development of conjugated polymer nanoparticles for
TRANSCRIPT
Clemson University Clemson University
TigerPrints TigerPrints
All Theses Theses
August 2021
Development of Conjugated Polymer Nanoparticles for Development of Conjugated Polymer Nanoparticles for
Applications in Superresolution Imaging and Sensors Applications in Superresolution Imaging and Sensors
Muskendol Novoa Delgado Clemson University, [email protected]
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Recommended Citation Recommended Citation Novoa Delgado, Muskendol, "Development of Conjugated Polymer Nanoparticles for Applications in Superresolution Imaging and Sensors" (2021). All Theses. 3585. https://tigerprints.clemson.edu/all_theses/3585
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DEVELOPMENT OF CONJUGATED POLYMER NANOPARTICLES FOR APPLICATIONS IN SUPERRESOLUTION IMAGING AND SENSORS
A Thesis Presented to
the Graduate School of Clemson University
In Partial Fulfillment of the Requirements for the Degree
Master of Science Chemistry
by Muskendol Novoa Delgado
August 2021
Accepted by: Dr Jason McNeill, Committee Chair
Dr. Carlos Garcia Dr. Leah Casabianca
Dr. Dvora Perahia
ii
ABSTRACT
Utilization of conjugated polymer nanoparticles (CPNs) as fluorescent probes has
attracted lots of scientific interest due to their exceptional brightness and photostability,
particularly there has been considerable interest in developing a photoswitchable
nanoparticle based on CPNs. Previous efforts by other groups of researchers, either did not
exhibit single-step switching or suffer from poor on/off contrast because of incomplete
quenching of the nanoparticle fluorescence. In this work, superresolution imaging via
controlled reversible generation and recombination of hole polarons as fluorescence
quenchers inside CPNs has been demonstrated resulting in a localization precision of
~0.6nm, which is about 4 times better than the typical resolution achieved.
We demonstrated a novel polydot nanoparticle made of PCBM doped PFBT with
photoswitching properties for super resolution microscopy. Another efforts were made to
continue improving photoswitching polydots, including the development of PCBM doped
MEH-CNPPV photoswitches trying to achieve better colloidal stability and narrower size
distributions, also electric field modulation studies were performed on the nanoparticles and
new protocols to produce DNA wrapped polydots were developed in this work, attempting to
extend the scope of the applications of CPNs in biosensors, biological imaging and to
demonstrate improved super resolution imaging.
iii
ACKNOWLEDGMENTS
During my time at Clemson University, I have made lots of friends and received help from
many people. I want to thank all of them, even though I only have space to mention a few
in this dissertation.
It has been a lot of fun working in Dr. Jason McNeill’s lab. I would like to thank him for
all the compounds, optics, electrodes that I purchased, for the time he spent with my
manuscripts, and for his sound advises about my research as well as career. I enjoyed
talking to him about science, research and live because he always has some good stories to
share. Also, he was understandable in times when I was ill and could not perform research.
In the McNeill’s group I got to meet great people. Yifei Jiang, Teeranan Nongnual,
Amirhossein Jafariyan, Liaoran Cao and Ming Lei have all given me great help in research.
I would also like to thank my committee, Dr. Carlos Garcia, Dr. Leah Casabianca, and
Dr. Dvora Perahia, for their patience and guidance. I appreciate the research advises they
gave me and their support.
Finally, I would like to thank my family and relatives back in Colombia, specially my
parents and Stefany Collazos for all their love and support through all the difficult
moments.
iv
TABLE OF CONTENTS
Page
TITLE PAGE ............................................................................................................... i
ABSTRACT ................................................................................................................ ii
ACKNOWLEDGMENTS .......................................................................................... iii
LIST OF FIGURES ..................................................................................................... v
CHAPTER
I. INTRODUCTION ..................................................................................... 1
Conjugated polymers and CPNs ........................................................... 1 Fluorescence spectroscopy ................................................................... 6
Single Molecule Spectroscopy .............................................................12
II. EXPERIMENTAL METHODS ................................................................17
Materials .............................................................................................17 Preparation of CPNs ............................................................................17
Characterization Methods ....................................................................19 Single Molecule Spectroscopy .............................................................26
III. RESULTS .................................................................................................32
Improved superresolution imaging using telegraph noise in organic semiconductor nanoparticles .......................................................................................32
Attempts to improve the photoswitching CPNs: PCBM Doped MEH-CNPPV Nanoparticles ................................................................................................44
Electric Field Modulation of CPN’s fluorescence. ...............................50 DNA wrapped polydots development ..................................................53
IV. GENERAL CONCLUSIONS AND FUTURE DIRECTIONS...................56
REFERENCES...........................................................................................................58
v
LIST OF FIGURES
Figure Page
1.1 Chemical structures of four common conjugated polymer backbones ............. 1
1.2 SEM images of nanoparticles of the conjugated polymer PFBT with different shapes and sizes. ........................................................................................................... 4
1.3 Illustration of Beer’s Law derivation ............................................................ 7
1.4 Jablonski diagram showing the interactions of singlet and triplet states in a fluorophore…... ............................................................................................................ 8
1.5 Illustration of single molecule localization. ..................................................15
2.1 Illustration of typical conjugated polymer nanoparticles preparation ..............19
2.2 A typical AFM image of PFBT nanoparticles. ..............................................21
2.3 Scattering intensity fluctuations caused by Brownian motions of particles and the corresponding autocorrelation function. ......................................................................23
2.4 Illustration of the single particle fluorescence microscopy setup. ...................27
3.1 Chemical structures of PFBT and PCBM. Number weighted particle size distributions of PCBM doped………………….34
3.2 AFM images of PCBM doped PFBT CPNs. ..............................................35
3.3 Fluorescence microscopy images showing the blinking behavior of 20% PCBM doped PFBT CPNs. 3D histogram of the localized centroid position of a blinking 20% PCBM doped PFBT CPN. Fluorescence intensity trajectories of 20% PCBM doped PFBT CPNs, acquired at two excitation intensities, showing different blinking duty cycles ...............................37
3.4 Proposed photoswitching mechanism in PCBM-doped CPN photoswitches….40
vi
List of Figures (Continued)
Figure Page
3.5 AFM image of unlabeled e.coli. Fluorescence microscopy images of unlabeled, PFBT CPNs labeled, 40% PCBM doped PFBT CPNs labeled E.coli ..................................................................................................41
3.6 Fluorescence microscopy images showing the blinking behavior of an E. coli labeled with 20% PCBM doped PFBT CPNs. A 3D fluorescence intensity map showing a few switched “on” CPNs on an E. coli. A scatter plot shows the superresolution image of an E. coli, constructed from the localized positions ofblinking CPNs. ....................................................................................43
3.7 Number weighted particle size distributions of PCBM doped MEH-CNPPV CPNs at various PCBM doping percentages, determined from DLS measurements. Normalized fluorescence spectra of PCBM doped PFBT CPNs at various PCBM doping percentages………………………………………………………………………………...46
3.8 Fluorescence microscopy images of 1% PCBM doped MEH-CNPPV CPNs, 10% PCBM doped MEH-CNPPV CPNs, images acquired at 400 W/cm2, 10 Hz framerate. .....47
3.9 Trajectories of PCBM doped MEH-CNPPV CPNs, acquired at several framerates and power intensities……………………………………………………….48
3.10 Fluorescence intensity trajectories of PCBM CPNs modulated by -2V-0V square wave pulses acquired at 10 Hz framerate, and excitation power of 100 W/cm2.. ...............52
3.1 Normalized fluorescence spectra for the samples and the control experiment using
an excitation wavelength of 445 nm……………………………………………………….5
1
CHAPTER ONE
INTRODUCTION
1.1 Conjugated polymers and CPNs
1.1.1 Conjugated polymers and applications
Since the observation of semiconducting properties of conjugated polymers in 1977
by Heeger, MacDiarmid, and Shirakawa,1 they have attracted great interest from the
scientific community for their fluorescent and semiconducting properties2-6 and particularly
their electro-optic applications such as polymer light emitting devices and photovoltaic cells
because of their light weight and flexibility.7,8 Conjugated polymers are a special class of
polymers, containing alternate single and double bonds along the polymer backbone. The
π electrons can be delocalized along the length of polymer backbone,9,10 which gives
conjugated polymers organic semiconductor behavior. Some examples of commonly used
conjugated polymer backbones are conjugated Polyfluorenes (PFs), polyphenylene
vinylenes (PPVs), polythiophenes (PTs) and polyphenyl ethynylenes (PPEs), (structures
shown in Fig. 1.1).
Figure 1.1: Chemical structures of four common conjugated polymer backbones.
2
Delocalization of the π and π* energy levels and the moderate energy gap (in the
range of 1.5 to 3 eV), allow efficient absorption of photons in the visible, near UV, and
near IR spectral ranges. Variation of the sidechain chemistry or the inclusion of
heteroatoms, such as O, N, or S in the backbone or the sidechains, allow tuning of
photophysical and chemical properties of the conjugated polymer.1,11,12,13 In principle, the
electronic states of a conjugated polymer molecule would be delocalized over the entire
polymer molecule (assuming a perfectly ordered structure at absolute zero), however,
under typical conditions structural features such as kinks, chemical defects, and bends in
the polymer chain lead to lengths of 4-10 repeating units over which conjugation is
unbroken.14,15 Conjugation length plays an important role in determining the photophysical
properties of the polymer, as the energy level of an electronic state is a function of the
space available for delocalization, as explained by Hückel theory. Longer conjugation
lengths have lower energy electronic states leading to red shifted absorption and emission
wavelengths; conversely, short conjugation lengths lead to blue shifted spectra. This is
important to consider when designing devices, as solution and film processing each have a
dramatic impact on conjugation length and spectral characteristics. 16
1.1.2 Conjugated polymer nanoparticles
Conjugated polymer nanoparticles (CPNs) are nanoparticles made from conjugated
polymers. These nanoparticles have emerged as a promising class of multifunctional
photoluminescent nanomaterials particularly as fluorescent probes in biomedical analysis
and other advanced fluorescence imaging and analysis applications,17 because of their
3
small sizes, tunable emission wavelengths, high absorption coefficients, and excellent
fluorescence efficiencies. Conjugated polymers nanoparticles (CPNs) are by far the
brightest fluorescent nanoparticles demonstrated (roughly 20-100 times brighter than
similar-sized colloidal semiconductor quantum dots under typical imaging conditions),18,19
due to the high extinction coefficient, high chromophore density, and (in some cases) high
fluorescence quantum yield of the conjugated polymer.20 CPNs have been demonstrated in
several fluorescence-based applications, such as multiphoton fluorescence imaging,21
single nanoparticle sensors,22 photoswitching nanoparticles,19,23,24 particle tracking25 and
photodynamic therapy.26 Particularly is worth noting that photoswitching CPNs have
shown promise on applications of CPNs to improve signal levels and resolution in
photoswitching-based ultraresolution fluorescence imaging.27,28
Conjugated polymer nanoparticles (CPNs) size range may vary between a few
nanometers to microns depending on the preparation methods, and consist of somewhat
closely packed chains of hydrophobic conjugated polymers, typically with a disordered or
semicrystalline structure.29-31 Suspended in water, or cast onto a surface from an aqueous
suspension, the overall shape of the particle is typically governed primarily by interfacial
tension, and thus approximately spherical for smaller (<50 nm dia.) particles,32 is worth
nothing that being among soft nanoparticles, CPNs have particle shapes ranging from
spherical to ellipsoidal (Fig. 2.2). Particularly for our studies, we will focus on smaller (<20
nm) nanoparticles. There is interest in knowing the detailed structure of CPNs, including
polymer chain conformation and chain packing, largely motivated by the expectation
(based on knowledge of systems with similar chromophore density, such as organic
4
semiconductors and light-harvesting complexes) that structure dictates the optical
properties and related dynamics of CPNs.20
Figure 1.2: SEM images of nanoparticles of the conjugated polymer PFBT with different
shapes and sizes. (a) 28nm spheres with an aspect ratio of 1.0. (b) 140nm long ellipsoids with
an aspect ratio of 1.5. (c) 200nm long ellipsoids with an aspect ratio of 1.2. (d) 1,000 nm spheres
with an aspect ratio of 1.0. The white bar represents 200 nm in each plot. Adapted with
permission from ref. 32 Copyright 2005 Macmillan Publisher Ltd.
1.1.3 Exciton dynamics and polarons in conjugated polymers
When a photon is absorbed by a conjugated polymer, an electron undergoes
excitation from the π to the π* band, generating a neutrally charged local excitation and
polarization or distortion of the polymer matrix. The primary neutral electronic excited
state in conjugated polymer is typically described as the Frenkel-type molecular exciton,
consisting of two or more chromophores quantum-mechanically coupled via transition
dipoles.33,34 The nature of exciton motion in the system varies with the chemical structure,
conformation, and processing conditions (as well as other factors such as temperature).
Excitons can undergo either radiative or nonradiative decay, move to another chromophore
via either a Dexter or Förster mechanism, or lose an electron to leave behind a hole polaron
5
(discussed below). Exciton mobility in the polymer occurs through a combination of
Dexter electron transfer and Förster energy transfer. As the emission spectrum from the
donor chromophore needs to overlap with the absorption spectrum of the acceptor
chromophore, there tends to be a red shift in the energy of an exciton as it diffuses through
the particle, observable in the emission spectrum. There have been extensive investigations
of exciton dynamics in conjugated polymer systems, including thin films,35-37 solutions,38,39
in a matrix,40, 41 and nanoparticles.42
Polarons are either electrons or holes (electron vacancies) that exist in an organic
semiconductor. 43, 44 Polarons can be generated through chemical doping, electrode
oxidation or reduction, direct injection from an electrode, or exciton dissociation. A
positive or negative charge is created and localized to a segment of the material, and cause
the distortion of the nearby structure, which yields a localized charge volume. Polarons are
mobile, so they can act as charge carriers. Polarons able to move to different locations in
the material, acting as charge carriers in such devices as organic field effect transistors and
solar cells.
Hole polarons in conjugated polymers are typically generated when an electron is
lost from the exciton, leaving behind a positively charged hole and a polarization of the
polymer matrix. The absorption spectrum of a hole polaron is typically red-shifted as
compared to the neutral polymer, resulting in an absorption spectrum with a high degree
of overlap with the emission of the neutral polymer, which in turn results in highly efficient
energy transfer to hole polarons, characterized by a large energy transfer radius (4-8 nm),
enabling a small number of polarons to cause a large number of excitons in the vicinity to
6
undergo FRET. As emission from polarons is typically red shifted and has a low quantum
yield, thus a relatively small hole polaron density can nearly completely quench
fluorescence from the conjugated polymer. 45, 46
Polarons are very efficient singlet exciton quenchers43, 47, 48 because of the high
degree spectral overlap between the emission of neutral polymer and absorption of
polarons, which facilitates efficient energy transfer to polarons. Since the hole polarons
can have a dramatic effect on the performance of conjugated polymer devices, there is
considerable interest in studying and understanding polaron dynamics and related
phenomena, such as the fluorescence twinkling in conjugated nanoparticles.49
1.2 Fluorescence spectroscopy
1.2.1 Absorption and fluorescence
When molecules containing π electrons absorb energy from ultraviolet or visible
light, the π electrons can be excited from the ground state S0 (HOMO, π) to an excited state
S1 (LUMO, π*) this event is called absorption. This is characterized by the Beer-Lambert
law (also known as Beer’s law). Beer’s Law can be derived by treating the molecule as an
opaque disk with a cross-sectional area σ (cm2, the effective absorption area). Fig. 1.3,
illustrates the derivation of Beer’s law, where an infinitesimal slab with length dz (cm) and
total area S (cm2) is taken, the molecule density of the sample is N (molecules/cm3), then
the total number of molecules in the slab is N*S*dz. And the fraction of the total area where
light gets absorbed due to each molecule would be (fractional area for each molecule) σ/S.
If the intensity of the light incident at the infinitesimal slab is Iz, then the light intensity
7
absorbed by the slab would be 𝑑𝐼 = 𝐼𝑧 ∗ (𝜎𝑠⁄ ) ∗ (𝑁 ∗ 𝑆 ∗ 𝑑𝑧) = 𝐼𝑧 ∗ 𝜎 ∗ 𝑁 ∗ 𝑑𝑧. Then, we
can derive the following equation,
𝑑𝐼
𝐼𝑧= −𝜎𝑁𝑑𝑧. (1)
Figure 1.3. Illustration of Beer’s Law derivation.
In equation 1, the negative sign represents the absorption of light. Integrating from
z = 0 to z = l, the equation becomes,
𝑙𝑛𝐼 − 𝑙𝑛𝐼0 = − ln𝐼0
𝐼= −𝜎𝑁𝑙. (2)
where I0 is the intensity entering the sample, I is the intensity of light leaving the sample,
and l is the light path length (cm). Since the definition of the absorbance of the sample A
is given by 𝐴 = 𝑙𝑜𝑔10(𝐼0
𝐼). We can combine this equation with equation 2 getting 𝐴 =
1
2.303𝜎𝑁𝑙. Then replacing molecule density N (molecules/cm3) with concentration C (M,
8
mol/L), and cross section σ (cm2) with molar extinction coefficient ε (M-1 cm-1), the
equation becomes,
𝐴 = 𝜀 ∗ 𝐶 ∗ 𝑙, (3)
where 𝜀 = (1
2.303)(
1
1000)𝜎𝑁𝐴, 𝐶 =
𝑁∗1000
𝑁𝐴, and NA is the Avogadro’s number. It is
worth noting that the molar extinction coefficient of a sample depends on the wavelength of
the incident light.
For a molecule with a ground state S0, the photon can excite the molecule to the
first excited singlet state (S1) as shown in Fig. 4. The molecule may also have a triplet state
T1.
Figure 1.4: Jablonski diagram showing the interactions of singlet and triplet states in a
fluorophore.
In Fig. 1.4, a Jablonski diagram is shown to illustrate the relationship between the states
S0, S1, and T1 which represent a singlet ground state, singlet excited state and triplet excited
state, respectively along with the rate constants for interchange between the states and
energy transfer from a donor molecule to an acceptor molecule.50
The various rate constants are:
kabs = Excitation of the molecule through the absorption of a photon
9
kIC = Internal conversion rate
kR = Radiative rate (Fluorescence)
kNR = Non-radiative decay
kPB = Irreversible Photobleaching
kISC = Intersystem crossing to the triplet state
kP = Phosphorescence
Internal conversion is the relaxation from higher vibrational states to the ground
vibrational state of the S1 state, with a time constant on the order of 10-12 s, ensuring that
in most cases transitions from the S1 state (to the ground state or the triplet state) start
from its lowest vibrational state.
After the molecule is excited, it spends a certain time in the S1 state before it decays
via one of several possible pathways. The time constant for residence in the excited state
is called the fluorescence lifetime, τF, and results from the combination of processes
depopulating it, in equation 4, 𝑘𝑛𝑟 is the non-radiative rate (𝑘𝑛𝑟 = 𝑘𝑖𝑐 + 𝑘𝑖𝑠𝑐 + 𝑘𝐸𝑇 + 𝑘𝑏),
which include all non-radiative relaxation processes:
𝜏𝑓 =1
𝑘𝑟+𝑘𝑛𝑟. (4)
The fluorescence quantum efficiency of fluorophores is characterized by
fluorescence quantum yield (ϕf), which is the ratio of number of photons, emitted to number
of photons absorbed. It can also be expressed in terms of rate constants as follow:
𝜙𝑓 =𝑘𝑟
𝑘𝑟+𝑘𝑛𝑟. (5)
It is worth noticing that for good fluorophores, 𝑘𝑟 + 𝑘𝑖𝑐 ≫ 𝑘𝑖𝑠𝑐 + 𝑘𝑏, and kr is similar or
ideally higher than kic, so that the quantum yield for most useful fluorescent tags ranges
10
from a few percent to close to 100% (for R6G).51 Experimentally, the fluorescence
quantum yield can be measured with steady-state fluorescence spectroscopy and the
fluorescence lifetime can be measured with time-resolved fluorescence methods. The
radiative rate constant then is estimated by 𝑘𝑟 =𝜙𝑓
𝜏𝑓.
1.2.2 Förster Resonance Energy Transfer
It is possible for many photophysical systems to transfer energy, such as in the light
harvesting complex,52 or from one species to another such as in DNA molecular
beacons.53,54 This non-radiative transfer from donor to acceptor is accomplished through
either the electron transfer mechanism known as Dexter energy transfer, or Förster
resonance energy transfer. The Dexter energy transfer requires wavefunction overlap
between donor and acceptor and is a short-range interaction (< 2 nm) that requires spin
conservation.50 Förster resonance energy transfer involves the interaction of transition
dipoles of donor and acceptor and is a longer-range interaction (up to 10 nm). Förster
theory assumes a weak interaction between the transition dipoles of the donor and acceptor,
with the application of Fermi’s Golden Rule to estimate the transition rate. The theory
predicts that the energy transfer rate depends on intermolecular distance to the inverse sixth
power,
𝑘𝐸𝑇 =1
𝜏𝐷(𝑅0
𝑟)6, (6)
where τD is the donor fluorescence lifetime in the absence of the acceptor, R is the donor-
acceptor distance, and R0 is the energy transfer radius or Förster radius, defined as the
distance at which the energy transfer efficiency is 50%. The energy transfer rate constant
11
(Eq. 6), being highly distance dependent, can be used a ‘molecular ruler’ by attaching the
donor and acceptor to the same molecule and observing the degree of energy transfer.55
Based on the assumption of weakly interacting transition dipoles and some other
assumptions, Förster developed an expression for the energy transfer radius in terms of
determined spectroscopic properties:
R06 =
9000ln(10)ϕDκ2
128π5NAn4 ∫ fD(λ)
∞
0ε𝐴(λ)λ
4dλ, (7)
where D is the quantum yield of the donor in the absence of acceptor; 2 is the
configurational factor (accounts for relative orientation of the donor and acceptor dipoles,
usually 2/3 in solution); n is the index of refraction of the medium; FD() is the pure donor
emission spectrum, normalized for the area under the curve; εA is the pure acceptor
emission spectrum; and is wavelength.50
The energy transfer efficiency E for FRET can be expressed as,
𝐸 =𝑅0
6
𝑟6+𝑅06. (8)
Equation 8, shows the strong dependence of the energy transfer efficiency on the donor-
acceptor distance. If the distance r decreases lower than R0, the efficiency increases to near
unity quickly. Conversely, the efficiency decreases dramatically to near 0 when r is greater
than R0. The energy transfer efficiency is usually measured using the relative donor
fluorescence intensity, in the presence (F) and the absence (F0) of acceptor,
𝐸 = 1 −𝐹
𝐹0. (9)
12
1.3 Single Molecule Spectroscopy
Single molecule spectroscopy was first demonstrated with doped crystals at low
temperatures56 and later at room temperature with near field scanning optical microscopy
(NSOM).57 More recently, most single molecule research utilizes confocal and wide field
microscopy arrangements.58,59
Fluorescence spectroscopy measurements in bulk solution typically only gives the
averaged properties of a large number of single molecules. In contrast, single molecule
spectroscopy (SMS),60,61 provides more per-molecule based molecular information, such
as the molecule’s structure, kinetics, and local environment, which is crucially important
when in heterogeneous systems, such as polymers, biological systems, nanostructured
interfaces, and nanoparticles. Another key advantage of single molecule measurements is
the ability to unravel complex dynamics, such as the sequence of events, which is
particularly useful for systems with complex, multi-step kinetic schemes that does not
follow conventional synchronization-based kinetics methods such as T-jump, pump-probe,
or stopped-flow. Single molecule fluorescence spectroscopy has been applied in various
research fields such as conjugated polymers,6,62-65 motor protein movements,66 and protein
folding.67
1.3.1 Single Molecule Excitation
The signal level in single molecule fluorescence measurements depends on several
factors, including the excitation intensity, optical cross-section and fluorescence quantum
yield of the fluorescent molecule, collection efficiency, and detector quantum efficiency.
The excitation rate of a single molecule can be estimated by analogy with Beer’s Law (Eq.
13
3), while the molar absorptivity (ε) parameter is most often used to describe macro-scale
experiments, the parameter used far more often at the single molecule level is absorption
cross section:
𝜎 =2.303𝜀
𝑁𝐴(10)
where σ is the absorption cross section (cm2) and NA is Avogadro’s number. This cross
section defines the effective area that a single molecule absorbs at a particular wavelength
of light.
The fluorescence cross-section is defined as the product of peak absorption cross
section (σ) and fluorescence quantum yield (ϕf) (𝜎𝑓 = 𝜎 × 𝜙𝑓). In bulk solution, the
absorption cross section and fluorescence quantum yield can be measured through steady-
state UV-Vis absorption and fluorescence emission experiments to obtain the brightness of
fluorophores. While at single particle level, it is difficult to directly measure the absorption
and quantum yield of a single fluorophore. Instead, the fluorescence cross section can be
determined through emitted photon counts per second divided by the excitation intensity
in photons per second per cm2 at single particle level (𝜎𝑓 =𝑁𝑝ℎ𝑜𝑡𝑜𝑛
𝐼𝑒𝑥).68
1.3.2 Single molecule localization and super-resolution microscopy
The resolution of conventional light microscopy is limited due to light diffraction
as shown by Ernst Abbe in 1873.69 The lateral resolution of a conventional optical
microscope is given by, 𝑑 =𝜆
2𝑁𝐴, where λ is the excitation wavelength and NA is the
numerical aperture of the microscope objective. A typical oil immersion microscope
objective (NA, ~1.25) with visible lights excitation yields ~200-250 nm resolution. Since
14
most biomolecules are much smaller than 250 nm, it is usually not possible to resolve the
individual components of biomolecular assemblies or their internal dynamics. Super-
resolution microscopy has been developed to obtain images with higher resolution than the
diffraction limit. There are two main types of functional super-resolution microscopy
methods: saturation-based methods (e.g. STED, GSD) and single molecule localization
based methods (e.g. PALM, STORM).2 In 2014, Eric Betzig, W. E. Moerner and Stefan
Hell were awarded the Nobel Prize in Chemistry for “the development of super-resolved
fluorescence microscopy”.
The principle for single molecule localization microscopy is through isolating
emitters and fitting the 2D intensity profile of the emitter with a point spread function (PSF,
approximately a Gaussian function) to obtain the location of the fluorophore. The process
is illustrated in Fig. 5.70 The localization precision is given by:
∆𝑙𝑜𝑐 = √(𝑠2
𝑁) + (
𝑎2 12⁄
𝑁) + (
8𝜋𝑠2𝑏2
𝑎2𝑁2 ), (11)
where N is the number of collected photons, s is the Gaussian width of PSF, a is the
effective pixel size of the detector and b the standard deviation of background noise in units
of photons. In the right side, the first term represents the effect of the photon counting
noise, while the second term represents the effect of finite pixel size of the detector and the
third represents background noise, including autofluorescence, scattered laser light,
thermal noise in the detector, and readout noise.
To enhance resolution, the goal is to maximize the photons collected from single
fluorophores and minimize background noise. In general, the more photons collected, the
better the resolution. Ideally, if there are 10,000 photons collected from a single fluorescent
15
probe with negligible background noise, the localization of the center position can be
determined with 1-2 nm accuracy. Background noise usually comes from the sample
autofluorescence, dark current, readout noise and some residual fluorescence from other
nearby fluorophores. Therefore, for single molecule-based super-resolution imaging,
fluorophores with large number of photons emitted prior to bleaching, and high contrast
over background are needed, and for high-speed tracking, a high emission rate at or below
saturation is also required.
Figure 1.5. Illustration of single molecule localization: (a) 2D image data of a single
fluorophore (b) Gaussian function fitting to obtain the center position.
Super resolution fluorescence microscopy based on single molecule localization
provides a substantial improvement in resolution over conventional fluorescence
microscopy and has been successfully applied to many important systems. The techniques
typically require a photoswitching fluorescent dye with certain characteristics. In our lab
we pioneered the development of a novel class of fluorescent nanoparticles based on
fluorescent conjugated polymer molecules49, 71 and in previous work combined with some
16
of the findings of this thesis, a photoswitching polydot nanoparticle was developed,
probing to be much brighter and photostable than typical photoswitching dyes.24, 72
17
CHAPTER TWO
EXPERIMENTAL METHODS
2.1 Materials
The conjugated polymers, poly[(9,9-dioctylfluorenyl-2,7-diyl)-co-(1,4-benzo-{2,1’,3}-
thiadiazole)] (PFBT, MW 10,000, polydispersity 1.7), poly[2-methoxy-5-(2-
ethylhexyloxy)-1,4-(1-cyanovinylene-1,4-phenylene)] (MEH-CN-PPV, MW 27000-
28000, polydispersity, 4.7) were employed in this study and purchased from ADS Dyes,
Inc. (Quebec, Canada). Tetrahydrofuran (THF, HPLC grade, 99.9%), phenyl-C61-butyric
acid methyl ester (PCBM, 99.5%) and (3-Aminopropyl) trimethoxysilane (APS, 97%)
were purchased from Sigma-Aldrich (Milwaukee, WI). All chemicals were used as
received without further purification.
2.2 Preparation of CPNs
A nano-precipitation method is employed to prepare conjugated polymer nanoparticles
(CPNs), as reported previously.73,74 This method is modified from the reprecipitation
procedure developed by Kurokawa and collaborators,75 and it is chosen because of its ease
and good reproducibility. This procedure involves dissolving hydrophobic conjugated
polymers in a water-miscible solvent such as THF and fast injection of the polymer solution
into deionized (DI) water. The rapid change of solvent quality by mixing results in polymer
chain collapse, leading to the formation of polymer nanoparticles. Then, the removal of
THF yields a clear aqueous nanoparticle suspension. There is competition between polymer
aggregation and nanoparticle formation (chain collapse) during the reprecipitation process,
18
and the combination of lower concentration with faster mixing rate disfavors aggregation
and favors smaller particle generation. Therefore, we are using a 20 ppm injection
concentration of polymer solution in this research. Higher concentrations tend to lead to a
larger fraction of the polymer lost due to aggregation, and/or larger nanoparticle sizes.
For a typical PFBT nanoparticle preparation, 10 mg of PFBT polymer is dissolved in 10
g of inhibitor-free HPLC grade THF with stirring to produce a 1000 ppm PFBT stock
solution. Then the stock solution was diluted to 20 ppm, and 2 mL of the polymer solution
was injected rapidly into 8 mL of DI water via micropipette. The THF solvent was removed
under vacuum at 40 °C for ~6 hours, and finally the sample was filtered through a 100 nm
PVDF membrane filter (Millipore) to remove aggregates. The PFBT particle preparation
process is illustrated in Fig. 2.1. Typically, less than 10% of the polymer was removed by
the filtration, as determined by UV-Vis absorption spectroscopy, indicating that most of
the polymers formed nanoparticles. The resulting suspension was clear and stable for
weeks without aggregation. The formation of CPNs is governed by hydrophobic
interaction, interfacial tension as well as surface free energy. The size of the CPNs can be
controlled by multiple steps in the preparation procedure. Rapid mixing of THF and water
results in a sudden decrease in solvent quality and favors small particle formation. In
contrast, large aggregates are typically observed when conjugated polymer THF solution
is added drop-by-drop into water. In addition, increase of the precursor concentration
typically results in larger particle sizes and larger fraction of polymer loss during the
filtration due to aggregation.
19
Similar procedures can be employed to prepare doped CPNs. To prepare PCBM doped
PFBT nanoparticles, conjugated polymer PFBT and fullerene derivative PCBM were
dissolved in THF and diluted to 20 ppm. The solutions of PFBT and PCBM were mixed in
various ratios to form precursors of varying dopant percentages (5%, 10%, 20%, 40%). 2
mL of the precursor solution was rapidly injected into 8 mL of water under mild sonication.
Then the THF solvent was removed by partial vacuum evaporation. After evaporation, the
sample was filtered through a 100 nm membrane filter (Millipore) to remove aggregates.
The same methods and procedures described above, were applied to prepare CNPPV
nanoparticles and PCBM doped CNPPV nanoparticles adjusting the doping percentages.
Figure 2.1. Illustration of typical conjugated polymer nanoparticles preparation.
2.3 Characterization Methods
We employed a variety of spectroscopic and microscopic techniques to investigate the
photophysical properties of CPNs. Atomic force microscopy (AFM) and dynamic light
20
scattering (DLS) were used to determine the size distribution of CPNs. Steady-state
absorbance and emission of CPNs were studied through UV-Vis and fluorescence
spectroscopy, respectively. Single nanoparticle spectroscopy was utilized to investigate
single particle properties, such as kinetics, photon number, and single particle spectra.
2.3.1 Atomic force microscopy (AFM)
Atomic force microscopy (AFM) is one of the scanning probe microscopy family, and
is usually used to characterize the surface properties of a material by scanning the surface
with a small tip.76 There are several different AFM scanning modes, which includes contact
mode, non-contact mode, and intermittent contact mode (also known as “tapping” mode).
Tapping mode was employed for the AFM scanning in this study, since it is typically the
method of choice for soft samples and/or samples that are weakly adhered to the surface.
The AFM tip is attached to a cantilever, which oscillates in the Z direction while the tip is
scanned in the X and Y directions across the sample surface. The tapping mode scanning
is performed by oscillating the cantilever at or near the cantilever’s resonant frequency (in
the range of 70-200 kHz) with a piezoelectric ceramic. The signal used to control the
cantilever’s oscillation (and damping) in the Z feedback control loop is detected by a photo
diode through the reflection of a laser beam from AFM cantilever back. During tapping
mode scanning, the cantilever oscillation amplitude is kept constant by adjusting the tip
distance from the surface through the feedback controller, called proportional-integral-
derivative controller (PID). The surface morphology image is assembled with a series of
scanning lines while the piezo moves the tip along the sample.
21
In this study, isolated particles immobilized on coverslips were imaged with an Ambios
Q250 multimode AFM in tapping mode. The scan range of the instrument is 40 μm in the
XY direction, and 5.7 μm in the Z direction. The scanning parameters employed in this study
were scan area of 5 μm×5 μm, 500 lines/scan, and a scan rate of 0.5 Hz (per line) with a
pixel resolution of 10 nm. The tip used in this work is Q-WM190 (NanoAndMore) at
tapping mode with mean resonance frequency of 190 kHz. The general guidelines for
setting PID parameters depend on the surface; to image flat surfaces with low scan rates
over small area, low Integral and Proportional gains are adequate; conversely, higher gains
are needed for rough surfaces at fasting scanning with large scan area. For typical AFM
images, the density of particles is ~10 per μm2. A typical AFM and a line scan for CPNs is
shown in Fig. 2.2. Since the particles are roughly spherical, the particle height was taken
as particle diameter due to the higher vertical resolution (Z direction) compared to the
lateral resolution (X-Y direction) as well as the tip convolution effect that typically
broadens the image of small particles in the XY plane.
Figure 2.2 A typical AFM image of PFBT nanoparticles (left), size distribution of the CPNs.
0 5 10 15 20 25 30 350
20
40
60
80
100
Nanoparticle Height (nm)
Occ
urre
nce
22
In this work, AFM samples were prepared on glass coverslips. Those coverslips were
cleaned with following steps: soap water, DI water, Nochromix/H2SO4 solution, and DI
water. Then the coverslips were functionalized with amine groups by dropping 50 μL
0.0005 M freshly prepared APS/ethanol solution onto the coverslip for ~2min, followed by
rinsing with DI water. The coverslip was then submerged into a ~20 times diluted CPNs
solution for 40 min. Excess CPNs were removed with DI water and the coverslip was dried
with nitrogen gas. APS covered coverslip was scanned as a control sample.
2.3.2 Dynamic Light Scattering (DLS)
Dynamic light scattering (DLS), also known as photon correlation spectroscopy, is a
method for determining size distribution in solution of particles such as nanoparticles,
polymers, proteins, and colloids. DLS measurement involves illuminating the sample with
a laser. The scattered light from different particles in solution can interfere constructively
(in-phase) or destructively (out-of-phase) and results in the speckle pattern. As particles
undergo Brownian motions in solution, the intensity of the spots on the speckle pattern will
fluctuate overtime due to changes in the distances between particles. The intensity
fluctuations thus contain the time scale of the particle movements and can be used to
determine the translational diffusion coefficients of the particles through autocorrelation
analysis. Applying Stokes-Einstein equation, the hydrodynamic diameters of the particles
can be calculated from the translational diffusion coefficients. Since the diffusion
coefficient is also temperature dependent, DLS measurement is typically performed under
isothermal environment. In addition, at high particle concentrations, multiple scattering
23
and viscosity effect occur, which could distort size distributions obtained from DLS
measurement. Therefore, DLS is typically performed with diluted samples (sometimes
involves a series of dilutions and extrapolating the result to the limit of zero concentration).
When the particle size is small compared to the wavelength of the laser (< λ/10), the
scattering process is isotropic, known as Rayleigh scattering. However, when the particle
size is comparable to the wavelength of the laser, the scattering intensity shows strong
angle dependence, known as Mie scattering.77 As a result, at certain angles, the scattering
intensity of some particles will completely overwhelm the signal from the others. In
addition, the scattering angle also controls the decay rates 𝛤 in the autocorrelation function
(𝛤 = 𝑞2𝐷, where D is the translational diffusion coefficient, q is the wave vector,
depending on the scattering angle), thus could affect data analysis. For highly dispersed
samples (especially with large particles), it is necessary to perform DLS at multiple angles
in order to obtain complete information about the particle size distribution.
Figure 2.3. (a) Scattering intensity fluctuations caused by Brownian motions of small particles and
the corresponding autocorrelation function. (b) Scattering intensity fluctuations caused by
Brownian motions of large particles and the corresponding autocorrelation function.
24
In this work, DLS measurements of CPNs were performed using a Nanobrook Omni
(Brookhaven Instruments Corporation, NY) with BIC Particle Solutions Software (V 3.1).
The CPN suspensions were diluted to a peak absorbance of ~0.1. Typical conditions
employed for the DLS measurements were 25 °C, count rate of 500 kcounts/s, scattering
angle of 90°, and acquisition time of 180 seconds. Polystyrene spheres (Thermo Fisher, 24
nm) were used as a size standard. Typically, CPNs suspension consists of mostly small
nanoparticles with small populations of larger aggregates (>100 nm). The NNLS method
provided reliable fitting results of the particle size distributions, which were highly
consistent with the results from AFM measurements.
2.3.3 UV-Vis and fluorescence spectroscopy
The UV-Vis absorption spectra were collected with a Shimadzu UV-2101PC scanning
spectrophotometer using 1 cm cuvettes. The instrument is equipped with two light sources,
which allows the scanning wavelength from 190-900 nm. A photomultiplier tube (PMT) is
employed as the detector in the system for sensitive absorbance measurements. To
determine the molar extinction coefficients/absorption cross-section of conjugated
polymers, conjugated polymers were dissolved in THF and diluted to a peak absorbance of
~0.1. According to the Beer’s Law, the molar extinction coefficient is given by 𝜀 = 𝐴/𝑙𝑐,
where A is the absorbance of the sample, l is the sample path length (1 cm) and c is the
molar concentration of conjugated polymer. If we replace the molar concentration c in the
Beer’s law with molecule density N (molecules/cm3), we can calculate the absorption
cross-section 𝜎 using equation 𝜎 = 2.303 ∗ 𝐴/𝑙𝑁. The extinction coefficient and
25
absorption cross-section of CPNs were calculated from the molar extinction coefficients
absorption cross-section of the corresponding conjugated polymer times the number of
polymer molecules per nanoparticle Nnp. Nnp is determined from the mean nanoparticle
volume (calculated from nanoparticle diameters determined by AFM) and the polymer
molecular weight (assuming a polymer density of ~1 g/cm3).
The fluorescence emission spectra were obtained with a commercial fluorometer
(Quantamaster, PTI, Inc.). The instrument has xenon arc lamp as excitation source. The
monochromators for excitation and emission have 1/4 m focal length with grating of 1200
grooves/mm. The detector employed in the instrument is a photomultiplier tube (PMT,
model 814) in photon counting mode. All the slit widths used in this work are 0.5 mm,
yielding a wavelength resolution of 2 nm (4 nm/mm for a 1200 grooves/mm grating, 1/4
m focal length). The fluorescence quantum yields of CPN samples were determined with
the fluorescent dye fluorescein in 0.01 M sodium hydroxide (pH = 12) used as standard.
All the CPN samples and the fluorescein standard solution were diluted to yield an
absorbance of ~0.05 at an excitation wavelength of 473 nm. The calculation of sample
quantum yield is employed using the following equation with the literature quantum yield
value of 0.92 for the fluorescein standard,78, 79
𝜙𝑓(𝑥) =𝐴𝑠𝐹𝑥𝑛𝑥
2
𝐴𝑥𝐹𝑠𝑛𝑠2𝜙𝑓(𝑠). (12)
In this equation, 𝜙𝑓is the fluorescence quantum yield, A is the absorbance at the excitation
wavelength, F is the integrated area under the corrected fluorescence emission curve, and
n is the solvent refractive index. Subscripts s and x represent standard and unknown sample,
respectively. For consistency, fluorescein in aqueous NaOH (pH = 12) is used as standard
26
and 473 nm is employed as excitation wavelength in the fluorescence quantum yield
measurement of all the samples in this research.
With the fluorescence spectrum of donor and absorption spectrum of acceptor, the
Förster radius (R0) between energy transfer pairs can be calculated using the following
equation.
R06 =
9000ln(10)ϕDκ2
128π5NAn4 ∫ fD(λ)
∞
0ε(λ)λ4dλ, (13)
where NA is Avogadro’s number; n is the refractive index of donor κ2, the orientation
factor is assumed as 2/3;50 ϕD, fD(λ), ε𝐴(λ) are the quantum yield of donor, normalized
fluorescence spectra of donor, and extinction coefficient of acceptor in THF solution,
respectively.
2.5 Single Molecule Spectroscopy
2.5.1 Single Particle Imaging
Single particle imaging was performed with a custom wide-field epifluorescence
microscope described as follows (Fig. 2.4). A 445 nm excitation laser (Thorlabs, LP450)
is passed through a liquid crystal noise eater (Thorlabs, NEL01) and then is guided to the
rear epi port of an inverted fluorescence microscope (Olympus IX-71) by an optical fiber.
The laser beam is reflected by a 500 nm long-pass dichroic (Chroma 500 DCLP) to a high
numerical aperture objective (Olympus Ach, 100×, 1.25 NA, Oil). At the sample plane, the
laser excitation exhibits a Gaussian profile with fwhm of ∼5 μm. Various laser intensities
were employed for the single particle imaging. Depending on the experiment, the typical
excitation power at the center of the laser spot ranges from 10-500 W/cm2. CPNs were
dispersed on a glass coverslip by the same method used for preparing AFM samples.
27
Figure 2.4. Illustration of the single particle fluorescence microscopy setup.
Fluorescence from the CPNs is collected by the objective lens, passes through a 500 nm
long-pass filter and then is focused onto a sCMOS detector (Andor, Neo sCMOS), yielding
a pixel pitch of 66 nm/pixel, as determined using a calibration slide. A piezoelectric
scanning stage (P-517.3CL, Polytec PI) is used to position the sample. The overall
fluorescence detection efficiency of the microscope is ~3%, determined from nile red
loaded polystyrene beads (Thermo Fisher) as standards. Depending on the experiment, a
variety of framerates ranging from 10 Hz to 1 kHz were used. At fast framerates, the region
of interest was set to the center of the sCMOS chip to maximize the performance of the
camera. When the number of photons detected per pixel is small comparing to the well-
depth, the typical camera settings are 11 bits per pixel, gain setting of 0.6, rolling shutter
mode. If the particles are bright and the number of photons detected per pixel is comparable
to the well-depth, the typical camera settings are 16 bits per pixel, gain setting of 1.6, rolling
28
shutter mode. The experimental gain factors are determined by analysis of photon counting
noise for a flat field, which are consistent with the factory values.
2.5.3 Single Particle Localization
The localization analysis of CPNs was performed using custom scripts written in Matlab
(Mathworks). To determine small movements in the fluorescence centroid associated with
polaron motion, the scripts first sum over all the frames, find the intensity of the brightest
pixel in the summed image and use 5-10% of the intensity as a threshold to distinguish
CPNs from the background noise. Then the scripts search for pixels above the threshold in
the summed image and compare their intensities to the neighboring pixels to roughly locate
the central pixel of the fluorescence spot of each CPN. Based on the rough locations of
CPNs, a 2D Gaussian function was fit to the fluorescence spot of each CPN, frame by
frame. Typically 9×9 pixels were used for the fitting (4 pixels on each side of the central
pixel). The scripts check the FWHM obtained from the fitting (should be around ~270 nm)
to make sure it is not from multiple CPNs that are close to each other. The centroid position
trajectory of a CPN was constructed from the centroid positions determined from the
corresponding fluorescence spot in all the frames.
A slightly different method was used to determine the position of photoswitching CPNs.
When imaging certain samples, sometimes background subtraction is needed to ensure
optimal localization accuracy. The background fluorescence was determined from the
frames with no CPN switched “on”. ~100 frames of the background fluorescence were
averaged and subtracted from each frame prior to analysis. After the subtraction, the scripts
29
first find the intensity of the brightest pixel of all frames, then use 5-15% of the intensity
as a threshold to distinguish CPNs from the background noise (a higher threshold might be
needed, if the autofluorescence is not effectively corrected). For each frame, the scripts
search for pixels above the threshold and compare their intensities to the neighboring pixels
to roughly locate the central pixel of the fluorescence spot of each CPN. Then the
fluorescence centroid positions of the CPNs were determined by nonlinear least-squares
fitting of a 2D Gaussian function to the fluorescence spots. Typically 9×9 pixels were used
for the fitting (4 pixels on each side of the central pixel). The scripts check the FWHM
obtained from the fitting to make sure it is not from multiple nearby CPNs. The localized
positions obtained from each frame were then used to construct the shape of the sample.
In general, there are typically a few percent of the CPNs showing minimal photoblinking,
consistent with large particles or aggregates. It was observed that the non-blinking particles
or aggregates in the image exhibit highly correlated slow movement in the centroid
position, due to drift and vibrations from the environment. For each frame, the non-blinking
particles were used as markers to measure at each frame how far the sample travelled
relative to the previous frame, allowing us to apply a vibration correction needed for the
experiment. The displacement was then subtracted from the localized positions of all the
CPNs in the current frame. The experimental localization precision can be measured in
multiple ways. For photoswitching CPNs, the experimental localization precision was
determined from the standard deviation of the localized position distribution (i.e., the per-
frame position uncertainty is obtained from a sequence of consecutive frames during an
“on” cycle). For CPNs showing clear movements in the fluorescence centroid caused by
30
polaron motion, the experimental localization precision was determined from the root mean
square displacement of the centroid position trajectory at lag time 0. Under typical imaging
conditions, due to the high brightness of CPNs, the number of photons used in the
localization is typically large (>2000). The experimentally determined localization
precision is consistent with the theoretical localization uncertainties determined from the
equation 𝜎 = 𝑠 √𝑁⁄ , where s is the standard deviation (STD) of the PSF and N is the
number of detected photons used in the fitting. When the number of photons used in the
localization is small (<1000), addition source of localization uncertainty should be
considered. Thompson and collaborators modeled the effect of pixel size and background
noise on the localization precision (assuming a gaussian PSF), which is given by the
following expression,70
𝜎 = √𝑠2
𝑁+𝛼2/12
𝑁+8𝜋𝑠4𝑏2
𝛼2𝑁2,(14)
where s is the STD of the PSF and N is the number of detected photons used in the fitting,
𝛼 is the pixel size, b is the background noise. STD of the single particle fluorescence spot
is 130 nm. The pixel size of the setup is 66 nm and the background noise (due primarily to
readout noise, autofluorescence, and scattered light) ranges from roughly 1.5 to 10,
depending on conditions. Assuming N=2000 and b=1.5, we obtained a localization
precision of ~3.0 nm. The first term (shot noise) on equation 14 contributed to 95% of the
uncertainty. The second (pixel size) and the third term (background noise) only contributed
to 5%. If we lower the number of detected photons to 500, the shot noise term still
contributed to 85% of the uncertainty, the background noise contributed to 14% and the
31
pixel size term only contributed to <1%. According to these results, the shot-noise-limited
expression, 𝜎 = 𝑠 √𝑁⁄ is fairly accurate for most of the conditions. Only when N<1000,
background noise needs to be considered. However, in some cases, due to the presence of
a high background caused by autofluorescence of the sample or residual fluorescence of
dyes or particles in the “off” state, background subtraction is required to perform single
particle localization. The subtraction procedure can introduce additional uncertainty (for
example, shot noise from autofluorescence), and thus equation 14, would not be a reliable
estimate of the overall localization uncertainty. In such cases, experimental uncertainty is
typically compared to computer-generated quasi-random data with noise characteristics
that closely match the experiment. In other words, a Monte Carlo approach to estimating
the expected localization uncertainty is performed, based on the standard Monte Carlo
approach for propagating uncertainty.80
32
CHAPTER THREE
RESULTS
3.1 Improved superresolution imaging using telegraph noise in organic
semiconductor nanoparticles
Reprinted and adapted with permission from Ref 24. Copyright (2017) American Chemical
Society.
In recent years, driven by the interest of studying biological structures and processes
beyond the diffraction limit, superresolution imaging techniques have undergone rapid
growth. Various photophysical processes, such as, photoactivation,27 photoswitching,28
stimulated emission81 and inter-system crossing28, have been utilized to overcome the
diffraction limit. The development of superresolution fluorescent probes, including
photoactivatable proteins,27, 82 photoswitchable dyes,83, 84 and nanoparticles85, 86 have
improved the spatial resolution of optical microscope to <10 nm, which enables us to image
cellular structures in an unprecedented level of detail.
To further improve the spatial resolution of superresolution microscopy,
photoswitchable fluorescent probes with high brightness, good reversibility, and high
on/off contrast are required. Owing to the exceptional brightness and photostability of
CPNs,19-22 there has been considerable interest in developing photoswitchable nanoparticle
based on CPNs.23, 86 Previous efforts in modifying CPNs or other fluorescent nanoparticles
for superresolution imaging typically involve incorporating or linking photochromic dyes
33
to the nanoparticles. However, these nanoparticles either do not exhibit single-step
switching or suffer from poor on/off contrast due to incomplete quenching of the
nanoparticle fluorescence. In this work, we demonstrate a novel method that utilizes
controlled reversible generation and recombination of hole polarons inside CPNs to
achieve superresolution imaging. Hole polarons are known to be highly efficient
fluorescence quenchers in conjugated polymer systems.45, 63, 87, 88 Nanoparticles of the
conjugated polymer PFBT doped with the fullerene derivative PCBM, rapidly establish a
large population of hole polaron charge carriers sufficient to nearly suppress nanoparticle
fluorescence. However, fluctuations in the number of charges lead to occasional bursts of
fluorescence, which is similar to the random telegraph signal noise observed in
semiconductor devices.89 The repeated, spontaneous generation of short, intense bursts of
fluorescence photons (3-5×104 photons detected per switching event, on average) are
roughly 1-2 orders of magnitude brighter than those of photoswitching dye molecules,
resulting in a localization precision of ~0.6 nm, about 4 times better than the typical
resolution obtained by localization of dye molecules.90
3.1.1 Nanoparticle Preparation and Characterization
Nanoparticles of the conjugated polymer PFBT doped with various percentages of
PCBM were prepared using nano-precipitation method described previously.71, 74, 91 20
ppm solutions of PFBT and PCBM in THF were prepared and filtered through a 0.45 μm
membrane filter (Millipore). The solutions of PFBT and PCBM were mixed in various
ratios to form precursors of varying dopant percentages (5%, 10%, 20%, 40%), 2 mL of
the precursor solution was rapidly injected into 8 mL of water under mild sonication. Then
34
the THF solvent was removed by partial vacuum evaporation. After evaporation, the
sample was filtered through a 100 nm membrane filter (Millipore) to remove aggregates.
Figure 3.1. (a) Chemical structures of PFBT and PCBM. (b) Number weighted particle size
distributions of PCBM doped PFBT CPNs at various PCBM doping percentages, determined from
DLS measurements. (c, d) Normalized absorption and fluorescence spectra (excited at 450 nm) of
PCBM doped PFBT CPNs at various PCBM doping percentages.
The size distribution of the nanoparticles was determined using AFM and DLS. No
significant difference in particle size was observed throughout the doping range, as shown
in Fig. 3.1 b and Fig. 3.2. The typical particle sizes determined from AFM and DLS are
10.2±3.5 nm, 14.4±4.4 nm in diameter, respectively. As PCBM doping percentage
increases, the nanoparticle absorption at low wavelength (< 400 nm) increases, which
corresponds to PCBM absorption, while the absorption peak of PFBT remains unchanged
at 450 nm (Fig. 3.1 c). The presence of PCBM effectively quenched the fluorescence of
35
PFBT--at 5% PCBM doping ratio, the fluorescence quantum yield dropped by 70% as
compared to undoped PFBT CPNs (Fig. 3.1 d).
Figure 3.2. (a) AFM image and (b) size distribution of 5% PCBM doped PFBT nanoparticles
(12.9±5.8 nm); (c) AFM image and (d) size distribution of 10% PCBM doped PFBT nanoparticles
(10.7±3.9 nm); (e) AFM image and (f) size distribution of 20% PCBM doped PFBT nanoparticles
(9.9±4.2 nm); (g) AFM image and (h) size distribution of 40% PCBM doped PFBT nanoparticles
(10.2±4.5 nm).
36
3.1.2 Single Particle Fluorescence and Localization Study
The single particle fluorescence study of PCBM doped PFBT CPNs was carried out with
an inverted microscope. The CPNs were dispersed on a glass coverslip and excited with a
445 nm laser. Sequences of fluorescence microscopy images were acquired at multiple
framerates (1Hz, 10Hz or 50Hz) using a sCMOS camera, for over 600 s (fig. 3.3a). It is
found that the blinking behavior of PCBM doped PFBT CPNs is highly sensitive to the
dopant concentration. At low PCBM doping level (<10%), the fluorescence intensity of the
doped CPNs jumps between multiple levels, indicating fluctuations in the quencher
population, however, most of the nanoparticles do not turn “off” during the experiment.
When the PCBM percentage is higher (>20%), we typically observe transitions between a
dark state and multiple “on” states in the single particle fluorescence (fig. 3.3 c, d). Upon
further increase of the PCBM doping level (>40%), the frequency and duration of “on”
events is further reduced. The single particle fluorescence study was mainly focused on
20% and 40% PCBM doped PFBT CPNs because the frequency and duration of “on”
events in this doping range appeared promising for single particle localization. For some
CPNs, we observed a distinctive initial decay in fluorescence intensity followed by “on”
and “off” blinking behavior, which is likely caused by polaron population establishing an
equilibrium. A similar phenomenon was also observed for undoped CPNs, discussion and
modeling of the initial fluorescence decay dynamics arising from polaron generation was
discussed previously in our group.20
37
Figure 3.3. (a) A sequence of fluorescence microscopy images showing blinking behavior of 20% PCBM doped PFBT CPNs. (b) 3D histogram of the localized centroid position of a blinking 20% PCBM doped PFBT CPN, determined frame by frame from a trajectory acquired at 200W/cm2, 1 Hz framerate. The inserted plot shows the centroid position histogram along X axis of the same CPN, which is fitted to a Gaussian distribution (σ = 2.1 nm). (c, d) Fluorescence intensity trajectories of 20% PCBM doped PFBT CPNs acquired at 10 Hz framerate, two excitation powers, (c) 200 W/cm2, (d) 800 W/cm2, showing different duty cycles.
Since polaron generation is a photo-driven process and polaron population in CPNs is
likely to be excitation intensity dependent, we used various excitation intensities to
modulate the blinking behavior of 20% PCBM doped PFTB CPNs. For each laser intensity,
dozens of single particle blinking trajectories were analyzed. The results are summarized
in the table 3.1.
38
Table 3.1. Blinking parameters of 20% PCBM doped PFBT CPNs, determined at 50 Hz. Excitation Intensity
“On”/”off” contrast
“On” duration (s)
Duty cycle Photons detected per “on” event
Number of cycles before photobleach
200 W/cm2 10.1±4.3 8.2±5.9 0.28±0.10 5.2±2.8×104 22.6±8.8
400 W/cm2 13.9±6.2 4.9±3.5 0.16±0.07 3.8±2.0×104 19.9±6.9
800 W/cm2 15.3±6.5 3.4±1.6 0.05±0.04 3.5±2.2×104 20.7±7.4
1600 W/cm2 16.7±5.9 2.1±1.2 0.008±0.01 3.0±1.8×104 15.9±9.0
According to the table 3.1, the duty cycle of the blinking CPNs (fraction of time in the
“on” state) depends on excitation intensity. At higher excitation intensity, the increased
polaron generation rate and equilibrium population lead both to fewer “on” events per unit
time and reduced “on” state durations (Fig. 3.3 d). If we assume that the polaron population
fluctuations in CPNs follow Poisson statistics, the duty cycle 𝐷 can be written as a function
of the equilibrium polaron population in CPNs,
𝐷 = 1 −∑𝑛𝑒𝑞𝑖 𝑒−𝑛𝑒𝑞
𝑖!
𝑛𝑞
𝑖=0
,(3.1)
where 𝑛𝑞 is the number of polarons required to totally quench the fluorescence of a CPN
and 𝑛𝑒𝑞 is the equilibrium polaron population inside the CPN. Based on the previously
estimated polaron quenching efficiency (~10%) in undoped PFBT CPNs, we assume that
𝑛𝑞 = 10. According to the equation 3.1 and duty cycles determined in the table 3.1, we
estimated that the equilibrium polaron populations in 20% PCBM doped PFBT CPNs
under 200W/cm2, 400W/cm2, 800W/cm2, 1600W/cm2 excitation intensities to be 12, 14,
17, 21 respectively, assuming 𝑛𝑞 = 10. The larger polaron population at high excitation
39
intensities nearly completely suppresses the polymer fluorescence--only low probability
large fluctuations in the polaron population lead to occasional, rare fluorescence bursts.
Assuming the localization precision is shot noise limited, the theoretical localization
precision or uncertainty is given by 𝜎 = 𝑠 √𝑁⁄ , where s is the STD of the PSF and N is the
number of detected photons.70 For 20% PCBM doped PFTB CPNs, under low laser
excitation intensity (200W/cm2) and 1 Hz framerate, an average of 6.3×103 photons were
detected per frame during “on” state, yielding a theoretical per frame localization precision
of ~1.7 nm. The total number of photons detected per switching event was calculated by
integrating over all the frames during an “on” event. Under 200W/cm2, the average “on”
duration is ~8 s, an average of 5.2×104 photons were detected per switching event (1-2
orders of magnitude higher than dye molecules), resulting in an expected theoretical
localization precision of ~0.6 nm, about 4 times better than the typical resolution obtained
by localization of photoswitching dye molecules.90 The expected resolution is confirmed
by frame-by-frame centroid analysis of single burst events.
It should be noted that the polaron generation/recombination dynamics are highly
dependent on the local structure. At the polymer/PCBM interface, charge separation is
likely to be instantaneous whereas in the regions far away from the interface, charge
generation is much slower. The (proposed) mechanism of the polydot photoswitch is
described as follows. Upon excitation, reversible photoinduced charge transfer of electrons
from the polymer to the PCBM dopant quickly establishes a dynamically fluctuating
steady-state population of hole polarons on the polymer. The density of hole polarons is
40
sufficient that there are multiple overlapping quenching spheres over nearly the entire
nanoparticle volume, rendering the particle essentially nonfluorescent. We roughly
estimate that 10-30 polarons per particle is sufficient to achieve near total fluorescence
quenching. However, due to the reversible nature of the electron transfer, occasionally the
local population of hole polarons within a region of the particle drops below a threshold
amount for a period of time, such that a burst of fluorescence is emitted (additional details
and evidence supporting this mechanism, including model calculations, were reported).24
Additional experiments are required in order to obtain a complete physical picture of
charge generation/recombination processes in such a complex system.
Figure 3.4. Proposed photoswitching mechanism in PCBM-doped CPN photoswitches.
3.1.3 Superresolution Imaging of E. coli
As a proof of concept, photoswitching polydots were adsorbed on Escherichia coli (E.
coli). E. coli stocks were frozen in glycerol at -80 °C. Prior to each experiment, E. coli was
streaked on a LB-Kan-Amp plate, single colonies were selected for growth in low-
fluorescence media (1X Gibco M9 minimal media, 1% glucose, 100 ug/mL leucine, 25
41
mg/L ferric citrate, 50 ug/mL thiamine), supplemented with kanamycin and ampicillin,
overnight at 37 °C (approximately 16-20 hours).
Figure 3.5. (a) An AFM image of unlabeled E. coli, (b, c, d) Fluorescence microscopy images of
(b) unlabeled E. coli, (c) E. coli labeled with PFBT CPNs, (d) E. coli labeled with 40% PCBM
doped PFBT CPNs, imaged under 800W/cm2 excitation, 10 Hz framerates.
The bacteria were then dispersed on a glass coverslip and washed with phosphate-buffered
saline (PBS) three times. The bacteria fixation was carried out by submerging E. coli under
ice cold methanol for 10 min. The E. coli were washed with PBS buffer for three times
after fixation. The fixed bacteria were rinsed with a solution of a cationic surfactant, (1-
hexadecyl) trimethylammonium bromide (0.01M), to introduce positive charges to the
bacteria surface, then submerged under 200µL of nanoparticle suspension (~1 nM) for 30
42
mins and washed with PBS buffer afterwards. It was observed that PCBM doped PFBT
CPNs (with a zeta potential around -35mV) were efficiently adsorbed on the positively
charged bacteria surface (hundreds of CPNs per E. coli after 30 mins). In contrast, poor
labeling efficiency was observed for E. coli that had not been treated with the cationic
surfactant (0 to a few CPNs per E. coli after 30 mins), likely due to repulsion between
CPNs and the naturally negatively charged bacteria surfaces. The E. coli were imaged
under 800W/cm2 excitation, N2 atmosphere using 10 Hz framerates. E. coli labeled with
20% or 40% PCBM doped PFBT CPNs exhibited pronounced blinking (Fig. 3.6 a). While
the background autofluorescence from E. coli is typically dim as compared to the
brightness of 20% and 40% PCBM doped PFBT CPNs (Fig. 3.5 b, d), background
subtraction was performed to ensure optimal localization accuracy. The background
fluorescence was determined from frames with no CPN switched “on”. ~100 frames of the
background fluorescence were averaged and subtracted from each frame prior to analysis.
The position of each CPN was determined using the single particle localization method and
the positions obtained, were then used to reconstruct the shape of the E. coli, which is
shown by the scatter plot in Fig. 3.6 c. Analysis of the scatter plot shows that features well
below the diffraction limit were resolved. As shown in the Fig. 3.6 c subplot, the two
clusters correspond to the localized positions of two nearby CPNs, which are clearly
separated. The 33.6 nm distance between the centers of the clusters is highlighted with a
red dashed line. These results suggest that nanoparticles separated by ~30 nm are readily
resolved. From the standard deviation (𝜎𝑥 + 𝜎𝑦)/2 of the two clusters, we determined the
per frame localization uncertainty of the two CPNs to be 5.95 nm (left) and 6.82 nm (right),
43
which are consistent with the brightness of 20% PCBM doped PFTB CPNs under the
imaging conditions.
Figure 3.6. (a) A sequence of fluorescence microscopy images showing the blinking behavior
of an E. coli labeled with 20% PCBM doped PFBT CPNs. (b) A 3D fluorescence intensity map
shows a few switched “on” CPNs on an E. coli, which are indicated by the red arrows. The
inserted plot shows a 2D view of the same image with localized positions of switched “on”
CPNs indicated by red crosses. (c) A scatter plot shows the superresolution image of an E. coli
constructed from the localized positions of blinking CPNs. The subplot shows the zoomed in
view of two clusters in the scatter plot, indicating CPNs separated by ~30 nm are clearly
resolved.
44
3.2 Attempts to improve the photoswitching CPNs: PCBM Doped MEH-
CNPPV Nanoparticles
Given the exceptional brightness and photostability of CPNs,19-22 there has been
considerable interest in developing photoswitchable nanoparticle based on CPNs.23, 86 The
unparalleled brightness of photoswitching polydots and their flexible optical and other
properties could yield improvements in demanding super resolution imaging applications
such as 2D or 3D super resolution localization-based microscopy of complex samples. The
higher brightness of photoswitching polydots should help overcome autofluorescence and
scattering in complex 3D samples that can reduce signal to noise ratio. However, designing
photoswitchable CPNs have been proven to be challenging. Previous efforts in modifying
CPNs for superresolution imaging typically involved incorporating photochromic dyes into
CPNs.
In section 3.1 of this document, we demonstrated that PCBM doped PFBT nanoparticles
exhibit spontaneous photoswitching behavior with unprecedented brightness. But there is
still a lot to be improved for these nanoparticles, to further develop the photoswitching
polydots and enable application to a broad range of imaging applications. In particular, we
wanted to achieve a more even distribution of PCBM in CPNs to reduce considerable
particle-to-particle variations in brightness, duty cycles, etc.
In this direction aggregation studies were performed with nanoparticles made of
different conjugated polymers including CNPPV and MEH-CNPPV, the DLS and AFM
data showed that MEH-CNPPV suspensions have better colloidal stability than PFBT,
45
yielding a narrower range of the nanoparticle sizes. Also, we already have stablished that
the addition of PCBM did not change the size distribution for PCBM doped PFBT
nanoparticles, so it was decided to make PCBM doped MEH-CNPPV polydots to study
their photoswitching behavior and wether or not we could a narrower size distribution of
the photoswitching polydots.
3.2.1 Nanoparticle Preparation and Characterization
Nanoparticles of the conjugated polymer MEH-CNPPV doped with various percentages
of PCBM were prepared using the nano-precipitation method described previously.71, 74, 91
20 ppm solutions of MEH-CNPPV and PCBM in THF were prepared and filtered through
a 0.45 μm membrane filter (Millipore). The solutions of MEH-CNPPV and PCBM were
mixed in various ratios to form precursors of varying dopant percentages (1%, 3%, 10%),
2 mL of the precursor solution was rapidly injected into 8 mL of water under mild
sonication. Then the THF solvent was removed by partial vacuum evaporation. After
evaporation, the sample was filtered through a 100 nm membrane filter (Millipore) to
remove aggregates. The size distribution of the nanoparticles was determined using AFM
and DLS. No significant difference in particle size was observed throughout the doping
range, as shown in Fig. 3.7. The typical particle sizes determined from AFM and DLS are
11.1±1.5 nm, 13.1±2.2 nm in diameter, respectively.
46
Figure 3.7. (left) Number weighted particle size distributions of PCBM doped MEH-CNPPV CPNs at various PCBM doping percentages, determined from DLS measurements. (right) Normalized fluorescence spectra (excited at 470 nm) of PCBM doped PFBT CPNs at various PCBM doping percentages.
It is worth noting that the fluorescence was almost completely quenched at 10% PCBM
doping ratio (Figure 3.7), the fluorescence quantum yield dropped by 95% as compared to
undoped MEH-CNPPV CPNs, so the doping ratios were adjusted in comparison to the (5-
40% doping ratio used in the PCBM doped PFBT experiment).
To further analyze the data a Stern-Volmer plot was made plotting F0/F vs [Q]
(molecular ratio between the quencher and the polymer in moles).92 The equation that
represents the Stern-Volmer linear relationship was determined by least squares linear
fitting and is giving by:
𝐹0𝐹= 1 + 5.532[𝑄],𝑅2 = 0.9957(3.2)
The value 5.532 is better known as KD, and 1/ KD (0.18), represents the molecular
fraction of the quencher needed to quench the initial fluorescence by 50%.
47
3.2.2 Single Particle Fluorescence
The single particle fluorescence study of PCBM doped MEH-CNPPV CPNs was carried
out with an Olympus IX71 inverted microscope with a 100X 1.3 NA fluorescence
objective. An illumination laser is fiber coupled to the microscope for epi illumination. For
some experiments, a manual XY micrometer stage (Thorlabs) is used to manipulate the
sample. The CPNs were dispersed on a glass coverslip and excited with a 445 nm laser.
Sequences of fluorescence microscopy images were acquired at different framerates (10Hz
and 20Hz) using a sCMOS camera, for around 180s.
Figure 3.8. Fluorescence microscopy images of (a) 1% PCBM doped MEH-CNPPV CPNs (b) 10% PCBM doped MEH-CNPPV CPNs, images acquired at 400 W/cm2, 10 Hz framerate.
a b
48
Figure 3.9. (a) The trajectory of a MEH-CNPPV CPN, showing characteristic exponential photobleaching, acquired at 400 W/cm2, 20 Hz framerate. (b) The trajectory of a 1% PCBM doped MEH-CNPPV CPN, showing some blinking behavior acquired at 200 W/cm2, 10 Hz framerate. (c) The trajectory of a 1% PCBM doped MEH-CNPPV CPN, showing initial blinking behavior followed by photobleaching, acquired at 400 W/cm2, 20 Hz framerate. (d) The trajectory of a 10% PCBM doped MEH-CNPPV CPN, showing initial blinking behavior followed by photobleaching, acquired at 200 W/cm2, 10 Hz framerate.
In figure 3.9 (a) we can see the florescence decay curve for an undoped MEH-CNPPV
nanoparticle, in contrast when a percentage of the dopant is added to the nanoparticle (Fig,
3.9 b, c, d) the photobleaching behavior is modified and does not follow single or double
exponential models, and some blinking behavior is present, analogous the PCBM doped
PFBT nanoparticle already described. It is worth noting that at low PCBM doping level
(1%) most of the nanoparticles exhibit fluctuations, however, do not completely turn “off”
49
during the experiment. When the PCBM percentage is higher (10%) we observed
transitions between a dark state and multiple “on” states in the single particle fluorescence.
The death number was calculated by using the equation:
𝑁 =𝑇𝑜𝑡𝑎𝑙𝑐𝑜𝑢𝑛𝑡𝑠 ∗ 𝑔𝑎𝑖𝑛
𝑄𝑢𝑎𝑛𝑡𝑢𝑚𝑒𝑓𝑓.∗ 𝑐𝑜𝑙𝑙𝑒𝑐𝑡𝑖𝑜𝑛𝑒𝑓𝑓(3.3)
The gain factor used in the calculations was 0.6 electrons/count, the quantum efficiency
of the camera is 0.57 electrons/photon and the collection efficiency 0.03. For undoped
MEH-CNPPV nanoparticles the average death number was 7.8x107 photons and the
average intensity over the first 20 frames (1s) was 6.7x103 counts, the single exponential
time constant determined from the exponential fitting was 14.3 s in average for a collection
of CPNs. For 1% PCBM doped MEH-CNPPV CPNs the death number ranged from
1.6x107 for lower intensity to 2.8x107 photons in higher intensity nanoparticles and the
average intensity over the first 20 frames (1s) was 1.1x103 counts. In the case of 10%
PCBM doped MEH-CNPPV CPNs the death number ranged from 1.3x107 for lower
intensity to 2.2x107 photons in higher intensity nanoparticles and the average intensity over
the first 20 frames (1s) was 500 counts.
In summary, we discovered blinking behavior for the PCBM doped MEH-CNPPV
CPNs which poses these nanoparticles as a candidate for a successful photoswitching
polydot with promising potential in superresolution imaging, given the narrower size
distributions and the higher colloidal stability in comparison with PCBM doped PFBT
CPNs, also the death numbers data show that the PCBM doped MEH-CNPPV
50
nanoparticles are brighter in the “on” state than conventional dyes used for superresolution
imaging. However, the single particle fluorescence data obtained for the PCBM doped
MEH-CNPPV photoswitches was very complex and goes beyond the scope of this thesis,
for future work it is evident and necessary to improve the current methods to analyze these
sets of complex data, developing better scripts for analysis and apply segmented analysis
of the nanoparticle trajectories to achieve better understanding of how the position
trajectories varied over time. It is also important to approach this data analysis issue from
simulation analysis of the polaron dynamics, understanding the autocorrelation data and
the polaron recombination and generation rates,87 respectively.
3.3 Electric Field Modulation of CPN’s fluorescence.
Based on the demonstration that PCBM doped PFBT nanoparticles exhibit spontaneous
photoswitching behavior with unprecedented brightness, other novel ideas were considered
to explore new possible applications including electrical switching for sensing membranes
potential or even the possibility of attaching nanoparticles to neurons and being able to
report when a neuron “fires”, thus changing the membrane potential.93
There is some information published about electric fields and conjugated polymers
fluorescence, 45, 94, 95 however, there is very limited information about electric field
modulation of the photoluminescence in conjugated polymer nanoparticles. Therefore,
based on our novel fluorescent photoswitch idea, we decided to test the response of our
nanoparticles to electric fields in the single molecule level, starting with a simple use of a
voltage trying to induce photoswitching of PFBT nanoparticles.
51
The PFBT nanoparticles for this study were prepared used the same nano-precipitation
method described previously in sections 2.2 and 3.1.1.71, 74, 75 The size distribution of the
nanoparticles was determined using AFM and DLS. The typical PFBT particle sizes
determined from AFM and DLS are 14.4±2.8 nm, 16.6±3.6 nm in diameter, respectively.
In this work, the samples were prepared on Indium tin oxide (ITO) coated glass
coverslips as an electrode attached to a copper wire using silver paint. Those coverslips
were cleaned with the following steps: soap water, DI water, and plasma cleaning. Before
the addition of nanoparticles, a dielectric material polystyrene (1.5% in Toluene) was spin-
coated on top of the ITO coverslip, followed by deposition of nanoparticles on top of the
PS film by drop casting, using 200 times dilution from the nanoparticles vial previously
prepared (~0.16ppm in polymer). It is worth noting that the experiments were performed
with and without dielectric (PS), and better results were observed with PS coated film.
Once the nanoparticles were deposited on the coverslip and placed on top of the
inverted microscope objective, a drop (~100 uL) of 0.01 M NaCl solution was placed in
the middle of the coverslip and a platinum wire was held inside the electrolyte solution.
These experiments were performed initially using DI water only, but there was no electric
field modulation observed. After adding the electrolyte, the system was connected to a
RIGOL wave form generator, and an oscilloscope in parallel to measure the voltage. Square
wave forms were used in most of the experiments, with different frequencies and
amplitudes of the electric field. The best results were obtained by using a -2V – 0V square
wave and pulses of 1-5 s of duration.
52
The single particle fluorescence study of PCBM CPNs was carried out with an inverted
microscope and the excitation laser at 445 nm. Sequences of fluorescence microscopy
images were acquired at 10Hz using a sCMOS camera, for over 120 s under a 100 W/cm2
excitation.
Figure 3.10. (a) Fluorescence intensity trajectories of PCBM CPNs modulated by -2V-0V
square wave pulses acquired at 10 Hz framerate, and excitation power of 100 W/cm2. (b) Data
zoomed for the first 30 s, showing the 1s square pulses on top of the fluorescence intensity
graph.
53
The results from the experiments shown in figure 3.10 show that there is an evident
effect on the photoluminescence of the PFBT nanoparticles under the influence of an
electric field, the intensity of the fluorescence goes up and down when turning the electric
field on instead of following the regular photobleaching exponential decay observed when
there is no external electric field applied in the system. These preliminar results are very
promising and lead us to believe that new possible applications including electrical
switching for sensing membranes potential or even the possibility of attaching
nanoparticles to neurons is possible, however it is necessary to pursue more elaborate
experiments to understand the mechanisms of charge transport in order to be able to
develop nanoparticles or photoswitches that can be sensible to electric fields at the cell
level.
3.4 DNA wrapped polydots development.
We recently demonstrated the first polydots or CPNs with excellent switching
characteristics for localization microscopy.24 Continuing with the overall research plan to
further develop the photoswitching polydots to enable application to a broad range of
imaging applications, we decided to pursue novel approaches for polydot sensors based on
DNA-wrapped particles. Based on reports of carbon SWNT wrapped with DNA and RNA
prepared by sonication,96 it was decided to attempt this with polydots to produce DNA-
wrapped polydots (i.e., DNA adsorbed on the particle surface). The initial efforts of this
initiative are shown in this thesis, focused on development of protocols for wrapping
polydots in DNA oligomers, and the discovery that the hybrid DNA polydots have the
potential to act as sensors for neurotransmitters such as dopamine.
54
Nanoparticles of MEH-CNPPV were prepared and characterized using the procedures
previously described on section 3.2.1 of this document. It is worth noting that MEH-
CNPPV was selected for this study due to its better colloidal stability as shown in previous
results. The typical MEH-CNPPV particle sizes determined from AFM and DLS are
11.1±1.5 nm, 13.1±2.2 nm in diameter, respectively. Several buffers were made to test the
best option to keep the pH above 7.4 and at the same time to have a low degree of
aggregation for the MEH-CNPPV nanoparticles. The best option was selected to be TE
(Tris-EDTA) 1mM buffer 7.8 pH. All dilutions were performed using this buffer.
The MEH-CNPPV suspension was diluted to a final concentration of 1.5 ppm of
polymer. This concentration was determined by absorbance measurements, where 67% of
the material was recovered after sample preparation and 93% after filtration, yielding a
total of 63% recovery (~37% loss). Two DNA oligomers samples PGEX3 and ss(GA)15
(purchased from Integrated DNA Technologies) were diluted to a 0.6 ppm concentration
and mixed under sonication (4 minutes) with the MEH-CNPPV nanoparticle suspension.
At this point absorbance and fluorescence spectra were taken and no changes were
observed due to the presence of DNA. Finally, dopamine was added to the mixture to a
final concentration of 20uM dopamine, 0.6 ppm MEHCNPV and 0.24 ppm DNA, no
changes in the absorbance were observed and the fluorescence data is shown as follow in
figure 3.11.
55
Figure 3.11. Normalized fluorescence spectra for the samples and the control experiment using
an excitation wavelength of 445 nm.
It is worth nothing that the addition of dopamine to the nanoparticles suspension does
not affect the fluorescence, but when mixed with DNA the fluorescence peak is enhanced
by a factor of 6.3 for the ss(GA)15 DNA and 4.8 for PGEX3’ commercial sequence
respectively as shown in figure 3.11. This experiment result is very interesting as we
demonstrated that the addition of dopamine to DNA wrapped MEH-CNPPV nanoparticles
enhances the fluorescence significantly and opens the possibility of doing superresolution
imaging of cellular dopamine efflux and to resolve where on the cell surface dopamine is
released and how cell morphology affects the location of release sites,97 among other
possible applications.
56
CHAPTER FOUR
GENERAL CONCLUSIONS AND FUTURE DIRECTIONS
4.1 Conclusions and future directions
In summary, we have developed a new class of fluorescent nanoparticles for
superresolution imaging with significantly improved spatial resolution. PCBM doped
PFBT CPNs establish large polaron populations inside the nanoparticles that nearly
completely suppress the polymer fluorescence. However, fluctuations in the number of
charge carriers lead to occasional bursts of fluorescence. For 20% PCBM doped PFBT
CPNs, we determined that around 3-5×104 photons were detected during the fluorescence
burst, which results in a localization precision of ~0.6 nm, about 4 times better than typical
resolution obtained by localization of dye molecules.
Since polaron generation is a photo-driven process, we showed that the blinking duty
cycle of PCBM doped PFBT CPNs can be controlled by excitation intensity as well as by
PCBM fraction. Finally, we demonstrated superresolution microscopy of E. coli using 20%
PCBM doped PFBT CPNs. At 10 Hz framerates, we obtained the precise shape of the
bacteria with a localization precision of ~5 nm. These results suggest that PCBM doped
PFBT CPNs represent a novel class of promising superresolution probes with
unprecedented localization precision and tunable spontaneous photoswitching (blinking)
properties, which provide clear advantages for imaging of various biological systems.
57
Other efforts to improve these photoswitches were attempted and it was encountered
that PCBM doped MEH-CNPPV nanoparticles also exhibit spontaneous blinking, with the
advantage of having a better colloidal stability and narrower distribution sizes, which is
important for better measurements on biological systems. For future directions in order to
improve this PCBM doped MEH-CNPPV photoswitch it is necessary to perform more
single particle fluorescence measurements to probe the relevant photochemistry and
photophysics. Also blinking kinetics experiments as a function of excitation intensity,
determining the effect of various particle compositions and surface functionalities, and
blending and doping. This will help to understand how the various components are
interacting, and whether undesired processes are occurring that could interfere with the
photoswitching process. It is important to analyze the data to treat the nanoparticles as a
diverse population, collecting and interpreting results representing the overall distribution
of particle properties and particle-to-particle variability.
Finally, we developed protocols for wrapping polydots in DNA oligomers, and
discovered that the hybrid DNA polydots can act as sensors for neurotransmitters such as
dopamine, resulting on a very promising, novel approach to chemical sensing in polydots,
which could yield a broad range of useful sensors for chemical microscopy. We found that
the resulting nanoparticles exhibited a roughly six-fold enhancement in fluorescence in the
presence of biologically relevant concentrations of a neurotransmitter. This could provide
the basis for a “turn-on” sensor for neurotransmitters that can be used in imaging of neuron
dynamics. Additionally, we can combine in future work the sensing with photoswitching,
for super resolution chemical microscopy.
58
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