Innovation Article

Jennifer Chu’s picture

By: Jennifer Chu

At the heart of any electronic device is a cold, hard computer chip, covered in a miniature city of transistors and other semiconducting elements. Because computer chips are rigid, the electronic devices that they power, such as our smartphones, laptops, watches, and televisions, are similarly inflexible.

Now a process developed by MIT engineers may be the key to manufacturing flexible electronics with multiple functionalities in a cost-effective way.

The process is called  “remote epitaxy” and involves growing thin films of semiconducting material on a large, thick wafer of the same material, which is covered in an intermediate layer of graphene. Once the researchers grow a semiconducting film, they can peel it away from the graphene-covered wafer and then reuse the wafer, which itself can be expensive depending on the type of material it’s made from. In this way, the team can copy and peel away any number of thin, flexible semiconducting films, using the same underlying wafer.

In a recent paper published in the journal Nature, the researchers demonstrate that they can use remote epitaxy to produce freestanding films of any functional material. More important, they can stack films made from these different materials to produce flexible, multifunctional electronic devices.

Jennifer Chu’s picture

By: Jennifer Chu

A modern airplane’s fuselage is made from multiple sheets of different composite materials, like so many layers in a phyllo-dough pastry. Once these layers are stacked and molded into the shape of a fuselage, the structures are wheeled into warehouse-sized ovens and autoclaves, where the layers fuse together to form a resilient, aerodynamic shell.

Now MIT engineers have developed a method to produce aerospace-grade composites without the enormous ovens and pressure vessels. The technique may help to speed up the manufacturing of airplanes and other large, high-performance composite structures, such as blades for wind turbines.

The researchers detail their new method in a paper published in the journal Advanced Materials Interfaces.

“If you’re making a primary structure like a fuselage or wing, you need to build a pressure vessel, or autoclave, the size of a two- or three-story building, which itself requires time and money to pressurize,” says Brian Wardle, professor of aeronautics and astronautics at MIT. “These things are massive pieces of infrastructure. Now we can make primary structure materials without autoclave pressure, so we can get rid of all that infrastructure.”

NIST’s picture

By: NIST

Artificial intelligence (AI) promises to grow the economy and improve our lives, but along with these benefits, it also brings new risks that society is grappling with. How can we be sure this new technology is not just innovative and helpful, but also trustworthy, unbiased, and resilient in the face of attack? We talked with NIST’s Information Technology Lab director Chuck Romine to learn how measurement science can help provide answers.

How would you define AI? How is it different from regular computing?

One of the challenges with defining AI is that if you put 10 people in a room, you get 11 different definitions. It’s a moving target. We haven’t converged yet on exactly what the definition is, but I think NIST can play an important role here. What we can’t do, and what we never do, is go off in a room and think deep thoughts and say we have the definition. We engage the community.

Paavo Käkelä’s picture

By: Paavo Käkelä

After two decades of offshore productions in low-cost countries, manufacturers are now struggling with the rapidly growing salaries and countereffects of cheap production. The question that industries are asking today is: Do we continue offshoring, or should we consider reshoring?

The right answer, according to Paavo Kakela, the CEO of EID Robotics, who provides modular microfactory systems, is that manufacturers should transform their operations to rightshoring.

During the 1990s, U.S. manufacturers were sold by the lower cost of Asian labor. This is how the global offshoring boom started in Asia. By the 2000 millennium, offshoring began to peak; it maintained this growth trend until 2010—the year when U.S. domestic-manufacturing employment rates reached all-time lows.

Anthony Veal’s picture

By: Anthony Veal

When Microsoft gave its 2,300 employees in Japan five Fridays off in a row, it found productivity jumped 40 percent.

When financial services company Perpetual Guardian in New Zealand trialed eight Fridays off in a row, its 240 staff reported feeling more committed, stimulated, and empowered.

Around the world there’s renewed interest in reducing the standard working week. But a question arises: Is instituting the four-day week, while retaining the eight-hour workday, the best way to reduce working hours?


Perpetual Guardian trial outcomes, as measured by researchers from the University of Auckland and Auckland University of Technology. 4dayweek.com, CC BY-SA

Phanish Puranam’s picture

By: Phanish Puranam

Machine learning, the latest incarnation of artificial intelligence (AI), works by detecting complex patterns in past data and using them to predict future data. Since almost all business decisions ultimately rely on predictions (about profits, employee performance, costs, regulation, etc.), it would seem obvious that machine learning (ML) could be useful whenever “big” data are available to support business decisions. But that isn’t quite right.

The reality in most organizations is that data may be captured but they are stored haphazardly. Their quality is uneven, and integrating them is problematic because they sit in disparate locations and jurisdictions. But even when data are cleaned up and stored properly, they’re not always appropriate for the questions or decisions that management has in mind. So, how do you know whether applying predictive analytics through AI techniques to a particular business problem is worthwhile? Although every organization and context is different, here are five general principles that should be useful in answering that question.

Jennifer Lauren Lee’s picture

By: Jennifer Lauren Lee

3D printing of metal objects is a booming industry, with the market for products and services worth more than an estimated $2.3 billion in 2015, a nearly fivefold growth since 2010, according to Wohlers Report 2016. For this type of manufacturing, a metal part is built up successively, layer by layer, over minutes or hours. Sometimes thousands of layers are added together to make a single piece, a reason why this process is conventionally referred to as “additive manufacturing” (AM). By convention, 3D printers that create functional parts, often metal, in a commercial environment are referred to as “additive manufacturing machines.” The term “3D printing” usually refers to the process used to make plastic parts, one-off pieces, art pieces, or prototypes.

Additive manufacturing machines are particularly handy for making objects with complex forms or geometry, or internal features like ducts or channels. They are becoming increasingly popular in the aerospace, automotive, medical, and technology industries, to make complex pieces such as fuel injector nozzles for engines or titanium bone implants for skull, hip, and other repairs.

Kelvin Lee’s picture

By: Kelvin Lee

Biopharmaceutical manufacturing uses living cells to produce therapies that treat diseases like cancer, diabetes, and autoimmune disorders. Manufacturing medicine using biology presents different challenges from the traditional chemical manufacturing processes that stamp out identical pressed pills.

Biomanufacturing processes are hard to control, and the products are difficult to define as “identical” from batch to batch. Despite these challenges, biopharmaceuticals are critical to public health because the advantages are significantly greater. Scientific understanding of diseases and the success of biologically manufactured therapies to treat them has increased dramatically. But it can take a decade from design to full production of a biopharmaceutical—not fast enough to meet the needs of all the patients, or to beat competition from overseas.

Michael Baxter’s picture

By: Michael Baxter

You would expect a building where vinegar is made to have a sour smell, highly pungent, perhaps with a whiff of apple. World Technology Ingredients (WTI) smells nothing like this. Their manufacturing facility, off a county two-lane in Jefferson, Georgia, has a vaguely mineral aroma. More dry than dank, and not altogether unpleasant.

Maybe that’s because the vinegar made here isn’t destined for grocery store shelves, but for food preservation. It’s called buffered vinegar, an all-natural additive that protects meats and other products from microbes. WTI makes a lot of this vinegar, more than it used to, in fact, and that’s partly because of Damon Nix.

On this Friday afternoon, Nix is taking a visitor through WTI’s plant, pointing out its sectors and stations. Here’s the wet vinegar, seven titanic tanks and even more smaller ones, emitting a hiss-and-motor chorus of mechanized blending. Over here’s the powdered version, mixed in towering contraptions on chalky floors (that will later be cleaned), then heated, blended, and bagged.

Orit Peleg’s picture

By: Orit Peleg

Gathered inside a small shed in the midst of a peaceful meadow, my colleagues and I are about to flip the switch to start a seemingly mundane procedure: using a motor to shake a wooden board. But underneath this board, we have a swarm of roughly 10,000 honeybees, clinging to each other in a single magnificent pulsing cone.

As we share one last look of excited concern, the swarm, literally a chunk of living material, starts to move right and left, jiggling like jelly.

Who in their right minds would shake a honeybee swarm? My colleagues and I are studying swarms to deepen our understanding of these essential pollinators, and also to see how we can leverage that understanding in the world of robotics materials.


Honeybee swarms adapt to different branch shapes. Credit: Orit Peleg and Jacob Peters

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