December 6, 2018
By Marco Annunziata
Our ability to discover and master new materials drives scientific and economic progress. Now the convergence of Artificial Intelligence and materials science can make this progress a lot faster.
The convergence of mind and matter, of digital and physical technologies lies at the heart of the fourth industrial revolution. The marriage of artificial intelligence (AI) and materials science represents one of the clearest examples.
Pure digital innovation has attracted the greatest attentionand a large share of financial investmentover the last several years. But we live in a material world, where the quality of our lives depends on improvements in physical products and services: food and shelter, health care, transportation, energy.
True, we spend a lot more time in our online virtual worlds; but this is mirrored by a growing number of Amazon packages at our doorsteps.
Our ability to discover and master new materials has defined successive stages of economic development: wood and clay; bronze and steel; paper; glass; plastics; semiconductors. It is our mastery of silicone that allowed the digital revolution to unfold.
Now we can harness the power of digital technologies to accelerate the discovery of new materials, by marrying AI and materials science. The Canadian Institute for Advanced Research reported earlier this year that leveraging AI could cut the average time needed to develop a new material to one to two years from the current 10 to 20 years.
AI often conjures dystopian images of mass unemployment; but this is instead another example of the power of human-machine collaboration.
In a recent interview, Greg Mulholland, founder and CEO of Citrine Informatics, stresses that the role of AI in materials science is to enable scientists to formulate better hypotheses at a faster pace, and test them more rapidly. Human expertise remains crucial; AI helps material scientists identify and compare a much wider range of options.
Manufacturing today benefits from three waves of innovation: new production techniques (like 3-D printing), new design methods (like generative design, also driven by AI) and new materials. These three waves of innovation are interdependent and mutually reinforcing: 3-D printing allows us to manufacture components with different geometries, yielding greater resistance, lighter weight and better performance; finding new geometries requires a different approach to design, where AI helps us break free from the mental constraints acquired through decades of traditional manufacturing methods; new materials can in turn broaden the range of possible design solutions.
Each of these trends is powerful in itself, but bringing them together compounds their transformational potential, for example by co-optimizing new geometries and new materials.
Going forward, we are likely to see the powerful impact of new materials across a range of sectors: more efficient batteries for electric vehicles, more environmentally-friendly plastics and dyes, new 3-D printed artificial organs and other medical implants.
Companies operating in the materials space will have to adapt. While past phases of economic development have been characterized by one or a few dominant materials, the future will shift towards greater specialization, towards a wider range of new materials individually suited to specific applications.
For companies in the materials space, success will hinge on the ability to quickly identify, design and develop the new materials that can best meet the shifting priorities of their customers. Companies will need a different set of skills, bringing together material scientists and data scientists and, increasingly, experts conversant in both data and materials science.
The coming together of AI and materials science can help boost manufacturing productivity; and innovations in tangible reality might prove as exciting as those of virtual and augmented reality.
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