Designing novel Sn-Bi, Si-C and Ge-C nanostructures, using simple theoretical chemical similarities

Abstract

A framework of simple, transparent and powerful concepts is presented which is based on isoelectronic (or isovalent) principles, analogies, regularities and similarities. These analogies could be considered as conceptual extensions of the periodical table of the elements, assuming that two atoms or molecules having the same number of valence electrons would be expected to have similar or homologous properties. In addition, such similar moieties should be able, in principle, to replace each other in more complex structures and nanocomposites. This is only partly true and only occurs under certain conditions which are investigated and reviewed here. When successful, these concepts are very powerful and transparent, leading to a large variety of nanomaterials based on Si and other group 14 elements, similar to well known and well studied analogous materials based on boron and carbon. Such nanomaterias designed in silico include, among many others, Si-C, Sn-Bi, Si-C and Ge-C clusters, rings, nanowheels, nanorodes, nanocages and multidecker sandwiches, as well as silicon planar rings and fullerenes similar to the analogous sp2 bonding carbon structures. It is shown that this pedagogically simple and transparent framework can lead to an endless variety of novel and functional nanomaterials with important potential applications in nanotechnology, nanomedicine and nanobiology. Some of the so called predicted structures have been already synthesized, not necessarily with the same rational and motivation. Finally, it is anticipated that such powerful and transparent rules and analogies, in addition to their predictive power, could also lead to far-reaching interpretations and a deeper understanding of already known results and information.

Boron Silicon B2Si3qand B3Si2pClusters: The Smallest Aromatic Ribbons

“…Finally, for verification of the reliability of the ribbon aromaticity model for these small structures, we perform substitution of a Si atom by a BH unit, both of which are isovalent, within a framework similar to an isolobal analogy , for B 3 Si 2 – . The result of such an operation, shown in Figure , leads to a global energy minimum of B 5 H 2 – , which is antiaromatic in the singlet state and aromatic in the triplet state.…”

“…Let us stress again that in contrast to hydrocarbons in which an aromatic isomer is substantially more stable than its next nonaromatic isomer, a typical characteristic of atomic clusters is that many lower-lying isomers of a certain size have a similar energy content and an aromatic character, implying even a small stabilization energy is often large enough to allow an aromatic isomer to emerge as the global energy minimum. Finally, for verification of the reliability of the ribbon aromaticity model for these small structures, we perform substitution of a Si atom by a BH unit, both of which are isovalent, within a framework similar to an isolobal analogy 59,60 for B 3 Si 2 − . The result of such an operation, shown in Figure 6, leads to a global energy minimum of B 5 H 2 − , which is antiaromatic in the singlet state and aromatic in the triplet state.…”

Quantum mechanically guided design of Co43Fe20Ta5.5X31.5(X=B, Si, P, S) metallic glasses

“…The similarities in effective charges of all four constituents, PDF shape, nearest neighbors and coordination number data between Co 43 Fe 20 Ta 5.5 B 31.5 and Co 43 Fe 20 Ta 5.5 P 31.5 as discussed above may be caused by the similar ionic potential (ratio between ionic radius and ionic charge). This phenomenon, known as the so-called 'diagonal relationship' [55][56][57][58] mainly occurring between elements of the second and third period, states that diagonally neighboring elements show similar chemical behavior. For instance, Be is more similar to Al than to B.…”

Enalos InSilicoNano platform: an online decision support tool for the design and virtual screening of nanoparticles

“…Enalos InSilicoNano platform aspires to be a useful tool for design of novel NPs with desired properties. 57,58 To this end we have successfully built and validated a QNAR model that can reliably predict the cellular uptake of a dataset of 109 NPs. The model was made publicly available through Enalos InSilicoNano platform and can be used for the predictions of cellular uptake of new structures that are designed or imported to the server.…”