A new research paper proposes an algorithmic approach for developing new materials, and some of them might be useful in 3D printing.
The research undertaken by the University of Liverpool could be quite profound in the future. They seem to have developed a way to predict the structure of materials given only the atoms that comprise the molecules.
The structure of a material largely determines its physical properties. For example, a substance with a complex crystalline structure could exhibit rigidity and strength, while a flexible material would have an entirely different molecular structure.
In additive manufacturing operations, particularly in the metal domain, we frequently find engineers tuning their 3D printers to produce prints with proper crystalline structure. That’s how they guarantee the strength of the parts.
Today this is done by extensive testing and tweaking of speeds, temperatures, humidity and other factors.
But what if this could be accomplished in an entirely different way? What if you could design a material with atoms directly?
The researchers explain what they’ve developed:
“Here we show that the structure of a crystalline material can be predicted with energy guarantees by an algorithm that finds all the unknown atomic positions within a unit cell by combining combinatorial and continuous optimization. We encode the combinatorial task of finding the lowest energy periodic allocation of all atoms on a lattice as a mathematical optimization problem of integer programming, enabling guaranteed identification of the global optimum using well-developed algorithms. A single subsequent local minimization of the resulting atom allocations then reaches the correct structures of key inorganic materials directly, proving their energetic optimality under clear assumptions.”
What does that mean? They provide this statement:
“This formulation of crystal structure prediction establishes a connection to the theory of algorithms and provides the absolute energetic status of observed or predicted materials.”
In other words, one can compute what a material will do.
University of Liverpool Professor Matt Rosseinsky said:
“Having certainty in the prediction of crystal structures now offers the opportunity to identify from the whole of the space of chemistry exactly which materials can be synthesised and the structures that they will adopt, giving us for the first time the ability to define the platform for future technologies.”
Now, let’s consider the implications of this development. First, ask the question, “how many ways can atoms be put together?”
The answer is, “a lot”.
Testing new substances physically to find optimal materials would be incredibly time consuming and would never approach the full spectrum of molecular possibilities. But if you were doing so computationally, there are no limits. You can find materials as long as you through CPU power at the problem.
The researchers say their work will open “path to overcome the combinatorial explosion of atomic configurations.” Their prediction is that this work could be used to help replace scarce or toxic elements with new equivalents that are more easily produced and used.
University of Liverpool Professor Paul Spirakis said:
“We managed to provide a general algorithm for crystal structure prediction that can be applied to a diversity of structures. Coupling local minimization to integer programming allowed us to explore the unknown atomic positions in the continuous space using strong optimization methods in a discrete space.
Our aim is to explore and use more algorithmic ideas in the nice adventure of discovering new and useful materials. Joining efforts of chemists and computer scientists was the key to this success.”
This is an important development for chemistry and material science, and it may possibly be used in the future to identify useful materials for 3D printing. The technology has many requirements that are quite different than conventional uses, and it may be possible to search for 3D printable materials using this approach.