So does peacocking work? Well the short answer to this question is not really, but in some cases it does. Now when the pickup community first started it was kind of started by some weird guys that like had no social skills But they still wanted to make progress with women and so they would talk to each other about it It was kind of like the blind leading the blind and people would overanalyze and they would come up with weird reasons And so somebody came up with the idea of peacocking and it seemed to work because it kind of mimicked evolutionary Psychology and a very bro science and not correct way at all But it also actually worked for some people.  They used to peacock a lot. They had a big top hat he used to wear But people don't talk about why it worked It worked because he was parting and very high-classy Like areas of Los Angeles where celebrities go out now I don't know if you guys have ever been out in LA, but LA people do not dress the same as the rest of the United States They don't dress as the same as the rest of the rest of the world Like it's very normal for you to see a guy who's you know It was on some reality TV show or whatever that thinks he's famous to be rocking a top hat like that or to be rocking like a ridiculous, you know vest get up like this Or something like that you'd see people rock in this sort of stuff And So people would so it worked for them and so they would think that it applies to everywhere Well, let me tell you it doesn't people dress very differently depending on the area that you go out in and yeah Sure, if you go to that certain part of LA There's gonna be a certain amount of women that think you're a celebrity and come up and start talking to you So they felt like it worked, but most other places you're just gonna be a weirdo and it's not gonna work You're just gonna ostracize yourself socially from pretty much everybody. Okay I know for a fact if you walk into a bar with like that top hat People are gonna think you're crazy. They're gonna make fun of you. They're gonna call you a tool Especially if you do that in New York other parts of the United States other parts of the world dress Normally, but you want to have maybe a little bit of an accessory to you that people can pick up on so the idea behind it is So what I like to go out in is I usually go out with maybe some Buda beads like these Right here. So I'll wear these And if a girl likes me or she wants to talk to me or something like that Usually the first thing that she'll say is she'll say hey, I love your beads Where'd you get them or like are you Buddhist or something like that? And I'm like, well, I'm not really Buddhist But I spent a lot of time in Thailand motor biking through all of Southeast Asia for about a year and I can tell her about that trip Now we're engaged in a conversation now that she can ask me about my travels and stuff like that And it's a really easy way to get the conversation started, but I only pick one piece Okay, that's the key thing and you don't want to make it too obnoxious So if you are going out, maybe pick like a skinny tie or maybe pick like a nice shirt Or maybe pick like some accessory or something like that that girls can pick up on and they can start the conversation with But don't make it too much You know Tai Lopez always says that you can be a nudist or a Buddhist but you can't be a nudist Buddhist because You can have one weird thing But you can't have two because then you're too far outside of the social sphere Okay, so I would recommend maybe wearing one sort of kind of unique accessory that girls can pick up on However, there is an exception to this rule.  Hell yes, you should you should wear like the craziest get-up that you can look what kind of outfits people are wearing in general When you're trying to dress for something you should see how the other people have a cool kids or whatever People who are doing the people who are doing the best you should look to see how they dress and kind of emulate it and figure out Your own style within it So if I'm going to a festival or I'm going to like a burning man event or I'm going to like I don't know a rave Which to be honest, I don't really go to those things that much anymore But if I am I'm gonna wear something silly I'm gonna wear something like this because Everyone's wearing something silly and it's easy for girls to come up and start talking to you about it They can like come up and like feel your feel your jacket. Oh my god. This is so soft. This is so cool Can I wear it? Of course you can't wear it. No, no way. Don't worry. What's your name? All right So if you're out at a festival if you're out of like a crazy party or something like that You should definitely peacock. You should definitely wear crazy costumes. I love Parties where you go and dress up at because you can easily talk about something you can talk about your outfit You can talk about like where you got it or where your costume isn't these things like that That's the time where you peacock But if you're just going out to an ordinary normal bar one accessory or one kind of unique thing that you have Is enough and don't I wouldn't go any further than that to be honest. Thanks a lot you guys If you made it to the end consider subscribing I come up with videos like this every single week Thanks a lot and good luck out there


Can I do a second coat or multiple coats of art resin? Yes, you can do a second coat of art resin. In fact, some people like to do third, fourth, and fifth coats working in with artwork as they go along for a 3D effect. That's one option. Most people who do a second coat, however, are trying to fix a surface imperfection that happened in the first coat.  Here's how to take care of that.  This is going to get out that imperfection, but it's also going to serve to provide some tooth between the first layer and the second layer. It will look very scuffed and kind of nasty for the short term, but don't worry because once you pour the second coat over top, all of those marks will go away. Of course, you're just going to want to wipe away any of that sanding debris before you pour your next coat of well-measured, well-mixed art resin over top. Cover with a box to make sure that you avoid any of those imperfections a second time, and you should be good to go. Art resin self-levels at about an eighth of an inch. You can pour deeper if you're pouring into a vessel such as a silicone mold. Now you wouldn't want to pour any deeper than about a quarter of an inch just because it's hard for bubbles to release at any thicker than that. And also the resin can really start to heat up in ways you don't want if you pour deeper than that. Keep in mind if you do pour deeper than an eighth of an inch, it will take longer to cure. You can also pour multiple layers of art resin if you just want a thicker look, or if you're trying to embed objects, or if you're pouring into a silicone mold. If you are looking for that layered look, there's two ways to achieve it. First, what you can do is wait 24 hours after your first pour, do your sanding, and pour your second coat at that point in time as originally described. Secondly, to save you some time, what you can do is wait three to five hours post-initial pour to where the resin has reached that jelly-like state. You won't do any sanding, instead you'll pour the second coat on top at that point in time, and the curing will actually happen simultaneously between the two layers, and they will bond together very nicely. So both ways will work entirely up to you. So whether you're working on an epic project with lots of layers, or you're just trying to fix up something small, rest assured that pouring another coat is always an option.


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I'm Michael from DTCL. So what is that? DTCL actually is a company specialized in blockchain. So like blockchain is very vague, right? Are you specializing in a specific way to implement it? Yes, actually we specialize mostly for healthcare solutions. So we have like research in healthcare, we have like hospital directly for the patients in healthcare. So how is it possible to use blockchain with healthcare and why? Basically it's like we can use blockchain as like a replacement for cloud services in healthcare. The difference is it's not stored in the cloud, it's stored in a decentralized blockchain solution. So because patient data is sensitive? Yes. So people are scared to put it on Google Cloud or Amazon or what? Yeah, Google Cloud is very, it's really the service, the issue with that is like Google own your medical data afterwards. So basically they can sell it to anywhere they want. They own your data. With the blockchain solution actually it's owned by the patient. So basically anybody that wants to access the patient that needs to have the authorization from the patient. So how do you implement it? You just take some blockchain and you package it up? Yes. Or you did something specific about it? Basically we have built a blockchain operating system for the hospital. Operating system? Yeah, basically it's like allow the hospital to build their own application on top of their operation system because basically all hospitals have their own applications. And they don't want to have a new application just come from their company because that might not match their requirements. So we just build the operating system of blockchain which they can integrate any application for the hospital. Like for example data management for patients, they can integrate applications also for IoT, for pharma company research as well. So you're not doing cryptocurrency? No, we're not doing cryptocurrency at all. But you're taking as an Ethereum? Well because our technology is based on Ethereum sidechain. So basically we use Ethereum but we only use the private sidechain because it solves a lot of problems. Like for example latency is much much faster so we can have a lot of transactions per second compared to the public chain of Ethereum. So is that like to make a private what you call blockchain? Is that an easy thing to do in the industry? Is that like following some instructions and then you can do that? Yeah on Ethereum actually it's pretty simple so now there's a lot of developers doing sidechain on Ethereum for different applications. Healthcare is one of them. And how about making an OS on the blockchain? Is that a standard thing many people do or are you like revolutionizing something? Yeah OS is more like a specialty basically a lot of people will build like some small application on Ethereum but what we're doing is more sophisticated and we want to build a whole OS so like a lot of application can be built on top of it so people are basically they don't need to think about blockchain they just need to think about the application and we're taking care of all the blockchain architecture behind. So what does it mean to make an OS on the blockchain? It means like basically you have the application it's running like simultaneously in many nodes like for example in a hospital, in a server at a company or elsewhere and those people can use this architecture to build their application on top of it like any application can be built on top of it it's a bit like Windows, you have application on top of Windows right you have like a Windows page and you can have the application running on top of it and it's the same except that now your like OS is not on personal computers it's in the blockchain. Isn't it just like a network or why do you call it an OS? Well because we think like the OS is the more specific term for it it could be called also a platform but I think operating system is more relevant in this case because basically the whole architecture is there and people can build on top of it. So I've heard a lot about these cryptocurrencies and the ICOs but what other things are like good about the blockchain? Like what good things are people doing out there? Are there some very good examples of how people are using it nicely? I think like everywhere where there's a problem with data security blockchain can be a very good use and also the other place where it can be good use is auditing for example like at Walmart they have a blockchain solution right now for the auditing regarding the supply chain so basically they want to know where is the data come from using blockchain is much more safe and easy to audit But security can it all just be done on the server and they can be done as securely as the blockchain? How can you guarantee it's more secure when you do blockchain stuff compared to just like Amazon cloud? Yeah the problem is with Amazon cloud the cryptology the security is not really comparable to blockchain basically all cloud services they are centralized all the data are put together so basically it's an accurate breach data that can access to all the data But it's still encrypted and that encryption strength is similar to what's used in blockchain But Amazon encryption is like one encryption for a lot of data So basically like once their encryption is broken they have high-critical access to all the data Blockchain is different encryption for all block of data So like every patient in the hospital for example they have different encryption you cannot have the problem of mass leakage of data But don't these I mean I don't know exactly how they do all these cloud services and stuff But I would imagine that they have more security than just having one password for all of Amazon you know There's like I would guess every single customer is encrypting data that with their own kind of thing No they don't have the security for each user Basically when they store the data they store for everybody I'm encrypted I don't know if they always are encrypted because Amazon like every cloud service will have their own technology and own security But basically they're not splitting the security like for every encryption of every user But wouldn't it be easy for them to do that? No it's actually very complicated because then encryption different for each user then how can I access the data of each user very easily The only way to do that is on blockchain that's the blockchain base of technology Alright But I would guess that every application on these cloud services is like a separate kind of you know like a password or a separate kind of encryption system but maybe it's not Well actually the problem is like you have to have a lot of the application but the application will all start from the same database Basically they need to share the database and that's where I first want to attack Do you want to attack the database to get like credit card information or data information from people from users But on your network or your OS they're still like an admin access to the whole thing No, there's nothing like that Basically if the patient loses completely out of the password, the security we put in place for him and he cannot retrieve the data we cannot help him to retrieve the data It's lost So we have other solution to crash this issue but basically we don't own any data You don't own any data? Like the company managing the blockchain they don't own the data For example in the case of hospital the data is owned by the users, by the patients So they can share it with the doctor if they want Exactly But then the patient has to be alive and conscious and be able to remember a password They might write it on the paper There's other solution to like access the password for example we can use biometrics so maybe you cannot need to remember a password you use the biometrics with the eyes or the finger to encode the data It's kind of like same as password So what's the status of your company? How many people do you have colleagues? Well actually in pharmaceutical we already have like 26 pharmaceutical companies they join our alliance with us and we offer a blockchain solution and for hospital we already have like a TMUH in Taipei using our services So basically they're already patient using our blockchain services for the hospital 26 pharmaceutical companies Yes, that's right From all over the world? Mostly in Taipei There's one from France as well And then there's one hospital here in Taiwan who's starting to use to testing it right? So basically that's our pilot and that's the other hospital in Taiwan looking to join this year But what's next for you then? After that we hope to go more worldwide So like hospital we have already dialogue with like hospital in Thailand and Japan Japan there's a hospital very interested to join us this year as well And if this works it could be applied to more than just hospitals Right? Yeah, any hospital actually and not just hospitals like healthcare providers in general Everywhere where privacy is important I would guess it could be much more than just medic healthcare Yeah, it's not just healthcare of course like research in pharmaceutical like IP research for example it's a very big industry where like they want to protect their data they don't want people to know in general what the research is about and it is protected then that can be put on the blockchain as well Is there any way to DDoS the whole blockchain so nobody can use it that would be pretty bad, right? If somebody attacks like figures out where the servers are sends a lot of data and then they're like overloaded Yeah, actually for blockchain if somebody attacks your hardware data actually blockchain is the best solution for that because basically we work on with many nodes at the same time if one node is like the hardware is all broken the other nodes will automatically take over So basically for hospitals there's no like a failure of system like nothing is working anymore the doctor cannot access the patient's data with blockchain is many nodes so basically even if there's such shutdown like the hardware somewhere there's other will take over and they can continue seamlessly So are you based here in Taiwan? Yeah, I'm based in Taiwan so basically a company is from Taiwan it's called DTCO But how many people? Right now our team is like only 12 people 12? But what do they do? Are they engineers? Mostly engineers so far because we focus on the development of the application and we have a few people now who are doing business development in Japan and Thailand and in Taiwan as well And what's been your background? Are you the CEO? No, I'm not CEO What are you? I'm just a business development as well I work before in Adventex I was more used to industrial IT and I also work with hospitals before as well


from San Diego, California. It's theCUBE, covering Cisco Live US 2019. Brought to you by Cisco and its ecosystem partners. Welcome back. We're here at the San Diego Convention Center for Cisco Live 2019, 30th year of the show, 28,000 in attendance. I'm Stu Minnan. We're actually at the midpoint of three days of live wall-to-wall coverage here and happy to bring back to the program two CUBE alumni. First to my right is Ben Nye, who is the CEO of Turbanomics, and sitting next to him is Thomas White, who's the Chief Marketing and Strategy Officer of AppDynamics or AppD, as everybody calls them here at the show. Gentlemen, thanks so much for joining us. Thank you. It's great to be here, Stu. All right, so Thomas, first of all, we had you on it reinvent, like soon after the acquisition of AppD by Cisco. It's been about two years. I believe it's been about two years that Turbanomics has been partnering with Cisco, so let's start with you and what's changed in those two years? Yeah, it's been amazing. Two years ago, we were on the doorstep of an IPO and it's been a rocket ship ride ever since. AppDynamics, after the last two years, the business has more than doubled. The team size is more than doubled and today we're really happy to be the largest and fastest growing provider of application performance monitoring in the market. But the reason why that is, is because our customers are embarking on this digital transformation and the application has really become the foundation of their modern day business. That's the way brands are engaging with their users now more than ever and then the application landscape has gotten way more complex with microservices and multiple clouds and all of the threats that go on in the infrastructure. And so what AppDynamics has been doing is just really providing that real-time business and application performance that our customers need to ensure business outcomes. We think of ourselves as the MRI for the application or the infrastructure. That's awesome. So Ben, it's been interesting to watch in the networking space for the last few years. For the most part, applications used to be that it's just this thing that ran through the pipes every once in a while. I need to think about performance. I need to make sure I got buffer credits or it's now going east-west rather than north-south and the like. But it was solutions like Turbinomic that sat on top of it and helped understand and help people manage their applications. Of course, AppD, pulling that story together even tighter. So give us the latest. We've talked to you at Cisco Live before, an important partnership. What's the latest in your world? Well, so one of the things we're doing is we're building an actual bundle together with AppD. And if you think about APM, you're getting the application topology as well as response time, end-user response time, which is critical to maintaining the brand and the digital economy that we're talking about. When you look at every one of those hops in the application note, there's an entire application stack that sits underneath there, a resourcing stack. And what we're doing is we're bringing ARM, which is application resourcing management with AI so that they're automatically adjusting the resources in all times continuously in order to support the performance needs that AppD is showing us. When you put together APM plus ARM, you have total application performance and that customers are really queuing to. So much so that we've actually decided to put this bundle officially together in the marketplace. We just became the first AppD resale software product and now we're taking that to market as C1 plus AppD. Well, congratulations on that partnership. Thomas, bring us inside the customers a little bit. What does this mean for them? What's that journey we talk about for the last 10, 15 years? Got to break down those silos. It's not just the networking team, tossing over some bandwidth and latency and them coming back and saying, I need some more. No, no, we're not going to give you any service level agreement or anything like that because that's not our job. We'll just set this up and you use what you got. So what's happening in your customers? The trend that we're seeing is a move toward this concept of AI ops, which is really the consolidation of bringing end user application, network and infrastructure monitoring closer together and tying that together with AI based insights to drive automation and actioning and very similar to what TurboNomics specializes in here. And so what we're seeing is the combination of Cisco plus AppDynamics plus companies like Turbo is beginning to build that self-healing, self-learning environment where developers and IT environments need to be able to drive automation and that automation ultimately gets to more innovation when you can reduce the mundane tasks that really take a lot of our developers' time. And so we're really excited about some of the work we're doing together when you think about the ability to take real-time business insights from the application and reprogram the network based on the needs of the app or change out the workloads and move them around on different servers depending on the needs of the app. These are all things that the combination of Turbo and Cisco and AppDynamics are doing together. Yeah, but actually I did a whole show down in DC a couple months ago, Cisco partner focused on AI ops and we understand customers had a lot of tools that they have to deal with. We need to simplify this environment, allow them to focus on their business, not managing this complex environment of all these tools. How does that whole concept of AI ops and automating this environment and managing my workloads, what are you seeing with your customers? Well, I think all the customers are saying, look, there's too many tools today. They don't need another resource monitor, et cetera. What they need is they need to understand through the lens of the application all the resource dependencies. So instead of looking at a field of servers and saying I have five nines of availability or storage or whatever, what they really want to see is what are the servers and storage and resources dependent on this specific app that runs the bank or the CPG company or the manufacturer? And can I make sure that those resources are supporting the performance of the application? And that's this total application performance concept, much more so than whether I have five nines of availability and all my other hosts. Make sense? Yeah, absolutely. Did you have a comment on that? I'm just going to say we're seeing so many different customers and different verticals, whether it's retail, hospitality, automakers, they're all benefiting from the cloud migration and now that they have the cloud migration, the ability to have that elasticity of their workloads, they're scaling in and out based on the application demands. This is becoming critical. This is no longer a luxury for the most cloud-dative companies in the world. Enterprises with mission-critical systems are all becoming dependent on these more modern technologies and I think they need partners like ours more than ever. One of the questions we've had is you talk to customers today and they are multi-cloud, but that multi or hybrid cloud is a bunch of pieces and one of our premises we asked from a research standpoint, how can the sum of those pieces be more valuable than just the independent pieces alone? Kind of the one plus one with an extra factor. Talk a little bit about the customers and also what does this combination do that I couldn't just grab these pieces together and kind of make it work in my portfolio of those dozens of tools that I have. Go ahead, Ben. I was going to say, I think that the customers, one of the things that's neat is we literally announced this partnership publicly two weeks ago and already have closed the first two just out of momentum that folks are realizing the need to be able to say, look, I can host my applications on-prem with a number of different vendors. I can host my applications off-prem with a number of different vendors, but the real question is, where am I going to get the most performance? Where can I do it in a compliant way with all my policies and how can I make sure that I'm doing it cost effectively? And when there's a multiplicity of trade-offs where I can choose, then it's incumbent upon each of those vendors, strategic as they are, to be able to offer the best service, the best performance, the best compliance and resourcing and that's what we're bringing to them and I think that's why you're seeing the pipeline is built to several double digit millions and already deals are closing. The other thing I'd add to that is that, going back to the point around AI ops and the evolution of a lot of these monitoring and automation technologies, a lot of our customers have a hybrid environment of different tools and providers that they leverage and so one of the things that we're really focused on is an open ecosystem where you'd be able to ingest data sources from various different players. Some of them can be Cisco, Turbinomics and ABD, but some of them can be other providers that also have very good products in very specific domains. I think the key is that being able to be able to bring that data together, drive cross-domain correlation in a more automated way than ever before, leveraging some of the more modern AI capabilities which drives the action that people really need and that is really the automation step is where customers start to see the benefits but I think the better and more valuable the data that you have, the better automation you can do because your predictability of your algorithms are much better at that point. All right, Ben, your customers that have rolled out this solution, I know the joint solution is brand new, but what are some of the key metrics? How do they define success? How do they know that they've reached that success? So, first and foremost, the line of business who's the customer to central IT, whether it's hosted or not, they care the most that performance does not degrade and is always improving, okay? But when they do that and they can show that, then all the decision that the rest of central IT takes down in from the container layer to the pods, to the virtual, to the cloud, IS, on-prem and off, those become acceptable choices for central IT to make because fundamentally line of business is saying, yep, we're good, right? So that's where we're seeing the value of being able to see the response time and bridging the application performance to the application resourcing that frankly hasn't ever been solved in five decades of IT and I think it goes back to what Thomas was just saying, it's the quality of the analytics that comes from AIOps. I don't think people need more tools to capture more data, right? There's a lot of data out there. The question is, can you make it actionable and are your analytics correct and frankly, are they the best? And I think we see that that's been a big parcel of what we've done. During the two years, Cisco's told us on multiple occasions, it's the fastest software OEM they've had by bringing it through, starting with the data center team and growing up through traditional Cisco and then with their purchase of AppD two years ago, that combination makes a ton of sense and now you've got the top all the way to the bottom and that's a pretty special spot, I think, unreplicated by any other strategic to date. Yeah, the other thing I just added that is the importance of being able to monitor the business in real time as well and so a lot of what we've talked about are the technology analytics, the IT operational analytics that we run our business on but being able to correlate the business transactions running through the application, so users, what their journey looks like, their abandonment rates, revenues, the ability to engage with the users, tying that back to the specific IT infrastructure in a way that's used to been a black box before, now that all comes to life by the combination of these technologies. So, Thomas, big trends we see at this show. Cisco's transformation towards a software company and the world of multi-cloud. AppD plays a pretty important piece of that. Discussion, talk a little bit about kind of where you are and where do you see Cisco moving along that journey and then help tie in where Turbinomic fits. Yeah, so I think it really goes back to the fact that as our customers are making this digital transformation, they're really looking at a variety of infrastructures, cloud providers to be able to offer these applications and what AppDynamics has done is really created this monitoring fabric that sits across any infrastructure and it tightly ties to the business value of the application. So if you combine that with a lot of what Cisco is doing around connectivity, securing the cloud, securing the infrastructure around it and tying that to where we're strong in networking and bringing all that together, I think fundamentally we've got a lot of the pieces of the puzzle to truly enable AI ops but we don't have them all and I think that's what's important that we partner with people like Ben because it brings together a set of automation capability around application resourcing that we don't have and our customers are better suited working with Ben and team on that. So how do we integrate those things in a frictionless way and make that part of our sales process? That's really what this partnership's all about. All right, Ben, where do we see the partnership going down the road? Oh, I think it's going to get more exciting. So right now we're pulling unidelectionally from AppD, I think we're going to go right back the other way. What Thomas referred to, which is one of my favorite parts of AppD is the business IQ, right? It's where you say what is the cost of the latency in any one hop and where do the abandonment rates happen from consumers on that application, right? Now we can price for the first time, what's the cost of the latency in that one tier and across the application overall? And then more importantly, what do we do about it? Well, that's the resourcing and the congestion that's being resolved in real time. And so I think the ability to look at the resiliency of applications both across and up and down, the APM plus the ARM and being able to guarantee or assure performance, total application performance, that's a big message. All right, want to give you both just final word here, about halfway through the conference here in San Diego. Thomas? Oh, I would just say that the energy that we're seeing, the feedback that we're getting from customers and the business insights, part of the world of solutions has been phenomenal. I think there's so many more developer oriented, application developer oriented individuals that's just go live than ever before. And I think that serves both of our businesses quite well. Look, I think this has been a great show, but one of the things you're going to see is all of these vendors who have had global presence for in this case, 30 years, Cisco Live, 30 years long, but now being able to think through, how do I become that much more application relevant? If you think about transformation of applications, it's going to come top down, not bottom up. And so while we have all the evolution and frankly disruption happening, digital disruption happening across it, the way to know which are the ones that are going to stick, they're going to come top down. And I think the moves that they're making all the way through buying app D, all the way through partnering with CWOM or Turbinomic has been emblematic of what that opportunity is in the marketplace and the realization that customers care about their applications, their applications run their business and you've got to look at the topology and you've got to look in response time and you've got to look at the resourcing. But that's a really fun spot for us to be in together. Ben and Thomas, congratulations on the expanded partnership and thanks again for joining us on theCUBE. Thanks Stu, always a pleasure. All right, we're here in the DevNet Zone, three days wall-to-wall coverage, I'm Stu Miniman, Dave Vellante's in the house, Lisa Martin's here too, we'll be back with lots more coverage. Thanks for watching theCUBE.


Welcome to Access a Trader, the number one community for those who are committed to taking control of their trading in order to achieve success, profitability, and longevity. Thank you for joining us. Here's Dan Shapiro to help you find your edge, master your process, and own your future. Hey guys, good evening everybody. Welcome to another edition of the Access a Trader.com Nightly Rapid Show. Happy Monday. Happy Monday everybody. Hope everybody had a great weekend. So let's talk about it. Number one, if you thought the market was very, very slow this morning, especially the first 40 minutes of the day, half hour, 40 minutes of the day, you're probably not alone. There was a huge latency issue pretty much streetwide. It doesn't matter pretty much what broker you're using. Quotes were slower. Everything was slower. So if you thought something was wrong with your system or your internet connection, just understand it was pretty much everywhere. And that kind of really did a good favor for the bulls. Let me explain to you why. I think the market today, the bulls did a phenomenal job. Absolutely phenomenal. If you guys remember in the weekend update, I was definitely sell side going into today's session. I felt that the market was so easily taken down without any effort. And by the time we looked at the end of the school board towards end of the week, we saw pretty steep declines, right? And the only question was, well, if we're going to get a gap up today and we go red, can the bear sustain the lack of aggression towards end of the week that we saw by the bulls? Instead, we got the opposite. We got a pretty big gap down. We were down, you know, 600, 700 points pre-market today. And the bears really had a shot today. I mean, really, really, if there was any day that they had a shot to really put their claws in the bulls or their foot on the bull's neck, this was the day. They had a really good shot of a gap down dump, whatever you want to call it, and they didn't do it. I believe because of the latency issues on so many different platforms this morning, I think a lot of traders didn't feel the need to kind of trust because they didn't trust their platform, whether the quotes are coming up slow, where they weren't getting quotes at all. A lot of people kind of stood on the sidelines. And what happened was the bulls slowly but surely so there was no fear. And the one thing that they did, which was incredibly important, they started moving up, right? Slowly but surely. First, he started seeing, for example, the stay at home plays. Zoom got a little bit better pre-market. You had Netflix get a little bit pre-market. You had Tesla with the initial sell-off pre-market got a little bit better. You saw Amazon getting a little bit better. And then slowly but surely you saw an incredible push to the upside. I think it was like a 400-point difference from bottom to top on the Nasdaq. Incredibly impressive. And the worst part the bears did was they completely fumbled the wall, completely fumbled the wall today. And not only did they let the bulls reclaim this rising 20-day support that we talked about last week, they reclaimed the 10-day moving average as well and an inch away from reclaiming the five. And again, if you believe that the five-day moving average like I do is the shortest term sentiment, again, if you're short overnight tonight, well, let's see. Let's see what kind of good human being you are because, again, everything tells us guys that going into tomorrow's session is incredibly bullish. You see a lot of names that really fought hard to keep from getting a lot of technical damage, like a Tesla, for example, like an Amazon, for example, like a Zoom and a Beyond and Apple and NVIDIA. They all reclaimed. They really all reclaimed and it's going to be a very, very tough job for the bears to seize control because, again, if you couldn't get the market down on an aggressive 600-point decline from last week's selling that nobody defended prices, you let the bulls get a little bit of breath and like any good boxer, any professional boxer that's getting hit against the ropes, if you don't finish them, that boxer with his experience, with his heart and with his tenacity is going to come back and eventually knock you out. And that's exactly what happened today to the bulls, just an absolute phenomenal job. And you start looking at companies like one by one by one. Again, the bulls could have retreated. They could have confirmed Tesla and brought it all the way down to 880. They didn't. They let Tesla off the ropes. They let Tesla come back out swinging and ultimately Tesla really knocked out. Again, we'll get all the individual pivots, but you start seeing that over and over again. Again, same thing. They had an opportunity to reclaim the 10-day on Amazon and go all the way down to the 2480s. Again, they didn't do so. They had a chance to really crush NVIDIA. NVIDIA was at the bottom of this range, guys. Look how many times. You're talking about one, two, three, four, five, six, seven, eight, nine, ten. You're talking about two and a half weeks up on the bottom of the range. They could have easily taken down NVIDIA and taken all the way down to the 330s. And again, they defended and went higher. Say what you want about BYND. Again, same thing. The bulls just did an absolute fantastic job reclaiming all levels. Boeing, again, up and down Boeing all week. And again, look, Boeing could have gotten murdered. And they held the previous days low on a 600-point decline in the Dow. Again, you could literally go from chart after chart after chart. The moral of the story is the bulls did an absolute phenomenal job. And it's going to be a very, very tough time for the bears going into tomorrow if we start confirming really higher channels. So look at where we are. If you look at every single ETF, kind of where we are, again, great job. Great job on the S&P. We'll use the spiders as a barometer. They held this rising 50-day moving average, reclaimed the 20, and literally one day away from reclaiming the five, again, shortest term sentiment. You look at the IWM. And the IWM had a ton. I mean, I'm talking a ton of put-buying on Friday going into this week. Ridiculous amounts of money being put on the line. We gapped up lower. And again, same thing. We reclaimed this rising support, and we reclaimed the 10. And now we're a step away from reclaiming the five. You look at, for example, the biotechs, right? They could have finished the biotechs, literally finished the biotechs confirming the 50-day moving average. And they would have been a swan dive. They couldn't even take out the previous days low. Again, you can make a case. Was it latency that people want to make sure their prices were holding up? You know, we're holding up. They trust the data that we're getting disseminated from their financial provider, whatever the case did. Again, fumble-rusky, baby. Fumble-rusky. The bears, they lost. It's just reality. They lost. Again, nothing is guaranteed tomorrow. But again, if you look at the charts, and I really encourage traders to look at a lot of charts today, you'll see the same thing, stocks reclaiming one way or another into supply. And all they do, again, unless there's some really horrific corona news overnight, right? You know, you got to like the action on the upside tomorrow. Again, more fed intervention in the middle of the day. They still talked about more stimulus. So you got a really good recipe going into tomorrow's session for the bull case. And again, when you look at the one thing what I liked, and here's kind of going back to last week, when the Dow went down 1,800 points, right? 1,800. And then the next day, a lot of the beta names gave it up as well. One thing we noted, and I forgot if I actually mentioned it on the video, we were talking about in the webinar, that I didn't see any really aggressive put-buying in beta from Thursday to Friday going into this week. We didn't see anything aggressive. The one thing that we did see aggressive was when the market gapped down today. And the NASDAQ was down a lot, and the Dow was down 6,700 points. You started seeing, I'm talking about aggressive, rinse and repeat buyers coming in. And out of money, weekly calls coming in on Tesla, coming in on Zoom, coming in on Amazon. Amazon was a month, so you saw the 180 call buyers step in on BYND. You saw the 195 call buyer coming in on Boeing. You saw two OK men with calls. So really good stuff for the bulls. Really, really good stuff. And for tomorrow, obviously, any gap up today needs to be bought on rising 60-minute support. And again, it's going to take a really, really aggressive effort from the bears to really seize the day again for tomorrow. So obviously, let's talk about the pivots. Again, I know a lot of you guys did have issues, and I get that. Again, there's nothing you could do when you don't trust the quotes and you don't trust the prices because they're coming in sometimes 20, 30 seconds late. And you can't put in orders. Again, there's just nothing you could do. It's just part of the game.  Really, really sick moves here. Here is the first sneaky really pivot on Tesla. 91850, 919, if it builds, just for the initial cash flow, 923, 925. So here is Tesla. So here is the 919 area right over here. So I felt it was going to go right here. 923, 925. And it did that. And then slowly, but surely, you started seeing ridiculous weekly call buyers coming in. 960s, the 1000s, the 1020s, the 1050s. We even saw the 1100s come in for Friday's expiration. And I just kept on putting in more levels over and over again, over and over again. So I said, well, if this thing takes out 927, it could go to 954. If it takes out 954, it could go to 970. If it takes out 977, I said there's a shot. It goes to 1008 today. It went to 998, just an insane move by Tesla. Again, it started out so innocently with Zoom as well. 22640 needs to build for initial cash flow spike to say that is an exaggeration. So here is the 2640. And the initial spike went to 228, 229. And once it started reclaiming 229, we knew this 332 was going to be a big, big area, right? Excuse me, the 232. Again, you started seeing 250 call buyers come in, 260 call buyers come in. I think I even saw 275. I might be wrong, but really, really aggressive. And again, it took out this macro area 232 and just really exploded. It went all the way to the 238 level before it came in. And then it really closed at the high. So really, really aggressive move there as well. DOCU again added to the NASDAQ 100. 156 needs to build. Here was DOCU. All right, so here is the 160, right here. 160 stock just absolutely exploded. Went to 164. Qs, again, they tested Friday's low and then they took them right back, right? Right back. This is that was the first sign that you knew there wasn't going to be a follow-through because again, bears just dropped the ball. Here is definitely the point mover of the day. Again, it started out so innocently. Again, we started seeing the weeklies come in. The 2580s, the 2600, the 2620s, the 2700 weekly calls, 2534 needs to build. Here is 2534 on Amazon. Here's the initial push, right? 2534, it went to 2544 and then it confirmed 2544 and went all the way up to 2584. You're talking about a $50 move and here's the great part. The stock hasn't even confirmed yet. Tomorrow, if it starts confirming the five-day, then this thing has a moonshot at 2608, 2616. So, Amazon still needs to confirm. It hasn't even confirmed macro yet, so really, really big move there. ZM going nuts, nice spike on DOCU. Again, it started out so innocently, right? Buyers coming in for the 960 calls. Stock went to 1,000. Huge move there. 105, and this is one of the very few shorts that actually did work out. Roku, if it builds below, can flush 105 as Friday's low. Again, not a huge move because, again, the market rebounded, but here's the 105 and it went all the way down to, well, I'd say all the way down, obviously modestly, to 103 and change, but again, pivot is a pivot is a pivot. So Tesla, document, new highs. So here, and I kept on giving spots here. I go, look. Now the big macro area is 956. It really needs to get to that change. Now we're seeing aggressive 1,000 call buyers coming in. And it took out 956 again, went to 1,000. BYND, beautiful close. Perfect, perfect close. 152, big spot needs to build. So BYND closed right above the 152 area to 154. Why is that important? Because again, this is my whole point. It confirmed the five-day moving average and now, you know, if it starts taking out of this candle here, you could see a move back to 52 week high. So big move on BYND as well. Again, here we go, 965 next. Any close in 970 gets you 1,000, went to 1,000. That's exactly what happened. And that's it there. Again, 2580s on Amazon, big, big move there. 1,000, here comes 1,000. Oh my God, 154 close, 154 close on BYND. So you got a lot of aggressive action, but more important than the individual action today was a very, very definitive shift in sentiment. So again, when you're going into any trading day, you need to have an opinion, right? Obviously you need to have a game plan. But once you have so much information, we always talk about the ability to collect data, right? Like again, all this information I've gotten through the trading day, through the five, six, seven hours I was sitting there watching all the action. And the most important part is not to jump the gun for tomorrow. But the key of the game is you have your spots, you wait for that confirmation. If they gap up, you wait for that opening range high. And depending on how much range you have from opening range high to the next supply zone, that's when you get more aggressive or get more passive on your tier size. So guys, have a great night, everybody. Happy Monday. And with God's help, I'll see you all tomorrow. Congratulations for putting in the time to take control of your trading. You're one step closer to owning your future and achieving the success you desire. Want daily trade ideas directly from Dan? Straight off his personal watch list? 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OK, well, let's start. I just list here sort of what we did last time, so I remind you. We talked about electron transfer homogeneous solution where we relate the second order rate to the first order rate by a association constant that I actually didn't talk about at all, but it could be, but I will pet. And then we talked about the potential energy surface that the electron transfer rate happens on. And we talked about adiabatic and diabetic surfaces, the diabetic surfaces being the non-interacting surfaces and the adiabatic being the actual surfaces. And we then got the Marcus expression for the rate for adiabatic electron transfer in which the pre-factor is a nuclear pre-factor of something of the order of 10 to the 13th. And from this, I mis-wrote it, of course. This is delta G0 plus lambda squared over 4 lambda RT. And from this dependence, you get a normal and inverted region, so if you plot the log of the rate constant versus the driving force, you find in one half of the curve the rate goes up with driving force as you increase driving force in the other half. It goes down, and that's the inverted region. And then we talked about non-adiabatic electron transfer that assumes that you don't always cross from reactants to products with unity probability. And so then you end up with a pre-factor that's basically an electronic frequency on which you transfer from one surface, one diabetic surface to the other that can be written that way. And we talked then about the reorganization energy is the inner sphere and the outer sphere, where the inner sphere is contributed by each react and contributes its own inner sphere reorganization energy, whereas the outer sphere is a composite term depending on both of them. We wrote the cross relations, and we ended with the distance dependence saying that HAB was a function of r, and the normal expression given is an exponential function of r. That's not required. There's nothing required about that as the functional dependence. The only thing you can say is the HAB comes about due to overlap between the tails of wave functions. You have the wave function on one side and the wave function on the other. And tails of wave functions tend to be exponential. So their overlap will tend to be exponential. It doesn't have to be. And so it's written like this. It's written as beta over 2 simply because HAB ends up as squared in the expression. And so then the distance dependence is a minus beta r rather than, so it's just written that way for simplicity. And there's been a lot of work determining what the beta should be. Certainly, Harry Gray's group has done a lot of work in proteins determining that, and in other case. Now what I want to do is I want to take a digression to absorption spectra. And the reason I want to do that is I want to develop functional forms I can then use to do electron transfer on a metal electrode. So we're going to talk about absorb of charge transfer transitions. And we'll draw our normal surfaces. And the charge transfer transition we're going to look at is shown as vertical, EOP. And we know that EOP, in our notation, is equal to the reorganization energy for a zero driving force reaction. The question I want to ask, though, is what does a spectra look like? This just tells you a stick figure that at one energy equal to EOP, you should have an absorption. But we know that's not true, that there's some distribution. And so I want to know what is the absorption spectra for a whole bunch of different energies drawn like so. And if I can describe the probability of transition for the different energies, I will get the whole spectra. And I'm going to do this totally classically. And what I'm going to say is I'm going to assume that the probability for transition from this position or from this position or from this position are all exactly the same. The only thing that's going to govern the spectra is how many molecules there are at this position versus this position. And so you'll have more at this position because it's a low energy position. So this will be the most intense part of the band, whereas this will have fewer molecules and this will be a less intense part of the band. And so we'll develop that. So this is our ground state. And E of the ground state is going to be lambda x squared. And this is our other state, which I guess I could call 2, where it's not quite an excited state in our thing, but we're thinking of it as the upper state is going to be, we draw this again as 0 and 1 for our coordinate. It will be x minus 1 squared. OK. And I know that E op is going to equal E2 minus E ground state. OK. And this, of course, is going to be lambda x squared, pardon me, lambda times x minus 1 squared minus lambda x squared. And you can solve this for x and you get x equals E op plus lambda minus E op plus lambda over 2 lambda. That's a minus E op. OK. And since what I want to say is that the probability of excitation is just depending on how many there are, the number of molecules there, which I'll call say n of i, will be n of i at some value x of i, well, x, call it, is going to be equals to some n, 0, E to the minus E at that point i over RT. And this is E to the minus. This E of i is this ground state energy. And so that's going to be lambda x squared over RT. And we have x squared here. And we have 0, E, E to the minus lambda, and then I guess I'll write it lambda minus E op, squared over 4 lambda squared writing below, halfway on the board, that's where lambda squared RT, OK? And that all equals minus E op squared over 4 lambda RT, OK? And this is a Gaussian function. It's sort of reminiscent of the Gaussian function we got for Marcus's theory. And if I plot basically the epsilon, this is now going to give me the epsilon. It's going to be proportional to epsilon versus the energy of E op. It's going to look something like that, where it maximizes that lambda, OK? And I can now generalize this fairly directly, is if I want to look at for non-thermal neutral reaction, where the dotted line shows the thermal neutral reaction. Well, I haven't drawn it well enough, too. But that distance is lambda up there. Pardon me, let me try that again, because I'm going to draw it the opposite direction, sorry. Because I want to go up. It's not a thermal electron transfer reaction, OK? And we know that this is lambda, this is thermal neutral, and this distance is delta G zero, OK? And so if this distance is delta G zero, this distance is delta G zero up there. And this distance, overall, I've called E op. So I can rewrite this in terms of lambda and delta G zero. And I get n zero is equal to, pardon me, n i, I guess, is n zero, e to the minus lambda plus party. It's minus E op, where what I do to get a negative sign in here that has screwed it up. I think I didn't quite solve this correctly. Let's go back to solve this. This has to be equal to lambda x squared minus 2 lambda x minus lambda minus lambda squared. These cancel. You bring this over. It'll be E op minus lambda. Do I have the sign wrong or do I? What do I have wrong here? So this is going to become E op plus lambda equals minus 2 lambda x, and x will equal minus E op. Pardon me, this is not minus x, a plus lambda, isn't it? I actually solved them correctly, or it doesn't work. Over minus 2 lambda. So this should be lambda minus E op. Isn't that what I had? Over 2 lambda? Because I don't want to get it into minus E. And I say E op. Hm. And I say that E op is equal to lambda. Oh, the question is what's the sign on delta? The g, I guess. That's OK. It's going to be plus delta g 0. And then I should get, so I claim that I'm going to get, although what I want to get is not that.  That's the problem. That's the problem, I think. Yeah, OK. OK, I guess I wanted to do it too simply. I think what I've got to do is I've got to rewrite these. So let me rewrite these. This is going to be E2, E1, E, E ground state, and E2. And so E ground state is going to be equal to lambda x squared. And E2 is going to be lambda times x minus 1 squared plus delta g 0, right? Now, if you solve it, so E op is going to equal E2 minus E ground state equals lambda times x minus 1 squared plus delta g 0 minus lambda x squared 2. And this will be lambda x squared minus 2 lambda x plus lambda plus delta g 0 minus lambda squared x squared. That cancels that. E op minus delta g 0 minus lambda all of minus 2 lambda equals x. So I got the same sign for lambda and delta g, which is what I need. OK, so then where I was going with this before I got sidetracked is that n is equal to n 0 e to the minus lambda times the squared. So it'll be E op minus delta g 0 minus lambda squared over 4 lambda rt. And if I write it in a more standard way, I change the sign in this such it's squared, it doesn't really matter. So it will be delta g 0 plus lambda minus E op squared over 4 lambda rt. OK, now that has nothing to do with anything really we're interested in unless you're interested in calculating charge transfer spectra, which is of some interest relative to this, but that's not really why I did it. What I want to do it is I want to reconsider electron transfer so I can write it basically in terms of this sort of distribution function of species. So I want to go back and now reconsider thermal electron transfer again. I have my parabolas. And this, as we recall, was the iron 2 plus of nucleus A, the iron 3 plus of nucleus B, whereas this is the iron 3 plus of nucleus A and iron 2 plus of nucleus B. And this we call reactants. And this we call products. OK, now I want to go back and reconsider if I consider each of the species alone what is happening in the electron transfer. This is considering as a super molecule. Now let me consider the iron A nucleus and the iron B nucleus separately. So the iron A nucleus, this is for the A, looks so like that. And it has, so this is going to be Fe 2 plus. And this is going to be Fe 3 plus plus an electron. OK, and the electron transfer, when I go from one species to the other, this is going to go from some place that's going to go from an iron 2 to an iron 3. So this is A. B, on the other hand, is the opposite. OK, and this is going to, again, be an iron 2 plus and an iron 3 plus. But this starts up there and somehow that's going to go down here. OK, so this is sort of a vertical energy transfer. It's going to go vertically because the speed at which the electron transfers fast compared to the motion of the nuclei. So the nuclei, you can't move when the electron transfers. And so the actual transferring part is vertical. But you might ask, what is the motion here? We know that the electron transfer moves along here, gets to the intersection point and then crosses over and comes back down. And what I say is that's going to be the motion here. It's going to move along here. It's going to reorganize itself to some distance. Then it's going to transfer. Likewise, this guy is going to reorganize himself to some other distance. And then he's going to transfer. And I'll call this delta G vertical A. And this is delta G vertical B. And when you view it this way, you have to say that when the electron transfers, that delta G vertical A has to equal delta G vertical B. And the probability of doing the transfer at this distance, I'm going to say is just dependent on the number of molecules that have this distance. So it's going to be very much like an absorption that I did here. I'm just going to say how many molecules have this energy of absorption. I'm going to be dependent on that. And so now I can write all that, hopefully. So the probability for the a nucleus to be at xi is going to be the total number of a's, which I'm going to throw away in a minute. But 4 pi lambda rt, yeah, I didn't go and evaluate n0. But if you think about n0, there's something about the integral of it. The integral of all the n's has to be equal to the total number of n's. And if you work that out, you find n0 comes out to the square root of 4 pi lambda rt. And this is going to be e to the minus. So what was it? It was the delta g squared plus lambda minus eop. So it's going to be minus delta g vertical a. And it's going to have the lambda in it. And then it has to have the delta g, which is the distance between the minima. And that free energy distance is the minus q e0. It's the cell potential between them. So that's going to be minus q e0. And to make it come out right, it would be nice if I don't do a self-exchange reaction. So I don't get rid of the driving force. So I'll assume that this is the qa, and this will be minus q e0 of b, where they may, in fact, be different. And this is all squared over 4 lambda rt. And pb of xj, we'll call it concentration b, all over the square root of 4 pi lambda rt. It might be better. Times e to the minus q e0 b. This was a plus lambda minus delta g v b squared over 4 lambda rt. And the probability of a transfer to a particular position i and j is going to be p, how do I write them? p of xi, pb of xj, where they're different distances, they've reorganized to different amounts, as we know they will because they have different force constants. And the total probability of the transfer is going to be somehow the integral of pij times the integral over all delta g v. So that's going to give us a b, the square root of 4 pi lambda rt. Now we've got to be a little bit careful, I guess. And I haven't been really careful. The reorganization energies for this couple and this couple, if I'm assuming the driving forces are different, the reorganization energies could be different. So just to keep them all separate, we should call them lambda a, lambda b, lambda a, lambda a, lambda b. So that we have everything distinctly marked as to who he belongs to. So I have two of these square roots times an integral e to the minus delta g vertical plus lambda a minus, what is it? I've gotten it wrong. It's minus q e a 0 plus lambda minus delta g vertical. This is for xi squared over the 4. This is a for lambda a rt e to the minus minus q e b 0 plus lambda b minus delta gv. I guess I called this b. I guess I called this a. I didn't distinguish them with the x's for lambda b rt e delta gv. And as I say, to have the electron transfer go so that you can serve energy, delta gv a and delta gv b have to be the same. So I can get rid of their distinguishing marks. They are forced to be the same. And now we have the integral of two Gaussians. And you can go show on Mathematica, or if you're really good at calculus, you can show that this, the integral of two Gaussians gives you a Gaussian. And the Gaussian comes out to just sort of what you would expect, because we know the answer to this is going to be a, or almost the answer, times b all times 4 pi lambda a plus lambda b rt e to the minus minus q e a 0 minus e b 0 plus lambda a plus lambda b squared squared. Got to get the signs in the right place, rt. It just comes out to the Gaussian, which is the Gaussian we know, which is just e to the minus delta g 0 plus lambda squared over 4 lambda rt, where the lambda is the sum of the individual reorganization energy. So that somehow we can write the overall term now as distribution functions for two individuals and get them to be here. And that's in a sense what I want to do, because I want to go and do electron transfer at a, OK, this 4 pi rt. Well, when you integrate a Gaussian, the Gaussian has some width. If we write the Gaussian as e to the minus x squared over a, this width is, what is it? 2 times the square root of a, OK? So what does that mean? So when you're going to integrate the Gaussian, it's basically the width of the Gaussian is going to determine a lot about the integral, right? It's going to be sort of a height times a width. So these guys, you always get forms like this to normalize the Gaussian. So when you do this integral, you're going to get like a 4 pi rt out, and you have to replace these two separate things with normalizes separate Gaussians by one that normalizes the two Gaussians. And it just works out magically. That's how it works. But the 4 pi, the lambda rt are basically normalization functions for the Gaussian, OK? There's a difference between them. And OK, you're asking, did I get it correct? Let's see, that's hard to see. This one is minus, and this one is plus, because you're going the opposite direction. And so that this one should have been plus, and this one should, and now is it written so delta G0 is correct? I think it is. I think it's written as delta G0 is correct, OK? So now, this is, turns out, this is the probability of electron transfer, or it's more like a rate because it has these rate constants, has these concentrations in there, but it doesn't have any frequency factor. So it needs some sort of frequency factor to actually fix it up. And we know what the frequency factor is, so the rate is actually going to be 4 pi squared HAB squared over H, all times my friend, where I've divided out the concentrations. So this is 4 pi squared HAB squared over H times 1 over the square root of 4 pi lambda RT, e to the minus delta G0 plus, OK, which is all what we know. And this is sort of our frequency factor in some way that we have to add. OK, so now we want to go on to electrodes. Now we're finally ready to do electrodes, and hopefully we'll make use of this. So now let's think about our metal electrode. Here's our metal electrode, OK? And the metal electrode has a whole bunch of energy levels in it. It's filled, it has a whole bunch of, and they're filled up to some level here, so they're all filled, where this is the Fermi level. Actually, I promised I'd write the energies as a scripty whereas potentials as a non-script to try to. What you will see is there is a great propensity to become confused between potentials and energies. And now we're going to think of some energy level, EI, and that's going to have a potential of minus QEI, OK? And when we put this in a solution, the solution is going to have some potential. And when it comes to equilibrium, you will have the potential of the solution equal to the Fermi level of the metal. They will come to equilibrium, we know that. And there's going to be some other position of the QE0. If the concentration of the species in solution, the oxidant and the reductant are equal, these will be the same place, but they don't have to be. And we want to ask about the electron transfer like so, OK? And we're going to assume that this redox couple is in a solution that has a high ionic strength, so it's basically outside of the drop of the potential in the solution, so we don't have to correct for that. That could be corrected for, but we don't want to correct for it, so we'll assume it's all outside of that. And what we're doing is we're going to transfer an electron to or from this band structure. And I guess what we are going to do is assume that Marcus theory works. We're going to assume that Marcus theory is the correct description for the microscopic description of electron transfer. And now we want to write a rate constant. So I'm going to say my rate constant, k, is going to be my 4 pi squared HAB squared, all times some integral of a distribution function for the bands of the electrode that have some energy epsilon, and times a distribution function for the redox species. How come I can't keep track of that eraser? Integrated over all energies. And the question is, what are we going to write for the various distribution functions? Now, the first thing we, I guess, need to ask is what is going to be the reorganization energy of the metal electrode? Does the metal electrode reorganize? We're going to put one more electron in, or take one electron out of the metal electrode. But the metal electrode has a band structure, and that band structure is dispersed over all the atoms in the electrode. So there's basically 10 to the 23rd atoms that we have this electronic structure separated over. And so the amount is going to affect any individual atom is minuscule. And so you aren't going to expect that it be any bond distance changes. You're going to expect that it be any bond distance changes in the metal electrode. So we will assume that the reorganization energy for the electrode is zero, that there's no. So the only thing we need to then say is, what's the probability of getting an electron out of there, and what's the number of states? And so we're going to assume that there's a density of states here, rho. That's a function of energy. That tells us how many states you have per E v, and it's going to be a function of that. So we're going to have a rho of E times the Fermi function, which tells us the probability that an electron will be occupying the state. Remember, these states aren't really all filled, and these are really all empty. It's some sort of Fermi function that basically goes from one that these are filled to zero up here. So we need to write some sort of Fermi function. That's a function of the energy 2. And that Fermi function we have to worry about is whether we're transferring an electron out of the electrode, and that's going to be the Fermi function for the unoccupied states, or if you're transferring it into the electrode, it's going to be the Fermi function for the unoccupied state. So for our Fermi function, for our filled states, which I'll call f, which is going to be 1 over 1 plus exp to the E i minus E f over RT, where this is the energy of the Fermi level and the energy of the ith level that we're considering, or in terms of potential, which is what I, it's going to be minus Q times E i minus E f over RT. And the Fermi function for the empty bands is going to be just equal to 1 minus the Fermi function for the filled bands, which ends up as E to the minus Q E i minus E f over RT divided by 1 plus. OK? So now we have the distribution functions for the distribution functions for the oxidant.  And we're going to write it as exp to the minus lambda plus delta g0 squared over 4 lambda RT, which we've written before. It's this function where the E0 is for the redox species in solution, and the vertical energy is basically the Q E i for this band. OK? So now I can write the whole rate constant. k equals 4 pi. I guess there's actually, there's a 1 over the 4 pi lambda RT, which I left out, is 4 pi over h, hab squared, all over the square root of 4 pi lambda RT times the integral of rho of epsilon over. OK, I guess we now have to decide which one we're talking about, and I'm going to talk about the transfer from the electrode to the redox couple. You could write either one. They come out clearly somewhat different, but basically the same thing. OK? So now what do we have? What do we have? This is going to be the E. Now the question is where? The E i dependence you see here, but it's actually also in here because delta G0 is going, we are going from this state to this state. So it's minus Q E0 minus a minus Q E i. So this is minus Q E0 minus E i. So we have a dependence of E i in the delta G0, we have a dependence of E i here in the Fermi function, and you could even think that we might have a dependent in rho. In general, what we're going to consider is that rho is, the density of states is constant enough. But let's look at what we have a second. What we have this part is a Gaussian.  And where does he peak? Well, he's going to peak, well, maybe I should write him out. My Gaussian looks like exp of minus lambda minus Q E0 minus E i squared over 4 lambda RT. And the Gaussian peaks where this is 0, so lambda minus Q E0 minus E i is equal to 0. That's where it peaks. So I can say Q E i is equal to, let's see if I can solve it so I get it actually right. This has to come across. So it's going to be minus Q E0 plus lambda. So if I'm plotting this as my energy E i up here, this point is going to be minus Q E0 plus lambda. You don't think it's right? When I multiply through here, and then you say I have to take this to the other side and make this minus, I'm sure that's what I want to do. Oh, yes, yes, yes. OK, yes, that's what I want to do. It's the problem of the potentials in energy. If I look at energies, these are energies now. These are energy terms. This is in terms of potential. If I'm plotting it in terms of energy, so I want it to be minus Q E i going up. So high energy is over here. Low energy is over here. High negative potential is up here. So on, and so forth. So I get, in terms of energy, this is minus Q E0 plus lambda. And that's where my peak is. My Fermi function, however, goes through a transition. And it goes through a transition where this is equal to zero. And so that's where minus Q E i minus E f is equal to zero. And so minus Q E i will equal minus Q E f. And so this goes through a transition like this, where this is minus Q E f. Now what we want is the overlap between these. So it's clear how I've drawn it now that there's very little overlap, and the rate you're going to get is very small. As I move the Fermi level up, the overlap becomes more and more, and I get a bigger and bigger rate. Now what does it mean to be moving the Fermi level up? The Fermi level is the level that is in the electrode. And when I'm not at equilibrium, if I apply a potential to the electrode, I can push this up. And then I have current flow precisely because the forward rate is faster than the backward rate. And so by pushing the Fermi level up, I actually push the rate up. In other words, the higher I push this Fermi level, the bigger the rate I get to my solution level. And that's because I'm in a sense populating this much more. And clearly when I push the Fermi level up here, so this is a full population, I'm getting as fast a rate as I can get. And so once I get up here, if I push the potential up higher, I never get any increase in rate. So what do I expect in terms of rate constant versus minus QEF? When I'm down here, I have a very low rate. And something happens, but probably not too much. Then I come over into the tail, and I really start catching some of the density. And the rate starts to go up. And then I get past the peak, and it flattens out. OK? Now, I think the question that I wanted to address is why that happens and what can we understand about the electrodes versus normal solution, normal redox species and solution. Here's my electrode again. With all my levels, I draw some sort of Fermi function where this is 1 and this is 0. I draw my minus QE0. And this is energy in that direction.  And he's displaced from QE0 by plus lambda. So I draw him where this distance is lambda. OK? And basically, if I think of it in terms of a solution, where in solution I have one redox couple transferring electron to another redox couple from his half cell potential to his half cell potential. And so I think of it as that I have rates that transfer, say, from this level to that guy, from this level to that guy, and from this level to that guy. This guy will have a very small rate because the reaction is uphill. He has plenty of population, but the reaction is uphill, and so there's not much reaction. This guy will have a pretty good rate because he's pretty much thermonutrile. So the Gaussian is reasonable size, but his Fermi function is about half because it's about at the transition. And this guy will have a little rate again because he has very little population because the Fermi function is 0, but his driving force is good. And so he'd have a good rate there. On the other hand, now if I push the Fermi function up, this guy has a very good rate. This guy still doesn't. Well, let me go push the Fermi function way up. So now this guy has a really good rate because he has some favorable driving force, and that favorable driving force is going to give you a favorable term here. That's a negative term that's going to be lambda minus that favorable energy transfer that makes this small. So this term here is very, very favorable. And now we're driving the reaction as fast as we can go because this is a really good rate. When we push the rate up even further, now I've got to draw it again because I don't have room to do that. This is my Qe is 0. My Fermi function now is going to look like this. And I ask about the rate here. What is that rate? Is that rate going to be big or little? Big, little. Well, we got both in a minute. It has a really big driving force. So what has happened here? This has become a very big negative number. When that becomes a very big negative number, it becomes larger than lambda, and it becomes inverted. So the rate goes down. So this guy has a slow rate, but there's always a guy down here now who has just the optimal rate. His delta G is just enough to wipe out the reorganization energy making it 0, so this rate is now fast. So you still get a fast overall rate. So in this case, it was this one that was fast. As you push it up, the top one is no longer fast, but you still have somebody in there who's fast. So that on a metal electrode, when you push the potential at a metal electrode up, the rate goes up and up, but ultimately limits. You never see the inverted region, because you have lots of levels, and you always have a level then once you fill your potentials high enough that is an optimum, even though you have some that are not optimum. Now I want to draw the other half of the picture. Now we want to ask about going the other direction. Now, where's the equations to go, the other direction? OK. OK, let's write our equations again. We have the rate, which I wrote the rate. I call it from the band structure to the oxidized molecule. And I wrote it is 4 pi squared HAB squared all over the square root of 4 lambda pi lambda RT. Togs an integral of rho e to the minus lambda minus q E0 minus E. Well, just leave it as E, because that's the E of the electrode. It could be E. I could write it as E applied or something, but one is squared over 4 lambda RT divided by 1 plus E to the minus q EI minus E of the electrode all over RT. The DEI is EI. This is EI, isn't it? That's EI, is that right? Everybody agree? And then I can go back and I can write the other one from the reduced to the band structure. That's all easy. And this part is easy. And the distribution function is E to the minus lambda. And since it's going the opposite direction, I've got to change the sign in delta G. So this is going to be plus q E0 minus EI squared over 4 lambda RT, OK? So we had our picture over here, where the Fermi function changes at EF, and this changes at E, q E0 plus lambda. And I'm going to ask now where this changes. That's because I want to draw the same picture now for this guy. And this is going to be minus q EI increases, becomes more negative in that way or positive energy. And this is going to peak where lambda plus q E0 minus EI equals 0, or minus q EI will equal minus q E0 minus lambda. So this is at minus q E0 minus lambda. And this Fermi function makes the same transition at the same place. Only instead of coming down, it goes up. So now you have something that goes where this is minus q E, as I'm calling it now, rather than EF, OK? So to draw my picture on my electrode, so now to make here my levels, here's minus q E. We're going to draw the equilibrium. We'll assume that ox equals red. So this will be minus q E0, which equals minus q E of the solution, right? And then you're going to get one guy who looks like this, one guy who looks like this, this distance is going to be 2 lambda. So this is going to be a lambda negative in energy, and this will be a lambda positive in energy. And when we transfer from some level minus q EI here, we're going to be transferring into this one, and this guy we're transferring out of, OK? Now that's the garusher model. You draw distribution functions for the species on the electrode, and you look at the rate of electron transfer. It all is basically a sort of Marcus theory that is redone for electrodes. OK, what more do I need to do there? I guess that's as much as we need to do in pictures. So now what I want to do is I want to get the standard rate constant for it, the rate constant that applies when you have a nice clean board, have a driving force set equal. Well, OK, I'll tell you. OK, so we're going to get the standard rate constant, which is going to be k 0. And that's going to be, so we have k equals 4 pi squared h A b squared over the square root of 4 pi lambda r t times, well, assume the density of states is it's constant, so we don't have the energy dependence in it. We'll pull it out of the integral, and now we have this integral of exp to the minus lambda minus q E 0 minus E i squared over 4 lambda r t all over 1 plus exp to the minus q E i minus E all over r t d E i. And what I want to do is I want to evaluate that for when minus q E 0 equals minus q E. OK, that's the state. In other words, you apply a potential to the electrode that's equal to the standard potential of the redox couple in solution. And you can then measure the current and clear the current relates to this rate. So in order to do this, I need to evaluate this. So I should define this integral, the whole thing. I won't write it. We'll just know what that is.  I'm going to say that epsilon i equal minus q E i minus E f. That's really if I take my electrode and here's my Fermi energy and here's the level i, it's this distance. It's the energy difference between the i-th level and the Fermi level. And therefore, q E i is equal to q E f minus epsilon i. No, that's not right. It must be this. Even though my notes don't say it, the notes have to be wrong. OK, so we want to plug that all into our integral. And our integral will equal the pre-factor all times 1 plus E to the epsilon i over kt. I call it epsilon i because I'm talking about the i-th level. But then, of course, I integrate it over, assuming the levels are basically continuous. So the i sort of subscript is sort of meaningless. But it's easy to keep in mind what you're talking about. So I leave it there. So this will be minus lambda. God, the signs look all wrong. Minus q E 0. And I plug this in. So this is going to be minus q plus epsilon squared over 4 lambda rt. Epsilon i. There's a q play to convert between potential and stuff. This was the i, and this is probably a minus sign. But that'll switch the limits. So I'm not worrying about any of that like this. There's something that mattered with my signs. And my signs here go back and forth. And so I'm not clear where it's lost. You see where it's I've lost? Plus, oh, that makes me very happy. Very happy. Thank you. And I'm going to evaluate it where this is equal, or the f is equal to E 0. So these are going to cancel one another. And so now I have n. We're going to need to ask where the overlap is. Now what we have, as I've drawn it now, our Fermi function occurs right where epsilon is 0. Well, this is 0. Epsilon is going up here. And our peak occurs at lambda. And this width, which we say is a square root of 4 pi lambda RT, is also controlled by lambda. So even if I make lambda big, what I do is I increase this width and stuff. So the relationship, in a sense, stays the same, independent of lambda. And what I find, if you do this, is that the overlap is always right in here.  So that the only place you get any overlap is for very small epsilon. That epsilon being up here equal to lambda, the Fermi function wipes it out. So what I'm going to do is I'm going to expand this and linearize it. And then I'll be able to integrate it. So I expand it, x squared minus 2x epsilon plus epsilon squared over 4 lambda RT, 1 plus e to the epsilon over RT, that is the lambda, what I've got x's here. So I can write this out as a product of three terms. The first term is not a function of epsilon. So I can take that out. So I get out of the integral, it's going to be e to the minus lambda over 4 RT times the integral, e to the minus, I'm OK so far.  And there's that piece in front, the pre-factor that I haven't written, the square root of 4 pi lambda RT. Now, what I've said is basically it's only epsilon values close to 0, so that piece I can throw out, because he's the smallest piece. And so now I get the integral e to the minus epsilon over 2 RT, 1 plus e to the epsilon over RT, d epsilon. And what I claim is you can integrate that, but just to show you can. If you divide through by an epsilon, minus epsilon over 2 i t, the numerator and denominator, you get this is 1 over e to the minus epsilon over 2 RT plus e to the plus epsilon over 2 RT, d epsilon. And everybody recognizes the denominator as the cosinch, 1 over or 2 times the cosinch of epsilon over RT, or epsilon over 2 RT, which is it. Now, I've forgotten. I think the 2 has to go in there. I don't know if I wrote that down. Now, I got a sign wrong. I divide numerator by, yeah, I know. The top is plus, and yeah, that's OK, right? So I divide the numerator and denominator by e to the, or multiply numerator and denominator by e to the minus epsilon over 2 RT, and then the numerator goes to 1, yeah. So then it works. So this is the cosinch of the, and that you can integrate, and you get, oh, now wait, I've lost a piece. You let me lose a piece there. This piece I've lost over here. So this is e to the minus lambda over 4 RT. So we have e to the minus lambda over 4 RT times all over the square root of 4 pi lambda RT times pi k RT. Difference between r and k, among friends, we won't mention. We don't have to worry about. And so I get k0 is 4 pi squared over h, hab squared, times the square root of 4 pi lambda RT times pi kT, e to the minus lambda over 4 RT. And that turns out to be 2 pi squared over h, hab squared times the square root of pi k RT over lambda, e to the minus lambda over RT, 4 RT. So I actually can explicitly get a rate for the reaction. So that's the standard rate. And I could do that for the other reaction, too, but it clearly is just a repeat of all of that. So we won't do any of that. The last question to ask is about reorganization energies. We clearly say there's a reorganization energy, and we basically attribute it mostly to the redox species, but there's some solvent problem, too. I mean, in the homogeneous reaction, we had the solvent polarized around the two species. And when we moved the electron, we had a repolarized solvent. Well, here you have an electrode that's a metal electrode, and you have some ion that approaches up to it. And the solvent will be polarized in some way around this. And if you bring up an ion to a metal electrode, you can think of it as that you have an image charge behind the electrode at the same distance behind that the charge is in front. And so you can work that out. And where do I have it? Somewhere, or if you've worked it out, or should I say somewhere, Rudy Marcus worked it out. And so if we say the anosphere for a metal electrode is going to be delta q squared over 4 pi epsilon 0, all times 1 over 2a1 minus 1 over 2d times 1 over dop minus 1 over ds, where a1 is the radius of the ion, and d is the distance from the ion to its image charge, which is, if we define this distance as r, d is equal to 2r. It's quite persistently in the literature written as 2d, although clearly d is sort of a hypothetical distance. The dop is, again, the optical dielectric constant, which is usually taken as a square of the refractive index. And ds is the static dielectric constant. So if I say that this can approach the electrode reasonably intimately so that d is equal to 2a1, then I get, at close contact, times 1 over 4a1, I think so, which I could rewrite as 1 over half times delta q squared over 4. Now if you recall, for the solution, anosphere for the solution, or for the homogeneous in solution, we wrote down as delta q squared over 4 pi epsilon 0 times 1 over 2a1 plus 1 over 2a2 minus 1 over r times 1 over dop minus 1 over ds. And this was for two ions in solution, a1, a2, radius, and the distance between them was r. And if we do close contact and we assume the ions are the same, we say a1 equals a2 and r equals 2aA, then we can work this out, and this is delta q squared over 4 pi epsilon 0 times, these two add up as two of these. This is 1 over 2a that subtracts, so it's a 1 over 2a times 1 over dop minus 1 over ds. And so that lambda outer for solution is equal to, or one half of lambda out of solution is equal to lambda outer at the metal electrode, OK? Likewise, we can say lambda in has a relationship. Lambda in at the metal electrode is one half lambda out in solution, because for the metal electrode, you have one ion that's reorganizing, whereas in solution, you have two ions reorganizing. So overall, lambda for the metal electrode is usually approximately one half lambda of the solution value. Now we have a little bit to say about SAMS, and then we're all done. OK, so now we've talked about the reorganization. Now you can write relationships between the rate constant in solution and the rate constant at the standard rate constant at the electrode if you want, and that's often done. But I'll leave that out, because I want to make one remark about SAMS. Now at the electrode, oh wait, oh yeah, OK, well two remarks. These rate constants I've written at electrode are all for a molecule basically at a distance from the electrode. I haven't talked really about the problem of diffusion toward the electrode or any of that. So if you want to worry about that, that has to be worried about somewhat separately. But there's a large class of large cottage industry of work that takes a metal electrode, generally a gold electrode, and puts a self-assembled monolayer on. These are usually alkane thiols, so they have sulfurs that will bond to the metal electrode. And what they have is one in, I don't know, 10 or 100 of these capped with a redox-active species. And they can very well characterize the SAM, and they can say quite well that it's nice and densely packed and it's all stacked at a particular angle. And then by changing the number of alkane units in, they can measure the rate constant for electron transfer. And they can get a distance dependence of electron transfer. And so it's one way of getting this beta value. And for this work, the betas you get for saturated alkanes are about 1.1, if you want, angstroms to the minus 1. And if you, as you might expect, if you make these aromatic and you make them planar, the beta goes way down because you can transfer distances much further. And if you make them so that you, well, then there's other work that has measured beta in solutions that don't have full chains, and then the beta gets worse. And so there's a whole industry of measuring and characterizing beta that's been done, and much of it on electrodes has been very helpful. OK, I think that's where we should end. Maybe I just should give an advertisement there. You can now do all of this stuff on semiconductor electrodes. And there are many differences and special things about that in semiconductor electrodes. But you'll have to take Nate's course to get any of that.