Smart Materials Solve Contradictions - Systematic Innovation

Smart Materials Solve Contradictions:
Connecting The Right Materials Solution To The Right Market Need
Darrell Mann
Systematic Innovation, United Kingdom
Abstract
In the paper, we propose that the primary value of any smart material comes from its contradiction-resolving
abilities, and that the key to successful commercialisation of any smart material involves making the right links
between a contradiction-solving material and a market need for that contradiction to be solved. The paper is
divided into two halves. In the first half of the paper we discuss the theoretical basis behind the contradictionresolving
importance in the innovation story and show that while it is already clear that a number of smart
materials are technically ready for the market, it is rather less than clear that many markets are ready for them. In
the second half of the paper, the attention turns to a number of mini-case study examples showing how smart
material capabilities can and have been matched to real contradiction-eliminating market needs.
Keywords
TRIZ, Phase Change, Non-Linear
1.0 Introduction
The designer of a suspension system for an
automotive application faces a difficult choice
when it comes to specifying the optimum type of
damping fluid. Sometimes the requirement is for
a high viscosity; sometimes it is for low. When
that designer makes the trade-off calculations to
choose the right viscosity of fluid, they miss an
enormous innovation opportunity, since the ‘ideal’
damping fluid would possess both high and low
viscosity.
In a similar vein, the designer of a bullet-proof
vest has a difficult choice to make when making a
choice to find the optimum material. On the one
hand the material needs to be very stiff; on the
other it needs to be flexible. The ‘ideal’ material
would again possess both characteristics.
Every time one of these designers makes the
decision to ‘optimise’, they miss a significant
opportunity to create a breakthrough solution that
is ‘ideal’. Designers are not traditionally taught to
think about materials that are viscous and nonviscous,
flexible and stiff, big and small, red and
blue or any other pair of conflicting design
criteria, and as a consequence rarely think
beyond design strategies that seek to ‘optimise’
material properties.
Smart materials like electro-rheological fluids or
shape-memory alloys or thermochromic inks
present engineers and designers with the
potential for paradigm-changing design solutions.
They do this precisely because they present
ways to solve these ‘X and –X’ contradictions.
For the most part, however, these smart
materials tend to be the output of academic
research programmes. This in turn frequently
results in potentially excellent platform
technologies that are unable to make the
transition to successful commercialisation. This
happens, firstly, because university laboratories
are rarely places that allow for demonstration of
full-scale manufacture capability, and, secondly,
because there is often little ability to see or
control a particular application of the basic
platform technology. The first problem leads to
materials that are viewed by industry as ‘too
expensive’, and the second problem frequently
leads to fuzzy and unclear IP situations. One of
the biggest problems here is that the patents on a
basic materials platform technology are bound by
the same rules as patents for specific application
of the platform technology. In crude terms,
patenting the platform technology buys 17 years
of protection. In too many situations,
unfortunately, this proves to be insufficient time to
enable the patent owners to make a return from
the applications that flow from it.
The net result is a significant gulf between basic
research and commercial realisation, with neither
the industry nor industrial worlds asking the right
questions. By way of quantifying the extent of the
problem, a recent study (Reference 1) indicated
that the average return for applied university
materials research is around $3 for every $100
invested. As an investor this figure would tend to
send a message that money is better spent
elsewhere. A big part of this paper, then, is trying
to better understand the roots of the problem and
to make suggestions that might help to bridge the
gulf. We start the discussion on the industry side
of the equation, and the problem of designers
that tend to operate with an ‘optimum’ as
opposed to ‘ideal’ mindset.
2.0 Wrist Replacement
Figure 1 illustrates an x-ray of a typical wrist
replacement. Usually prompted by the onset of
chronic arthritis, wrist replacement surgery has
one of the worst track records for durability
across the range of all joints that surgeons are

able to replace. Of the 30,000 or so wrist
replacement operations carried out in the UK
every year, almost half are replacementreplacements,
where a surgeon is replacing a
previous replacement that has somehow failed.
big opportunity, then we might start making some
innovation progress.
Figure 2 illustrates what the contradiction-aware
designer might see when looking at this wrist
replacement problem:
BECAUSE
durable
replacement
joint
compressive
load
spreading
AND
AND
taper
tensile
loading
no taper
REQUIRES
Figure 2: Wrist Replacement Joint Contradiction
Figure 1: X-Ray Of Typical Wrist Replacement
One of the main problems, as may be seen from
the figure is that a lot of metal is required and
there isn’t a lot of bone around to hold it. The
problem is further complicated because, unlike,
for example, hip replacements, wrists have to
cope with a much wider range of loads. A hip
joint spends nearly all of its time in compression,
and when it is in tension, the load is limited to the
weight of the leg. A wrist joint, on the other hand,
experiences both tension and compression loads
on a regular basis. In both cases, these loads
can exceed the weight of a person’s whole body.
Although wrist replacement joint engineers might
not explicitly recognise it, they are caught in the
middle of a challenging contradiction. The main
problem area is the tapered pin inserted into the
prepared end of the radius. When the joint is in
compression (such as, say, when the patient is
doing a push-up exercise), it is desirable to
distribute the loads over as much of the taper as
possible in order to minimise the likelihood of
splintering the radius. Conversely when the joint
is in tension (such as when the patient is doing a
pull-up exercise), the taper is a bad thing,
because it becomes very easy to dis-lodge the
pin. One possible remedy to this problem, of
course, is to tell the patient they shouldn’t do pullups
or lift heavy objects anymore. Well, if that
sounds like a pretty big compromise to expect the
patient to make, it is ultimately not too far
different from the compromise that the joint
designer is also making.
By recognising that a taper is a good idea for the
compression case, an optimization-focused
design strategy now sets about ‘optimizing’ the
taper angle. If the designer was made aware that
every time he or she started conducting
sophisticated mathematical design calculations to
find the optimum anything, they were missing a
It is difficult for anyone – TRIZ-aware or
otherwise – to contemplate a problem statement
that says we want a design solution that has a
taper and doesn’t have a taper. But, of course,
that is exactly what we need to be thinking about
if we are to create some kind of a breakthrough
solution to the problem.
One of the reasons the Figure 2 template
(Reference 2) is useful, is that it offers the
problem solver several contradiction resolution
opportunities. Essentially each of the six lines in
the picture represents a conflict or contradiction.
Fail to solve one of them, and we still have five
other possibilities. Were the designer to start with
the ‘taper and no taper’ physical contradiction,
they would immediately be presented with the
usual separate-in-space, separate-in-time, etc
strategies. Recently, these strategies have been
complemented with a model that allows a
problem solver to map the eligible separation
strategies to the Inventive Principles that are
most likely to help resolve the contradiction
(Reference 3). The eventual model is illustrated
in Figure 3:
6, 8, 12, 33
38, 39
1, 28, 30
31, 40
CONDITION
SPACE
14, 17, 26, 29
2, 3, 4
5, 13, 22
24, 25, 35
11, 16,19
20, 23
7, 15, 27
34, 37
TIME
2, 3, 4
5, 13, 22
24, 25, 35
32, 36
9, 10, 18, 21
Figure 3: Mapping Physical Contradiction Resolution
Strategies To The 40 Inventive Principles
For this particular wrist replacement ‘taper-andno-taper’
problem, all three of the time, space

and condition resolution strategies appear to be
possible, and so the place to start looking for the
most relevant Inventive Principles is at the region
at the centre of the figure where all three regions
intersect. What this means is that the most likely
Principles to solve the wrist replacement problem
– based on the thousands of problem solvers that
have travelled a similar road before us – are 2, 3,
4, 5, 13, 22, 25 and 35.
Although it might not look or feel like it, Principle
35 is the one that is trying to point problem
solvers in the direction of smart material
solutions. As discussed in Reference 4, Principle
35 is simultaneously the most frequently
recommended Inventive Principle and the one
that is the least well applied by problem solvers.
When applied to the ‘taper and no taper’ problem,
it is easy to see why – simply telling a designer to
‘change one of the design parameters’ is only
slightly better than useless in the vast majority of
cases. The missing piece in the jigsaw, or rather
the biggest mis-interpretation of this Principle is
that it is often viewed as a call to optimize ‘a
parameter’, whereas in actual fact – since TRIZ is
fundamentally not about optimization – it is a call
for problem solvers to adjust parameters far
enough that a non-linear shift in performance
occurs. Figure 4 shows an example of the sort of
way in which this strategy is most effectively
applied.
Principle 35A (and D) recommended direction
Figure 4: Parameter Changes Across Phase-
Boundaries
Principle 35E
recommended
direction
Having made the connection to non-linear shifts,
it is necessary to work out what parameters are
required to be shifted. A very good way to do this
involves looking back at the Figure 2 template
and examining ‘what changes’ between the two
extremes of the contradiction. So, what changes
between tension and compression in the wrist
joint? Well, for one thing, the loading makes a
switch from negative to positive. Strain also
changes, and if strain is changing, so is the size
of the hole in the bone. Stress is changing, which
in turn means pressures are changing.
Next, we need to explore if any of these changes
are relatively different between the bone and the
metal replacement joint. The reason for this is
that any differences between the two materials
may well cause problems. Having asked this
question, it very quickly becomes apparent that
there are many differences between the
properties of bone and titanium. Not least of
which is the fact that their stress-strain
characteristics are very different. And not only
different, but different in different ways as loading
transitions from compression to tension.
Ultimately, the differences reduce down to a
difference in Poisson’s Ratio characteristics. In
actual fact, the Poisson’s Ratio behavior under
tension of bone is the exact opposite of that of
titanium and other metals: ‘stretch’ bone and, at
first, it gets fatter (i.e. it has a negative Poisson’s
Ratio). Stretch titanium, on the other hand, and it
gets thinner (i.e. it has a positive Poisson’s
Ratio).
So far so good. Having found a number of
differences between what was there in the
original healthy joint and what the surgeon is
going to replace it with, and having picked up the
idea of transitioning boundaries as a means of
solving contradictions, we are in a position to
conduct a targeted search for a ‘smart material’
solution. And, ideally, one in this case, where
under tension we achieve a negative Poisson’s
Ratio, and under compression we achieve a zero
or slightly positive Ratio.
Are there solutions to this problem? Are there
materials that are able to change their Poisson’s
Ratio properties? It doesn’t sound too likely.
Afterall, we can go to any materials textbook and
discover that every material has a nice neat,
single-value Poisson’s Ratio printed next to it.
The answer, however, turns out to be yes,
auxetic materials and/or structures, if
appropriately configured, are amply able to do
the job. Auxetic structures that are able to vary
their Poisson’s Ratio properties according to
different conditions have been observed for some
time now. Alas, so far, no-one has made the
connection between problem and potential
solution. From the designer’s perspective, we
propose here, it is because the wrong problem
has been specified. More on that subject later. In
the meantime, it will be useful to see whether it
might be possible to generalize what has
happened in this wrist replacement problem to all
types of physical contradiction problems involving
physical materials and objects:
3.0 A Generalised Model
The wrist replacement contradiction is by
definition a mechanical problem. Any smart
material solution to this problem requires the
material to respond to in different ways to
different conditions. The key word in that
sentence is ‘respond’. The important question
that goes with it is ‘what type of response does
this situation require?’
The next question that needs to be thought about
is, what is changing that can act as a stimulus to
create the desired response. The key word in that
question being ‘stimulus’. In the case of the wrist
replacement problem, the primary stimulus is
load. Changing load, therefore, acts as a stimulus
that prompts to trigger a changing Poisson’s
Ratio response. In general terms, this is a

situation where we have a mechanical stimulus
and are looking to trigger a mechanical response.
The reason for thinking about the world in this
kind of stimulus-response manner is that it allows
us to make a very simple and effective way to
classify smart material solutions. Table 1
presents the results of arranging known smart
materials in this way. Across the top of the table
is a range of different kinds of response that a
designer might wish to achieve. This is usually
the place to start when looking at the table since
it focuses on the outcome we are looking to
achieve, and therefore the type of problem we
are trying to solve. The ‘stimulus’ column down
the left hand side of the table then prompts the
user to think about what is changing (or what
could be changed) in the system in order to
trigger the desired response. The range of
different classes of stimulus is intended to remind
users that there are a number of possible
options. In the wrist replacement problem, as in
any situation where we are trying to create an
‘ideal’ solution, the idea is to make use of a
stimulus that is already present in the system.
What the list reminds us, is that if there is no
existing stimulus, there may be things we could
add to the system.
Table 1:List of known ‘intelligent’ or ‘smart’ resources:
response→ electrical magnetic optical thermal mechanical chemical
↓stimulus
electrical
magnetoelectronics,
spinelectronics,
spintronics
electrochromic,
electroluminescent,
electro-optic,
piezo-chromic,
Kerr Effect,
thermoelectric
(Peltier)
piezo-electric,
electrostrictive
electrorheological
electro-kinetic
electrolysis,
electro-chemical,
bio-electric,
electro-migration
magnetic
optical
thermal
mechanical
chemical
magnetoelectronics,
spin-electronics,
spintronics
Hall Effect
photoconductive
thermo-electric,
superconductivity,
Radiometer
Effect
pyro-electric
piezo-electric,
electrostrictive
opto-magnetic
Curie point
rheopexic,
auxetic,
shearthinning,
dilatants,
non-
Newtonian,
pseudoplastic
magnetochemical
Pockel Effect
magneto-optic,
piezo-chromic
thermochromic,
thermoluminescent
magnetostrictive
mechanochromic,
rheo-chromic
colour-change,
litmus,
luminescence
exo-thermic
endothermic
optical bistability
photothermic
optomechanical
photoacoustic
shapememory
magnetothermal
magnetostrictive,
magnetorheological
nuclear-magneticresonance,
magneto-chemical
photo-chemical,
photosynthesis,
photo-catalyst
catalysis
The best way to think of the table is as a list of keywords
that can be used to instigate and guide a more
detailed Internet or patent database search to find actual
solutions. In the wrist replacement case, the box at the
intersection between desired mechanical response and
input mechanical stimulus indicates that auxetic
materials are already an established solution in some
applications. All of the entries in the Table – which we
don’t claim to be comprehensive at this point in time,
merely ‘a hopefully ‘useful start’ – comprise materials or
materials systems where the kind of non-linear ‘phasechange’
behaviour illustrated in Figure 4 has been
achieved.
4.0 Another Example
Figure 5 illustrates an example of a rather more simple
use of one of the smart materials identified in the table.
The picture illustrates a ‘self-timing’ egg. The
incorporated smart material solves a common problem
with boiled eggs that we all like our eggs cooked a
certain way, but we often get a result we weren’t
expecting. The reason we get our eggs cooked
incorrectly more often than not is that we all cook our
eggs using an ‘optimization’ rather than ‘ideal’ mindset.
That you probably don’t recognise this fact is a good
indication of how difficult and insidious the optimizationversus-ideal
shift can be.

Applying a bit of thermochromic ink to an egg-shell on
the other hand merely needs the connection between
the solution and a real problem to be made. If the
designer gets the self-timing egg solution wrong, the
consequence for the customer is an over-cooked egg.
The joint designer, on the other hand put simply has the
responsibility for the quality of a patient’s life sitting on
his or her shoulders.
Figure 5: ‘Self-Timing’ Egg
We have all of us thought about the egg problem as an
optimization problem because we all know how long we
like our eggs cooked for. Alas, we have all remembered
one (optimized) number (‘a four minute egg’), when of
course, no two eggs are the same. What the self-timing
egg solution does is effectively says, wouldn’t it be nice
if my specific egg in my specific pan ‘tells me’ how
cooked it is.
The desired response, thinking to Table 1 is ‘tells me’.
The table presents a number of possibilities here. Most
likely the simplest of those possibilities, and certainly the
choice made by the owners of the Figure 5 solution, is
optical’. The next question, then, is what are the
available stimuli that might trigger the desired response.
Again, as with the wrist replacement problem, we need
to look at what is changing in the system. Again as far
as the owners of the solution were concerned, the
simplest and most obvious change is in the temperature
of the egg.
There is a rather splendid quotation in John Naisbitt’s
latest book (Reference 5), ‘don’t get so far ahead of the
parade that no-one knows you’re in the parade
anymore’. This quote gets right to the heart of the
scientist’s dilemma in the world of smart materials. If the
basic patent on a platform material technology protect
your IP for 17 years (there are various tricks and
strategies that can be applied to extend this period, but,
for argument’s sake we will stay with this number since it
doesn’t significantly alter the form or extent of the
dilemma). The moment patents are filed, the clock is
ticking in terms of commercialising and achieving a
return on the investment that created the basic material.
This means that unless applications that can be brought
to market well inside the 17 year window, the basic
material technology has limited if any value.
Thermochromic inks are fundamentally simple and
inexpensive, so their transition to market for a host of
applications has been relatively simple. Despite many
years of effort on auxetic materials, looking at the other
end of the spectrum, there are still virtually no
commercialised applications. Despite the often profound
benefits they present to designers in a host of situations.
Perhaps a good example of an organisation ‘getting it
right’ is Dow Corning and the ‘Active Protection System’
(APS) material solution spun out of research at Imperial
College in London – Figure 6.
Look up optical response from thermal stimulus in Table
1, and the first answer in the list of possibilities is
thermochromic. Which is precisely the solution adopted
by the self-timing egg inventors. Or rather, almost (as
ever, there is always a ‘yes, but’) because what makes
the solution especially powerful is that it contains two
subtly different thermochromic inks, each with a slightly
different colour change trigger temperature. Hence, the
word ‘soft’ (as shown in the Figure) is triggered at one
temperature, and the word ‘hard’ is triggered at another,
slightly higher temperature.
5.0 From The Material Scientist’s Perspective
In many ways the self-timing egg and the wrist
replacement joint cases provide two ends of a spectrum
as far as the materials scientist is concerned. In the wrist
replacement case, the medical devices industry may
well be guilty of defining the wrong problem, but one of
the reasons they have been thinking in optimization
rather than contradiction-solving terms is that they know
how difficult it is to prove to the regulatory authorities
that the solutions they are proposing are safe. Tweaking
the shape of a titanium pin is a far easier thing to prove
is safe than some new form or structure of titanium.
Proving a new material is safe can involve several years
of expensive validation testing.
Figure 6: Dow-Corning Active Protection System
APS is a material system that is flexible under low
loading conditions (top-left part of the figure), but which
becomes very stiff when subjected to a high impulse
load (top right). In terms of Table 1, APS is, like the
afore-mentioned auxetics, a material that achieves a
mechanical response to a mechanical stimulus. The
material is in fact a very elegant example of a shearthickening
dilatant silicone coating.
The material has a potential role to play in any situation
where the ‘flexible and stiff’ contradiction is present.
Having patented the basic platform technology the race
is now on to find appropriate applications for the
technology. Being aware of the contradiction being

solved has allowed the researchers to target a number
of possible applications, the ultimate of which currently
appears to be in things like bullet-proof vests.
Proving that the material is suitable for such a
demanding application, of course, requires time and
significant resources. A very good strategy therefore is
to identify shorter-term niche applications. A good
example here – and perhaps a poster-child
demonstration of just how hard the whole innovation
timing task is – is the application in shin-pads for soccer
players.
Making a few thousand shin-guards doesn’t sound like a
great reason for investing in the productionisation of the
APS material, but what it may well do very admirably is
provide a very high profile advertisement to let others in
other fields know about the material. Plus it provides for
the acquisition of real world data on the durability and
effectiveness of the material – information that will be
vital in supplying the necessary evidence that will be
required by the regulatory bodies for the more
challenging applications of the material.
This author knows nothing of the actual Dow Corning
strategy for APS. We do, however, work with a number
of universities struggling with the issue of successfully
commercialising their smart material platform technology
research. There can never be a simple answer to the
problem. But what can be said with certainty is that the
problem almost always has a contradiction at its heart,
and that, as a consequence, thanks to the TRIZ
research, someone, somewhere will already have
solved the contradiction. Figure 7, finally, highlights one
of the frequently used solutions to the commercialisation
contradiction:
initial platform technology
patent application
initial high value niches…
..support mainstream
applications…
17 years
…and fund research to create
new platform technology patents
(which in turn extend the 17 year window)
Figure 7: Smart Material Innovation Timing
Everything in this picture stems from the 17 years that
the original patents ‘buy’. (An immediate alternative that
emerges here is for universities to consider not
patenting, but rather keep their smart material
formulations a trade-secret until such times as the first
commercial possibilities are close to fruition.) In simple
terms, if the patent game is going to be played, the aim
is to generate revenues that pay for the research that in
turn permit new and better platform patents to be
constructed, which in turn, then keep moving the 17 year
time window far enough into the future that the
mainstream applications have sufficient time to get to
the market and begin generating the revenues that will
pay for the pensions of all involved.
6.0 Putting It All Together
The paper has discussed the gulf between smart
material solutions and successful commercial
exploitation. The gulf exists because both materials
scientists and designers and engineers frequently come
to the story with the wrong mindset.
Designers and engineers need to begin thinking about
contradiction-solving as a part of their job. They also
need assistance to make it easy to find possible
candidate solutions to the contradictions they find. Table
1 of this paper is intended to act as a first step towards
making a more direct connection between contradiction
type and available solutions.
For materials scientists, the challenge is more about
managing the transition from basic material technology
to successful commercialisation. As ever, all dilemmas
are contradictions, and in turn all contradictions can be
solved. The key to their resolution in the case of smart
materials has a lot to do with finding sufficient high-value
niche applications that will generate sufficient revenues
to enable the research that will in turn open up the
mainstream applications.
7.0 References
1) Graff, G.D., ‘Managing University And Government
IP’, Commercialisation and Technology Transfer
Seminar, ‘Leveraging IP For Wealth Creation’,
Kuala Lumpur, December 2007.
2) Mann, D.L., ‘Evaporating Contradictions: Physical
And/Or Technical’, TRIZ Journal, March 2007.
3) Systematic Innovation E-Zine, ‘Re-Thinking The
Physical Contradiction Solution Strategies’, Issue
76, July 2008.
4) Systematic Innovation E-Zine, ‘Effective Use Of
Principle 35’, Issue 58, January 2007.
5) Naisbitt, J., ‘Mindset: Reset Your Thinking And See
The Future’, Collins, 2007.
www.systematic-innovation.com