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Properties of Transition Metals02:58

Properties of Transition Metals

29.7K
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.
29.7K
Coordination Number and Geometry02:57

Coordination Number and Geometry

19.0K
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.
19.0K
Coordination Compounds and Nomenclature02:54

Coordination Compounds and Nomenclature

26.7K
In most main group element compounds, the valence electrons of the isolated atoms combine to form chemical bonds that satisfy the octet rule. For instance, the four valence electrons of carbon overlap with electrons from four hydrogen atoms to form CH4. The one valence electron leaves sodium and adds to the seven valence electrons of chlorine to form the ionic formula unit NaCl (Figure 1a). Transition metals do not normally bond in this fashion. They primarily form coordinate covalent bonds, a...
26.7K
Metal-Ligand Bonds02:51

Metal-Ligand Bonds

24.2K
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...
24.2K
Phase Transitions02:31

Phase Transitions

23.1K
Whether solid, liquid, or gas, a substance's state depends on the order and arrangement of its particles (atoms, molecules, or ions). Particles in the solid pack closely together, generally in a pattern. The particles vibrate about their fixed positions but do not move or squeeze past their neighbors. In liquids, although the particles are closely spaced, they are randomly arranged. The position of the particles are not fixed—that is, they are free to move past their neighbors to...
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Metallic Solids02:37

Metallic Solids

20.6K
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....
20.6K

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Related Experiment Video

Updated: Jan 28, 2026

Reverse Microemulsion-mediated Synthesis of Monometallic and Bimetallic Early Transition Metal Carbide and Nitride Nanoparticles
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Reverse Microemulsion-mediated Synthesis of Monometallic and Bimetallic Early Transition Metal Carbide and Nitride Nanoparticles

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A coordination-based model for transition metal alloy nanoparticles.

Luke T Roling1, Tej S Choksi, Frank Abild-Pedersen

  • 1SUNCAT Center for Interface Science and Catalysis, Department of Chemical Engineering, Stanford University, Stanford, CA 94305, USA.

Nanoscale
|February 26, 2019
PubMed
Summary

We developed a simple model to predict bimetallic nanoparticle energies using atom identity and coordination. This approach accurately forecasts atomic stability, crucial for catalysis and materials design.

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Area of Science:

  • Computational materials science
  • Nanoparticle catalysis
  • Surface chemistry

Background:

  • Bimetallic nanoparticles are crucial for heterogeneous catalysis.
  • Predicting their stability and active sites is computationally challenging.
  • Accurate energy predictions are needed for rational design.

Purpose of the Study:

  • To develop a simple, predictive model for bimetallic nanoparticle relative energies.
  • To enable rapid forecasting of atomic site stability.
  • To facilitate the reverse engineering of active site motifs.

Main Methods:

  • Parameterizing metal atom energies based on identity and coordination number.
  • Utilizing metal atom adsorption calculations on surface slab models.
  • Testing model transferability across diverse nanoparticle structures and compositions.

Main Results:

  • A transferable model accurately predicts relative energies for 21 fcc bimetallic pairings.
  • The model excels at predicting atomic rearrangements near surfaces.
  • Rapid site stability forecasting with atomic specificity is achieved.

Conclusions:

  • The developed model offers a computationally efficient approach for bimetallic nanoparticle design.
  • Accurate prediction of site stability is vital for understanding segregation and catalysis.
  • This work establishes robust property-structure relationships for nanoparticle engineering.