Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Sampling Methods: Sample Types

Sampling Methods: Sample Types

Sampling materials are classified into three main types: solid, liquid, and gas.
Solid samples include a variety of substances, such as sediments from water bodies, soil, metals, and biological tissues. Two standard methods for extracting sediments from water bodies are grab sampling and piston coring. Grab sampling involves using a device to collect a discrete sediment sample from the bottom of a water body with minimal disturbance. Grab samples do not always represent the entire area due to...

You might also read

Related Articles

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

Sort by

Same author

Group model-building approach to understand the dynamics and identifying entry points to build resilience in the groundnut value chain in Senegal.

Frontiers in nutrition·2026

Same author

Engineering a Bicistronic Expression System for Mammalian Cell-Based Production of Biofunctional Recombinant Follicle Stimulating Hormone (FSH) of Bos Indicus Origin.

Biotechnology journal·2026

Same author

Quantum interference in a twisted high-Tc SQUID senses emergent interfacial order.

Nature communications·2026

Same author

Distinct lymphocyte immune signatures to nivolumab and recombinant IL-7 ex vivo in patients with sepsis.

Journal of leukocyte biology·2026

Same author

Depression trajectory modifies the association between estimated glucose disposal rate and incident stroke: a prospective cohort study.

BMC cardiovascular disorders·2026

Same author

Directly training on quantized model via gradient scale correction for edge device.

Neural networks : the official journal of the International Neural Network Society·2026

Search research articles

Related Experiment Video

Updated: Jun 25, 2025

Author Spotlight: Standardizing the Development of Amine-Based Silica Composites as CO2 Adsorbents for Direct Air Capture

Author Spotlight: Standardizing the Development of Amine-Based Silica Composites as CO2 Adsorbents for Direct Air Capture

Published on: September 29, 2023

The Open DAC 2023 Dataset and Challenges for Sorbent Discovery in Direct Air Capture.

Anuroop Sriram¹, Sihoon Choi^1,2, Xiaohan Yu²

¹Fundamental AI Research, Meta AI, Meta, Menlo Park, California 94025, United States.

ACS Central Science

|May 27, 2024

Summary

Direct air capture using metal-organic frameworks (MOFs) can combat climate change. Quantum calculations offer a more accurate way to screen MOFs for carbon dioxide removal, improving decarbonization efforts.

More Related Videos

Deposition of Porous Sorbents on Fabric Supports

Deposition of Porous Sorbents on Fabric Supports

Published on: June 12, 2018

Capturing Actively Produced Microbial Volatile Organic Compounds from Human-Associated Samples with Vacuum-Assisted Sorbent Extraction

Capturing Actively Produced Microbial Volatile Organic Compounds from Human-Associated Samples with Vacuum-Assisted Sorbent Extraction

Published on: June 1, 2022

Related Experiment Videos

Last Updated: Jun 25, 2025

Author Spotlight: Standardizing the Development of Amine-Based Silica Composites as CO2 Adsorbents for Direct Air Capture

Author Spotlight: Standardizing the Development of Amine-Based Silica Composites as CO2 Adsorbents for Direct Air Capture

Published on: September 29, 2023

Deposition of Porous Sorbents on Fabric Supports

Deposition of Porous Sorbents on Fabric Supports

Published on: June 12, 2018

Capturing Actively Produced Microbial Volatile Organic Compounds from Human-Associated Samples with Vacuum-Assisted Sorbent Extraction

Capturing Actively Produced Microbial Volatile Organic Compounds from Human-Associated Samples with Vacuum-Assisted Sorbent Extraction

Published on: June 1, 2022

Area of Science:

Materials Science
Environmental Science
Computational Chemistry

Background:

Direct air capture (DAC) is crucial for decarbonization.
Metal-organic frameworks (MOFs) are promising porous adsorbents for CO2 capture.
Previous MOF screening methods for DAC were limited by empirical force fields and ignored water adsorption and framework deformation.

Discussion:

Quantum chemistry calculations provide a more accurate simulation of MOF-CO2 interactions.
This study overcomes limitations of previous screening methods by including H2O adsorption and MOF deformation.
Thousands of MOFs were computationally screened, generating a large dataset.

Key Insights:

Quantum calculations reveal more accurate MOF performance for DAC.
Inclusion of H2O and deformation effects significantly impacts CO2 adsorption in MOFs.
Machine learning models can efficiently describe the large dataset generated by quantum calculations.

Outlook:

The generated data and machine learning models can accelerate the discovery of optimal MOFs for DAC.
This approach facilitates the development of advanced materials for large-scale carbon capture.
Enables more efficient and accurate screening of materials for climate change mitigation technologies.