 to this second seminar on the philosophy of chemistry. It's my very great pleasure to introduce you to our speaker of today, Guillermo S. Terpo from Max Planck Institute in Leipzig. Guillermo is one of the few real specialists in the field of mathematical chemistry. He has written many books and many papers on the topic, and one of the more recent research avenues he's been following is what is called the computational history of science. So using very large data sets to actually study and answer interesting historical questions, in this case, questions in chemistry. And today he's even going to tell us what questions it triggers on the philosophical side of chemistry. So without further ado, the floor is yours. You get one hour, and we will have a short break, and then we have one hour for a Q&A. Okay, thank you, Peter, for the nice introduction, wonderful invitation, and then let's start to talk about this. And... Oops. Can we have this off? Is it off then? I hear a computer is off. Oh. Sorry, I don't know. I think so. Yes, but... No, please. Yeah. Maybe you went into sleep mode or something, but do you have this thing? We don't have it, all right. Boy. It just shouldn't go to sleep mode. Okay, let's see before I make it with Simone. Can we speak first? Do you need the cable for the battery? Well, maybe to be sure, but the rest of all, after the lab, it was automatically... And I will just... Just to be sure. Thank you. Okay, then I'm going to talk about... Yeah, as Peter said, the computational history of chemistry and the relationship with philosophy of chemistry. And this is more or less the outline of what I'm going to present here. I'm going to talk about what I mean by computational history of chemistry. One central concept is chemical knowledge and how we formalize that, because I'm coming from the Matz Planck Institute for Mathematics and Designs, and then we love to formalize everything. Then that's related to that. And this is also part of the formalization, is the concept of chemical space. And then I will connect the chemical space and all what I have said before with the periodic system. And in between, I will include some questions that I consider important for the philosophy of chemistry. Then this is the idea of computational history of chemistry and is that with that, with computational history of chemistry, we can go for large scale patterns in the unfolding of chemistry. I mean, by analyzing data from the history of chemistry, we can look for large scale patterns in the history of chemistry, which is different from the micro-historical approaches, which are, for example, you select one particular period or one particular person and then you explore their types of that person that does micro-history. But in this case, we are something like in the long-distance approach trying to get two large scale patterns of the development of chemistry. That's more or less the idea. And in doing so, what we want to do is to detect the driving forces of what is happening in chemistry and what has happened along history of the discipline. And if we are able to detect those driving forces, then perhaps we can try to estimate the future of chemistry. This is something that historians normally don't like because history is about the past, not about the future. But the advantage I see in these methods is that we can not only see patterns in the past, but also use those patterns to see what's going to happen with the field we are studying in this particular case, chemistry. And we can model that and play with the data to see what's going to happen if we tune chemistry in this and that way to see what's going to be the future of the discipline. But all of that is based on something which is the definition we have for chemical knowledge. This idea is reported in this book with Jurgen Jos at the Max Lang Institute there in Lexich. And the idea we have is that chemical knowledge is a complex dynamical system. And by a complex dynamical system, what we have is that chemical knowledge is something like emerging from the interaction of three things, from the material system of chemistry, the semiotic and the social system of chemistry. Then now let me try to explain what is meant by those systems, by the material system. We have the reactions, the substances, and also the technologies associated to the chemical practice. That's the material system. The semiotic system involves all the theories and conceptual frameworks that have been developed in the unfolding of chemistry and also the communication channels, journals, patents and conferences, things like that are included here. And the social system that's very trivial I would say, is made by people, by chemists, by institutions, by governments, by academies, by industry, which is very important in the unfolding of chemistry. Then our claim is that by the interaction of those systems and every one of those systems has a particular structure. That's one of our aims to try to get to the point of describing the structure of those systems. And by the interaction of those three systems we have that chemical knowledge emerge. And then as a chemical, sorry, as a complex dynamical system, the key point of a complex dynamical system is that it's based on simple rules of interaction on the systems or the agents involved in this case in chemical knowledge. Then we need to find the simple rules of interaction of these three systems. That's the challenge that they aim of this kind of research. This is the book that I mentioned where we formalized the idea of chemical knowledge as a complex dynamical system. But this is kind of, it's not that new. For example, Todd Stoy, in Warren Pease, he said that history is something like a physical law. He said that history is an emerging property of force and he used that word force, of the masses of hundreds of people doing things and it's something like self-organized and then they develop in different ways and that's the force behind history. He said that in very metaphorical way, but some people are taking that very seriously. For example, people at the Santa Fe Institute in the States, this is an institute for complex systems. They are taking, you don't see the name of the book. Let me see what it is. It's history, big history and meta history. This book here and they are using big data and also mathematical methods and methods from statistical thermodynamics to try to understand the historical process with those mathematical methods. For example, stochastic analysis and things like that. And there are a couple of papers in that direction. Okay, then this is more or less the idea. At the end what we need to have is a signal of a particular subject we are studying of chemical knowledge or of one of the three systems that I mentioned. Then for example here we have a frequency of something that we are counting and going to give some examples of this and this is then the temporal scale that tells us something about the history of the system we are studying. Let's suppose that we have this. Then one thing we can do with that is of course if we are interested in history, then we can go and see the signal we have. I mean, we are here today and then we can see the past. And then for example, you can find that there are some turning points in those signals. Those are those turning points are highlighting here. Those are relevant past events. And then my point here is that with these methods what we can do is to try to detect crucial events in the history of the subject we are studying. And that has to do for example, yeah, that's come here later, but that has to do with the concept of scientific revolutions. It's something like trying to detect scientific revolutions using data that's more or less a mathematical method. So that's one thing. And another thing we can do is forecasting. If we know that the history of what we are addressing follow this path, then we can use methods, for example, of time series analysis to try to predict what is gonna be the shape of the system we are studying in the future. What would be the shape or what if this is something like an account or a statistics of chemical knowledge, what would be the chemical knowledge of the future? Another one is if we are able to detect the driving forces of this signal, then we can start to play with that. And that's very important, for example, for all those discussions nowadays, talking about the dangers of the Anthropocene and things like that. Then if we say that chemistry is contributed badly to all those narratives of the Anthropocene, then one thing we could do with those methods is to try to detect those important forces driving chemistry in that direction and try to tune chemistry to put it in the right path. Let's say green chemistry, that's the reason of this green color here, to turn that red chemistry into green chemistry by turning the important driving forces. Then some opportunities that I see here for the philosophy of chemistry is the study of scientific revolution in a systematic way using data and mathematical methods. And also that has to do with ethics. For example, this part here, if you know what you need to tune, then that brings an ethical dimension in the narrative of chemistry as well as here. What happen if we keep doing the kind of chemistry we are doing and we have done in the past centuries or something like that? Then this is the general description of the chemical knowledge as a complex dynamical system and let's begin with the material system. And I'm going to show only the material system and some interaction with the other systems because this is a working process. And I'm going to show the interaction of the influence of the social system upon the material system and also the relationship between the material system and the semantic system, the influence of this one upon this one and of this one upon this one. Now I'm going to the point of the chemical space. The chemical space is an important concept but it's not that complicated, it's only this. It's the whole collection of substances and reactions that have been reported by chemists all over the history of chemistry. That's the chemical space. If you go to the literature, there are different definitions of chemical space. Quantum chemists have a definition, chemoinformaticians, they have another definition but they do not have a definition. Then it's a whole collection of substances and reactions. And chemists have been very good at that. They, for example, with a mailing handbook, the American handbook, they started to collect information in 1817 on general chemistry and with the passage of time it was concentrated on inorganic chemistry. And there are several volumes of those. In organic chemistry, it was that the handbook was initiated by Baish time. It's the Baish line handbook of organic chemistry and there are also many, many, many volumes of that but fortunately that information has been digitized. And now we have that information and the internal databases and one of those databases is REAXIS which is found by Elsevier. They include information on patterns and journals and different sources. Then we have, what we have there is all that information stored here in the mailing in Baish time plus all that information of today's chemistry. All that is there. That's our source of information. We studied in this results I'm going to mention here we studied reactions and substances and in particular substances and in January in 2017 this was the number of reactions, number of substances and we found that 70% of the substances were reported in journals then we decided to go for journals to study the chemical space as reported in journals. And after filtering and selecting single step reactions with publication every year then we ended up with this number of reactions and this number of substances and based on that is that I'm going to show those results and this was this paper that we published in 2019 and several of the results I'm going to show here are based on that paper. One of the first things is the growth of new substances. Joanie Schumann Joanie Schumann I've done a similar study but he was he's so brave he did that by hand. He was accounting the number of patients in the Gamelin and Baish time handbook and with that he was applying some statistical methods and then he ended up with that similar growth. But we are very lazy and we didn't do that but we did was to check the database and run some script and then we were counting the number of new substances and the paper by Joachim was in 1997. This was 2019, counting the number of new substances and this is the plot in large scale and the red one is the fitting line and then this is the conclusion we draw from that. There are many things here. Then one, the first thing is that chemistry is growing chemistry at the level of the material system I mean the number of substances is growing exponentially. There is an exponential growth. Joachim already found that. This was the growth rate we found which is a bit lower than the one that Joachim found because we are here counting number of new substances. He was not counting that. Number of new substances and this is the growth rate which means with that you can calculate the double time. I mean and that's what is written in there. About every 16 years chemists have been able all over the history of chemistry all over now since 1800 onwards have been able to double the number of substances every 16 years. That's more or less the speed of chemistry. That's one thing, that was just playing with that but at my institute we have many mathematicians a machemist and when I showed this plot to one of the mathematicians there to Duke Liu Duke said okay, yeah, we can play with the variability of the signal and then he was playing with that. He is a specialist in time series analysis and then he was looking at the how many new substances are reported one year and the next year and then playing with those differences which is this plot. This is the difference of the number of new substances in log scale between one year and the next year. And then what he found is that the first there was a period between 1800 and 1860 which was very volatile and after that there was a drop and it was a drastic drop because here we run some normal test of normality and if we shift the window here then the distribution is not normal. Then there are some drastic changes and the drastic change was here in 1860 and another one here in 1880, yeah. Then was very volatile at the beginning, drastic drop and this is the value of the variability then you see the reduction in the noise and a further reduction in 1880. That's good and that has to do with the detection of scientific revolutions which could be but now we need to, it's not just detecting then we need to give sense to that. But the important thing is that there are parts of the growth with different variability which is where it's shown here. Then that has to do with the scientific revolutions and then we can apply to different signals and see what's happening whether that makes sense or not, whether that agrees or not with what Kuhn said, things like that. Then we went to explore in detail what happened in each particular period and then for example in this period between 1860 we found that the proportion of compounds containing metals was high in respect to the rest of the history of chemistry. But anyhow the number of compounds containing carbon and hydrogen was also high. But metal compounds were present there. Because of that we call it the proto-organic regime because carbon and hydrogen were anyhow important. Between 1860 and 1980 the percentage of compounds containing metals dropped. 90% of the compounds contained carbon and hydrogen that's what I call the kingdom of organic chemistry. Then it was here in organic chemistry with some organic chemistry but after 1860 organic chemistry was driving the expansion of the chemical space. And importantly you could say okay, you have many elements in the periodic system. And yeah by 1860 there were about 60. But with the passage of time there were more elements but the funny thing and interesting thing is that most of the substances reported in this period more than 100 years are combinations of carbon, hydrogen, nitrogen and oxygen, nothing else. That's pure organic chemistry. But something happened around 1980 and then there was a slow drop in the number of compounds containing carbon and hydrogen and a small increase in the percentage of compounds containing metals. And in fact we were looking for the chemical carbon metal and we found that there was a surge of those compounds. And that means that there are something like the rise of a surge of organic metallic chemistry. Therefore we call it the Organometallic Regine. Okay but why? We have a partial explanation of that. I think you know the city. Around this time historian has written about have written about this period. A lot Ursula Klein and Alain Roch they have written that at that time chemistry was suffering a transformation or enjoying a transformation. And what happened here was the introduction or the adoption of a structure of a theory and that theory was the chemical structural theory. Before chemists were talking about composition of substances. With the structure of chemical theory they start to draw molecules that was more or less that that's a mealtic transition that has to do with the semiotic system. Okay and Ursula Klein has written a book and several papers on that and she said that what happened here it was the introduction of a paper tool in chemistry. And it changed, that's what I have here like a tourist guide. It's something like let's suppose that Leven is that what it pronounced? Okay. Leven is the city is the chemical space and you want to explore the city. And you can do it as a random walker then you go there and then perhaps you find some interesting places or not. That's one way of exploring. That's variable that's high. But another one is if you get a tourist guide and you go directly to the important tourist place and then you perhaps optimize your visit or you go with Peter and you go to the interesting places. That was what happened around 1860. The paper tool of molecular structural theory was taken by chemists as a tourist guide to explore the chemical space. But that has a cost and is that you know where to go but you don't go to somewhere places. And that reinforced for example, I know that in that place I find very interesting compounds of carbon, hydrogen, nitrogen and oxygen. Then they keep going there but I don't explore somewhere place. That has to do with the reduction in the variability. But we don't know what happened here. And that was what I mentioned that around this time something happened between the material system or it was an effect of the semiotic system system acting upon the material system. We don't know what happened in 1980. We know that there was a rise of organic metallic chemistry and we somehow believe and that belief comes from data that we have but we haven't published this yet. And it's that perhaps at this time there was a transition supported by technology, a technological shift. Before 1980, all the chemical instrumentation was adapted for liquid. Liquid chromatography, gas chromatography but those were for solution of substances. But around this time, they started to move in the direction of solids and solid materials, new materials NMR for solids. That's, and we have done some checking of the data and then for example we found around this time the report of uses of electronic microscopy skyrocketed. None of that has to do with that technological shift but we need to go into the details of that. This is another thing that we did. And this is the fraction of the chemical space. What we did was to count the number of substances and divided by the total of substances containing carbon. No, green one is hydrogen, containing carbon and several others but what is important here around 1980, platinum metals. Then you see that carbon and hydrogen have been very, very important all over the history but here in this period you had a mixture that has to do with the volatility. Then we did another thing and then we said, okay, the chemists are producing new substances very fast. They are doubling the production times every 16 years. They are doing well but let's see about, let's address the point of compositions and a composition is something like this. If this is a sulfuric acid then we take only the elements belonging to the formula and the elements compound in the substance. Then for sulfuric acid, the composition is H-Powk acid. Then we were counting how often chemists report a new composition and it's this red block. This one is the one you know of new substances and this one is the one of new compositions. Then in general you could say they are doing not so well. They are exploring, they are reporting more and more compositions. They are not so biased but we measure the distance between those compositions year after year and we found this. It's something like they report several compositions this year, next year more compositions. It's something like you have different boxes. Those are the compositions and now they are going to add substances to those boxes. This block what is telling us is that they are putting a lot of substances in some few boxes. That's the reason of the drop in the distances between that and this has to do with the concentration of substances in very few of those boxes. Then yes, they are discovering new combinations of elements but somehow they prefer some particular compositions. What I have here is the top one composition for different years. That for example here you see that carbon hydrogen was carbon hydrogen has been always important but here you see metals, sodium, aluminium. But look at this, carbon hydrogen, nitrogen and oxygen. Carbon hydrogen, oxygen and from 1890 onwards you see that the top one composition is the one that I mentioned. It's not recent, it's from 1890 onwards. Carbon, hydrogen, nitrogen and oxygen they have been totally concentrated on that. Okay, then this triggers several questions. For example, what are the consequences upon chemical knowledge of that strong bias towards organic chemistry? It's not chemistry, is chemistry only organic chemistry or if the chemical space is democratically populated we are doing that very bad. We are concentrated on our efforts in organic chemistry and not in organic chemistry. Why? It's because carbon is very easy to connect with some other elements or it also has some social influence. What is the role of the chemical industry here for example? To what extent does this bias affect the aims of chemistry? That's what I mentioned before. If we want to expand chemical knowledge we are with those bias we are not doing well. We are just concentrated on some part and we should also devote some time to some other parts. And that has to do with the ethics of chemistry whether our responsibility as chemists is to explore all the possibilities of the chemical space or to keep exploring one particular region of the chemical space. It's the responsibility of chemists to ensure high diversity of substances homogeneous population of the chemical space or to perform and get better and better preparative methods, synthetic methods of organic substances. If this is the aim of chemistry, we are doing well. But if the aim of chemistry is to explore the whole chemical space, we are doing well. And yeah, that was more or less what I wanted to say. Now another thing, and it's the role of synthesis. When you read that chemistry textbook and when you read that book on the history of chemistry normally you see what they say is that organic synthesis and synthesis model in general but especially organic synthesis, they say that it started in around 1828 with the synthesis of urea by villa. Then what we did was to test that hypothesis. This is what we did. If we have this reaction and then we have that this substance was reported for the first time in this reaction, then that means that A was extracted because A is appearing here. It's not the product of any reaction. The first time it was, it appears in the database was on the side of the starting material. Then the only possibility is that it was extracted from nature. If the first time one substance appears as a product then of course it was synthesized. Then what we did was to count the traction of synthesized substances over the whole total number of substances reported every year. This is what you know, number of new substances reported and this is the fraction. And this is the escape. For the blue one is this one, from this one is this one. This is the fraction. Then you see, for example, by the 1800, a bit more than 40% of the chemical space was produced or was discovered by synthesis. 60% by extraction. But look at this. It was 1800, yeah and I was wrong. 1850% of the chemical space was already discovered through synthesis. It was not after 1828, but by 1900, almost all the chemical space has been discovered through synthesis and it has a lot of implications. Chemistry is not anymore the science of discovering things in nature. And since the very beginning of the 19th century was not that. Then it is really true that chemists and chemists or chemists do their own object. They create their own object, let's say. Okay, this is an important fact. And then this is important because it's also, it's telling us that with this kind of approach with true data, we can assess historical narratives and challenge them. Okay, now let's go to the point of how chemists have been using those substances and producing those substances. What we did was to take the substances in the chemical space and count what we did was to count how many times those substances have been used in chemical reactions. And we did it period after period. Before 1860, between 1860 and 1879, what you see here is in a log log scale is this kind of strength, which is a heavy chain distribution. And this is a historical pattern then period after period where we have the same behavior. And the meaning of this is that, for example, these points over here is that the meaning is that many substances, many starting materials have been used only once. This is the number of uses. Then more than 95% of the chemical space today is used only once. I mean, you develop, you synthesize a substance, but no one, you use it once. And it's something like, you do your PhD, you write your thesis, you get your paper and go home or go for another thing because no one else is going to use that substance. That's more or less what is happening in chemistry. But anyhow, there are some few substances. A small set of substances is used thousands of times. Those are what we call the toolkit of chemistry. Then most of the substances, if you imagine that is something like a constellation of substances which they don't have so many uses, but there are some halves, if you imagine that as a network, there are some halves, there are some substances which are very often used. And the top one over the history of chemistry is ascetic anhydride, and the second one is material iodide. That was on the side of the starting materials, but now let's consider the side of the product. We did the same. We counted how often a substance is reported as a product in chemical reaction. And then we found a similar trend, a heavy-trade distribution, meaning that many products have been synthesized only once, so that I mentioned before. Synthesize only once and use only once. But there are some halves in terms of production. There are some substances which are very often produced. And as a chemist you would say, yeah, of course. There are many reactions that produce what? CO2, methane and things like that, hydrochloric acid. Yeah, those are some of the substances appearing here, but if you get rid of them then you start to see some patterns in chemistry. Something like chemists have some targets. There are some substances which are important for some reason and chemists try to get to those substances. Then, for example, after the Second World War, or during the Second World War, you see how important was to get a component of uranium. And then you see how the exploration of the chemical space is also driven by social factors. Then in general chemists frequently use used starting materials to discover many substances not used anymore. Those are very sad news for chemists because it's something like, you are producing a lot of substances, but you don't use them. You keep using those that you know very well. That has to do with the way you're thinking. And the point is that that triggers questions on the ethics of chemistry because we are spending a lot of resources in those synthesis, but we don't use that. Then why chemists? And I'm including that because I remember my fire spider was publishing how to synthesize several substances. I created several of those substances that I don't use anymore. Then why this waste of effort? Is this the disciplinary waste of training the neurogeneration of chemists? Because you could say, okay, because chemists need to know how to acetylate a component. But why? Why is that important? Is that the only way of doing it? Of teaching how to acetylate a component. Or why is that the acetyl group is so important? There are no other ways to get to some other places of the chemical space. And where are the codes of that bias brought of the chemical space? And this is an important subject. And that has to do with the, because as I mentioned, I'm working with mathematicians. And I also mentioned here somehow that this chemical space can be imagined as a network that is expanding. What we have found is that the chemical space, the wet lab chemical space, I mean the chemical space we produce in the laboratories, is very sparse. I mean substances, because of those strengths that I mentioned is that there are many substances in the periphery. And in the center, there are very few paths. That kind of network has a particular geometry. But if you go at the level of micro-organisms and pay attention to the chemical network of the metabolism, metabolic networks, you see that the geometry is totally different. Micro-organisms, if they produce a substance, they try to use it and to incorporate that substance in a network that is kind of close. But the human-made network is something like this. Then the point is, can we turn, can we tune chemistry to try to go in that direction and to do it more close and environmentally correct in some sense? Okay, there. So far what we have is that we have an exponential growth. Good news, exponential growth. But this was this paper. It's a really nice paper. This one by Kiboski and his group. And it was nice because he said that we were very positive in our paper. He said they are claiming that chemistry is growing so fast exponentially, but in terms of number of new substances. But what about classes of reactions? And that has to do with a key point is what about knowledge? The fact of producing substances can be taking us, the fact of producing knowledge is if I take, if I know how to settle a substance and I do that 10,000th of time, that means that I'm creating more knowledge. But that's not, that's the point of Kiboski. And then what he did in this paper, and he wanted me was to, and using the same database, what he did was to count how often chemists come up with a new class of a reaction. For example, if I go here, you can, for example, this is the Diels Alder reaction. And then this is a class of reaction. But if you have here a group like this, then you end up with this. This is something like an instantiation of the Diels Alder reaction. But if you have this, that's another instantiation of a Diels Alder reaction and you can play by adding things here, but you have the same reaction. It's a different instance of the same class. The question by Kiboski was, how often chemists come up with a new class? And then he found that the news are not that good. New classes are growing linearly and sometimes even sublinear. Then in terms of knowledge is that we are producing a lot of things, but in terms of knowledge of new things, of new ways of doing things, not that rapid. Another paper is this one by Liefhuss. They explore, but they didn't do this over the time. It was something like five years or something like that. They explore the diversity of the shape of the molecules that are reported in the scientific literature. And they found that that diversity is very low. Chemists often report substances with this structural motif. We are crazy about hexagons, and sometimes like this, and sometimes like this, but we don't go farther than these places. We are always concentrated on this and that has to do with the classes of reactions we have. And the molecular diversity of the chemical space is very low. The number of classes to expand the chemical space is very low. And then what that means is that chemistry has been something like dreaming about self-reinforcing processes. And this is coming from a paper by these two fellows. They are working in economics. They say that this is the kind of fate of a self-requited process, and they said that there are three phases for that. At the beginning, we have different options, and in this context would be different options to explore the chemical space, but somehow you say this reaction is better than this one, and then you start to repeat that. And then you begin to narrow the possibilities and something else happens, and then you keep repeating that in a very efficient way. And this has a lot to do with the volatility of the signal. This is what is happening in chemistry. Okay, another thing we did was to try to look for simple rules of interaction, and then what we found was this. Almost 90% of the reactions involve no more than three substances. I mean, no more than three starting materials. Almost 50% of those are made for chemistry for only the combination of two substances. Then what we need was to take this set, and then we explore how often chemists have been using these substances and how often the other. What we found is that very often when chemists combine one substance with the other, and that's a historical trend, one of the substances is a very well-known substance, meaning it's a substance with many reactions, for example, acetic anhydride. And the other one is a new substance. It's something like I want to control my reaction with something I know very well, and then I invite this new substance to test the reactivity of that substance. That's more or less the way of proceeding in chemistry, and this is an example of a simple rule of interaction. We call that the simple or the fixed substrate approach, and it's when you take the substance you know very well, and then you make it react with another substance. And as I mentioned before, one of those substances, or some of those substances which have been used many times is acetic anhydride, methanol, and ethyl iodide. Yeah. And there are many, many books and papers talking about the very devastating effect of chemistry, especially in the first world war, and somehow in the second world war. But this is the effect of chemistry upon wars. But here, with this data, we can proceed in the reverse direction. What was the effect of wars upon chemical production? Then we found this. These are the two deeps in this signal. This is the first world war, the second world war, and with that you see how dramatic was the first world war for chemical production. The second world war not that much. In fact, the first world war, some chemistry back 37 years, almost two decades back in production, in production scale, I mean in the number of new substances reported. And the second world war, only 16 years. And that has to do with the social structure of chemistry, around the time of the first world war, chemistry was heavily concentrated in Germany. And if they stopped working then, you see the effect. But after that, then the society learned that okay, centralization is not a good policy. Let's start to do chemistry in some other places, also in the industry in some other places. And that's one of the reasons of that mild effect of the second world war. This is an instance of a social system, of the social system acting upon the material system. That's a case. And so far, what we have in these 44 minutes is that this is a brief summary of what we have to discuss here, is that there is a chemical space in terms of the number of new substances growing exponentially with that growth rate that is not even affected by world war time. And this is really important. You see that this is the trend, first world war, but then after that chemistry, it's not that chemistry was growing something like this and then happened the war and chemistry kept growing with the same slope, but something would have been like, no, no, in chemistry what happened was something like a catching up phenomenon. And Jochen also noticed that, Jochen too, okay. But that's important. And it would be really nice in terms of mathematics and mathematical modeling to try to see what is behind that, what is behind that, that catching up phenomenon. Chemists have been very conservative in the selection of their starting material, those synthetic and hydrogen, material, iodine. And therefore the chemical space exploration and the discovery of the chemical space has been rather uneven with some concentration and strong concentration in organic chemistry, carbon, hydrogen and nitrogen and oxygen compounds is something like chemistry is a combinatorial game of carbon, hydrogen, hydrogen and oxygen. And this is what I am presenting here is instances of these two aims we had in the beginning and it's to detect large scale patterns and also to detect driving forces, for example, the use of a few starting materials. But that's one thing, but I promised to talk about some more things. One of my promises was to mention the influence of the material system upon the semiotic system and then now let's pay attention to that. This is a cartoon by Harappé and Colombian cartoon. And I think it encodes or captures the essence of the periodic system. The periodic system are all based on the knowledge of substances and reactions and the properties of those substances and the conditions of those reactions. Without that, it would be impossible to come up with a periodic system. There is, nowadays if you open a chemistry textbook what you see here is electrons and nuclei. Because that's the current explanation, but historically it came from substances and reactions. Then I'm going to use that. I'm going to use the chemical space here but we have the chemical space and we are going to see in mathematical terms we would say we are going to explore the mapping of the chemical space into the periodic system. This is more like the area. We have that the chemical space is expanding exponentially and then we are adding more and more and more substances. The time is passing and then those are the questions we are asking here. If we know, it's not written here, no, but if we know, because Mendeleev wrote that very clear in his 1869 paper, if we know that the periodic system is about order and similarity among the chemical elements, then we can use the chemical space of every year to see how those relationships, order and similarity among chemical elements are changing all over the time. Then we can ask this, what happened about the time of publication of Dalton's set of atomic weights? With that and with the chemical space available by 1810, would we create a possible periodic system? This is the one by Mendeleev. Could we take the chemical space until 1869 and see whether we can recover what Mendeleev saw? And now we have the chemical space until today. How is the periodic system today based on the chemical space of today? That's what I'm going to do here. This is the chemical space at a given time and then what we are going to do is to connect the chemical space at a particular time with the periodic system at that time. Ah, that was what I wanted to say. Then the periodic system is based on two relations order and similarity and order in former times was given by atomic weight and nowadays it's by atomic number, number of protons. And similarity was based on chemical formula. That was more or less the approach that Mendeleev followed. And he said that, or it's not, those are not the words by Mendeleev, but this is more or less what he did. Similarity between element is proportional to the degree of replaceability of one element for the other in the formula. It's, for example, if you have sodium chloride, then sodium chloride, and then if you say, okay, what happened if I replace sodium for potassium? Then you get potassium chloride. Does potassium chloride exist in my chemical space? Yes, okay, then those elements are similar because you can replace one element for the other. And the more components supporting that replaceability, the more similar the elements are. That's more or less the algorithm we follow. But, this is very nice, but it's not that easy. Because in the 19th century, there were different competing atomic weights, and other rock had written a lot about that. Dalton had a system of weights, the Manning had another one, Mejer had another one, and the Leye had another one, different variations. Between these two there was more variations, but here there was a drastic variation, and there is a lot of theory behind that. But the point is that there were different systems of atomic weights, and this is important because with the system of atomic weights, you go and you assume some formula, and then playing with that, you go to talk about similarity. If you have the wrong formula, then you are not able to talk about similarity. And also that has implication for the atomic weight. Then we did two things. This is another paper we published, and this is the part of this topic. Then what we did was to take two approaches. One is a present-day approach that historians hate, and the second one is a retro-dictive approach that historians love. This one is, Dalton said, for Dalton, the formula of water was HO. That was the simple one, and he believed that that simple one was the right one. But we know that it's not HO, it's H2O. Then in this approach, we see the past with eyes in the present. Then we correct all the formulas of the past, and then we say, no, no, no, Dalton, you are wrong. It's not HO, it's H2O, and we do that. In the retro-dictive approach, we believe that Dalton has a HO, and then because the database is even at this. Then now, in this case, what we did was to create an algorithm to take the atomic weights of Dalton and to perturb the molecular formula to come up with the formula that he was seeing through his system of atomic weights. Those are the two approaches. This is a p-d-g-e, let me see. Can I open this? Because it has a link. Yeah, sure. Yeah. We created a website where you can play with the data, and what you can do is this. This is the arrow of time. Those are the elements by 1800, and then you start to see how they are appearing. But that's not the most important thing. I think the most important thing is here, where you have a network of similarities. Then, look at this, for example. The meaning of this is that hydrogen is similar to silver, and silver is also similar to hydrogen. That's the meaning of those arrows. And for every year, we have the chemical space, and then we work out late in the similarities among the chemical elements, playing with the formulas and things like that, and then that was what we did. And then you see here the evolution of the similarities on the predict system based on the chemical space of every year, and then that's. But then the important thing of this depiction here is that, for example, you can select here. You can say, okay, what is, what we shot the formulas containing hydrogen. And you can also say, okay, now I want to see which are the commonalities between hydrogen and sodium. And then you get those, the intersection, then you get that. And that data is there, you can play with that. That's one of the things I wanted to mention. How can I go? Okay, then you see the formula for each element, the common formula, and one set of elements. And you see also with that network, the evolution of the predict system. But we did more and was to compare every periodic system with the rest of the predict system. You see that the predict system was here represented as a network of similarities. Then what we did was to compare the network of this year with the network of the next year, that was what we did. And this is the similarity among the predict system. This is the time, this is the time. And then in this direction, what you see is the preservation of the predict system. It's how much of the past periodic system is in the future system. And here, you see how much of the future system is in the system of the past, is the reverse situation. What you see is that there is a kind of strong similarity in neighboring years. It's a kind of, and that's expected because it's difficult to believe that the chemistry of one year is going to be totally different to the chemistry of next year. That's one thing. But we found something interesting. Some features of the 1869 system over here were observed as early as 1816, that's this region over here. I mean, several of the similarities observed by 1869 were already known since 1816. And here in this case, what we have is that in this case here, that a large part of the system has been preserved since 1826, in 1826, several of the similarities were discovered and they have been something like self-reinforced with the expansion of the chemical space. And we found this interest in region here is something like a strong preservation of the space. That's what we call the Golden Periodic System. That means that a large fraction of similarities observed between this period, 1831 and 1842, remain at least until 1869. A strong similarity here. Between 1831 and 1842, but the system was formulated in the 1860s. But yeah, perhaps I can mention that later or let's mention that here. Why? Why that happened? Why if the chemical space was showing the important feature of the periodic system? Why it took something like 25 years more to formulate the system? And I think there is a delay between the semiotic system and the material system. It's something like chemists, they knew that something was happening in chemistry, but they didn't have the necessity of a system at that time. The semiotic system was not ready for that. Okay, but I mentioned that I have another approach and historian Hayes to be present this and then let's go to apply the algorithm. Then what we did was to, this was the input, this was the output, whereas we have here is the algorithm action and it was something like playing the game as that from the main menu and then the ledger and several others included, the bercelius and several other others. But just to show an example, then we took this, which is provided by database and then we got this, this one and then we got this one and this was what happened. Then it's the chemical space I've seen by each chemist. This is the chemical space and then based on this chemical space, for every chemist we created the chemical space and then we were measuring the similarities with some other periodic systems. This was what we observed. Here what we have in the blue one, those are the authors we have, Alton, Thompson, Bercelius, Gamelin, Lenz and Meija, Ogling, Hingrich, Meija, and Meija. Meija has different versions of the system and Meija as well, but we would need to go farther and we were lazy in that direction. And the blue curve talks about the future of the system not observed in 1869. Then of course, for Dalton would be very difficult to get to those similarities observed by 1869. That was the level of difficulty that he has. And here the red one is the efficacy of atomic weights in approaching the 1869 system. And of course, Dalton did very bad because the atomic weights were very bad. But then you start to see how the features of the system not observed in 1869 were dropping, dropping and dropping, but you see here a strong drop. And you see here, yeah, here there is a good improvement of the efficacy of the system of weights they have. But then here something happened with the Gamelin. It improved a lot. The efficacy of atomic weights increased and the feature of the system not observed, I mean something like the false positives drop. Then with the Gamelin something happened. Something happened around 1840 with the system by Gamelin that has to do with the maturity of the chemical space in the previous slide and what I showed when I showed that in diagram where I showed that stripe here, over here. This one. Yeah, that was around that time. Then something happened in 1940 that something like consolidated the encoding of the similarities of the periodic system. Okay. That's the question. Why if the chemical space was showing that the periodic system was ready by about 1835 what it took several years to be formulated? There is a semiotic delay regarding the material system. There is another question. Is it always the case that the semiotic system has a delay regarding the material system in chemistry? Is that delay between the semiotic system and we could say because in the material system of chemistry what we have is the facts of chemistry. Then you can generalize that to another science and then you could say that there is a semiotic system and there is a system of facts there. Is the delay between the semiotic system and the system of facts a trend in science? Is always the case in other sciences? And if so, are there those differences, those delays always more or less the same for different disciplines? I mean, those delays are the same for chemistry, physics and biology? Okay. Another thing we did was to play because I mentioned that we have access to the whole chemical space and then in the previous slide where I showed was the effect of the chemical space on the periodic system between 18 and 1869. But now what I want to show is this whole picture between 1800 and 2021. And this work was made by address Marulanda Brand and the previous one was made by Wilmer Leal. Okay, and this paper, what we did, he also created a website. And this is very nice as well. Yeah, it's coming. What we did was to, we did the same, we explored the similarities between the periodic systems. Who is number, dictation, number. Okay. Look at this. This is the arrow of time that you can play. What you have here is the similarities among the chemical elements. They are ordered by atomic weight or atomic number in general. And then you can play with those similarities. You see how, for example, after the second world war, you get the lanternaries and the octinoids there. But that's not what I want to show. What I want to show is this. Is that the similarities in the periodic system depend a lot on the chemical space. And for example, if you take a chemistry textbook and there is a lot of discussion on the position on hydrogen and the periodic system. And some say, no, it's similar to the alkali metal. Some say, no, it's similar to the halogens. And some are saying, let's put it in the middle or something like that. But then let's see, what is the chemical space telling us? Then let's go back in time, let's suppose 1820 and click on hydrogen. Those are the similar, the stronger the color, the more similar the element is to the one I clicked. Then those are the elements similar to hydrogen. Alkali metals. And if you remember, that was the ratio at the beginning, that was the regime of inorganic chemistry. That makes sense. But then what about today? After the strong explosion of organic chemistry. Hydrogen is not any more similar to the alkali metals. And it's not any more similar to the alkali metals because there are thousands, perhaps millions of compounds where you can replace hydrogen for chlorine, chlorine, iodine. Then you have this here and also there are some similar to the carbon nitrogen and oxygen because of the strong emphasis on carbon, hydrogen, nitrogen and oxygen. And you can play with several other elements there that the website is there and you can play with that. We also did the same. This is the period that we studied in the first paper and now we have the complete picture. And then to make the story short is that we found some periods of change. For example, here was setting up the basic chemical alphabet of discovery of chemical elements. And once we got a kind of stable number of elements then we started to explore the chemistry of that alphabet. And after that came the kingdom of organic chemistry and there was a strong stabilization of the periodic system. That's why you see the red region of her hair over there. More stabilization given by organic chemistry that was here between 1940 and 1980 after formation of the similarities. So that is got here. And that was given by the discovery of octinoids and the red discovery of the chemistry of the land tonight and things like that. And here what we have is a current stabilization of the system and the interesting thing is that that's converted. And that has to do with the self-reinforcing manner in which we have expanded the chemical space. Then just to conclude, then with the data we have and with the ideas we have and with also the ideas of philosophers and historians of chemistry, we can do many, many more things that are prone for many more studies in the history and philosophy of chemistry. Summarizing this is the there is an exponential growth of the chemical space that is not affected by world wars, there are statistical regimes of production that has to do with the detection of strong transitions that may think of a potential scientific revolution. The important role of synthesis for expanding the chemical space which has been very conservative and concentrated on carbon, nitrogen and oxygen using the fixed substrate approach of using a few starting materials to expand the chemical space. And in terms of the predict system, is that the predict system is not set in stone? We are not saying here that we are changing the rules of quantum chemistry. We are not talking about that. What we are saying is that the similarities among chemical elements depend or if you take as that there is some relationship between the chemical space and the predict system, then the chemical space may affect the predict system because of the diversity of the chemical space. Assuming that, and as I showed the results, and then the predict system is not set in stone but rather a historical object and I showed how, for example, the similarity of hydrogen is a good example to show how that depended on history. And then the predict system has been affected by material aspects of chemistry and also social factors by material aspects is the discovery of new elements, the discovery of new oxidation states that we also saw that. The effect of social factors, for example, the influence of worldwide research in the discovery of actinides and the red discovery of lanthanides. And this is the question is, why if the chemical space was ready by the 1840s using the retroactive and presentist approach, that both methods show that about 1840 the chemical space was showing a red diffident existence. Why did it take about two decades more to formulate the system? Those are some questions. And why we have that? Why we have that role? Nothing else, nothing more. Why is that exponential? What is driving the expansion in an exponential way of the chemical space? What is the role of the size of the chemical community, for example? And we are right now studying that. And this is a kind of philosophical question. Shall we keep pushing for an exponential growth or for an exponential discovery or for example, new reactions that would be more attached to production of knowledge? How we model the growth of the chemical space? And this is the dream because at the beginning I showed that the chemical knowledge depends on the social, semiotic and material system. What is the interplay? I showed some binary relationship but it would be really nice to play, to put all the orchestra to produce the symphony of chemical knowledge. And the question about, with one error here, the 3D case of the delay between the semiotic system and the material system. And with that I would like to acknowledge the support of Curbidios, Petrash Tadla of these institutions, of Reaxis, of course, without that it would be possible to obtain this work. The glue mathematician, the mathematician, mathematician, chemist, astronomer, he has different kind of knowledge. Duke is a mathematician and statistician and Alejandro Garcia-Chun is a physicist. Andres Bernal did the first visualization. He's a chemist, Marisol is a chemist and a very talented programmer. Andres did the second visualization and the second, the whole picture between the chemical space and the pre-existing between 1800 and today. He's now doing the PhD in Switzerland. Wilmer Leal is now, he did a lot of work for the first paper. And he's now in the States doing a course doc and Alejandro Giannis is finishing his PhD in Colombian. He was also involved in the data analysis of this. And with that, thank you very much. I'm sorry for taking 10 more minutes. Sure about you. I'm okay, yeah, go ahead. Let's maybe take five minutes. I think I'm back again. I'm hoping so. I see the microphone. Is it working? Good. Turn the screen so that we can see you. Yeah, yeah, yeah. You can sit there then. Yeah, I was probably in this one. There's no questions so far on YouTube live. So, questions here, yeah, Kevin? Yeah, the question is over. They just started to talk, they were talking about the idea of progress of the industry. So the progress we're going to do is we're discussing what is the problem is working. The progress in the material side of the chemical relation, the reaction of the expansion of the chemical space is because of the material energy. And how it's related to the symmetrical part of the product, the polyacid is not ready in the industry because you are talking about how the semi-ITF order, so the data is a historical object. So you see when you go over the shift in the semi-ITF or something of, I think of hydrogen, semi-ITF, similarity. Is the paradigmatic shift, or is it? Will progress just type of deepening of your understanding of the chemical space by adding of new and new and new material reactions that you get just new energy of the chemical space. So it's truly a paradigmatic shift of how you're going to visualize the value of the data. We are thinking, yeah, talking about progress here means that you have something like a target and I think chemists don't have a target. They just want to go for, to try to explore more and more, try to discover more and more. And in that process they are using what they have at hand and for example at the beginning they had all those acids and they were putting that on substances and seeing what happened. And that was the time of similarity between hydrogen and alkali metals. But then for example with the Kaliya Parada they were able to manage and to handle organic substances. And then with that technology they could go into the direction of organic chemistry but the aim has been always to try to discover more substances. And what we see here is that similarity that is strongly connected to those activities they have, but I don't know if we can say that that's a progress or yeah, I think is if the target is to explore more or to discover more substances, I mean to increase the size of the space then of course we are progressing. But if the target is to produce more knowledge we are not that good at that. So you said it's truly a part of that shift in the conception of hydrogen as similar to alkali metal and sort of the conception of hydrogen as part of, okay. Mm-hmm, mm-hmm, okay. Yeah, okay, thanks so much. Yeah, thanks so much. I'd really like to talk about this gamer. I'm a historian, but I don't hate pessimism. So, yeah, so I have a lot of things that I tell about so I'm going to be brief. But yeah, the first one is that I think not all historians not all hate pessimism. I think it's a matter of actually I think some kind of historians, like environmental historians, they are, we are very pessimistic. We can get about explaining the present. No, no, no, no, no, no, no, yeah. And so it is a very, it has a very pessimistic connotation. Perhaps the kind of explanations are not pessimistic, are very sort of localized. I'm trying to understand that because it's all right. But I don't think, well, I didn't see your presentation as too pessimistic to be honest. Okay, that's good. I mean, I think the explanatory goals might be different than like archaic-based historian, but anyways, so that's that comment. Another one is if you can unpack a little bit what you mentioned a few times on, so there are tropocene, I don't know if you want to talk a bit more about that and sort of just something I really like which was this notion of knowledge space of the middle of those three parts, which is one, but they all have interactions between each other and among each other, the three of them. So how does that relate to any criticisms that we might, that people working in the tropocene literature might bring to the history of chemistry? Because your knowledge space, how does that relate to let's say, I don't know, the toxicity of companies and the lack of regulation? I think that's what people in the tropocene literature might bring up as like, this is the problematic. Not so much what scientists do, but really sort of a lack of regulation or you know. And so how does this knowledge space relate to, I want to say the real world effects of chemistry? That's a very good point. I have thought a lot about that and is, I would say that because what I show, most of what I show is based on publications in journals. I mean, this is the academic space, the academic chemical space. That has nothing to do with the tropocene. Not directly, it's not directly related to the tropocene because what matters in the tropocene discussion is all those substances that go to the rivers and they are accumulating and those are coming mainly from the industry. But we really have information on patents. And that was one of what I was saying. And we haven't explored that in detail. But one thing we found is that, for example, the chemical space of the level of substances is growing as I show, but the chemical space at the level of patents is growing faster. That means that chemistry is something like going in the direction of, okay, it's something like keep playing with your academic chemistry, but let's get serious and chemists are moving also in the direction of the, and that has happened since the 19th century, moving in the direction of the industry. Then there is a strong, and we have access to that. Then the same approaches can be used to explore, you can get rid now of all the academic publications and concentrate on patents and see what is produced by chemical industry. And see, and also we have access to the properties. You mentioned that that's the most important thing in the tropocene, whether those substances are going to be bio-accumulated or not and things like that. We have access to the information. That's what I call, I normally say that we have the chemical space that is that the reaction network, and there is another space, which is the space of properties. And then for every substance, we have a connection between the substance and the space of properties. And we want to explore the evolution of that space of properties over the history. For example, if you are now thinking that space of properties, the question would be, are we creating more substances, which are, for example, hepatotoxic, or are we creating more substances that are bio-accumulated? And if we are doing so, then we need to do something to adjust that. And there is a strong connection with the Anthropocene, but I didn't show that here, but we have the data to do it. Just a follow-up question. How do you have that data? So the patent data that's available, is there some, I don't know, maybe it's very naive, but to some of these companies, has knowledge that we just don't get access because these products are kind of something that we just don't really... The viewers are asking if you can briefly repeat the question because they're not going to be able to decide. Or we can move things. Yeah, it's going to be difficult, I think. So if you can just briefly repeat it. Or you go and that repeats. So the last one or the last one? Or the one you just asked. Yeah, so now I just asked whether, but yeah, yes, so how do you have access to the knowledge from patents and whether there is some that it's closed behind the doors of this company? Yeah, that's one question. And the one before was how this approach can be used to address the question of the Anthropocene. And that was the question that they replied that I gave before. And now the one is how do we have access to these, whether industry is opening that. There is a restriction of opening the files after a certain time. And once that is possible, then the REAXIS is incorporated that information. But another point is that the REAXIS is not an open and freely available database. They are owned by Elsevier and they sell licenses to use that. But they have been very, very kind with us and after a negotiation we got an agreement and then we have full access to the database. That's where I say that we have information on the properties of the substances. And the people behind those substances, we can also study social issues here. Sometimes we have also information on the affiliation. It's not that complete, but we have now some means to complete it. But yeah, we have access to all of that and in terms of patents after a certain time, you can get access to that. Yeah, thanks. I have more questions, but I'm going to keep it for now. Yes, my first question would be rather, maybe in detail, but I'm quite intrigued by the fact that you put the technology in the material parts. While technology doesn't seem to be something material to me, it's partly semiotic, it's partly social, so why the decision? It's creepy. Yeah, the question was why I put a technology as part of the material system and not part of the semiotic system, for instance. And yeah, you are right. Those sets, those systems are not crispy sets and the intersection is not empty. They have some overlap. And we thought a lot about that and also, for example, in the semiotic system for example, in the semiotic system, shall we include algorithms, artificial intelligence or not, because nowadays there are books written by algorithms and then who's the author of that? Then there are different discussions on that, but we at the end, we decided to put technology there because that's part of, I mean, when you perform a chemical reaction and you analyze the product and you do the separation, you are incorporated. It's something like, this is another substance. This is part of the repertory of making a reaction. That was mainly the reason. But it's a very pragmatic reason. There is no other reason. Okay, thank you. Another question would be, unless, for a moment, like whether the focus on substances, I don't know anything about chemistry, so maybe that question will become, it will be explained by that aspect, but why is there such a focus on substances and growth of substances and so on in your work? And doesn't that create a certain bias? I guess, like in every science there is also in chemistry a lot of other theoretical kinds you could focus on and evolution of those, like at some point you said that there was only linear growth in the reaction, kinds of reaction, something like that. So then you see another completely different evolution and there is something a bit weird about this exponential growth and certainly when it's going all in one direction, which you hinted to, I think at some point too, that it seems like it doesn't seem theoretically very interesting if there is a very efficient way to develop, to create a lot of new substances, but it's efficient. There's no real new theoretical patterns developed here. And so doesn't just like by studying chemistry, focus on substances, give us this bias away from maybe more interesting structural or theoretical phenomena. I don't know. Okay, shall I repeat the question? That's a challenge, but let's go into the questions. No, I think I can summarize it. The question is why I'm focusing on substances rather than in some other objects that I could study. For example, I would say theories. If my interest is chemical knowledge, what substances? Why not theories, for instance? That would be a very valid claim. Whether that creates bias. Yeah, and that focus on substances may create a bias and that's totally true, but I'm not the only one saying that. For example, Jeff Nishuma and Bernard Betts. I'm not able to pronounce that. That's my experience. Yeah, this famous lady of history of chemistry, Bernadette, I call her always Bernadette there. She and Joachim, they have said that, and I believe that that's why we put at the center the chemical space is that all theoretical ideas in chemistry come, for example, the very existing come from the knowledge we have of substances and reactions and the properties of substances and the conditions of those reactions. Something like that's the source of chemical knowledge. Of course, we could explore, for example, the structure, and we were talking about that in the break, the structure of concepts. How? Because I imagine the concept also as a network, network of concepts, and it's a dynamical network changing over the time. We could explore that network, but I would say that that network depends on the chemical space. That's my point. And there are methods to study that with computational linguistics and things like that, and we are also trying to move in that direction. But the strong emphasis in substances, in substances was because that was what we had at the beginning, but now we have information on the growth of new reactions. And as I showed, Rivaski has also shown results on the growth of new classes of reactions. But for example, in the growth of new reactions, we see that there is also an exponential growth. It's more or less the same growth rate as the substances. Then it's something like, I imagine that as chemists are waging the chemical space, and they are connecting substances via reactions and the speed of connecting is more or less the speed of discovery of new substances. That's more or less the idea. But yet we can also explore some other things. For example, network of concepts and the social structure that has to do with the social system, we are also moving in that direction. Maybe just a finger there. Would you go as far as saying that what is shows is that chemistry is still very much a science of trial and error? In a sense, you also show that most of these substances are only used once. Most of them have only been synthesized once. They're not re-synthesized. And I remember in the research group, I was in all of the students and postdocs who were making liquid crystals and they were making ionic liquids and it was the same kind of game, yeah? Putting the Lego pieces together and then putting a larger group on it or a different functional group for expanding the chain of the carbon, and then going to measure the properties because they had a certain goal in mind. They had to have this or that property. And it's because we couldn't predict beforehand that that particular compound would do the job perfectly and none of the others, that we were kind of forced to synthesize a whole series of very similar substances to then actually reject 99% of them and maybe focus on just this one. So I think, and I wonder if that would change and if maybe the exponential growth would change because I know that nowadays in catalysis, for example, yeah, this was very much a trial and error thing. They were just trying to see what could help to catalyze a chemical reaction. Nowadays, with all the knowledge we have, with the computational power we have, we're able to already design certain possible catalysts, maybe already calculate computation whether we will do the job or not, even before we get to the level of synthesizing. So maybe we're going to get more focused in what we synthesize because we kind of know where we want to go and that it will do the job. I think a good proxy of trial and error is the volatility of the signal. And I think today we are far from trial and error or we are doing the same. I mean, we are playing the game of trial and error but in a more narrow sense. Before in the 19th century, at the beginning of the 19th century, there were really trial and error. At least those were the times where we have more freedom in playing with, I'm gonna pull this here and see what happens. But now then with the passage of time, we start to see that there are some methods that go in the direction of discovering a particular substance with some particular properties and that work. Then let's repeat that with some small variation and that reduce the variability of the signal. And that's what is happening. Then we keep doing trial and error but in some, it's something like you have the chemical space before you were trying here, there, there and now then we keep expanding the chemical space and then we say, okay, there is something interesting here. Then we do trial and error but here, not that. And then it's something like focus trial and error and of course we have been driven by technology as well. The computational approach and computational predictions are playing a big role here. For example, now if you want to publish a paper with a new synthesis of some substance, you need, and if you want to go for a Jack's paper, you need to go not only with the synthesis, with the spectroscopic evidence of the new molecules you created, the new substance you create, but also you need to go with the calculations, the DFC calculations supporting your claims. Then there is a lot of effort and a lot of contribution for computation there but you keep doing the trial and error but in a very narrow section of the chemical space. And that's where I think this happened. So I don't think it's kind of forgot what Peter was talking about. You said that what meant that the essence of chemistry was to be grounded on discovery of self-substantial reactions. I was like, I really like the picture that you gave of the structure of science. I wasn't doing it how universal do you think it is? And if the structure applies to all science so it's usual to the chemistry kind of science and what makes chemistry really like a unity this is the usual part of the physics of what you are on our side. I think the question is whether, if I get it right, is whether those changes we have seen in, for example, in reduction of the variability are proper of chemistry or you can extend that to some other sciences. And I think that has, this is a general trend that has to do with our specialization in science. And yeah, if you go, for example, if you go to do a PhD and then you say a very crazy idea to your advisors, I think you are not allowed to do that. You need to do that because the business of science is to keep producing that very rapidly and to keep producing papers. And then that freedom is somehow constrained. And I think that happened in every field. And we have seen that here in chemistry and I think that recently there was a paper, I think it was a nature paper where they, it was by the group of Evans, if I'm not wrong, he said that the disruptive character of science is going down and it was measuring not things like this, but the production of new of, it's something like the degree of innovation of science is going down. But if you see the number of publications, they are growing very fast. I think that's a general trend. And I think those strong transitions that we found that could be chemical revolution, scientific revolutions, I think that those are happening in several fields of science. So again, the general structure that leads to this kind of effect is the same for all science. Yes, I think so. And perhaps you could use those methods to try, you could define a standard, you could say let's suppose that you say, what we observe here in chemistry that those two transition three regimes is something like the path to get a mature science. And then you can go and see how it's happening that in some other sciences and then you can measure the degree of maturity of that science, it would be something like that. Oh, that's really good. That's something that's for you. But in the case of usually people who are trying to show us a unique science, like we have the island, the island, talking about like fissiles, to distinguish it from other scale of science. Do you see it here against this kind of distinction of? No, I think this is a general trend. Probably. Yeah, thanks. I have a comment from Jeff Sieman. I'll read it in the knee care and you can see if you want to react. He says it's easier to count the number of new compounds, but very hard to classify what is a new reaction. So for example, a novel transformation within a very complex molecule may actually not be later generalizable versus a new generalizable reaction type, which would often then be called by a named reaction, such as the deals of the reaction that you mentioned. There are methods to do that. And I'm very good Jeff that you could make it. There are methods, for example, Griebowski used that. When you have a chemical reaction, you can detect with methods of chemo-traumatic. You can detect the atoms involved in the chemical transformation and the bones which are breaking and forming. That's the reaction center. And then the approach that Griebowski followed was to detect in a whole bunch of chemical reactions was to detect the reaction center of all the reactions. That's what he found, for example. If I give you one million reactions of the type deal solder, the reaction center is going to be the same. That cycle or those six carbons involved in the transformation. Then whenever you find the same cycle, you could say that those are different versions of the same transformation. Then in formal terms or in practical terms, what you do to look for chemical classes is to look for the reaction center. And then you can do that using computers. And that was the method that Griebowski used. And I think it's a very nice method. But then with that, you can go at the level and to get a very big list of chemical reactions and detect how often you really get a new reaction center. Hi, I have a question. So your project reminds me a bit to what my supervisor and I do because he's doing, like, he uses data from journals, biological journals about taxonomy, and there's this analysis at that sort of computational level. And I do the sort of archival based research. So I wonder how, and there's always this tension of how to integrate the two projects, right? How to integrate his findings with my findings. Also, epistemically, we are based at different levels. So I wonder how you interact with archival based historians. You mentioned some like Bernadette. So I wonder how do you integrate very empirical findings with your view of findings completely in one? There was this odd phenomenon of after World War I, the production going on and then not, as you say, not going at the same level, but going to the point it was supposed to be. And as a historian, I find this sort of ontological, right? Like the progress of chemistry had to be there. Exactly. So as a historian, I'm freaking out because I'm like, how could this be? This is not what should be happening. So do archival based historians provide other kinds of explanations for this phenomena? Have they even, I mean, have they found this phenomena or how did they explain what happened after World War I in terms of chemical knowledge and the expansion of chemistry? Okay. And we need to rebuild that. Okay. Sorry, next time I... No, no, no, don't worry, don't worry. If you give more context than that, better for me. The question has two parts and it's, how is that interaction? I mean, how I interact with historians of chemistry and how they are receiving this and how I am collaborating with them. And also that was one part. And the second part was that in the, we have the growth of the number of new substances. We have the drops because of the war. And then we find that because of the catching up phenomena, we go back to something, if nothing were happening, something like that, nothing had happened. And then you said that there is a kind of teleological idea here in the expansion of the chemical state and I was also puzzled with that. Okay. Then the first thing is about the interaction with historians. I feel very lucky with that because I know that bringing new methods is always a problem. I have experienced that in several fields. For example, before I was working more in the interaction between mathematics and chemistry and chemists are very reluctant to accept mathematical ideas and it's always a problem to bring things from other disciplines. But in these terms, I think historians are very open. I was mentioning to Peter that a couple of weeks ago, I was in a meeting with Bernard Ardé, Delana Alonso, Jeffrey Johnson, several historians, leading historians are they and they are very open to this. For example, Jeffrey Johnson. Jeffrey Johnson has written a lot about the effect of words and word words in applied chemistry and the other way around the role of chemistry on word words. And I remember we were discussing in that meeting and I was showing some trends for particular elements and then it's very rich that interaction because what I see are some trends and I see here something happened and then I go to talk to them and they say, yeah, of course, at that time, this fellow was doing this and that and what I find interesting of these methods is that with that, you can go for the whole period or centuries or something like that. You see something particular in some particular years or something like that and then you go within and then you see they can start to check and revise their archives and they find some explanation for that because then one thing is important with those methods, we detect patterns, crucial points, but nothing else. You need the historical narrative behind that, the causal relationship is, or perhaps a historian may say, why don't you explore this fast or something like that, this kind of property or something like that then we go and see that. But you need to have a good relationship with them and unfortunately they have been very open to these methods. Now about the teleological point of the expansion of the chemical display, that's impressive and because of that, we are not right now trying to develop mathematical models to try to play with some basic rules to try to get to that. I mean, and we are using agent-based modeling which is playing with, for example, how often or which are the rules of interaction of chemists to produce new substances and how you can adapt those rules and something like happened before and after the world war, what happened during the war that changed the way of doing that, that put that in the same train that had before. We are also exploring that in terms of the mathematics of the network, it's finding the chemical space and Jeffrey Johnson has also several ideas in that direction. He has written recently about the recovery after work because, for example, it could be that chemists because you need to take also into account the speed of publishing papers that may change in, of course, that change in work times but you can keep working, perhaps not with the same amount of people but you keep producing results and once the work finished, then you publish that and then you get to that point but those are things that we need to test with mathematical models. It's for a talk. So, this one has a final question. Please join me in thanking you for a fantastic talk. Thank you. Thank you.