His system could alleviate the drawbacks of existing desalination plants.
David Warsinger thinks he’s found an innovation that could help combat one of the 21st century’s great environmental challenges: water shortages around the globe.
His fix is an improved form of reverse osmosis—the most common method of desalination. Today, an estimated 5% of the world’s population relies on desalinated water, drawn from the ocean or brackish inland sources, to meet at least some daily needs. This figure will continue to rise as aquifers are further squeezed by pollution, overuse, and shifting rainfall patterns linked to climate change. According to the United Nations, some 3.6 billion people live in areas that experience water scarcity at least one month of the year—and that number is likely to exceed five billion by 2050. “Globally, we are truly tapping out our water resources,” Warsinger says.
Yet desalination today has major limitations. Traditional reverse osmosis, in which pressurized water is forced through a salt-removing membrane, uses a lot of energy and is costly. It also leaves behind a large part of the water as brine—an especially big problem for inland plants, where source water is scarcer.
Warsinger’s system, which he developed with Emily Tow while they were both at MIT, is known as batch reverse osmosis, and it is designed to make the process more efficient. The technique allows desalination to occur in batches, with salinity and pressure varying over time. Whereas traditional reverse osmosis systems apply constant pressure, the batch system is engineered to apply less pressure to water that’s less salty, saving a considerable amount of energy. It also increases the rate of fresh water extraction by minimizing the build-up of salt on the membranes.
Warsinger’s lab at Purdue, where he’s now a professor of mechanical engineering, has since worked to refine the batch design. His team has developed a trailer-sized prototype it hopes to use for pilot plants in Peru and Kenya.
His company’s artificial limbs are not only high-functioning but cheap enough for people in low-income countries.
Four years ago, during a university challenge, Mohamed Dhaouafi found out that one of his teammates’ cousins had been born without upper limbs and couldn’t afford prosthetics. An engineering student at the time, he’d been searching for a project that would have a social impact—and as he started to research limb loss around the world, he found a massive unmet need. The World Health Organization estimates that there are 30 million people with amputated limbs in poor countries, and only 5% of them have access to prosthetics. Fitting children with high-quality devices is particularly expensive because they’re constantly growing. But without prosthetics, stigma and mobility problems keep large numbers of them from attending school, setting many up for lifelong unemployment. “We’re not just talking about limb differences,” Dhaouafi says. “We’re talking about poverty, access to education, access to health care.”
Today, Dhaouafi has a product he believes will help make advanced artificial limbs more accessible. His Tunisia-based startup, Cure Bionics, is in the process of finalizing an adjustable multi-grip bionic arm that will sell for about $2,000—a fraction of the cost of similar devices. His team plans to keep costs down by 3D-printing key components and engineering much of the circuitry in-house.
But this doesn’t mean they’re skimping on quality: like bionic arms developed elsewhere, Cure’s prototype is equipped with sensors that allow users to operate the hand by flexing or relaxing the muscles in their residual limb. The company is also developing algorithms to help the arm recognize the body’s electrical signals more accurately, which will minimize reliance on an orthopedist for adjustments. At a later stage, Cure plans to introduce a virtual--reality headset that will gamify the physical therapy process for children. “Instead of a doctor asking you to imagine picking up an apple, you’ll be using your hand to jump between buildings like Spider-Man,” Dhaouafi says.
Dhaouafi and his colleagues are closing in on their initial product launch: they’ve already tested their arm with five Tunisian youths and will soon initiate trials at three government hospitals. Ultimately Dhaouafi hopes to offer a range of high-quality, affordable prosthetics for young people across Africa, the Middle East, and beyond.
Photo by the Obama Foundation
Alex Le Roux
A massive 3D-printing project in Mexico could point the way to the future of affordable housing.
Alex Le Roux thinks 3D printing can open new possibilities for architectural design and cut the cost of building housing around the world.
As cofounder of Icon, a startup based in Austin, Texas, Le Roux is the mastermind behind the Vulcan, an industrial--scale 3D printer that can construct the wall system of an entire house in just 24 hours of print time. According to the United Nations, some 1.6 billion people lack adequate shelter, and a third of the world’s urban population lives in informal settlements or slums. Part of the reason, Le Roux says, is that traditional building methods lead to wasted materials and excess labor costs, driving up housing prices beyond the reach of many poor families.
The Vulcan is designed to change that by introducing automation to the process. The 12-foot-tall robotic device works by extruding inch-thick layers of a special concrete mix fed in from a separate machine, much like a giant tube of toothpaste. Icon programs its home designs ahead of time to make the operator’s job as simple as possible. “Once these two machines are set up on a job site, you download an app and you’re off to the races,” Le Roux says.
In March 2018, Icon built the US’s first officially permitted 3D-printed house. It has now built 16 houses in Austin and in Mexico, where it’s constructing the world’s first 3D-printed community, designed to accommodate 50 low-income families. Icon’s ultimate goal, Le Roux says, is to reduce the cost of homebuilding by 50%.
Photo by Natalie Cass, Score Headshots
A loved one’s diagnosis led her to employ machine learning in the search for a Parkinson’s cure.
In 2016, Katharina Volz received news that someone close to her had Parkinson’s. At the time Volz had just finished her PhD at Stanford and was locked into a well-earned career in academic research, working on stem cells. But the news changed all that.
“I just knew I could actually make a difference,” she says. “Sometimes you feel helpless. But actually I felt deeply responsible for finding a way to get curative treatments for this disease, because I knew I could do something about it.” Volz now leads a company, OccamzRazor, that has successfully married machine learning with biomedical research and is pushing the search for a Parkinson’s cure.
Volz noticed a problem when it comes to researching Parkinson’s, and it’s one that arguably plagues science at large. Experts studying the disease were specializing in particular aspects of it and generally didn’t know much about and couldn’t engage with other aspects. These academic silos made it hard for new insights to be properly shared and explored, impeding our continued understanding of how Parkinson’s progresses.
“Even if you’re the smartest researcher in the world, you can’t put all of this information together and make the connections you need to truly understand how the disease operates,” says Volz. “As humans, our ability to draw these numerous connections is limited.”
That’s where machine learning comes in. Volz realized AI could do a better job than a human at reading all the different papers and data sets published on a topic and identifying insights that could lead to breakthroughs. Though machine learning isn’t her specialty, she brought together a team of AI researchers, along with experts from other fields like computational biology, drug development, and neuroscience. She raised money from various investors, including Jeff Dean (the head of AI at Google) and the Michael J. Fox Foundation. Thus, in 2016, OccamzRazor was born.
The company is tackling the problem in two major steps. First, it has developed programs that read and understand published materials on Parkinson’s. Next, it is using AI to integrate genomics, proteomics, and clinical data sets. The goal is to predict new pathways and genes important to Parkinson’s that can then be tested in the laboratory.
The result is what OccamzRazor calls the “Parkinsome”—a knowledge map of Parkinson’s that reveals how the disease is caused and progresses, points to signs and symptoms that can help make an early diagnosis, and identifies potential therapeutic targets. After OccamzRazor validates its findings, it partners with biotech and pharma companies to develop drugs.
The goal is to take this approach beyond just Parkinson’s. Volz and her team have plans to scale up the platform to build comprehensive knowledge maps for other complex diseases related to the aging of the brain. “Diseases inform each other,” says Volz. “Studying Parkinson’s is one of the best ways to study brain aging in general.”
Photo by David Vintiner