Traditional applications of metal-organic frameworks (MOFs) are focused on gas storage and separation, which take advantage of the inherent porosity and high surface area of these materials. The MOFs’ use in technologies that require charge transport have lagged behind, however, because MOFs are poor conductors of electricity. We show that design principles honed from decades of previous research in molecular conductors can be employed to produce MOFs with remarkable charge mobility and conductivity values that rival or surpass those of common organic semiconductors and even graphite. We further show that these, ordered, and crystalline conductors can be used for a variety of applications in energy storage, electrocatalysis, electrochromics, and selective chemiresistive sensing. Another virtually untapped area of MOF chemistry is related to their potential to mediate redox reactivity and heterogeneous catalysis through their metal nodes. We show that MOFs can be thought of as unique macromolecular ligands that give rise to unusual molecular clusters where small molecules can react in a matrix-like environment, akin to the metal binding pockets of metalloproteins. By employing a mild, highly modular synthetic method and a suite of spectroscopic techniques, we show that redox reactivity at MOF nodes can lead to the isolation and characterization of highly unstable intermediates relevant to biological and industrial catalysis, and to industrially relevant catalytic transformations that are currently performed only by homogeneous catalysts.
The birth of artificial-intelligence research as an autonomous discipline is generally thought to have been the month long Dartmouth Summer Research Project on Artificial Intelligence in 1956, which convened 10 leading electrical engineers — including MIT’s Marvin Minsky and Claude Shannon — to discuss “how to make machines use language” and “form abstractions and concepts.” A decade later, impressed by rapid advances in the design of digital computers, Minsky was emboldened to declare that “within a generation ... the problem of creating ‘artificial intelligence’ will substantially be solved.”
The problem, of course, turned out to be much more difficult than AI’s pioneers had imagined. In recent years, by exploiting machine learning — in which computers learn to perform tasks from sets of training examples — artificial-intelligence researchers have built special-purpose systems that can do things like interpret spoken language or play Atari games or drive cars using vision with great success.
But according to Tomaso Poggio, the Eugene McDermott Professor of Brain Sciences and Human Behavior at MIT, “These recent achievements have, ironically, underscored the limitations of computer science and artificial intelligence. We do not yet understand how the brain gives rise to intelligence, nor do we know how to build machines that are as broadly intelligent as we are.”
Poggio thinks that AI research needs to revive its early ambitions. “It’s time to try again,” he says. “We know much more than we did before about biological brains and how they produce intelligent behavior. We’re now at the point where we can start applying that understanding from neuroscience, cognitive science and computer science to the design of intelligent machines.”
In this talk I will focus on applying in situ transmission electron microscopy (TEM) and lab-on-a-chip to mechanistic investigations of energy materials. Recent advances in nano-manipulation, environmental TEM and MEMS have allowed us to investigate coupled mechanical and electrochemical phenomena with unprecedented spatial and temporal resolutions. For example, we can now quantitatively characterize liquid-solid and gas-solid interfaces at nanometer resolution for in situ corrosion, fatigue and hydrogen embrittlement processes. These experiments greatly complement our modeling efforts, and together they help provide insights into how materials degrade in service due to combined electrochemical-mechanical forces.
Resource scarcity, flattening yields, changing climate, and booming urban populations impose increasing limits on current food systems. The MIT Media Lab Open Agriculture Initiative is committed to driving a paradigm shift to computationally-based food systems that address environmental, economic, and social challenges. The next agricultural revolution now taking root harnesses the power of distributed food-computing across a global network of innovators and producers to foster an agile, open, and responsive food future.
In an increasingly carbon-constrained world, lignocellulosic biomass, natural gas, and carbon dioxide have emerged as attractive options to supply energy, fuels, and chemicals at scale in a cleaner and more sustainable manner. However, the unique chemical makeup of these alternative carbon sources has created daunting conversion challenges, requiring the development a new generation of robust, active, and selective catalysts. In this lecture, I will show how advanced synthesis techniques can be coupled with rigorous reactivity and characterization studies to uncover unique synergies in nanostructured catalysts.
First, the cooperativity between catalytic pairs in metalloenzyme-like microporous materials will be demonstrated. Specific examples will include the synthesis of diacids from coupling bio-derived keto acids, and the conversion of methane into acetic acid via tandem oxidation and carbonylation reactions.
Second, new developments in the use of heterometallic early transition metal carbide (TMC) nanoparticles will be described as a novel platform to replace (or drastically reduce) noble metal utilization in electro- and thermo-catalytic applications. A new method to synthesize TMCs and core-shell TMC-noble metal structures with exquisite control over composition, size, crystal phase, and purity will be demonstrated. Structure-activity descriptors can then be elucidated and used to guide the design of new catalytic materials.
We live in the era where almost everything we do is recorded somewhere. Naturally such massive amounts of social data contains wealth of information about us. This presents us with a huge opportunity to utilize it for operating businesses efficiently, making meaningful policies and better social living. In this talk, I will discuss how we can utilize social data for predicting preferences of a business's customers accurately. We will discuss such a desirable, scalable data processing system for predicting customer preferences that we have built and deployed. We will describe success stories of this technology in the retail industry.
For centuries we enjoyed light and sound as tools to manipulate, store and control the flow of information and energy. However, our need to transmit information and energy through these wave channels suffered a physical limit dictated by diffraction. For example, Young’s double slit experiments suggest that for an observer at a distance away from the two slits, one cannot distinguish these slits from one when the gap of these slits are close to wavelength of light. Can we overcome the diffraction limit by bending and folding waves, in a similar fashion to paper origami?
In this seminar, I will present our efforts to fabricate 3D complex microstructures at unprecedented dimensions. In the arena of sound waves, these structures show promise on focusing and rerouting ultrasound through broadband and highly transparent metamaterials. Recently our research effort on acoustic metamaterials has been expanded to tailoring the wavefront and energy flow of elastic waves. In the optical domain, we report our development of optical imaging probes to measure the distinct local modes in the nanostructures that promote electron-photon interaction down to layers of a few atoms thick, which promise for efficient light emission and detection. These novel metamaterials could be the foundation of broadband photo-absorbers, directional emitters, as well as compact and power-efficient devices.
An important evolution in the provision and consumption of electricity services is underway. Technological advances in information and communication technologies, demand response, distributed generation, energy storage, and advanced power electronics and control devices are creating new options for the provision of electricity services. A framework for proactive regulatory reform is needed to enable the efficient evolution of the power system, including improvements to the pricing of electricity services, incentives for distribution utilities, power sector structure, and electricity market design. With this framework in place, myriad consumers and producers of electricity services can make efficient choices based on accurate incentives reflecting the economic value of these services and their own diverse personal preferences.
Contact