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Cite This: Langmuir 2019, 35, 13182−13188
pubs.acs.org/Langmuir
Neuromorphic Liquid Marbles with Aqueous Carbon Nanotube
Cores
Richard Mayne,*,†,‡ Thomas C. Draper,‡ Neil Phillips,‡ James G. H. Whiting,§,∥,‡
Roshan Weerasekera,§,∥ Claire Fullarton,†,‡ Ben P. J. de Lacy Costello,†,‡ and Andrew Adamatzky‡
Department of Applied Sciences, Faculty of Health and Applied Sciences, ‡Unconventional Computing Group, Faculty of the
Environment and Technology, §Department of Engineering Design and Mathematics, Faculty of the Environment and Technology,
and ∥Health Technology Hub, University of the West of England, Frenchay Campus, Bristol BS16 1QY, U.K.
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†
S Supporting Information
*
ABSTRACT: Neuromorphic computing devices attempt to
emulate features of biological nervous systems through
mimicking the properties of synapses toward implementing
the emergent properties of their counterparts, such as
learning. Inspired by recent advances in the utilization of
liquid marbles (LMs, microliter quantities of fluid coated in
hydrophobic powder) for the creation of unconventional
computing devices, we describe the development of LMs with
neuromorphic properties through the use of copper coatings and 1.0 mg mL−1 carbon nanotube (CNT)-containing fluid cores.
Experimentation was performed through sandwiching the LMs between two cup-style electrodes and stimulating them with
repeated dc pulses at 3.0 V. Our results demonstrate that “entrainment” of CNT-filled copper LMs via periodic pulses can cause
their electrical resistance to rapidly switch between high to low resistance profiles upon inverting the polarity of stimulation: the
reduction in resistance between high and low profiles was approximately 88% after two rounds of entrainment. This effect was
found to be reversible through reversion to the original stimulus polarity and was strengthened by repeated experimentation, as
evidenced by a mean reduction in time to switching onset of 43%. These effects were not replicated in nanotube solutions not
bound inside LMs. Our electrical characterization also reveals that nanotube-filled LMs exhibit pinched loop hysteresis IV
profiles consistent with the description of memristors. We conclude by discussing the applications of this technology to the
development of unconventional computing devices and the study of emergent characteristics in biological neural tissue.
due to certain features of their biological counterpartssuch as
massive parallelism, emergence, and low energy consumption9,10being highly desirable to emulate.
This article aims to create neuromorphic computing devices
from liquid marbles (LMs). LMs are spherical microliter
quantities of fluid with a superhydrophobic particulate coating,
which can range in size between tens and thousands of
micrometers in diameter.11−14 These systems exhibit novel
characteristics such as low coefficients of friction,15−17 which
have been exploited by nature.18,19 It has been demonstrated
that LMs have myriad uses including microreactors,14,20−23 gas
biosensors,24,25 and unconventional computing media.26,27 LMs
are responsive to various forms of stimuli, which can be used to
control various characteristics such as coalescence, shape, and
wetting.28 Our laboratory has developed LM devices that are
capable of implementing computation through a variety of
nonstandard logics26,27,29 where the LMs are considered as data,
or otherwise to contain data (i.e., chemical reactants), which
may interact with other LMs via collisions that will result in data
translation or transfer via ricochets or coalescence. Toward these
1. INTRODUCTION
Computation is a ubiquitous property of natural matter that,
through a universal and objective language, will unite the
sciences. More generally, physical systems may be applied to
mathematical problems to create machines and computers.
Complex systems may be correspondingly abstracted in
algorithmic terms in order to describe phenomena that have
traditionally evaded the grasp of understanding, such as
complexity arising from biological sensorial-actuation networks,
through which phenomena such as “intelligence” are hypothesized to emerge,1−7 even in organisms that do not possess
nervous systems.8 This application of computing concepts and
development of experimental devices therein encompasses the
field of “unconventional computing”.
A neuromorphic characteristic of an engineered system is so
named if it mimics the structure or functionality of a
component/multiple components of the metazoan nervous
system. Typically, this will involve attempts to replicate the
phenomenon of synaptic plasticity: self-modulation of the
impedance of neuron−neuron junctions (synapses) toward
replicating state retention (“learning”) via a process of
entrainment (phase synchronization) with graduated input
(“neuromodulation”). Neuromorphic devices are worthy of
research attention as an unconventional computing paradigm
© 2019 American Chemical Society
Received: August 15, 2019
Revised: September 16, 2019
Published: September 17, 2019
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goals, we (and others) have also examined LM dynamics to
enhance their usefulness for these purposes, for example,
evaporation30,31 and ballistic interactions.32,33 The current work
is therefore presented as a route toward developing microliterquantity three-dimensional ballistic-chemical reactors that
exhibit neuromorphic properties and may hence be used as
unconventional computing media.
The first liquid-state neuromorphic devices to be demonstrated were composed of UV-curable zinc oxide polymers;34 for
our LMs however, the liquid core chosen was an aqueous
dispersion of carbon nanotubes (CNTs). In 2001 Cui et al.35
experimentally demonstrated that single walled-CNTs can be
switched between two conductance states (high-conductance
and low-conductance), which differ by more than 2 orders of
magnitude, with a threshold voltage shift of 1.25 V. Theoretical
analysis has shown that CNTs can act as Schottky barrier
transistors36 and several patent applications for CNT switching
devices have been filed.37,38 Regarding progress toward
implementations of CNT computing systems, field effect
transistors have been described,39 and experimental laboratory
evidence suggests that the solid-state switching signatures of
CNTs might be due to their relative mechanical movements.40
CNT artificial synapses have previously been prototyped
separately by K. Kim et al.41 and S. Kim et al.:42 the synapse
operates via dynamic interactions between CNTs and hydrogen
ions in an electrochemical cell integrated in the synapse. Our aim
was to capitalize on these properties of CNTs within LMs.
The following article is structured as follows: first, we present
our methods for producing neuromorphic LMs, using a copper
coating and a CNT-containing solution core. After presenting
our results, which detail the electrical characterization of our
LMs, including descriptions of entrainment protocols, we
proceed to discuss their design, putative uses, and present
limitations.
Figure 1. Scanning electron micrographs of the experimental materials
used. (a) Copper flakes, which were used for LM coatings. (b) CNTs,
used in LM cores.
the LMs were rolled into the depression. The second electrode,
mounted to a clamp stand, was then lowered onto the LM. The
electrode spacing was assessed by eye to compress the LM slightly, at an
interelectrode gap of 2.0−2.5 mm, which ensured that the upper surface
of the LMs remained in contact with the upper electrode in the event of
LM deformation. These electrodes were chosen for their shape rather
than their electrical properties, hence, a brief series of replicate
experiments were performed using flat copper plates instead of the cup
electrodes, each measuring 10 × 10 × 1.0 mm, to ascertain that the
results observed were indeed a function of the sample, rather than the
electrode material.
No steps were undertaken to prevent fluid evaporation from the LM
because (a) a focus of our investigation was evolution of LM
characteristics over time in standard room temperature and humidity
conditions and (b) our previous work30 has demonstrated that the
effects of evaporation over the experiment duration (50 min) is likely to
have been negligible.
Electrical measurements were made via a Keithley source measure
unit (SMU) 2450 (Keithley Instruments, USA), using a 4-to-2
electrode setup. A current limit of 100 mA was used throughout. The
principal experiment involved repeatedly stimulating the LM using a 3.0
V pulse (0.5 s ramp time, hence 1.0 s per pulse), followed by a delay (i.e.
0 V) of the same duration. This stimulation pattern of 0 → 3 V was
repeated 375 times per “phase”, each phase therefore lasting 750 s.
Furthermore, a second stimulation phase was started which was
identical to the first, except for polarity being switched to −3.0 V. This
overall pattern was repeated, that is 375 pulses at 3.0 V, then 375 pulses
at −3.0 V, twice, such that each experiment’s duration was 3000 s.
These four phases are here named s1 → s4. The stimulus voltage was
greater than the thermodynamic requirement for the hydrolysis of water
and, one would suspect, also high enough to overcome the inherent
kinetic barrier. However, perhaps because of the inverting pulsed nature
of our experiment, no obvious hydrolysis was observed.
All experiments were repeated 10 times. Pulse frequency, duration,
and magnitude were all chosen as the result of prior testing, toward
designing experiments where minimal voltages were used in order to
reduce breakdown of water products while keeping experiments short
enough to reduce the impact of fluid evaporation from marbles. For
completeness, IV sweeps were also conducted with the same instrument
using a 3 V double-sided sweep, 0.1 s dwell time with a 0.1 A current
limit.
Further control measurements were also collected on 100 μL
samples of fluids (dispersed CNTs and solvated Triton X-100 in DIW,
Triton X-100 in DIW, both at the same concentrations as previously
stated, and pure DIW), henceforth referred to as “free liquid” (FL)
experiments. This was achieved through the use of bespoke circuit
boards developed in our laboratory for bulk electrical testing of fluid
samples, connected to the same measurement apparatus described
above (Figure 2c). Full details of these boards’ design and fabrication
are included in the Supporting Information.
All analyses were performed using MATLAB 2017a (MathWorks,
USA). All datasets were found to be normally distributed via Shapiro−
Wilk tests (p < 0.01 in all instances) and hence further investigation into
effect size was not conducted. Each experiment (CNT LMs, water LMs
and water, Triton X-100 and CNT FL experiments) was repeated 10
2. EXPERIMENTAL SECTION
LMs were prepared using copper flakes (Goodfellow, UK) (average
diameter 76 μm, n = 838) and 100 μL of liquid droplets. Copper flakes
of this variety, which have substantial surface roughness, have been
previously demonstrated to be sufficiently hydrophobic for generating
LMs.43 Upon gentle contact of the liquid with the bed of copper flakes,
spontaneous LM formation was observed; the copper flakes migrated
around the droplet of liquid, forming a completely coated LM without
the need of rolling (this phenomenon has been previously observed
using ethanol/water binary solutions and hydrophobized glass beads,44
as well as with copper flakes43). The experimental LM fluid core was a
single-walled CNT dispersion at 1 mg mL−1, in deionized water (DIW)
containing 1% (w/v) Triton X-100 (CHASM Advanced Materials,
USA). Addition of the surfactant Triton has been demonstrated to
maintain complete dispersion of CNTs in aqueous solutions.45 CNT
dimensions were approximately 20 nm diameter and over 1 μm length.
Typical electron microscopical appearances of the materials used are
shown in Figure 1 (see the Supporting Information for preparation
details).
CNT solutions were sonicated prior to use for 10 min. Control LMs
were prepared using DIW (15 MΩ cm) cores. Attempts were made to
fabricate control LMs using 1% Triton X-100 in DIW, but the surfactant
nature of the additive in the absence of hydrophobic CNTs prevented
LMs from forming. Previous reports using Triton X-100 (even with a
more hydrophobic powder coating) also had limited success forming
stable LMs at this concentration.46 Care was taken to ascertain, both
before and after experiments, that LMs had not wetted either electrode
surface.
LMs were subject to electrical characterization via two cup-style Ag/
AgCl electrodes (Figure 2a,b), each with a total end-to-end resistance
not exceeding 0.5 Ω. One electrode was placed concavity-side up and
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Figure 2. Experimental electrical recording apparatus. (a) LM recording apparatus. Two 10 mmø Ag/AgCl cup electrodes were used to “sandwich”
LMs, with an electrode spacing of 2.0−2.5 mm. Scale bar 5 mm. (b) Schematic diagram of LM recording apparatus (not to scale). CS: clamp stand;
LM: liquid marble; K: Keithley SMU; E: electrodes. (c) Fluids were placed into wells overlying needle-shaped electrodes; only one pair of electrodes
were used in the experiments described here. Scale bar 10 mm.
Figure 3. Graphs to illustrate typical resistance of LMs exposed to 3 V pulses at periodically alternating polarities. Colored areas indicate stimulation
phases (red for s1, green for s2, orange for s3 and blue for s4) and resistance values at 0 V have been omitted for clarity. (a) CNT LM, showing NSEs
(asterisks). (b) Control water-filled LM. No NSEs are visible.
times, except for IV sweeps and copper electrode tests, where n = 5. All
varieties of statistical tests used were two-tailed.
switching effect” (NSE), the characteristics of which were as
follows (Figure 3a). Repeated stimulation with 3 V pulses during
s1 caused CNT-filled LMs to maintain a high-resistance state
(quantitative data are presented in subsection 3.2), during which
fluctuations in their electrical properties were minor. The
switching of polarity during s2 resulted in the LM initially
assuming a similar profile as during s1, before suddenly switching
3. RESULTS AND DISCUSSION
3.1. Description of Neuromorphic Property. An
emergent characteristic was observed in LMs filled with the
CNT solution that will henceforth be known as a “neuromorphic
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The time to NSE onset during phases s2 and s4 was also
investigated. Similarly to the CNT LM’s resistance, onset times
were highly variable, ranging from 11 to 309 s, mean 84.8 s
during s2 and 4−106 s, mean 41.8 s during s4. It was observed
that the longer time to NSE onset correlated with datasets with a
higher overall resistance, hence, this phenomenon was reasoned
to also be linked to LM−electrode contact area. When measured
as a percentage difference in onset between s2 and s4, it was
found that the difference between time to onset was significantly
shorter between s2 and s4 (Table 3).
to a more conductive profile. The majority of LMs experienced
drops in resistance of 1 to 2 orders of magnitude during s2.
Entering phase s3 (reverting to the original polarity), the LMs
were observed to briefly retain their lower resistance profile
before rapidly dropping back to a high resistance profile, similar
to those observed in s1. After a final polarity change during s4, the
LMs were observed to return to their low resistance profile. The
LMs invariably switched to their low resistance profile in a
shorter time period than during s2.
It is noteworthy that an NSE was not observed in the waterfilled control LMs (Figure 3b) or in any of the FL experiments.
The NSE was observed in CNT-filled LMs sandwiched between
copper (rather than Ag/AgCl) electrodes, but not in water-filled
LMs or any variety of FL when tested with copper electrodes.
For example datasets, see the Supporting Information.
3.2. Characteriztion of Neuromorphic System Effect.
Differences in mean resistance of CNT-filled LMs between
phases s1 → s4 were found to be significant through analysis of
variance (ANOVA) (Table 1). There was also a significant
Table 3. Table To Show Two-Sample t-Test Results,
Comparing Percentage Changes in Mean NSE Onset Time
between Phases s2 and s4 in LMs Containing CNTsa
s2 → s4
CNT LM
H2O LM
CNT FL
T FL
H2O FL
3.236
0.035b
1.086
0.392
3.490
0.041b
0.700
0.561
1.970
0.137
F: F-statistic, p: p-value. bp < 0.05.
difference in mean resistances of CNTs in FL between these
phases, although NSEs were not observed in these experiments.
No significant difference between means between phases was
observed in any other sample type. The resistance of CNT LMs
was subject to a large degree of variation [which ranged from
5.67 to 46.3 kΩ (mean 46.6 kΩ) in unstimulated s1 CNT LMs
and 0.05−19.3 kΩ (mean 3.15 kΩ) in s4 CNT LMs], likely
resulting from inconsistent contact areas between LMs and their
top electrodes, hence data on conductivity changes are here
presented as percentage changes in resistance between phases
(Table 2). Percentage differences in mean resistance between
phases s1 → s2 and s1 → s4 were found to be significant, with
variation reducing markedly in the latter measurement.
Table 2. Table To Show One-Sample t-Test Results,
Comparing Percentage Changes in Resistance between s1 →
s2, s1 → s4, and s2 → s4 in LMs Containing CNTsa
mean PC
med PC
CI low
CI high
SD
p
63.95
87.70
29.23
97.64
98.48
38.67
22.18
71.58
−13.82
105.7
103.8
72.27
58.40
22.53
60.17
0.007b
0.000c
0.159
SD
p
39.73
22.75
0.0005b
3.3. CNT LM IV Profile. A typical IV profile for a previously
unstimulated CNT LM is shown in Figure 4. Allowing for the
LMs saturating at the instrument current limit when exposed to
a continuous dc source, all samples (n = 5) were observed to
produce a pinched-loop hysteresis, consistent with the
description of a memristive device.47
3.4. Further Discussion. We have described here laboratory
experimental work in which we generated LMs which exhibit the
neuromorphic properties of: (1) switching between two distinct
electrochemical states in response to excitatory or inhibitory
electrical input signals; (2) potentiation, that is, an increase in
signal in response to repeated dc pulses (“training”); and (3)
memory of previous states, as evidenced by a reduced time to
NSE and IV profiles consistent with descriptions of memristors.
We propose, therefore, that CNT LMs may be considered as soft
nonbiological synapses. Although CNTs have been successfully
used as components of LM cores before,48 to our knowledge,
this is the first published description of a neuromorphic LM.
We did not observe any incidence of the NSE in CNT FL
experiments, although as there was a statistically significant
difference in mean resistance between phases, we are not
discounting the possibility that this may still occur with alternate
testing parameters. Regardless of whether this effect is a function
purely of CNTs or otherwise, the NSE has specific applications
when packaged within a LM. Although copper has been
described as a LM coating material before,43 its significance in
enabling the NSE is unclear and will form the topic of future
work.
Although the mechanisms underlying the NSE in CNT LMs
were not elucidated with the experiments detailed here,
significant work has been done on the electrical properties of
CNTs and their propensity to align according to electromagnetic fields is well-established.49 Furthermore, many
neuromorphic devices based on CNT technologies have been
proposed and work has begun on implanting CNTs into
biological neurons, the effects of which appear to include
neuromodulation.50
Previous authors have studied the effects of charging of CNTs
in response to electrical stimulation, which could likely underlie
the phenomena observed in this study.51−53 This is also
somewhat consistent with results on CNTs sustaining and
promoting neuronal electrical activity in networks of cultured
cells as reported by Cellot et al.,50 where it is proposed that the
a
s1 → s2
s1 → s4
s2 → s4
med PC
43.20
a
CI: confidence interval (in %), Med: median (in %), PC: percentage
change (in %), SD: standard deviation bp < 0.01.
Table 1. Table To Show ANOVA Results, Comparing
Differences in Means between Phases in LMs Containing
CNTs and Water, in Addition to FL Controls Containing
CNTs, Triton X-100 (T), and Watera
F
p
mean PC
a
CI: confidence interval (in %), Med: median (in %), PC: percentage
change (in %), SD: standard deviation. bp < 0.05. cp < 0.0001.
This raises the question as to whether CNT LM resistance
drops further in s4 than in s2. Although approximately 60% of
CNT LMs demonstrated a subsequent reduction in resistance s4
from the values they exhibited during s2, the remainder either
continued to reproduce similar resistances or a slightly increased
resistance, hence a significant difference in percentage change
between s2 → s4 was not observed.
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Figure 4. Graph to show a typical IV sweep profile from a CNT LM exposed to a 3 V double-ended sweep. Arrows indicate sweep direction.
reported effects could be due to clustering of CNTs and the
resulting close contact with the neural membrane. We discuss
hypothetical mechanisms underlying the NSE in the Supporting
Information.
Switching behavior may be used as the basis for computing
circuitry, including logic gates and bistables: this would be the
most facile route toward producing CNT LM computing
devices. When considering their neuromorphic characteristics,
however, even a single memristive device which exhibits spiking
behavior may be capable of implementing combinatorial logic
operations (e.g., full adders) when device I/O operations are
sequence-sensitive.54,55 It is therefore clear that more refined
methods are available to enhance the viability of CNT LMs as
unconventional computing media.
The benefits to our devices being encapsulated within LMs
are manifold12,13 but revolve around their representing soft,
ballistic data sources whose contents may be considered as
chemical reactors. Through the exploitation of principles of
collision-based computing,56 LM computing devices may be
used to implement nonstandard, “collision-based” conservative
logics.26 Integration of LM features such as collisions whose
outcome may be engineered (reflection or coalescence) and the
potential for chemical reactions between two heterogenous fluid
cores following collision, further enhances the toolbox of
traditional conservative logic. The applications of such a device
include enhancing our understanding of the nervous system and
hence information processing in mammals, control of adaptable
and autonomous liquid robots,57 and various lab-on-a-chip
applications.
Our future work on neuromorphic LMs will establish the
number of stimuli and switching cycles necessary to produce an
NSE, their longevity under these conditions, and how consistent
memory effects are over time. Further work on elucidating the
mechanism underlying the phenomena described here will also
be prioritized.
3. Repeated stimulation across multiple phases causes the
NSE to occur more rapidly, which may also be equated
with training.
We propose that this technology is of interest to the design
and fabrication of massively parallel wet computers whose
applications range from computing to biomedicine.
■
ASSOCIATED CONTENT
* Supporting Information
S
The Supporting Information is available free of charge on the
ACS Publications website at DOI: 10.1021/acs.langmuir.9b02552.
Overview of the Hex PBC design used in FL experiments,
typical datasets for control experiments, electron
microscopy of LM materials, and the hypothetical
model for neuromorphic effect (PDF)
■
AUTHOR INFORMATION
Corresponding Author
*E-mail:
[email protected].
ORCID
Richard Mayne: 0000-0003-1915-4993
Notes
The authors declare no competing financial interest.
ACKNOWLEDGMENTS
The authors thank Dr. David Patton and Sue Hula, of the
Department of Applied Sciences at UWE Bristol, for their
expertise with the scanning electron microscope. T.C.D., C.F.,
B.P.J.d.L.C., and A.A. acknowledge support of EPSRC with
grant EP/P016677/1.
■
■
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