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

Metallic Solids

Metallic Solids

Metallic solids such as crystals of copper, aluminum, and iron are formed by metal atoms. The structure of metallic crystals is often described as a uniform distribution of atomic nuclei within a “sea” of delocalized electrons. The atoms within such a metallic solid are held together by a unique force known as metallic bonding that gives rise to many useful and varied bulk properties.
All metallic solids exhibit high thermal and electrical conductivity, metallic luster, and malleability....

Cluster Sampling Method

Cluster Sampling Method

Appropriate sampling methods ensure that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
To choose a cluster sample, divide the population into clusters (groups) and then randomly select some of the clusters. All the members from these clusters are in the cluster sample. For example, if you randomly sample four departments from your...

Qualitative Analysis

Qualitative Analysis

For solutions containing mixtures of different cations, the identity of each cation can be determined by qualitative analysis. This technique involves a series of selective precipitations with different chemical reagents, each reaction producing a characteristic precipitate for a specific group of cations. Metal ions within a group are further separated by varying the pH, heating the mixture to redissolve a precipitate, or adding other reagents to form complex ions.
For instance, group IV...

You might also read

Related Articles

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

Sort by

Same author

BenchQC: A Benchmarking Toolkit for Quantum Computation.

Journal of computational chemistry·2025

Same author

Exploring the Influence of Chalcogens on Metalloporphyrins: A DFT Study.

Molecules (Basel, Switzerland)·2025

Same author

Computational investigation of structural, electronic, and spectroscopic properties of Ni and Zn metalloporphyrins with varying anchoring groups.

The Journal of chemical physics·2024

Same author

Atomically precise nanoclusters predominantly seed gold nanoparticle syntheses.

Nature communications·2023

Same author

Au<sub>20</sub> (<sup>t</sup> Bu<sub>3</sub> P)<sub>8</sub> : A Highly Symmetric Metalloid Gold Cluster in Oxidation State 0.

Angewandte Chemie (International ed. in English)·2022

Same author

Computational Comparative Analysis of Small Atomically Precise Copper Clusters.

The journal of physical chemistry. A·2020

Same journal

Kinetic and Mechanistic Insights into H-Abstraction and Subsequent Isomerization and Decomposition of Monoglyme and Key Combustion Intermediates.

The journal of physical chemistry. A·2026

Same journal

First-Principles Analysis of Protonation-Induced Electronic Effects in Tetrakis(<i>p</i>-aminophenyl)porphyrin (TAPP).

The journal of physical chemistry. A·2026

Same journal

Exploring the Reactivity of the CH Radical toward Nitrous Oxide in the Context of the Interstellar Medium.

The journal of physical chemistry. A·2026

Same journal

Infrared Photodissociation Spectroscopy of Benzene-V<sup>+</sup>(CO)<sub>n</sub> "Piano Stool" Cations.

The journal of physical chemistry. A·2026

Same journal

Correction to "Solvent-Dependent Ultrafast Photochemical Dynamics of <i>N</i>-Methyl Oxindole Overcrowded Alkene Molecular Motors".

The journal of physical chemistry. A·2026

Same journal

Accelerating the Discovery of Superhalogens via Physics-Informed Graph Neural Networks.

The journal of physical chemistry. A·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Sep 17, 2025

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Published on: September 8, 2023

Exploring Quantum Computing for Metal Cluster Analysis.

Nia Pollard¹, A'Laura C Hines¹, Andre Z Clayborne^1,2

¹Department of Chemistry and Biochemistry, George Mason University, Fairfax, Virginia 22030, United States.

The Journal of Physical Chemistry. A

|June 27, 2025

Summary

This summary is machine-generated.

Quantum computing enhances metal cluster analysis by integrating quantum-DFT embedding. This workflow improves electronic structure modeling for materials discovery, despite current hardware limitations.

More Related Videos

Computation of Atmospheric Concentrations of Molecular Clusters from ab initio Thermochemistry

Computation of Atmospheric Concentrations of Molecular Clusters from ab initio Thermochemistry

Published on: April 8, 2020

Scalable Quantum Integrated Circuits on Superconducting Two-Dimensional Electron Gas Platform

Scalable Quantum Integrated Circuits on Superconducting Two-Dimensional Electron Gas Platform

Published on: August 2, 2019

Related Experiment Videos

Last Updated: Sep 17, 2025

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Published on: September 8, 2023

Computation of Atmospheric Concentrations of Molecular Clusters from ab initio Thermochemistry

Computation of Atmospheric Concentrations of Molecular Clusters from ab initio Thermochemistry

Published on: April 8, 2020

Scalable Quantum Integrated Circuits on Superconducting Two-Dimensional Electron Gas Platform

Scalable Quantum Integrated Circuits on Superconducting Two-Dimensional Electron Gas Platform

Published on: August 2, 2019

Area of Science:

Computational Chemistry
Quantum Computing
Materials Science

Background:

Classical computational methods face limitations in chemical accuracy and efficiency for nanoscale systems.
Developing advanced computational workflows is crucial for accurate materials modeling.
Quantum computing offers a potential avenue for overcoming classical limitations.

Purpose of the Study:

To develop and implement a quantum-DFT embedding workflow for metal cluster analysis.
To leverage quantum computing for improved electronic structure modeling.
To assess the capabilities and limitations of near-term quantum devices in computational chemistry.

Main Methods:

Integration of the Variational Quantum Eigensolver (VQE) with Density Functional Theory (DFT).
Application of the quantum-DFT embedding workflow to aluminum and gold clusters.
Testing the workflow's ability to determine electronic properties and catalytic potential.

Main Results:

Successfully determined electronic properties for aluminum clusters up to Al7-.
Investigated gold clusters for nitric oxide reduction potential.
Identified challenges including memory limitations, lack of relativistic corrections, and open-shell system handling.

Conclusions:

Quantum DFT embedding shows potential for advancing materials discovery and nanomaterial design.
Current quantum hardware and algorithms require further development for complex chemical systems.
This proof-of-concept study highlights the promise of quantum computing in computational chemistry.