matter with Spectral Subtractions

Published on: January 10, 2019

12.6K

Related Experiment Videos

Last Updated: Sep 18, 2025

Two-way Valorization of Blast Furnace Slag: Synthesis of Precipitated Calcium Carbonate and Zeolitic Heavy Metal Adsorbent
11:14

Two-way Valorization of Blast Furnace Slag: Synthesis of Precipitated Calcium Carbonate and Zeolitic Heavy Metal Adsorbent

Published on: February 21, 2017

12.5K
Two-Dimensional Visualization and Quantification of Labile, Inorganic Plant Nutrients and Contaminants in Soil
12:03

Two-Dimensional Visualization and Quantification of Labile, Inorganic Plant Nutrients and Contaminants in Soil

Published on: September 1, 2020

6.3K
Improving Infrared Spectroscopy Characterization of Soil Organic Matter with Spectral Subtractions
08:57

Improving Infrared Spectroscopy Characterization of Soil Organic Matter with Spectral Subtractions

Published on: January 10, 2019

12.6K

Area of Science:

  • Environmental Science
  • Soil Science
  • Computational Chemistry

Background:

  • Nickel (Ni2+) contamination from industry and agriculture poses ecological and health risks.
  • Understanding nickel adsorption in soils is crucial for environmental management.
  • Previous studies lacked comprehensive analysis of nonlinear and interactive effects on nickel adsorption.

Purpose of the Study:

  • To investigate the nonlinear relationships and interactive effects of various factors on Ni2+ adsorption in soil.
  • To utilize machine learning and SHAP for quantitative analysis of these complex interactions.
  • To identify key factors and their synergistic or antagonistic effects on nickel immobilization in soil.

Main Methods:

  • Analysis of 662 experimental datasets using machine learning models (CatBoost and XGBoost).
  • Application of SHapley Additive exPlanations (SHAP) to interpret model predictions and uncover feature interactions.
  • Evaluation of model performance using test R2 values.

Main Results:

  • CatBoost model outperformed XGBoost (test R2 = 0.85 vs 0.83).
  • Initial Ni2+ concentration (C0) was the most significant factor, followed by ionic strength (IS), solid-to-liquid ratio (SL), clay content, and cation exchange capacity (CEC).
  • Nonlinear effects of SL were observed, with maximum adsorption at low ratios.
  • C0 showed synergistic interactions with CEC and clay content, enhancing Ni2+ immobilization.
  • Elevated IS diminished the synergistic effects of C0 with soil properties.

Conclusions:

  • Machine learning and SHAP provide powerful tools for dissecting complex multifactorial processes in soil science.
  • Initial nickel concentration, soil properties (CEC, clay content), and ionic strength are critical determinants of nickel adsorption.
  • Understanding these interactions is vital for accurate environmental risk assessment and developing effective soil remediation strategies for heavy metal contamination.