Everyone remembers the two fundamental chemical bond types: covalent and ionic. Recently, a third one has been proposed, which is called "charge-shift bonding". The valence bond wavefunction that describes the system, e.g., a fluorine molecule, is a linear combination of different charge shift states, e.g.:
Ψ(F2) = C1*φ(F-F) + C2*φ(F+F-) + C3*φ(F-F+)
Now, the fluorine molecule stands here as an example because the energy contribution of the covalent term is positive, meaning that the system exists in a "superposition" of two resonant states, F+F- and F-F+, while the covalent contribution actually destabilizes the molecule. This is a very interesting phenomenon, particularly because it is reminiscent of the Mott transition. For more details on charge-shift bonding, see the review in Nature Chemistry, and the blog post for a more strict explanation of the concept.
While this is an interesting explanation of why the fluorine molecule falls apart so happily, it has been suggested that a similar mechanism can be behind the differences in energy of linear vs. branched alkanes. Basically, the latter have more available options for second-atom "resonances" (C+CC- and C-CC+). Here's the paper and the blog post
Now, this is a very interesting explanation of a long-standing problem. On the other hand, though, the fact that even such seemingly simple and familiar systems as alkanes sometimes have to be treated using multi-reference methods is, in my view, somewhat disencouraging...
Since the silence has to be broken somehow, this time it's going to be a post about the practical aspects of computational chemistry.
It is well-known that description of long-range correlations leading to London dispersion forces (better known as "van der Waals forces", although it's only one of the multiple interactions falling into this category) is notoriously hard for quantum chemistry tools. Basically, until recently, to get reasonable description of dispersion interactions in weakly bound systems, one would have to either use high-level correlated ab initio methods (for which, until recently, computing resources adequate for simulating systems of any reasonably interesting size had been effectively unavailable), or augment their quantum chemistry (most often, DFT) with empirical classical interatomic potentials - sort of undermining the whole idea of a "first-principles" calculation. The latter approach can also be described as "atom-atom" (as opposed to the "electron-electron" ab initio approach).
There's been a recent improvement in the form of a fully nonlocal density functional which appears to describe many systems fairly well. I've tried it myself, using the JuNoLo code which gave me a mere 3% error for the c lattice constant of graphite. This is actually very impressive, and since this functional is now starting to get included in standard DFT codes (most notably, SIESTA), there's clearly a big future for this approach (although it is known to fail for some systems: I've heard it fail for Ni on graphene). Finally, there's also another first-principles approach employing exact exchange and RPA correlation, somewhat similar in the approach (i.e., nonlocal) also appearing to give good results.
While this is, strictly speaking, an ad hoc semiempirical correction, and the first obvious question that comes into mind is that of transferability. Luckily, the experience of classical interatomic potentials suggests that dispersion interactions are not extremely sensitive, and the vdW parameters in such force fields as OPLS seldom need fine tuning. The paper cited above appears to suggest that the accuracy of this new DFT+LAP method is extremely good for a huge range of C,H,N,O compounds. However, the authors only list interaction energies and no forces nor geometries. Therefore I decided to check myself how well it would perform for fcc C60 fullerite. Using the setup from the above paper gives a lattice constant of 1.4118 nm which, compared to the experimental value of 1.417 nm, is just amazingly good: the error is a mere 0.37% (!!!), and even if we subtract the radius of C60 and look only at the nearest-neighbor intermolecule distance, it's still only 1.3% off! What's further encouraging is that the bulk modulus also comes close to recent experimental results: the error is +25% for the modulus and -25% for the dB/dP, which can be considered quite good an agreement for elastic properties - mind also that these values have been calculated using Murnaghan fit, which is not well suited for such systems (dB/dP != const).
Some more open questions remain from the no-free-lunch side. First, it has yet to be demonstrated that (if) this approach works for other systems such as those containing metal atoms. Second, since it is an "atom-electron" approach, it has to contain the notion of an atom in some way or another - this time it's the pseudopotential; real systems don't have well-defined atoms, hence the "purity" of the approach again suffers somewhat. Interestingly, I'm more or less sure that DFT+LAP can be used to describe core electrons exactly, in a "semicore"-like manner, but someone has to test this.
Finally, I want to note that this approach seems to redefine the physical meaning of the pseudopotential: while the latter originally is interpreted as describing the "effective interaction" of valence electrons with core electrons, vdW-DF calculations suggest that it is unnecessary to include the core charge density in the DFT calculation to get the correlation energy responsible for dispersion attraction right. This seems kind of funny.
I haven't had much time to fill this blog with useful info, so it seems I'll have to start with a presentation of my own research. A paper is up at arXiv [edit: and in Nanotechnology] describing what I believe to be a possible (though admittedly rather complicated) route to achieve very precise control over functional molecules in a scanning probe microscope.
This has been inspired by discussions with Danila Medvedev and by reading the email discussion on scanning probe mechanosynthesis between Chris Phoenix and Philip Moriarty. In particular, the place where Moriarty mentions the use of carbon nanotube probes (which seems somewhat obvious in retrospect), and the place where Phoenix suggests imaging a known substrate feature to calibrate the relative position of the probe tips in space (which seems a serious complication: it should be better to use probes with well-known tip structure, e.g., carbon nanotubes).
One of the problems with nanotubes is that, although the caps are normally more prone to chemical functionalization than the walls, you still don't know exactly where your functional group lands. However, it appears that (6,0) nanotubes should have caps with a single site that is especially chemically vulnerable: a carbon atom belonging to three pentagons at the very tip. Therefore such a nanotube could be used as a very thin scanning probe with a well-defined funtionalization site known in advance. However, this would only work for very tiny functional groups, since larger molecules would rotate freely around the single covalent bond, destroying all the benefits of site-specific functionalization.
This problem could be solved by using a bundle of several nanotubes and attaching a larger molecule by at least three points. The figure shows an adamantane molecule supported in this manner (C3 alkane chains are used to fit the too-small molecule on top of the bundle). You can also see that if individual nanotubes could be actuated, this could be utilized to tilt the molecule; together with three translations of the manipulator and the axial rotation (either of the manipulator or of the substrate) this would amount to the six degrees of freedom claimed in the paper title.
The rest of the paper is dedicated to explanations of exactly why I believe such a design (or a similar but much simpler which I haven't thought of yet) should be feasible with the technology that is either available presently or immediately accessible. Let's see if I can get this past the peer-review stage; in the meantime, everyone's comments and suggestions are most welcome!
… if you really want to understand the detailed molecular interactions that make it go in a particular direction, make certain contacts, break other contacts, hydrolyze GTP, you know, form bonds, etcetera, and do it all amazingly accurately, then you do need a high resolution picture of those states. But, that’s not going to be enough. It’s going to take a lot of work by biochemists, by computational people who do molecular dynamics and things like that to really, eventually, understand it in the sense that we would understand, say, a more typical reaction.
Hi! My name is Vasilii Artyukhov, and at the moment I've got no time to write much since I'm so busy working on a paper, but in time I hope I'll be posting here various molecular simulation related stuff, including both reviews of interesting work, my own research, and probably any other thoughts that may seem appropriate. I don't think the traffic is going to be too heavy anytime soon, so you can safely subscribe to the RSS feed.
A model of single-electron transport. Calculation of the thermodynamic parameters for electron capture by the bound proton of oxyacids. A. S. Zubkov, V. I. Artyukhov, L. A. Chernozatonskii and O. S. Nedelina, Rus. J. Phys. Chem. B, 5, 748-764 (2011). http://www.springerlink.com/content/f2718344245g7827/
Structure and Layer Interaction in Graphite Fluoride and Graphane: A Comparative Computational Study. V. I. Artyukhov and L. A. Chernozatonskii, J. Phys. Chem. A114, 5389-96 (2010). http://pubs.acs.org/doi/abs/10.1021/jp1003566
Quantum-chemical study of methane nitrosation with NO in the presence of superelectrophiles containing the trichloromethyl cation. A. L. Chistyakov, I. V. Stankevich, N. P. Gambaryan, I. S. Akhrem and V. I. Artyukhov, Doklady Phys. Chem. 414, 132 (2007). http://www.springerlink.com/content/9282587p12211p04/
I am a computational chemical physicist presently working at the ME&MS Department of Rice University. My main subject area is nanotechnology, but I'm also very interested in other aspects of molecular simulation, particularly, computational molecular/material design. My publication list can be found here, and an online CV can be found here.