 My name is Wei Ren from Shanghai University. I'm so pleased to introduce our special guest, Professor Xing Gao Gong from Fudan University. I will give a very brief introduction to Professor Gong. He received his physics degree from Hunan Normal University in 1982 and a PhD from the Institute of Solid State Physics, Chinese Academy of Sciences in 1993. He joined the Fudan University in 2000 and is currently a Xi De Chair Professor of Physics and is also the Director of the Key Laboratory of Computational Physical Sciences, Ministry of Education. His research is focused on computational studies of the structural and electronic properties of materials. He's the Fellow of the American Physical Society. He's also a member of Chinese Academy of Sciences. Without further ado, let me give the microphone to Professor Gong. Welcome. Okay, thank you very much. Thank you, Professor, then for the introduction. I'm really, really, very, very happy to join this special school with my older friends, Stefano, Gebara, and many other friends. So, I'm very happy to join this school. I'm very happy to see this name, Quantic Special, and as Stefano explained in his opening, his name invented in Beijing. That's an electronic structure of a school in Beijing, but it's partially involved as an organizer. Actually, in the last 20 years, I'm also using Quantic Special in my group, although sometimes I'm also using WASP in some cases. So, I'm very happy to join this kind of school. Today, I'm going to talk about my recent research on this kind of interfaces in photo attack devices. And why? Okay. So, this is kind of related to this photo electronic effect, which is invented something 200 years ago, which was explained by famous Einstein. Of course, this work is also an invention of this quantum mechanics. Now, this kind of thing has become this really sonar cell, and it's become very popular in the whole world. Now, in China, this kind of thing developed very fast in last few years. And I have a good number of years. In last year, this kind of sonar energy now becomes 5% of total electricity in China. And now China has a very emotional plane in the next maybe 30 years. The sonar energy will be increased to 30% of this total electricity. So, this could be a major power income to the whole world, and also to China, of course. And although this kind of physics is almost, the basic physics is there, but to make this kind of cell is not that easy. Actually, many physical processes are involved. And this is the picture I will not show you because it's the main process for this kind of sonar cell. And firstly, you need a semiconductor, I'll say an absorber to absorb the night, which you need to need a proper banner gap. I'm sure here is a VBM or CBM here, a proper banner gap. Usually it's something like 1.1 volts to 1.5 volts. These kind of materials you need to shine a night, of course, and these materials absorb the night. As soon as you go to the night, the photo is absorbed, it's emitted these electrons from the Venice band to the connection bands, and these holes and electrons pairs are generated. You need some relaxations from these electrons to the CBM and the hole will be relaxed to the VBM. Then you need to transport these whole electrons and then to get the output and get this voltage and then again external mode to make it work outside. So this is basically the physics of this sonar cell. And actually there's many more details, more complicated things inside it. For instance, as soon as you get these electron holes paired there, instead of transported away, there will be sometimes recombinations and jumping at night, a photo away. This is useful for the working of this sonar cell. So basically the problems now we need to improve is for the efficiency of the sonar cell is we need a very good absorber. For instance, now most people using the silicon, from the physical point of view, the silicon is not the best absorber because of this indirect banding gap. So in the last 30 or 20 years, even 10 years, people are trying very hard to find some better absorber with a direct banding gap. This way they can have very similar materials to absorber night. And also there is a lot of complexity in the device because of the interfaces. So they need this interface to get these electrons or holes out of this absorber. So this kind of thing is really crucial for the efficiency of this cell. And this is, I'm going to show you what the real sonar cell looks like. You can see in the device there's many layers, in real systems, even more layers in the cell. Here you can see one, two, three, four, five, say if you counted the back, it was six layers. And only this one is absorber. Other things is you need to get these electron holes out that these layers. And you can see in this device there's many interface. These many interface really affect this efficiency. Even in this absorber, you can see here, there's many green boundaries. There are many, many green boundaries here. And of course you can use single crystal. If you use single crystal with green boundaries, the cost will be increased very significantly. So in many materials absorbers, they're still using these materials using many green boundaries. So these kind of interface and green boundaries really affect this kind of properties of this cell. The existence of these interfaces, I say, really affect this efficiency. And also they need these kinds of materials to be, to build these interfaces to make these band, band and bandings nice, something like this. So this is really a tricky, a complicated thing in the experiment. So today I'm going to give you some of my recent results about this kind of how to study or understand the interfaces. I'll say the algorithm is a band of set, how to calculate this, now when you put two materials together, how to calculate this band of set for any materials. This is a really tough problem for the devices. And also I'm going to give you some results for these green boundaries. So in the episode, what's the physics and standards experiment. And also give you some, or recent results or recent algorithm, how to really study these interface structures with these neural network potentials or potentials with this very complicated interface structures. Okay. For these semiconductors, usually you have this kind of band alignment. And so this is a very typical, this is from the textbook. So if we put two materials together, the VBM, CBM, usually you have this kind of three type of alignment. And this could be something that matters. So the question is how to calculate or say give some ideas. Usually you cannot get exactly, give some ideas to experiment what this kind of alignment will be. In your activity calculations, we usually we can get as a band gap. Although there's many problems how to get it actually a band gap, but still you can get some approximate numbers. And you can get this number for my materials, but it's very difficult to get this, really an alignment. The question is why they cannot get an alignment. That's because in the, all of these benefit calculations, we use a periodic boundary conditions. In the protocol condition systems, you cannot, the potential is not uniquely determined because you solve the postal equations. So you cannot get exactly how this VBM, alignment for this VBM or CBM for two materials. So this is a problem where now, where now I go. But in the experiment, also your real systems, we do need this kind of things. And I think there's many measures to do this. But I would like to make one since here. It's almost 20 years ago and the way and the single, they have proposed to do this. And you have two materials here, one material, one here. So you need to calculate the alignment. You can form a superities. You do one calculation, you do one calculation. In this case, the potential is determined. Okay. The relative potential is uniquely determined. So in this case, you can calculate that this kind of so-called band alignment. But this is a problem. So you essentially, when you put two materials together, you need to deform this, usually you need to form this kind of materials. So you may ask, the deformation will change in this kind of band offset. So I think this is my first work for coming to center doctors, and I think 50 years ago, and we made some corrections by taking into account the banded deformation potentials. So we calculated the deformation potentials from one materials where you had deformations. So in this way, as soon as you get this deformation potentials, in this way you can make corrections for this band offset calculations with the deformations. And this is really works for some small distortions when two materials form this, and so on. And this really works good for some many systems. But if these systems have a large deformation, maybe 10% of even 5%. And the method from adiabatic deformation potential doesn't work well. So a few years ago we proposed another method, even a simple method, we call it three step method. And when you put these two materials with large distortions, and we have built some intermediate states for themself. So in this case we know how this potential deforms. And in this way we can calculate this band offset easily without any adiabatic deformation potential. This is really somehow works well. And we made some tests in the benchmark for this one. For instance, we put this system, or Ganyancent, we put it in numbers here. So we'll use this first version of for supernatism method. This could be something like 0.86 for the band offset. For the visor adiabatic deformation potential corrections, something like a 0.7, with these three step method is a simple method, something like 6.8, something like 0.7. So this can be reasonable good for these three step method. And for this Ganyancent, the indiancent, this will be significantly different because using this traditional first version of supernatism, this is also almost zero band offset. And if you use adiabatic deformation potential, it's going to be something like a 0.4. And this three step is something like a 0.4. Expanded people. Data is something 0.4. So in this case, this three step method works well for these distortion systems. But with some systems, you cannot form supernatism. So if A and B materials with different symmetry, so there's no way to get this supernatism by any net information, or you say if you put it against the interface, it could be a disaster. So we propose another method, we call intermediate method for carrier band offset. So we propose another new phase of supernatism. And we make sure A and X could be for supernatism. And A X is for supernatism and B X and B for supernatism. So in this case, we calculate band offset between X and also the band offset from X and B. And then we can A and B. So this way we can get the band offset to something this. When A and B cannot form supernatism, this could be a way to get the band offset approximately. So we propose how to find a good intermediate phase. And usually you need no band energy and also a large band gap and how to match my point. You need no band energy and large band gap and good structures constantly match with two end point structures and B. So with your paper we propose some simple algorithm to this but it's not necessary. But with a large band gap so to make sure this kind of sense is working so we made some benchmark. We look at this band offset with karygium pterolite and karygium sulphurite. This is a zinc-brank. This is war-side. This is very special systems because in zinc-brank and war-side you still have a chance to form supernatism because it's one of the A and C directions and you can put this kind of thing together. So of course you can use another method like we propose to find intermediate state. So if we do something like a three-step method, so that means we directly put these two things together we get 3.7 electron volts for this band offset and now we use the intermediate state so we find the phase something like this. We call the karygium pterolite sulphur these phases we just find it by computers. It's not a real phase. It may be not existing maybe or maybe not but it doesn't matter. We also use pve-gap something like a 0.8 electron volts something like a semiconductor and we put it together here so you can combine with this karygium sulphur and also with the karygium pterolite. In this way we get something like a band gap and I mean something 0.7 so it's very close to a three-step method this is from the direct method and this is from the intermediate state so this is really quite reasonable so we do another application of test so we do a diamond graphite so this is top of the different symmetry so you can find no way to put it together to form these sub-nities so we get something like we call the intermediate phase it's a carbon carbon 60 carbon 16 which can combine with this diamond and also with this maybe with diamond and also with graphite so we get something like the benefit is something like 1.5 it's very close to I explain the people 1.4 so this really makes sense this intermediate state is working so you may ask why I'm working on this kind of since this is because in the solar cell there's really something happen which leads to very special method of cagolid so let's come to this kind of solar cell matrix called CZ ETS this is carbon zinc sulfur or cyanide this is since you went to some these materials you went to something like 12 or 10 years ago and these people believe this must be very good systems because this is very cheap materials only carbon zinc or cheaper elements so it's also very good better gap something like 1.5 and but people will find that this kind of since the efficiency is much lower than the theoretical prediction so now it's something like 12% is theoretical should be something like 30% even better than the silicon so we need to look at these real materials to see what really happen so if you look at these real devices experiment people find that during this interface between this and this back contact there is a new face, new materials formed it's something like a mobilium sulfur or mobilium cyanide too so experiment people don't understand these interlayers it's good or not, who knows that so we won't theoretically want to understand what really happen and it's usable or harmful so we need to calculate these bangles that between these CZTase and the mobilium sulfur or cyanide you know most people maybe know that for the mobilium sulfur is there two-dimensional systems is there but for the CZTase it's a second-branded materials so you don't have an easy way to put it together to calculate these bangles so we propose two artificial materials which is also similar to these chemical compositions and we find this kind of two materials with something like the PBE banner gap with something 1.4 or something like that 0.9 so we put it together we find these phases and we put it together with these mobilium sulfur too on those CZTase and then we can calculate these bangles set so what do we find so for these mobilium sulfur too or the CZTase this is a bangles set so the VBM of this mobilium sulfur too is something like 0.3 electron volts lower than these absorbers of this BBM but if this is CZTase so this mobilium the VBM is higher so this is intrinsically different but which one is the right let's look at this one so here in the absorber the holes near the VBM of CZTase so in principle people want these holes transport from this VBM to the bank conduct but if you look at these structures there's no way that positive does not want to jump to no energies so this kind of band alignment will prohibit the transportation of the hole but if it is for the CZTase okay so with this kind of band alignment the holes here in the absorber generated by the photons and will automatically easily transport from absorber to the conduct so this is the people want the way and this is the experiment to find the way okay so this is from the calculations we tell the experiment people that for the CZTase for the CZTase the interface layer with the mobility sulphide is really bad which handles the holes P type CTS transfer into the mobility electrode so this is very bad but you need to have this one actually experiment people already they realize something because they experiment people find if in these materials if you annoy some cyanide and the efficiencies will be increased I hope this is the reason because if we have some cyanide in the phases they will form some mobility cyanide in a way for the beta hole transportation so in this way as soon as we get this we understand this is very bad and this is what we want so the conclusion is that the device is actually in the CIGS in other generations of this solar cell they use mobility as the back contact so in the new and other absorbers if you use the same back contact this is not the problem so this is our conclusion you really need to do something for this bad contact otherwise they prohibit this transportation of the holes so this is the conclusions from the method so we propose how to optimize the cell performance so we say we need to doping some cyanide in the interface in absorbers, CIGS and mobility contact in this way the form this mobility cyanide which will be fascinating this transportation of the holes this is our proposal for the experiment people okay so this is for this interface problems and now I want to come to the green boundary in the absorbers as I showed before in these absorbers like many absorbers there always is many green boundaries what's the green boundary effect to the efficiency of the solar cell and how we understand the role of the green boundaries exist in these absorbers so this is we we get some understanding and we understand many experiment data so actually in the literatures there's many many calculations many calculations to understand to calculate these green boundaries in the trans structures mainly all the calculations found that there are many non-removable defect states well many defect states as it means the green boundary contributed to the defect states in the band between the VBM and the CBF these are different states even in the calculating in the CIGS you can see many different states and also in the CGT as I just mentioned there are many different states and also there are many theoretical papers to try to remove these different states by doping something but what they found is there's no way there's no way to remove these kinds of things so experiment people found many defect states many non-removable defect states in this kind of green boundaries of the solar absorber what's happening in the experiment experiment people find that the post of pre-treatment is really necessary for better or good devices but the treatment is with different materials for instance using CIGS we must use the sodium and potassium and with CGT it's also something like potassium but if you come to cation tail line you must use the cation chromium too so here is something like sodium and this is cation so people really found this really necessary for post treatment or pre-treatment they found that with this treatment these kind of materials really comes to green boundaries but why this kind of treatment will increase this efficient solar cell there's no answer so we performed some calculations we answered this one to tell you so what role does post treatment play in the green boundaries so after some calculations we propose something like we call the self passivation role for these different states of the green boundaries for instance in the green boundaries there are some missing atoms for instance these are atoms so in the perfect structures there must be some ketones between these four atoms but in the green boundaries there are some ketones missing so this is the typical green boundary structures so what self passivation role means we say in the green boundaries the different states from anion core can be self passivated by its ketones so this is way easy to understand so for instance here this is anion core so all of the atoms are anion atoms so the different states produced by these kind of structures can be passivated by doping a ketone atoms these are simple pictures and this could be for a tenor rate and for the quadrate also the same so this is something like some empirical rules so I'm not going to show how it works, it really works so this is for this three cladium terrarium green boundaries and this is anion core and so some some ketones atoms missing away so this is for really a different states and if you perform first-person calculation by a quantum space or as a method you will find that there's really different states here near this center of this green boundary and if you look at the structure there are some different different boundaries in the gap so this is actually all the people know that these kind of stories so what my rules said in this kind of core cell so this is the structures with this quantum space so we say if you put one ketone red atoms inside of this the different states will move away so for instance we put the one ketone red atoms this is the cladium here and this is structures and if you calculate the band structures or electron structures you'll find that this really opening gap and this is the different states move away so this is just the confirmation of several personal rules here for these systems and this is if you put instead of put the ion away you put the interstitials here again the gap is open and this is the different states but if you look at the energies they say if you put the interstitials into these green boundary structures and in some cases chemical regions really get this energy gain and ejectivity is also could be stable and a different state can be moved so this is the same for other materials like CZ CITS in this case you put a sodium or a copper inside of this green boundaries you can move these many different states away or gap or open and for CIS for the pure crystal green boundary just made in a different state here and you put some copper inside it and this different state move away so in this case both copper and potassium really can pass away these different states in CIS and CITS but why experiment people don't use this copper but sodium this is it must be some other story and in this in CIS we already knows that from our calculations that these materials there's many different states there's many different states and you should produce by the copper and the copper will be produced by the zinc will be produced by the copper this is different states are really very bad so we need to really to reduce this kind of symmetry the different states how to reduce these different states you just need to put the next copper inside it so if you want to pass away the different states in the green boundary using copper in this case we will produce more these kind of defects so experiment so we cannot use copper instead of using sodium so with this kind of studies we understand why the experiment people use a different process for this kind of for the sodium cell so for this calatum terrarium they're using calatum chromium for pass away because the green boundaries need this calatum to pass away the different states so if we have these different states in pass away there's less different states and there's less recombination rates for these electronic holes for the CIS and the CCTS we found that both sodium and copper are possible for pass away these different states in the green boundaries but only sodium is helpful because you cannot use copper because if you have more copper you will have more defects for this copper replacement which is really harmful for the devices so with this we understand this why they use this kind of pre or post process for this sort of cell so if you realize that what examples I show here are for 2-6 systems 2-6 semiconductors is this the preservation rule correct for this silicon germanium or something 3-5 semiconductors okay so when we write a certain paper we free ask us and at the very beginning we say we could be right and unfortunately the conclusion is not so they are just the proposed self-compression version rule is not right for these 3-5 semiconductors so why and we give some ideas but people perform similar calculations for 1-7, 2-6, 3-5 and 4 these kind of 4 series of semiconductors and some people will realize this for this 1-7 ionic systems the zinc plant is not the most stable but in this case we won't understand the physics so we calculated this 1-7 for these systems also with zinc plants structures from the structure we do find that for 1-7 and 2-6 the structure relaxation quite similar there is a large structure relaxation in the boundary core so you can see that some 40% 20% for some bounds in the core of ground boundaries but for the 3-5 and the 4 I see the elements the semiconductors the boundary are almost 0 very very small so this gives the indication that the self-compression self-compression rule for the 2-6 semiconductors will not correct for these systems so we will give you some more ideas why so if we look at the joint structures for this 4 series of semiconductors if you look at 1-7 and 2-6 if you look at these charges distributions in the core of ground boundaries these two are quite similar they are quite similar but for the 3-5 and the silicon for the ground boundaries and the silicon the charges in the core are also similar what's the difference between these two you can see here for the ground boundaries there is something like a boundary a boundary between two irons here in the connective term let's do a low boundary between these irons for the garland acetyl there is a boundary between the garland acetyl and also the silicon so this gives a strong indication this will be different and this is in the electron structure you can see this is a metal this is a metal different states in the boundary so this is a strong different states from these more detail electrons in electron structure calculations we found that this is in this garland acetyl silicon there are two electrons more two extra electrons in this boundary core if you look at the band structure you can see here some bands are occupied I don't know how to say this is two electrons so we give you ideas if you have two electrons in the cell you can remove two electrons away so how can we remove two electrons away we can adopt it this is a simple way so we double we replace one gallium with copper or silver so gallium has three electrons and copper has only one electrons so as soon as we do this kind of replacing from calculations you can see in the garland acetyl there are many different states here as soon as we move two electrons away the copper and silver there is a gap so some difference never move away so in this case we can make we can remove different states from different gaps but this is only theoretical possible so we make some calculations but for experiment people it's very difficult to say we replace this gallium with the copper in the same boundaries so it's hard to be realized in experiment how to do this they can only use these hydrogens to take one electrons away so this is for acetyl and the garland acetyl people use hydrogens okay okay I have some 10 minutes okay so now we move to this interfaces they are observable and these buffoliers this is observable for CIGS or CGTAS or for cation terrarium people use these buffoliers for the cation this is a type of this way you can remove the electrons away with these these this gallium terrarium is one of the most important materials to go many uses and also good for this solar cell because it has 1.5 volts so it's very good it's a binary so since 40 or 50 years ago we had this kind of this kind of materials but still some problems and one problem is what's happened there is really an interface between the CIGS and the CGTAS so we need to do some calculations the simulations for these interfaces and we do because this interface is very complicated we cannot simply do this by the first principle so we use these machine learning potentials developed for that in our laboratories actually by my colleague by Netsupan Liu and he has a pen name something like NASP this is his his potential I think this is the first very first talk by Professor Robert he uses this potential this is something similar it's a neural network potentials then we use this kind of potentials and we use this global structure of the machines we also developed in our group because I'm 12 to optimize these kind of structures for the evolution structures and this potential we tested it's reasonable good from the energy point of view and also energy change you can see the red and the first principle in NASP it's very small difference less than 1% of this kind of one it looks quite good so we use this kind of potential to start these interfaces even using this kind of potential you still need more to start these interfaces so that is mismatch between these two materials it's something like 9% and so we instead we need to find the printed together so we make a huge stripper lattice because now we put this curriculum and we put a curriculum sample printed together and so we we build this stripper lattice with 8 unit cell and this is 9 unit cell in this case you can see this less than 1% of total let's count this is 7.5 this is 7.7 so in this case we try to minimize this kind of distortion the gap between these interfaces and this comes together and form these so called interfaces and then we want to start these interface structures and properties the minimum model for this system will be called something like 1740 atoms and we also build a much big one so today we put results here so what's the structure we performed first of all similarly anemones and we found the model calculations models here and heating up and up to very high temperatures you can see energy boom it's a jump that indicates the structure change and then you heat up and you become an adequate so instead we want to find more energy structures we take structure here and then cooling down and see what's happened and this is what we got this is a structure we got it and you can see the interfaces to create two regions one region is really perfect there's one powerful system it's like a very powerful one and there is still something like how to say a dislocation because this is 8 atoms on 9 so this is a dislocation it's 8 dislocations here and also we found some some inter diffusions atoms is diffused up because this is I need in front of high temperatures if you put these atoms down the energy is a little bit low so high temperatures this indicated in high temperatures the inter diffusion of this sulfur is connecting with inter diffusion of sulfur and terror is quite possible so this we get these kind of structures and so this could be some dislocation here could be the most stable one and also we also we explore the inter structure with the defects and that means we not chemical compositions for the film vacancy or in the studios in the interfaces we use this evolution method to check the structure on the interface and by the way I would like to mention for the perfect systems as a result missing many atoms and the structures we obtain by is the same as we obtain by this evolution method so whether we can get it so first we can get this interface we can define the interface energies so this is a very standard deflation which depends on the chemical potential of the molecules and also these atoms so we can calculate these kind of chemical potentials with neural potentials and DFT you can see it's quite very very close so we believe this neural network potential is quite reasonable for this kind of systems when we calculate this interface energies we use this kind of model so this is bug 1, bug 2 that's colloidal and there is some vacuum because if you use the periodic manipulation there's two interfaces which automatically simultaneous happen in the model we cannot get these real simple interface energies so we use these models we get these interface energies so once we got it once we got it for this colloidal for the regions for the regions so colloidal systems the interface with pure perfect chemical competition very stable for this colloidal which places so the systems with two or three or four interstitials because they're very stable okay and in any case in any case if it's a vacuum the structure with the colloidal vacuum is really unstable and if you look at this interface energy changes for the chemical potential of the sulfur for the sulfur reaching positions the interfaces prefer a perfect system resulting in defects but with the sulfur poor positions they prefer one or two sulfur vacancies here the system becomes stable so this is the test is that the interface is really depends on the system size conditions okay if this the structure interface could be perfect or could be some defects if you look at this colloidal material the stories could be quite similar if for this colloidal regions they prefer these perfect systems for this colloidal poor positions they prefer some vacancies for this terrarium which positions they prefer some interstitials inside it for this terrarium poor positions regions they prefer some perfect systems so in any case the interface structure is really depends on your chemical potentials when you system size so we use these AI potentials we get some interfaces the properties of these solar cell devices of course with these kind of real structures we can calculate it's quite similar to this nature panel set but it's some different defect and formed okay I'm not to finish all of my talk so I just want to tell you that we developed a serious method to calculate the nature panel set which is necessary to quantity for these real devices of solar cell and also I think it's also important for other devices where the interface becomes very important and also we understand that it's the properties in these 2,6 or 1,7 semiconductors we propose that it's kind of so-called self-preservation unfortunately this one is only not working for the guiding asset or 3,5 or 4 and we based on the neural network potentials we predict the interface of the structures and this could be for the in the town and this could be a more important algorithm to start these interface properties for these real materials of your devices and we are working on more company systems with this similar method to prove that these kind of systems are really working so this is my cooperation with many people and the work is supported by ASFC and the most and the Ministry of Science and Technology and Shanghai Municipal support thank you very much for your attention thank you let's stop here thank you very much Professor Gong amazing presentation I think we have some time for questions and the discussion let me check may I break the ice okay save it thank you very much for the beautiful lecture you gave us I have just one question about your use of neural networks for predicting the atomistic structure of the interface so interface is between 3, 5 of 2, 6 or mixed semiconductors for instance 4 to 5 to 6 or 4, 2, 3, 6 or 2, 3, 5 can be charged and much more so in the presence of defects so local charge is expected to have an important role in the interface energetics I'm wondering whether your neural networks can properly mimic the local charge state or in other terms if your training dataset includes charged interface configurations thank you it's very serious questions first what I have to show you here this is only for 2, 6 systems so the charge is not that serious in these systems so without defects no defects there and the charge transfer so it's not that serious but with defects there's something during the test training the dataset we have included these we included liquid we could defect in the solid so these could be not serious problems in the systems I have just presented we really realize that your comments are such questions now we are working on a more complete system with lithium battery systems interfaces this is we found some cases are fair so we are trying to include more staff more companies with euros to solve these problems for some systems like lithium battery systems charge state change how is it like a copper the charge state could be changed so this can be tested it still works well yeah if you really take this kind of conclusion your training test thank you she is here thank you for all the people in the audience please if you have any questions please again and ask directly I think I saw the first question even before the end of the presentation Nira Kuhari asked how to calculate interface energy of absorbed hetero structure so I have shown it here yeah here we define this interface energy here this is the total energy of your estimation cell you need to minus the energy of these atoms that are included this included could be a defect since here so if you use these kind of systems one seems for the newcomers that normally have two phases so in this case here we use just one interface so it's easier yes Stefano so after talk we can discuss a little bit can we discuss a little bit sure so really to I'll send you a zoom link a private zoom link sorry there is a question from the streaming youtube so I'm reading it would free oscillations due to the defects affect the transport properties in these devices sorry if you ask questions from the youtube so the question is would free oscillations due to the defects affect the transport properties in these devices you mean for their oscillations free oscillations yes of course of course of course this will be seriously affect this kind of electrostatic or different states okay it's kind of oscillations there it's significant affect these defect properties for these carry recombinations okay thank you okay that was a question from youtube channel in our zoom meeting room I also see a lot of comments thank you for the wonderful lectures and someone also said quite a lot of work and nice results okay so on behalf of the audience I would like to thank Professor Gong once again for the lecture okay thank you so Shingao watch out your email we'll see each other in two three minutes okay good bye bye thank you bye bye thank you thank you all