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

Data Validation01:15

Data Validation

351
Method validation is a crucial process in analytical chemistry designed to confirm that a given method consistently produces reliable and high-quality results. This process is essential when a method is applied to different sample matrices or when procedural modifications are made, ensuring that the results meet acceptable standards across various applications.
Key parameters for method validation include:
351
Mechanistic Models: Compartment Models in Individual and Population Analysis01:23

Mechanistic Models: Compartment Models in Individual and Population Analysis

119
Mechanistic models are utilized in individual analysis using single-source data, but imperfections arise due to data collection errors, preventing perfect prediction of observed data. The mathematical equation involves known values (Xi), observed concentrations (Ci), measurement errors (εi), model parameters (ϕj), and the related function (ƒi) for i number of values. Different least-squares metrics quantify differences between predicted and observed values. The ordinary least...
119
Molecular Models02:00

Molecular Models

42.2K
Physical models representing molecular architectures of chemical compounds play essential roles in understanding chemistry. The use of molecular models makes it easier to visualize the structures and shapes of atoms and molecules.
42.2K
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

150
Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
150
Atomic Absorption Spectroscopy: Lab01:21

Atomic Absorption Spectroscopy: Lab

770
For AAS measurements, samples must be introduced as clear solutions, often requiring extensive preliminary treatment to dissolve materials like soils, animal tissues, and minerals. Common methods for sample preparation include treatment with hot mineral acids, wet ashing, combustion in closed containers, high-temperature ashing, or fusion with reagents.
 Solutions containing organic solvents, such as low-molecular-mass alcohols, esters, or ketones, enhance absorbances by increasing...
770
Predicting Reaction Outcomes02:24

Predicting Reaction Outcomes

9.0K
Kinetics describes the rate and path by which a reaction occurs. In contrast, thermodynamics deals with state functions and describes the properties, behavior, and components of a system. It is not concerned with the path taken by the process and cannot address the rate at which a reaction occurs. Although it does provide information about what can happen during a reaction process, it does not describe the detailed steps of what appears on an atomic or a molecular level. On the other hand,...
9.0K

You might also read

Related Articles

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

Sort by
Same author

Exploring celecoxib polymorph landscape using AIMNet2 machine learning interatomic potential.

Chemical science·2026
Same author

Are diffusion models ready for materials discovery in unexplored chemical space?

Patterns (New York, N.Y.)·2026
Same author

Platonic representation of foundation machine learning interatomic potentials.

Nature machine intelligence·2026
Same author

Advancing Reproducibility and Open Data in Theoretical and Computational Chemistry.

Journal of chemical theory and computation·2026
Same author

Controlling Electrode-Electrolyte Interactions to Enhance Capacitance.

Journal of the American Chemical Society·2026
Same author

Reactive Machine Learning Interatomic Potentials for Chemistry and Materials Science.

Chemical reviews·2026
Same journal

One-dimensional carbon chains free of end-capping groups.

Nature chemistry·2026
Same journal

Covalency control of photomagnetic relaxation in a manganese(II) photoswitch.

Nature chemistry·2026
Same journal

Trefoil polymers from a knotted synthon.

Nature chemistry·2026
Same journal

Inverted metal-free active template synthesis of rotaxanes via axle‑mediated macrocyclization.

Nature chemistry·2026
Same journal

Serendipitous twist in a hemithioindigo molecular motor enables energy storage.

Nature chemistry·2026
Same journal

Concise synthesis and strain-release diversification of bridgehead-substituted [2]-ladderanes.

Nature chemistry·2026
See all related articles

Related Experiment Video

Updated: Nov 3, 2025

Applying Cheminformatics to Develop a Structure Searchable Database of Analytical Methods
05:34

Applying Cheminformatics to Develop a Structure Searchable Database of Analytical Methods

Published on: June 6, 2025

1.1K

Best practices in machine learning for chemistry

Nongnuch Artrith1,2, Keith T Butler3, François-Xavier Coudert4

  • 1Department of Chemical Engineering, Columbia University, New York, NY, USA. na2782@columbia.edu.

Nature Chemistry
|June 1, 2021
PubMed
Summary

No abstract available in PubMed .

More Related Videos

Constructing and Visualizing Models using Mime-based Machine-learning Framework
06:19

Constructing and Visualizing Models using Mime-based Machine-learning Framework

Published on: July 22, 2025

1.4K

Related Experiment Videos

Last Updated: Nov 3, 2025

Applying Cheminformatics to Develop a Structure Searchable Database of Analytical Methods
05:34

Applying Cheminformatics to Develop a Structure Searchable Database of Analytical Methods

Published on: June 6, 2025

1.1K
Constructing and Visualizing Models using Mime-based Machine-learning Framework
06:19

Constructing and Visualizing Models using Mime-based Machine-learning Framework

Published on: July 22, 2025

1.4K