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

Gradient and Del Operator01:14

Gradient and Del Operator

4.3K
In mathematics and physics, the gradient and del operator are fundamental concepts used to describe the behavior of functions and fields in space. The gradient is a mathematical operator that gives both the magnitude and direction of the maximum spatial rate of change. Consider a person standing on a mountain. The slope of the mountain at any given point is not defined unless it is quantified in a particular direction. For this reason, a "directional derivative" is defined, which is a vector...
4.3K
Implicit Differentiation01:25

Implicit Differentiation

16
In classical mechanics, motion is often described through relationships between spatial coordinates and time. A car moving along a straight highway with constant acceleration serves as a simple case where velocity is an explicit function of time. This scenario results in a linear equation, enabling straightforward analysis using basic differentiation techniques.In contrast, a satellite in circular orbit follows a path defined by an implicit function. The position of the satellite is constrained...
16
Implicit Differentiation: Problem Solving01:29

Implicit Differentiation: Problem Solving

26
Curves defined implicitly, where variables cannot be separated algebraically, require specialized techniques for analysis. The conchoid of Nicomedes exemplifies such a case. Its equation links x and y in a way that prevents isolation of one variable, making implicit differentiation essential to determine the slope and behavior at any point on the curve.The implicit form of the conchoid can be expressed as:To differentiate this equation, y is treated as a function of x, and the chain rule is...
26
Gauss's Law01:07

Gauss's Law

9.4K
If a closed surface does not have any charge inside where an electric field line can terminate, then the electric field line entering the surface at one point must necessarily exit at some other point of the surface. Therefore, if a closed surface does not have any charges inside the enclosed volume, then the electric flux through the surface is zero. What happens to the electric flux if there are some charges inside the enclosed volume? Gauss's law gives a quantitative answer to this question.
9.4K
Fast Decoupled and DC Powerflow01:24

Fast Decoupled and DC Powerflow

726
The fast decoupled power flow method addresses contingencies in power system operations, such as generator outages or transmission line failures. This method provides quick power flow solutions, essential for real-time system adjustments. Fast decoupled power flow algorithms simplify the Jacobian matrix by neglecting certain elements, leading to two sets of decoupled equations:
726
Forced Transdifferentiation01:28

Forced Transdifferentiation

2.3K
Transdifferentiation, also known as lineage reprogramming, was first discovered by Selman and Kafatos in 1974 in silkmoths. They observed that the moths’ cuticle-producing cells transformed into salt-producing cells. Many such cases of natural transdifferentiation occur in organisms. In humans, pancreatic alpha cells can become beta cells. In newts, the loss of the eye’s lens causes the pigmented epithelial cells to transdifferentiate into the lens cells.
Artificial...
2.3K

You might also read

Related Articles

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

Sort by
Same author

New range-separated screened and full-range hybrid functionals.

The Journal of chemical physics·2026
Same author

Exploring quantum active learning for materials design and discovery.

Physical chemistry chemical physics : PCCP·2026
Same author

Seeking metal-organic frameworks for hydrogen storage using classical and quantum active learning.

Physical chemistry chemical physics : PCCP·2025
Same author

Substitutional Cu doping at the cation sites in Ba2YNbO6 toward improved visible-light photoactivity-A first-principles HSE06 study.

The Journal of chemical physics·2024
Same author

Active-learning for global optimization of Ni-Ceria nanoparticles: The case of Ce<sub>4-x</sub>Ni<sub>x</sub>O<sub>8-</sub> <sub>x</sub> (x = 1, 2, 3).

Journal of computational chemistry·2024
Same author

Reinforcement learning for in silico determination of adsorbate-substrate structures.

Journal of computational chemistry·2024
Same journal

Continuous Information Descriptors for Electron Localization: Relativistic Spatial Responses, Nonadditivity, and Chemical Bonding.

Journal of chemical theory and computation·2026
Same journal

Determining Quantum Mechanical Methods Suitable for Quantitative Modeling of Hydrogen Atom Transfer by Halogen Atoms.

Journal of chemical theory and computation·2026
Same journal

Predicting Solvation Free Energies of Molecules and Ions via First-Principles and Machine-Learning Molecular Dynamics.

Journal of chemical theory and computation·2026
Same journal

Connection between <i>GW</i> and Extended Coupled Cluster.

Journal of chemical theory and computation·2026
Same journal

Resolving Local and Global Conformational Heterogeneity of the Human Intrinsically Disordered Proteome.

Journal of chemical theory and computation·2026
Same journal

Molecular Modeling of Surfactant Interaction on Phospholipid Bilayers Mimicking Corneal Epithelium.

Journal of chemical theory and computation·2026
See all related articles

Related Experiment Video

Updated: Jan 16, 2026

Excitonic Hamiltonians for Calculating Optical Absorption Spectra and Optoelectronic Properties of Molecular Aggregates and Solids
08:04

Excitonic Hamiltonians for Calculating Optical Absorption Spectra and Optoelectronic Properties of Molecular Aggregates and Solids

Published on: May 27, 2020

8.9K

Toward Versatility: A Flexible Generalized Gradient Approximation Exchange Functional.

Sankha Ghosh1, Amr Oshi1, Dennis R Salahub1

  • 1Department of Chemistry, Department of Physics and Astronomy, CMS - Center for Molecular Simulation, IQST - Institute for Quantum Science and Technology, Quantum Alberta, University of Calgary, 2500 University Drive NW, Calgary, Alberta Canada, T2N 1N4.

Journal of Chemical Theory and Computation
|September 26, 2025
PubMed
Summary
This summary is machine-generated.

Researchers developed the Ghosh-Oshi-Salahub (GOS) exchange functional, a versatile tool for generalized gradient approximation (GGA) calculations. GOS accurately predicts properties for diverse systems, outperforming existing functionals.

More Related Videos

Identification and Classification of Position-specific GABAA Receptor Subunit Missense Variants for Their Role In Hippocampal Pyramidal Neurons
08:04

Identification and Classification of Position-specific GABAA Receptor Subunit Missense Variants for Their Role In Hippocampal Pyramidal Neurons

Published on: June 6, 2025

1.4K
Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns
13:44

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns

Published on: August 30, 2013

43.6K

Related Experiment Videos

Last Updated: Jan 16, 2026

Excitonic Hamiltonians for Calculating Optical Absorption Spectra and Optoelectronic Properties of Molecular Aggregates and Solids
08:04

Excitonic Hamiltonians for Calculating Optical Absorption Spectra and Optoelectronic Properties of Molecular Aggregates and Solids

Published on: May 27, 2020

8.9K
Identification and Classification of Position-specific GABAA Receptor Subunit Missense Variants for Their Role In Hippocampal Pyramidal Neurons
08:04

Identification and Classification of Position-specific GABAA Receptor Subunit Missense Variants for Their Role In Hippocampal Pyramidal Neurons

Published on: June 6, 2025

1.4K
Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns
13:44

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns

Published on: August 30, 2013

43.6K

Area of Science:

  • Computational Chemistry
  • Materials Science
  • Quantum Mechanics

Background:

  • Generalized Gradient Approximation (GGA) functionals are crucial for accurate electronic structure calculations.
  • Existing GGA functionals like PBE and WC have limitations in describing diverse chemical and solid-state systems.
  • A need exists for a versatile GGA functional applicable across various material types and bonding regimes.

Purpose of the Study:

  • To develop a novel, flexible exchange (X) functional named Ghosh-Oshi-Salahub (GOS).
  • To achieve unified accuracy for thermochemistry of molecules, transition metal compounds, and solids.
  • To outperform established PBE and WC X functionals in predicting material properties.

Main Methods:

  • Construction of the GOS functional based on a rational framework with two tunable parameters.
  • Interpolation across different density variation regimes (slow, moderate, rapid).
  • Rigorous satisfaction of ab initio constraints while ensuring numerical stability and analytical simplicity.

Main Results:

  • The GOS functional demonstrates superior performance in predicting the thermochemistry of the G2 set molecules.
  • Accurate prediction of lattice constants for periodic solids with varying conductivity.
  • Outperforms PBE and WC X functionals across a broad range of chemical and solid-state applications.

Conclusions:

  • GOS is a versatile and accurate GGA functional recommended for general use.
  • Its performance makes it suitable for constructing hybrid functionals and pseudopotentials.
  • Enables advanced molecular and solid-state applications with high accuracy.