Friday, 11 October 2019 16:53

2019 Materials Day Poster Session winners

MIT Materials Research Laboratory 2019 Poster Session winners are Mechanical Engineering graduate student Erin Looney, Media Arts and Sciences graduate student Bianca Datta, and Materials Science and Engineering Postdoctoral Associate Michael Chon. 

The Poster Session was held immediately after the Materials Day Symposium on Oct. 9, 2019. Winners, who were selected by non-MIT affiliated attendees, each receive a $500 award.

Bianca Datta
Media Arts and Sciences graduate student

POSTER: “Simulation-based optimization towards fabrication of bio-inspired nanostructures exhibiting structural coloration.”

Datta is using simulation techniques and rapid prototyping to design surfaces that display color like butterfly wings.

Advisor: Christine Ortiz, Morris Cohen Professor of Materials Science and Engineering

Michael Chon
Postdoctoral Associate

POSTER: “High capacity CMOS-compatible thin film batteries on flexible substrates”

Chon is developing all solid-state flexible microbatteries that combine a germanium anode, a ruthenium dioxide cathode and lithium phosphorous oxynitride (LiPON) solid electrolyte. The thin film batteries can be stacked and folded or incorporated directly into integrated circuits.

Advisor: Carl V. Thompson, Stavros Salapatas Professor of Materials Science and Engineering, and Director, Materials Research Laboratory

Erin E. Looney
Mechanical Engineering graduate student

POSTER: “Machine learning-based classification of environmental conditions for PV module testing and design”

Looney simulates solar cell material operation under real world conditions by combining temperature, solar spectra and humidity data to estimate performance with 95 percent accuracy. She showed that a statistical method called a k-means algorithm can produce these results with 1,000 times fewer data inputs.

Advisor: Tonio Buonassisi, Professor of Mechanical Engineering

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 – Materials Research Laboratory
Updated October 28, 2019

Wednesday, 01 November 2017 17:43

A magical dimension

Engineering at the nanoscale opens new doors to control optical, electronic and magnetic behaviors of materials and enable new multi-functional devices

Materials Day Panel 9584 DP Web
MIT MRL External Advisory Board Chair Julia Phillips [far left] moderated the Materials Day Symposium panel on “Frontiers in Materials Research.” She was joined by [from second left] Professors Karen Gleason, Caroline Ross, Timothy Swager, and Vladimir Bulović. The session was held Wednesday, Oct. 11, 2017.

Newly discovered optical, electronic and magnetic behaviors at the nanoscale, multifunctional devices that integrate with living systems, and the predictive power of machine learning are driving innovations in materials science, a panel of MIT professors told the MIT Materials Research Laboratory [MRL] Materials Day Symposium.

“The development of new material sets is a key to the launch of new physical technologies,” Professor Vladimir Bulović, founding director of MIT.nano, said. “Once we get down to the nanoscale, we can start inducing quantum phenomena that were never quite accessible. So that scale between 1 nanometer, the typical size of a molecule, and on the order of, let’s say, 20 nanometers, that’s a magical dimension, where you can fine tune your optical, electronic and magnetic properties.”

Professor Caroline Ross, Associate Head of the Department of Materials Science and Engineering, cited a trend of harnessing nature to self assemble complex structures. “As we want to make things smaller and smaller, we need to have nature helping out,” she said. Ross noted progress on a range of new multi-functional materials that use, for example, extremely low voltage levels  to control magnetism or that use strain to control electronic properties. “All of these can enable new kinds of devices from those materials, so you can imagine devices which are smart that can have memory or logic functions, that can have analog instead of just digital type of behavior, that can work together to make smart circuits. … The difficulties of integrating those types of materials will be well paid for by the new sorts of functionality we can get from the devices we make.”

MIT MRL External Advisory Board Chair Julia Phillips moderated the Materials Day Symposium panel on Wednesday, Oct. 11, 2017. Phillips is a former Sandia National Laboratories executive.

Professor Timothy Swager, Director of the Deshpande Center, said the expectation that new medical devices, for example, are compatible with our bodies demands different requirements than previous generations of electronics. “Thinking about how we interface complex dynamic chemically reactive systems with a material is really a very important area that, I think, will continue to be of importance and many good discoveries are going to come about as result of the interest in that area,” he said.

Associate Provost and Professor Karen Gleason spoke of the growing influence of machine learning on materials advances and the potential for one-dimensional and two-dimensional materials to provide better computers and memory storage. “It’s going be incredible for materials discovery as we learn how to use machine learning to predict what materials are optimal, but there’s also a credible place for materials in making this technology grow. Now computational power and memory and databases have gotten large enough that the predictive power is actually great.”

“The biggest component is you need the data so you need all of these sensors for accurate positioning, for detection of gases, for health. People want wearables,” Gleason said. “So I think this is an enormous field with tremendous impact in many different ways that materials can play.”

Bulović said while it takes a lot of perseverance to implement a new idea on the nanoscale, “It’s important to highlight that the invention of an idea happens in a moment, that eureka moment, but to actually scale that idea up so a million people can hold it in their hands, that takes a decade sometimes, especially if it’s in the materials space. Recognition of that is important in order to support the evolution of the new ideas.”

The annual Materials Day Symposium was hosted for the first time by the MIT Materials Research Laboratory, which formed from the merger of the Materials Processing Center and the Center for Materials Science and Engineering, effective Oct. 1, 2017. The MIT MRL will work hand-in-hand with MIT.nano, the central research facility being built in the heart of the MIT campus due to open in June 2018. MIT will receive a $2.5 million gift from the Arnold and Mabel Beckman Foundation to help develop a state-of-the-art cryo-electron microscopy (cryo-EM) center to be housed at the MIT.nano facility.

“I don’t think we can underestimate the value of the tool sets in providing us the direction to what we need to do to advance life as we know it,” Bulović said. “I get struck by the example of DNA … It took 80-plus years to obtain the first inkling that there was something twisted inside our cells. Then we debated for another decade, is this thing really a twisted molecule inside our cells. If you add it all up, 80, 90 years of debate. Today that’s reduced to a couple of hours of work by one graduate student who can take a cell, pull out a nucleus, put it under a scanning tunneling microscope or cryo electron microscope and see a twisted molecule we call DNA now.”

Swager noted that biologists also will use MIT.nano. “They are going to be using the cryo-EM in the basement, so nano is not only for engineers and molecule builders. … I think that’s going to be really exciting and where that fusion leads us, who knows.”

Moderator Phillips asked the panelists what tool sets that would like to see in MIT.nano. Gleason said she would like to see chemical vapor deposition for thin polymer films. Ross said that MIT needs to be at the forefront for materials characterization tools. “We need to have the best tools to do the best work,” Ross said. She would like to see MIT.nano get the best possible electron microscope and advanced deposition tools for oxide molecular beam epitaxy and building up complex materials layer by layer. Swager said it is important for the shared facility to house tools for rapid prototyping and fabrication of devices.back to newsletter

Denis Paiste, Materials Research Laboratory
November 27, 2017

Related: Poster Highlights

Interdisciplinary materials science model offers key to progress

Thursday, 16 August 2018 15:19

Abstract

Abstract: The theme of this year’s meeting will largely be focused on imaging-enabled nanoscale research on the structure, properties and processing of materials. Invited speakers will describe new tools and methods for atomic-scale structural and chemical characterization of materials, and application of these methods to optimization of processing and properties of materials for a wide range of applications. Results from imaging-based in situ studies of vapor- and liquid-phase processes for synthesis of nanostructured materials and in situ studies of nano- and micro-scale phenomena that can be used to engineer properties of bulk materials will be presented. Development of compact high-brilliance X-ray sources that can provide synchrotron-level materials analyses with laboratory-scale systems will also be discussed. Studies of nanoscale electronic, photonic, mechanical and catalytic properties of materials will be included and discussion of prospects for development of new state-of-the-art tools and methods for imaging-based and x–ray based materials research will be featured.

We are no longer accepting registrations but you are welcome to register in person on the day of the event. Lunch will only be provided to people who pre-registered.

SPEAKERS     

Thursday, 16 August 2018 15:27

Advisory Board Meeting

The external advisory board dinner will be held on October 9, 2019. Immediately following the Materials Day Poster Session.

Location: MIT Student Center, West Lounge
Cocktails will start at 6:30pm.

The advisory board meeting will be held on October 10, 2019.

Location: Bush Room, Building 10-105
8:30am - 4:30pm



Thursday, 16 August 2018 15:20

Agenda

Machine Learning in Materials Research  

 MATERIALS DAY AGENDA

October 9, 2019
MIT, Kresge Theatre (W16)

Register

8:00am

Registration
Kresge Lobby, MIT Bldg. W16
8:45-9:00am


Welcome and Overview
Professor Carl V. Thompson
Director, Materials Research Laboratory, MIT
Session I:
9:00-9:30am

 

Keynote: 
Accelerating Materials Design and Discovery for Electric Vehicles
Dr. Brian Storey
Director, Accelerated Materials Design & Discovery, TOYOTA Research Institute
9:30-10:00am


Text and Data Mining for Material Synthesis
Associate Professor Elsa Olivetti
Department of Materials Science & Engineering, MIT

10:00-10:30am


Advancing Chemical Development Through Process Intensification, Automation, and Machine Learning
Professor Klavs F. Jensen

Departments of Chemical Engineering and Materials Science & Engineering, MIT

10:30-11:00am
BREAK
11:00-12:00pm Poster Previews: 2-minute talks by selected poster presenters

12:00-1:30pm

Lunch
Stratton Student Center, 3rd Floor

Twenty Chimneys/Mezzanine Lounge (Building W20)
Session II:
1:30-1:50pm


Computing at MIT
Professor Asu Ozdaglar

Department Head, Electrical Engineering & Computer Science, MIT
1:50-2:20pm


Machine Learning in Optics: From Spectrum Reconstruction to Metasurface Design
Associate Professor Juejun (JJ) Hu
Department of Materials Science & Engineering, MIT
2:20-2:50pm



Elastic Strain Engineering for Unprecedented Properties
Professor Ju Li

Departments of Nuclear Science & Eng. and Materials Science & Engineering, MIT


2:50-3:20pm



Learning matter: Materials Design Through Atomistic Simulations and Machine Learning
Assistant Professor Rafael Gomez-Bombarelli

Department of Materials Science & Engineering, MIT

3:20-3:30pm



Session Wrap Up
Professor Carl V. Thompson
Director, Materials Research Laboratory, MIT


3:35-5:30pm



Poster Session and Social
La Sala de Puerto Rico, 2nd Floor
Stratton Student Center (Building W20) 

5:30pm
Poster Awards
5:45pm
Adjourn
Monday, 28 October 2019 17:08

Atomic engineering

Machine learning coupled with mechanical strain and radiation nudging of atoms promise powerful new control over materials.
Ju Li Materials Day 2452 DP Web
MIT Professor Ju Li speaks at the MIT MRL Materials Day Symposium Oct. 9, 2019. Image, Denis Paiste, Materials Research Laboratory.

Exerting human will on materials atom-by-atom is an engineer’s dream. “Machine learning will help us get there,” Professor Ju Li, Battelle Energy Alliance Professor of Nuclear Science and Engineering, and Professor of Materials Science and Engineering, says. Today, his work to gain insights into improving materials is advantaged by machine learning and automated experimentation, tools that he suggests will take over much of the work of current day engineers. Li spoke at the MIT MRL Materials Day Symposium Oct. 9, 2019.

Li and colleagues first applied machine learning tools to control elastic strain, which is a combination of stretch, shear and pressure that allows a material to deform reversibly, focusing on nanoscale-sized silicon and diamond. These changes can affect the electronic and optical properties of materials, for example, strained silicon technology uses biaxial elastic strain of about 1 percent to boost electronic current flow by more than 50 percent. “With improvement in sample quality, you can stretch silicon nowadays by more than 10 percent, deeply into what I call the ultra-strength ocean,” Li says.

Research on niobium nanowires drawn inside a nickel-titanium shape memory alloy showed when this material is strained under a load, this material can undergo 6% elastic deformation reversibly up to half a million times, Li relates. Synchroton images show this is truly elastic deformation and not a phase change, he says.

“Niobium is a standard superconductor and with strain you can change its superconducting temperature,” Li says. Elastic strain in these nanowires can change the critical temperature by about 20 percent. “From an engineering point of view, if you have to use liquid helium cooling, this gives you a lot of advantage. And you can also change the critical magnetic field significantly, both the upper critical field and lower critical field.”

“With nanotechnology, we suddenly have a big explosion of samples which can sustain a large dynamic range of elastic strain in tension, in shear, in combined loading,” Li notes. But calculating these effects on materials needs to account for six different strain possibilities, making it an ideal problem to address with machine learning. “Because strain has six components that you can change, it’s difficult to visualize,” he says. This work can reveal, for example, the least-energy pathway of changes in the bandgap of a material in response to mechanical actuation.

Using machine learning and a neural network, Li was able to predict a strain pathway to turn silicon’s electronic properties from semiconducting to metallic. “You really need to be able to go far out in strain energy to be able to hit direct bandgap silicon, but if you hit that, you can make lasers and integrated photonics much more miniaturized, because you don’t need phonons to give off photons.” Li says.

The neural network also identified topological transitions of band structure at certain elastic strains, which allows the researchers to label and visualize them. These new techniques have a wide range of applications from topological quantum computing to solar cell technology. Li’s team applied them to diamond and, he says, “This is the first time we are able to get unobstructed visualization of the six-dimensional ideal strain surface of silicon and diamond.”

In earlier work, experimentalists have demonstrated that they could bend and stretch ultrafine needles of diamond without breaking it. “We can make diamond a direct bandgap material with much less energy than you need from experiment, and we can make the bandgap of diamond become that of gallium nitride,” he says.

“In collaboration with Ming Dao and Subra Suresh, we’re looking at this experiment again and we are basically finding that by judiciously choosing the direction of bending, you can make diamond to have exceedingly small bandgaps. So that has yet to be experimentally validated,” Li adds.

Another line of research focuses on guiding the well-collimated electron-beam in a transmission electron microscope to move individual atoms, such as an individual phosphorus atom on graphene. Experiments show the ability to rotate a carbon-phosphorus bond 180 degrees because of the momentum transfer from the relativistic electron to the phosphorus atom, Li says. “By changing the direction of the electron beam, we can also have the carbon-phosphorus bond rotate 90 degrees, and control clockwise versus counter-clockwise rotation. This flips the concept of radiation damage, because instead of damaging the sample, we can create precisely any atomic structure that we want.”

Using an analogy of moving a phosphorus atom to dribbling a soccer ball around a field, Li, explains, “Sometimes we actually kick out the phosphorus atom, and in that case we have to go back and pick out a new ball from the side of the field and then play again. So there is a tradeoff of throughput of atomic manipulation by electron radiation and the risk of losing the soccer ball, and we can play that game by using machine learning.”

Li continues, “The machine can learn and improve the theoretical calculations, so in the future we have this optimized balance between throughput, which we believe eventually can hit one millisecond per atom step, in other words, you can assuredly move 1,000 atomic steps in one second. And with that, we’ll be able to have what I call atomic engineering. This is the ability to exert human will onto single individual atoms, to dictate their precise location, spin, redox state, etc.”

back to newsletter Denis Paiste, Materials Research Laboratory
October 29, 2019 

Monday, 28 October 2019 18:00

Driving toward a healthier planet

Toyota Research Institute embraces machine learning to advance the switch from internal combustion engine to electric vehicles.
  Dr. Brian Storey gives the keynote address at the MIT MRL Materials Day Symposium Oct. 9, 2019. Image, Denis Paiste, Materials Research Laboratory.
Dr. Brian Storey gives the keynote address at the MIT MRL Materials Day Symposium Oct. 9, 2019. Storey directs Toyota Research Institute’s accelerated materials design initiative from its Kendall Square office in Cambridge, Mass., and is embracing machine learning to advance the switch from internal combustion engine to electric vehicles. Image, Denis Paiste, Materials Research Laboratory.

With 100 million Toyota vehicles on the planet emitting greenhouse gases at a rate roughly comparable to those of France, Toyota has set a goal of reducing all tailpipe emissions by 90 percent by the year 2050, according to Dr. Brian Storey, who directs Toyota Research Institute’s Accelerated Materials Design & Discovery program from its Kendall Square office in Cambridge, Mass. He gave the keynote address at the MIT MRL Materials Day Symposium Oct. 9, 2019.

“A rapid shift from the traditional vehicle to electric vehicles has started,” Storey says. “And we want to enable that to happen at a faster pace.”

“Our role at TRI is to develop tools for accelerating the development of emissions free vehicles,” Storey says. He says machine learning is helping to speed up those innovations, but the challenges are very great, so his team has to be a little humble about what it can actually accomplish.

Electrification is just one of four “disrupters” to the automotive industry, that are often abbreviated CASE (Connected, Autonomous, Shared, Electric). “It’s a disrupter to the industry because Toyota has decades of experience of optimizing the combustion engine,” Storey says. “We know how to do it; it’s reliable; it’s affordable; it lasts forever. Really the heart of the Toyota brand is the quality of the combustion engine and transmission.”

Storey states that as society shifts toward electrification – battery or fuel cell vehicles – new capability, technology and know-how is needed. Storey says “while Toyota has a lot of experience in these areas, we still need to move faster if we are going to make this kind of transition.”

To help with that acceleration, Toyota Research Institute is providing $10 million a year to support research of approximately 125 professors, postdocs and graduate students at 10 academic institutions. About $2 million a year of that research is being done at MIT. Storey is also a Professor of Mechanical Engineering at Olin College of Engineering.

For example, the Battery Evaluation and Early Prediction (BEEP) project, which is a TRI collaboration with MIT and Stanford, aims to expand the value of lithium-based battery systems. In experiments, many batteries are charged and discharged at the same time. “From that data alone, the charge and discharge data, we can extract features. It’s super practical because we get the data. We extract features from the data, and we can correlate those features with lifetime,” Storey explains.

The traditional way of testing whether a battery is going to last for a thousand cycles, is to cycle it for a thousand times. Storey notes that if each cycle takes one hour, one battery requires 1,000 hours of testing. “What we want to do is bring that time way back, and so our goal is to able to do it in 5, to cycle 5 times, and get a good estimate of what the battery’s lifetime would be at 1,000 cycles doing it purely from data,” Storey says.

“Our dream, which is a work in progress, is to have a system architecture that overlies all these projects and can start to tie them together. We are creating a system that’s built for machine learning from the start…”

Brian Storey, Director of Accelerated Materials Design & Discovery at Toyota Research Institute (TRI)

Published results in Nature Energy in March 2019 show just a 4.9% test error using data in classifying lithium-ion batteries from the first five charge/discharge cycles.

“This is a nice capability because it actually allows acceleration in testing,” Storey notes. “It’s using machine learning, but it’s really using it at the device scale, the ‘as-manufactured’ battery.”

The cloud-based battery evaluation software system allows TRI to collaborate easily with colleagues at MIT, Stanford and Toyota’s home base in Japan, he says.

Program researchers operate it in a closed loop, semi-autonomous way, where the computer decides and executes the next best experiment. The system finds charging policies that are better than ones that have been published in the literature, and it finds them rapidly. “The key to this is the early prediction model, because if we want to predict the lifetime, we don’t have to do the whole test.” Storey adds that the closed loop testing “pulls the scientist up a level in terms of what questions they can ask.”

TRI would like to use this closed loop battery evaluation system to optimize the first charge/discharge cycle a battery goes through, which is called formation cycling. “It’s like caring for the battery when it’s a baby,” Storey explains. “How you do those first cycles, actually sets it up for the rest of its life. It’s a real black art and how do you optimize this process?”

TRI’s long-term term goal is to improve battery durability so that, from the consumer point of view, the battery capacity never goes down. Storey emphasizes “we want the battery in the car to just last forever.”

Storey notes TRI is also conducting two other research projects, AI-Assisted Catalysis Experimentation (ACE) with CalTech to improve catalysts for fuel cell vehicles such as Toyota’s Mirai, and a materials synthesis project, mostly within TRI, to use machine-learning to identify whether or not the new materials predicted on the computer are likely to be synthesizable.

For the materials synthesis project, TRI began with the phase diagrams of materials. “You build up a network of every material you’ve got in the computational database and look at features of the network. Believing that somehow those materials are connected to other materials through the relationship in this network, provides a prediction of synthesizability,” Storey explains. “The way you can train the algorithm is by looking in the historical record of when certain materials were synthesized. You can virtually roll the clock back, pretending to know only what you knew in 1980, and use that to train your algorithm.” A report on the materials synthesis network was published in May 2019 in Nature Communications.

Brian Storey Materials Day 2308 DP Web
Dr. Brian Storey, Director of Accelerated Materials Design & Discovery at Toyota Research Institute (TRI), speaks at the MIT MRL Materials Day Symposium Oct. 9, 2019. Image, Denis Paiste, Materials Research Laboratory.

TRI is collaborating with Lawrence Berkeley National Laboratory and MIT Professor Martin Z. Bazant on a project that couples highly detailed mechanics of battery particles revealed through 4D scanning tunneling electron microscopy with a continuum model that captures larger scale materials properties. “This program figures out the reaction kinetics and thermodynamics at a continuum scale which is otherwise unknown,” Storey says.

“We’re putting our software tools online, so over the coming year, many of these tools will start becoming available,” Storey says. Hosted by Lawrence Berkeley, the Propnet materials database is already accessible to internal collaborators. Matscholar is accessible through GitHub. Both projects were funded by TRI.

“Our dream, which is a work in progress, is to have a system architecture that overlies all these projects and can start to tie them together. We are creating a system that’s built for machine learning from the start, allows for diverse data, allows for systems and atom scale measurements, and is capable of this idea of AI-driven feedback and autonomy. The idea is that you launch the system and it runs on its own, and everything lives in the cloud to enable collaboration,” Storey says.

back to newsletterDenis Paiste, Materials Research Laboratory
October 29, 2019

 

Related 
Study measures how fast humans react to road hazards​
Deep learning with point clouds
Data-driven prediction of battery cycle life before capacity degradation, Nature Energy 
Network analysis of synthesizable materials discovery 
Multi-university effort will advance materials, define the future of mobility
Monday, 29 October 2018 15:28

Improving materials from the nanoscale up

Transformative new tools to probe atomic structures in action are yielding better designs for metals, solar cells and polymers.

Powerful new combinations of X-rays, electrical probes and analytical computing are yielding insights into problems as diverse as fatigue in steel and stability in solar cells.

“Fatigue in steel is a major issue; you don’t see any changes in the shape of your material, and suddenly it fails," Assistant Professor C. Cem Taşan said during the MIT MRL Materials Day Symposium on Wednesday, Oct. 10, 2018. “We are putting a lot of effort in maintenance and safety, yet still we have devastating accidents,” he said, recalling the airline incident in April 2018 when a jet engine turbine blade broke apart and shrapnel from the engine broke a plane window fatally injuring a passenger.

“The airline company basically said that component passed all the maintenance requirements. So it was checked, and they couldn’t see any kind of fatigue cracks in it,” Taşan, the Thomas B. King Career Development Professor of Metallurgy, explained. Taşan is developing new steel and other metal alloys that are safer, stronger and lighter than those currently available.

Failure in metals is a complex mix of cracks and other changes in the microstructure caused by temperature, bending, stretching, compression and other forces, but most can survive at most one of these impacts before unleashing a cascade of subtle changes that ultimately result in failure.

Design for repair

Taşan outlined progress on a vanadium-based alloy that changes back to its original state when stress is taken away, and a new type of steel that can be transformed back to its original state when heat is applied. Stress tests to measure fatigue in Taşan’s new steel showed improvement over other steels.

Underlying these findings are new nanoscale experimental techniques that Taşan employs to identify the multiple causes of failure in metal alloys. Taşan combines energy-dispersive X-ray spectroscopy and scanning electron and transmission electron microscopes to capture data on tension, bending, compression or nanoindentation of materials. These type of microscopic measurements are called in situ techniques.

Another technique studies how a metal alloy absorbs hydrogen and its effect on the metal. For example, Taşan played movies that show how plastic strain is accommodated to two phases in a high-entropy alloy.

“These techniques allow us to see how the failure process is taking place, and we use these techniques to understand the mechanism of these failure modes and potentially repair mechanisms. Finally, we use this understanding to design new alloys that utilize these mechanisms,” Taşan said. “You are trying to design a mechanism that can be used by the material over and over and over again to deal with the same type of crack that it is facing.”

Taşan’s investigations revealed three different types of crack closure mechanisms in steel: plasticity, phase transformation and crack-surface roughness. “If I want to activate all of these crack closure mechanisms, what I need to do is design a microstructure that is metastable, nano-laminate(d) and multi-phase at same time,” he said. He said the new steel alloy successfully combines all three characteristics.

Materials Research Laboratory Director Carl V. Thompson noted that how a material is made determines its structure and its properties. These properties include mechanical, electrical, optical, magnetic and many other properties. Materials science and engineering encompasses an entire cycle from designing methods for making materials through analyzing their structure and properties, to evaluating how they perform. “Ultimately most people go through this process to make materials that perform in either a new way or in a better way for systems like automobiles, your cell phone, or medical equipment,” Thompson said.

Engineering perovskite solar cells

Silvija Gradečak, Professor in Materials Science and Engineering, addressed the promise and the problems of perovskite solar cells. Hybrid organic-inorganic perovskites, such as methyl ammonium lead iodide, are a class of materials that are named after their crystal structure. “They are potentially lightweight, flexible and inexpensive as photovoltaic devices,” Gradečak said.

However, perovskite solar devices tend to be unstable in water, oxygen exposure, UV irradiation, and under voltage biasing. As many of these changes are dynamic and happen at nanoscale, understanding the structure of these materials can be complemented with information from electrical currents. “By using the electron beam, we can mimic the condition of the electron current within the device,” she said.

Gradečak uses a technique called cathodoluminescence to probe these perovskite materials. “Our cathodoluminescence setup is unique because it enables so-called hyperspectral imaging. It means that the full optical signal is detected in each point of the complementary structural image. As the beam interacts with the sample, we are detecting light, and we do this as the electron beam moves across the sample. That is specifically important for samples that are unstable as they are irradiated with the electron beam,” she says.

This technique revealed that perovskite material examined under an electron microscope while applying a voltage to the sample for 1 minute resulted in a dramatic current increase in the material. “That also corresponds to the I/V (current/voltage) measurements outside of the scanning electron microscope that we performed,” she said. When the voltage bias is removed, the sample relaxes back to its initial state.

“What we think is really happening is that by biasing, there are ions that are moving and they agglomerate at the edges of the sample or at the grain boundaries, and after you remove the bias, they will relax back,” Gradečak said.

Work in Gradečak’s group by Olivia Hentz (PhD ’18) combined photoluminescence data with Monte Carlo simulations to extract mobility of the defects that are moving. “More interesting, and how we can apply this method, is to understand how the material’s properties are influenced by synthesis. If you synthesize the material and you change, for example, the grain size, we can think about whether these ions that are moving will have different mobilities inside of the grain versus along the grain boundaries,” Gradečak said.

Hentz found that the mobility at the grain boundaries is 1,500 times faster than in the bulk. “The ions do move in the material, they move under the biasing conditions and that mobility is very different inside of the grain and along the grain boundaries,” Gradečak said. “By engineering the material and engineering the grain size, one can influence by how much the material will be influenced during the device operation. And this result correlates with the fact that single crystalline perovskite materials are significantly more stable than polycrystalline ones.”

Transformative new tools

In the Keynote address, BP Amoco Chemical Company Senior Research Chemist Dr. Matthew Kulzick detailed new X-ray technologies and sample chambers that are yielding insights into fighting metal corrosion, improving catalytic reactions and more. “The current evolution of tools is spectacular,” he said, noting the stunning images at 20-nanometer scale showing highly localized composition of materials.

MIT Nuclear Reactor Lab Director David E. Moncton discussed advances in X-ray tubes, noting that current versions of small scale X-ray tubes are about 100 times better than those of 100 years ago. X-ray source brilliance is increasing at two times Moore’s Law, which predicted the exponential growth of transistors in silicon chips, he noted.

Still Synchroton sources such as the Advanced Photon Source a national user facility at Argonne National Laboratory, offer beam brilliance that is 12 orders of magnitude higher than X-ray tubes. “Advanced X-ray capability is the most important missing probe of matter at nano centers and materials research labs that are not located at synchrotron facilities,” he said.

Compact X-ray free-electron laser devices hold the promise of bringing synchrotron-like examination capabilities to campus research labs, Moncton said. Moncton, who was the founding director of the Advanced Photon Source, is collaborating with Associate Professor William S. Graves at Arizona State, which is home to world’s first compact X-ray free-electron laser (CXFEL).

“The emittance is very similar to a synchrotron source,” Moncton said. “If you built a compact X-ray FEL on this compact source platform, it would outperform today’s synchrotron facilities by a number of orders of magnitude.”

X-ray phase contrast imaging has also advanced microscopy, Moncton said, displaying an image showing air bubbles in the lungs of a fruit fly. Pump-probe techniques enable studies of biological proteins performing bio-chemical processes in real time.

“Having a local synchrotron-like source would be revolutionary,” Moncton said.

Less damaging microscope

Professor of Electrical Engineering Karl Berggren described his efforts to develop a new type of electron microscope based on the quantum character of electrons to improve microscopy. One of the goals is to reduce radiation damage to biological samples from imaging them.

With support from the Gordon and Betty Moore Foundation, Berggren is collaborating on this research with Professor of Physics Mark Kasevich at Stanford University in California, Professor of Physics Peter Hommelhoff at the Friedrich Alexander University, Erlangen-Nürnberg, in Germany, and Professor of Physics Pieter Kruit at the Technical University of Delft in the Netherlands. “What we’d like to do is basically try to take advantage of the counter-intuitive quantum properties of electrons,” Berggren said.

In one approach, he employs a series of electron beam splitters and mirrors to improve the performance of scanning electron microscopes. “What we’re doing now is essentially making a test bed by which we can develop all the electron optics to try to put together a machine,” Berggren said. Along the way, his group has developed a microscope that lets you image the top and bottom of a sample at the same time.

“We know that electrons at high voltage will pass through many samples with interacting with just a small phase shift,” he said. “In fact, we want to work in that limit for imaging bio molecules.” The right combination of beam splitters could reduce electron-induced damage to the sample by 100 times, he said.

Nanowire self-assembly

Dr. Frances M. Ross, formerly of the Research Division at the IBM T. J. Watson Research Center and a new arrival at the Department of Materials Science and Engineering this academic year, described her observations of nanowire growth in an electron microscope. This vapor-liquid-solid process was first described in 1964, but the atomic-level details of how the nanowires grow could not be observed until recent improvements in electron microscopy technique.

Movie shows the growth of a silicon nanowire (lower region) from a catalytic droplet of gold silicon (AuSi) liquid (dark hemisphere above). Growth takes place by rapid addition of planes of silicon atoms at the catalyst/silicon interface. The nanowire diameter is 50 nanometers and growth took place at 500oC. Video courtesy of Frances M. Ross. Reproduced from Chou et al., “Nanowire growth kinetics in aberration corrected environmental transmission electron microscopy,” Chem. Commun., 2016, 52, 5686-5689, with permission from The Royal Society of Chemistry."

Showing a movie of a silicon nanowire growing from a gold-silicon catalyst droplet, Ross said, “To grow these silicon nanowires, we just put gold on silicon and heat it up. The gold and silicon automatically form droplets, in the same way that water forms droplets on a sheet of glass.” When additional silicon is then supplied, the droplets act as a catalyst and a silicon nanowire grows from each droplet. “Nanowire growth illustrates the fact that we can get a self-assembly process that is intrinsically very simple to form a structure that can be quite complex,” Ross explained. “You can see features like the atomic level structure of the nanowire and catalyst, the effect of temperature and gas environment, and even the dynamics of the growth interface and how the catalyst really works.” The silicon nanowire grows in little jumps despite a steady flow of source material, she noted, providing detailed information on the pathways by which the atoms assemble into the nanowire.

Adding nickel to this process resulted in a nickel disilicide particle embedded in the silicon nanowire – a quantum dot. “You almost expect to see unexpected things because the movies capture every point along the way as the material evolves,” Ross said. “In situ microscopy is really the only way to get these type of detailed relations between the structure, the properties and even the catalytic activity of individual nanoscale objects.”

“We’re in a very exciting time for electron microscopy, where advances in instrumentation are helping us understand materials growth at the atomic scale,” Ross said.

Uncovering crystal structure

James LeBeau, Visiting Professor of Materials Science and Engineering, explained that scanning transmission electron microscopy provides direct imaging of atomic structure using an extremely small (< 1x10-10 m) electron probe. LeBeau uses the scanning transmission electron microscope to develop and apply new ways to characterize atomic structure of materials to understand their properties. Further, he is applying machine learning to control the microscope, using an approach similar to that used to enable self-driving cars to recognize signs and lane lines.

Beyond imaging, “we can also acquire a full chemical spectrum at every single point in our dataset. This allows us to not only directly determine which atoms are in the material, but their bonding configuration as well,” LeBeau explained. He displayed an image showing lanthanum atoms sharing a sub-lattice with strontium and aluminum sharing a sub-lattice with tantalum. “These datasets become directly interpretable. You see the chemistry,” he said.

“We can even use this data to measure the atomic scale electric field,” LeBeau said, showing an image in which the color represents the electrostatic field vector and the intensity of the color represents its magnitude. LeBeau also was able to use these techniques to uncover the particular crystal structure of ferroelectric hafnium dioxide (HfO2). The atomic scale insights are critical as hafnium dioxide is compatible with silicon processing technology, which will pave the way for new memory applications. “By combining different types of data, we can explain the origin or ferroelectricity in these films and really rule out alternative explanations,” he said.

Twenty graduate students and postdocs gave two-minute previews during the Materials Day Symposium, which was immediately followed by a Poster Session. In all, 60 presented research posters in La Sala de Puerto. The winning presenters were graduate students Vera Schroeder, Rachel C. Kurchin, Gerald J. Wang and Philipp Simons, and Postdoctoral Associate Mikhail Y. Shalaginov.

back to newsletterDenis Paiste, Materials Research Laboratory
October 29, 2018

Materials Day 2017

Bringing together researchers from different science and engineering fields promises solutions to global needs in energy, health and quality of life.

Interdisciplinary materials research holds the key to solving the existential challenges facing humanity, former Sandia National Laboratories executive Julia M. Phillips told the annual MIT Materials Research Laboratory [MRL] Materials Day Symposium on Wednesday, Oct. 11, 2017. “What is both very exciting for us as materials researchers, also a little frustrating, is that the real impact of materials occurs when they turn into something that you actually carry around in your pocket or whatever,” Phillips said.

During the second half of the 20th century, many of the technological advances that we take for granted today, such as laptop computers and smart phones, came from fundamental advances in materials research and the ability to control and make materials, she noted. Phillips, who retired from Sandia National Laboratories as Vice President and Chief Technology Officer, also serves as chair of the MRL External Advisory Board and is a member of the National Science Board.

MRL formed from the merger of the Materials Processing Center and the Center for Materials Science and Engineering, effective Oct. 1, 2017. MRL Director Carl V. Thompson noted in his introductory remarks, the appointment of Associate Professor of Materials Science and Engineering Geoffrey S.D. Beach as co-director of the MRL and principal investigator for the National Science Foundation Materials Research Science and Engineering Center.

Fueled by industrial needs and government-funded research in the post-World War II era, “Materials research was undeniably an early model for interdisciplinary research,” Phillips said. With new tools such as scanning probe microscopes to understand the structure and properties of materials, materials scientists in the last half of the 20th Century created whole new classes of materials and products, ranging from super alloys that enabled larger and more reliable jet engines to strained layer superlattices that underlie modern magnetic recording,7 lasers and infrared detectors.

Future gains will come from the ability to synthesize and control increasingly complex materials, Phillips says, noting progress in areas such as high-temperature superconductors, porous solids like metal organic frameworks, and metamaterials that generate new properties from combining biological materials, organics, ceramics and metals at near molecular scale precision in ways not found in nature. “Somewhere in the fuzzy space between molecules and materials,” Phillips notes, these newer materials have very interesting properties that are still in the process of being fully explored, and they will be exploited in the years to come. “It’s very clear to many people that these also will be transformational as we move forward,” she says.

The materials research approach, which brings together researchers from across different science and engineering fields to solve complex problems, provides a model for solving 21st Century challenges in energy, environment and sustainability; health care and medicine; vulnerability to human and natural threats; and expanding and enhancing human capability and joy. “These are exemplars, but you can see materials written all over this list, and I would posit that any comparable list you might come up with would have materials written all over it,” Phillips said. “In order to address those grand challenges, we really need to be able to treat realistically complex systems that bring together all of these disciplines from the sciences, from engineering, from the social and behavioral sciences, and arguably even from the arts.”

Progress in scientific understanding and computational modeling are accelerating researchers’ ability to predict the structure and properties of new materials before actually making them, Phillips said.

MIT faculty members Antoine Allanore, Polina Anikeeva, A. John Hart, Pablo Jarillo-Herrero, Juejun Hu, and Jennifer Rupp presented research updates on their recent work which spans a range from ultra-thin layered materials for new electronic devices and cellular level probes for the brain and spinal cord to larger scale methods for 3D printing and metals processing.

Merging 2D materials with CMOS

Associate Professor of Physics Pablo Jarillo-Herrero stacks atomically thin, two-dimensional [2D] layers of different materials to discover new properties. Jarillo-Herrero’s lab demonstrated photodetectors, solar cells and the world’s thinnest LED. With materials such as tungsten selenide [WSe2], changing the number of layers also changes their electronic properties. Although graphene itself has no bandgap, closely aligning the lattices of graphene and boron nitride opens a 30-millivolt bandgap in graphene, he said.

“You have full electronic control with gate voltages,” Jarillo-Herrero said. Using bilayer molybdenum ditelluride, which is 10,000 times thinner than a silicon solar cell, he showed in work published in Nature Nanotechnology, a photodetector just 10 nanometers thick can be integrated on a silicon photonic crystal waveguide.

“You can just stack this at the very end of your CMOS [complementary metal oxide semiconductor] processing, and you don’t have to do any extra fabrication, any extra growth, you can just slap it on top,” Jarillo-Herrero explained. “It can be made as thin as 4 nanometers, so it’s still ultra thin, and you have a high degree of control in an ultra thin platform. The whole thing is semitransparent so we can see the light go in and out.” These new devices can be operated at telecommunications wavelengths by tuning the bandgap of the material.

Phase change materials

Juejun (JJ) Hu, the Merton C. Flemings Associate Professor of Materials Science and Engineering, is reducing power consumption, shrinking device size and ramping up processing speed with innovative combinations of materials that alternate between two different solid states, or phases, such as an alloy of germanium, antimony, selenium and tellurium. These materials are the basis for nonvolatile storage, meaning their memory state is preserved even when the power is turned off. Hu collaborated with MIT Professor Jeffrey C. Grossman and former postdoc Huashan Li to identify desirable materials for these alloys from first principles calculations, and graduate materials science and engineering student Yifei Zhang did much of the experimental work.

An earlier generation of devices based on germanium, antimony and tellurium [GST] suffers from losses to light absorption by the material. To overcome this problem, Hu substituted some of the tellurium with a lighter element, selenium, creating a new four-element structure of germanium, antimony, selenium and tellurium [GSST]. “We increase the bandgap to suppress short wavelength absorption, and we actually minimize any carrier mobility to mitigate the free carrier absorption,” he explained. Switching between amorphous and crystalline states can be triggered with a laser pulse or an electrical signal.

Although the structural state switching happens on the order of 100 nanoseconds, figuring out the techniques to accomplish it took a year of work, Hu said. Specifically, he found that using materials that switch between amorphous and crystalline states allows light to be directed over two different paths and reduces power consumption. He coupled this GSST optical phase change material with silicon nitride microresonators and waveguides to show this behavior. These switches based on phase change materials can be connected in a matrix to enable variable light control on a chip. Ultimately, Hu hopes to use this technology to build re-programmable photonic integrated circuits.

New tools for brain exploration

Class of 1942 Associate Professor in Materials Science and Engineering Polina Anikeeva works at the border between synthetic devices and the nervous system. Traditional electronic devices, with hardness like a knife, can trigger a foreign-body response from brain tissue, which typically is as soft as pudding or yogurt. Working with Prof. Yoel Fink and other MIT colleagues, Anikeeva developed soft polymer-based devices to stimulate and record activity of brain and spinal cord tissue borrowing from optical fiber drawing techniques.

An early version of their multi-functional fibers included three key elements: conductive polyethylene carbon composite electrodes to record brain cell activity; a transparent polycarbonate waveguide with cyclic olefin copolymer cladding to deliver light; and microfluidic channels to deliver drugs.

“Using this structure, for the first time, we were able to record, stimulate and pharmacologically modulate neural activity,” Anikeeva said. But the device recorded activity from clusters of neurons, not individual neurons. Anikeeva and her team addressed this problem by integrating graphite into the polyethylene composite electrodes, which increased their conductivity enough to shrink them into a structure that is as thin as a human hair. The device has six electrodes, an optical waveguide and two microfluidic channels.

Yet adding graphite increased the size and hardness of the glassy polycarbonate device, so her group turned to a new process using rubbery, stretchy polymers that they then coated with a conductive metal nanowire mesh. “This mesh of conductive metal nanowires can maintain low impedance even at 100 percent strain, and it maintains its structural integrity without any changes up to 20 percent strain, which is sufficient for us to operate in the spinal cord,” Anikeeva said.

Her students implanted these nanowire-mesh coated fibers in mice, which allowed them to stimulate and record neural activity in the spinal cord. A video showed a mouse moving its hindlimb when an optical signal delivered to the lumbar spinal cord traveled down the sciatic nerve to the gastrocnemius muscle. In these experiments, the device implanted in mice showed no decline in performance a year after surgery, Anikeeva said.

More recently, Anikeeva developed iron oxide-based nanoparticles that heat up in an applied magnetic field, which can trigger a response from neurons in the brain that express ion channels that are sensitive to heat such as capsaicin receptor, the same mechanism that is triggered when we eat hot peppers. Experimenting with mice, Anikeeva injected these tiny particles deep in the brain in a section that is associated with reward. “In our lab, we have started by modeling hysteresis in magnetic nanoparticles, synthesizing a broad range of these nanomaterials by engineering iron oxide with dopants and looking at different sizes and shapes, developing power electronics and a biological tool kit to assess this process,” Anikeeva explained. “In this case, there is no external hardwire, no wires, no implants, nothing is sticking out of the brain… however, they can now perceive magnetic field.” she said. To quantify their results, the researchers measured calcium ion influx into neurons. Work is now focused on shortening the response time to a few thousandths of a second by improving the heat output of the magnetic nanoparticles.

Ceramics for Solid-State Batteries, CO2 Sensors and Memristive Computing

Jennifer L. M. Rupp, the Thomas Lord Assistant Professor of Materials Science and Engineering, presented research showing a solid lithium garnet electrolyte can lead to batteries miniaturized on an integrated circuit chip.

Safety concerns regarding lithium batteries stem from their liquid component, which serves as the electrolyte and presents a risk of catching fire in air. Replacing the liquid electrolyte with a solid one could make batteries safer, Rupp explained. Her research shows that a ceramic material made of garnet, a material that is perhaps more familiar as a gemstone, can effectively pass lithium through a battery cell, but because it is solid, can be very safe for batteries and also have the opportunity to be miniaturized to thin film architectures. This garnet is a four-element compound of lithium, lanthanum, zirconium and oxygen. “The lithium is completely encapsulated; there is no risk of inflammation,” Rupp said.

In published research, Rupp showed that pairing a lithium titanium oxide anode with a ceramic garnet electrolyte and blurring the interface between the two materials allowed much faster battery charging time for large-scale cells. Lessons learned from applying these garnet materials pointed also to a new use for carbon dioxide sensing. “We can reconfigure the electrodes to have one electrode which simply goes as a reference, and another which undergoes a chemical reaction with carbon dioxide, and we use a tracker potential to track the effective change of carbon dioxide concentration in the environment based on bulk processing,” she explained. Rupp is also developing strained multi-layer materials to improve storage for memristive memory and computing elements.

Frontier for metals at high temperature

Associate Professor of Metallurgy Antoine Allanore pointed out that from 1980 to 2010, the world almost doubled its consumption of materials, with the fastest growth in metals and minerals. Such demand is due to the formidable low cost and high productivity of materials processing. The majority of such processes involve at some stage a high temperature operation and often the molten state of matter. Developing the science and engineering of the molten state brings huge opportunities, for example heat management in high-temperature processes such as metals extraction and glass making.

Steelmaking, for example, is already a highly efficient manufacturing process, turning out rebar, coil or wires of steel at a cost less than 32 cents per kilogram [about 15 cents per pound]. “Productivity is actually the key criteria to make materials processing successful and matter at the scale of the challenge of adding 2 billion people in the next 20 years,” he said.

Allanore’s group demonstrated that tin sulfide at high temperature, about 1,130 degrees Celsius [2,066 Fahrenheit], is an effective thermoelectric generator. “We have indications that the theoretical figure of merit for some sulfides, can be up to 1 at 1,130 [degrees Celsius]. For molten copper sulfide for example, we have estimates of the thermal conductivity, the melting point, and we have a cost that is a little bit high in my opinion, but that’s the nature of the research,” Allanore said. When his group looked at existing data, they found that for many molten compounds of sulfur and a metal, such as tin, lead or nickel, the thermoelectric figure of merit, as well as the compositional phases, had never been quantified, opening a frontier for new materials science research at high temperature. “It’s actually very difficult to know what are the true properties of the liquid,” Allanore said. “I need to know if that material will have semiconductivity. I need to know if it’s going to be denser or lighter than another liquid. … We don’t actually have computational methods to predict such property for liquids at high temperature.”

To address the problem, Allanore studied the relation in high-temperature melts between transport properties, including electrical conductivity and Seebeck coefficients, and a thermodynamic property called entropy. “We’ve put together a theoretical model that connects the transport property, like thermal power, and the thermodynamic property like entropy. This is important because it works for semiconductors, it works for metallic materials and more importantly it allows to find out regions of immiscibility in liquids,” Allanore said. Immiscibility means a material in the given condition will separate into two phases that do not mix together and remain separate.

Allanore has also developed a new method for observing molten compounds such as alumina, using a floating zone furnace, which is a transparent quartz tube located at the focal distance of four lamps. “If we can do that with oxides, we would really like to do that with sulfides,” he explained, showing a picture of molten tin sulfide sitting on a graphite plate in the floating zone furnace. The wide range of temperatures and properties of molten materials, “the ultimate state of condensed matter”, allows for better heat management, higher processing temperatures and electricity harvesting or electrical control of heat flow, he said.

3D printing a new manufacturing model

Traditional manufacturing requires economies of scale, in particular, large production volumes because of the fixed costs necessary to set up the production process, but 3D printing and other additive manufacturing technologies offer an alternative of high-performance, customizable products and devices, Associate Professor of Mechanical Engineering A. John Hart said.

Additive manufacturing is already a $6 billion a year business with reach from Hollywood special effects to high-tech jet engine nozzles. “Additive manufacturing already enables a diverse collection of materials, applications, and related processes – including by extrusion of plastics, melting metals, using lasers, and by coordinated chemical reactions that essentially are done with point wise control,” Hart explained.

“We can think of accessing new spaces in terms of the value of the products we create using additive manufacturing, also generally known as 3D printing. 3D printing is reshaping the axes by which we judge the economic viability of a manufacturing process, and allowing us to access new value spaces. For instance, we can think not only about production volume, but think about advantages in complexity of geometries, and advantages by customization of products to specific markets or even individuals. In these ways, 3D printing is influencing the entire product life cycle,” Hart said.

For instance, Hart’s group studied existing 3D printers to discover how to speed up the process from about 60 minutes to just 5 to 10 minutes to print a handheld mechanical part such as a gear. Former graduate student Jamison Go [SM, 2015] led this work, Hart said, building a desktop 3D printer about the size of a small microwave oven. The system features a control system for the printhead that moves the motors to the corner; an extrusion mechanism that drives the feedstock polymer filament like a screw; and a laser that penetrates and melts the polymer.

“By combining the fast motion control, the high heat transfer, and the high force, we can overcome the limits of the existing system,” Hart explained. The new design is three to 10 times faster in build rate than existing machines. “These kinds of steps forward can also change how we think about producing objects. If you can make something fast, you can think about how you might, or how others might, work differently,” he said. He mentioned, for instance, physicians who may need to 3D print a part for an emergency medical operation, or a repair technician who could use a 3D printer rather than hold inventory of many spare parts.

Hart’s group is currently working in collaboration with Oak Ridge National Lab on algorithms for optimization of 3D printing toolpaths, and adapting his innovations to large-scale 3d printers. “We can think about upscaling these principles to high productivity systems that are not only printing small things but printing big things,” Hart said. Hart has also worked with 3D printing of cellulose, which can be used for customization of consumer products and antimicrobial devices, and is the world’s most abundant natural polymer. He co-founded the company Desktop Metal with three other MIT faculty members and Ric Fulop SL ’06, who serves as Desktop Metal’s CEO. “The company is only two years old and will soon ship its first product which enables an entirely new approach to metal 3D printing,” Hart said.

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Denis Paiste, MIT Materials Research Laboratory
October 30, 2017

Coming up in November Newsletter: Materials Day Panel Discussion and Poster Session coverage

 

 

 

Monday, 23 September 2019 11:24

Machine Learning in Materials Research

Annual MIT Materials Day Symposium highlights latest innovations on Oct. 9, 2019.

Machine learning tools are both helping to design new materials and devices and to help those devices run at their best.

MIT Associate Professor of Materials Science and Engineering Juejun (JJ) Hu
JJ HU

Optical spectrometers, for example, are devices that record Iight intensity as a function of wavelength and identify chemicals based on their response to light. MIT Associate Professor of Materials Science and Engineering Juejun (JJ) Hu, last year developed a new chip-based spectrometer that employs an algorithm which improves resolution 100 percent compared to the textbook limits, called Rayleigh limits.

“We developed an algorithm that allows us to extract the information with much better signal-to-noise ratio,” Hu explains. “We have validated the algorithm for many different kinds of spectrum.”

Unlike the conventional shape of glass lenses which are often curved, his new optical devices feature an array of specially designed optical antennas that add a phase delay to the incoming light, which enables many different functions. Hu currently is working with UMass researchers to perfect an algorithm that can screen potential designs for these devices. The algorithm can evaluate the workability of irregular shapes that go beyond conventional shapes likes circles and rectangles.

“The algorithm allows us to train it with existing data,” Hu says. “It can recognize the underlying connections between complex geometries and the electromagnetic response.” The algorithm can find hidden relations much faster than conventional full-scale simulation methods. The algorithm can also screen out potential combinations of materials and functions that just won’t work. “If you use conventional methods, you have to waste lots of time to exhaust all the possible design space and then come to this conclusion, but now our algorithm can tell you really quickly,” he says.

Hu will present his research at the MIT Materials Research Laboratory’s annual Materials Day Symposium on Wednesday, Oct. 9, in Kresge Auditorium. The Symposium runs from 8 a.m. to 3:30 p.m. and is immediately followed by a Poster Session in La Sala de Puerto Rico on the second floor of Stratton Student Center. Register here.

MIT Atlantic Richfield Associate Professor of Energy Studies Elsa A. Olivetti
ELSA OLIVETTI

Atlantic Richfield Associate Professor of Energy Studies Elsa A. Olivetti will discuss her work on an artificial-intelligence system that scours through scientific papers to deduce materials science “recipes.” Her team is currently working on experimental verification, particularly focused on catalysts materials.

“We are constantly refining and improving our system from improving overall accuracy to expanding to other parts of the paper, such as results, to other kinds of documents, such as patents,” Olivetti says.

AI can also help to improve sustainability. “If we can know better how to make new materials, we might be able to inform how to make them in a lower resource consuming way,” Olivetti says.

Keynote speaker Dr. Brian Storey, Toyota Research Institute’s Director of Accelerated Materials Design & Discovery, will discuss several collaborative projects focusing on research and development of materials for battery and fuel cell electric vehicles.

Other Materials Day speakers are: Professor Carl V. Thompson, Director, Materials Research Laboratory; Professor Klavs F. Jensen, Departments of Chemical Engineering and Materials Science & Engineering; Professor Asu Ozdaglar, Department Head, Electrical Engineering & Computer Science; Professor Ju Li, Departments of Nuclear Science & Engineering and Materials Science & Engineering; and Assistant Professor Rafael Gomez-Bombarelli, Department of Materials Science & Engineering.

MIT graduate students and postdocs will give two-minute talks on their research during a “Poster Previews” session before the lunch break. The Poster Session runs 3:35 to 5:45 p.m. with an awards presentation at 5:30 p.m.

back to newsletterDenis Paiste, Materials Research Laboratory
September 25, 2019

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