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

Polymer Classification: Crystallinity

Polymer Classification: Crystallinity

Unlike ionic or small covalent molecules, polymers do not form crystalline solids due to the diffusion limitations of their long-chain structures. However, polymers contain microscopic crystalline domains separated by amorphous domains.
Crystalline domains are the regions where polymer chains are aligned in an orderly manner and held together in proximity by intermolecular forces. For example, chains in the crystalline domains of polyethylene and nylon are bound together by van der Waals...

You might also read

Related Articles

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

Sort by

Same author

Pain-free survival after endoscopic neurotomy versus radiofrequency ablation of the C2 dorsal root ganglion for cervicogenic headache: a real-world comparison study.

Frontiers in pain research (Lausanne, Switzerland)·2026

Same author

Combined application of straw and biochar: reducing nitrogen fertilizer demand and enhancing soybean yield.

Frontiers in plant science·2026

Same author

Bridged h-BN Nanosheets Coatings: Simultaneous Shielding Atomic-Oxygen Irradiation and Achieving Superior Friction Performance.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)·2026

Same author

Soil-borne diseases in medicinal plants: linking allelopathy and host immunity to microbiome-based interventions.

Frontiers in plant science·2026

Same author

Ultrasound-Assisted Zwitterion Grafting on NiO<sub>x</sub> for Suppressing Self-Assembled Monolayer Migration in Perovskite Solar Cells.

Advanced materials (Deerfield Beach, Fla.)·2026

Same author

Interlayer-Surface Synergistic Regulation in High-Entropy O3-Type Layered Oxides Toward Structurally Robust and Air-Stable Sodium-Ion Batteries.

Small (Weinheim an der Bergstrasse, Germany)·2026

Same journal

Bioinspired Artificial Bioenergetic Organelles: Design Principles, Nanofabrication and Therapeutic Translation.

Advanced materials (Deerfield Beach, Fla.)·2026

Same journal

Advanced Electrolyte Materials Design for High-Energy Lithium Metal Batteries Beyond 500 Wh Kg<sup>-1</sup>.

Advanced materials (Deerfield Beach, Fla.)·2026

Same journal

Hydrophilic-Stable Nucleoside-Based Hydrogen-Bonded Organic Frameworks (N-HOF) for Therapeutic Bacterial Hybrid Systems.

Advanced materials (Deerfield Beach, Fla.)·2026

Same journal

Lanthanide-Bridged Dual-Atom Catalysts for Efficient Chlorine Electrosynthesis.

Advanced materials (Deerfield Beach, Fla.)·2026

Same journal

Composite Liquid Marble Templated Millimetric Capsule With Tunable Rigidity, Porosity, and Thermal Reconfigurability Toward 3D Cell Culture.

Advanced materials (Deerfield Beach, Fla.)·2026

Same journal

Bias-Triggered Conductivity Relaxation (BCR): A Unique Tool to Simultaneously Investigate Thermodynamics, Kinetics, and Electrostatic Effects of Oxygen Reactions in MIEC Thin Films.

Advanced materials (Deerfield Beach, Fla.)·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Jun 10, 2026

Indirect Fabrication of Lattice Metals with Thin Sections Using Centrifugal Casting

Indirect Fabrication of Lattice Metals with Thin Sections Using Centrifugal Casting

Published on: May 14, 2016

Inverse Design of Amorphous Materials With Targeted Properties.

Jonas A Finkler¹, Yan Lin², Tao Du³

¹Department of Chemistry and Bioscience, Aalborg University, Aalborg Øst, Denmark.

Advanced Materials (Deerfield Beach, Fla.)

|June 9, 2026

Summary

This summary is machine-generated.

Researchers developed AMDEN, a novel inverse design framework using diffusion models to generate amorphous materials for energy storage and catalysis. This method addresses challenges in creating relaxed structures, paving the way for accelerated materials discovery.

Keywords:

accelerated materials discovery amorphous materials inverse design machine learning

More Related Videos

Negative Additive Manufacturing of Complex Shaped Boron Carbides

Negative Additive Manufacturing of Complex Shaped Boron Carbides

Published on: September 18, 2018

Synthesis and Characterization of Functionalized Metal-organic Frameworks

Synthesis and Characterization of Functionalized Metal-organic Frameworks

Published on: September 5, 2014

Related Experiment Videos

Last Updated: Jun 10, 2026

Indirect Fabrication of Lattice Metals with Thin Sections Using Centrifugal Casting

Indirect Fabrication of Lattice Metals with Thin Sections Using Centrifugal Casting

Published on: May 14, 2016

Negative Additive Manufacturing of Complex Shaped Boron Carbides

Negative Additive Manufacturing of Complex Shaped Boron Carbides

Published on: September 18, 2018

Synthesis and Characterization of Functionalized Metal-organic Frameworks

Synthesis and Characterization of Functionalized Metal-organic Frameworks

Published on: September 5, 2014

Area of Science:

Materials Science
Computational Materials Science
Machine Learning

Background:

Amorphous materials like glasses are crucial for energy storage, nonlinear optics, and catalysis.
Their disordered structure offers vast design potential but is challenging to model.
Current inverse design methods are less developed for amorphous materials due to data limitations and simulation cell size requirements.

Purpose of the Study:

To propose and validate an inverse design method for generating amorphous material structures.
To address the challenges of diffusion models in creating relaxed amorphous material configurations.
To introduce new amorphous material datasets for framework evaluation and future research.

Main Methods:

Developed AMDEN (Amorphous Material DEnoising Network), a diffusion model-based framework.
Introduced an energy-based AMDEN variant incorporating Hamiltonian Monte Carlo refinement.
Created diverse amorphous material datasets with varying properties and compositions.

Main Results:

Demonstrated the effectiveness of the AMDEN framework in generating amorphous material structures.
Showcased the capability of the energy-based variant to produce relaxed, low-energy configurations.
Provided new datasets to facilitate further research in amorphous material design.

Conclusions:

AMDEN offers a promising approach for the inverse design of amorphous materials.
The integration of Hamiltonian Monte Carlo refinement is key to generating realistic, relaxed structures.
The developed datasets will accelerate the discovery and design of novel amorphous materials.