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

One-Degree-of-Freedom System01:24

One-Degree-of-Freedom System

565
In mechanical engineering, one-degree-of-freedom systems form the basis of a wide range of electrical and mechanical components. Using these models, engineers can predict the behavior of various parts in a larger system, which gives them insight into how different forces interact with each other.
A one-degree-of-freedom system is defined by an independent variable that determines its state and behavior. One example of a one-degree-of-freedom system is a simple harmonic oscillator, such as a...
565
Bending of Material: Problem Solving01:09

Bending of Material: Problem Solving

263
In this lesson, determine the ratio of the maximum bending moments applied to two metal pipes, given that both pipes can withstand a maximum stress of 100 MPa. Both pipes have an outer radius of 1.8 cm. Pipe A has an inner radius of 1.5 cm, and Pipe B has an inner radius of 1 cm. The ratio of the maximum bending moment applied to two metallic pipes, each with a different inner and outer radius, is determined by considering their dimensions. The inner radius of the first pipe is 1.5 cm, and for...
263
Three-Dimensional Force System:Problem Solving01:30

Three-Dimensional Force System:Problem Solving

898
A three-dimensional force system refers to a scenario in which three forces act simultaneously in three different directions. This type of problem is commonly encountered in physics and engineering, where it is necessary to calculate the resultant force on the system, which can then be used to predict or analyze the behavior of the object or structure under consideration.
To solve a three-dimensional force system, first resolve each force into its respective scalar components. Do this using...
898
Degrees of Freedom01:02

Degrees of Freedom

3.5K
The degree of freedom for a particular statistical calculation is the number of values that are free to vary. Thus, the minimum number of independent numbers can specify a particular statistic. The degrees of freedom differ greatly depending on known and uncalculated statistical components.
For example, suppose there are three unknown numbers whose mean is 10; although we can freely assign values to the first and second numbers, the value of the last number can not be arbitrarily assigned.
3.5K
Two-Dimensional Force System: Problem Solving01:29

Two-Dimensional Force System: Problem Solving

702
Solving problems related to two-dimensional force systems is an essential aspect of mechanics and engineering. By applying the principles of vector analysis and force equilibrium, one can determine the effect of multiple forces acting on an object in a two-dimensional space.
The first step to solving a two-dimensional force system problem is to draw a free-body diagram of the object under consideration. This diagram helps identify all the external forces acting on the object, including their...
702
Relative Motion Analysis using Rotating Axes-Problem Solving01:29

Relative Motion Analysis using Rotating Axes-Problem Solving

456
Consider a crane whose telescopic boom rotates with an angular velocity of 0.04 rad/s and angular acceleration of 0.02 rad/s2. Along with the rotation, the boom also extends linearly with a uniform speed of 5 m/s. The extension of the boom is measured at point D, which is measured with respect to the fixed point C on the other end of the boom. For the given instant, the distance between points C and D is 60 meters.
Here, in order to determine the magnitude of velocity and acceleration for point...
456

You might also read

Related Articles

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

Sort by
Same author

Unsupervised and probabilistic learning with Contrastive Local Learning Networks: The Restricted Kirchhoff Machine.

Proceedings of the National Academy of Sciences of the United States of America·2026
Same author

A Predictive Model for Coupling Cell Division Orientation to Tissue Mechanics During Epithelial Morphogenesis.

bioRxiv : the preprint server for biology·2026
Same author

Effect of translational shear on interfacial structure in the viscous fingering instability.

Science advances·2026
Same author

Evolutionary pathways in epistatic mechanical networks.

Proceedings of the National Academy of Sciences of the United States of America·2026
Same author

Training of physical neural networks.

Nature·2025
Same author

Cornerstones are the key stones: using interpretable machine learning to probe the clogging process in 2D granular hoppers.

Soft matter·2025

Related Experiment Video

Updated: Sep 24, 2025

A Virtual Simulation Experiment of Mechanics: Material Deformation and Failure Based on Scanning Electron Microscopy
06:54

A Virtual Simulation Experiment of Mechanics: Material Deformation and Failure Based on Scanning Electron Microscopy

Published on: January 20, 2023

2.4K

Transient learning degrees of freedom for introducing function in materials.

Varda F Hagh1,2, Sidney R Nagel1, Andrea J Liu3

  • 1James Franck Institute, University of Chicago, Chicago, IL 60637.

Proceedings of the National Academy of Sciences of the United States of America
|May 5, 2022
PubMed
Summary
This summary is machine-generated.

Choosing the right "degrees of freedom" is key in material design protocols. Optimizing particle sizes, not stiffness, significantly improves stability in jammed particle packings, offering a new framework for material development.

Keywords:
degrees of freedomjammingmaterial trainingmechanical stabilitymetamaterials

More Related Videos

Studying Large Amplitude Oscillatory Shear Response of Soft Materials
06:07

Studying Large Amplitude Oscillatory Shear Response of Soft Materials

Published on: April 25, 2019

13.0K
Characterizing Dissipative Elastic Metamaterials Produced by Additive Manufacturing
09:39

Characterizing Dissipative Elastic Metamaterials Produced by Additive Manufacturing

Published on: June 28, 2024

1.1K

Related Experiment Videos

Last Updated: Sep 24, 2025

A Virtual Simulation Experiment of Mechanics: Material Deformation and Failure Based on Scanning Electron Microscopy
06:54

A Virtual Simulation Experiment of Mechanics: Material Deformation and Failure Based on Scanning Electron Microscopy

Published on: January 20, 2023

2.4K
Studying Large Amplitude Oscillatory Shear Response of Soft Materials
06:07

Studying Large Amplitude Oscillatory Shear Response of Soft Materials

Published on: April 25, 2019

13.0K
Characterizing Dissipative Elastic Metamaterials Produced by Additive Manufacturing
09:39

Characterizing Dissipative Elastic Metamaterials Produced by Additive Manufacturing

Published on: June 28, 2024

1.1K

Area of Science:

  • Material Science
  • Computational Materials Design
  • Statistical Mechanics

Background:

  • Many material design and training protocols involve introducing new degrees of freedom by relaxing constraints.
  • These degrees of freedom are then evolved based on specific rules to reach a desired material state.
  • Existing protocols lack a unifying framework to understand why some methods are more effective than others.

Purpose of the Study:

  • To develop a unifying framework for understanding material design and training protocols.
  • To identify the critical factors that determine the success of these protocols.
  • To provide insights into optimizing the selection of degrees of freedom for improved material properties.

Main Methods:

  • Development of a theoretical framework unifying diverse material design protocols.
  • Analysis of the impact of different degrees of freedom (e.g., particle size, stiffness) on material properties.
  • Simulation and analysis of jammed particle packing systems.

Main Results:

  • The choice of introduced degrees of freedom significantly impacts protocol effectiveness.
  • Introducing particle sizes as degrees of freedom leads to highly stable states in jammed particle packings.
  • Varying particle stiffnesses as degrees of freedom has a less significant impact on stability.

Conclusions:

  • A unifying framework reveals that the selection of degrees of freedom is crucial for effective material design.
  • Optimizing particle size is a more effective strategy than optimizing stiffness for achieving stable jammed particle packings.
  • This framework can guide the development of more efficient and successful material design protocols.