The self-assembling computer chips of the future

Computers used to be as big as a room,

but now they fit in your pocket,

on your wrist,

and can even be implanted
inside of your body.

How cool is that?

And this has been enabled
by the miniaturization of transistors,

which are the tiny switches in the circuit
at the heart of our computers,

and it's been achieved
through decades of development

and breakthroughs
in science and engineering

and of billions of dollars of investment.

But it's given us
vast amounts of computing,

huge amounts of memory,

and the digital revolution
that we all experience and enjoy today.

But the bad news is,

we're about to hit a digital roadblock,

as the rate of miniaturization
of transistors is slowing down.

And this is happening
at exactly the same time

as our innovation in software
is continuing relentlessly

with artificial intelligence and big data,

and our devices regularly perform
facial recognition or augment our reality

or even drive cars down
our treacherous, chaotic roads.

It's amazing.

But if we don't keep up

with the appetite of our software,

we could reach a point
in the development of our technology

where the things that we
could do with software

could in fact be limited by our hardware.

And we've all experienced the frustration
of an old smartphone or tablet

grinding slowly to a halt over time

under the ever-increasing weight
of software updates and new features,

and it worked just fine
when we bought it not so long ago.

But the hungry software engineers

have eaten up all
the hardware capacity over time.

The semiconductor industry
is very well aware of this,

and is working on
all sorts of creative solutions,

such as going beyond transistors
to quantum computing

or even working with transistors
in alternative architectures

such as neural networks

to make more robust
and efficient circuits.

But these approaches
will take quite some time,

and we're really looking for a much more
immediate solution to this problem.

The reason why the rate of miniaturization
of transistors is slowing down

is due to the ever-increasing complexity
of the manufacturing process.

The transistor used to be
a big, bulky device,

until the invent of the integrated circuit

based on pure crystalline silicon wafers.

And after 50 years
of continuous development,

we can now achieve transistor
features dimensions

down to 10 nanometers.

You can fit more than
a billion transistors

in a single square millimeter of silicon.

And to put this into perspective,

a human hair is 100 microns across.

A red blood cell,
which is essentially invisible,

is eight microns across,

and you can place 12 across
the width of a human hair.

But a transistor, in comparison,
is much smaller,

at a tiny fraction of a micron across,

and you could place
more than 260 transistors

across a single red blood cell,

or more than 3,000 across
the width of a human hair.

It really is incredible nanotechnology
in your pocket right now.

And besides the obvious benefit
of being able to place

more smaller transistors on a chip,

smaller transistors are faster switches,

and smaller transistors are also
more efficient switches.

So this combination has given us
lower cost, higher performance,

and higher efficiency electronics
that we all enjoy today.

To manufacture these integrated circuits,

the transistors are
built up layer by layer

on a pure crystalline silicon wafer,

and in an oversimplified sense,

every tiny feature of the circuit

is projected onto the surface
of the silicon wafer

and recorded in
a light-sensitive material,

and then etched through
the light-sensitive material

to leave the pattern
in the underlying layers.

And this process has been
dramatically improved over the years

to give the electronics
the performance we have today.

But as the transistor features
get smaller and smaller,

we're really approaching
the physical limitations

of this manufacturing technique.

The latest systems
for doing this patterning

have become so complex

that they reportedly cost
more than 100 million dollars each,

and semiconductor factories
contain dozens of these machines.

So people are seriously questioning,
is this approach long-term viable?

But we believe we can do
this chip manufacturing

in a totally different

and much more cost-effective way

using molecular engineering

and mimicking nature
down at the nanoscale dimensions

of our transistors.

As I said, the conventional manufacturing
takes every tiny feature of the circuit

and projects it onto the silicon,

but if you look at the structure
of an integrated circuit,

the transistor arrays,

many of the features are repeated
millions of times.

It's a highly periodic structure.

So we want to take advantage
of this periodicity

in our alternative
manufacturing technique.

We want to use self-assembling materials

to naturally form the periodic structures

that we need for our transistors.

We do this with the materials,

and the materials do the hard work
of the fine patterning,

rather than pushing the projection
technology to its limits and beyond.

Self-assembly is seen in nature
in many different places,

from lipid membranes to cell structures,

so we do know it can be a robust solution.

If it's good enough for nature,
it should be good enough for us.

So we want to take
this naturally occurring,

robust self-assembly,

and use it for the manufacturing
of our semiconductor technology.

One type of self-assembled material --

it's called a block co-polymer --

consists of two polymer chains
just a few tens of nanometers in length,

but these chains hate each other.

They repel each other,

very much like oil and water
or my teenage son and daughter,

but we cruelly bond them together,

created an in-built
frustration in the system

as they try to separate from each other,

and in the bulk material,
there are billions of these,

and the similar components
try to stick together,

and the opposing components
try to separate from each other

at the same time.

And this has a built-in frustration,

a tension in the system,

so it moves around, it squirms

until a shape is formed.

And the natural self-assembled
shape that is formed

is nanoscale, it's regular, it's periodic,

and it's long range,

which is exactly what we need
for our transistor arrays.

So we can use molecular engineering

to design different shapes
of different sizes

and of different periodicities.

So for example, if we take
a symmetrical molecule,

where the two polymer chains
are similar length,

the natural self-assembled
structure that is formed

is a long, meandering line,

very much like a fingerprint,

and the width of the fingerprint lines

and the distance between them

is determined by the length
of our polymer chains,

but also the level of built-in
frustration in the system.

And we can even create
more elaborate structures

if we use unsymmetrical molecules,

where one polymer chain is
significantly shorter than the other.

And the self-assembled structure
that forms in this case

is with the shorter chains
forming a tight ball in the middle,

and it's surrounded by the longer,
opposing polymer chains,

forming a natural cylinder.

And the size of this cylinder,

and the distance between
the cylinders, the periodicity,

is again determined by how long
we make the polymer chains

and the level of built-in frustration.

So in other words, we're using
molecular engineering

to self-assemble nano-scale structures

that can be lines or cylinders,

the size and periodicity of our design.

We're using chemistry,
chemical engineering

to manufacture the nanoscale features
that we need for our transistors.

But the ability

to self-assemble these structures

only takes us half of the way,

because we still need
to position these structures

where we want the transistors
in the integrated circuit.

But we can do this relatively easily

using wide guide structures that pin down
the self-assembled structures,

anchoring them in place

and forcing the rest
of the self-assembled structures

to lie parallel,

aligned with our guide structure.

For example, if we want to make
a fine, 40-nanometer line,

which is very difficult to manufacture
with conventional projection technology,

we can manufacture
a 120-nanometer guide structure

with normal projection technology,

and this structure will align

three of the 40 nanometer guides,

aligns in between,

so the materials are doing
the most difficult fine patterning.

And we call approach
"directed self-assembly."

The challenge with directed self-assembly

is that the whole system
needs to align almost perfectly,

because any tiny defect in the structure

could cause a transistor failure,

and because there are billions
of transistors in our circuit,

we need an almost
molecularly perfect system.

But we're going to extraordinary measures

to achieve this,

from the cleanliness of our chemistry

to the careful processing
of these materials

in the semiconductor factory

to remove even the smallest,
nanoscopic defects.

So directed self-assembly
is an exciting new disruptive technology,

but it is still in the development stage,

but we're growing in confidence
that we could in fact introduce it

to the semiconductor industry

as a revolutionary new
manufacturing process

in just the next few years.

And if we can do this,
if we're successful,

we'll be able to continue

with the cost-effective
miniaturization of transistors,

continue with the spectacular
expansion of computing

and the digital revolution,

and what's more, this could even
be the dawn of a new era

of molecular manufacturing.

How cool is that?

Thank you.

(Applause)