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

Van de Graaff Generator01:15

Van de Graaff Generator

2.1K
Van de Graaff generators (or Van de Graaffs) are devices used to demonstrate high voltage due to static electricity that can also be used for research. Robert Van de Graaff first built one in 1931 (based on original suggestions by Lord Kelvin) for use in nuclear physics research.
Van de Graaff uses both smooth and pointed surfaces, conductors, and insulators to generate large static charges and, hence, large voltages. A substantial excess charge can be deposited on the sphere because it moves...
2.1K
DC Generator01:19

DC Generator

1.6K
An alternator converts mechanical energy into electrical energy that varies sinusoidally, resulting in AC current. Meanwhile, a DC generator converts mechanical energy into electrical energy, which are DC pulses with the same polarity. The construction of a DC generator is similar to that of an alternator, except that the pair of slip rings is replaced by a single split ring, also called a commutator. The commutator functions like a periodic rotary switch; it changes the contacts with the...
1.6K
Synthetic Biology02:55

Synthetic Biology

5.2K
Synthetic biology is an interdisciplinary science that involves using principles from disciplines such as engineering, molecular biology, cell biology, and systems biology. It involves remodeling existing organisms from nature or constructing completely new synthetic organisms for applications such as protein or enzyme production, bioremediation, value-added macromolecule production, and the addition of desirable traits to crops, to name a few.
Golden rice
Golden rice is a genetically modified...
5.2K
Non-equilibrium in the Cell01:16

Non-equilibrium in the Cell

5.1K
An important concept in studying metabolism and energy is that of chemical equilibrium. Most chemical reactions are reversible. They can proceed in both directions, releasing energy into their environment in one direction, and absorbing it from the environment in the other direction. The same is true for the chemical reactions involved in cell metabolism, such as the breaking down and building up of proteins into and from individual amino acids, respectively. Reactants within a closed system...
5.1K
Inductive Effects on Chemical Shift: Overview01:27

Inductive Effects on Chemical Shift: Overview

1.8K
The protons in unsubstituted alkanes are strongly shielded with chemical shifts below 1.8 ppm. Methine, methylene, and methyl protons appear at approximately 1.7, 1.2 and 0.7 ppm, while the proton signal from methane appears at 0.23 ppm. An electronegative substituent, such as chlorine, withdraws the electron density from the protons, increasing their chemical shift. Progressive substitution of the hydrogens in methane by chlorine shifts the proton signals increasingly downfield, to 3.05 ppm in...
1.8K
Gravimetry: Inorganic And Organic Precipitating Agents00:49

Gravimetry: Inorganic And Organic Precipitating Agents

4.0K
In gravimetry, the precipitant is chosen carefully to obtain a pure solid that can be easily filtered. Common inorganic precipitants can be used to determine several cations and anions. In some cases, the formation of the same precipitate can be used to determine the cation and the anion. For example, the reaction of barium and chromate ions to give barium chromate is used to determine both barium and chromate. However, precipitates such as hydroxides, oxalates, and metal ammonium phosphates...
4.0K

You might also read

Related Articles

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

Sort by
Same author

Interplay between Slow Chirality Inversion and Slow Guest Uptake in a Triple-Helical Closed-Cage Metallocryptand.

Journal of the American Chemical Society·2026
Same author

Sterically protected π-electron systems for efficient solid-state photon upconversion.

Nature communications·2026
Same author

Genome-wide association and multi-omics functional screens reveal the genetic architecture of foveal development.

medRxiv : the preprint server for health sciences·2026
Same author

Theoretical investigation of catalytic oxidation of benzyl alcohol by Au, Cu and Au-Cu nanoclusters.

Physical chemistry chemical physics : PCCP·2026
Same author

Asymmetric alloying for heterogeneous metal-ion clusters of chiral-at-carbon CAu<sup>I</sup><sub>4</sub>Ag<sup>I</sup><sub>6</sub> polyhedra exhibiting red to near-infrared photoluminescence.

Nature communications·2026
Same author

Role of Second Halogen Atoms of Dihalobenzene in Controlling the Photoluminescence Properties of Single-Walled Carbon Nanotubes by Reductive Arylation.

ACS nanoscience Au·2026
Same journal

Grammatical evolution-based design of nucleotic analogs for SARS-CoV-2's replication-transcription complex.

Physical chemistry chemical physics : PCCP·2026
Same journal

Optical frequency comb Fourier transform spectroscopy of the CH<sub>2</sub><sup>79</sup>Br<sup>81</sup>Br, CH<sub>2</sub><sup>79</sup>Br<sub>2</sub>, and CH<sub>2</sub><sup>81</sup>Br<sub>2</sub> isotopologues in the 1180-1210 cm<sup>-1</sup> region.

Physical chemistry chemical physics : PCCP·2026
Same journal

First-principles modeling of polysilazane-derived SiCNH ceramics: insights into the organization of the free-carbon phase.

Physical chemistry chemical physics : PCCP·2026
Same journal

Determining the binding strength of phenolic anchoring groups on hydrated WO<sub>3</sub> surfaces.

Physical chemistry chemical physics : PCCP·2026
Same journal

Activation of methane by the tantalum trioxide anion, TaO<sub>3</sub><sup></sup>.

Physical chemistry chemical physics : PCCP·2026
Same journal

Temperature-dependent recombination dynamics in BH/ZnBr<sub>2</sub> Co-doped CsPbI<sub>3</sub> thin films.

Physical chemistry chemical physics : PCCP·2026
See all related articles

Related Experiment Video

Updated: Nov 29, 2025

A Virtual Machine Platform for Non-Computer Professionals for Using Deep Learning to Classify Biological Sequences of Metagenomic Data
09:34

A Virtual Machine Platform for Non-Computer Professionals for Using Deep Learning to Classify Biological Sequences of Metagenomic Data

Published on: September 25, 2021

4.3K

Deep learning enabled inorganic material generator.

Yashaswi Pathak1, Karandeep Singh Juneja, Girish Varma

  • 1International Institute of Information Technology, Hyderabad 500 032, India. deva@iiit.ac.in.

Physical Chemistry Chemical Physics : PCCP
|November 18, 2020
PubMed
Summary
This summary is machine-generated.

This study introduces a deep learning framework for inorganic material discovery. It efficiently generates novel materials with desired properties by combining generative and predictive models.

More Related Videos

DNA Origami-Mediated Substrate Nanopatterning of Inorganic Structures for Sensing Applications
08:59

DNA Origami-Mediated Substrate Nanopatterning of Inorganic Structures for Sensing Applications

Published on: September 27, 2019

11.9K
Analyzing Mitochondrial Morphology Through Simulation Supervised Learning
12:06

Analyzing Mitochondrial Morphology Through Simulation Supervised Learning

Published on: March 3, 2023

4.5K

Related Experiment Videos

Last Updated: Nov 29, 2025

A Virtual Machine Platform for Non-Computer Professionals for Using Deep Learning to Classify Biological Sequences of Metagenomic Data
09:34

A Virtual Machine Platform for Non-Computer Professionals for Using Deep Learning to Classify Biological Sequences of Metagenomic Data

Published on: September 25, 2021

4.3K
DNA Origami-Mediated Substrate Nanopatterning of Inorganic Structures for Sensing Applications
08:59

DNA Origami-Mediated Substrate Nanopatterning of Inorganic Structures for Sensing Applications

Published on: September 27, 2019

11.9K
Analyzing Mitochondrial Morphology Through Simulation Supervised Learning
12:06

Analyzing Mitochondrial Morphology Through Simulation Supervised Learning

Published on: March 3, 2023

4.5K

Area of Science:

  • Materials Science
  • Computational Chemistry
  • Artificial Intelligence

Background:

  • Machine learning accelerates materials property prediction.
  • Discovering new materials requires extensive chemical space exploration.
  • Generative models offer efficient sampling and property-driven material generation.

Purpose of the Study:

  • To develop a deep learning framework for generating inorganic materials.
  • To enable efficient exploration of chemical space for material discovery.
  • To demonstrate the framework's capability in generating materials with target properties.

Main Methods:

  • Developed a deep learning based inorganic material generator (DING) framework.
  • Utilized conditional variational autoencoders (CVAEs) for the generator module.
  • Employed deep neural networks for predicting material properties (enthalpy of formation, volume per atom, energy per atom).
  • Used a one-hot key representation for material composition.

Main Results:

  • Demonstrated the robustness of predictor models.
  • Showcased the continuity of the latent material space.
  • Successfully generated materials with targeted property values.
  • Validated the DING framework's potential for efficient chemical space exploration.

Conclusions:

  • The DING framework provides an efficient approach to inorganic material discovery.
  • The architecture is extensible to various material properties.
  • Facilitates rapid identification of novel materials with desired characteristics.