Working to make geothermal energy practical
Kathy Hannun brought something to geothermal heating and cooling technology that it hasn’t had before: affordability.
In the past, using heat from the earth has been something of a luxury good—systems were expensive and had to be custom-built for the house they were heating, with prices to build and install them in New York reaching well above $60,000.
“The earth is a relatively constant temperature of 50 °F year-round once you get down about six feet and below, lasting hundreds of feet down,” she says. Using ground loops filled with water mixed with a propylene glycol solution, it’s possible to exchange heat very efficiently between the earth and the home that’s being heated or cooled. “Horizontal geothermal systems put the loops in about 10 feet below ground,” she explains. “This requires a lot of surface and rips up a large section of ground.” Getting ground loops installed in the yard has in the past been quite an ordeal, requiring massive drilling equipment and significant surface damage. Instead, using technological innovations pioneered by the oil and gas industry, Hannun’s Dandelion Energy has created a drilling system that limits the amount of land needed and the surface damage done to achieve the same result.
Dandelion can install a system for a total cost of less than $30,000.
Hannun came to geothermal while working as a product manager for Google X. Her goal: take geothermal “down the path that solar has been down over the past two decades, and bring it from a very niche technology to one that replaces furnaces and boilers.”
His approaches can treat dirty wastewater and can make desalination more efficient.
Anurag Bajpayee built a one-stop shop for cleaning up the world’s most contaminated water. And after just six years, his Boston-based company, Gradiant, has more than 200 employees and operates more than 20 treatment plants around the world.
Bajpayee started Gradiant with lab-mate Prakash Govindan, who like him was working on desalination techniques. The oil and gas industry was at the peak of the shale boom thanks to advances in fracking, where rock formations are fractured using pressurized fluids to extract oil and gas trapped inside. They quickly found customers keen to use Govindan’s technology to extract water from fluids contaminated during the process, which reduces water requirements and minimizes how much toxic brine needs to be stored in deep disposal wells.
Since then they’ve developed an extensive patent portfolio, says Bajpayee, and commercialized two more treatment technologies—one that efficiently pulls specific contaminants out of industrial wastewater so it can be reused, and another that disinfects water without the use of chemicals like bleach. This year Gradiant will launch its first commercial system based on a new technology that can be installed in seawater desalination plants to increase recovery of fresh water by up to 85%.
As a PhD student at MIT he invented a membrane-free desalination technique that Scientific American recognized as one of its annual Top 10 World-Changing Ideas. But Bajpayee realized that it was a long way from commercial viability and any business built around this one idea was likely to fail. Instead he decided to develop and collect lots of different technologies, so his company could tackle any water contamination problem it encountered.
A tinkerer figures out how to tell which genes are active inside a cell
After Jason Buenrostro graduated from Santa Clara University with a degree in biology and engineering, he went to work in a lab at Stanford, overseeing an $800,000 gene sequencing machine.
He wanted to understand the effects of the genetic mutations his machine detected. But many of the mutated genes he found were considered junk because they didn’t direct the production of proteins. So in his graduate research at Stanford, he pivoted to developing methods for measuring these underexplored regions.
DNA is essentially identical from cell to cell, but a kidney cell differs from a brain cell in the activity of those genes. Regions of DNA need to be tightly wound to fit inside the nucleus, and only open DNA regions can be active.
Buenrostro and his colleagues developed a tool called ATAC-seq to measure these open regions of the genome, many of which don’t make proteins but regulate genetic activity. “I didn’t realize how useful [a tool] it would be for people. It kind of exploded,” says Buenrostro, noting that ATAC-seq now has its own Wikipedia page.
More recently, Buenrostro has further developed the technology to identify open DNA at the level of a single cell. With this tool, researchers can determine which genes are active in single cells, studying how these cells sometimes develop into cells of new types, and how some functions go awry in disease.
Buenrostro wants to use these methods to learn new basic information about the differences between healthy and diseased cells and to use this information to engineer new behaviors into cells as they develop and mature.
Buenrostro, who now oversees a lab of 10, says, “I want to understand cell fate decisions to ultimately be able to engineer cells to do whatever I would like them to”—for instance, fighting cancer.
Her robots do some of the grunt work so hospital staffers can spend more time with the patients
Vivian Chu developed the AI software for a hospital robot called Moxi, which has already been tested in four Texas hospitals. During those trials, Moxi worked 22/7—with two hours off a day for charging—picking up supplies such as syringes with its gripper hand and then dexterously moving its arm to drop them into the tray in its base. After that, it would roll down the hallway, taking care not to bump into people, and drop the supplies off in drawers outside patients’ rooms. Moxi can also complete other repetitive tasks such as delivering lab samples and removing soiled linen bags, easing the workload of hospital staff and freeing up more time for them to spend with patients.
Chu’s graduate thesis focused on robots that can combine different kinds of sensory information from their surroundings—visual, auditory, kinetic—to guide their actions when they encounter a new situation. For example, one of her robots automatically adjusts the force it applies when pulling on a drawer handle if it learns that the drawer is already half open. Chu hopes to add similar functionality to future versions of Moxi. “It gives you that richness and robustness to be able to learn about the world,” says Chu, the chief technology officer of Diligent Robotics, which she cofounded in 2017.
Growing up in a three-generation household in the heart of Silicon Valley, she experienced firsthand how her family struggled to take care of her grandparents as they aged, and that’s where Chu wants to use her robotics expertise in the future to make a positive impact. She hopes to give elderly people staying in nursing homes “the tools to be able to age with dignity, age with grace, [and] be more independent for longer.”
Developed a massive 3D metal printer—for building an entire rocket
Tim Ellis uses 3D metal printing, machine learning, and automated manufacturing to build rockets and satellites. Relativity Space uses this approach to build rockets with just a thousand moving parts (see our profile of the company). A typical rocket, in comparison, has 100,000 moving parts—which not only makes the rocket more expensive but also gives it that many more ways to fail.
Step one for Ellis was building a massive 3D metal printer that stands about 20 feet (6 meters) tall and can print 95% of the parts for a rocket that’s up to 10 feet in diameter and 100 feet tall. Step two was writing the code to automate much of the process and using machine learning to optimize which parts to print, and how to do it.
Relativity Space says it will soon be able to print and iterate a design in as little as 60 days, compared with the industry standard of 18 months—dramatically bringing down costs. This earned the company its first contract, with Telesat, a major Canadian satellite operator, to build rockets to launch some of the company’s satellites starting in 2021.
“We founded Relativity with the long-term vision of 3D-printing the first rocket made on Mars,” says Ellis. “Over time we’ll actually shrink the factory to the point where then we could launch it to another planet.”
On the cusp of the next big battery breakthrough
Qichao Hu believes he’s on the cusp of one of the most highly anticipated developments in industry: the next battery revolution.
As founder and CEO of SolidEnergy Systems, a startup based in Woburn, Massachusetts, he’s come as close as anyone to commercializing rechargeable batteries made of lithium metal. These promise twice the energy density of lithium-ion batteries, the current industry standard for nearly all electronics and electric vehicles.
Since the development of the lead-acid battery in 1870, there have been only five major breakthroughs in battery technology—with energy density doubling roughly every 30 years. If the pattern holds, the next breakthrough is almost due: lithium-ion batteries, whose anodes are usually made of graphite or silicon, were first commercialized in 1991 by Sony.
The boost in energy density offered by lithium metal batteries could effectively double the range of an electric vehicle. The problem is that lithium metal is highly reactive. When charging, early prototypes of lithium metal batteries would form needle--like structures known as dendrites, which could short the cells and cause them to catch fire or explode.
Hu, who was born in China and moved to New York at 12, developed a liquid electrolyte, consisting of a high--concentration solvent in salt, which reduced the formation of dendrites. Building on this solution, SolidEnergy Systems developed a pilot line of lithium metal batteries in 2016 that are now being tested in drones. Later in 2019, it will open the world’s largest manufacturing facility for lithium metal batteries in Shanghai, where Hu hopes to scale up production to tens of thousands of cells per month.
Using AI to make packaged foods better
Biologist turned serial entrepreneur Riana Lynn sees AI as a tool that could make packaged food that not only tastes good but is also affordable, nutrient-dense, and plant-based. After visiting farms and food companies around the world, she realized that the best way to achieve her goal was to make research and development in the food industry more efficient.
Lynn’s Chicago-based company, Journey Foods, employs an “in-house automated scientist,” JourneyAI. Built around algorithms that Lynn helped to create and a database of nutrient and market data, Journey starts with a nutrition goal—“What if we make a product that’s high in vitamin C and protein at lower cost?”—and then devises a recipe that meets that goal.
The company started with fruit snacks. These snacks, called Journey Bites, are made entirely of fruit puree, natural sources of flavor such as cayenne pepper and chia seeds, and “nutrient boosters” that have been devised from the company’s testing of fruit cultures, different types of seaweed, and other sources.
Lynn says the company is now “opening our platform for more products. We’ve been asked to build out data sets for pasta, cookies, plant-based proteins, and more. We’ll be working on beverages by the fall.”