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Related Concept Videos

Crystal Field Theory - Octahedral Complexes02:58

Crystal Field Theory - Octahedral Complexes

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...
Coordination Number and Geometry02:57

Coordination Number and Geometry

For transition metal complexes, the coordination number determines the geometry around the central metal ion. Table 1 compares coordination numbers to molecular geometry. The most common structures of the complexes in coordination compounds are octahedral, tetrahedral, and square planar.
Valence Bond Theory02:42

Valence Bond Theory

Coordination compounds and complexes exhibit different colors, geometries, and magnetic behavior, depending on the metal atom/ion and ligands from which they are composed. In an attempt to explain the bonding and structure of coordination complexes, Linus Pauling proposed the valence bond theory, or VBT, using the concepts of hybridization and the overlapping of the atomic orbitals. According to VBT, the central metal atom or ion (Lewis acid) hybridizes to provide empty orbitals of suitable...
Metal-Ligand Bonds02:51

Metal-Ligand Bonds

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...
Properties of Transition Metals02:58

Properties of Transition Metals

Transition metals are defined as those elements that have partially filled d orbitals. As shown in Figure 1, the d-block elements in groups 3–12 are transition elements. The f-block elements, also called inner transition metals (the lanthanides and actinides), also meet this criterion because the d orbital is partially occupied before the f orbitals.
Complexation Equilibria: Factors Influencing Stability of Complexes01:09

Complexation Equilibria: Factors Influencing Stability of Complexes

In complexation reactions, metal cations are the electron pair acceptors, and the ligands are the electron pair donors. The stability of the metal complexes depends primarily on the complexing ability of the central metal ion and the nature of the ligands. Generally, the complexing ability of the metal ion depends on the size and charge of the ion. As the metal ion size increases, the stability of the metal complexes decreases, provided that the valency of the metal ion and the ligands remain...

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  3. 3dtmc-llm: A 3d Geometry-aware Large Language Model For Transition Metal Complexes.
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  3. 3dtmc-llm: A 3d Geometry-aware Large Language Model For Transition Metal Complexes.

Related Experiment Video

Modeling Ligands into Maps Derived from Electron Cryomicroscopy
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Published on: July 19, 2024

3DTMC-LLM: A 3D Geometry-Aware Large Language Model for Transition Metal Complexes.

Jingyuan Zhu1, Farshad Shiri1, Liren Xiao1

  • 1Department of Chemistry, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong SAR, Hong Kong 999077, China.

Journal of Chemical Information and Modeling
|June 25, 2026

View abstract on PubMed

Summary
This summary is machine-generated.

This study introduces 3DTMC-LLM, a multimodal large language model (LLM) for transition metal complexes (TMCs). It effectively integrates 3D structural data with text, advancing AI in chemistry and materials science.

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Area of Science:

  • Chemistry
  • Materials Science
  • Artificial Intelligence

Background:

  • Large language models (LLMs) show promise in reasoning but struggle with complex scientific phenomena.
  • Transition metal complexes (TMCs) are crucial for catalysts and materials, but their intricate structures are challenging for language-based AI.
  • Existing AI models lack the multidimensional understanding needed for complex chemical systems.

Purpose of the Study:

  • To develop the first multimodal large language model (LLM) specifically designed for transition metal complexes (TMCs).
  • To bridge the gap between structural data and textual representations for enhanced AI interpretability in chemistry.
  • To improve AI-driven discovery and prediction for TMCs.

Main Methods:

  • Introduced 3DTMC-LLM, a novel multimodal LLM tailored for TMCs.
  • Utilized a pretrained 3D encoder trained on 12 million TMCs for structural data processing.
  • Implemented a lightweight single-token projection layer for efficient alignment of structural and textual information.

    • Main Results:

    • 3DTMC-LLM demonstrated competitive or superior performance in knowledge generation, property prediction, and reactivity modeling.
    • The model excelled particularly in tasks requiring an understanding of three-dimensional structural dependencies.
    • Benchmarked against state-of-the-art LLMs and domain-specific models, showing significant advantages.

    Conclusions:

    • Multimodal AI approaches, like 3DTMC-LLM, can accelerate research and discovery in TMCs.
    • This framework opens new avenues for developing general-purpose AI models for chemistry.
    • Integrating diverse data types is key to unlocking AI's potential in complex scientific domains.