Jove
Visualize
Contáctanos

Videos de Conceptos Relacionados

Extraction: Advanced Methods00:56

Extraction: Advanced Methods

1.1K
Metal ions can be separated from one another by complexation with organic ligands–the chelating agent– to form uncharged chelates. Here, the chelating agent must contain hydrophobic groups and behave as a weak acid, losing a proton to bind with the metal. Since most organic ligands used in this process are insoluble or undergo oxidation in the aqueous phase, the chelating agent is initially added to the organic phase and extracted into the aqueous phase. The metal-ligand complex is...
1.1K
Metallic Solids02:37

Metallic Solids

20.5K
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....
20.5K
Metal-Ligand Bonds02:51

Metal-Ligand Bonds

23.9K
The hemoglobin in the blood, the chlorophyll in green plants, vitamin B-12, and the catalyst used in the manufacture of polyethylene all contain coordination compounds. Ions of the metals, especially the transition metals, are likely to form complexes.
In these complexes, transition metals form coordinate covalent bonds, a kind of Lewis acid-base interaction in which both of the electrons in the bond are contributed by a donor (Lewis base) to an electron acceptor (Lewis acid). The Lewis acid in...
23.9K
Crystal Field Theory - Octahedral Complexes02:58

Crystal Field Theory - Octahedral Complexes

30.6K
Crystal Field Theory
To explain the observed behavior of transition metal complexes (such as colors), a model involving electrostatic interactions between the electrons from the ligands and the electrons in the unhybridized d orbitals of the central metal atom has been developed. This electrostatic model is crystal field theory (CFT). It helps to understand, interpret, and predict the colors, magnetic behavior, and some structures of coordination compounds of transition metals.
CFT focuses on...
30.6K

También podría leer

Artículos Relacionados

Artículos vinculados a este trabajo por autores compartidos, revista y gráfico de citas.

Ordenar por
Same author

Multiphase nanocomposite prelithiation agents for service life lithium replenishment in Si-based Li-ion batteries.

Science advances·2026
Same author

Prognostic model for diffuse large B-cell lymphoma based on an HBV-associated gene signature and immune microenvironment insights.

Annals of hematology·2026
Same author

Comparative effectiveness and safety of biologics and targeted small-molecule therapies plus stable background therapy in systemic lupus erythematosus: a systematic review and network meta-analysis.

Frontiers in immunology·2026
Same author

Perspective on Material Design and Interface Engineering toward Low-Stack-Pressure All-Solid-State Lithium Batteries.

Advanced materials (Deerfield Beach, Fla.)·2026
Same author

Energy-Transfer-Modulated Structural Evolution during Lithium-Sodium Ion Exchange in Layered Oxide Cathodes.

Journal of the American Chemical Society·2026
Same author

In Situ Phosphoester Polymer Layer Locking Oxygen Migration in Ni-Rich Cathodes Under Ultra-High Voltage.

Advanced materials (Deerfield Beach, Fla.)·2026
Same journal

On-Cell Detection of Polysaccharide One-Bond <sup>1</sup>J<sub>CH</sub> Couplings by Proton-Detected Solid-State NMR.

Journal of the American Chemical Society·2026
Same journal

Correction to "Unraveling the Effects of Fe Incorporation on High-Performance Water-Splitting Photoanodes".

Journal of the American Chemical Society·2026
Same journal

Proximity-Driven Protein Ligation Beyond the Concentration Limit.

Journal of the American Chemical Society·2026
Same journal

GraPhAI: Neural Networks for Solving Centrosymmetric Crystal Structures.

Journal of the American Chemical Society·2026
Same journal

Probing Stage Transition Kinetics in Li-Graphite Intercalation Compounds by Time-Resolved In Situ Solid-State NMR via <sup>13</sup>C Labeling.

Journal of the American Chemical Society·2026
Same journal

Dynamic Covalent Programming at DNA Base-Pairing Interfaces.

Journal of the American Chemical Society·2026
Ver todos los artículos relacionados
JoVE
x logofacebook logolinkedin logoyoutube logo
ACERCA DE JoVE
Visión GeneralLiderazgoBlogCentro de Ayuda JoVE
AUTORES
Proceso de PublicaciónConsejo EditorialAlcance y PolíticasRevisión por ParesPreguntas FrecuentesEnviar
BIBLIOTECARIOS
TestimoniosSuscripcionesAccesoRecursosConsejo Asesor de BibliotecasPreguntas Frecuentes
INVESTIGACIÓN
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchivo
EDUCACIÓN
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualCentro de Recursos para ProfesoresSitio de Profesores
Términos y Condiciones de Uso
Política de Privacidad
Políticas

Video Experimental Relacionado

Updated: Jan 14, 2026

Author Spotlight: Magnetometric Characterization of Intermediates in the Solid-State Electrochemistry of Redox-Active Metal-Organic Frameworks
06:53

Author Spotlight: Magnetometric Characterization of Intermediates in the Solid-State Electrochemistry of Redox-Active Metal-Organic Frameworks

Published on: June 9, 2023

2.6K

Minería de electrolitos en estado sólido de bases de datos de marco metálico-orgánico a través de grandes modelos de

Jinglang Zhang1,2, Jiaxin Li1,2, Guanhua Zhao2

  • 1Tianjin Key Laboratory of Advanced Carbon and Electrochemical Energy Storage, School of Chemical Engineering and Technology, and National Industry-Education Integration Platform of Energy Storage, Tianjin University, Tianjin 300350, China.

Journal of the American Chemical Society
|October 24, 2025
PubMed
Resumen
Este resumen es generado por máquina.

La inteligencia artificial, utilizando grandes modelos de lenguaje (LLM), acelera el descubrimiento de nuevos marcos metálico-orgánicos (MOF) para electrolitos en estado sólido (SSE). Este enfoque basado en IA identifica materiales MOF SSE prometedores con una alta conductividad iónica y estabilidad electroquímica.

Más Videos Relacionados

Author Spotlight: Experimental Approaches for the Synthesis of Low-Valent Metal-Organic Frameworks from Multitopic Phosphine Linkers
07:14

Author Spotlight: Experimental Approaches for the Synthesis of Low-Valent Metal-Organic Frameworks from Multitopic Phosphine Linkers

Published on: May 12, 2023

3.7K
Author Spotlight: Accelerating Discovery in Microporous Material Chemistry
07:20

Author Spotlight: Accelerating Discovery in Microporous Material Chemistry

Published on: October 6, 2023

4.3K

Videos de Experimentos Relacionados

Last Updated: Jan 14, 2026

Author Spotlight: Magnetometric Characterization of Intermediates in the Solid-State Electrochemistry of Redox-Active Metal-Organic Frameworks
06:53

Author Spotlight: Magnetometric Characterization of Intermediates in the Solid-State Electrochemistry of Redox-Active Metal-Organic Frameworks

Published on: June 9, 2023

2.6K
Author Spotlight: Experimental Approaches for the Synthesis of Low-Valent Metal-Organic Frameworks from Multitopic Phosphine Linkers
07:14

Author Spotlight: Experimental Approaches for the Synthesis of Low-Valent Metal-Organic Frameworks from Multitopic Phosphine Linkers

Published on: May 12, 2023

3.7K
Author Spotlight: Accelerating Discovery in Microporous Material Chemistry
07:20

Author Spotlight: Accelerating Discovery in Microporous Material Chemistry

Published on: October 6, 2023

4.3K

Área de la Ciencia:

  • Ciencias de los materiales
  • La electroquímica
  • Inteligencia artificial

Sus antecedentes:

  • Las estructuras metal-orgánicas (MOF) son prometedoras como electrolitos en estado sólido (SSE) para la conducción de iones Li+.
  • El desarrollo de las SSE del MOF está limitado por la complejidad y la falta de directrices de diseño.

Objetivo del estudio:

  • Aprovechar la IA, específicamente los LLM y el aprendizaje automático, para acelerar el descubrimiento y el diseño de las SSE del MOF.
  • Establecer un nuevo paradigma para el descubrimiento de materiales a través de la minería asistida por IA.

Principales métodos:

  • Minería de texto interactiva que utiliza LLM para extraer datos del MOF SSE.
  • Construcción de un conjunto de datos especializados de las propiedades estructurales y electroquímicas de los MOF.
  • Clustering de la representación para identificar candidatos prometedores a la SSE del Ministerio de Educación a partir de un gran conjunto de datos.

Principales resultados:

  • Se extrajeron con éxito las SSE del Ministerio de Fomento de más de 11 000 candidatos utilizando LLM y clustering.
  • Se identificó a NOTT-400 como un SSE MOF prometedor con una alta conductividad de Li+ (2,23 × 10-4 S cm-1) y una amplia estabilidad electroquímica (0-4,79 V).
  • Valida el enfoque impulsado por la IA a través de la caracterización fisicoquímica y la demostración electroquímica.

Conclusiones:

  • La IA, en particular los LLM, puede acelerar significativamente la identificación de nuevas SSE MOF.
  • La metodología impulsada por la IA proporciona un enfoque confiable y eficiente para el descubrimiento de materiales.
  • Este trabajo establece un nuevo paradigma para el diseño de las SSE MOF con propiedades deseables.