On science
One atom at a time AI is not only changing the way we process data, it’s changing how we carry out research, period. Text: Katrina Jurva Photo: Venla Helenius EVERY MONDAY morning at 9am,
Milica Todorović grabs a bowl of porridge and sits down to talk with computer scientists about how machines learn. Todorović is one of the many researchers from the natural sciences looking to apply the power of AI in her daily work; by keeping up with what experts in machine learning are doing, she hopes to bring some tiny things together in smarter ways. What kinds of tiny things? Think minuscule. Milica Todorović’s work focuses on how devices from mobile phones to solar panels function at the atomistic level, the smallest unit of ordinary matter. Her days revolve around finding the best composite materials to get the job done. With global challenges like adopting green energy, the world needs these kinds of advanced materials to bring about the next wave of technology and energy solutions. “The forefront of materials engineering is really in making complex materials that combine vastly different properties,” explains Todorović. In her case, this typically involves a mix of organics, generally soft materials like cellulose from wood products, and inorganics, like metals. With the seemingly never-ending list of configurations out there, “we need to shake up our ways of thinking to find new solutions,” she says.
Getting to the bottom of things
Optimizing materials for the technologies of the future is not just about tweaking one small thing here or there, it’s about understanding how the materials inside devices interact at the most fundamental level. Picking the right materials is the first step, yet having these in hand doesn’t 28 / AALTO UNIVERSITY MAGAZINE 23
guarantee smooth function. Choices made at the assembly stage can inadvertently create less-than-optimal structural contacts, ultimately affecting how a device performs. You can select the best possible components, but if you don’t combine them in just the right way or at the right temperature, you’ll end up with something less than ideal. When it comes to the inner makings of materials, say, in electronics, the possibilities of different matches are nearly endless. At the same time, the better the match between materials, the stronger the device becomes. The question is how to get there. Conventional thinking in quantum mechanics, the area of physics that looks at the world at the smallest possible scale, has seen this type of calculation as simply too big to get results at the speed in which they are needed. Until now, researchers have relied on applying certain design principles based on knowing AI could speed up the processes of materials research enormously, say Milica Todorović and Patrick Rinke.
what materials traditionally work well together. This makes a lot of sense. With years of study behind them, scientists have a strong sense of the types of composite materials that suit certain applications and are well equipped to find a solid solution from a pot of options. But in a field where the sheer number of combinations exceeds human analytical capacity, nothing is certain. Studies on composite materials tend to be costly in terms of human-hours and computing time. In the end, there is a lot of guessing and chemical intuition involved. “Our chemical intuition can guide us a long way, we’re just never sure if there isn’t some configuration that we hadn’t considered that might be relevant,” Milica Todorović admits.