In this lecture, we will be looking at a specific spectroscopy tool which has been widely used in materials chemistry and as the title suggests, there are two issues that are involved in this spectroscopy. The name suggests that it is a x-ray photoelectron spectroscopy therefore, there is a x-ray that is produced when a photoelectron is ejected. So a combination of two processes that are happening brings about a very rich chemistry that one can learn. Material scientists, physicists and chemists have used this technique extensively and this is now a very established tool for characterization materials in the last three decades improvised and very sophisticated instruments have come. In the last two decades, the machine could actually occupy a very big room but today the sophistication of this instrumentation has moved such a way that even a benched up x-ray photoelectron spectrophotometer can be used. So we will look into this issue of what this principle behind the spectroscopic tool is. And if there is something very highly complementary to x-ray diffraction, it is the spectroscopic tools and as you would see in this lecture, there are several spectroscopic issues that are manifested when x-rays are emitted and how this can be mapped and how we can translate this into quantifying some results we will see in the next few slides. And to start with let us see how we create x-rays and how the spectrum of a x-ray tube is generated. Now when an incident electron beam is incident on a core electron that is in the location, then there are several things that can happen. Electron can be ejected out of the to the vacuum level which means it is totally out of the binding force or binding energy of the metal or it can actually have a electron loss energy situation that is involved or electrons can be produced x-rays can be produced from one of the L-shells to a K-shell when electron jumps from one to the other. So we can actually look at the particular x-ray that is produced during this transfer of this electron from L-shell to K and that can be a characteristically mapped for a particular element and this is the characteristic radiation that one observes which has two components K alpha and K beta but usually we try to use K alpha because the intensity of K alpha is much higher than K beta. So we will now look at the process that involves generation of x-rays which is typical of a material and this has to do with the core shell electrons instead of the valence band electrons therefore this is particularly called as x-ray photoelectron spectroscopy. Now when we look at this analysis tool it is mainly classified or generally referred to as surface analysis and the study of the outermost layers of materials can be studied therefore in thin film may be through the bulk but in the bulk materials you can only penetrate to very few nanometers therefore it is mostly a surface phenomena rather than a bulk phenomena that we can look for but generally this can bring about rich chemistry because all the impurities that are occluded to a given bulk material can be analyzed because the depth that it can go is only for few nanometers. Now depending on the manifestation of the interaction of the beam with the sample there are several things that can happen one is based on electron spectroscopy and another one is based on ion spectroscopy. So a series of characterization tools can emerge out of the approach that we take if you are going to use a electron beam to interact then the manifestations are XPS that is x-ray photoelectron spectroscopy or another secondary process that happens during the XPS which is Auger electron spectroscopy or there could be another secondary effect which is a electron energy loss spectroscopy all this when electron beam is interacting with the core shell electrons. We can also have ion interaction with the matter and as a result we can come across several spectroscopic tools which can carry useful information one is a SIMS that is secondary ion mass spectroscopy can give you very refined information into all the corresponding elements or impurities that are present in the surface or the Rutherford back scattering which is another very sophisticated tool where helium ion is sent into the lattice and if the lattice is actually ordered then you have a good channeling that is happening but if it is a disordered material the helium ion will get scattered back and therefore you can look at the length of this ordering of the lattice or how orderly the lattices are developed during the process can be mapped and specially those who are involved in thin film technology use RBS as a very sophisticated tool which can give you a clear insight into the epitaxial growth of the film whether the film is growing along a particular axis or not can be mapped using RBS and then you also have ions scattering spectroscopy. So a range of spectroscopic tools are categories in the form of surface analysis and today we will look little bit more deeper into the XPS technique. So what is XPS X-ray photo electron spectroscopy is actually based on the photoelectric effect that is why it is called X-ray photo electron spectroscopy and this was developed in mid 60 by Kai Seibann and his research group at the university of Uppsala in Sweden and since then this has been a pioneering probe tool. So what is XPS and how historically we can identify this 1887 it was actually the discovery of photoelectric effect and this was not explained based on classical physics because what we saw from the photoelectric effect was not commensurate to the theory that was existing about light. So in 1905 it was Einstein who used the issue of quantization proposed by Max Planck and he explained what this photoelectric effect means and the first formulation of basic XPS theory by Rutherford in 1914 and then photoelectron spectra of different elements were recorded in 1920 and then on it has been a major effort as a surface probe tool. Now what really happens in the photoelectric process as you would see the incident X-ray actually falls on the core shell electron that is K shell and this is immediately ejected as a photoelectron. So this is the photoelectron that we are trying to map but in the process there are several things that can happen once the hole is created here then the neighboring shells that is in the L1, L2 or L3 will quickly translate one of the electrons to the lower shell that is K shell and thereby secondary processes do emerge. So XPS spectral lines are identified by the shell from which the electron was ejected it could be from K shell or L or M and so on. The ejected photoelectron has a kinetic energy which is h nu minus binding energy minus phi and this is actually from the instrument. We will look at this equation because we are familiar with this expression from photoelectric effect which is a work function plus half mv square this is your basic expression from photoelectric effect but what you would see here is an extra parameter that is coming which we will try to understand as to why we do that. Following this process the atom will release energy by emission of an ogre electron. So where this ogre electron is coming to picture the L electron falls to fill the vacancy which is step 1. So once the photoelectron is ejected out from which was from here it the photoelectron was ejected and in that place one of the L 2 or L 3 electrons will actually come and fill this place and to conserve energy one of the other electron will be emitted. As a result you are actually getting a ogre electron which is actually not the photoelectron which was ejected in the first step therefore two different processes do occur. One is ogre electron which is coming and the other one is the photoelectron extra photoelectron. So the kinetic energy of the ogre electron is actually different from the kinetic energy of the photoelectron. In photoelectron we are bringing in other phi and this binding energy is also a work function of the sample. This is typical of the sample and this is typical of the machine or the electron gun which will come to it. Therefore there are two work functions that are related when we talk about XPS. We are talking about the kinetic energy of the ogre electron which is linked to the energy of the electrons in different levels. So both are different the information that you get is different. So the x-ray induced ogre electrons can be actually mapped in this way. So when we have this x-ray photoelectron then the electron actually is ejected from the core shell and this the core shell electron which is gone. So that means the binding energy is the energy that we go from here to the valence band and from valence band to the vacuum level. So that is your energy that is associated with the kinetic energy of the ejected electron. And when we think of the ogre electron it is the energy that is translated from one of these shells to the vacuum level. So the kinetic energy of the ogre electron therefore is going to be completely different or will be less than the kinetic energy of the photoelectron. However the kinetic energy is actually independent of the x-ray photo photon energy as far as the ogre electron is concerned. However in the binding energy scale ogre peak positions depend on the x-ray source. We will also look at it shortly from now. When we look at a typical x-ray photoelectron spectra then there are some notations spectroscopic notations which are included and they are actually summed up either as k L1, L2, L3 or it is actually abbreviated as 1 is half, 2 is half, 2 p half, 2 p 3 by 2. So we need to understand in perspective what this exactly means. The suffix that we are looking at is mainly coming from the J and J is nothing but spin orbit coupling. So where L is your orbital momentum or orbital angular momentum number, quantum number therefore the L and the spin of the electron will couple together and give half. For example if your spin is half then 0 plus half will give you half. If it is 0 in this case if this is going to be 1 then 1 minus half will give you half or 1 plus half will give 3 by 2. So the suffix is actually a product of both L plus S which is denoted as J. So depending on the shell we can abbreviate this as L1. If we say L1 then we talk about 2 is half, L2 is 2 p half, L3 is 2 p 3 by 2. So by this way we can actually map all the shells or the electrons related to that particular shell and these are having very characteristic binding energy which we will see shortly from now. So this is the spin orbit coupling that we picked up from the earlier slide.  So if L plus half is there then we talk about half or 3 by 2 or L minus half will be half. So this is the way it is denoted your 2 is nothing but your principal quantum number that determines which shell the electron is involved in this spectra and this is to do with the coupling. So if you are actually looking at a 2 p half or 2 p 3 by 2 spectra then there will be certainly a ratio of the area for this peak. So if we talk about 2 p 3 by 2 then the area under the curve will be approximately 2 times more than the 2 p half. And similarly between 3 d 3 by 2 and 3 d 5 by 2 you will have a intensity ratio of 3 is to 2 and same is the case for 4 of electrons 4 of 5 by 2 and 4 of 7 by 2 will have a ratio of 3 is to 4. So looking at this we can easily map even without a notation looking at the area under the peak we will be able to immediately say what is the sort of peak that we are looking at. So typically the peak will look like this and this is the case for gold 4 d 5 by 2 and gold 4 d 3 by 2 as I told you in the previous case that if it is a d electron then the ratio would be somewhere between 2 is to 3 and you can see that very well here and the area under this curve will be the measure. So the separation between the 2 peaks are named as spin orbit coupling and the values of spin orbital splitting of a core level of an element in different compounds are nearly the same. So this splitting will nearly be the same for almost all the elements and the peak ratios of the core level of an element in different compounds are also nearly the same because it does not depend on the material but it depends on the spin orbit coupling. So these are very unique to the quantum states. So what we can identify therefore is in spin orbit splitting the peak area will assist in the element identifications. Now how will X-ray photoelectron spectra chamber look like? The analyzer which will actually analyze the X-ray photoelectron will actually be a semi hemispherical chamber and this is how it goes. If you have a X-ray source which is hitting the target that is your sample. Now electron is ejected out beyond the vacuum level and this is actually translated through a semi hemispherical chamber which is the inner layer is actually coated with gold. So outer chamber might look metallic but then it is actually plated with gold. So gold is your analyzer and this is actually channelized so as to get the stuff directly to the detector through a photomultiplier tube. So this is in essence a simple setup of a X-ray photoelectron spectra, spectrophotometer. So because we are actually using an analyzer which is gold in this case now this has to be since the gold is acting as a reference detector where all the photoelectrons are collected the work function of the gold is also to be equated or grounded to the sample. Therefore the Fermi level of both the sample and the analyzer has to be same and as a result we need to include the work function of gold electrode also and this is a typical picture of a assembled analyzer that we are talking about. So you would have the sample fitted here and then it will go through the detector and the photoelectron will be mapped. So this is a cartoon that tells how simple or how intricate the assembly is made. Now when we talk about XPS energy scale there are two things that we need to understand. One is the XPS energy with respect to kinetic energy and the XPS energy scale with respect to binding energy two things are there. So when we talk about kinetic energy the expression that we follow is kinetic energy is equal to the incident energy of the electron beam and the binding energy of your sample minus the work function of your spectrophotometer which is nothing but gold. So we usually take the gold work function and we minus that because that is also involved in the analyzing process. Photoelectron line energies therefore are dependent on photon energy whereas the Auger electron line energies are not dependent on photon energy. This is a very important principle. So only the XPS lines are dependent on the photon energy which we are talking about this and the binding energy is not dependent on this h nu. So why we use spectrophotometer work function? Because electrons are detected when reaching the detector's Fermi level kinetic energy is therefore measured relative to the detector's zero point. That is why we use the work function and in addition sample may be on a different potential that is it can be charged. When we talk about the energy scale in terms of binding energy then you will easily find out that we are talking now about binding energy which is equal to h nu minus kinetic energy minus phi spectrophotometer. So in this case the photoelectron line energy is not dependent on photon energy whereas Auger electron is dependent on photon energy when we think about binding energy. So the binding energy can be calibrated by standards. Typically we always use carbon 1S standard because when we are running the vacuum system there will be some amount of carbon in the vacuum which will get deposited on the surface of the sample. Therefore carbon impurity will always be there. However you treat your sample and therefore carbon 1S which is coming from the vacuum chamber will actually serve as an internal standard. How much ever we try to flush out this sample yet we will see a very clear carbon 1S spectra and that is typically 285 electron volt and that is used as a reference point. Then we also have gold 4 or 7 that is 7 by 2 which appears at 84 as a reference point. If suppose these binding energies are differing by one electron volt or two electron volt then we need to use this as a correction factor when we are analyzing our sample. So that is the way we do. The two things that we saw is the binding energy reference or the kinetic energy reference. Now this is the process that we talked about taking the electron from the core level to the Fermi level which is the binding energy plus the work function of the sample from where you take the electron from the Fermi level to the vacuum level and then this electron is actually put into the vacuum level of the analyzer therefore we are talking about the work function of the spectrophotometer. So when we look at the kinetic energy of the photo electron then we are talking about H nu H nu minus B minus the sample and similarly we have to take into consideration the work function of the sample minus the spectrophotometer. Therefore if we merge all these four parameters H nu minus B minus phi sample minus the difference of sample and spectrophotometer then we boil down to this expression. And similarly for binding energy we have this equation H nu minus kinetic energy minus phi. That is the reason why we have two different ways of evaluating the ejected electrons. And this is a map which tells us the relative binding energy of different elements and the 1s electrons usually have a range between 0 to 1100 electron old and this is for the atoms with atomic number 0 to 10. And as you progressively increase then you can see all the binding energies can be mapped the 2s and 2b and these are all very specific to the core shell of different elements. So each number will have a very precise count. So there would not be any change and therefore we can easily try to analyze the local state of each of this metal or elements. But when you go to higher energies as you can see here there are some gaps for 4f and for 4d electrons. Mainly coming because of the heavier electrons and the screening and the penetration effect which will actually distort the way the of the principle describes. Therefore there are some gaps here for which we can see how we can account for those regions. Mainly those are heavier metals therefore you would see those missing data present here. So bulkier the atoms then you have this of the principle dictating the binding energy. When we have a survey spectrum taken for indium phosphide for example then these are the different peaks that one would see and each peak and every hump that is shown here has some message to convey. For example if you look at indium 3d 5 by 2 and indium 3d 3 by 2 these two peaks are coming because of the photo electrons without energy loss whereas there will be a broadening or a small satellite feature that is coming which is actually a background effect coming because of the photo electrons energy loss. And as you would see here you can pinpoint each of this peaks which is characteristic for indium 3s 3p 3d and phosphorous 2s 2p and indium 4d. So each of this peak can be monitored precisely and this is a survey spectrum of a nickel foil which clearly gives you the peak for 2p and also for 3s and 3p electrons and in between you also see the ogre lines which are coming and typically you cannot avoid the ogre lines in a survey spectrum but you can easily make out which is coming from a ogre spectra mainly because they will be asymmetric and it will be broad. So those peaks which are asymmetric and broad are coming due to the ogre effect whereas the sharp ones are due to the photo electrons. So in a survey spectrum you can easily pinpoint on those features and if you try to expand or enlarge this portion you can see this in the inset you can clearly get the nature of the peak whether it is symmetric or asymmetric and what is the broadening and is there any other extra features that are coming all this can be seen when we try to expand this scale. So every satellite feature that you see to the primary feature will give some idea about the local state and the oxidation state of those elements. One more thing that we need to understand why this is a surface technique is because of the sampling depth that is involved the sampling depth is actually defined as the depth from which 95 percent of all photo electrons are scattered by the time they reach the surface. So when electrons are ejected the time taken or the distance it travels by the by the time 95 percent of the photo electrons can be scattered is the sampling depth and that is of the order of three lambda most lambda's wavelengths are in the range of 1.12 3.5 nanometer for a alpha aluminum k alpha radiation usually we use aluminum k alpha or magnesium k alpha as the radiation for XPS. So the sampling depth is approximately 3 lambda for XPS and this is condition therefore your sampling depth can be ascertained to be anywhere between 3 to 10 nanometers and that is all we can prove. One of the very useful information that you get from XPS is the oxidation state we will see several examples in the next few slides where we will we can understand what are the intricacies as we study those numbers. This is the case for lithium metal and this is the case for lithium oxide as you see here the binding energy is actually lower for lithium metal because of the increased screening of the 2 S electrons and therefore the binding energy will always be on the lower side and that is what you see here in the two peak spectrum if you have lithium oxide and lithium metal together then you see two peaks coming one corresponding to lithium metal and the higher binding energy peak is actually corresponding to lithium oxide and that is because the lithium 2 S electron has been given to oxygen in the bonding and therefore the binding energy is much more stronger for lithium oxide. So you would get a two peak spectra which clearly tells what is the center and what is the coordination site that is involved in this compounds. So examples of other chemical shifts we can see here this is a compound with the fluorine as substituted groups and then you have carbon hydrogen bonds carbon oxygen bonds. So clearly we have three different range of substitutions in this polymer and if you take a XPS spectra you can clearly find out that carbon 1 spectra will have three peaks and all these three peaks correspond to different bonding CF will give at a very higher binding energy than CO than CH. So clearly the peak separation suggests that there are three different sets of carbon that is present and similarly you take a spectra of silicon in comparison with silicon fluoride of different fluorine substitutions SAF or SAF 2 SAF 3 SAF 4 then you can clearly see the silicon spectra gives different features and this is what we call as satellite feature these two are called as satellite features and if we properly deconvolute then we can quantify what is actually present in this sample. So if you map this in each case for example silicon the oxidation state is 0 and then silicon fluoride oxidation state is 1 silicon F2 is actually 2 plus silicon F3 here 3 plus. So if you make a comparison between the core shell shift here versus the oxidation state it is actually linear and as you would see here for each oxidation state the increase in the core shell shift is by the order of 1 electron volt. So roughly we can take this to heart that for every oxidation state the jump would be approximately 1 electron volt. So if carbon or any other element for example oxygen is 2 minus if you are looking for oxygen 1 minus then you would only see a difference of around 1 electron volt or less than 1 electron volt there it cannot be 2 then there is something else which is happening. Therefore this calibration clearly gives you an idea that it has to be somewhere around 1 electron volt for a change in oxidation state by plus 1 or minus 1. This is another case if you have CF4 or CO2 or CH4 as we saw from the previous graph we can clearly see the carbon 1s peaks are shifted core level chemical shifts these are related to the overall change on the atom and the reduced charge which means increased binding energy there are number of substitutes which can be evident from the number of peaks. The electronegativity of the substitution also is magnified between oxygen, fluorine and hydrogen. So the shift is very clear and the formal oxidation state can also be traced. In fact for many of the organic compounds or material with organic substitutions just like IR which gives fingerprint region so is the case for these functional groups. In the case of carbon nitrogen single bond you can see 286 in the case of keto group or ester group it is 289 and when we go for fluorocarbons it is 290 and when we go for complete substitution of CF3 you can go to 293. As you see here the range of shift in the binding energy for carbon 1s can vary up to 285 to 293 which is nearly 12 electron volt and that totally depends on the substitution that is going along with the carbon atoms. So this can become a very useful tool because as I told you carbon 1s 285 is a very good calibrant which is the hydrocarbon. So compared to that any other functional groups that are there you can easily pick out selectively which particular carbon atom is there. For example if you take a compound which is hygroscopic it will also absorb carbon dioxide so it will form carbonates. So easily you can map based on the position of your carbon 1s whether it is a carbonate impurity is present. So the core level chemical shift for carbon 1s can be easily found out and therefore the chemical environment can easily be ascertained in our materials. In the next example we will take example of metal oxide in comparison with pure metal and try to see what is the approximate shift and what is the nature of shift that you can expect. As you can see here this is iron 2p spectra and in this case you can see metallic iron actually shows a much sharper peak but once we talk about oxides or iron oxide then we see a more broader peak and the difference between the iron oxide peak Fe 2p peak from that of the pure metal is approximately of 3 electron old. And this 3 electron old suggests that the oxidation state of iron actually has shifted from 0 to plus 3 and similarly let us take the case of a partially oxidized magnetite and if you map the Fe 2p line spectra of this magnetite you would find out apart from the Fe 3 peak which is visible here very clearly you also see a small inflection and there is a asymmetry in the XPS peak. The moment we see asymmetry in the peak then we got to be cautious the base line shift here can actually come from many issues which we will also see but one of the things that we need to find out is the sort of a satellite feature that is bent here and if we try to deconvolute we would see a proportion of this peak and a smaller proportion of this peak coming into picture which suggests that it is partially converted to Fe 2 plus. So the nature of the XPS peak will clearly tell us not only about the proportion but also about the mixed valence states. Take for example the case of oxygen 1s spectrum and in the case of metal oxide you would see a very clear oxygen 1s whereas because of surface hydration you will also see a satellite peak which is coming. So you can easily map whether the ion oxide is pure or it is having some water of hydration associated with it. Similarly in the case of cubic boron nitrate crystal if you try to take this crystal and look at the boron 1s or nitrogen 1s you would be confused with the sort of spectra that you are seeing here mainly such an unsymmetric broad spectrum is coming because of the surface impurity and in the case of boron nitrate you would actually have an oxide impurity which brings about this broadening and this multiplied feature and similarly the case of nitrogen you can see that there is a ambiguity there. What you do here is as a protocol in XPS before we map the 1s or 2s or 2p spectra as a regular protocol it is suggested to sputter the sample with 200 electron volt organ ions and this sputtering actually is bound to remove all the surface occlusions or adsorbed molecules. Therefore after sputtering you can clearly see that the boron 1s is giving a very sharp Gaussian peak. Similarly nitrogen 1s gives a very resolved peak therefore it is very important when we study XPS that we just do not map your spectra rather you do the surface treatment in the first place but one should also understand this organ sputtering can modify the oxidation states of the elements which are already present therefore we need to be very careful to have a rough idea about such a impact of the sputtering ions on the sample therefore if we look for look for a mixed valency then we need to be doing this in a much more careful way but generally the organ sputtering will try to take out all the surface impurities which are settled on the sample. Let us take the case of aluminum oxide. Aluminum oxide actually we can not only map the trivalent state of the zero valency in this case the metal and the aluminum oxide clearly shows a two peak spectra so we know that both aluminum oxide and the aluminum is there but apart from that we also get to see that the oxide thickness can be mapped which is of the order of 3.7 nanometer how do we do that we have already seen what is the length depth that we can scan which is ranging up to 10 nanometer based on that when the oxide is actually 9 nanometers it is possible to distinguish the contribution from both the oxide and metal photo electrons and the expression that is given here is d which is the depth or the thickness of the oxide layer which is given by 2.8 ln 1.4 and this is the ratio of your oxide versus the metal photo electron peaks therefore we can actually quantify what is the amount of surface oxidation that has occurred on a aluminum foil. So XPS can actually give you a quantized picture of that situation we will also look at some more examples of mixed valence states in mixed metal it is actually metal oxides. Take for example the perovskites the transition metal 2p bands showing both plus 3 and plus 4 states the first peak what we see here in this case is actually coming from the plus 3 state and then we also see a satellite feature. So for all compounds whether it is ferrites or manganites or cobaltites we can always look at the mixed valence states of the B cation and therefore this can become a very useful way to analyze it and as you see here when we have mixed valency the 2p 3 by 2 is asymmetric with the satellite feature therefore one has to deconvolute this spectra in order to quantify how much of 3 plus and how much of 4 plus ions are there and similarly in this case all the perovskite compounds like lanthanum nickelate, lanthanum ferrite, lanthanum vanadate all this show asymmetry related to the 3 plus and 4 plus states. Here is another cartoon which gives us a range of oxides starting from LA-MNO3, cobaltites, ferrites everything can be mapped for example these 2 compounds can serve as a standard when we are specially analyzing mixed valence compounds or substituted ones as you know here a pure LA-MNO3 actually should have Mn in 3 plus but when you substitute calcium in lanthanum site Mn3 and Mn4 ratio will be present. So how do we map that we can take the individual spectra of Mn2O3 which is predominantly 3 plus and MnO2 which is predominantly 4 and therefore these 2 can act as a standard to find out how much of 3 and 4 is present and looking at the peak positions we can clearly map whether the 3-4 combination exist. Similarly in the case of ferrites we can use Fe2O3 as a standard to see how much of reduction in the oxidation state or oxidation has happened from Fe3 to Fe4 and here again there are other examples given only thing in this case it is about K absorption H therefore you can see the values are much less because we are talking about K shell so this K absorption H can also serve as a useful number when we try to map between substituted ones and the parent perovskate oxides. When we look at the XPS there are other advantages that we have for example if we look at lanthanum nickelate and substituted with more than 2 metallions all that we can observe from the lanthanum 4D 5 by 2 and 4D 3 by 2 you can see here hardly there is any change in other words the lanthanum valency is not affected in the process when substitution is going on therefore rareth positions peak positions can also serve as a internal standard because they do not exhibit mixed valency except for presiodimium which shows 2 plus 6 plus and 4 plus oxidation state lanthanum in general can show a very precise number and so is the case for oxygen 1S you would hardly see any change happening unless or otherwise a peroxo species is present. So when we have this perovskate compounds taking a look at lanthanum and oxygen position itself can be a useful calibrant to see whether the effect is predominantly coming from the mixed valence states. So the features of such XPS spectres are given here and this can also be used for a methodical study. For example if we are going to make a systematic substitution of zirconium into Siria then this can use as this technique can be a very successful one as you would see here with substitution of zirconium you can see this 890 EV peak is actually decreasing in intensity why because zirconium is in 4 plus and cerium can actually exist in both 4 as well as 3. So when you substitute zirconium then there is a fallout of one of the oxidation states of cerium as a result you can clearly see a systematic trend and so is the case for zirconium you can see the position or the peak intensity varying as we substitute in Siria. So we can clearly map or make a very detailed study especially when we are looking at solid solutions of two dissimilar metals. And similarly XPS has been used almost to crack the chemistry behind the superconductors and I will be dealing with the superconducting oxides in one of the lectures in module 5. But here quickly I want to bring out the usefulness of X-ray photoelectron spectra in elucidating the electronic states of the copper valency for example in the case of the 34k superconductor which is lanthanum strontium cuprate compared with the 90k superconductor the conductivity as we see both are metallic but if you look at the formal valence of both the 34k and 90k superconductor this is actually nearly the same compared to a semiconductor and the formal valence also goes beyond to suggest that copper is not exactly in copper 2 plus but it is in a higher valence state. So if you make a comparison with a standard compound which is cupric chloride which is a well studied system and if you try to reposition this to match with the copper 2p core level spectra you can clearly see that there is the copper 2p 3 by 2 and 2p half spectra's they are both divided in other words they show a split in each peak. So the split in each peak clearly shows that copper is not remaining totally in copper 2 plus but a part of copper 2 plus is oxidized to copper 3 plus and that is happening in order to bring the charge neutrality into this lattice and therefore this valence state of copper 2 plus and copper 3 plus has really helped the community to ascertain what is the conduction mechanism which actually drives this superconducting oxides to show absolute zero resistance. So XPS is a very useful tool therefore to provide the mechanism in a much more elegant way and this is another example which I will be talking about in module 1 under combustion synthesis where noble metal ionic catalyst has been proved to be existing because if you think of any catalysts with noble metals like platinum on silica platinum and Syria or platinum on alumina it is always recognized that these noble metals are in zero valence state and that is why they show very high efficiency in converting the effluent gases in automobile exhaust. So till today most of the companies are using this platinum coated solid supports for catalytic conversion but what has been found recently that if you take platinum and actually treated with Syria in a combustion mode platinum is not actually sitting on the surface but it is actually getting precisely doped in the cerium site and as you would see here very clearly these are the valence bands spectra for platinum, palladium and other noble metals whereas when palladium is actually doped into Syria you can see the spectra is completely different from the noble metals. So what it suggests that platinum is actually getting doped and it is in two place state and because of that one can see that 2 percent and 1 percent platinum doped in titanium shows a tremendous increase in the conversion compared to the undoped Syria state. So a mechanism has been very clearly elucidated based on XP spectra where the substitution of this noble metal precisely into Syria and the valence state has been ascertained using XP spectra and similarly if you take alloy and then try to see what is the influence of doping gold along with aluminum we can clearly find out that if you have gold then the oxidation of aluminum to aluminum hydroxide or aluminum oxide can be inhibited largely because of this alloy formation with gold. So if you take the XP spectra of aluminum and you do a comparison with aluminum gold alloy you can clearly see that the conversion rate is much faster in this case compared to gold alloyed aluminum. So when we try to look at the degradation process of alloys XP's again can prove very useful. So in next few slides I just leave with some parameters which we need to bear in mind what to look for and what not to look for or what to avoid in XP's data. Number one as we know that we are looking at the splitting and as a result we are mapping the unusual oxidation states and we will also be observing the auger lines in the XP spectra but apart from that we will also get X-ray satellites and surface charging effects, intrinsic satellite effects all this can come into picture. So one has to be careful while trying to analyze the nature of XP spectra. For example surface charging can become a very important issue when a specimen's neutralizer is actually on you can see this is the peak due to AL2O3 and this is due to aluminum metal but once you remove the specimen neutralizer because of the surface charging this peak actually gets shifted here but the aluminum peak will remain the same but this peak has actually moved here. So we need to be very careful about the charging effects which can totally mislead our analysis and also the XP's data analysis has to be viewed carefully now we can try to use the peak area analysis in this way or we can just draw a baseline this way and try to analyze but what is actually expected is a optimization of your baseline which has to be in this form. Now there are several softwares which can help us in adjusting the baseline correction so that the area under this peak can be mapped to quantify the amount of this oxidation state that is present. Therefore the peak analysis or the deconvoluted peaks need to be analyzed with proper precision. So this can prove to be a very useful technique especially when you play with the heavier metals. So more than organic samples the inorganic samples have taken a much better attention as far as XP's is concerned and lot more information can be drawn with XP's and this can be quantified. So this is one of the spectroscopy where it is not only quantitative but it is also a quantitative picture. In the next few lectures we will also look at other spectroscopic tools which can be used for surface analysis.


Hi everyone, Joe for jazzy's casebreaks.com on a Thursday coming at you with 2019 2020 panini mosaic basketball Cellopak break number three five zero giving away five spots in that 14 box basketball mixer But as always we're gonna do the break itself first So big thanks to all of these folks right here. They're all teams are in let's roll it Let's randomize it four and one five four times for each list one two three Four and five and of course the randomizer at the end will be new dice roll new list And then four and one five times for the teams one two Three five time after five. We've got the Golden State Warriors down to the Charlotte Warrants All right, so there's the first half of the list right there. There you go Charles Pelicans Could be interesting. I don't know in this one little packed break and then Kim zoom in with the Grizzlies Who knows what can happen there? Let's sort by column B Correct David the optic the Donner's optic cello the one that sells out noir And no trade window folks that the exclusive is the the blue velocity parallels And in this one that we're about to do the mosaic has the pink camo parallels So there's the final printout right there hot off the presses Let's see what we've got here. There's taco fall down there Whoa green Zion Williamson That's not too shabby out of a single cello pack break Pelicans Charles with the pals you still have a chance at the mixer spot, too That's nice. I don't know what these greens are going for these days, but probably a million dollars We got a rookie silver back there, too And that's gonna be RJ Barrett NBA debut rookie silver. What is packed? And that goes to Kim zoom in with the New York Knicks And taco fall Mike tower with the Celtics. Who knows you could have a he can he could be like bowl bowl and suddenly Suddenly emerge out of nowhere Become a presence in the playoffs pink camo we have here Rudy go bear Duncan Robinson and Jackson Hayes is that rookie Duncan? When's when's Duncan Robbins rookie a couple of years ago? I don't know pink camo Duncan Robbins, and he's playing well He can hit the three. He's pretty good There you go. There you have it Joe for jaspercasebreaks.com We got to do I think a couple more of these to sell out that basketball mixer So go and get it jaspercasebreaks.com. Bye. Bye


So, the first time I started working in an open source code was an application server called Trinidad, which was working with JRuby specifically in web applications. And, you know, up to that point in my career, I had really thought of engineering and programming as simply something I did as a profession.  What happened when I was participating in the Trinidad project was we realized that one of our early adopters was Air France.  Because when somebody is worrying about scheduling airplanes and making the system run on time, you realize all of a sudden that you're impacting people's lives. And it led, and about two years ago, I actually had a personal experience that led into this. Two years ago, they found just over a dozen tumors in my lungs. And I had cancer and tumors through my head and my neck. And they told me that I had four to six months to live. So I went up to Huntsman, went all around the United States to different cancer research centers. And what's interesting is, out of the 16 places that I visited, two had an experimental drug that they wanted to try on me. One of them was out in Boston at Dana-Farber Cancer Institute. And it didn't work. And the other one was at Fred Hutch in Seattle. And one of the neat things about it was they'd actually used a database of chemical expressions that actually worked on top of expressions that happened inside of tumors to determine that there should be an experimental drug putting two drugs together in order to cause an expression and hopefully make an impact. And at the time, I had a prognosis of about two months to live when I started it. And 19 of us started this drug. And today, 10 of us are still alive. And so, when I think about, yeah, thank you. When I think about what the power the people in this room have, the power that each of us have, we have the opportunity to impact the world in a way we never thought possible. We stand on the verge of a brand new world in terms of healthcare, a brand new world in terms of energy. And it's dependent on all of our minds getting together. Not only that, he's not here, but I actually thanked him earlier. When I was originally diagnosed, I met Mike Moore for lunch. And Mike Moore, we were in a restaurant, we were just catching up. And I told him about my diagnosis. And he sat there with me at that lunch and cried with me. And he held me as a friend and just said, hey, man, I'm right here. Anything you need, I got you. And right there, you can see the expression of a community, a Ruby community, the mini swan community that gets together and says, hey, I got you, no matter what. The way that we build, the people we build with, the things that we build, we'll change the future and make it a future that we choose to live in. Thanks, everybody. I'm going to use this extra time. Who here still uses Rails 3? It's okay, you're probably going to be like, it's all right, it's all right. They're still alive, they're still out there. Heroku still supports it, so it's going to be there. So that's what we're doing here. And I don't need it in it, so I'm good. Can you guys see? Anyway, we have a huge monolithic app. And well, we have one main problem is that it's old, it's clunky, it takes a while to do everything. So even running like Rails generate, it takes a long time. So I'm just going to show you here really quick. If you do Rails G, but at the very end, we're going to add a time to it, so we can see how long it runs. I'm just going to let it run. It's pretty slow. And so that affects development, right? And so we want to build things fast and do things. And because it's Rails 3, we can't use Spring to reload our development environment. So you see all those warnings that's leftover, awesome technical debt. And it took about 10 seconds to run, right? And so we can't use Spring, so what do we use? This is awesome gem called Zeus, right? So it's awesome because it says right here, we support Rails 3. So we tried it, but this is one of those cases where it works on my machine and it didn't work on my coworkers. And it's like some magic voodoo of gems that need to happen, collaborating together for it to work. But eventually we figured out that you need some sort of, what is it? Let me see, my history. You need that object C, disable initialize fork safety equals yes, in order to work, just disable some parallelization that happens because this runs on top of a go instance. So when I hit start, oh no, oh Zeus is already running. My bad. See, it's rooming my room. Here we go. If I run this now, it's going to put the output to my log. You can see here, tail. It's like, oh, it's booting and everything. And then it says users fill something. It's like, when did fill create a user in my machine? That's really weird.  But once that's open and running, let's see. If I do time, Zeus, g, what was the previous result, 10 seconds? So here we go, 0.55. We got it, all right? So even better, as you can see here in my super tiny screen. Jeez, this is super small. Anyway, you can't see it. But I can run Zeus off of my RubyMind server or IDE. And it had the configurations. In here, there's an object seed disabled initialized. That's the variable. And the cool thing now is that I can run it directly from here. The other thing, too, is that it generates two files, this JSON right here, and then this custom plan file, which you can use to do a lot of cool stuff. On the documentation, it says, yeah, just init it. There you go, there's your two files. And so here you can see on the left, there's what's actually going to be running. Can you guys see that? Is that good enough? All right. So I took some of them out because I don't need to run a Rails server on Zeus because it turns out that it doesn't really kill database connections cleanly. So I was like, OK, I'm OK dealing with that manually. And there's a custom plan right here. So another quirk that we have, we're running our spec very limited test suite. We want to switch to many tests for speed. And well, it turns out that we ended up having to run both at the same time. And Zeus also runs by default. If you have our spec, it will automatically grab it. There's no way for you to configure it to say, can I use minispec, please? No. You have to overwrite some methods here. As you can see, this is all for the test environment. It loads up the test environment. There's an equivalent on the left side, and then the test helper, and then the actual test. And then it has its own metal runner. Have you guys heard of metal? It's like you can run a single test using many tests instead of a nice little synthetic sugar. So anyway, I'm going to run this really quick. Tricky thing is, when I was running this and Zeus spun up and I was trying to run my test, there was no many tests. I'm like, what's going on? So thanks to your Ruby mind, I was able to go into the source code and then go here. Oh, OK, I can see what's going on. I'm going to go to the metal runner. Why didn't you not execute in my test? And as you can see, I'm highlighting here. It's like, hey, execute. When you're running minute test five or minute test old, what are you going to do? Nothing. Thank you. It's like, replace my arguments. No problem. Let's get out. OK. So we had to do a little monkey patching and actually say, hey, can you please run? Anyway, that way we were able to have both tests running together. So Zeus, T, and then we have run that, please. And then the bottom, Zeus, RSpec. And we have both tests running together. Yay. And that's it. I will let you see the results of the RSpec. It takes a while. If you want to know what happened, just let me know. Just to find me. Brandon kind of made me feel weird about talking about joy right now. But that's when you think about it, it's actually what he was talking about actually is a really joyful thing. But I'm going to talk about something else that I've been thinking a lot about lately. Being open and joyful about learning things and not doing stuff that I've been guilty of, which is to present a facade that I am an expert in something or that I know a lot about stuff and not really exposed particularly to juniors but also my own colleagues and peers that there is a learning process and we're all still learning. And you can be open and joyful about the fact that we're all continuously learning. So yay, we're all learning.  But he wrote the rack on Reloader because he found out that a thing wasn't working the way he wanted it to work. So he went and started poking around and found out. And we don't get to see all that, but that happens for Jeremy Evans, that happens for everyone. So we should be actually trying to do whatever we can to enable that learning amongst ourselves. And part of why we're not open and joyful is because we have these behaviors that hinder being open and joyful about our learning. RecurCenter is not a bootcamp, but it's a place that you can kind of go and learn some stuff. But they've got these social rules, no feigning surprise. So you're never allowed inside the RecurCenter to be like, oh, you didn't know that? Oh, like this is like, how could you not know that 2I converts the integer? Like I just barely heard Ruby was a thing. How would I know about 2I? Like that's a silly example, but that's what I'm talking about. Everything might seem silly to someone that's been doing that, but you didn't know that at some point. And finding that out can be awesome, it can be super fun, but everyone's got to kind of hide that and they got to hide away and learn in secret so that they can present this perfect employable facade. And if you, this is going to kind of get into diversity because that's where inclusivity leads is diversity. So let me just continue with these no well actuallys. So that's another thing that I'm really bad at. So I'll over here, some people discussing something and working back. Well, actually, let me interject with how smart I am. I know this thing and I didn't know it when I learned it. Like there's still working things through and I can contribute to that conversation. But the well actually is me contributing not assistance and not guidance. It's me being like, I'm so smart. That's me, like that's what a well actually is. It's not helpful. It's anti-learning, no backseat driving. It's kind of similar to the well actually. That's like, I'm over here coding and I hear some people talking and I'm like, well, that's not how it goes. But I'm not going to go join them and work with them. I'm not going to go like contribute to that. I'm just going to like sort of hang out over here and be like, oh, no, I don't know. So no backseat driving. Just be thoughtful. Experiences differ. This is a good thing. We should embrace that diversity. Play with things, experiment, explore and share those experiences of the act of learning in a joyful way. Share those discoveries instead of just presenting as an expert on something. I gave a talk last night at drug, the downtown Ruby Meetup on command line apps. I've written a handful of them for little scripts, but I'm not some expert, but I kind of felt the need to sort of present from a place of knowledge, because that's what I was doing, but we can share that this is stuff we're still learning. I didn't know everything about options parser last night and I was open about that and it led to conversations and a bunch of people got interested and so this sort of thing's like, it's not hard to actually expose that you are still on this journey because we just need to get used to the idea that all of us are. All of us are continuously learning. Jeremy Evans is way ahead of me, but I'm catching up. Julia Evans is a perfect example of this. She's got a blog, jvns.ca. This is a comment about some of her stuff. She brings so much enthusiasm about learning technology that she makes me see familiar things that are new. This is from an agri-news commenter. Who is experienced? Who is knowledgeable? But Julia just kind of crushes that joyful learning and discovery. Bring joy. This is Julia Evans. Thank you. Can you see my screen? It's probably way tiny or something. Going to work on that then. So this is actually also from a talk that I gave at a couple of meetups over the last six months. It is about visualizing encryption using bitmap images. Essentially, let me actually just pull that code up really fast. I don't think you need to see the terminals, so too tiny for you. CD image, encryptor. I'll just pull that code up and make it big. Okay, so essentially, I'm reading in a file name. I'm taking that file name. I'm reading in the file and turning it into bytes. And then I take the first 54 bytes off because that's the headers. Every bitmap, the first 54 bytes say, this is how you read this image. This is where it wraps. This is how high, how many pixels wide, how many pixels high it is, et cetera. What the color space that it's in. So you don't really need to know that. Just I'm removing the 54 bytes. And then the rest of it is the data that is actually the image. So then I create a very simple image encryptor in this, all I do is take in a secret, like the key and the data and I sort. Then I come down here and I just actually utilize actual encryption that we would use with SSL or Ruby session usually uses AES 256 CBC for its encryption method. So largely ignore the code here. All you really need to see is I'm creating a simple encryption, which is pretty much what encryption looked like 20 years ago. And then I'm creating ECB, which is still used for SSL in Microsoft Internet Explorer, like up to seven. And because of that, a lot of SSL still is actually using that. Not very secure. Then we have CBC and CTR. I am just going to go back to a terminal and open up this folder. This is all actually on GitHub. So you could pull that up. I'll show you that in a second if I have time. But let's just look at the original image. So right here we have, here's our original bitmap. As you can tell, it looks like Superman. If I were to look at my simple one that I encrypted, as you can tell, you can actually still make out the image, but it definitely looks different. If that was a bunch of fine texts, you probably wouldn't be able to make anything out. If you were to look at the ECB example, which as I said is still used by like a lot of encryption out there, you'll see this also isn't very secure. If this was actually an ASCII file or something, it would probably be a lot harder for you to see that pattern, but a machine learning algorithm could probably find that about as easy as you could look at this and see it, because our brains are optimized for image recognition, not like other kinds of decryption. If we were to click on the CBC one, which is what Rails, at least back with Rails 4, was using for session encryption, you'll see that this is actually a lot better masked. In fact, I don't think you could see the pattern in it. Same with CTR, which is very similar, but multi-threaded, so it's a little bit faster to encrypt and decrypt. And then here's a GCM one that Matt had metered the other day. It looks about the same as well. So let me actually just show you the code for that in case you want to play around with that. github.com slash lrs slash imageencrypter. So let me just make that bigger. So if you are interested in this, that would just be lrs slash imageencrypter at github.com and that has a code that you could play around with different image encryptions or multiple other bitmaps if you wanted to do that and just kind of play around with that. Anyway, thanks for listening to me and have a great Rubyhack. So when I put the title of this up originally, I put it up as Ruby from an ops perspective, but actually in second after thinking about it, it's not really the right title. It's probably more like ops using Ruby or Ruby as used by ops. As an opsist, we have to write a lot of utilities, scripts, tools, jobs of various types. And over the years, the languages and the tools we've used to do those have evolved. The most part, at the very beginning, shell scripts, command-mines, little sharp tools that were always there, it's the way to do things. And that was kind of one of the only ways to do things. You could write some C or a few other types of things, but it was primarily these scripts. And they over time became unwieldy, they became big, they became kind of ugly, hard to maintain, and they got really frustrating and led to lots of bugs and lots of other problems. Perl came to the rescue. And it saved the lives of many systems administrator in the Linux administration world and in other operating systems. It had all kinds of super rich kind of modules to do just about anything. It was like magic, it was cases where you would go to write what could be a simple shell script, maybe five or six lines, you do it in Perl anyways, because it was just that much more powerful. It gave you opportunities that if later on you wanted to add some additional functionality, super easy, super expandable. It was awesome. Over time, it kind of got ugly issues with installing modules via RPMs versus installing modules with C-Pan. You ended up in dependency hell.  They also kind of muck with the language a little bit, confuse things, and it slowly kind of started to fizzle. Ruby came to the rescue after that. So many tools came out 10 years ago or so that used Ruby for the building of some big system administrator tools. Things like formin, puppet, fluent D. All these things were necessary to run a server in a more contemporary way. We're all done in Ruby. So we decided, a lot of us decided to jump on that and learn it and mine the value that it provided. What did we gain from this? We learned a new language. Always good to have an extra arrow in the query. One more thing. Perl always had this idea of there's more than one way to do it. Now we up that and say we can do it a bunch of different ways in Perl and we can do it a bunch of different ways in Ruby. Gave us a huge amount of options depending on the exact situation, the exact server, all those cases. There was some weird interesting side effects to this. Us people using Ruby and developers using Ruby, now all of a sudden we had an interesting common language. We were able to help devs if they ran into problems and they were able to help me if I ran into problems. This was kind of mind blowing to me at the time. I got a new appreciation for what Rubyists and Ruby developers were going through. I think they got a better appreciation of what we were going through. We were able to support each other in all kinds of new ways. It was a brand new era of collaboration between two groups that had traditionally been very, very separate, in some ways very antagonistic. Now, because of this language, things definitely got better. I think there's even an argument that you could make to say that Ruby itself was one of the primary elements that allowed the DevOps world to evolve. I don't know if it would have been the same had Ruby not come into the picture and had not this collaboration started. So I wanna take this opportunity to thank the Ruby community for building such wonderful stuff and being so open to ops people. So thank you. It got ugly again. It got ugly again. Version changes, multiple versions of Ruby, all kinds of that stuff. It got ugly again. Containers to the rescue. I can continue to write Ruby code in containers. Doesn't matter what version, doesn't matter what gems, isolated processes. Wonderful. I look forward to continue to using Ruby in the future as long as it's easy and future rich. Thank you. Thank you. Thank you. Hey folks, my name is Mike Nadel. I am with Drip. We are based in Minneapolis, but we just opened an office here. And I wanted to tell you about what we do. We are an e-commerce marketing automation company. So we have about 5,000 customers and they use Drip to ingest data about their customers. They build automations around that and they use that to engage with their customers in a personalized and meaningful way. We are a Ruby-centric polyglot dev shop. We've got about 20 developers on our team and about 120 overall in the company. We are hosted 100% in AWS. We use AWS services including Lambda, Dynamo, Kinesis. We run on EC2 as well. We have Redis and PostgreSQL. We value pair programming. Some of our teams do it exclusively, other teams do it when they feel it adds value and we let our teams figure out that for themselves. We are a transparent, flat, collaborative culture. We value TDD. We have about, well, our build will break if you drop below the current test coverage of 92%. So we're always trying to push that up. We are heavy sidekick users that drives a lot of our concurrency and our volume. We do about 400 million jobs a day through sidekick. Our database is about 10 terabytes. Operating at that scale introduces some really interesting challenges. It's really fun. We're agile but not particularly dogmatic about it. We deploy to production upwards of 10 times a day and we're hiring. So I'll be at the meet and greet. I would love to talk to you about drip, about technology. I'm also passionate about espresso. Talk about that and I'll be around. How much time do I have to fill? Three more minutes. Shit. Oh man. Any questions? We have three employees in Salt Lake. Two of them are our chief marketing officer and our chief technology officer. They commute part-time to Minneapolis. We have a full-time employee and we also have another full-time employee starting here in about two months. So you deploy a lot. Do you practice U-Bank or U-Bank? We don't actually. So that last step is manual, in part because we haven't found a, well, we haven't yet automated active migration, or excuse me, Rails migrations yet, but that's the final piece and then we can turn on that. Murray can fix that. Yes. We're hiring SREs, or DevOps people as well, so. Any other questions, please? Yes. I may have missed it. What do you guys do? We are a e-commerce marketing automation company. So, I would love to give you a demo, but I was afraid that it would take too much time. Okay, so. I might, man. So, what we do is we ingest data from our customers. They will send us page views, they'll send us their Shopify catalog, their Shopify orders, things like that, and then our customers could go in and segment their users based on that so they could say, show me everyone that purchased something within the last 30 days, but didn't click on an email that I sent them to update them about some information. We could target them for communication. We could build rules and automations around that as well and we allow our customers effectively to build these workflows and rules based on what's happening on their commerce side. Yes. All right.  We do not. Ah, nope. Anyone else? Sop up? I'm not sure. 12 seconds, that's right. So, what's up? Tell a joke. Oh no. Um, where does, oh, come find me tonight and I'll tell you the joke and the punchline. I knew that was gonna happen. Thank you.


Hello and welcome into the Gary Stewart Show. I'm Joe Wamba joined with Gary Stewart, head coach of the men's basketball team. And coach, it's been a while since we got to talk. It's been four games that you've played, two of them over the holiday break. Just talk about those games, all of them separated by two possessions. Well, first of all, Joe, happy new to you and everybody watching. We've played better. And so that's really, really encouraging. As you mentioned, we've had four two possession games, had the ball with an opportunity to go ahead or tie, or had the lead with less than 90 seconds left in all those games. And what you want to do is you want to keep putting yourself in those positions. Eventually, we'll close those out. I'm really happy with our progression. The program is in good shape. Joe, we've had our best academic semester since I've been here. We graduated three young men in December. So the last thing I think is to play a little bit better the last 90 seconds. And I think that better days are ahead for us. Well, certainly congratulations to those three men that did graduate. Now, what does it do in terms of momentum headed into the rest of the conference schedule, having those tight games, and maybe converting them into victories down the line? Well, the good thing is that you're able to go back and you can look at the tape and you can identify things that we can do better. And we can do those things better instantaneously, better decisions with the basketball. Our rotations can be better. We had a possession the other day where we had three guys go for the basketball on a defensive rebound. They knocked it out of each other's hands. Ball goes out of bounds in a tight game like that. Now you're giving a team another opportunity to score. And they did capitalize on that. So those type of things, you get that rebound. That's three points that they didn't score. So we're fully aware of areas that we can improve in. And I fully expect us to do that. And the shot clock resets on that rebound. They get an extra 30 seconds to maybe kill the clock if they wanted to. So that's a tough lesson to learn, but it's a good one to learn going into conference schedule. It is. It is. And yet that particular game is a 41-24 differential on the backboard. So we did some really good things there. We just needed to get one more. Any certain players that you're keying in on have a big second half of the semester or a second half of the season? Well, it's a long season. So you want to see how your young people handle that. Moving forward, obviously we're back in the conference play. And you want to continue to see the progression. We asked our guys to be obsessed with improvement. So that's very, very important. We see that in practice. We start to see the consistency in terms of the concentration, the effort, the attention to detail. So you want to continue that. All in all, I just think that we're on the right track. I think we just need to continue this journey. Well, Coach, we appreciate your time and wish you the best of luck in continuing that improvement. I've definitely seen it in the minutes that I get to see you guys out practicing. It's a real pleasure for me. Thank you, Jill. And happy New Year to you as well. Thank you. He's Gary Steward. I'm Joe Wamba, and this has been the Gary Steward Show.