RobOT

The Materials Innovation Factory at the University of Liverpool, where Professor Andrew Cooper’s group is based.

The properties of a material in the solid state are determined by how it assembles at the molecular level. We spoke to Professor Andy Cooper and Professor Graeme Day about the work of the RobOT project in developing tools to predict the properties of molecular crystals, which could open up new possibilities in the development of functional materials.

Crystal Engineering: A new level of ‘designability’ A lot of attention in chemistry research over

Organic molecules

the last 10 years or so has been devoted to the development of metal-organic frameworks, a type of framework material that uses metal atoms to link together molecules, usually resulting in a crystalline structure.

While there is a good understanding of how molecules fit together in these frameworks, there are still some drawbacks to existing methods of assembling molecules, a topic central to the work of the RobOT project.

“We had the idea of making more designable crystals,” says Professor Andy Cooper, the project’s Principal Investigator. This work is based on the relatively well-established area of molecular crystal engineering, to which Professor Cooper and his colleagues in the project then applied two further enabling elements. “The first is crystal structure prediction, to predict, from first principles, how these molecules assemble. Then we’re also using high-throughput robotic methods, to more rapidly explore the function space,” he outlines.

The wider goal in the project is to develop a tool capable of predicting how organic molecules will assemble, rather than forcing them to assemble in a particular way. This would enable researchers to identify which molecules might be well-suited to a specific application, and so move away from trialand-error in the development of functional molecular crystals towards design. “We will take a molecule and predict how it packs. If it’s promising we might choose to work on it – if not, then we move on to predict the properties of the next one. So it’s kind of a selection process rather than engineering,” says Professor Cooper. There are multiple ways in which a molecule might pack though, and molecular crystallisation is not an intuitive process, so sophisticated predictive computational methods are required.

“We’ve adopted an approach distinct from the chemical, rules-based approach. The benefit is that if you get it right, then it’s effectively generic, and can be used to predict

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an enormous array of structures,” explains Professor Cooper.

This research involves both experimental characterisation and synthesis of molecules, along with computational prediction of their properties. On the experimental side, Professor Cooper and his colleagues have analysed large numbers of molecules, also looking to calculate key properties. “We focused on porosity, and on the way that large surface areas can absorb gases, for methane storage for example. But the principles of the approach could be applied to conductivity, light absorption, really any property that you can calculate,” he says. The team has developed what are called energystructure-function maps to search for specific properties, which represent a valuable resource for further analysis. “For example, if you think of a new application in something like spintronics, or a memory application, then you can look back to all of the molecules that you’ve considered previously and recalculate new properties,” outlines Professor

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Cooper. “To some extent, the power of this grows as you do more predictions, and you can build a database of predicted structures.”

The work of Professor Graeme Day is crucial to this ability to predict the properties of a crystal structure. Based at the University of Southampton, Professor Day and his group hold deep expertise in the development of predictive computational methods. “We’ve been working on developing algorithms and software to predict, given a specific molecule, the likely ways in which it will pack into a 3-dimensional crystal structure,” he explains. Molecules can never fill space perfectly however, so they will also leave gaps when they pack together in a crystal. “We’re looking for the types of interactions between molecules that will in a way enhance that free space that you find in crystal structures. We’re using strong interactions between functional groups on molecules, testing ideas that we’ve come up with in collaboration with the synthetic chemists, and putting them through the computational algorithms to see if our expectations pan out,” says Professor Day. A molecule within a crystal structure is typically surrounded by copies of itself, so one of the major challenges in research is to understand the ways in which that molecule

interacts with itself, to essentially optimise the stability of a structure. This is a complex area of research, as for any given molecule, a computer can generate tens of thousands, or even millions, of possible structures. “We spend a lot of time calculating and assessing the relative stabilities of these structures, to give us an idea of which would actually form if we went ahead and made that particular

Cooper acknowledges that they are not yet infallible, in terms of guaranteeing that a particular molecule will pack in a certain way and give rise to the desired properties. The chemistry is extremely subtle, and it’s not yet possible to predict with certainty how a molecule will pack within a crystal structure, so Professor Cooper says the methods and tools will be used more to assess probabilities

We’ve adopted an approach distinct from the chemical, rulesbased approach. The benefit is that if you get it right, then it’s effectively generic, and can be used to correctly predict an enormous array of structures. molecule,” outlines Professor Day. While a major priority in the project has been finding promising molecules in terms of porosity, Professor Day is also interested in applying the same types of approaches to predict structures that lead to other properties.

“We are also investigating the possibility of applying the methods to look for molecules where the way that they pack into the crystal structure leads to good mobility of electrons, so that material could then be used in electronic devices,” he says.

The predictive methods developed within the project are very powerful, yet Professor

rather than provide guarantees. “We can assess the probability of a molecule packing in the right way, and we can certainly also get a good sense of which systems will have no chance of functioning in a particular way,” he says. “For example, if you predict the properties of a certain molecule and there are no porous structures on the landscape, then the chance of the eventual material being porous is probably very low. So you can eliminate the certain fails—the things that really have no chance—and devote more attention in research to things that are more likely to succeed.”

Materials discovery using energy-structure-function maps: In the energy-density plots each point corresponds to a computed crystal structure and each structure is colour coded to highlight a structural or functional property. These energy-structure-function maps shown the predicted pore dimensionalities, and calculated deliverable methane capacities, for the predicted T2 crystal structures. Using these energy-structure-function maps, the project team were able to find new functional materials.

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EU Research

RobOT Robust Organic Tectonics Project Objectives

The objective of the ERC RobOT project was to introduce a new level of ‘designability’ into the discovery of functional molecular crystals, by integrating computational prediction with synthesis, analysis, and application.

Project Funding

Funded by an ERC-AG-PE5 - ERC Advanced Grant - Materials and Synthesis through grant agreement number 321156 (ERC-AG-PE5-ROBOT).

Project Partners

• University of Liverpool • University of Southampton

Contact Details

Crystals of one of the materials that was discovered using the new method, as seen by an electron microscope. This is a structure with a very high methane deliverable capacity, making it promising for natural-gas-powered vehicles. Credit: University of Southampton. Read more at: https://www.eurekalert.org/pub_releases/2017-03/uos-mm032217.php

Project Coordinator, Cooper Group, University of Liverpool Crown Street, Liverpool L69 7ZD, United Kingdom T: +44 151 794 3548 E: aicooper@liv.ac.uk W: https://www.liverpool.ac.uk/coopergroup/research/ Functional materials discovery using energy– structure–function maps, Nature, 2017, 543, 657–664

Professor Andy Cooper (left) Professor Graeme Day (right)

Property prediction This is very valuable in terms of molecular design. It can sometimes take six months or more to make a new molecule, with no guarantee that it will have the desired properties, whereas predictive methods could enable researchers to work significantly more efficiently. “Instead of making six molecules and hoping that one of them works, we could computationally predict the properties of 100 molecules, or 1,000, and then focus on the most promising three or four,” explains Professor Cooper. These calculations can be performed relatively quickly, giving researchers important insights into the most promising molecules with respect to certain properties. “The idea is to design the properties in silico, in a computer, from which you can have a good expectation that you will get the property that you want,” outlines Professor Cooper. “In the past, trial-and-error methods have commonly been used, even in crystal engineering, which is based on control of crystallisation. We’re trying to move away from trial-and-error towards design.”

The tool itself is not yet ready for the commercial marketplace, yet it is becoming more user-friendly over time, and Professor Cooper believes the project’s research holds clear relevance to industry. For example, there is a lot of interest in using organic semi-

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conductors in mobile devices. “You could assay 1,000 candidate molecules, and from that calculate which have promising charge transport and which behave as semi-conductors,” says Professor Cooper. Cost-efficiency is of course an important issue for the commercial sector, something of which Professor Cooper is well aware. “Computation can be seen as expensive in terms of time, but lab work is costly in both time and money. The cost of the computation is more than outweighed by the saving of working on the right molecules, rather than molecules that have no chance of assembling in the way that you want,” he says. “You can also trial crazy things which you wouldn’t want to make speculatively because the chance of success might be very low.”

The primary focus of this research at this stage is improving the design of the tool, rather than exploring commercial applications. While the RobOT project is coming towards the end of its funding term, researchers are keen to pursue further investigation in this area in the future.

“The next step is to let the computer inform what new molecules we try out when we’re looking for a certain property,” outlines Professor Day. “We could also broaden out the scope and type of properties and types of materials where we can apply these tools and methods. We think that they could have a big impact across a broad range of application areas.”

Professor Andy Cooper Andy Cooper is a Professor of Chemistry at the University of Liverpool and Director of the Materials Innovation Factory. A unifying theme in his research is the close fusion of computational prediction and experiment to discover new materials with step-change properties. He was elected to the Royal Society in 2015.

Professor Graeme Day Graeme Day is a Professor of Chemical Modelling at the University of Southampton.

His research interests are the development of computational methods for predicting the structures and properties of molecular materials, and in applying these methods to a range of problems, including the design of functional materials.

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