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← The self-assembling computer chips of the future

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Showing Revision 8 created 02/27/2019 by Brian Greene.

  1. Computers used to be as big as a room.
  2. But now they fit in your pocket,
  3. on your wrist
  4. and can even be implanted
    inside of your body.
  5. How cool is that?
  6. And this has been enabled
    by the miniaturization of transistors,
  7. which are the tiny switches
    in the circuits
  8. at the heart of our computers.
  9. And it's been achieved
    through decades of development
  10. and breakthroughs
    in science and engineering
  11. and of billions of dollars of investment.
  12. But it's given us
    vast amounts of computing,
  13. huge amounts of memory
  14. and the digital revolution
    that we all experience and enjoy today.
  15. But the bad news is,

  16. we're about to hit a digital roadblock,
  17. as the rate of miniaturization
    of transistors is slowing down.
  18. And this is happening
    at exactly the same time
  19. as our innovation in software
    is continuing relentlessly
  20. with artificial intelligence and big data.
  21. And our devices regularly perform
    facial recognition or augment our reality
  22. or even drive cars down
    our treacherous, chaotic roads.
  23. It's amazing.
  24. But if we don't keep up
    with the appetite of our software,
  25. we could reach a point
    in the development of our technology
  26. where the things that we could do
    with software could, in fact, be limited
  27. by our hardware.
  28. We've all experienced the frustration
    of an old smartphone or tablet

  29. grinding slowly to a halt over time
  30. under the ever-increasing weight
    of software updates and new features.
  31. And it worked just fine
    when we bought it not so long ago.
  32. But the hungry software engineers
    have eaten up all the hardware capacity
  33. over time.
  34. The semiconductor industry
    is very well aware of this
  35. and is working on
    all sorts of creative solutions,
  36. such as going beyond transistors
    to quantum computing
  37. or even working with transistors
    in alternative architectures
  38. such as neural networks
  39. to make more robust
    and efficient circuits.
  40. But these approaches
    will take quite some time,
  41. and we're really looking for a much more
    immediate solution to this problem.
  42. The reason why the rate of miniaturization
    of transistors is slowing down

  43. is due to the ever-increasing complexity
    of the manufacturing process.
  44. The transistor used to be
    a big, bulky device,
  45. until the invent of the integrated circuit
  46. based on pure crystalline silicon wafers.
  47. And after 50 years
    of continuous development,
  48. we can now achieve
    transistor features dimensions
  49. down to 10 nanometers.
  50. You can fit more than
    a billion transistors
  51. in a single square millimeter of silicon.
  52. And to put this into perspective:
  53. a human hair is 100 microns across.
  54. A red blood cell,
    which is essentially invisible,
  55. is eight microns across,
  56. and you can place 12 across
    the width of a human hair.
  57. But a transistor, in comparison,
    is much smaller,
  58. at a tiny fraction of a micron across.
  59. You could place more than 260 transistors
  60. across a single red blood cell
  61. or more than 3,000 across
    the width of a human hair.
  62. It really is incredible nanotechnology
    in your pocket right now.
  63. And besides the obvious benefit
  64. of being able to place more,
    smaller transistors on a chip,
  65. smaller transistors are faster switches,
  66. and smaller transistors are also
    more efficient switches.
  67. So this combination has given us

  68. lower cost, higher performance
    and higher efficiency electronics
  69. that we all enjoy today.
  70. To manufacture these integrated circuits,

  71. the transistors are built up
    layer by layer,
  72. on a pure crystalline silicon wafer.
  73. And in an oversimplified sense,
  74. every tiny feature
    of the circuit is projected
  75. onto the surface of the silicon wafer
  76. and recorded in a light-sensitive material
  77. and then etched through
    the light-sensitive material
  78. to leave the pattern
    in the underlying layers.
  79. And this process has been
    dramatically improved over the years
  80. to give the electronics
    performance we have today.
  81. But as the transistor features
    get smaller and smaller,

  82. we're really approaching
    the physical limitations
  83. of this manufacturing technique.
  84. The latest systems
    for doing this patterning
  85. have become so complex
  86. that they reportedly cost
    more than 100 million dollars each.
  87. And semiconductor factories
    contain dozens of these machines.
  88. So people are seriously questioning:
    Is this approach long-term viable?
  89. But we believe we can do
    this chip manufacturing
  90. in a totally different
    and much more cost-effective way
  91. using molecular engineering
    and mimicking nature
  92. down at the nanoscale dimensions
    of our transistors.
  93. As I said, the conventional manufacturing
    takes every tiny feature of the circuit

  94. and projects it onto the silicon.
  95. But if you look at the structure
    of an integrated circuit,
  96. the transistor arrays,
  97. many of the features are repeated
    millions of times.
  98. It's a highly periodic structure.
  99. So we want to take advantage
    of this periodicity
  100. in our alternative
    manufacturing technique.
  101. We want to use self-assembling materials
  102. to naturally form the periodic structures
  103. that we need for our transistors.
  104. We do this with the materials,
  105. then the materials do the hard work
    of the fine patterning,
  106. rather than pushing the projection
    technology to its limits and beyond.
  107. Self-assembly is seen in nature
    in many different places,
  108. from lipid membranes to cell structures,
  109. so we do know it can be a robust solution.
  110. If it's good enough for nature,
    it should be good enough for us.
  111. So we want to take this naturally
    occurring, robust self-assembly
  112. and use it for the manufacturing
    of our semiconductor technology.
  113. One type of self-assemble material --

  114. it's called a block co-polymer --
  115. consists of two polymer chains
    just a few tens of nanometers in length.
  116. But these chains hate each other.
  117. They repel each other,
  118. very much like oil and water
    or my teenage son and daughter.
  119. (Laughter)

  120. But we cruelly bond them together,

  121. creating an inbuilt
    frustration in the system,
  122. as they try to separate from each other.
  123. And in the bulk material,
    there are billions of these,
  124. and the similar components
    try to stick together,
  125. and the opposing components
    try to separate from each other
  126. at the same time.
  127. And this has a built-in frustration,
    a tension in the system.
  128. So it moves around, it squirms
    until a shape is formed.
  129. And the natural self-assembled shape
    that is formed is nanoscale,
  130. it's regular, it's periodic,
    and it's long range,
  131. which is exactly what we need
    for our transistor arrays.
  132. So we can use molecular engineering

  133. to design different shapes
    of different sizes
  134. and of different periodicities.
  135. So for example, if we take
    a symmetrical molecule,
  136. where the two polymer chains
    are similar length,
  137. the natural self-assembled
    structure that is formed
  138. is a long, meandering line,
  139. very much like a fingerprint.
  140. And the width of the fingerprint lines
  141. and the distance between them
  142. is determined by the lengths
    of our polymer chains
  143. but also the level of built-in
    frustration in the system.
  144. And we can even create
    more elaborate structures

  145. if we use unsymmetrical molecules,
  146. where one polymer chain
    is significantly shorter than the other.
  147. And the self-assembled structure
    that forms in this case
  148. is with the shorter chains
    forming a tight ball in the middle,
  149. and it's surrounded by the longer,
    opposing polymer chains,
  150. forming a natural cylinder.
  151. And the size of this cylinder
  152. and the distance between
    the cylinders, the periodicity,
  153. is again determined by how long
    we make the polymer chains
  154. and the level of built-in frustration.
  155. So in other words, we're using
    molecular engineering

  156. to self-assemble nanoscale structures
  157. that can be lines or cylinders
    the size and periodicity of our design.
  158. We're using chemistry,
    chemical engineering,
  159. to manufacture the nanoscale features
    that we need for our transistors.
  160. But the ability
    to self-assemble these structures

  161. only takes us half of the way,
  162. because we still need
    to position these structures
  163. where we want the transistors
    in the integrated circuit.
  164. But we can do this relatively easily
  165. using wide guide structures that pin down
    the self-assembled structures,
  166. anchoring them in place
  167. and forcing the rest
    of the self-assembled structures
  168. to lie parallel,
  169. aligned with our guide structure.
  170. For example, if we want to make
    a fine, 40-nanometer line,
  171. which is very difficult to manufacture
    with conventional projection technology,
  172. we can manufacture
    a 120-nanometer guide structure
  173. with normal projection technology,
  174. and this structure will align three
    of the 40-nanometer lines in between.
  175. So the materials are doing
    the most difficult fine patterning.
  176. And we call this whole approach
    "directed self-assembly."

  177. The challenge with directed self-assembly
  178. is that the whole system
    needs to align almost perfectly,
  179. because any tiny defect in the structure
    could cause a transistor failure.
  180. And because there are billions
    of transistors in our circuit,
  181. we need an almost
    molecularly perfect system.
  182. But we're going to extraordinary measures
  183. to achieve this,
  184. from the cleanliness of our chemistry
  185. to the careful processing
    of these materials
  186. in the semiconductor factory
  187. to remove even the smallest
    nanoscopic defects.
  188. So directed self-assembly
    is an exciting new disruptive technology,

  189. but it is still in the development stage.
  190. But we're growing in confidence
    that we could, in fact, introduce it
  191. to the semiconductor industry
  192. as a revolutionary new
    manufacturing process
  193. in just the next few years.
  194. And if we can do this,
    if we're successful,
  195. we'll be able to continue
  196. with the cost-effective
    miniaturization of transistors,
  197. continue with the spectacular
    expansion of computing
  198. and the digital revolution.
  199. And what's more, this could even
    be the dawn of a new era
  200. of molecular manufacturing.
  201. How cool is that?
  202. Thank you.

  203. (Applause)