Where Industry Meets Innovation

  • Contact Us
  • sign in Sign In
  • Sign in with certificate
mit campus

Resources

Search Videos

  • View All
  • ILP Videos
  • MIT Faculty Shorts
  • Tech-TV
  • Startup Exchange

Conferences Videos

  • 2017 MIT Research and Development Conference
    11.15.17
  • 2017 MIT China Conference in Shanghai
    10.25.17
  • 2017 Innovations in Management Conference
    09.27.17
  • 2017 Health Sensing & Imaging Conference
    09.19.17
  • 2017 MIT Startup Ecosystem Conference
    05.03.17
  • 2017 MIT ICT Conference
    04.12.17

Featured Videos

Loading
Please wait...

RECENT VIDEOS

552 Results | Prev | 1 | 2 | 3 | .. | 54 | Page 55 | 56 | .. | 109 | 110 | Last | Next
 

01.27.2017
36 mins
ILP Video

Extremely cost-effective semiconductor layer-transfer process via graphene & Highly uniform advanced RRAM (English)

Jeehwan Kim
Class of 1947 Career Development Assistant Professor of Mechanical Engineering
MIT Department of Mechanical Engineering
As a strategy to save the cost of expensive substrates in semiconductor processing, the technique called “layer-transfer” has been developed. In order to achieve real cost-reduction via the “layer-transfer”, the following needs to be insured: (1) Reusability of the expensive substrate, (2) Minimal substrate refurbishment step after the layer release, (3) Fast release rate, and (4) Precise control of a released interface. Although a number of layer transfer methods have been developed including chemical lift-off, optical lift-off, and mechanical lift-off, none of those three methods fully satisfies conditions listed above. In this talk, we will discuss our recent development in a “graphene-based layer-transfer” process that could fully satisfy the above requirements, where epitaxial graphene can serve as a universal seed layer to grow single-crystalline GaN, III-V, II-VI and IV semiconductor films and a release layer that allows precise and repeatable release at the graphene surface. We will further discuss about cost-effective, defect-free heterointergration of semiconductors using graphene-based layer transfers.

Lastly, I will introduce our new research activities in developing advanced RRAM devices. Resistive switching devices have attracted tremendous attention due to their high endurance, sub-nanosecond switching, long retention, scalability, low power consumption, and CMOS compatibility. RRAMs have also emerged as a promising candidate for non-Von Neumann computing architectures based on neuromorphic and machine learning systems to deal with “big data” problems such as pattern recognition from large amounts of data sets. However, currently reported RRAM devices have not shown uniform switching behaviors across the devices with high on-off ratio which holds up commercialization of RRAM-based data storages as well as demonstration of large-scale neuromorphic functions. Recently, we redesigned RRAM devices and this new device structure exhibits most of functions required for large-array memories and neuromorphic computing, which are (1) excellent retention with high endurance, (2) excellent device uniformity, (3) high on/off current ratio, and (4) current suppression in low voltage regime. I will discuss about the characterization results of this new RRAM device.
Read More

01.27.2017
32 mins
ILP Video

MIT Startup Introductions (English)

Startup:
Coventry Associates - Holosonics - TagUp - Yaxa - Poly6 - Diamond Nanotechnologies - Akselos
Startup: Coventry Associates - Holosonics - TagUp - Yaxa - Poly6 - Diamond Nanotechnologies - Akselos
Read More

01.27.2017
42 mins
ILP Video

Bioinspired Hydrogel Scaffolds, Electronics and Machines (English)

Xuanhe Zhao
Robert N Noyce Career Development Associate Professor of Mechanical Engineering
Associate Professor of Civil and Environmental Engineering
Head, Soft Active Materials Laboratory (SAMs)
MIT Department of Mechanical Engineering
While human tissues are mostly soft, wet and bioactive; machines are commonly hard, dry and biologically inert. Bridging human-machine interfaces is of imminent importance in addressing grand challenges in health, security, sustainability and joy of living facing our society in the 21st century. However, designing human-machine interfaces is extremely challenging, due to the fundamentally contradictory properties of human and machine. At MIT SAMs Lab, we propose to use tough bioactive hydrogels to bridge human-machine interfaces. On one side, bioactive hydrogels with similar physiological properties as tissues can naturally integrate with human body, playing functions such as scaffolds, catheters, drug reservoirs, and wearable devices. On the other side, the hydrogels embedded with electronic and mechanical components can control and response to external devices and signals. In the talk, I will first present a bioinspired approach and a general framework to design bioactive and robust hydrogels as the matrices for human-machine interfaces. I will then discuss large-scale manufacturing strategies to fabricate robust and bioactive hydrogels and hydrogel electronics and machines, including 3D printing. Prototypes including smart hydrogel band-aids, hydrogel robots and hydrogel circuits will be further demonstrated.
Read More

01.27.2017
24 mins
ILP Video

Artificial intelligence for Infosec: Actively learning to mimic an analyst (English)

Kalyan Veeramachaneni
Principal Research Scientist
MIT Laboratory for Information and Decision Systems
In this talk, I will present an analyst-in-the-loop security system, where analyst intuition is put together with state-of-the-art machine learning to build an end-to-end active learning system. With evolving attacks, we need a system that can continuously collect analyst input, incorporate the input and learn/adapt models that can mimic analysts. We will explore what kind of input from analysts is needed, how models can be learnt and adapted, how to utilize analyst time effectively and how to measure efficacy of such systems. Our system, called AI2, has four key features: a big data behavioral analytics platform, an ensemble of outlier detection methods, a mechanism to obtain feedback from security analysts, and a supervised learning module. When these four components are run in conjunction on a daily basis and are compared to an unsupervised outlier detection method, detection rate improves by an average of 3.41, and false positives are reduced five fold.
Read More

01.27.2017
40 mins
ILP Video

Addressing the sustainability challenge in materials extraction and processing (English)

Antoine Allanore
Thomas B King Assistant Professor of Metallurgy
MIT Department of Materials Science and Engineering
The demand for materials, particularly minerals and metals, has experienced an exceptional growth in the last decades. In parallel, the capital and environmental costs of the corresponding technologies have reached levels that are unsustainable for most countries. Increasing environmental awareness, increasing availability of clean electricity, and the foreseen global population increase are setting the stage for novel processes that match the expectations from society. In this context, recent research and development results pertinent to sustainable metal and materials extraction are presented, including oxides and sulfides processing.
Read More

MIT Partners

  • mit video
    MITVideo aggregates and curates video produced by the Institute's offices, laboratories, centers and administration.
  • tech tv
    MIT Tech TV is the video-sharing site for the MIT community.