Amidst all the excitement over carbon nanotubes and graphene, it is easy to forget that most engineering happens with metals, and almost always with alloys. There are probably about 50 elements that might be used in alloys (the non-radioactive metals plus a few non-metals like phosphorus and carbon), and each might be present in quantities from a few ppm up to 99.99%. This means that there are trillions of possible alloys, even if you limit yourself to only half a dozen ingredients, and use cheap(ish) metals as the main ingredients.
There are also umpteen different factors that will affect the properties of any given alloy, such as rate of cooling, various heat treatments, and hot or cold working. This gives you many more effectively different alloys.
I would guess that perhaps a few tens to a few hundreds of thousand alloys have been studied over the centuries, and many useful ones have been discovered. However, this leaves trillions more to be tried. Attempts have been made to predict alloy properties ab initio, but these attempts generally fail, or rely on empirical observations of a small range of alloys. Real alloys often behave completely differently from the predictions.
As a biologist, I am used to "fishing trips" involving vast combinatorial libraries. You want an aptamer that will bind X? Well, you just start with a library of a few billion aptamers and find the ones that work. Similar approaches are used to create novel antibodies and even enzymes.
Materials scientists, however, don't seem to have gone in for this approach. Therefore, MaxCo. proposes developing the Alloyotron - a system for searching vast numbers of alloys for useful properties.
The Alloyotron systematically creates small (say, 0.1 gram) batches consisting of powdered elements, with a huge diversity of compositions. Each little mixture is sintered into a pellet using a combination of heat and pressure. Each little sintered pellet, in turn, is held aloft in a jet of inert gas for a few seconds whilst lasers converge on it and melt whatever it contains. It's held there, molten, for a few moments to allow thorough mixing (though some mixtures will partition), and then cooled either rapidly (by another gas jet shooting it into a cold bath) or slowly (by gradually reducing the laser power).
So, the machine is producing a succession of alloy beads, of varied composition and varied cooling rate. Conceivably, they could also be subjected to various additional heat profiles. These beads then drop into a machine that measures properties including hardness, density, thermal conductivity, ductility (by squashing them flat and imaging the resultant shape - more ductile alloys will produce discs; less ductile ones will make flower shapes), Young's modulus and (tricky but doable) tensile strength. Finally, each alloy's melting point (or yield-point) is measured.
All of the above happens automatically, perhaps at the rate of one sample per second. Most of the alloys will be useless, but a tiny percentage of the 30 million alloys analysed during a year will warrant further analysis, and of these a handful will prove to be useful and worth further development and tweaking.-- MaxwellBuchanan, Sep 13 2019 Let us know when you start feeding your machine with the Actinide series ...-- 8th of 7, Sep 13 2019 //the non-radioactive metals plus a few non-metals//-- MaxwellBuchanan, Sep 13 2019 You'd want a larger bar or rod shape for testing tensile strength, maybe a few cm per side.
A small electric furnace with several crucibles/molds might be more practical than the lasers and gas jets, but not as theatrical. Most heat treatment processes take hours, and some take days, so for one sample per second you'd need a massively parallel operation.-- discontinuuity, Sep 13 2019 //You'd want a larger bar or rod shape for testing tensile strength// Now, you see, that's one of the problems with materials science. Ask them to test a sample, and they'll want something big. If they were any good, they'd invent machines for testing the tensile strength of smaller samples.
Unless the sample has a large grain size (admittedly an issue for some alloys), there is no earthly reason why you can't measure the tensile strength of a 1mm, or even 100µm sample. The shape is an issue, but not an intractable one. At a pinch (no pun intended) you can measure shear strength instead, by holding the spherical sample between two plates with almost-a-hemisphere dimples in them and applying the shear force. Shear strength is probably as good an initial measurement as tensile strength.
Re. the crucibles - yes, but gets mechanically complex; things react with crucibles or stick to them.
Re. the cooling rate - agreed, but testing 0.1 vs 1 vs 10s cooling would be a good start. We're not looking to cover every possible alloy/treatment combination - just a better sampling of the trillions of options.-- MaxwellBuchanan, Sep 13 2019 [edit: the annos above appeared while I was writing this]
Such a machine would indeed be useful if it could be built. But, there are many more variables than you mention, and the idea that samples could be tested at a rate of once a second is outrageous.
For example, even the oldest types of tool steel are usually subject to a two stage heat-treatment of hardening and tempering. Newer tool steels come in oil- and air-hardening varieties, the heat treatment process taking substantially longer than one second. Many grades of high speed steel have heat treatments that take several hours.
We know that the properties of steel depend on its crystal structure, but the laser sintering process may make the results entirely unhelpful. It may even produce amorphous steel, with no grain boundaries at all, despite the ingredients leading to a particular structure when mixed in a furnace.
The corrosion-resistant properties of wrought iron are due, in part, to a macro grain structure that would be absent from a 0.1g bead.
Many alloys behave differently and interestingly after work-hardening, such as extrusions or drawn wire, which would again be difficult to test in the machine you describe. Some alloys are precipitation-hardening - the earliest usable aluminium alloys apparently took several days to reach their final strength.
All in all, the brute-force approach to metallurgy seems ambitious, and any variables that can be blindly permuted with ease are probably already exhausted. If you want to create new alloys, the best tool is probably still a microscope.-- mitxela, Sep 13 2019 //the idea that samples could be tested at a rate of once a second is outrageous.// It's not outrageous at all. That's the mindset that has left (metallic) materials science back in the 1950s. In contrast, biologists have figured out how to sequence DNA molecules millions (literally) of times faster and ~10,000x cheaper over the last 30 years.
//heat treatments that take several hours.// Yes, and we won't be able to examine alloy structures that require that (unless, of course, you send a procession of samples, one per second, along a zoned furnace, similar to the baking of bread).
//laser sintering process// I'm not laser sintering. I'm sintering first to make a pellet, then melting the pellet with lasers.
//macro grain structure// Yes, agreed, large-grain- dependent structures won't be accessible.
//work-hardening// Yes, agreed, you could not really do work- hardening (well, you could, quite easily, if these damned metallurgists would stop thinking in terms of anvils and hundred-ton rollers).
//any variables that can be blindly permuted with ease are probably already exhausted// So, to take the example of just mixing any 5 of the 50 or so relevant elements; and with say 5 different percentages for each of the elements, there are about 8 x 10^11 possibilities. I do not believe for one instant that any significant fraction of that repertoire has been explored. The Alloyotron will only scratch the surface, but will be orders of magnitude faster than conventional metallurgists.
I'm not suggesting for an instant that a large-scale analysis like this will be efficient: many of the possible combinations would be rejected by a sensible metallurgist before even being made. But I am suggesting that:
(a) if metallurgists weren't so hidebound, they could produce a machine for massively parallel (or very fast serial) testing of millions of combinations
(b) a useful (though far from exhaustive) subset of conditions can be tested
(c) interesting samples would form the starting point of the detailed analysis and optimisation by real metallurgists.
// If you want to create new alloys, the best tool is probably still a microscope.// No. Microscopes are excellent tools for understanding alloys that you have made, thereby suggesting ways to improve them. I know, because this is my daughter's field of expertise. She has spent her PhD doing very detailed and sophisticated analysis of essentially one alloy. It's good work. But you can't examine - not with an optical microscope, a TEM, an SEM or an atom probe - an alloy that you haven't made.
Incidentally, it's worth re-emphasizing that prediction of alloy structures from first principles is, at present, not possible to any significant degree.-- MaxwellBuchanan, Sep 13 2019 I notice a tendency toward using this for steel. A bad Idea I think. Given the volume and efforts that have gone into steel alloys, I doubt there are any low hanging fruit there. There's already a flavor of steel for practically everything. Even then, unless weight is a major issue, it's often easier to just spec 2x the mild steel rather than 4340 for example.
Where you might find some joy is titanium and other slightly exotic alloys. At the moment, the development of steel is so mature that there are steels with better strength/weight than titanium alloys... so there's likely more opportunity in fiddling around in there.-- bs0u0155, Sep 13 2019 As the properties of most alloying additives are pretty-well understood, skipping broadly down combinations and leaving a gaps to interpolate seems a wise course.-- RayfordSteele, Sep 13 2019 // I doubt there are any low hanging fruit there.// Possibly, but possibly not. The properties of most iron alloys were not deduced a priori, and often vary widely for small changes in the amounts of the other components. It's quite likely that some useful steel alloys remain to be discovered.
//titanium and other slightly exotic alloys.// Quite so.
//the properties of most alloying additives are pretty-well understood// No, they're not. For *common* alloying elements used one or two at a time with *common* main components, the properties of the alloys are known and, to a very limited extent, "understood". For anything outside the current spectrum of alloys, the effect of alloying elements is not really understood and certainly not predictable in most cases.-- MaxwellBuchanan, Sep 13 2019 1 or 2 at a time?
Hardly. Most alloys I deal with have at least 6 or 7, admittedly some of them in trace amounts.
We know what these elements do by themselves when they are subject to the temperatures required. Unless they are chemically combined they will behave similarly in an alloy matrix trial.-- RayfordSteele, Sep 14 2019 (Disclaimer: I failed Engineering Materials at university, so take my comments with a pinch of salt. Or pepper. Or something...) When it comes to work-hardening, tempering, heat- treatments, etc, etc, exactly WHAT happens at the atom and grain level is the question. Once that is understood (some-one correct me if it already is...) this system is a go. In theory, this "small scale" testing should work if you have (at least) 2 grains (to measure grain-boundary properties). Every other property should be able to be "pre-made" in the sample from the outset; being small means things can happen faster during manufacture (no waiting for heat to propagate, for example). The samples (at least some of them) will have to be larger to accommodate larger-grain alloys, but not so big that it can't still be a "high speed" process.-- neutrinos_shadow, Sep 15 2019 That's what I figured. I'm not claiming that this approach will replace good old-fashioned metallurgy. It will give erroneous results for some alloys, and will fail to measure some key properties or to achieve the best structure in some cases. But sheer weight of numbers mean you'll get a few interesting and unpredictable leads.
It's the same in molecular biological "fishing trips" that produce massive datasets (such as environmental sequencing). The data is generally not as good as you'd get from bespoke experiments; you miss a lot. But give me 30Gb of moderately trashy sequence data and I'll guarantee to find some interesting things in it, and then those are the things you follow up on.-- MaxwellBuchanan, Sep 15 2019 I think a key question here is whether alloy properties are scale invariant or not.
Curiously, in biology the answer is yes, no, both and neither - in both directions - a mouse's haemoglobin is exactly the same as that of an elephant's - I'd venture the exact function is performed in both - despite the scaling differences. Meanwhile, assuming that bone constituents are the same in mice and elephants (is that a fair assumption?), it's clear that a mouse's femur has very different operational parameters to those of an elephant's.-- zen_tom, Sep 16 2019 Yes, but the material properties of mouse bone are very similar to those of elephant bone. I think you're confusing intrinsic properties with extrinsic properties; a length of 2x4 is stronger than a pencil, even though they are made of more or less the same material.
Almost by definition, the properties of an alloy will be independent of the size of the sample, as long as the sample is large enough to contain a representative number of crystals.
There _are_ some things that you can't really measure on small samples; for example, critical crack length is often centimetres or more. But you can measure a lot of other properties (and, to a reasonable approximation, derive the CCL from them).-- MaxwellBuchanan, Sep 16 2019 Also you should measure how brittleness and resistivity change as a result of heat work. We use Kanthal heating elements which have to be thrown away after about 200 uses.How the alloy is cooled will be a huge variable in this. For example the alloy that turbine blades are made out of is pretty special, but its properties are vastly more conducive to your aeroplane not crashing in a fiery inferno if it is cooled and pulled out of the melt in the right way so that the turbine blade is a single crystal and hence has very little 'creep' when heated. This is an example where scale may matter: i.e. it's easier to measure 'creep' on a large scale, and also harder (but concomitantly more useful) to get a big thing to be a single crystal than a small thing.-- hippo, Sep 16 2019 [hippo] now there's a coincidence. My No.1 daughter also works on jet engine alloys (currently for the front end, but she did some work on high-temperature back-end stuff).
I would have thought that single-crystal applications were relatively rare. But, I take your point. As I mentioned, this isn't supposed to be a panacea for alloy discovery - just a relatively fast way to trawl through a lot of compositions very fast with the likelihood of finding at least a few interesting things.
And regarding your Kanthal elements - if the sample were small enough, it must shirley be possible to regulate its temperature with a pulsed laser: deliver the heat in short enough pulses that there's no huge thermal gradient (across the very small sample), and measure the temperature by IR emission between the pulses, no?-- MaxwellBuchanan, Sep 16 2019 I saw a thing on TV about making single crystal parts. As I recall, it involved a mould with a spiral path. After pouring, the assembly cooled from the top, and although at first crystalisation was chaotic, individual crystals would compete with each other down the spiral, so only one made it through to the part proper. Very clever.
Since we're making comparisons to molecular biology, I think it might be worth trying to either utilise some order in the screen (the 'dilution series' or 'gradient PCR' approach), or conversely do things at very small scale completely at random (the 'shotgun library' approach).
In the first case, you might prepare stock batches of two or three different molten alloys, then combine them in varying proportions. This allows you to prep a large number of samples varying in one or two ways relatively efficiently, and is probably much easier to e.g. get good mixing of ingredients even with some constituents at low concentration.
In the second case, you might create a significant number of different sub-samples in the same form factor (e.g. all mostly iron, but each with, say, additional 20% base metal or 2% exotic), thoroughly mix them all and then combine into random groups of 5. Then for the interesting ones you'd need to work out what you had by post-trial analysis.-- Loris, Sep 16 2019 [Loris] Ah yes, that sounds familiar - I must have watched the same thing as you-- hippo, Sep 16 2019 Yes, good idea.-- Frankx, Sep 18 2019 Is this a good project for a deep learning algorithm. Given the number of current alloy data points, the computation may spot a pattern unseen by human logic. This S.A.D. machine would be the data sensor to the algorithm's investigation.
One problem is cooking times. It may miss alloys that need a millennia at a certain temperature or condition for the unique properties.-- wjt, Sep 20 2019 That's already been acknowledged, multiple times.
Machine learning might be profitably applicable, but I wouldn't expect it to be easy.
But I want to build this machine now.-- notexactly, Sep 26 2019 Gr. Millennium (singular)-- pertinax, Sep 27 2019 So, I asked my daughter (who is a metallurgist) about this. She agreed it would be possible and that you'd probably find some interesting alloys.
However. The main problem she identified is that different research groups work on specific applications, with very little crossover. So, if your group is working on, say, turbine-blade alloys they are not going to be equipped for (or be interested in) following up on new alloys that are, say, super-hard or remarkably ductile.
There's also a regulatory aspect, at least in aerospace. New companies can spend decades earning the credibility to develop new alloys of a particular type and getting them certified for use. So, if a mass-screening program came up with a completely new alloy, it would not be commercially viable for them to develop it as far as aerospace applications (or, presumably, other safety-critical applications).-- MaxwellBuchanan, Oct 06 2019 Those "problems" make me want to do this even more.-- notexactly, Oct 07 2019 random, halfbakery