viernes, 26 de enero de 2018

Prototypes for the new space age

What happens when 20 researchers conduct 14 projects from entirely disparate fields of research over the course of 90 minutes — while floating in zero gravity? Thrills, learning, magic — and results.

This past November, the Media Lab Space Exploration Initiative chartered a flight with the Zero Gravity Corporation to conduct experiments that relied on the unique affordances of microgravity. Projects ranged across disciplines: design, architecture, engineering, biology, music, robotics, and beyond — manifesting the Initiative’s goal of democratizing access to space. On Jan. 23, the group reassembled to share the results of their projects and celebrate the success of the first flight, at a symposium for the MIT community.

“Space used to be for a very small number of people who had to study in a particular field and train for years. But space will soon be for everyone,” says Maria Zuber, MIT’s vice president for research and one of the initiative’s principal investigators. “The Media Lab students bring a creative view, and a lot of out-of-the-box thinking. If we expose those minds to space, we’ll have the benefit of their thinking about facilitating the opening up of the space frontier.”

Rapid prototypes, rapid results

The January symposium demonstrated the remarkable diversity of research areas represented on the flight, and also underscored the far-reaching ideas behind the projects. Even by Media Lab standards it was an unusual assortment, running the gamut from peer-reviewed publications, to architectural modeling, to futuristic fashion. These researchers are imagining and prototyping for humanity's future in space, beyond the basic concerns of survival.

The researchers had only a few weeks to submit project proposals, and between two and five months to design their experiments and get them flight-ready and approved. Every proposal had to meet strict research criteria as well as stringent safety and operational standards. Each experiment had to be designed to run in only 20-30 seconds of zero gravity at a time, over the course of 90 minutes.

The results of the 14 research projects that flew are as varied as their fields of inquiry. A few highlights:

Scratch in Space: Eric Schilling, of the Media Lab’s Scratch team, spent his time in microgravity playing games designed by members of the Scratch community, ages 8-15. He recorded his efforts and compiled them into a video.

TESSERAE: The self-assembling architecture project of Ariel Ekblaw, of the Responsive Environments group, is aimed at a future need for low-cost orbiting space infrastructure. She published the results from the flight as part of a technical paper with AIAA (American Institute of Aeronautics and Astronautics) and presented the paper at their 2018 SciTech conference.

Search for Extra-Terrestrial Genomes (SETG): A project from MIT EAPS, headed by Maria Zuber, SETG is the first experiment to sequence DNA at lunar and Martian gravity. The team published a paper on their results, and are now developing a life-detection device that they hope to send to Mars one day.

Orbit Weaver: Fluid Interfaces group alumna Xin Liu’s Orbit Weaver is a hand-mounted device that shoots out a line and attaches to a surface with a magnet, theoretically allowing her to move with greater control in 3-D space. It’s paired with the Orbit Weaver Suit, a custom flight suit made of reflective material that enhances the performance-art aspect of Liu’s work. The project has been featured in Vice China’s Creators Project.

“I’m incredibly proud of all of the Media Lab projects and Lab students that have contributed,” says Ariel Ekblaw, the initiative’s founder and leader. “A typical zero gravity research flight is about a year in planning. That our participants were able to design and execute their experiments in just a few months really speaks to the culture of the Media Lab, both in terms of rapid prototyping and deployment, and the student-led, grassroots enthusiasm.”

Next steps

At the symposium, Ekblaw also outlined what’s ahead for the Space Exploration Initiative:

  • Annual zero-gravity flight. The flight this past November will be the first of many; the goal is to get as many different projects from as many different research groups and areas of interest up and into zero gravity as possible.

  • Blue Origin flight, summer 2018. Six projects will be selected as payloads for a suborbital flight, allowing for more extended periods of microgravity.

  • International Space Station, winter 2019: One to three payloads will board the ISS, allowing for consistent zero gravity conditions.

Beyond the Cradle

In just a few weeks on March 10, Space Exploration will host its second Beyond the Cradle event, a gathering of students, scholars, and luminaries including astronauts, industry leaders, science fiction visionaries, and researchers. The event will be livestreamed; all are invited to watch and engage in imagining our space future.



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After 16 years as heads of house, Anne and Bill McCants to step down from Burton Conner

Following a 16-year head-of-house career that spanned three decades and two residence halls, Professor Anne E. C. McCants and her husband Bill have announced that they will step down from their post in Burton Conner House (BC) at the end of this academic year.

In an email to all heads of house earlier this month, Professor McCants shared that she is “starting a three-year term as the president of the International Economic History Association, a position which I realize is going to require a lot more travel of me than is feasible while serving as head of a residence hall as large and complex as BC.”

Vice President and Dean for Student Life Suzy Nelson offered praise for the McCants’ work as heads of house. “Their experience and perspective have been a great support to me and the entire head of house community, and their commitment to the students of BC will serve as an example for future heads of house to emulate,” says Nelson.

McCants is director of the Concourse program for first-year students and a professor of history in the School of Humanities, Arts, and Social Sciences (SHASS). Her research and teaching focus on the social and economic history of Europe in the Middle Ages and early modern period. She was named a MacVicar Faculty Fellow in 2004 and is a recipient of numerous honors including the Levitan Prize to support innovative and creative scholarship in SHASS. Also, she has twice won the Arthur C. Smith Award for exemplary service to undergraduate life and learning.

Anne and Bill McCants first became heads of house in Green Hall (W5) when it was a residence for women graduate students. They supported the community from 1992 to 2002, a period they recall as “wonderful.” After Professor McCants served consecutive terms as head of History at MIT, the couple found themselves missing the direct student interaction they enjoyed in Green Hall and were inspired to join BC in 2012.

Since BC is a cook-for-yourself community, food is a consistent theme in their reflections on the last six years. In an email, the McCantses said, “Every year, we have invited each of the nine floors to the head of house apartment for a home-cooked dinner. Attendance has been high and enthusiastic over all six years.” They particularly remember BC’s annual apple bake event as a showcase for the community’s “creativity, collaboration, and generosity at its best. Great food, fun, and art.”

“Anne and Bill McCants cared deeply about student well-being,” says junior Katie Fisher, the BC president. “Burton Conner residents will especially remember them for hosting floor dinners and a finals study break in their apartment, as well as their brownie recipe. This dorm will not be the same without them.”

Burton Conner House (W51) is located at 410 Memorial Drive in Cambridge, Massachusetts. It was opened in 1939 and houses more than 350 undergraduates. According to its website, BC “consists of nine floors — five on the Burton side, four on the Conner side — each of which has its own unique personality.” The floors are made up of suites — mostly coed with between four and nine residents each — that contain a bathroom and a kitchen. House amenities include lounges and conference rooms, music rooms, a snack bar, recreational table games, a weight room, barbecue pits, and elevators.

But for the McCantses, BC is about much more than the building and its contents. “This role has afforded us opportunities for one-to-one interactions with students in times of both joy and crisis, challenge and repose, that are truly unforgettable,” they wrote.

Those interested in becoming a head of house should email Judy Robinson, senior associate dean for residential education, for more information. The search process will kick off with an informal reception on Monday, Feb. 12, at 7 p.m. in BC for interested tenured faculty. Potential candidates will be able to meet current heads of house and staff to discuss this singular opportunity. A search committee of current heads of house, staff, and students will review candidate qualifications, vet potential finalists with BC residents, and make recommendations to Chancellor Cynthia Barnhart and Dean Nelson. The final selection will be made by Barnhart in time for the appointees to relocate to their new home before the fall term.

Please email Kaye Gaskins to RSVP for the reception by March 9. Those who cannot attend but would still like to apply should email a current CV and cover letter to Robinson explaining why they would like to be BC’s head of house.



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New study reveals how brain waves control working memory

MIT neuroscientists have found evidence that the brain’s ability to control what it’s thinking about relies on low-frequency brain waves known as beta rhythms.

In a memory task requiring information to be held in working memory for short periods of time, the MIT team found that the brain uses beta waves to consciously switch between different pieces of information. The findings support the researchers’ hypothesis that beta rhythms act as a gate that determines when information held in working memory is either read out or cleared out so we can think about something else.  

“The beta rhythm acts like a brake, controlling when to express information held in working memory and allow it to influence behavior,” says Mikael Lundqvist, a postdoc at MIT’s Picower Institute for Learning and Memory and the lead author of the study.

Earl Miller, the Picower Professor of Neuroscience at the Picower Institute and in the Department of Brain and Cognitive Sciences, is the senior author of the study, which appears in the Jan. 26 issue of Nature Communications.

Working in rhythm

There are millions of neurons in the brain, and each neuron produces its own electrical signals. These combined signals generate oscillations known as brain waves, which vary in frequency. In a 2016 study, Miller and Lundqvist found that gamma rhythms are associated with encoding and retrieving sensory information.

They also found that when gamma rhythms went up, beta rhythms went down, and vice versa. Previous work in their lab had shown that beta rhythms are associated with “top-down” information such as what the current goal is, how to achieve it, and what the rules of the task are.

All of this evidence led them to theorize that beta rhythms act as a control mechanism that determines what pieces of information are allowed to be read out from working memory — the brain function that allows control over conscious thought, Miller says.

“Working memory is the sketchpad of consciousness, and it is under our control. We choose what to think about,” he says. “You choose when to clear out working memory and choose when to forget about things. You can hold things in mind and wait to make a decision until you have more information.”

To test this hypothesis, the researchers recorded brain activity from the prefrontal cortex, which is the seat of working memory, in animals trained to perform a working memory task. The animals first saw one pair of objects, for example, A followed by B. Then they were shown a different pair and had to determine if it matched the first pair. A followed by B would be a match, but not B followed by A, or A followed by C. After this entire sequence, the animals released a bar if they determined that the two sequences matched.

The researchers found that brain activity varied depending on whether the two pairs matched or not. As an animal anticipated the beginning of the second sequence, it held the memory of object A, represented by gamma waves. If the next object seen was indeed A, beta waves then went up, which the researchers believe clears object A from working memory. Gamma waves then went up again, but this time the brain switched to holding information about object B, as this was now the relevant information to determine if the sequence matched.

However, if the first object shown was not a match for A, beta waves went way up, completely clearing out working memory, because the animal already knew that the sequence as a whole could not be a match.

“The interplay between beta and gamma acts exactly as you would expect a volitional control mechanism to act,” Miller says. “Beta is acting like a signal that gates access to working memory. It clears out working memory, and can act as a switch from one thought or item to another.”

A new model

Previous models of working memory proposed that information is held in mind by steady neuronal firing. The new study, in combination with their earlier work, supports the researchers’ new hypothesis that working memory is supported by brief episodes of spiking, which are controlled by beta rhythms.

“When we hold things in working memory (i.e. hold something ‘in mind’), we have the feeling that they are stable, like a light bulb that we’ve turned on to represent some thought. For a long time, neuroscientists have thought that this must mean that the way the brain represents these thoughts is through constant activity. This study shows that this isn’t the case — rather, our memories are blinking in and out of existence. Furthermore, each time a memory blinks on, it is riding on top of a wave of activity in the brain,” says Tim Buschman, an assistant professor of psychology at Princeton University who was not involved in the study.

Two other recent papers from Miller’s lab offer additional evidence for beta as a cognitive control mechanism.

In a study that recently appeared in the journal Neuron, they found similar patterns of interaction between beta and gamma rhythms in a different task involving assigning patterns of dots into categories. In cases where two patterns were easy to distinguish, gamma rhythms, carrying visual information, predominated during the identification. If the distinction task was more difficult, beta rhythms, carrying information about past experience with the categories, predominated.

In a recent paper published in the Proceedings of the National Academy of Sciences, Miller’s lab found that beta waves are produced by deep layers of the prefrontal cortex, and gamma rhythms are produced by superficial layers, which process sensory information. They also found that the beta waves were controlling the interaction of the two types of rhythms.

“When you find that kind of anatomical segregation and it’s in the infrastructure where you expect it to be, that adds a lot of weight to our hypothesis,” Miller says.

The researchers are now studying whether these types of rhythms control other brain functions such as attention. They also hope to study whether the interaction of beta and gamma rhythms explains why it is so difficult to hold more than a few pieces of information in mind at once.

“Eventually we’d like to see how these rhythms explain the limited capacity of working memory, why we can only hold a few thoughts in mind simultaneously, and what happens when you exceed capacity,” Miller says. “You have to have a mechanism that compensates for the fact that you overload your working memory and make decisions on which things are more important than others.”

The research was funded by the National Institute of Mental Health, the Office of Naval Research, and the Picower JFDP Fellowship.



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jueves, 25 de enero de 2018

Startup makes labs smarter

Although Internet-connected “smart” devices have in recent years penetrated numerous industries and private homes, the technological phenomenon has left the research lab largely untouched. Spreadsheets, individual software programs, and even pens and paper remain standard tools for recording and sharing data in academic and industry labs.

TetraScience, co-founded by Spin Wang SM ’15, a graduate of electrical engineering and computer science, has developed a data-integration platform that connects disparate types of lab equipment and software systems, in-house and at outsourced drug developers and manufacturers. It then unites the data from all these sources in the cloud for speedier and more accurate research, cost savings, and other benefits.

“Software and hardware systems [in labs] cannot communicate with each other in a consistent way,” says Wang, TetraScience’s chief technology officer, who co-founded the startup with former Harvard University postdocs Salvatore Savo and Alok Tayi. “Data flows through systems in a very fragmented manner and there are a lot of siloed data sets [created] in the life sciences. Humans must manually copy and paste information or write it down on paper, [which] is a lengthy manual process that’s error prone.”

TetraScience has developed an Internet of Things (IoT) hub that plugs into most lab equipment, including freezers, ovens, incubators, scales, pH meters, syringe pumps, and autoclaves. The hub can also continuously collect relevant data — such as humidity, temperature, gas concentration and oxygen levels, vibration, light intensity, and mass air flow — and shoot it to TetraScience’s centralized data-integration platform in the cloud. TetraScience also has custom integration methods for more complicated instruments and software.

In the cloud dashboard, researchers can monitor equipment in real time and set alerts if any equipment deviates from ideal conditions. Data appears as charts, graphs, percentages, and numbers — somewhat resembling the easily readable Google Analytics dashboard. Equipment can be tracked for usage and efficiency over time to determine if, say, a freezer is slowly warming and compromising samples. Researchers can also comb through scores of archived data, all located in one place.

“Our technology is establishing a ‘data highway’ system between different entities, software and hardware, within life sciences labs. We make facilitating data seamless, faster, more accurate, and more efficient,” says Wang, who was named to this year’s Forbes 30 Under 30 list of innovators for his work with TetraScience.

More than 70 major pharmaceutical and biotech firms, including many in Cambridge, Massachusetts, use the platform. Numerous labs at MIT and Harvard are users, as well.

Pain in the lab

For Wang and his TetraScience co-founders, building their smart solution was personal.

As a Cornell University undergraduate, Wang worked in the Cornell Semiconducting RF Lab on high-energy physics research. Frustrated by the time and effort required to manually record data, he developed his own system that connected and controlled more than 10 instruments, such as a signal generator, power meter, frequency counter, and power amplifier.

Years later, as an MIT master’s student studying microelectromechanical systems, Wang worked on sensing technologies and processing of radio frequency signals under the guidance of Professor Dana Weinstein, now at Purdue University. During his final year, he wound up at the MIT Media Lab, working on a 3-D printing project with Tayi, who had spent his academic career toiling away in materials science, chemistry, and other labs. Tayi and Savo were already conducting market research around potential opportunities for IoT in labs.

All three bonded over a shared dislike for data-collecting tools that have remained relatively unchanged in labs for a half-century. “We felt the pain of manually tracking data and not having a consistent interface for all our equipment,” Wang says.

This is especially troublesome at scale. Large pharmaceutical or biotechnology firms, for instance, can have several hundreds or thousands of instruments, all with different hardware running on different software. Humans must record data and input it manually into dozens of separate recording systems, which leads to errors. People also must be physically in a lab to control experiments. Smart labs were the new frontier, Wang, Savo, and Tayi agreed.

In 2014, the three launched TetraScience to build a platform that connected equipment and pooled data into a single place in the cloud — similar to the one Wang created at Cornell, but more advanced. Back then, they used a slightly modified Raspberry Pi as their “hub,” while they refined their software and hardware.

For early-stage startup advice, the startup turned to the Industrial Liaison Program and MIT’s Venture Mentoring Service, and leveraged MIT’s vast alumni network for feedback on their technology and business plan. “We definitely benefited from MIT,” Wang says.

Saving time and money

An early trial for the platform was with the Media Lab, where researchers used the platform to monitor not equipment, but beehives. The researchers were studying how hives could be implemented into building infrastructure and how design and materials could promote bee health. As bees are sensitive to changes in environment, the researchers needed to constantly monitor temperature and humidity around hives over several months, which would be challenging if done manually.

Using TetraScience’s platform, the researchers were captured all the necessary data for their project, without suiting up and approaching all the hives daily — saving “hundreds of hours … and 686 bee stings,” according to the startup. Testing at MIT, Wang says, “helped us gain an understanding of the industry and value proposition.”

From there, the TetraScience platform found its way into more biotech companies and into more than 60 percent of the world’s top 20 pharmaceutical companies, according to the startup. Benefits of today’s TetraScience platform include speeding up research, improving compliance, producing better-quality data and, ultimately, saving millions of dollars and countless hours of work, Wang says.

Numerous case studies, listed on the startup’s webpage, showcase the platform’s efficacy and value at major pharmaceutical firms and cancer research centers, and at Harvard and MIT.

For example, in the final stages of approval of a multibillion-dollar drug, a large pharmaceutical firm conducted an accelerated lifetime test, where any prolonged deviation from preset conditions would require restarting the experiment, at the cost of millions of dollars, weeks of unusable data, and delayed commercialization. Within a few weeks of the test’s conclusion, a major deviation in one experiment occurred late at night. Within seconds, according to the study, TetraScience’s platform detected the deviation and alerted scientists, who caught it immediately, stopping any significant damage.

The platform also offers benefits for determining equipment efficiency and usage. In a 2017 case study with another pharmaceutical firm, TetraScience monitored 70 pieces of equipment. The startup flagged 23 instruments as “heavily underused.” The firm used that data to reduce service contracts for 14 instruments and sell nine instruments, leading to improved efficiency and hundreds of thousands of dollars in savings that could be put toward more research and development. 

Although the startup’s focus is on pharmaceutical and biotechnology industries, the platform could also be used in oil and gas, brewing, and food and chemistry industries to see similar benefits. “Those industries all use similar instruments [as life science labs] and produce the same kind of data, such as monitoring the pH of beer, so we will get into those industries in the future,” Wang says.



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Study: Distinct brain rhythms and regions help us reason about categories

We categorize pretty much everything we see, and remarkably, we often achieve that feat whether the items look patently similar — such as Fuji and McIntosh apples — or they share a more abstract similarity — such as a screwdriver and a drill. A new study at MIT’s Picower Institute for Learning and Memory explains how.

“Categorization is a fundamental cognitive mechanism,” says Earl Miller, the Picower Professor in MIT’s Picower Institute for Learning and Memory and the Department of Brain and Cognitive Sciences. “It’s the way the brain learns to generalize. If your brain didn’t have this ability, you’d be overwhelmed by details of the sensory world. Every time you experienced something, if it was in different lighting or at a different angle, your brain would treat it as a brand new thing.”

In the new paper in Neuron, Miller’s lab, led by postdoc Andreas Wutz and graduate student Roman Loonis, shows that the ability to categorize based on straightforward resemblance or on abstract similarity arises from the brain’s use of distinct rhythms, at distinct times, in distinct parts of the prefrontal cortex (PFC). Specifically, when animals needed to match images that bore close resemblance, an increase in the power of high-frequency gamma rhythms in the ventral lateral PFC did the trick. When they had to match images based on a more abstract similarity, that depended on a later surge of lower-frequency beta rhythms in the dorsal lateral PFC.

Miller says those findings suggest a model of how the brain achieves category abstractions. It shows that meeting the challenge of abstraction is not merely a matter of thinking the same way but harder. Instead, a different mechanism in a different part of the brain takes over when simple, sensory comparison is not enough for us to judge whether two things belong to the same category.

By precisely describing the frequencies, locations, and the timing of rhythms that govern categorization, the findings, if replicated in humans, could prove helpful in research to understand an aspect of some autism spectrum disorders (ASD), says Miller. In ASD, categorization can be challenging for patients, especially when objects or faces appear atypical. Potentially, clinicians could measure rhythms to determine whether patients who struggle to recognize abstract similarities are employing the mechanisms differently.

Connecting the dots

To conduct the study, Wutz, Loonis, Miller, and their co-authors measured brain rhythms in key areas of the PFC associated with categorization as animals played some on-screen games. In each round, animals would see a pattern of dots — a sample from one of two different categories of configurations. Then the sample would disappear and after a delay, two choices of dot designs would appear. The subject’s task was to fix its gaze on whichever one belonged to the same category as the sample. Sometimes the right answer was evident by sheer visual resemblance, but sometimes the similarity was based on a more abstract criterion the animal could infer over successive trials. The experimenters precisely quantified the degree of abstraction based on geometric calculations of the distortion of the dot pattern compared to a category archetype.

“This study was very well-defined,” says Wutz. “It provided a mathematically correct way to distinguish something so vague as abstraction. It’s a judgment call very often, but not with the paradigm that we used.”

Gamma in the ventral PFC always peaked in power when the sample appeared, as if the animals were making a “Does this sample look like category A or not?” assessment as soon as they were shown it. Beta power in the dorsal PFC peaked during the subsequent delay period when abstraction was required, as if the animals realized that there wasn’t enough visual resemblance and deeper thought would be necessary to make the upcoming choice.

Notably, the data was rich enough to reveal several nuances about what was going on. Category information and rhythm power were so closely associated, for example, that the researchers measured greater rhythm power in advance of correct category judgments than in advance of incorrect ones. They also found that the role of beta power was not based on the difficulty of choosing a category (i.e., how similar the choices were) but specifically on whether the correct answer had a more abstract or literal similarity to the sample.

By analyzing the rhythm measurements, the researchers could even determine how the animals were approaching the categorization task. They weren’t judging whether a sample belonged to one category or the other, says Wutz. Instead they were judging whether they belonged to a preferred category or not.

“That preference was reflected in the brain rhythms,” says Wutz. “We saw the strongest effects for each animal’s preferred category.”

Tim Buschman, assistant professor in the Princeton Neuroscience Institute and Department of Psychology at Princeton University, says the study helps to explain a crucial aspect of the brain’s ability to generalize: flexibility.

“Once we see one dog bark, we instantly know that all dogs bark. However, there is a right amount to generalize; we don’t want to learn that all four-legged mammals bark,” says Buschman. “The current manuscript provides insight into how the brain flexibly modulates how much we should generalize — a little (all dogs bark) or a lot (all mammals have hair). The study provides new insight into how the brain flexibly switches between two different modes — there is a ‘bottom-up’ mode that is rooted in the more concrete representations of our senses, allowing for a little generalization; and a ‘top-down’ mode that uses higher-order brain regions to generalize more broadly.

“This study is an important first step in understanding how the brain generalizes knowledge and lays the groundwork for understanding cognitive conditions, such as autism, that impair one’s ability to generalize,” says Buschman. 

The National Institute of Mental Health funded the study, which was co-authored by graduate student Jacob Donoghue and research scientist Jefferson Roy.



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miércoles, 24 de enero de 2018

Play Labs startup accelerator announces second annual open call for submissions

Play Labs and the MIT Game Lab has announced that applications are now open for the second batch of startups within the playful technology accelerator, which will run from June through August 2018 on campus at MIT in Cambridge, Massachusetts. Startups that are accepted into Play Labs will each receive an initial investment of $20,000 in either cash or Bitcoin in return for common stock. Startups that graduate from the program and meet certain criteria will be eligible for up to $80,000 in additional funding from the Play Labs Fund and its investment partners.

Deadlines for applications are due March 15, 2018, after which time finalists will be selected and a subset of those finalists will be given offers to participate in the program. Applications are open to both MIT-affiliated startups, and startups with no MIT affiliation that wish to come to MIT for the summer to participate.

Play Labs provides mentoring, facilities, and funding for early-stage startups that utilize “playful technology.” The areas of technology for this second batch of incubated startups include:

  • Digital Currency/Blockchain: The explosion of digital currencies like Bitcoin and the underlying technology, blockchain, have created a new virtual economy and opportunities for decentralizing many industries.
  • E-sports/Video Games: Video games have moved into the competitive era, and e-sports is seen as one of the biggest opportunities for expansion.
  • Virtual Reality (VR)/Augmented Reality (AR): A big focus for the first batch of incubated startups in Play Labs, now VR and AR are categories that continue to evolve and will revolutionize many industries.
  • Artificial Intelligence/Machine Learning: Artificial intelligence and machine learning software and hardware (i.e., robotics), have advanced to the point of many practical applications.

Candidate startups may apply these technology areas into any industry, including video games, e-sports, finance, healthcare, manufacturing, and more.

As before, the program will be run by Bayview Labs and its executive director, Rizwan Virk ’92 a prolific Silicon Valley angel investor, advisor, and mentor. Virk and Bayview have been early investors in Bitcoin and blockchain startups, as well as a long list of successful gaming-related tech startups including Tapjoy, Discord, Funzio, Pocket Gems, Telltale Games, and Sliver.tv.

“MIT has been the starting point for many successful startups over the years,” says Virk. “We had a successful first batch and we are excited to see what exciting technology projects MIT students, alumni, and the greater community will come up for this second batch. We started the accelerator because a lot of focus for these areas has been on the West Coast, but I believe that the ecosystem around MIT and Boston has great talent and startup ideas in these areas.”

“When I graduated from MIT and thought of doing my first startup, I wish I had this kind of accelerator program, with support from both MIT staff and industry entrepreneurs and mentors,” says Virk. “That’s why I designed the program in this way.”

Bayview will run Play Labs in conjunction with the Seraph Group, a seed stage venture capital investment firm founded by Tuff Yen. The teams will be supported by a group a successful mentors and partners, including Rajeev Surati PhD ’99 and co-founder of Flash Communications, Photo.net, and Scalable Display Technologies, based on his PhD research at MIT. Also participating is VR@MIT, a student organization on campus dedicated to fostering VR and AR entrepreneurship at MIT.

The MIT Game Lab, a research group in MIT's Comparative Media Studies/Writing program, and Ludus, the MIT Center for Games, Learning, and Playful Media, will host and conduct the educational program for Play Labs. Teams will be given workspace on the MIT campus for the duration of the program.

“MIT students thrive on innovation and creative exploration,” says Scot Osterweil, managing director for Ludus. “We are pleased that through Play Labs we will help them move their most imaginative ideas into the realm of the possible.”

“We see tremendous opportunity to invest, support, and partner with the MIT community of outstanding people, which is why we are supporting Play Labs’ second batch,” says Tuff Yen, president of Seraph Group. “Our network of successful investors will bring valuable experience, access and resources to startups.”

Full information on the program, eligibility, and benefits can be found on the Play Labs website.



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Novel methods of synthesizing quantum dot materials

For quantum dot (QD) materials to perform well in devices such as solar cells, the nanoscale crystals in them need to pack together tightly so that electrons can hop easily from one dot to the next and flow out as current. MIT researchers have now made QD films in which the dots vary by just one atom in diameter and are organized into solid lattices with unprecedented order. Subsequent processing pulls the QDs in the film closer together, further easing the electrons’ pathway. Tests using an ultrafast laser confirm that the energy levels of vacancies in adjacent QDs are so similar that hopping electrons don’t get stuck in low-energy dots along the way.

Taken together, the results suggest a new direction for ongoing efforts to develop these promising materials for high performance in electronic and optical devices.

In recent decades, much research attention has focused on electronic materials made of quantum dots, which are tiny crystals of semiconducting materials a few nanometers in diameter. After three decades of research, QDs are now being used in TV displays, where they emit bright light in vivid colors that can be fine-tuned by changing the sizes of the nanoparticles. But many opportunities remain for taking advantage of these remarkable materials.

“QDs are a really promising underlying materials technology for energy applications,” says William Tisdale, the ARCO Career Development Professor in Energy Studies and an associate professor of chemical engineering.

QD materials pique his interest for several reasons. QDs are easily synthesized in a solvent at low temperatures using standard procedures. The QD-bearing solvent can then be deposited on a surface — small or large, rigid or flexible — and as it dries, the QDs are left behind as a solid. Best of all, the electronic and optical properties of that solid can be controlled by tuning the QDs.

“With QDs, you have all these degrees of freedom,” says Tisdale. “You can change their composition, size, shape, and surface chemistry to fabricate a material that’s tailored for your application.”

The ability to adjust electron behavior to suit specific devices is of particular interest. For example, in solar photovoltaics (PVs), electrons should pick up energy from sunlight and then move rapidly through the material and out as current before they lose their excess energy. In light-emitting diodes (LEDs), high-energy “excited” electrons should relax on cue, emitting their extra energy as light.

With thermoelectric (TE) devices, QD materials could be a game-changer. When TE materials are hotter on one side than the other, they generate electricity. So TE devices could turn waste heat in car engines, industrial equipment, and other sources into power — without combustion or moving parts. The TE effect has been known for a century, but devices using TE materials have remained inefficient. The problem: While those materials conduct electricity well, they also conduct heat well, so the temperatures of the two ends of a device quickly equalize. In most materials, measures to decrease heat flow also decrease electron flow.

“With QDs, we can control those two properties separately,” says Tisdale. “So we can simultaneously engineer our material so it’s good at transferring electrical charge but bad at transporting heat.”

Making good arrays

One challenge in working with QDs has been to make particles that are all the same size and shape. During QD synthesis, quadrillions of nanocrystals are deposited onto a surface, where they self-assemble in an orderly fashion as they dry. If the individual QDs aren’t all exactly the same, they can’t pack together tightly, and electrons won’t move easily from one nanocrystal to the next.

Three years ago, a team in Tisdale’s lab led by Mark Weidman PhD ’16 demonstrated a way to reduce that structural disorder. In a series of experiments with lead-sulfide QDs, team members found that carefully selecting the ratio between the lead and sulfur in the starting materials would produce QDs of uniform size.

“As those nanocrystals dry, they self-assemble into a beautifully ordered arrangement we call a superlattice,” Tisdale says.

Scattering electron microscope images of those superlattices taken from several angles show lined-up, 5-nanometer-diameter nanocrystals throughout the samples and confirm the long-range ordering of the QDs.

For a closer examination of their materials, Weidman performed a series of X-ray scattering experiments at the National Synchrotron Light Source at Brookhaven National Laboratory. Data from those experiments showed both how the QDs are positioned relative to one another and how they’re oriented, that is, whether they’re all facing the same way. The results confirmed that QDs in the superlattices are well ordered and essentially all the same.

“On average, the difference in diameter between one nanocrystal and another was less than the size of one more atom added to the surface,” says Tisdale. “So these QDs have unprecedented monodispersity, and they exhibit structural behavior that we hadn’t seen previously because no one could make QDs this monodisperse.”

Controlling electron hopping

The researchers next focused on how to tailor their monodisperse QD materials for efficient transfer of electrical current. “In a PV or TE device made of QDs, the electrons need to be able to hop effortlessly from one dot to the next and then do that many thousands of times as they make their way to the metal electrode,” Tisdale explains.

One way to influence hopping is by controlling the spacing from one QD to the next. A single QD consists of a core of semiconducting material — in this work, lead sulfide — with chemically bound arms, or ligands, made of organic (carbon-containing) molecules radiating outward. The ligands play a critical role — without them, as the QDs form in solution, they’d stick together and drop out as a solid clump. Once the QD layer is dry, the ligands end up as solid spacers that determine how far apart the nanocrystals are.

A standard ligand material used in QD synthesis is oleic acid. Given the length of an oleic acid ligand, the QDs in the dry superlattice end up about 2.6 nanometers apart — and that’s a problem.

“That may sound like a small distance, but it’s not,” says Tisdale. “It’s way too big for a hopping electron to get across.”

Using shorter ligands in the starting solution would reduce that distance, but they wouldn’t keep the QDs from sticking together when they’re in solution. “So we needed to swap out the long oleic acid ligands in our solid materials for something shorter” after the film formed, Tisdale says.

To achieve that replacement, the researchers use a process called ligand exchange. First, they prepare a mixture of a shorter ligand and an organic solvent that will dissolve oleic acid but not the lead sulfide QDs. They then submerge the QD film in that mixture for 24 hours. During that time, the oleic acid ligands dissolve, and the new, shorter ligands take their place, pulling the QDs closer together. The solvent and oleic acid are then rinsed off.

Tests with various ligands confirmed their impact on interparticle spacing. Depending on the length of the selected ligand, the researchers could reduce that spacing from the original 2.6 nanometers with oleic acid all the way down to 0.4 nanometers. However, while the resulting films have beautifully ordered regions — perfect for fundamental studies — inserting the shorter ligands tends to generate cracks as the overall volume of the QD sample shrinks.

Energetic alignment of nanocrystals

One result of that work came as a surprise: Ligands known to yield high performance in lead-sulfide-based solar cells didn’t produce the shortest interparticle spacing in their tests.

“Reducing that spacing to get good conductivity is necessary,” says Tisdale. “But there may be other aspects of our QD material that we need to optimize to facilitate electron transfer.”

One possibility is a mismatch between the energy levels of the electrons in adjacent QDs. In any material, electrons exist at only two energy levels — a low ground state and a high excited state. If an electron in a QD film receives extra energy — say, from incoming sunlight — it can jump up to its excited state and move through the material until it finds a low-energy opening left behind by another traveling electron. It then drops down to its ground state, releasing its excess energy as heat or light.

In solid crystals, those two energy levels are a fixed characteristic of the material itself. But in QDs, they vary with particle size. Make a QD smaller and the energy level of its excited electrons increases. Again, variability in QD size can create problems. Once excited, a high-energy electron in a small QD will hop from dot to dot — until it comes to a large, low-energy QD.

“Excited electrons like going downhill more than they like going uphill, so they tend to hang out on the low-energy dots,” says Tisdale. “If there’s then a high-energy dot in the way, it takes them a long time to get past that bottleneck.”

So the greater mismatch between energy levels — called energetic disorder — the worse the electron mobility. To measure the impact of energetic disorder on electron flow in their samples, Rachel Gilmore PhD ’17 and her collaborators used a technique called pump-probe spectroscopy — as far as they know, the first time this method has been used to study electron hopping in QDs.

QDs in an excited state absorb light differently than do those in the ground state, so shining light through a material and taking an absorption spectrum provides a measure of the electronic states in it. But in QD materials, electron hopping events can occur within picoseconds — 10-12 of a second — which is faster than any electrical detector can measure.

The researchers therefore set up a special experiment using an ultrafast laser, whose beam is made up of quick pulses occurring at 100,000 per second. Their setup subdivides the laser beam such that a single pulse is split into a pump pulse that excites a sample and — after a delay measured in femtoseconds (10-15 seconds) — a corresponding probe pulse that measures the sample’s energy state after the delay. By gradually increasing the delay between the pump and probe pulses, they gather absorption spectra that show how much electron transfer has occurred and how quickly the excited electrons drop back to their ground state.

Using this technique, they measured electron energy in a QD sample with standard dot-to-dot variability and in one of the monodisperse samples. In the sample with standard variability, the excited electrons lose much of their excess energy within 3 nanoseconds. In the monodisperse sample, little energy is lost in the same time period — an indication that the energy levels of the QDs are all about the same.

By combining their spectroscopy results with computer simulations of the electron transport process, the researchers extracted electron hopping times ranging from 80 picoseconds for their smallest quantum dots to over 1 nanosecond for the largest ones. And they concluded that their QD materials are at the theoretical limit of how little energetic disorder is possible. Indeed, any difference in energy between neighboring QDs isn’t a problem. At room temperature, energy levels are always vibrating a bit, and those fluctuations are larger than the small differences from one QD to the next.

“So at some instant, random kicks in energy from the environment will cause the energy levels of the QDs to line up, and the electron will do a quick hop,” says Tisdale.

The way forward

With energetic disorder no longer a concern, Tisdale concludes that further progress in making commercially viable QD materials will require better ways of dealing with structural disorder. He and his team tested several methods of performing ligand exchange in solid samples, and none produced films with consistent QD size and spacing over large areas without cracks. As a result, he now believes that efforts to optimize that process “may not take us where we need to go.”

What’s needed instead is a way to put short ligands on the QDs when they’re in solution and then let them self-assemble into the desired structure.

“There are some emerging strategies for solution-phase ligand exchange,” he says. “If they’re successfully developed and combined with monodisperse QDs, we should be able to produce beautifully ordered, large-area structures well suited for devices such as solar cells, LEDs, and thermoelectric systems.”

QD synthesis and spectroscopy were supported by the US Department of Energy, Office of Basic Energy Sciences. Structural studies of QD solids were supported by the MIT Energy Initiative Seed Fund Program. Mark Weidman and Rachel Gilmore were partially supported by a National Science Foundation Graduate Research Fellowship. Measurements were performed at the Center for Functional Nanomaterials at Brookhaven National Laboratory, the Cornell High Energy Synchrotron Source, and the MRSEC Shared Experimental Facilities at MIT. 

This article appeared in the Autumn 2017 issue of Energy Futures, the magazine of the MIT Energy Initiative.



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