SIAM’s special interest group on Mathematical Aspects of Materials Science has successfully crashed this year’s fall meeting of the Mathematical Research Society with a Symposium NN on Mathematical and Computational Aspects of Materials Science. Symposium NN will run from December 1 to December 4. For more information on this year’s meeting in Boston, see the fall meeting webpage.
As you may have noticed, a comment on the previous post inspired me to adjust the post. (Actually, it raised an issue that will deserve a post of its own.)
Since I would like this blog to be useful to a wide audience, I appreciate comments, corrections, suggestions, criticisms, etc., either posted on this blog or emailed to me. After all, I should be described (to paraphrase Jane Austen) as a partial, prejudiced & ignorant crystallographer, and I would like to keep posts as correct as possible.
(Comments, by the way, do not appear on the main page; notice at the upper right hand corner of this post, just right of the headline in small gray type next to two small gray bubbles, is a note about comments for that post. To see comments for a post, or to post a comment, click the headline of the post, and at the bottom of this new page are comments and a form for entering comments.)
Unfortunately, most comments entered come from spambots, programs that surf the web, looking for sites like this one to post ads for X-rated products, post links in order to inflate their own page rank, etc. In order to prevent this blog from being weighed down by this kind of nonsense, comments are moderated. That means that a comment is entered, it sits in a “pending” folder until I get to it and approve it.
I try to check the pending folder daily, but if you posted a comment and it doesn’t appear within a day or so, feel free to email to me. (Feel free to email me about this site in any case: I appreciate the feedback.)
I apologize for the inconvenience, but I think that this is the least inconvenient system for the situation we have.
Let’s start with crystal structure prediction. Suppose that you would like a crystal with various properties (it’s purple, porous with channels two nanometers wide, nonconductive, etc.). Traditionally, finding such a crystal would involve synthesizing many novel chemicals and annealing them, and hopefully a sequence of increasingly successful combinations would ultimately lead to success. This was the method that the alchemists employed in their pursuit of the Philosopher’s Stone, and whose modern, automated incarnation is called Combinatorial Chemistry. It may have been good enough for Paracelsus and Robert Boyle, but it is expensive and frustrating.
More to the point, this is not what engineers and architects do. In construction and industry, someone composes a set of blueprints specifying the final product and (hopefully) intermediate steps, and then someone (often someone else) uses those blueprints to construct the desired product – which, no coincidence, satisfies the original specifications. Chemists should be able to do that.
The general project is crystal engineering, which Wikipedia defines as “the design and synthesis of molecular solid-state structures with desired properties, based on an understanding and exploitation of intermolecular interactions.” Wikipedia says that the oldest reference to the term is G. M. J. Schmidt, Photodimerization in the Solid State in Pure & Applied Chemistry 27:4 (1971), pp. 647 – 678, but Web of Science says oldest reference they have is an abstract for a paper presented to the American Physical Society meeting in Mexico City, Mexico, August, 1955 by R. Pepinsky entitled Crystal Engineering – A New Concept in Crystallography, abstract published (but not posted!) in the Physical Review 100:3 (1955), p. 971. There being nothing new under the sun, the notion probably has been floating around since the beginning of the 20th century.
In the last few decades, crystal engineering has become of field of its own: on October 23, Web of Science listed 2,520 hits from all databases, and now the subject has its own textbook: Crystal Engineeering : A Textbook by Gautam Desiraju, Jagadese Vittal, and Arunachalam Ramanan.
The growth of the field is a little more problematic. Here are the 2,520 hits in the Web of Science by date:
Notice that after Pepinsky’s 1955 talk, Web of Science has no hits until 1976 (Schmidt’s 1971 paper did not have “crystal engineering” in any of the fields Web of Science checks – a warning to people who rely on such databases), and things really didn’t get going until 1991. Most of the growth was during the 1990s: a linear regression shows that publication growth during 2001 to 2013 has been nearly linear, an average additional 3.3 papers a year, or less than 3 % growth per year. Growth in citations looks more exponential, which shows that crystal engineering has been gaining a higher profile lately, but the number of citations has been flattening out during the last few years:
Let’s take a closer look.
In 1988, John Maddox wrote an op-ed in Nature:
A new calculation of the polymorphs of silica appears to have broken new ground in deriving crystal structure from chemical composition. But X-ray crystallographers need not worry — yet. |
and grumped that “[o]ne of the continuing scandals in physical sciences is that it remains in general impossible to predict the structure of even the simplest crystallographic solids from knowledge of their chemical composition.” This is an intermediate position: he is complaining that as of then, a chemist couldn’t choose a random small molecule and predict the structure (or structures!) exhibited by its crystal.
But even if Maddox was taking an intermediate position, he had launched the verb, and it was quickly associated not only with predicting what crystal a given molecule would produce, but what crystal structures could exist. During the past few decades, chemists have explored the possibility of taking the desired properties as a list of specifications, designing a crystal at the molecular or atomic level that will satisfy those specifications, generating a synthesis process from the design, and synthesizing the crystal – which will satisfy the specifications. As of 22 July 2014, Google Scholar listed 3,450 hits for “crystal structure prediction”, and on 25 June 2015, Web of Science reported rapid growth in the field since the mid-nineties:
Notice that unlike crystal engineering, there has been no recent growth slowdown. (Although I have heard chemists and crystallographers use the phrases “crystal enumeration” and “crystal structure enumeration”, and I have seen those phrases in print, Web of Science reports no hits for either one.)
As of 19 October 2014, Web of Science listed 702 hits for either “crystal prediction” or “crystal structure prediction”, and the journals that had published at least twenty articles in the subject were:
Journal | Hits |
Crystal Growth & Design | 64 |
CrystEngComm | 47 |
Physical Chemisty / Chemical Physics | 33 |
Physical Review B | 30 |
Journal of Chemical Physics | 25 |
Journal of Physical Chemistry | 25 |
And this is just those articles for which one of the two phrases is picked up by the Web of Science topics field.
Crystal structure prediction is new enough so that one can’t say what the fundamental mathematical issue is, but one could start with the work of Alexander Wells, whose book on Three dimensional nets and polyhedra presents the notion of a net, i.e. a finite or infinite graph embedded in three dimensional space. The vertices of this graph are points in space, while the edges are line segments (or curves) whose endpoints are vertices; typically, we all edge intersections should be at vertices.
(“Nets” might also be called “Euclidean graphs” or “geometric graphs” as they are graphs embedded in a Euclidean space.)
A net could represent a material structure by having the vertices represent atoms or molecular building blocks and having the edges represent chemical bonds or linkers. (We sidestep the issue of whether we believe in chemical bonds.) Then a (classical) crystal may be represented by a periodic graph, i.e. a graph with translational symmetries in three axial directions. We have reached the formulation of “crystal nets” as described in Michael O’Keeffe and Bruce Hyde’s Crystal Structures I : Patterns and Symmetry.
In mathematics, once you get your paws on a definition you can do things with it. We have a definition of the word “periodic graph”, which is the central mathematical notion in what Omar Yaghi calls reticular chemistry. A mathematician then mimics Stewart Robertson’s agenda and proposes the following:
- Let P be the set of all periodic graphs. Since P itself has a geometric and topological structure, we might call P the space of all periodic graphs.
- We usually regard two periodic graphs as being the “same” if one is the result rigidly moving the other around, so we can define the equivalence relation ≅, where “A ≅ B” means that the periodic graph A is the result of moving B. Given a periodic graph A, its equivalence class is the set [A]_{≅} = { B : A ≅ B}. It is this equivalence class that fixes the size and shape of the structure, so once could say that the space of these equivalence classes, which we denote P/≅, are the models of (classical) crystal structures.
- This is not quite how periodic graphs are currently specified in, say, the Reticular Chemistry Structure Resource (RCSR). Current practice is to specify periodic graphs by isomorphism type. Call two periodic graphs A and B isomorphic if there is a one-to-one correspondence between their vertices such that that there is an edge connecting two vertices of A if and only if there is an edge connecting the corresponding two vertices of B. If two periodic graphs A and B are isomorphic, write A ∼ B, and the isomorphism type of A is [A]_{∼} = {B : A ≅ B}. We could denote the entire space of periodic graph isomorphism types by P/∼, and RCSR has a catalogue of periodic graph isomorphism types.
As Igor Barburin observed (see his comment below, which inspired a revision of this post), the situation is a bit more subtle than this. While two periodic graphs are often considered to be the “same” if they are isomorphic, a database like RCSR may have, for each periodic graph listed, a particular periodic graph in its catalogue, listed as a geometric object with geometric properties. For example, while pcu comes in many shapes and sizes, RCSR lists a particular geometric realization of pcu (of maximal symmetry). The infinitely many other geometric realizations of pcu are themselves classifiable by geometric properties (including symmetries) – and topological issues like chirality.
We will discuss issues in classifying and cataloguing periodic graphs in later posts…beginning with the question of exactly why Dr. Baburin’s comment inspired me to replace the word “classify” with the word “specify”.
Anyway, two of the central problems of crystal structure prediction is the generation and classification of periodic graphs by rigid motion equivalence relations, by isomorphism types, and by other criteria. But even that is not enough. The Atlas of Prospective Zeolites Structures has over five million nets, but few of them have been synthesized. If crystal structure prediction is to be more than a recreational activity, it must include designing the synthesis process. After all, the purpose of a blueprint is to provide a roadmap for building the structure.
But at present, most of the activity seems to be in generating periodic graphs. But before we survey that activity, we should follow Socrates’ advice and get a handle on what it is we are talking about. So what do we know about periodic graphs…?
The Society of Industrial and Applied Mathematics’ Special Interest Activity Group on Mathematical Aspects of Materials Science has just launched a Facebook page. This seems to be the informal penumbra around plans to create a wiki at the group’s website.
A bit over a century ago, the scientific community had decided what a crystal was. A crystal was a material whose atomic or molecular arrangement (this was the same era during which atoms and molecules were finally accepted) repeated periodically in three axial directions. Sir William Bragg and his son developed x-ray crystallography, and crystallographers could develop good descriptions of what these repeating “unit cells” looked like.
This was probably a necessary step. Socrates would say that if we are going to study crystals, we must first decide what a “crystal” is.
Socrates’ is not a universal sentiment. To paraphrase Ludwig Wittgenstein, to teach a student what a crystal is, one presents the student with a diamond and say, “crystal”, and then with a large salt cube and say, “crystal”, and then with a lump of amethyst and say, “crystal”, and then the student starts getting the idea. In real life, Wittgenstein is right: definitions (and food fights over definitions) emerge from catalogues of examples and counterexamples.
That does not mean that definitions are a waste of the taxpayer’s money. Consider my current obsession: predicting crystals. Crystal prediction requires software, software requires theory, and theory requires definition. If one is to predict crystals, one needs to know precisely what crystals are. For crystals (as they were understood over most of the Twentieth century), one will probably wind up doing a variant of one of the following:
- Design a crystal by assembling a structure within the space of a unit cell. One takes a generic parallelopiped, with side (vectors) labeled x, y, and z, as in this picture…
…and then one identifies the three pairs of opposing faces of the unit cell, so that a fly buzzing into one face will then buzz out of the opposing face in the same direction. Within this unit cell, one assembles a structure, possibly adjusting the shape of the cell (i.e. adjusting x, y and z) en route. (References for this sort of topology includes Michael Henle’s Combinatorial Course in Topology and Hajime Sato’s Algebraic Topology : An Intuitive Approach.) - Assembling a structure by taking some kind of fragment or collection of fragments, and then attaching them one to another to another, all monitored by a device that can recognize when a unit cell or equivalent has been assembled. (References for this sort of group theory include John Meier’s Groups, Graphs and Trees.) This is the approach I proposed in my presentation to the MathCryst commission.
(All this also requires linear algebra – see, e.g. Hoffman & Kunze’s Linear Algebra – and abstract algebra – see, e.g. Israel Herstein’s Topics in Algebra.)
Both of the above approaches presumes a definition of “crystal” that is somewhat like this:
- A crystal is a material composed of a finite number of types of constituents, and whose structure admits a symmetry from any constituent to any other constituent of the same type.
This is the fundamental classical definition based on nanoscopic structure, and it is the one that a mathematician might start with. But this definition is not the definition that emerged from Eighteenth and Nineteenth centuries and held sway until the 1980s. For the more popular definition, I’ll quote from Charles Kittel’s Introduction to Solid State Physics (2nd ed.):
- A perfect crystal is considered to be constructed by the infinite regular repetition in space of identical structural units or building blocks.
This definition is at least as old as Kepler, and may go back to the Greek atomists. Mathematically, these two definitions are equivalent, a fact that one might regard as the Fundamental Theorem of [Classical] Mathematical Crystallography: A material is composed of a finite number of types of constituents such that its structure admits a symmetry from any constituent to any other constituent of the same type if and only if it is constructed by the infinite regular repetition in space of identical structural units or building blocks.
Yet Kittel was typical in starting with the second definition, and the first definition – if it is mentioned at all – is mentioned as a rationale for the second. In practice, these two classical definitions above are quite different.
- The first definition arises from the apparent homogeneity of crystals, that is, it is about an observable property of crystals. Thus it is somewhat like what computer scientists call a specification: given a crystal, this is the “spec” that it has to satisfy. A specification may not say very much about what the object is so much as how it behaves.
- The second definition is closer to what applied mathematicians call a model. It is both descriptive (giving a better idea of how to recognize a crystal if you encounter one) and prescriptive (giving a better idea of how to construct one, if only out of styrofoam balls and toothpicks).
(Of course, the first definition is rather model-ish. We will see more pure specifications in a moment. In general, there is a spectrum from specification-ish to model-ish.)
Perhaps the main theme of the 2014 IUCr Congress is that old definitions have been replaced by new ones, thanks to quasicrystals and the like. Very roughly, the new definitions can be associated with the work of Dan Schechtman (who won the 2011 Nobel Prize in Chemistry) and of Aloysio Janner and Ted Janssen (who shared the 2014 Ewald Prize), respectively:
- From the IUCr Online Dictionary: A material is a crystal if it has essentially a sharp diffraction pattern… (the rest of the entry devoted to what “essentially” means). In Volume C of the IUCr tables, Janner, Janssen, Looijenga-Vos and Wolff restrict this definition to require that “… its diffraction pattern is characterized by a discrete set of resolved Bragg peaks, which can be indexed accordingly by a set of n integers …”. These definitions are specifications, pure and simple. They impose criteria that must be satisfied in order for an object to be a quasicrystal, but they does not tell us what quasicrystals are.
- There are a number of mathematical models of crystals. For example…
- One model is the cut-and-slice model, which I can oversimplify as follows. Given an n-dimensional lattice L, and one creates a slice consisting of an k-dimensional subspace S and a n- k – dimensional “window” W, to get the n-dimensional slice W × S. Project all points of L in the slice orthogonally onto S, and the projected points give the positions of the atoms (see, e.g. Marjorie Senechal’s Quasicrystals and Geometry).
- Another popular model is called inflation, which is a higher dimensional (and geometric) analogue of what computer scientists call a grammar. A grammar consists of several rules for replacing individual letters with strings of letters. For example, the grammar defined by a → a, a → bab generates strings from a of the form b…bab…b, with equal numbers of b’s on both sides of the a. Notice there is no rule for replacing b’s: in inflation, many sets of substitution rules have at least one rule for each letter. One can go beyond strings of letters to geometric shapes, replacing a shape (or tile) with some configuration of several tiles, and then “inflating” the configuration until the new tiles are the same size as the original ones, and repeating (see, e.g. Michael Baake and Uwe Grimm’s Aperiodic Order I: A Mathematical Invitation).
Such models give us visualizations of what a quasicrystal is. Cognitive scientists claim that we think in metaphors, and that is what makes these definitions valuable.
Having a lot of definitions suggests that a field is new and practitioners have not settled on a definition to inflict on students. We can ask mathematicians for a new Fundamental Theorem, but it is possible that the situation is more complicated. For example, in 2000, Jeffrey Lagarias asked eleven questions about the relations between various definitions. At the 2014 IUCr Congress, Lorenzo Sadun (with Johannes Kellendock) announced that the answer to Problem 4.10 was “no”, suggesting that the world is a little more complicated than anticipated. (See also Lagarias’s short paper on these definitions. I’d like to thank Lorenzo for helping me with some of these definitions.)
If we have several definitions, and if they are not equivalent, then we have a problem. Outside of encouraging food fights, definitions provide a methodological anchor. But it would be helpful if we could settle on what the subject of our endeavor is.
Often (as in classical crystallography), the goal is a single widely usable definition. In logic, a notion is robust if it is expressible in many different but straightforward ways. In mathematics, a representation theorem says that two different notions are actually equivalent. The Fundamental Theorem of [Classical] Mathematical Crystallography is such a representation theorem – and a particularly important one, since it connects a specification with a model. So some of us may hope for a demonstrably robust notion, whose robustness can be demonstrated by a representation theorem.
But that may not be in the cards. Sometimes the universe is messy, and what we really need is a catalog. We may then hope that organizing principles will arise out of the mounds of data, like quarks arising from the heaps of subatomic particles in the early 1960s.
Either way, we don’t seem to be there yet. And that means that the paradigm shift presided over by Shechtman, Janssen and Janner is still underway.
The Twenty-third Congress of the International Union of Crystallography met in downtown Montreal, one or two kilometers south of McGill University, whose medical school peeks over the stadium towards downtown:
Downtown Montreal sits right on the St. Lawrence River, and amidst the tall buildings there squats the Palais des Congres…
…whose southern entrance opens to a small park…
…a few blocks from Rue Wellington (sorry, as an Anglophile, I had to mention that).
Not being good at estimates, I don’t know how many people attended, but there were enough people to fill a very large auditorium and keep eight parallel sessions going through the last (seventh) day – the IUCr estimates over 2,200.
Like many attendees, I cherry-picked events, but I did have a revelation. Suppose you go to a conference on a sprawling, multidisciplinary field, where the plenary talks focus on The Latest Hot Topic (more about that below, and in the next post), and where there are approximately a zillion parallel microsymposia on various subfields. Where would you go to get a general impression of what is going on?
To the poster sessions, of course.
Posters and exhibits were relegated to a large multipurpose room tucked beneath the multi-story complex that makes up the conference space. To someone used to mathematics conferences, where the exhibits are dominated by publishers hawking monographs and textbooks, the IUCr exhibits seemed to consist largely of software and hardware. Almost like a (gasp) trade show. There was, so I heard (but I did not see it on exhibition), one book on display (the Little Dictionary of Crystallography, which quickly sold out). And surrounding the exhibits were hundreds of posters.
Poster presenters are an odd lot. My father preferred presenting posters over giving talks: he wasn’t convinced that people actually listened to the talks (!). And with a poster you could have a one-on-one conversation with passersby – which, as educational psychologists will tell you, is a more reliable way to impart information that talking at lots of people from a distance. Another thing about posters is that screening committees are less picky: you can take risks and talk about odd topics without getting hurled out the door. The result is that some posters talked about funky or fun stuff that would never have made it into a microsymposium. And considering how many graduate students present posters at a meeting this large, you can get an impression of what is going on at major research centers simply by walking along the aisles of posters.
Returning to the talks, especially the plenary and keynote addresses, Quasicrystals were what’s hot. Dan Schechtman spoke about Quasicrystals – A Paradigm Shift in Crystallography. “Paradigm shift” refers to Thomas Kuhn’s model of scientific progress. Normal science is conducted under a reigning paradigm, and every once and a while, a paradigm’s inadequacies become manifest, and there is a shift to a new and more adequate paradigm. Paradigm shifts can be unpleasant to live through: think of Ignaz Semmelweis, who proposed washing hands before surgery to remove contagions, and who was dismissed from his post, harassed by his colleagues, and committed to a mental asylum, where he was beaten to death by the guards. Schechtman’s opponents were more civilized and he weathered the storm (which appeared to have lasted about a decade) and ultimately won a Nobel prize.
Schechtman mentioned four things a scientist needs to effect a successful paradigm shift.
- One has to be very good at transmission electron microscopy (“TEM”). Schechtman focused on one particular skill that made his discovery possible. It takes many years to become any good at TEM, and few succeed. This may be generally true: sociologists and psychologists are increasingly remarking on the need for a great skill to accomplish a great deed: a great idea, in of itself, is often not enough.
- One needs tenacity. Schechtman told the story of a student who saw a quasiperiodic diffraction pattern before he did, recognized its significance, but (possibly reflecting on Semmelweis’ fate) said nothing. Schechtman said that an odd observation may be an artifact (it probably is), but you will never know if you don’t pursue it. Schechtman also mentioned resilience, which is not quite the same thing. (On the other hand, there is the tenacious and resilient example of Louis Agassiz – the fellow who discovered ice ages and later showed great tenacity and resilience as the last great holdout against evolution.)
- Believe in yourself. Schechtman actually had an arch-enemy, Linus Pauling, who was convinced that quasicrystals were classical crystals with very large units. But Schechtman persevered. There are two ways of looking at this. One is that this is the basic advice for aspiring writers: you know you aren’t a real writer until you can paper your wall with rejection slips (Lord of the Flies, which won Golding a Nobel, got 20 rejections, as did Frank Herbert’s Dune, while Harry Potter and the Philosopher’s Stone garnered only sixteen – and A Wrinkle in Time got 26 rejections while Gone with the Wind got 38).
There are two things that Schechtman did not mention: recognition and communication.
- When I was a graduate student at UCLA, Paul Erdös (one of the great eccentrics in mathematical history) visited us, and told us the following story (which I have not checked to see if it is true). Before Marie Curie’s work on radioactivity, workers in a lab observed that if you left pitchblende and undeveloped film together, the film would get fogged. In reaction, the lab workers put a rule in their books: pitchblende and undeveloped film should not be stored together. Henri Becquerel later observed the same phenomenon and, paying more attention, told his co-workers (the Curies) about it. From Alexander Fleming’s chance observation of penicillium’s chemical warfare against germs to Charles Goodyear dropping rubber on a stove, some of the greatest discoveries were made by people who were paying attention.
- In the mid-Nineteenth century, the physicists knew that they needed an algebra of three-dimensional space. In fact, William Hamilton knew that they needed an algebra of umpteen dimensional space (and Hamilton’s quaternions did not fit the bill). Hermann Grassmann developed such an algebra, but being of a philosophical bent, communicated his discoveries in books that Hamilton and other physicists were unable to decipher. Decades later, Willard Gibbs independently developed a similar algebra – which we now call vector algebra – and Gibbs was much better at marketing: he delivered his discoveries in bite-sized articles aimed at the audience he had.
And as far as reception goes, it may be wise to follow the advice from the Yes, Prime Minister episode, The Ministerial Broadcast. When a politician is to announce something routine, the opening music should be Stravinsky, the politician should wear a modern suit, and the background should feature abstract art. When a politician is to announce something truly revolutionary, the opening music should be Bach, the politician should wear a dark suit, and the setting should be oak paneling, leather volumes and Eighteenth century portraits.
Schechtman was merely the most notable of the speakers on aperiodicity. Marjorie Senechal gave a keynote address on Mathematical Crystallography in the 21st Century, and started by saying that major areas for future research include folding and flexing, diffraction and imaging, superspaces, symmetry, self-assembly and self-organization, and mapping the aperiodic landscape. She then focused on aperiodic structures from two points of view. From the point of view of the final structure, she said that under certain conditions, a Delaunay set must periodic, and asked if there was a (nice) set of conditions for a Delaunay set to have a discrete diffraction pattern. Then from the point of view of the formation of the structure, she observed that icosahedral shell structures of less than two thousand or so atoms are more stable than cuboctahedral structures, and asked how the transition from icosahedral to cuboctahedral takes place. She concluded by mentioning the Defense Advanced Research Projects Agency (DARPA), which frequently posts “challenge” problems. In 2007, DARPA posted 23 challenge problems for mathematicians (which for some reason DARPA took down, but Professor Vasilios Alexiades of the University of Tennessee archived the list), and Challenge Number Eleven was:
- Optimal Nanostructures. Develop new mathematics for constructing optimal globally symmetric structures by following simple local rules via the process of nanoscale self-assembly.
Senechal said that she asked someone at DARPA what all these terms meant, and was told that DARPA hadn’t assigned specific meanings to the terms. So the challenge is somewhat open-ended.
Officially, the big event was the Ewald Prize, which was awarded to Aloysio Janner and Ted Janssen for developing the “superspace model” of quasicrystals, and that leads into my next (curmudgeonly) posting…
The Commission will meet on August 11, 12:15, in room 441.
Recall from the 17 August 2013 post that Luis Bettencourt, David Kaiser, Jasleen Kaur, Carlos Castillo-Chavez, and David Wojick had constructed and tested a model of emergence, and the results suggested that for an emerging field, recruitment of new participants is critical.
When recruiting, there are two audiences one may have in mind.
- Of course, there are students. Students are energetic, ambitious, and have yet to develop that conservatism that keeps middle class academics in their own fields.
- There are also colleagues. Colleagues usually do not change fields unless impelled to do so (by necessity or by wanderlust). Colleagues know how the game is played, and they bring expertise.
These are two different audiences. I don’t know how much is known about recruitment of students versus colleagues (perhaps very little, as “emerging fields” as a branch of the sociology of science is itself an emerging field), so all I can do is engage in armchair theorizing. The advantages and disadvantages of joining an emerging field can be assessed differently by students and researchers.
- A new field is an opportunity. Economists and ecologists have long observed that when individuals find a new environment they can exploit, they can more readily succeed than they would in established terrain. In a new field, there is less competition, there are basic and tractable problems to be solved – and considerable rewards for doing so.
- A new field is a gamble. Most new businesses fail, most revolutions fail, and probably most new academic fields implode; we remember the successes while the failures are quietly forgotten and rarely make it into the history books. Some do succeed, but fail to deliver on their promises. Even successful ventures may not produce timely success, and the original revolutionaries may not live to see the success of their revolution.
Let’s consider two issues: attraction and access.
Mathematical crystallography faces the same problem that small-town boosters have: how to attract new enterprise. We are all familiar with Chamber of Commerce boosters (the old-fashioned non-ideological kind) who appeared in the business section of the newspaper, talking up the potential of the town. That’s us. So how do we attract enterprise?
It pays to advertise, or so the poem goes. In academia, one can advertise with accessible, semi-popular works. The power of advertising may be over-rated: in assessing the impact of Richard Feynman’s 1959 speech, There’s Plenty of Room at the Bottom in inspiring nanoscience, Chris Toumey found that while many people later remembered Feynman’s article being discussed, there was little documentable evidence of impact prior to the 1980s.
Still, books like Herman Weyl’s Symmetry, Marjorie Senechal and George Fleck’s Shaping Space, and John Conway, Heidi Burgiel and Chaim Goodman-Strauss’s Symmetries of Things may be useful in attracting students to the field.
Papers might also be useful advertising, although the ones that come to mind look more like materials for recruiting colleagues. For example, in 2003, Omar Yaghi et al published a manifesto, Reticular synthesis and the design of new materials, advocating the development of a design process to facilitate the synthesis of novel crystals. On the other hand, in 2008, Massimo Nespolo published a manifesto, Does mathematical crystallography still have a role in the XXI century? which introduced readers to some of the active research areas. And I have just published an article, Prospects for mathematical crystallography, allied to postings in this website.
One possible selling point is that mathematical crystallography is an interdisciplinary field. Unfortunately, this could be a liability. Interdisciplinary fields have been all the rage for some time, but institutional support tends to be a bit thin. In 1995, the National Research Council issued a report on Mathematical Challenges from Theoretical / Computational Chemistry, which addressed institutional obstacles to recruiting for a closely related interdisciplinary field:
- For faculty, the institutional support and reward structures are designed for within-disciplinary efforts. For example, faculty are evaluated by departments, which often focus on their own disciplines. In addition (though the report did not go very much into this), internal funding is often made available through departments, and credit for external funding is usually assigned to departments.
- For students, the curriculum is often determined by departments, usually independently of each other. A student in one department could face a long sequence of prerequisites before being prepared to take a relevant course in another department.
The NRC did not mention another problem: external funding agencies like their grant proposals to go into the correct pigeonhole, which is a problem for interdisciplinary programs. So by all means, talk up the interdisciplinary aspects of mathematical crystallography. But we may have to support some institutional reform.
This brings us to a major obstacle: access. Chemists who want to join need to learn physics and mathematics, physicists who want to join have to learn chemistry and mathematics, and mathematicians who want to join need to learn chemistry and physics. I am most familiar with problems learning mathematics, so let’s look at those.
In 1992, Mattel’s Barbie doll said that Math class is tough. Mattel got in trouble with the American Association of University Women because Barbie’s audience was little girls, but there is a feeling that mathematics is an unusually difficult subject. There are a number of theories as to why.
- One theory is that mathematics is a foreign language many people are too impatient to learn. Learning any language takes time and effort. (It doesn’t help when popular culture decrees that a person either has the math gene – in which case everything is easy – or they don’t, and no amount of work will help.)
- There is a theory that mathematics is an eccentric activity our savannah ape ancestors felt no adaptive pressure to master (although Keith Devlin argues that our ancestors felt a strong adaptive pressure to develop linguistic capacities that evolved into mathematics).
- There is a theory that vast numbers of people suffer from mathematical deficiencies due to poor education, poor parenting, or (of course) television
- There is a theory that mathematics is an alien landscape that excites phobias in susceptible people.
- And there is the theory that the primary (or most readily addressed) problem is how mathematics is taught.
There are even a few people who claim that math is not hard, or at least shouldn’t be. But considering that mathematics has a reputation that chemistry and even physics does not, participants in a mathematical field need to think about how to make their field accessible to novices.
Meetings (like the upcoming IUCr 2014 meeting; see the previous entry for details) are invigorating and fun and provide opportunities to meet and recruit people, but the work of learning a new field is a more lonely business and it involves a lot of reading. We have a strong interest in having a lot of accessible material. And accessibility is a problem in academia.
Etymological dictionaries tell us that arcane is a descendent of the Latin arcere, to contain or maintain, to keep or ward off, and perhaps to the Greek arkein, to keep off. It is associated with the Latin arcana, or mysterious secrets. These are all members of the family of words led by the Latin arca, or ark, as in Noah’s Ark and the Ark of the Covenant.
As a new word, arcane bubbled up in the Sixteenth century, in the midst of the explosion of books created by Gutenberg’s press. Books on just about everything suddenly appeared, and they sold. Just as the Internet not only made everything available to everyone, and made a virtue of universal access, so the Gutenberg revolution made all knowledge available to any plowman able to afford a book.
But some works seemed to remain out of reach, hence the notion of arcane works. Perhaps the printing press was partially responsible for the Plato boom that inspired Renaissance scientists: Plato was a natural novelist (see, e.g., his great literary invention, Atlantis). Perhaps the printing press was partially responsible for Aristotle’s poor reputation in that era: the Complete Works are a jumble of often unintelligible notes and fragments of dubious provenance. And Aristotle was hardly unique. As Great Works became available to the Common Man, common men found many of them inaccessible.
Communication theorists tell us that arcana can serve a purpose. I don’t mean unintentional arcana, like a bunch of moldy papers somehow associated by a major philosopher. I mean (often unconsciously) intentional arcana, like books by German metaphysicians we could name. Consider this grumpy passage by the greatest of them all, Immanuel Kant. In his Prolegomena to Any Future Metaphysics, a sort of Kant-for-Dummies-by-Kant-Himself, Kant writes that his major work, the Critique of Pure Reason
… will be misjudged because it is misunderstood, and misunderstood because men choose to skim through the book, and not to think through it – a disagreeable task, because the work is dry, obscure, opposed to all ordinary notions, and moreover long-winded. |
Some communication theorists might detect a little pride in that sentence. Still,
I confess, however, I did not expect, to hear from philosophers complaints of want of popularity, entertainment, and facility, when the existence of a highly prized and indispensable cognition is at stake, which cannot be established otherwise, than by the strictest rules of methodic precision. |
There are two interesting points about this passage. First, Kant was irritated that philosophers, much less educated laymen, were unwilling to invest the vast amount of time and energy required to read the Critique. But second, he did write the Prolegomena after all, and that was consistent with what some commentators have claimed about Kant: he had an agenda, and that agenda required readers and students. Kant started his introduction to the Prolegomena with the words, “These Prolegomena are destined for the use, not of pupils, but of future teachers …”; perhaps concerned by the criticism of his colleagues, he wanted to make sure that teachers, at least, understood what he was trying to say.
Academics aren’t the only ones who make the difficulty of the material into a gatekeeper, but that is one of our bad habits. Especially when our goal is accessibility. It all boils down to who the audience is. New Yorker archivist Joshua Rothman compared journalists, whose text is relatively undemanding because it is intended for a mass audience, to academics.
In academia, by contrast, all the forces are pushing things the other way, toward insularity. As in journalism, good jobs are scarce—but, unlike in journalism, professors are their own audience. This means that, since the liberal-arts job market peaked, in the mid-seventies, the audience for academic work has been shrinking. Increasingly, to build a successful academic career you must serially impress very small groups of people (departmental colleagues, journal and book editors, tenure committees). Often, an academic writer is trying to fill a niche. Now, the niches are getting smaller. Academics may write for large audiences on their blogs or as journalists. But when it comes to their academic writing, and to the research that underpins it—to the main activities, in other words, of academic life—they have no choice but to aim for very small targets. Writing a first book, you may have in mind particular professors on a tenure committee; miss that mark and you may not have a job. Academics know which audiences—and, sometimes, which audience members—matter. |
But mathematical crystallographers are not trying to fill a niche. We are trying to get people involved (or if you prefer, we are trying to create an array of niches). That means that we should be writing papers and books for as wide an audience as possible. So here are some “best practices” we probably should engage in:
- Papers should be self-contained. In an interdisciplinary field, one’s readers may be unfamiliar with some jargon and some concepts. It may be useful to define them in the paper if that does not take up too much space. Of course, sometimes that would be distracting, so another thing one needs is:
- Papers should have primary references. Where does the novice reader go to find out what actions, entropy, and carboxyl groups are? It takes very little space to give a citation to a general reference known to be accessible.
It may be a good idea to imagine a graduate student when writing a paper.
Every three years, the International Union of Crystallography holds a Congress and General Assembly. The first was in 1948 at Harvard University in Cambridge, Massachusetts, and the 23rd will be held this summer from August 5 to August 12 in Montreal, Canada.
The entire meeting looks rather large – at the 2011 meeting in Madrid, there were 2,655 “scientific participants” from 73 countries, resulting in 490 oral presentations and 1,550 posters – and this meeting will probably be comparable.
- Registration opens on August 4.
- The workshops are on August 5, and the Ewald Prize will be awarded to Aloysio Janner and Ted Janssen for their work on aperiodic crystals.
- The keynote and plenary speeches, microsymposia, software fayres, poster sessions, and various commissions will be held from August 6 to August 12.
- The Gjønnes Medal in Electron Crystallography will be awarded to John Steeds and Michiyoshi Tanaka on August 12.
Here are some events that may be of interest to the mathematically inclined:
- As of May 31, there are four plenary lectures listed.
- Dan Schechtman, who received a Nobel Prize for discovering quasicrystals.
- Juan Garcia-Ruiz will go From the Crystal to the Rose: The Route to Biomimetic Self-assembled Nanostructured Materials.
- Dave Bish’s talk does not look at all mathematical, but as a science fiction fan, I have to report that he will talk on The First X-ray Powder Diffraction Measurements on Mars.
- Jianwei Miao will go Beyond Crystallography: Coherent Diffraction Imaging and Atomic Resolution Electron Tomography.
- As of May 31, I counted 31 keynote speeches, not counting the two Gøonnes Prize lectures. A few heads-up for the mathematically inclined or the crystal engineer:
- Crystal Engineering and Applications of Functional Metal-Organic Frameworks by Xiao-Ming Chen on August 7.
- Mathematical Crystallography in the 21st Century by Marjorie Senechal on August 8.
- Workshops consist of sessions of extended presentations by experts, and cost $ 25 to $ 60 … and space is limited, so make reservations asap. They are all being held on Tuesday, August 5. These seem to be largely on software.
- Introduction to Aperiodic Crystals.
- Hands-on Tutorial on Crystal Structure Prediction using the USPEX Code (bring your laptop, it says).
- There will be two workshops on the SHELX program “for the determination of small (SM) and macromolecular (MM) crystal structures by single crystal X-ray and neutron diffraction.”
- Advanced Structure Refinement Techniques, Disorder Modeling, and CIF Preparation with OLEX2, a “simple to use program containing everything you need to solve, refine and finish small-molecule crystal structures.”
- There are several ancillary “commission meetings” during the conference, including an Open (i.e., everybody is invited) Commission Meeting on Mathematical and Theoretical Crystallography, which is scheduled to meet on August 11 during lunchtime – 12:15 – 13:45 on the fifth floor in room 441. Come and bring a colleague – or even better, a student!
- Recent developments are presented in 112 microsymposia and in poster sessions. Here are some microsymposia whose descriptions suggest substantial mathematical content or opportunities.
- 2. Recent Advances in Quasicrystal Research, organized by An Pang Tsai and Janusz Wolny, on August 6.
- 31. In-situ XRD: Parametric and Symmetry Constrained Refinement, organized by Robert Dinnebier and John Evans, on August 7.
- 33. Symmetry Constraints in Magnetic Structure Determination: Experiment and Theory, organized by Branton Campbell and Mois Ilia Aroyo, on August 8.
- 34. Crystals and Beyond, organized by S. I. Ben-Abraham and Jeong-Yup Lee, on August 8.
- 62. Symmetry and Isomorphism in Material Design and Crystal Growth, organized by Tatyana Bekker and Antoni Dabkowski, on August 9.
- 72. Methods, Algorithms and Software for Powder Diffraction, organized by Ryoko Oishi-Tomiyasu and Jon Wright, on August 10.
- 95. Symmetry and its Generalisations in Science and Art, organized by M.A. Louise de la Penas and Emil Makovicky, on August 11.
- 96. New Computational Approaches to Structure Solution and Refinement, organized by Richard Cooper and Lukáš Palatinus, on August 11.
- 104. Crystal Structure Prediction and Materials Design, organized by Roman Martonak and Tian Cui, on August 12.
- 112. New Approaches to Crystal Structure Prediction, organized by Graeme Day, on August 12.
Of course, in addition to the microsymposia, there will be approximately five million posters, including mine. Drop by and browse.
- There will also be a Software Fayre where software developers can demonstrate their software. While mathematical crystallography may influence crystallography in developing theory, it seems likely that the most impact will be in software.
About Montreal…
Montreal is an island in the St. Lawrence River with a population of about two million people. It was inhabited as early as 4,000 years ago, but during the Sixteenth century, all the people disappeared (!). The French started settling the place in the Seventeenth century, but it was surrendered to the British in 1760. It lies in the province of Quebec, and is now the second largest city in Canada.
Major academies in Montreal include Concordia University, Université Laval, McGill University, the Université de Montréal (including its affiliate, the École Polytechnique de Montréal), the Université du Québec à Montréal (the Ecole de technologie superieure) is affiliated with the university), and the Université de Sherbrooke.
The deadline for reserving accommodations is “[u]ntil blocks are sold out or June 25, 2014, whichever comes first,” and since this is a tourist season, blocks may not last until June 25 (and affordable airplane tickets may be difficult to find).
Summers are, according to Wikipedia, hot and humid, with temperatures ranging from 63 F to 77 F (17 C to 25 C), with mean temperature 70 F (21 C), 4 inches (100 mm) of rain a month, and relative humidity of 79 %. In general, sunny with occasional storms. Despite last year’s story on Montreal in July, High heat and humidity warnings bring serious health threat, to a Florida resident like me it sounds comparatively pleasant.
For future reference …
The 24th Congress and General Assembly will be held in 2017 in Hyderabad, India, capitol of Andhra Pradesh, with a population of nearly eight million people, and home to several academic institutions, including the Birla Institute of Technology and Science, Pilani – Hyderabad, the English and Foreign Languages University, the University of Hyderabad, the Indian Institute of Technology Hyderabad, the Jawaharlal Nehru Technological University of Hyderabad, and Osmania University.
Mapping the Community VIII: Infrastructure
I am starting up this blog roughly where I left off. I am still working on material that showed up in the paper, Prospects for Mathematical Crystallography. Despite the fact that the paper discusses infrastructure and access, I think I will go ahead and post on those two subjects anyway: they are important for developing an emerging or re-emerging field. I will then move on to crystal prediction, which I just started in the paper, but which I think should be reviewed in detail, primarily because that is my own field.
Science and mathematics history books tend to devote little attention to the infrastructure of mathematics and science. The traditional view is that what is important are the great discoveries, and the great discoverers who made them. Lately, science and mathematics historians have grown more interested in the process of discovery, and that includes a close look at how discoveries take place. For some of the natural sciences, this entails obvious infrastructure. For example, even before the invention of the telescope, astronomers used an array of observational devices, which cost money. These devices ranged from little astrolabes to immense sextants, not to mention observational towers. And while the telescope put a relatively cheap instrument into the hands of the masses, Isaac Newton’s reflecting telescope was an omen of the incredibly expensive telescopes to come.
Even mathematics could create a demand for this kind of infrastructure: just about everybody nowadays uses computers for something.
But there was a need for another kind of infrastructure. Philosophers and scientists, as well as artists and writers, want to go where things are happening because that’s where people who want to do things are going. In Medieval Europe, that tended to be the big monasteries; now, it’s the big universities and big corporations, which are concentrated in cultural centers.
- Scientists and engineers tend to be employees of institutions, especially corporations and educational institutions. Scientists and engineers not only need the expensive equipment required by modern science – and engineers have always needed expensive equipment, ever since Imhotep built the Djoser pyramid – but they also need libraries and colleagues. Also, many scientists and engineers support themselves by marketing their results, which means publishers, often integrated with academic institutions.
- Artists, writers, and philosophers often view themselves as freelancers, but considered as an economic activity, most visible art these days (on products from book covers to billboards) is commercial art, and much of the text read these days (on products from greeting cards to computer manuals) is commercial text. Poetry is a multi-billion dollar industry: just turn on the radio (most rock stars are independent contractors associated with a small number of record labels), and philosophers follow ancient traditions when they hire themselves out to publicity machines or join senior management. Some artists (e.g. sculptors and architects) need materials, and all need to interact with colleagues. And all need someone to market their works.
All fields need infrastructure to build and maintain lines of communication and collaboration. Recalling from the 17 August 2013 post that recruitment is critical for new fields, the infrastructure must make a field attractive and accessible. That means introductory books and expository articles as well as workshops and tutorials, not to mention special topics courses and course modules. And in the Twenty-first century, software.
Beyond the colleges and universities themselves, there are several academic organizations with a particular interest in crystallography. These organizations can provide forums for events like workshops and tutorials, as well as assist in finding resources for developing and / or marketing books, articles, course materials, and software. Some of them also provide mechanisms for people seeking jobs (always a concern). Such organizations include:
- The American Chemical Society publishes 44 journals and has over 160,000 members. The ACS maintains the SciFinder, the former Chemical Abstracts.
- The American Mathematical Society publishes 14 journals and has nearly 30,000 members. The AMS maintains MathSciNet, the former Mathematical Reviews, one of the two major databases of mathematics publications.
- The American Physical Society has over 50,000 members, and. It has a Division of Chemical Physics and a Division of Materials Physics.
- The Deutsche Physikalische Gesellschaft (German Physical Society) has over 60,000 members and publishes two journals.
- The European Mathematical Society, together with the Liebniz Institute for Information Infrastructure and the Heidelberg Academic of Sciences, produces zbMATH, the former Zentralblatt für Mathematik und ihre Grenzgebiete, is one of the two major databases of mathematics publications.
- The International Union of Crystallography, a consortium of 42 national crystallographic associations, as well as three regional associates and two scientific associates. (There are also connections with six other organizations). The IUCr publishes books and journals as well as organizing meetings and maintaining forums for communications and obtaining resources. And the IUCr organizes campaigns like the International Year of Crystallography for education, recruiting and generating popular support.
- The Materials Research Society was founded in 1973 and has about 16,000 members.
- The Mathematical Association of America is primarily concerned with undergraduate education (just as the National Council for Teachers of Mathematics is concerned primarily with K-12 education).
The Society for Industrial and Applied Mathematics has 14,000 members and publishes 16 journals. It also sponsors “Special Interest Activity Groups” in several areas, including Mathematical Aspects of Materials Science.
There are many other organizations, most notably the American Association for the Advancement of Science, which publishes one of the two likely most prestigious science journals in the world, Science (the other being Nature).
The scientific community is huge, and just reading journals and attending meetings can create a narrow view of what is going on in one’s own subject. Sometimes one needs a broader perspective of one’s own field. And occasionally, when working on a project, it is more convenient to use someone else’s invention rather than reinventing the wheel. For these and other reasons, it is often convenient to have a database of publications at hand. All these databases have quirks. These databases are expensive to maintain, so some are available only by subscription (and occasionally very expensive subscription at that). If you go to the public links of some of these databases, you may find only limited or no functionality for non-subscribers. Anyway, here are some of the major ones:
- For crystallography, one might first turn to chemical and physical databases. The American Chemical Society maintains SciFinder, the former Chemical Abstracts, which has some statistical tools. The Institution of Engineering and Technology maintains INSPEC, which contains the former Physics Abstracts (in collaboration with the American Institute of Physics) and the former Science Abstracts (in collaboration with the British Science Association, the Institute of Physics, the Institution of Civil Engineers, and the Royal Society).
- In mathematics, the two primary databases are MathSciNet, formerly the Mathematical Reviews, maintained by the American Mathematical Society, and its European competitor and collaborator; and zbMATH, maintained by the European Mathematical Society, the FIZ-Karlsruhe – Liebniz Institute for Information Infrastructure, and the Heidelberg Academy of Sciences. Both these databases survey thousands of refereed journals and thus provide a fairly comprehensive picture of the mathematical community, but zbMATH has better statistical tools (although it can’t compute impact factors).
- The most popular overall database is probably the Web of Science, which is maintained by Thompson-Reuters, and is part of the Web of Knowledge. The core of this database is the former Scientific Citation Index, and this is the primary source of the notorious impact factors we all see at evaluation time. Unfortunately, the Web of Knowledge tends to regard itself as a private club, listing articles only from those publications it condescends to notice, and as a result its coverage is spotty (and abysmal outside of the natural sciences) – for this reason, while its statistical tools are snazzy, Web of Science impact factors should not be taken too seriously.
- At the opposite extreme from Thompson-Reuters is WorldCat, maintained by a consortium of over 10,000 libraries called the Online Computer Library Center. When they search everything, they do mean everything: when I searched for “crystal structure”, the first entry was Indiana Jones and the Crystal Skulls. Google also has a wide net, for items listed in Google Scholar; Google also has entire books (and teasers) on Google Books, although often the best descriptions of books appear in Amazon.
- The U.S. government also has resources. The Department of Energy’s Office of Scientific and Technical Information maintains Sci-Tech Connect and WorldWideScience.org. Several U.S. federal agencies collaborate on Science.gov – “Your Gateway to U.S. Federal Science”. (The recent demise of the Department of Energy’s Science Accelerator makes one wonder about the longevity of these operations.) Of course, if it’s books you are after, you should check the Library of Congress.