 We're here in Thessaloniki at the Nanotechnology Conference, and who are you? So, my name is Lefteres Bidorikis, I'm professor at the University of Ioannina, and our job is doing molecular modeling and multi-scale modeling of organic electronic materials and devices. Does that mean computational modeling? What is it? So that means that you design everything and you simulate everything in a computer. You sit in your desk, you design the equations, you design the molecules, you design the devices. And then you see how they work and what they do. And sometimes you can even optimize their performance by actually solving the equations. And you can do that all the way down to the nano or to the atoms or what? No, it's the other way around. We start from the atoms and the molecules and the electrons, and we move all the way down to the device and the performance of the device. What device? So, let me show you here for example. This would be a nice graph showing a big map of what we're doing. So for example, we start with the molecules that we want to study. Once we know the molecules, we study by electronic methods all the quantum mechanics of the molecules. And then once we know this, we can make efficient models of the molecules and go and see the molecular structure. An atomic structure will have many molecules together. We can move one step further and actually study microstructures. This is mesoscopic structures where we can see the blending of different polymers together, forming domains. This is probing the thermodynamics of the system. Once we do this, we have to go back, retrieve the atomic information and redo quantum mechanics in order to get all the electronic properties of these assemblies here. Electronic properties means we know how the electrons interact from molecule to molecule, how they move and what they will do in these materials. We can do something which is called kinetic Monte Carlo. This means that we follow the stochastic quantum nature of the electrons. And this way we can follow and retrieve all the electronic properties of the materials like mobility and transfer of current through them. Once we have all these analyses and now we know the materials. We started from electrons here and we came down to the macroscopic quantities. Then we can start to design our applications and devices. What do I mean? This is one example. This is a photovoltaic cell. Many different layers, each one doing its own function. The active layer is going to be what we designed. The other layers, we know the properties, we just put them in. Which one is active where? The active layer which would be here. This is an example of a very promising polymer, PCD-TBT, blended with a fuller-in acceptor molecule. And these are the guys here who absorb the light, create the electrons and drive the electrons to the contacts to give us current. This is an organic photovoltaic device. We then do the optics, we do the electrics, how the electrons move, how the charge concentration changes in the device, the fields developed in the devices. And eventually we get the very final deliverable of this modeling, which is the current voltage curve. This tells us how good a photovoltaic cell we have. We want to optimize the performance, which means to get the most current out of the cell. So you mentioned all this and you do quantum calculations twice? Yes. So what's happening here? If you want to start and simulate everything, you need to do quantum mechanics at two levels. One would be the structural level, and this is the path that we call the structural path here. This means that you do quantum mechanics to understand how the molecules interact with each other to form the structure. Right? How they come and blend together. When you find the structure, you need to go back again and see the electronics. How the electrons behave from molecule to molecule. So it's at two levels of quantum mechanical calculations at the electronic level. And you can see them here as follows. We start from the atoms, we follow the structural path to find the actual structures that are created. Is this something you just calculate or how do you do this? I will show you videos of how this is happening. These are calculations at very different length and time scales. And this is established science or are you groundbreaking doing something that nobody else is doing? So this is established science from the point that groups have done specific parts of these cycles. But we believe that we are one of the very first groups to really have started from the actual atom, an electron and really move all the way down. So put all the different... All the way to an actual device. Which is a photovoltaic... In this case it's a photovoltaic, a flexible photovoltaic. It could be a flexible OLED, organic light emitting diode. It could be a TFT transistor. It could be many different other things. So this research that you're doing, this work is useful for all the flexible technologies. They all want to have optimal... It's not only for the flexible. It's basically for all the technologies that use organic molecules. So it's for everything that has to do with organic electronics. It could be flexible but you could also do it on a rigid substrate. So the quantum mechanics and all that is like a century old knowledge a little bit? Yes. But how is it possible that it... I mean, this is just working. It just works, all these calculations. So what you do is you start from the deepest level which is quantum mechanics. You cannot solve the device at the quantum mechanical level because it's impossible. You would need a computer which is the size of the whole earth, for example, right? So what you do is you get information from the quantum mechanical level, abstract it and create simpler models. These simpler models allow you to study many molecules like here instead of just a single molecule. Quantum mechanics is only single molecule. It's very difficult. The more information you abstract, the more simple you make the system, the larger the simulation can be, the larger the device that you can simulate. So the whole process here is not we go and just do calculations, but we do calculations, find the important features, create simpler models and move to the next length scale. We study the next length scale, find the important information, keep the important ones, make a simpler model and move to the next one. And this is the path. You go to broader and broader and coarser models. So you can only do this by simplifying in the beginning? There's no other way. But is it okay to simplify? It is okay to simplify. I mean, I'm joking. No, no, no. You have to simplify. You study the complexity by understanding what are the important parts and you parameterize the complexity. If you do not do quantum mechanics, you have no idea about the complexity of the system. Once you study it, you see how it responds. You map the quantum complexity into simple curves and you use these curves to go to the next level. This is what is called multi-scale modeling. And this material here, is it something that's on development or something that you cannot change and this is a great one, or are you trying to experiment with different ones? So you try to experiment with different materials. We started with this polymer here. We will do many more polymers and this is a way of prescreening materials in the computer. So instead of having to actually make the material and make the device, which is very expensive, we can prescreen the material in the computer, study how it behaves and have some idea which will behave better or not. Also study the device, the layers, their sizes, where to put them, what layers to put. So basically we're getting all the information that we need for all the different aspects of the device and in the computer try to put them together and see how they work best. Is it very difficult to make new material here or to find them or how does it work? You have to follow the chemists. So there are materials that come out in the literature that are new materials and they tell us that they have good new properties and we can actually go and simulate them. On the other hand we can actually, we haven't done that yet, but we could do small modifications in the structure of the molecule and see if this is going to be good or bad for the device. So we can actually design the molecules themselves. This is a grand vision of putting everything on the computer and designing even new materials. We have not been there yet, but this is one of the visions that we have. But isn't that what physicists do already? They do it on the computer before they do it for real? Yes. So for many different materials it's much easier if you do inorganic materials which are crystalline. There you understand the physics much better. Here we're working with organic semiconductors which are amorphous. And so all the things that we know from physics do not hold here. And can you show a video? So I can show you a video to get an example. So here is an example where you have a substrate of fuller in molecules and we want to throw and see how the polymer will be deposited on the substrate. This is another simulation where we have a donor and acceptor molecule. Initially they were blended in a totally random configuration and you can see how they evolve and the phase shape, phase separate and they form domains. Different domains of a donor and acceptor. And this is a realistic structure that you can see in... Where is it a square? Square is the simulation cell which is supposed to repeat in space periodically. And there is another one and now you can see here a simulation of a charge randomly going from molecule to molecule as it does this quantum hops from one molecule to the other. This trail here we take we do statistical analysis and we will extract the electronic properties like mobility as a function of frequency, etc. How does it work, the hops? The hops are quantum mechanical hops. We do all the quantum mechanics that I showed to understand all the parameters that are responsible for the hops. And then having the parameters and the numbers we do the simulation of the hops in what is called the kinetic Monte Carlo simulation. And so at the university do you have many students working on this? Here are some here. You can take a... Here is Maria. She can show some more details on these things. Hi, so who are you? Hello, my name is Andrea Maria and I am a PhD student in our group. I'm going to show you some representative studies of our group. Here is a computational study of PCDPT. PCDPT is a promising electron donor which yields high values of efficiency and great lifetimes. So what we want to do here is to study PCDPT atomistic structure properties based on ab initio methods like density functional theory and molecular dynamics. So we are starting from ab initio BFT method and we are dividing PCDPT into two subunits. So we study each one of these dihedrals and we rotate each dihedral in order to get and accurate energy profile. When we find the best method to calculate our energy profile we proceed to the whole polymer and we go again the same procedure and after that in order to check our convergence we go to two units of PCDPT. So we have now our energy profiles and we know how the whole molecule behaves as we rotate each one of these dihedral angles. So we have to repeat the same procedure but this time we are using molecular dynamics and we are using general amber force field. So we perform the same procedure and we rotate each dihedral of the molecule here and we see that the results are different. So what we have to do we have to calculate again some parameters of the general amber force field in order to fit this method with previous ab initio method and we did this and we came to perfect agreement. So after we have constructed our new force field with our new parameters which are fitted to ab initio and correct of course behavior we use this force field in order to see how 8 units of PCDPT behave and here we can see that when we start from a chain from a polymer chain and apply this force field from a polymer chain we can see that the whole behavior of the polymer changes and it started from a long chain and it became this round of stuff and it started to curve around itself. So this is the first step of our multi-scale modeling and now we proceed to the second step which is another molecule we are talking about ICBA which is a very promising electron acceptor, a fuller and based electron acceptor which yields again very good efficiency when it is combined with P3HT. So here we are performing a structural study and study of transverse properties. What we want here to see is how the three different isomeric of ICBA behaves and what efficiency can give each one. There are some experimental studies that shows that different isomeric of ICBA yield different efficiency and they told that they told us that this is due to molecular packing. So the first one that we want to see is if molecular packing is affected by different isomers of ICBA. So we perform structural simulations we calculated different kind of distributions for the three different 3G isomers and we saw almost no difference. So we can say we can conclude that against what experimental guys say 3G isomerism does not affect molecular packing. And that's cool. Maybe you can summarize something. What's going to happen in the future? What's next? University? Yeah, shortly. Because what's going to happen in the future? What's the plan? So the plan is as we said to make this much stronger in terms of finding new molecules designing new molecules and devices being able to work with experimentalists in making faster, cheaper and easier new devices and new technologies. And do you cooperate with other universities? So the very big collaboration we have right now is with Aristotle University within the project CORNET which is a European project and there are many partners there University of Sari is one big partner Fluxim, a company NPL in UK. It's a big project that actually wants to do a lot of multi-scale simulations and also multi-scale characterization this is there part from the university Aristotle to be able to really understand how organic electronic materials and devices behave and in parallel with this also to make the standards and the protocols and the standards of what is the proper way to do simulations what is the proper way to do customization and all of this together will basically hopefully help the community to move much faster and bring new technologies in the market much faster and cheaper.