Welcome to the introduction to the computational chemistry playlist.
Computational chemistry can be broadly defined as the use of computers to solve the equations
of a theory or model for the prediction of properties of chemical systems.
Traditionally, science had two main branches: theory and experiment.
Theory made certain predictions for experiment, and experiment tested those predictions and
refined the theory.
When I use the term "model" up here as in "theory or model" I just mean a simplified
representation of a physical system.
Sometimes when you're talking about theory, you're talking about something much more broadly
applicable and something much more general, and sometimes when we're talking about a model,
we're talking about something more simplified and more specific to certain kinds of systems.
But sometimes the terms are used interchangeably.
Look at the context of the discussion to see whether or not theory and model mean the same
thing.
We had our traditional situation with theory and experiment, but due to the advent of modern
computers (computers are now capable of performing arithmetic so quickly) that we have essentially
another branch of science emerging called "simulation".
Now with theory, we can generate mathematical equations which are very complicated and require
a lot of intense computing, but simulation can find solutions to those theories or to
those models (applied to specific physical systems).
And similarly, something that would be a very difficult experiment to perform we can perform
a simulation which can help with the interpretation of that experiment, and its refining and testing
of hypotheses.
Experiment can further develop new parameters than can go back into improving the simulation
and its feedback to experiment.
These three branches of science are all feedback loops into one another, with simulation being
the newest member of the three.
As I mentioned, simulation is the newest member.
That's because computing did not become widely popular until the second half of the 20th
century.
That is because computing is now much faster than it has ever been before.
Why is computing so much faster now?
Things we have going in our favor are Moore's law.
The fact that the transistors which do the computations on computers are getting much
much smaller, much much cheaper, and produced in much greater volumes than before.
Moore's law is about the number of transistors that you can fit in the same area doubling
every 18-24 months.
Obviously, if something doubles every 1-2 years, then over the course of a decade you
can get 2 orders of magnitude quicker, and that is the situation from the 1930's up until
the early 2000's.
We also have the advent of parallel computing, where lots of computers can work together
on a single task.
We have cheaper hardware.
Things have been getting exponentially cheaper for quite some time now.
Whereas a single megabyte (1,000,000 units) of storage would have cost $1,000,000's in
the 1950's, now terabytes(1,000,000,000,000 units) of storage online are almost free.
Hardware is getting to the point where the cost per unit is shrinking dramatically, and
it's getting much much cheaper to compute things as well.
And also over the course of decades companies have developed much better software, and there
is a variety of software as well that is used specifically for computational chemistry,
which allows these simulations to be run.
In computational chemistry these properties that we're simulating, that we're trying to
predict, can be anything.
If you can measure it in an experiment, then in principle you can compute it.
Perhaps there isn't a software package which has been developed to compute certain properties
yet, but any property that can be measured can be computed in principle.
These properties include things based on energy (interaction energy, binding energy, conformational
energy, excitation energy, ionization energy, anything involving the energy of a molecule
or system of molecules).
Things that involve structure (the geometry of a molecule or a system, the location of
the atoms, the geometry of a solvation shell, of a crystal structure, dipole moments, polarizabilities
of electron clouds).
Also things related to spectra (infrared [IR] spectra, nuclear magnetic resonance [NMR],
microwave [rotational], UV-Vis, X-ray) all of these spectra can be simulated in various
ways.
Then there are a variety of properties which are emergent out of these or combinations
of these (bulk thermodynamic data, equilibrium, kinetic rates).
Over the course of the computational chemistry playlist these are the types of ideas that
we'll discuss, the various models that are used to compute them, what is behind them,
and how we go about carrying out these simulations.