In a nutshell, computational chemistry models are about depicting, reproducing and predicting the electronic-based molecular reality. I had this conversation with my students last week and at some point I drew a parallel between them and art in terms of how such reality is approached.
Semi empirical methods
Prehistoric wall paintings depict a coarse aspect of reality without any detail but nevertheless we can draw some conclusions from the images. In the most sophisticated of these images, the cave paintings in Altamira, we can discern a bison, or could it be a bull? but definitely not a giraffe nor a whale, most in the same way Hückel´s method provides an ad hoc picture of π electron density without any regard of the σ portion of the electron density or the conformational possibilities (s-cis and s-trans 1,3-butadiene have the same Hückel description).
More sophisticated semi-empirical Hamiltonians like PM3 or PM6 have better parametrizations and hence yield better results. We are still replacing a lot of information for experimental or adjusted parameters but we still cannot truly adopt it as truthful. Take this pre-medieval painting of one of the first Kings of England, Aelred the Unready. It is, by today standards, a good children´s drawing and not a royal portrait, we now see more detail and can discern many more features yielding a better description of a human figure than those found in Altamira or Egypt.
HF is the simplest of ab initio methods, meaning that no experimental results or adjustable parameters are introduced. Even more so, from the HF equations for a multi-electron system that complies with Pauli’s exclusion principle the exchange operator arises as a new quantum feature of matter with no classical analogue. Still, there are some shortcomings. Correlation energy is disregarded and most results vary according to the basis set employed. Take the impressionist movement, specially in France: In Monet´s Lady with Umbrella we have a more complicated composition, we observe many more features and although we have a better description of color composition some details, like her face, remain obscure. The impressionists are characterized by their broad strokes, the thicker the strokes the harder it is to observe details similar to what happens in HF when we change from a small to a large basis set, respectively.
CI (Configurations Interaction)
Extension of HF to a multi-reference method yields better results. In CI we take the original guess wavefunction -as expressed through a Slater Determinant- and extend it with one or many more wavefunctions; thus a linear combination of Slater Determinants gives rise to a broader description of the ground state because other electronic configurations are involved to include more details like the ionic and covalent pictures (configurations). The more terms we include the more real the results feel. If we take classical figurative paintings we have a similar result; most of these paintings are constituted of many elements and the more realistically each element is captured the more real the whole composition looks even if some are just merely indicated.
CCSD(T) full-CI, CASPT2
In Edwards Much’s the scream, we might think we have lost some information again and went back to impressionism but we know this is actually an expressionist painting; we can now not only observe details of the figurative portion of the image but Munch has captured his subject´s fear in the form of distorsions on the subjective reality. In this way, CCSD(T), full-CI and CASPT2 methods provide a description of the ground as well as the excited states which -in experimental reality- are only accessed through a perturbation of the elecron density by electromagnetic radiation. Something resembling radiation has perturbated the subject in The Scream rendering him frightened and wondering how to return to his ground state or if such thing will be even possible.
Density Functional Methods
At least due to its widespread use, DFT has risen as the preferred method. One of the reasons behind its success is the reduced computing time when compared to previous ab initio methods. So DFT is pretty much like photography, in which reality is captured in full but only apparently after selecting a given lens, an exposition, a filter, shutter speed and the occasional Photoshop for correcting issues such as aliasing. In photography, as in DFT, all details concerning the procedure or method for capturing an uncanny reproduction of reality must be stated in every case for reproduction purposes.
Now, in the end it all comes down to Magritte’s Pipe. Ceci n’est pas une pipe -or, ‘this is not a pipe’- reminds us that painting as with modeling we don’t get reality but rather a depiction of it. In this famous painting we look at an image that in our heads resembles that of a pipe but we cannot grab it, fill it with tobacco and smoke it.
The image above is a digital file, which translated becomes a scaled reproduction of an image painted by Magritte in which we see the 2D projection of the image of an object that reminds us of a pipe. In fact, the real name of this work is The Treachery of Images, definitely quite an epistemology problem on perception and knowledge but before I get too metaphysical I should finish this post.
Can you find where cubism or surrealism should be placed? with MPn methods, perhaps?
Sometimes you just need to optimize some fragment or moiety of your molecule for a number of reasons -whether because of its size, your current interest, or to skew the progress of a previous optimization- or maybe you want just some kind of atoms to have their positions optimized. I usually optimize hydrogen atoms when working with crystallographic files but that for some reason I want to preserve the rest of the molecule as refined, in order to keep it under a crystalline field of sorts.
Asking Gaussian to optimize some of the atoms in your molecule requires you to make a list albeit the logic behind it is not quite straightforward to me. This list is invoked by the ReadOptimize keyword in the route section and it includes all atoms by default, you can then further tell G09 which atoms are to be included or excluded from the optimization.
So, for example you want to optimize all atoms EXCEPT hydrogens, then your input should bear the ReadOptimize keyword in the route section and then, at the end of the molecule specification, the following line:
If you wish to selectively add some atoms to the list while excluding others, here’s an example:
atoms=C H S notatoms=5-8
This list adds, and therefore optimizes, all carbon, hydrogen and sulfur atoms, except atoms 5, 6, 7 and 8, should they be any of the previous elements in the C H S list.
The way I selectively optimize hydrogen atoms is by erasing all atoms from the list -using the noatoms instruction- and then selecting which are to be included in the list -with atoms=H-, but I haven’t tried it with only selecting hydrogen atoms from the start, as in atoms=H
I probably get very confused because I learned to do this with the now obsolete ReadFreeze keyword; now it sometimes may seem to me like I’m using double negatives or something – please do not optimize all atoms except if they are hydrogen atoms. You can include numbers, ranks or symbols in this list as a final line of your input file.
Common errors (by common I mean I’ve got them):
Lets look at the end of an input I just was working with:
> AtmSel: Line=”P 0″
> Maximum list size exceeded in AddBin.
> Error termination via Lnk1e in…
AtmSel is the routine which reads the atoms list and I was using a pseudopotential on phosphorous atoms, I placed the atoms list at the end of the file but it should be placed right after the coordinates and the connectivity matrix, should there be one, and thus before any external basis set or pseudopotential or any other specification to be read by Gaussian.
As a sort of test you can use the instruction:
%kjob l103 %chk=myfile.chk ...
at the Link0 section (where your checkpoint is defined). This will kill the job after the link 103 is finished, thus you will only get a list of what parameters were frozen and which were active. Then, if things look ok, you can run the job without the %kjob l103 instruction and get it done.
As usual I hope this helps. Thanks for reading except to those who didn’t read it except for the parts they did read.
Last week at the congress of the Mexican Society of Chemistry I presented some of our results in the study of photosynthesis. Below I embeded the talk. Unfortunately for the wider audience of this blog, the talk is in Spanish (if anyone out there is willing to make subtitles for it I’ll hire you on the spot!)
The slides are also in Spanish although they should be easier to follow for non-Spanish speakers and they are uploaded in SlideShare at this link.
A big thank you to Maria Eugenia “Maru” Sandoval for all the hard work and time invested in this project!
Thanks for clicking!
Having a long calculation terminated just because it ran out of time in the queue is very frustrating; even more so if restarting it from the last accesible point is hard to do.
I have recently performed some particularly demanding calculation: Basis Set Superposition Error (BSSE) with the Counterpoise method and second order Moller-Plesset perturbation theory calculation (MP2). The calculation ran out of time but I was able to restart it because I had the rwf file! My input looked a bit like this:
#p mp2/GEN counterpoise=2 maxdisk=200GB
So here is how it works.
The very first line of your calculation gives you the process ID number which is not necessarily the same as the PID given by the queue system (in fact, is not the same because the latter corresponds to the submitted script, not the instructions in it i.e. your calculation)
Entering Gaussian System, Link 0=g09 Initial command: /opt/SC/aplicaciones/g09-C.01/l1.exe /tmpu/joaqbf_g/joaqbf/Gau-38954.inp -scrdir=/tmpu/joaqbf_g/joaqbf/ Entering Link 1 = /opt/SC/aplicaciones/g09-C.01/l1.exe PID= 38955.
(emphasis in red is mine)
This is the number you want to write down. You will need to find the corresponding rwf file (usually in your SCRATCH directory) as Gau-PID.rwf (in the aforementioned case, Gau-38955.rwf). If you are a bit paranoid like myself you want to copy and keep this file safe but be aware that these are very long files, in my case it was 175 GB long. Now you need to launch your calculation again with the following input:
%rwf=myfile.rwf %nosave %chk=myfile.chk Title Card # restart rest of input
You can add all other controls to the Link0 section such as %nprocshared or %mem according to your needs.
I’m pretty sure it should work for other kinds of calculations in which taking from the checkpoint file is not as easy, so if you run into this kind of problems, its worth the try.
A new publication is now available in which we calculated the binding properties of a fluorescent water-soluble chemosensor for halides which is specially sensitive for chloride. Once again, we were working in collaboration with an experimental group who is currently involved in developing all kinds of sustainable chemosensors.
The electronic structure of the chromophore was calculated at the M06-2X/6-311++G(d,p) level of theory under the SMD solvation model (water) at various pH levels which was achieved simply by changing the protonation and charges upon the ligand. Wiberg bond indexes from the Natural Population Analysis showed strong interactions between the chloride ion and the chromophore. Also, Fukui indexes were calculated in order to find the most probable binding sites. A very interesting feature of this compound is its ability to form a cavity without being a macrocycle! I deem it a cavity because of the intramolecular interactions which prevent the entrance of solvent molecules but that can be reversibly disrupted for the inclusion of an anion. In the figure below you can observe the remarkable quenching effect chloride has on the anion.
A quick look to the Frontier Molecular Orbitals (FMO’s) show that the chloride anion acts as an electron donor to the sensor.
If you are interested in more details please check: Bazany-Rodríguez, I. J., Martínez-Otero, D., Barroso-Flores, J., Yatsimirsky, A. K., & Dorazco-González, A. (2015). Sensitive water-soluble fluorescent chemosensor for chloride based on a bisquinolinium pyridine-dicarboxamide compound. Sensors and Actuators B: Chemical, 221, 1348–1355. http://doi.org/10.1016/j.snb.2015.07.031
Thanks to Dr. Alejandro Dorazco from CCIQS for asking me to join him in this project which currently includes some other join ventures in the realm of molecular recognition.
Simulation of Raman Spectroscopy and crystal cell effects – Selenium Carboxylate Eur. J. Inorg. Chem.
Computing spectroscopic features of molecules is always an interesting challenge, specially when intermolecular contacts are into play. Take vibrational spectroscopy for instance, all the non-covalent interactions present in a solid will have an important effect on the the calculated frequencies and their intensities. However calculating the spectroscopical properties of a solid quickly becomes a daunting task.
My colleague and friend Dr. Vojtech Jancik asked me to calculate the Raman frequencies for a new compound: Selenoyl bis-carboxylate, which according to him was very hard to obtain due to the very nature of selenium. So we performed various calculations on the isolated molecule to reproduce the measured Raman spectrum but we soon realized that a calculation on the crystal cell was needed if we wanted to get a more thorough picture of the experiment.
The level of theory used was PBEPBE/LANL2DZ. Optimization of the title structure pointed to a low coordination capacity by carboxylate groups as evidenced by the longer Se -O-C=O distances and reduced Wiberg bond indexes. A blue shift was observed for all bands and so we calculated the Raman frequencies at the crystal structure which gave us a better correspondence between spectra. Finally we computed the Raman spectra for the full unit cell comprised of four molecules with which an excellent agreement was obtained (a scaling factor of 0.8 was used).
Unfortunately we failed to further extend this calculation to a larger system with four unit cells and 32 molecules apparently due to insufficient memory; the calculation just stalled and stopped without error after consuming its time in the queue. I’ll try to take a look into it some day.
You can read the whole story in: Synthesis and Crystal Structure of the First Selenonyl Bis(carboxylate) SeO2(O2CCH3)2
Lukas Richtera · Vojtech Jancik · Joaquín Barroso‐Flores · Petr Nykel · Jiri Touzin · Jan Taraba
Thanks for reading!
Last Monday the School of Chemistry at the National Autonomous University of Mexico celebrated 50 years of their modern graduate studies program; as part of the celebrations a formal investiture ceremony for those of us who got our PhD’s after 1990 was organized.
It was a great opportunity to reconect with old friends and teachers, I even got to meet my old high school chemistry teacher, Dr. Salvador Sánchez who in no little way helped me decide to follow chemistry as a career choice, and Dr. Raymundo Cea who was my first thesis director in the first years of this century. The University Rector, Dr. José Narro, gave a speech on the challenges of chemistry in the upcoming years, and Dr. Helgi Jung-Cook spoke about the challenges a PhD student faces and how much rewarding is to finish. Much is yet to be done for the advancement of science in the world and even more in Latin America, but even so UNAM is doing a great effort of keeping a strong base of scientists available for all branches of social development by continuosly supplying the much needed human resources with the highest standards.
In all it was an emotional and inspiring ceremony but above all a fun way to look back to those days in grad school when little happened outside our labs. Thanks to my parents, my sister and my lovely wife and unborn daughter for joining us all in this celebration of Mexican chemistry. (all photo credits: My Dad.)
It is with great pleasure that I announce the graduation of another member of our research group: Luis Enrique “Kike” Aguilar defended his BSc thesis yesterday and is now counting the days left for the Autumn when he’ll move to the Netherlands for a masters in computational chemistry.
Luis Enrique, Kike, calculated the interaction energies of 144 different inclusion complexes where calix and thia-calix[n]arenes were once again the chosen hosts (36 of them) and two drugs for the treatment of chronic myeloid leukemia (CML), namely Sorafenib and Bosutinib, were the guests.
The publication of the corresponding article in which we once again were fortunate enough to count with the collaboration of Dr. Rodrigo Galindo from Utah University in the molecular dynamics section, is still pending but we’re confident enough that it wont take much longer until it’s out there.
Kike is a very diligent student with great learning skills, I’m sure he’ll succeed in any enterprise he sets himself off. Congratulations, Kike! Thanks for being a part of our research but more importantly for being a part of our community.
Earlier this week we had at our annual symposium at the institute of chemistry where we had distinguished international visitors such as Prof. Theodor Agapie, Prof. Lanny Liebeskind (associate editor of Organometallics), Prof. Marc Petit and Prof. Francois Gabbaï (associate editor of Organometallics), as well as our very own colleagues like Dr. Fernando Cortés who presented a recent paper published on Nucleic Acids Research, and Vojtech Jancik who talked about the high resolution crystallography performed at CCIQS. One of the presentations I liked the most was the one by Dr. Abel Moreno who is now doing some research on the proteins that crystallize calcium carbonate in the formation of egg-shells; Dr. Moreno recently got some 70 million years old fossilized dinosaur egg-shells, from which he is expecting to isolate some samples! Very exciting! I visited Dr. Moreno’s lab to take a look at this fossils and forgot to take a picture of them but trust me they were very cool to look at.
Our lab contributed with a poster by ´Maru´Sandoval (pictures below) in which she presented her research on the excited states of bacteriochlorophyll molecules present in the Fenna-Matthews-Olsen (FMO) complex of photosynthetic bacteria, and more importantly on the excitonic transference between them with the use of the singlet fission model.
These are great opportunities to establish collaborations and get new ideas for future work. Kudos to the organizers and administrative staff for keeping the academic life of our institute to high standards!