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Scientific Presentations with Prezi

An interesting way to present scientific or technical information in a simple but nonlinear manner.
by

Christopher Wilmer

on 31 December 2010

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Transcript of Scientific Presentations with Prezi

Can an entire book be written in the space of one sentence? A really useful way to give scientific presentations using Prezi - By Christopher E. Wilmer The "problem" with scientific presentations is that: You either give lots of details, and put everybody to sleep
You give no details, but then nobody believes you (and rightly they shouldn't!) A common work-a-round is to tell the simple story first and then put all the details at the end in case someone has questions... The simple story... Title
Slide! Conclusion
Slide Slide #1 Slide #2 Slide #3 Slide #57 A Cure
For All
Diseases It Works, Trust Me! We used Monte Carlo double-blind clinical placebo R^2 = 0.4 Slide #58 Significant hypertrophy of O(NLog(N)) Nash Equilibrium.
QED Slide #107 Questions? ...the details. This work-a-round suffers many deficiencies... "Thank you Dr. So-and-so, could you please go back to, err... slide 15 (or was it 16?), and explain how your retrovirus reverses climate change?" ... not only do you have to navigate back to slide 15 (or 16?), you have to then navigate all the way forward to slide 79 where you have the details! With Prezi, there is finally a good solution. First, show the audience your entire
presentation at once. Rapid screening of metal-organic frameworks for carbon dioxide capture via the charge equilibration method
Christopher E. Wilmer & Randall Q. Snurr
Chemical & Biological Engineering, Northwestern University The simple story (very short!) The Title of This Presentation Dr. So-and-so, Collaborator #1, ... , Collaborator #N (encourage them to ask questions during your presentation)
[this is common in the sciences] Details! Unfortunately, Prezi does not currently have buttons for non-linear slide navigation...
so for now we have to click (carefully!)
in the right place.

Let's look at an example from my actual research. Details! Details! Details! Details! Questions? Click here This is a demonstration
of a nonlinear presentation. Back to story? Click here Questions? Click here Back to story? Click here Details are added vertically, while the story goes horizontally. Questions? Click here MOFs have the highest surface area per gram of any known material. The best MOFs today have over 6000 square meters per gram of material.

Since gases universally like to stick to surfaces, the more surface there is in a material the more gas molecules will stick.
The technical word for "sticking" is adsorption. Back to story? Click here Questions? Click here Back to story? Click here In general, the amount of adsorption depends on temperature and pressure. The example above was done by Andrew R. Millward and Omar M. Yaghi at very high pressures
(over 30 times the pressure of the atmosphere). Questions? Click here Back to story? Click here Questions? Click here Back to story? Click here Questions? Click here Back to story? Click here Questions? Click here Back to story? Click here Questions? Click here Back to story? Click here Navigating with a keyboard or wireless remote would remove the on-screen buttons, which clutter the display. Finally, I'd like to mention that I avoided using many of Prezi's features here, not because I don't like them, but because I wanted to give a "pure" demonstration of a single idea.

Please let me know what you think!
c.wilmer@gmail.com Adsorption Pressure Note: To advance the presentation as it was intended, use the "next" button in your browser.

Only if you have a question, click on the "Questions" button for details. Once you have read the details, click on the "Back to Story" button.
(sometimes you have to click 2 or 3 times, sorry!) There is good reason to believe that a MOF can help reverse climate change. If we design the right MOF, we can capture greenhouse gases from powerplants before they are released into the atmosphere. How do we find the "right" MOF for the job of saving the planet?

The traditional strategy is to make new MOFs in the lab and test them experimentally.

This is too slow. There are millions of possible MOFs, and a solution to climate change is needed urgently. W We have developed an accurate physical simulation method that can very rapidly predict which MOFs are best for capturing carbon. The MOFs that we have identified so far are inexpensive and can be used to develop carbon capture technologies better than what exists currently. But we hope to find even better MOFs in the near future, using the same methods. This simulation protocol was reported in the Journal of the American Chemical Society in 2009, by Prof. A.Ö. Yazaydin in the Snurr research group. (summary of results on the right)
Adsorption isotherms were predicted using the Grand Canonical Monte Carlo technique. This technique determines the energy of the interactions between the CO2 molecules and the MOF atoms in millions of random configurations. The final result is an accurate picture of the average interaction energy between CO2 molecules and the MOF at a given pressure and temperature. A.Ö. Yazaydin, R.Q. Snurr, T.H. Park, K. Koh, J. Liu, M.D. LeVan, A.I. Benin, P. Jakubczak, M. Lanuza, D.B. Galloway, J.J. Low, R.R. Willis, Screening of metal-organic frameworks for carbon dioxide capture from flue gas using a combined experimental and modeling approach, J. Am. Chem. Soc. 131 (2009) 18198–18199. In the simulations, the MOFs were assumed to be perfectly rigid, and the interactions between CO2 molecules and MOF atoms were modelled by the 6-12 Lennard-Jones potential.

Electrostatic interactions were modelled via fixed partial atomic charges on all atoms that were determined in a previous step.

Each point on the adsorption isotherm was calculated using 100,000 equilibration cycles, followed by 100,000 production cycles. We have recently made a significant advance in the speed with which we can predict the properties of new MOFs. Previously, we calculated the distribution of electrons in MOFs by solving Schrödinger's quantum mechanical equation: Schrödinger's equation Electron distribution But it is much faster to simply use Coulomb's law and well known atomic electronegativities to get the same information! The energy of every atom in a MOF, as a function of the number of electrons it posseses, can be approximated by a 2nd degree polynomial where the linear coefficient is the measured Mulliken electronegativity. The quadratic coefficient is half the measured "atomic hardness", which is derived from the measured electron affinity and ionization potential. If we sum this energy term for every atom in the MOF and model the interactions between the atoms by Coulomb's law, we get an equation for the energy of the MOF itself: The electron distribution that minimizes this master energy equation is the "true" distribution. For more details on our method, please see:

C.E. Wilmer and R. Q. Snurr "Towards rapid computational screening of metal-organic frameworks for carbon dioxide capture: calculation of framework charges via charge equilibration", Chemical Engineering Journal (2010), in press At a small fraction of the computational cost, we predicted the same CO2 adsorption for 13 different MOFs using the approximate technique (Charge Eq.) as the when using Schrödinger's equation (ChelpG). Soon we will apply this technique to screen millions of MOFs at once, and we think we will find the diamond in the rough. The End. I would like to acknowledge:
Prof. Randall Q. Snurr and Prof. A.Ö. Yazaydin for their guidance and the TeraGrid computing resources.
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