Monthly Archives: February 2017

America opens headquarters steps from MIT campus

These are not your grandmother’s fibers and textiles. These are tomorrow’s functional fabrics — designed and prototyped in Cambridge, Massachusetts, and manufactured across a network of U.S. partners. This is the vision of the new headquarters for the Manufacturing USA institute called Advanced Functional Fabrics of America (AFFOA) that opened Monday at 12 Emily Street, steps away from the MIT campus.

AFFOA headquarters represents a significant MIT investment in advanced manufacturing innovation. This facility includes a Fabric Discovery Center that provides end-to-end prototyping from fiber design to system integration of new textile-based products, and will be used for education and workforce development in the Cambridge and greater Boston community. AFFOA headquarters also includes startup incubation space for companies spun out from MIT and other partners who are innovating advanced fabrics and fibers for applications ranging from apparel and consumer electronics to automotive and medical devices.

MIT was a founding member of the AFFOA team that partnered with the Department of Defense in April 2016 to launch this new institute as a public-private partnership through an independent nonprofit also founded by MIT. AFFOA’s chief executive officer is Yoel Fink. Prior to his current role, Fink led the AFFOA proposal last year as professor of materials science and engineering and director of the Research Laboratory for Electronics at MIT, with his vision to create a “fabric revolution.” That revolution under Fink’s leadership was grounded in new fiber materials and textile manufacturing processes for fabrics that see, hear, sense, communicate, store and convert energy, and monitor health.

From the perspectives of research, education, and entrepreneurship, MIT engagement in AFFOA draws from many strengths. These include the multifunctional drawn fibers developed by Fink and others to include electronic capabilities within fibers that include multiple materials and function as devices. That fiber concept developed at MIT has been applied to key challenges in the defense sector through MIT’s Institute for Soldier Nanotechnology, commercialization through a startup called OmniGuide that is now OmniGuide Surgical for laser surgery devices, and extensions to several new areas including neural probes by Polina Anikeeva, MIT associate professor of materials science and engineering. Beyond these diverse uses of fiber devices, MIT faculty including Greg Rutledge, the Lammot du Pont Professor of Chemical Engineering, have also led innovation in predictive modeling and design of polymer nanofibers, fiber processing and characterization, and self-assembly of woven and nonwoven filters and textiles for diverse applications and industries.

Rutledge coordinates MIT campus engagement in the AFFOA Institute, and notes that “MIT has a range of research and teaching talent that impacts manufacturing of fiber and textile-based products, from designing the fiber to leading the factories of the future. Many of our faculty also have longstanding collaborations with partners in defense and industry on these projects, including with Lincoln Laboratory and the Army’s Natick Soldier Research Development and Engineering Center, so MIT membership in AFFOA is an opportunity to strengthen and grow those networks.”

The design of industrial processes for drug manufacturing

When organic chemists identify a useful chemical compound — a new drug, for instance — it’s up to chemical engineers to determine how to mass-produce it.

There could be 100 different sequences of reactions that yield the same end product. But some of them use cheaper reagents and lower temperatures than others, and perhaps most importantly, some are much easier to run continuously, with technicians occasionally topping up reagents in different reaction chambers.

Historically, determining the most efficient and cost-effective way to produce a given molecule has been as much art as science. But MIT researchers are trying to put this process on a more secure empirical footing, with a computer system that’s trained on thousands of examples of experimental reactions and that learns to predict what a reaction’s major products will be.

The researchers’ work appears in the American Chemical Society’s journal Central Science. Like all machine-learning systems, theirs presents its results in terms of probabilities. In tests, the system was able to predict a reaction’s major product 72 percent of the time; 87 percent of the time, it ranked the major product among its three most likely results.

“There’s clearly a lot understood about reactions today,” says Klavs Jensen, the Warren K. Lewis Professor of Chemical Engineering at MIT and one of four senior authors on the paper, “but it’s a highly evolved, acquired skill to look at a molecule and decide how you’re going to synthesize it from starting materials.”

With the new work, Jensen says, “the vision is that you’ll be able to walk up to a system and say, ‘I want to make this molecule.’ The software will tell you the route you should make it from, and the machine will make it.”

With a 72 percent chance of identifying a reaction’s chief product, the system is not yet ready to anchor the type of completely automated chemical synthesis that Jensen envisions. But it could help chemical engineers more quickly converge on the best sequence of reactions — and possibly suggest sequences that they might not otherwise have investigated.

Jensen is joined on the paper by first author Connor Coley, a graduate student in chemical engineering; William Green, the Hoyt C. Hottel Professor of Chemical Engineering, who, with Jensen, co-advises Coley; Regina Barzilay, the Delta Electronics Professor of Electrical Engineering and Computer Science; and Tommi Jaakkola, the Thomas Siebel Professor of Electrical Engineering and Computer Science.