Skip to main content
Log in

On the topology of the space of coordination geometries

  • Regular Article - Statistical and Nonlinear Physics
  • Published:
The European Physical Journal B Aims and scope Submit manuscript

Abstract

Coordination geometries describe the arrangement of the neighbours of a central particle. Such geometries can be thought to lie in an abstract topological space, a model of which could provide a mathematical basis for understanding physical transformations in crystals, liquids, and glasses. Through the generalisation of a recently proposed local order parameter, the present work conceives a metric model of the space of three-dimensional coordination geometries. This model appears to be consistent with elementary geometry and suggests a taxonomy of coordination geometries with five main classes. A quantifier of coordination-geometric typicality is derived from the metric. By the statement of a postulate on the topology of the space being modelled, the range of structures that are possible to resolve using the local order parameter is greatly increased.

Graphic abstract

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

Data availability statement

The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.

References

  1. D. Moroni, P.R. ten Wolde, P.G. Bolhuis, Phys. Rev. Lett. 94, 235703 (2005). https://doi.org/10.1103/PhysRevLett.94.235703

    Article  ADS  Google Scholar 

  2. A.R. Natarajan, A. Van der Ven, Phys. Rev. Lett. 121, 255701 (2018). https://doi.org/10.1103/PhysRevLett.121.255701

    Article  ADS  Google Scholar 

  3. P.N. Plessow, Phys. Chem. Chem. Phys. 22, 12939 (2020). https://doi.org/10.1039/d0cp01651a

    Article  Google Scholar 

  4. Y.-C. Hu, H. Tanaka, Nat. Commun. 13, 4519 (2022). https://doi.org/10.1038/s41467-022-32241-z

    Article  ADS  Google Scholar 

  5. H. Terrones, A.L. Mackay, J. Math. Chem. 15, 157 (1994). https://doi.org/10.1007/bf01277557

    Article  MathSciNet  Google Scholar 

  6. S.K. Kolli, A.R. Natarajan, J.C. Thomas, T.M. Pollock, A. Van der Ven, Phys. Rev. Mater. 4, 113604 (2020). https://doi.org/10.1103/physrevmaterials.4.113604

    Article  Google Scholar 

  7. J.C. Thomas, A.R. Natarajan, A. Van der Ven, Npj Comput. Mater. 7, 164 (2021). https://doi.org/10.1038/s41524-021-00627-0

    Article  ADS  Google Scholar 

  8. J. Çamkıran, F. Parsch, G.D. Hibbard, J. Chem. Phys. 156, 091101 (2022). https://doi.org/10.1063/5.0079985

    Article  ADS  Google Scholar 

  9. P.J. Steinhardt, D.R. Nelson, M. Ronchetti, Phys. Rev. B 28, 784 (1983). https://doi.org/10.1103/physrevb.28.784

    Article  ADS  Google Scholar 

  10. L. Pauling, J. Am. Chem. Soc. 51, 1010 (1929). https://doi.org/10.1021/ja01379a006

    Article  Google Scholar 

  11. R. Staub, S.N. Steinmann, J. Chem. Phys. 152, 024124 (2020). https://doi.org/10.1063/1.5135696

    Article  Google Scholar 

  12. R.V.L. Hartley, Bell Syst. Tech. J. 7, 535 (1928). https://doi.org/10.1002/j.1538-7305.1928.tb01236.x

    Article  Google Scholar 

  13. A. Stukowski, Modell. Simul. Mater. Sci. Eng. 20, 045021 (2012). https://doi.org/10.1088/0965-0393/20/4/045021

    Article  ADS  Google Scholar 

  14. H. Tanaka, H. Tong, R. Shi, J. Russo, Nat. Rev. Phys. 1, 333 (2019). https://doi.org/10.1038/s42254-019-0053-3

    Article  Google Scholar 

  15. L. Yang, S. Dacek, G. Ceder, Phys. Rev. B 90, 054102 (2014). https://doi.org/10.1103/physrevb.90.054102

    Article  ADS  Google Scholar 

  16. R. Hundt, J.C. Schön, M. Jansen, J. Appl. Crystallogr. 39, 6 (2006). https://doi.org/10.1107/S0021889805032450

    Article  Google Scholar 

  17. M.Ó. Searcóid, Metric spaces (Springer, 2006), p.2

    MATH  Google Scholar 

  18. M. Ester, H.-P. Kriegel, J. Sander, X. Xu, in Proc. of 2nd International Conference on Knowledge Discovery and Data Mining( 1996) pp.226–231

  19. Z. Bar-Joseph, D.K. Gifford, T.S. Jaakkola, Bioinformatics 17, S22 (2001). https://doi.org/10.1093/bioinformatics/17.suppl_1.s22

    Article  Google Scholar 

  20. P.H.A. Sneath, R.R. Sokal, Numerical taxonomy (Freeman, 1973)

    MATH  Google Scholar 

  21. T.F. Cox, M.A.A. Cox, Multidimensional scaling (Chapman & Hall, 1994)

    MATH  Google Scholar 

  22. S.L. Devadoss, J. O’Rourke, Discrete and computational geometry (Princeton University Press, 2011), pp.98–117

    MATH  Google Scholar 

  23. C.J. Bradley, A.P. Cracknell, The mathematical theory of symmetry in solids: representation theory for point groups and space groups (Oxford University Press, Oxford, 2010)

    MATH  Google Scholar 

  24. E.C. Bain, N. Dunkirk, Trans. AIME. 70, 24 (1924)

    Google Scholar 

  25. W. Burgers, Physica 1, 561–586 (1934)

    Article  ADS  Google Scholar 

  26. R.J. Gillespie, Coord. Chem. Rev. 252, 1315 (2008). https://doi.org/10.1016/j.ccr.2007.07.007

  27. J.J. Thomson, Lond. Edinb. 7, 237 (1904). https://doi.org/10.1080/14786440409463107

  28. M. Atiyah, P. Sutcliffe, Milan J. Math. 71, 33 (2003). https://doi.org/10.1007/s00032-003-0014-1

    Article  MathSciNet  Google Scholar 

  29. H. Wadell, J. Geol. 43, 250 (1935). https://doi.org/10.1086/624298

    Article  ADS  Google Scholar 

Download references

Acknowledgements

The authors would like to thank Alán Aspuru-Guzik and Chandra Veer Singh for their helpful discussions.

Author information

Authors and Affiliations

Authors

Contributions

JÇ conceived the project, obtained the results, and wrote the manuscript. FP and GDH contributed to the results and the writing.

Corresponding author

Correspondence to John Çamkıran.

Appendices

Appendix A: Commonly encountered geometries

Table 2 lists 22 of the most commonly encountered geometries of coordination. These include 11 zero-lone-pair molecular geometries predicted by valence shell electron pair repulsion theory [26] and eight solutions of the Thomson problem [27], the latter of which also happen to be minimum-energy sphere packings for \(k \le 12\) [28]. Mathematically, these correspond to the first four Platonic solids, all eight strictly convex deltahedra, 12 capped (anti)prisms, four regular bipyramids, two circumscribable bicupolae, and the rhombic dodecahedron (a Catalan solid). Figure 5 depicts their extracopularity distances.

Appendix B: A technicality of fixed discretisation

One of the inevitabilities of the fixed approach to bond angle discretisation is the confusion of angles that are close yet unequal even in the ideal form of a coordination geometry. Among the geometries herein studied, this issue is observed to afflict those of type (X)PP, (X)SA, (X)TP, and SDS. In the analysis described in Sect. 5, we corrected their bond angle counts as follows. Let \(f_{g}(\theta )\) denote the number of close yet unequal angles that are mapped to the class representative \(\theta \) for a coordination geometry g. Then, our correction to \(\left|\Theta _{gh}\right|\) is given by

$$\begin{aligned} \left|\Theta _{gh}\right|^* = \sum _{\theta \in \Theta _{gh}} \max \{ f_{g}(\theta ), f_{h}(\theta ) \}. \end{aligned}$$
(B1)

Appendix C: Miscellaneous parameters

1.1 1. Sphericity

The sphericity \(\Psi \) of a given coordination geometry is defined by the ratio of the surface area of a sphere with the same volume V as the convex hull of that geometry to the surface area A of the boundary of its convex hull [29],

$$\begin{aligned} \Psi = \frac{\pi ^{1/3}(6V)^{2/3}}{A}. \end{aligned}$$
(C1)

1.2 2. Moment of inertia per neighbour

The moment of inertia per neighbour I/k of a particle with a given coordination geometry can be computed as follows:

  1. 1.

    Calculate the centroid c of the particle’s neighbourhood as the average position of its neighbours, \(c = \left\langle q\right\rangle \).

  2. 2.

    Determine the Euclidean distance \(\ell (q)\) of each neighbour q from the centroid, \(\ell (q) = \Vert q-c \Vert \).

  3. 3.

    Take the sum of the square of these distances to get the moment of inertia, \(I = \sum _q \ell (q)^2 \).

  4. 4.

    Divide I by k to get the per-neighbour value.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Çamkıran, J., Parsch, F. & Hibbard, G.D. On the topology of the space of coordination geometries. Eur. Phys. J. B 96, 72 (2023). https://doi.org/10.1140/epjb/s10051-023-00528-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1140/epjb/s10051-023-00528-9

Navigation