TED@Merck KGaA, Darmstadt, Germany
Karl Skjonnemand: The self-assembling computer chips of the future
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The transistors that power the phone in your pocket are unimaginably small: you can fit more than 3,000 of them across the width of a human hair. But to keep up with innovations in fields like facial recognition and augmented reality, we need to pack even more computing power into our computer chips -- and we're running out of space. In this forward-thinking talk, technology developer Karl Skjonnemand introduces a radically new way to create chips. "This could be the dawn of a new era of molecular manufacturing," Skjonnemand says.
Karl Skjonnemand - Technology developer
As a passionate technology leader, Karl Skjonnemand has a hunger for solutions to advanced technology problems. Full bio
As a passionate technology leader, Karl Skjonnemand has a hunger for solutions to advanced technology problems. Full bio
Double-click the English transcript below to play the video.
00:13
Computers used to be as big as a room.
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But now they fit in your pocket,
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on your wrist
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and can even be implanted
inside of your body.
inside of your body.
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How cool is that?
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And this has been enabled
by the miniaturization of transistors,
by the miniaturization of transistors,
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which are the tiny switches
in the circuits
in the circuits
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at the heart of our computers.
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And it's been achieved
through decades of development
through decades of development
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and breakthroughs
in science and engineering
in science and engineering
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and of billions of dollars of investment.
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But it's given us
vast amounts of computing,
vast amounts of computing,
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huge amounts of memory
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and the digital revolution
that we all experience and enjoy today.
that we all experience and enjoy today.
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But the bad news is,
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we're about to hit a digital roadblock,
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as the rate of miniaturization
of transistors is slowing down.
of transistors is slowing down.
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And this is happening
at exactly the same time
at exactly the same time
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as our innovation in software
is continuing relentlessly
is continuing relentlessly
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with artificial intelligence and big data.
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And our devices regularly perform
facial recognition or augment our reality
facial recognition or augment our reality
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or even drive cars down
our treacherous, chaotic roads.
our treacherous, chaotic roads.
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It's amazing.
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But if we don't keep up
with the appetite of our software,
with the appetite of our software,
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we could reach a point
in the development of our technology
in the development of our technology
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where the things that we could do
with software could, in fact, be limited
with software could, in fact, be limited
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by our hardware.
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We've all experienced the frustration
of an old smartphone or tablet
of an old smartphone or tablet
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grinding slowly to a halt over time
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under the ever-increasing weight
of software updates and new features.
of software updates and new features.
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And it worked just fine
when we bought it not so long ago.
when we bought it not so long ago.
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But the hungry software engineers
have eaten up all the hardware capacity
have eaten up all the hardware capacity
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over time.
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The semiconductor industry
is very well aware of this
is very well aware of this
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and is working on
all sorts of creative solutions,
all sorts of creative solutions,
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such as going beyond transistors
to quantum computing
to quantum computing
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or even working with transistors
in alternative architectures
in alternative architectures
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such as neural networks
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to make more robust
and efficient circuits.
and efficient circuits.
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But these approaches
will take quite some time,
will take quite some time,
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and we're really looking for a much more
immediate solution to this problem.
immediate solution to this problem.
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The reason why the rate of miniaturization
of transistors is slowing down
of transistors is slowing down
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is due to the ever-increasing complexity
of the manufacturing process.
of the manufacturing process.
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The transistor used to be
a big, bulky device,
a big, bulky device,
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until the invent of the integrated circuit
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based on pure crystalline silicon wafers.
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And after 50 years
of continuous development,
of continuous development,
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we can now achieve
transistor features dimensions
transistor features dimensions
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down to 10 nanometers.
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You can fit more than
a billion transistors
a billion transistors
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in a single square millimeter of silicon.
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And to put this into perspective:
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a human hair is 100 microns across.
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A red blood cell,
which is essentially invisible,
which is essentially invisible,
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is eight microns across,
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and you can place 12 across
the width of a human hair.
the width of a human hair.
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But a transistor, in comparison,
is much smaller,
is much smaller,
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at a tiny fraction of a micron across.
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You could place more than 260 transistors
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across a single red blood cell
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or more than 3,000 across
the width of a human hair.
the width of a human hair.
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It really is incredible nanotechnology
in your pocket right now.
in your pocket right now.
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And besides the obvious benefit
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of being able to place more,
smaller transistors on a chip,
smaller transistors on a chip,
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smaller transistors are faster switches,
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and smaller transistors are also
more efficient switches.
more efficient switches.
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So this combination has given us
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lower cost, higher performance
and higher efficiency electronics
and higher efficiency electronics
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that we all enjoy today.
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To manufacture these integrated circuits,
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the transistors are built up
layer by layer,
layer by layer,
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on a pure crystalline silicon wafer.
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And in an oversimplified sense,
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every tiny feature
of the circuit is projected
of the circuit is projected
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onto the surface of the silicon wafer
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and recorded in a light-sensitive material
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and then etched through
the light-sensitive material
the light-sensitive material
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to leave the pattern
in the underlying layers.
in the underlying layers.
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And this process has been
dramatically improved over the years
dramatically improved over the years
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to give the electronics
performance we have today.
performance we have today.
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But as the transistor features
get smaller and smaller,
get smaller and smaller,
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we're really approaching
the physical limitations
the physical limitations
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of this manufacturing technique.
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The latest systems
for doing this patterning
for doing this patterning
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have become so complex
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that they reportedly cost
more than 100 million dollars each.
more than 100 million dollars each.
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And semiconductor factories
contain dozens of these machines.
contain dozens of these machines.
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So people are seriously questioning:
Is this approach long-term viable?
Is this approach long-term viable?
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But we believe we can do
this chip manufacturing
this chip manufacturing
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in a totally different
and much more cost-effective way
and much more cost-effective way
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using molecular engineering
and mimicking nature
and mimicking nature
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down at the nanoscale dimensions
of our transistors.
of our transistors.
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As I said, the conventional manufacturing
takes every tiny feature of the circuit
takes every tiny feature of the circuit
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and projects it onto the silicon.
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But if you look at the structure
of an integrated circuit,
of an integrated circuit,
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the transistor arrays,
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many of the features are repeated
millions of times.
millions of times.
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It's a highly periodic structure.
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So we want to take advantage
of this periodicity
of this periodicity
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in our alternative
manufacturing technique.
manufacturing technique.
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We want to use self-assembling materials
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to naturally form the periodic structures
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that we need for our transistors.
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We do this with the materials,
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then the materials do the hard work
of the fine patterning,
of the fine patterning,
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rather than pushing the projection
technology to its limits and beyond.
technology to its limits and beyond.
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Self-assembly is seen in nature
in many different places,
in many different places,
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from lipid membranes to cell structures,
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so we do know it can be a robust solution.
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If it's good enough for nature,
it should be good enough for us.
it should be good enough for us.
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So we want to take this naturally
occurring, robust self-assembly
occurring, robust self-assembly
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and use it for the manufacturing
of our semiconductor technology.
of our semiconductor technology.
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One type of self-assemble material --
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it's called a block co-polymer --
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consists of two polymer chains
just a few tens of nanometers in length.
just a few tens of nanometers in length.
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But these chains hate each other.
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They repel each other,
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very much like oil and water
or my teenage son and daughter.
or my teenage son and daughter.
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(Laughter)
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But we cruelly bond them together,
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creating an inbuilt
frustration in the system,
frustration in the system,
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as they try to separate from each other.
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And in the bulk material,
there are billions of these,
there are billions of these,
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and the similar components
try to stick together,
try to stick together,
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and the opposing components
try to separate from each other
try to separate from each other
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at the same time.
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And this has a built-in frustration,
a tension in the system.
a tension in the system.
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So it moves around, it squirms
until a shape is formed.
until a shape is formed.
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And the natural self-assembled shape
that is formed is nanoscale,
that is formed is nanoscale,
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it's regular, it's periodic,
and it's long range,
and it's long range,
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which is exactly what we need
for our transistor arrays.
for our transistor arrays.
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So we can use molecular engineering
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to design different shapes
of different sizes
of different sizes
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and of different periodicities.
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So for example, if we take
a symmetrical molecule,
a symmetrical molecule,
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where the two polymer chains
are similar length,
are similar length,
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the natural self-assembled
structure that is formed
structure that is formed
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is a long, meandering line,
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very much like a fingerprint.
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And the width of the fingerprint lines
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and the distance between them
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is determined by the lengths
of our polymer chains
of our polymer chains
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but also the level of built-in
frustration in the system.
frustration in the system.
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And we can even create
more elaborate structures
more elaborate structures
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if we use unsymmetrical molecules,
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where one polymer chain
is significantly shorter than the other.
is significantly shorter than the other.
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And the self-assembled structure
that forms in this case
that forms in this case
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is with the shorter chains
forming a tight ball in the middle,
forming a tight ball in the middle,
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and it's surrounded by the longer,
opposing polymer chains,
opposing polymer chains,
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forming a natural cylinder.
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And the size of this cylinder
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and the distance between
the cylinders, the periodicity,
the cylinders, the periodicity,
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is again determined by how long
we make the polymer chains
we make the polymer chains
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and the level of built-in frustration.
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So in other words, we're using
molecular engineering
molecular engineering
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to self-assemble nanoscale structures
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that can be lines or cylinders
the size and periodicity of our design.
the size and periodicity of our design.
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We're using chemistry,
chemical engineering,
chemical engineering,
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to manufacture the nanoscale features
that we need for our transistors.
that we need for our transistors.
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But the ability
to self-assemble these structures
to self-assemble these structures
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only takes us half of the way,
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because we still need
to position these structures
to position these structures
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where we want the transistors
in the integrated circuit.
in the integrated circuit.
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But we can do this relatively easily
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using wide guide structures that pin down
the self-assembled structures,
the self-assembled structures,
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anchoring them in place
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and forcing the rest
of the self-assembled structures
of the self-assembled structures
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to lie parallel,
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aligned with our guide structure.
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For example, if we want to make
a fine, 40-nanometer line,
a fine, 40-nanometer line,
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which is very difficult to manufacture
with conventional projection technology,
with conventional projection technology,
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we can manufacture
a 120-nanometer guide structure
a 120-nanometer guide structure
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with normal projection technology,
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and this structure will align three
of the 40-nanometer lines in between.
of the 40-nanometer lines in between.
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So the materials are doing
the most difficult fine patterning.
the most difficult fine patterning.
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And we call this whole approach
"directed self-assembly."
"directed self-assembly."
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The challenge with directed self-assembly
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is that the whole system
needs to align almost perfectly,
needs to align almost perfectly,
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because any tiny defect in the structure
could cause a transistor failure.
could cause a transistor failure.
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And because there are billions
of transistors in our circuit,
of transistors in our circuit,
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we need an almost
molecularly perfect system.
molecularly perfect system.
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But we're going to extraordinary measures
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to achieve this,
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from the cleanliness of our chemistry
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to the careful processing
of these materials
of these materials
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in the semiconductor factory
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to remove even the smallest
nanoscopic defects.
nanoscopic defects.
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So directed self-assembly
is an exciting new disruptive technology,
is an exciting new disruptive technology,
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but it is still in the development stage.
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But we're growing in confidence
that we could, in fact, introduce it
that we could, in fact, introduce it
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to the semiconductor industry
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as a revolutionary new
manufacturing process
manufacturing process
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in just the next few years.
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And if we can do this,
if we're successful,
if we're successful,
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we'll be able to continue
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with the cost-effective
miniaturization of transistors,
miniaturization of transistors,
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continue with the spectacular
expansion of computing
expansion of computing
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and the digital revolution.
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And what's more, this could even
be the dawn of a new era
be the dawn of a new era
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of molecular manufacturing.
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How cool is that?
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Thank you.
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(Applause)
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ABOUT THE SPEAKER
Karl Skjonnemand - Technology developerAs a passionate technology leader, Karl Skjonnemand has a hunger for solutions to advanced technology problems.
Why you should listen
Karl Skjonnemand has launched several new products and built new business in different industries with novel materials. He currently leads a diverse group of R&D teams working on innovative materials for semiconductor applications.
Skjonnemand grew up overseas then returned home to the UK where he studied physics followed by a PhD in molecular electronics. Since 1999, he's worked in industrial research and development in Taiwan, Japan, USA and the UK. He's a strong believer that thought diversity within R&D creates a powerhouse for innovation.
Karl Skjonnemand | Speaker | TED.com