Multi-step non-covalent pathways to supramolecular systems
Citation for published version (APA):
Hermans, T. M. (2010). Multi-step non-covalent pathways to supramolecular systems. Technische Universiteit
Eindhoven. https://doi.org/10.6100/IR672791
DOI:
10.6100/IR672791
Document status and date:
Published: 01/01/2010
Document Version:
Publisher’s PDF, also known as Version of Record (includes final page, issue and volume numbers)
Please check the document version of this publication:
• A submitted manuscript is the version of the article upon submission and before peer-review. There can be
important differences between the submitted version and the official published version of record. People
interested in the research are advised to contact the author for the final version of the publication, or visit the
DOI to the publisher's website.
• The final author version and the galley proof are versions of the publication after peer review.
• The final published version features the final layout of the paper including the volume, issue and page
numbers.
Link to publication
General rights
Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights. • Users may download and print one copy of any publication from the public portal for the purpose of private study or research. • You may not further distribute the material or use it for any profit-making activity or commercial gain
• You may freely distribute the URL identifying the publication in the public portal.
If the publication is distributed under the terms of Article 25fa of the Dutch Copyright Act, indicated by the “Taverne” license above, please follow below link for the End User Agreement:
www.tue.nl/taverne
Take down policy
If you believe that this document breaches copyright please contact us at: openaccess@tue.nl
Multi-step non-covalent pathways to
supramolecular systems
PROEFSCHRIFT
ter verkrijging van de graad van doctor aan de Technische Universiteit Eindhoven, op gezag van de rector magnificus, prof.dr.ir. C.J. van Duijn, voor een commissie aangewezen door het College voor Promoties in het openbaar te verdedigen op donderdag 6 mei 2010 om 16.00 uurdoor
Thomas Marinus Hermans
geboren te Turnhout, België
Dit proefschrift is goedgekeurd door de promotor: prof.dr. E.W. Meijer Copromotor: dr.ir. M.H.P. van Genderen
This research has been financially supported by the BSIK program entitled: Molecular Imaging of Ischemic Heart Disease (project number BSIK03033) A catalogue record is available from the Library of the Eindhoven University of Technology ISBN: 978‐90‐386‐2218‐7 © T.M. Hermans 2010 Cover design: ICMS animation studio (Koen Pieterse) Printed by: Wöhrmann print service (WPS), Zutphen, The Netherlands
Multi-step non-covalent pathways to
supramolecular systems
Kerncommissie: prof.dr. E.W. Meijer (Technische Universiteit Eindhoven) dr.ir. M.H.P. van Genderen (Technische Universiteit Eindhoven) prof.habil.dr. G. Fytas (University of Crete, IESL‐FORTH & Max Planck Institute for Polymer Research Mainz) dr. A.P.H.J. Schenning (Technische Universiteit Eindhoven) prof.dr. B.A. Grzybowski (Northwestern University) Overige commissieleden: prof.dr. J.A. Put (Universiteit Hasselt & DSM Innovation Center) prof.dr.ir. H.E.H. Meijer (Technische Universiteit Eindhoven) Voorzitter: prof.dr.ir. B.M. ter Haar Romenij (Technische Universiteit Eindhoven)
Brief Contents
Chapter 1 Self‐assembled structures using supramolecular building blocks 1 Chapter 2 Dendrimer‐based guest–host complexes in chloroform 23 Chapter 3 Multi‐step non‐covalent synthesis leading to 69 dendrimer‐based assemblies in water Chapter 4 Dilution‐induced self‐assembly of dendrimer‐based 81 guest–host particles in water Chapter 5 Multivalent supramolecular dendrimer‐based drugs 101 Chapter 6 Tunable supramolecular hydrogels 117 Chapter 7 Supramolecular guest–host interactions 141 studied by H‐cell microfluidics Epilogue Conclusions and outlook 185 Summary 187 Samenvatting 191 Curriculum Vitae 195 List of Publications 197 Dankwoord 199Contents
Chapter 1 Self‐assembled structures using supramolecular building blocks 1 1.1 Self‐assembly: structures arising from building blocks 2 1.2 Self‐assembly kinetics: influences of diffusion, interaction probability 7 and reversibility of interactions 1.3 Timescale of interactions versus timescale of analysis 11 1.4 Supramolecular Chemistry: non‐covalent assembly of building blocks 13 1.5 Better control over self‐assembly: stepwise self‐assembly 14 1.6 Aim and outline of this thesis 17 1.7 References 20 Chapter 2 Dendrimer‐based guest–host complexes in chloroform 23 2.1 Introduction 24 2.2 Non‐covalent dendrimer interactions: the urea–adamantyl motif 28 2.2.1 Guest–host binding investigated: introduction 29 2.2.2 Guest–host binding investigated: results from 1 H DOSY NMR 34 2.2.3 Influence of guest–guest dimerization on guest–host binding 35 2.3 Multivalent guest molecules 38 2.3.1 Introduction to multivalency 38 2.3.2 Synthetic route to multivalent molecules 38 2.3.3 Multivalency theory: non‐cooperative binding leads to chelate cooperativity 41 2.3.4 Results: guest–guest interactions 45 2.3.5 Results: multivalent guest–host interactions 46 2.3.6 Discussion 49 2.4 General conclusions 51 2.5 Experimental section 52 2.6 References 59 2.7 Appendices 62 2.7.1 Appendix: MAPLE script for multivalent guest molecules 622.7.2 Appendix: Determining Ceff by molecular dynamics 66
Chapter 3 Multi‐step non‐covalent synthesis leading to dendrimer‐based assemblies in water 69 3.1 Introduction 70 3.1.1 Introduction to magic angle spinning (MAS) NMR 71 3.2 Analyzing the guest–host complexes in the neat state by MAS NMR 72 3.3 From the neat state towards aqueous solution: atomic force microscopy 74
3.5 Concluding remarks 77 3.6 Experimental section 78 3.7 References 78 3.8 Appendix 79 Chapter 4 Dilution‐induced self‐assembly of dendrimer‐based guest–host particles in water 81 4.1 Introduction 82 4.2 Results trapped‐core particles (n/B < 1) in aqueous solution 83 4.3 Results patchy particles (n/B > 1) in aqueous solution 87 4.4 Conclusions and discussion 93 4.5 Experimental section 94 4.6 References 97 4.7 Appendix 99 Chapter 5 Multivalent supramolecular dendrimer‐based drugs 101 5.1 Introduction 102 5.2 Approach to supramolecular polymer therapeutics 102 5.3 Affinity of the guest molecules towards the 5‐HT3 receptor 103 5.4 Affinity of the guest molecules towards the dendrimer host in chloroform 104 5.5 Guest–host complexes of dendrimer host and bioactive guests in water 107 5.6 Concluding remarks 108 5.7 Experimental section 109 5.8 References 114 5.9 Appendix 115 Chapter 6 Tunable supramolecular hydrogels 117 6.1 Introduction 118 6.1.1 Multiple hydrogen‐bonding supramolecular polymers 119 6.2 Synthesis and macroscopic analysis of UPy‐hydrogelators 120 6.3 UPy‐10‐PEG‐Zk polymers 122 6.3.1. UPy‐10‐PEG‐Zk polymers: neat state analysis 122 6.3.2 UPy‐10‐PEG‐Zk polymers: dilute aqueous solution 123 6.3.3 UPy‐10‐PEG‐Zk polymers: hydrogels at higher concentrations 125 6.4 UPy‐10‐PEG‐Zk hydrogels: a drug release model system 128 6.5 UPy‐based supramolecular hydrogels for growth factor delivery 129 6.6 Concluding remarks 131 6.7 Experimental section 133
6.9 Appendix 139 Chapter 7 Supramolecular guest–host interactions studied by H‐cell microfluidics 141 7.1 Introduction to microfluidics: fluid handling at a small scale 142 7.2 The H‐cell 144 7.2.1 The H‐cell: introduction 144 7.2.2 Diffusion in an H‐cell: influence of pressure‐driven flow 148 7.3 Results: diffusion in the H‐cell by confocal microscopy 151 7.4 Guest–host binding in the H‐cell 155 7.4.1 Guest–host binding in the H‐cell: theory and simulations 155 7.4.2 Guest–host binding in the H‐cell: model systems 159 7.5 Binding interactions in the UPy‐10‐PEG‐10k system 161 7.5.1 Fluorescence correlation spectroscopy on UPy‐Rho and UPy‐10‐PEG‐10k 162 7.5.2 H‐cell experiments on UPy‐Rho and UPy‐10‐PEG‐10k 165 7.5.3 Discussion 169 7.6 General conclusions 172 7.7 Experimental section 174 7.8 References 177 7.9 Appendices 179 7.9.1 Appendix: additional FCS analysis 179 7.9.2 Appendix: MATLAB data conversion script 179 7.9.3 Appendix: MATLAB model and fitting procedure 181 7.9.4 Appendix: Additional fits of H‐cell experiments type 1, 2 and 3 (micelle) 184 Epilogue 185 Summary 187 Samenvatting 191 Curriculum Vitae 195 List of Publications 197 Dankwoord 199
1
Self-assembled structures using supramolecular
1.1 Self‐assembly: structures arising from building blocks
Self‐assembly is the reversible organization of pre‐existing building blocks into ordered structures without human intervention.1
This magical order from disorder is very appealing to the human eye and common in natural systems. There is a limit, however, to the operational domain of these spontaneous assembly processes, which is mainly determined by the size of the building blocks and the patience of the researcher. Frenkel’s definition of this limit says that the building blocks should be able to move around due to thermal (“Brownian”) motion and that they should do so at a reasonable timescale.2 A benchmark for this (“Smoluchowski”) time is the time (τ) it takes a particle to move its own diameter, which is defined by: 3 3 ( ) 2 k TB (1.1)
Where η is the viscosity of the solution, σ the particle diameter (spherical), kB Boltzmann’s
constant and T the temperature. For a 1 μm particle this in the order of seconds, but for a 1 kg brick in a density matched solvent it is already 10 million years (τ ~ σ3
). Basically, the interesting regime on a human timescale is found for particles smaller than about 1 μm.
For successful self‐assembly to take place, not only should the building blocks be able to move around, they should also interact with one another. These interactions can be attractive or repulsive and stem from different origins. For molecules we distinguish: ionic (Coulomb; attractive/repulsive), van der Waals (London dispersion; attractive), dipole– dipole (Coulomb, Debye, Keesom, London; attractive/repulsive), hydrogen‐bonding (attractive) and aromatic (π–π; attractive) interactions, which all have different strengths and scaling relations (with respect to distance). The summation of attractive and repulsive components yields an overall interaction potential, which can be used to describe the interaction between two and eventually multiple building blocks (Figure 1.1). The scaling with distance (~ r–n) of the attractive forces is typically in the order of n = 1 to n = 7 and relatively long‐range compared to the repulsive forces, n = 9 to n = 15 (Figure 1.1). The interaction potential depends on the chemical environment surrounding the building blocks, which is in most cases dominated by the solvent used to solubilize the components.
The interactions between building blocks larger than small molecules (e.g. protein or colloids) and/or surfaces have been described using similar scaling relations: electrostatic (attractive/repulsive), van der Waals (attractive), steric (repulsive), hydrophobic (attractive) and capillary/menisci (attractive/repulsive) interactions.3
Repulsion can be caused by the fact that solid bodies cannot interpenetrate (due to the Pauli exclusion principle), by short‐ranged Coulomb interactions or because of entropic contributions (e.g. a polymer brush on a colloid). These types of potentials hold for particles that have the same interactions in all directions: so‐called isotropic particles (Figure 1.3a).
Figure 1.1: The interaction energy versus the distance between two isotropic building blocks. The summation of the attractive and repulsive interactions is called the interaction potential. The well‐ known Lennard–Jones potential (LJ), used for molecular size building blocks, is an example of an interaction potential built up from a repulsive (r–12
) and attractive (r–6
) component (ξ and β are constants). An analogous potential for larger building blocks is the Derjaguin–Landau–Verwey‐ Overbeek or DLVO potential.4 The hatched area cannot be reached since the building blocks are touching each other (r = 2Rs). Such isotropic particles can assemble into well‐organized structures at different length scales (Figure 1.2). Most of the interactions acting between the building blocks can be tuned by changing the composition of the solvent in which the self‐assembly is being performed. a b c Figure 1.2. Assemblies of isotropic building blocks (like those schematically depicted in Figure 1.3a) at different length scales. a) A thin gold film imaged using a 1 MV field emission microscope showing individual gold atoms (scale bar is 250 pm).5 b) AB2 super lattice of 9 nm PbSe (A) and 3.4 nm CdSe (B) nanoparticles (scale bar is 20 nm).6
c) AB3 super lattice of 203 nm (A) and 101 nm (B) silica nanoparticles (scale bar is 5 μm).7
Many types of established potentials (i.e. the summation of attractive and repulsive interactions), such as the Yukawa‐type, hard‐sphere and sticky Baxter, have been successfully used to describe a wide range of self‐assembly processes. This is in some cases quite remarkable if the building blocks described are examined in more detail. Proteins for example are very inhomogeneous particles with often charged or hydrophobic patches present at their surface. Applying one of the previously described potentials to such a system seems awkward, since they are all spherically symmetric, or in other words, the attractive and repulsive interactions are assumed to be the same in all directions. Recently, models that do explicitly include attractive or repulsive patches on the surface of the particles have been
developed and they show a wealth of intricate modes of self‐assembly not seen before in the spherically symmetric models (Figure 1.3.b and c).8–12 N N R O H N H N O H R N N R O H N H N O H R N N N N O N O N R H R H H H N N N N O N O N R H R H H H N N N N O N O N R H R H H H N N N N O N O N R H R H H H N N N N O N O N R H R H H H N N N N O N O N R H R H H H a b c = =
Figure 1.3: Symmetric versus non‐symmetric interactions. a) A spherically symmetric interaction potential, analogous to for example an ion–ion interaction. Ordered structures like e.g. the NaCl crystal lattice can be obtained when the attractive forces are large enough. b) An attractive patch is positioned at a fixed location on the surface of the building block, which gives rise to various interesting structures that cannot be obtained with a spherically symmetric potential. c) If one patch is present per building block, dimers are formed; two patches under a 60 degree angle can give rise to hexamer rosettes. Molecular analogues based on multiple hydrogen‐bonding systems are shown next to the structures: the quadruple hydrogen‐bonding ureidopyrimidinone dimer13 and macromolecular rosettes14 . Figure 1.4. Various anisotropic building blocks. a) An assembly consisting of 8 nm gold nanoparticles connected to a 31 nm gold particle using complementary DNA strands (scale bar is 20 nm)15 . b) Small gold nanoparticles ligated to a (cowpea mosaic) virus particle (scale bar is 5 nm). On the right the schematic representation of the assembly is shown.16 c) Polymer nanoparticles with bumpy and chain‐ segregated surfaces (scale bar is 100 nm).17
d) Tetrapod particles obtained by linking CdSe nanorods to the tetravalent avidin protein using a biotin linker (scale bar is 100 nm).18
e) Macroscopic PDMS hexagons with alternating hydrophobic and hydrophilic edges self‐assemble into open networks (scale bar is 1 cm).7
f) A tetrahedral particle consisting of four polystyrene particles (scale bar is 1 μm).19
g) ABA ternary particles made using a microfluidic flow focusing device (scale bar is 100 μm).20
In supramolecular chemistry the hydrogen bond has for long been used to create a highly directional interaction (Figure 1.3c). More recently, also anisotropic (nano)particles have been developed with a rich structural variety. These particles can be isotropic in shape,
but have anisotropic interactions or they can be anisotropic in both aspects. How the self‐ assembly process changes for such particles has been studied in macroscopic systems (Figure 1.4e), however, for manmade micro‐ and nanoscopic anisotropic building blocks such studies are still at an early stage.
A conceptually more difficult aspect of assembly is the contribution of enthalpy (H) and entropy (S) to the self‐assembly process. Let’s assume the temperature (T), the pressure and the number of molecules stay constant during self‐assembly. The process will occur spontaneously when the change (Δ) in Gibbs free energy (G) is negative, ΔG = ΔH – TΔS < 0. This is true for ΔH < 0, ΔS ≈ 0 (enthalpy driven) or ΔS > 0, ΔH ≈ 0 (entropy driven) or a combination of the two. Since a self‐assembled structure looks more ordered than an isotropic solution of the building blocks one would expect it to have less freedom (ΔS < 0); it is thus often concluded that enthalpy is needed to counterbalance the entropic contribution. However, many rod‐like systems self‐assemble into ordered patterns even when they have additional repulsive interactions making the assembly enthalpically unfavorable. Such rods actually have more degrees of freedom in the ordered state even though this is counterintuitive at first sight.
Figure 1.5: Schematic representation of stability. If the energy barrier (ΔEc) is much larger than the thermal energy (kBT) the system will not overcome it and will remain kinetically stable. If the barrier,
however, is around or below kBT the systems will eventually reach its thermodynamically stable state
(before reaching this lowest energy state it is called metastable). Scheme adjusted from Hiemenz– Rajagopalan.21
Irrespective of the driving forces for the assembly process, the question is often if a true thermodynamic equilibrium state can be reached (Figure 1.5). If the transition of diamond to graphite is considered, thermodynamic equilibrium is not very relevant. What is more interesting is whether a system is stable in the time it is analyzed or used, which does not mean there cannot be dynamics. Stable assemblies can consist of many building blocks constantly moving about or exchanging, while on average maintaining the overall structure. Moreover, the preparation method taken to obtain the final structure is of key importance.
The toolbox to steer the building blocks along certain pathways through the energy landscape—dictating the eventually obtained structure—is ever expanding. In molecular systems this is termed stepwise non‐covalent synthesis, which will be explained in more detail in section 1.5.
Lastly, systems do not have to be in a local or global energy minimum, referring to kinetic and thermodynamic stability, respectively, to be able to form well‐ordered assemblies. Actually, in Nature many assemblies manage to reside in yet another state, not in a local or global energy minimum. Such systems need to dissipate energy and produce entropy constantly to retain their structure. They are referred to as self‐organized structures or dynamic self‐assemblies22
, though attempts to make this nomenclature universal have not succeeded yet. As soon as the energy flow is stopped, the assemblies disintegrate. Traditional thermodynamics cannot be used to describe such self‐organized systems and new theory is at this point non‐existent.* Non-dissipating (Thermodynamically or kinetically stable) Dissipating (Non-equilibrium) dE1 dE2 dQ2 dQ1
Figure 1.6: Schematic representation of the differences between an ordered structure formed from building blocks under thermodynamic equilibrium or which is kinetically stable (on the left). The system retains its order when it is in a closed environment (i.e. no energy is exchanged). For a non‐ equilibrium structure (on the right) energy has to be supplied to the system constantly (dE1). A different rate of energy influx (dE2) can result in a different structure. For all non‐equilibrium systems an arrest of the energy supply results in disintegration of the structure. Scheme adjusted from reference 22.
Many biological assemblies are self‐organized and are sustained by the ATP–ADP (adenosine tri‐ and diphosphate, respectively) cycle of the metabolic process. Rotating magnetic fields were used by Grzybowski et al. to obtain one of the few manmade self‐ organized assemblies.23–24 Small polymer discs attract each other because they contain magnetite and thus act as small magnets. Repulsive interactions between the discs are induced by spinning them about their axis, creating a local fluid motion in their vicinity (Figure 1.7).
So far we have seen that for the spontaneous assembly of building blocks < 1 μm a range of (a)symmetric attractive and repulsive interactions have to be tuned along a specific
pathway to arrive at the desired stable (dissipating or non‐dissipating) structure. The rate at which the building blocks assemble can have a large impact on the structure, which will be described in the next section.
Figure 1.7. Magnetic millimeter‐sized discs form self‐organized patterns at the air–water interface by the interplay of magnetic attraction and hydrodynamic repulsion. a) The discs float on the liquid surface and rotate around their axis at the same speed (ω) as the magnet under the discs. b) Various patterns can be obtained from isotropic discs depending on the number present in the system (shown 1 to 6 discs). c) Chiral discs (R and S) have more complex behavior. Like for the isotropic discs the structure depends on ω, but the handedness of rotation of the macroscopic magnet is now an additional factor that contributes to the various structures. Figure modified from references 23‐24.
1.2 Self‐assembly kinetics: influences of diffusion, interaction probability and reversibility of interactions
So far, a number of possibilities to obtain ordered structures from building blocks were described. To arrive at such a stable state takes time, which is described by kinetics. In this section chemical or enzymatic kinetics will not be considered. To start off easy, we consider the assembly of identical, spherical particles with an isotropic force distribution (Figure 1.3a) in solution (monomers). Depending on the magnitude of the effective attraction, the probability of adhesion on contact (pa) is variable. So, when pa = 1 the monomers always stick
to each other upon contact, for pa smaller than 1 the chance of sticking is less than unity and
for pa equals zero they do not stick at all. In the former case, the growth of assemblies of
many monomers is limited by the rate at which new monomers can be supplied to the growing structure, which is called “diffusion‐limited”. For pa smaller than 1 the monomers
have already diffused towards the structure, but they need several tries to finally attach yielding much denser structures, which is termed “reaction‐limited” (Figure 1.8). In the simplest case only the monomers attach to the growing structure (“monomer–cluster” assembly, Figure 1.8). In solution, however, it is likely that small monomer clusters, formed at the same time, will at some point encounter each other and stick together (“cluster– cluster” assembly, Figure 1.8).
“Eden” “Witten-Sander” RLCCA RLMCA DLMCA DLCCA df = 3.00 df = 2.50 df = 2.09 df = 1.80 Reaction-Limited Diffusion-Limited Monomer–Cluster Cluster–Cluster Figure 1.8. Assemblies of identical spherical particles obtained by computer simulations using various irreversible growth mechanisms in solution (the particles move by Brownian motion).21 The Eden or reaction‐limited monomer–cluster assembly (RLMCA) is formed by monomers being added to a growing structure with a chance of sticking less than unity, yielding a dense assembly. If the monomers stick to the first branch of the structure they encounter a more open structure is formed (Witten–Sander or diffusion‐limited monomer–cluster assembly). If not just monomers, but also small clusters of monomers can stick to each other (cluster–cluster assembly) also in the reaction‐limited case (i.e. reaction‐limited cluster–cluster assembly) more open structures are formed. The quantity df
refers to the fractal dimension of the formed structure. The least dense assemblies are formed for diffusion‐limited cluster‐cluster assembly (DLCCA).
In other words, there is not just a single structure present in solution (as shown in Figure 1.8), but many monomers are in close proximity that eventually form a single structure (system‐wide percolation). In practice such highly percolated systems are described as gels, because the solid percolating phase (i.e. the assembled monomers) is retaining the continuous liquid phase by capillary forces. In Figure 1.9 two‐dimensional simulations are shown of diffusion‐limited cluster–cluster assembly at different initial concentrations of monomers. A high initial concentration leads to fast gelation and a dense fractal network. Lower concentrations yield a more open structure, which needs more time to form.
The types of structures shown in Figure 1.8 and Figure 1.9 are characteristic for their growth mechanism, but if we were to repeat the same simulation with the same settings we would not get the exact same structure. It would look similar, but the structures will have slight differences. To describe these apparently irregular structures quantitatively a different method is needed.
a b t = 0 t = 100 t = 16799 (gel) t = 0 t = 10 t = 394 (gel) time time time time
Figure 1.9. Two‐dimensional simulations of irreversible diffusion‐limited cluster–cluster assembly at two different concentrations starting from monomer building blocks. a) A dilute solution (number density equals 0.1) at simulations times 0, 100 and 16799 (gel). b) A concentrated solution (number density equals 0.3) at times 0, 10 and 394 (gel). For high concentrations the gel state (fully percolated network) is reached much sooner. Adjusted from reference 25.
Assume for the moment that a certain assembly is completely solid, without any interstitial space, and that its density ρ is equal to that of the monomers. Then, the mass of the total assembly m with a radius r will be:
m(4 / 3)r3
(1.2)
So, a similar assembly but double in size will weigh eight times more. It turns out that the scaling of mass for assemblies such as those in Figure 1.9 can be described by:
m(4 / 3)rdf (1.3)
where df or the fractal dimension is smaller than three (i.e. the normal spatial or Euclidean
dimension). These assemblies are referred to as fractals or self‐similar structures. It turns out that df can be used to quantify the different structures formed by the different growth
mechanisms (see values of df in Figure 1.8), when the assembly of the monomers is
irreversible. This theory is able to describe for example the self‐assembly of small gold nanoparticles as shown by Weitz and coworkers (Figure 1.10).26–27
Figure 1.10. Irreversible assembly of 7.5 nm gold nanoparticles induced by either an excess of pyridine, which displaces all charged ions from the surface instantaneously (DLCCA), or a smaller amount of pyridine giving rise to a slower assembly process (RLCCA). The cluster size and df was
measured using light scattering and characteristic microscopy images are shown next to the curves. Figure adapted from references 26‐27.
Now, assume that the monomers can also detach from the assembly with a probability pd (Figure 1.11), making the entire process reversible.
28
For the forward reaction we keep the two limits identical to those for the irreversible assembly; for pa = 1 the sticking
is diffusion limited and for pa << 1 it is reaction limited. If pa/pd is small, so the probability of
detaching is much larger than that of sticking; basically only monomers will be present in solution. Conversely, if this ratio is large all monomers will cluster together in one single percolating structure. The probabilities of sticking and detaching combined with the diffusion coefficient of the monomers leads to a life time of encounter (te), which is the
average time two particles move through the solution together. This is an important new parameter to describe this reversible assembly process.
+ pa pd
Figure 1.11. Reversible monomer assembly. Two monomers stick to each other upon contact with a probablility (pa) and detach again with a probability (pd). Taking into account the diffusion coefficient
of the monomer particles,the probabilities give rise to series of correlated collisions with a life time te.
Interestingly, for very dilute systems (i.e. the flocculation regime) there is no difference in the final stable structures for different pa, which means that there is no distinction between
reversible diffusion‐limited or reaction‐limited assembly. It does, however, matter for the time it takes to reach this final structure. The fractal dimension of the structures in this dilute regime is 2.0, a value in between that of irreversible DLCCA (1.80) and RLCCA (2.09). In more concentrated solutions the growing assemblies soon start to interact with each other. If te crosses a critical value, a systemwide percolating network is formed. This structure is
constantly forming and reforming and is called a transient gel and has a df of 2.7. It is clear by
now that similar fractal structures can be obtained by either reversible or irreversible growth mechanisms. The latter mechanism, however, will lead to a constantly increasing diffusion
coefficient (D) of the monomers, while for the former reversible mechanism D will reach a stable value at some point in time. It is therefore not only important to study the overall structure of the formed assembly (i.e. a fractal network), but also the behavior of the individual monomers (i.e. their dynamics).
If we allow many more than two interactions on average per monomer, the systems can densify and eventually phase separate, which leads to structures that are much coarser compared to the fractal structures. Fractal assemblies have been predicted as precursors for spinodal decomposition29–30 and have been observed in protein aggregation31 (Figure 1.12b), but solid experimental evidence and a full understanding have not been obtained yet. a b c time time Figure 1.12. Different stages in the assembly process of silicatein proteins. a) After 15 minutes globular assemblies are formed consisting of only few proteins. b) Fractal structures are observed after 30 minutes with a df of ~1.7. c) After 1 hour filaments are formed presumably by secondary short range
attractions. Adjusted from reference 31.
So far we have seen that the assembly of building blocks depends on their size and shape and on (the direction, strength and scaling of) the interactions between them. Moreover, the rate of assembly and the pathway taken towards the final assembly are very important. In the next section we describe the timescale needed to analyze the assembly of building blocks of various sizes and which techniques are available to this end.
1.3 Timescale of interactions versus timescale of analysis
In the analysis of nanometer‐sized assemblies, taking an image often takes a long time compared to the velocity of movement. The motion of a nanometer‐sized particle through a solvent (i.e. diffusion) appears slow on the macroscopic scale, but when zoomed in to the scale of the moving object or molecule, the movements are violent and chaotic (“Brownian storm”). For example, a molecule with a diameter of 10 nm diffuses its own radius in 1 μs, which is a speed of only 0.036 km h–1
. If an average car would move its own diameter in the same time its speed would be ~1.5 x 107
km h–1
, which gives an indication of how violent molecular movements would appear if looked at on their own scale. For this reason many visualization techniques rely on immobilization of the components in the system. When the system is “frozen” there is sufficient time for analysis. In this way, we can visualize a molecular assembly with high resolution but the kinetics are lost in the process. Moreover,
these static analysis methods are often perturbing the system they aim to analyze or are performed ex situ (i.e. the system is taken out of its “natural” environment for analysis, which likely changes its behavior). Examples are atomic force microscopy (AFM)32–33
, scanning tunneling microscopy (STM)34
, transmission electron microscopy (TEM), scanning electron microscope (SEM) or X‐ray crystallography35
(Figure 1.13).
On the other hand, there are analysis techniques which aim to capture the kinetics of assembly. Relaxation techniques, for example, perturb the system from its equilibrium state and monitor the rate at which the system recovers: temperature jump and ultrasonic relaxation, laser photolysis or stopped‐flow. Sensitive assemblies, however, can permanently be disrupted by such perturbations, limiting the applicability of these techniques. A second method is to label just a few molecules and follow their movements at a very short timescale (e.g. fluorescence correlation spectroscopy) or by correlating their collective movements by the by for example light scattering36–38
. It is therefore possible to get information about the kinetics without any perturbations. Lastly, bulk measurements—averaging the movement and interactions of many molecules—can provide indirect information about the system’s kinetics e.g. nuclear magnetic resonance (NMR)39–40 or surface plasmon resonance (SPR)41–43 . Figure 1.13. An overview of some analysis techniques probing either structure or dynamics (some can do both at the same time). The graph shows the needed timescale of analysis (τ) for a particle with a diameter (d), when considering interactions occurring between two or more molecules.
Self‐assembling systems with building blocks in the sub 10 nm range pose an additional problem. In Figure 1.13 it can be seen that in this region there is no technique that can provide both structure and dynamic simultaneously. Therefore, it is crucial to use a combination of static and dynamic techniques, as will be shown in this thesis.
1.4 Supramolecular Chemistry: non‐covalent assembly of building blocks
Using non‐covalent interactions, such as those described in the previous sections, to obtain ordered structures is common in the field of supramolecular chemistry. For binary systems, the small building block is referred to as the guest and the larger as the host; together with their interactions being referred to as guest–host chemistry (Figure 1.14). O O O O O O K H H H H Ag Figure 1.14: Guest–host complexes of increasing size and complexity. From left to right: A silver ion has a weak interaction with the double bond in ethane, a potassium ion complexed inside a crown ether and an alkyl ammonium guest inside the cavity of a self‐assembled spherical host complex consisting of six resorcinarenes.
Figure 1.15. Some examples of natural self‐assembled structures and of synthetic analogues that are resembling them. a) Collagen fibers are formed from fibrils, which are in turn formed from α‐chain triple helices.44
b) The globular human serum albumin protein.45
c) The DNA double helix.46 d–f) Synthetic fibrous structures that resemble the collagen fibers (by Aida47
, Stupp48
and Würthner49 , respectively) g) Three‐dimensional structures obtained from pieces of synthetic DNA that were programmed to self‐assemble into a specific structure resembling a globular protein.50
h) A helical foldamer resembling DNA by Lehn and coworkers.51
The start of this field can be traced back to the end of the nineteenth century, with the discovery of cyclodextrin inclusion complexes, the formulation of the concepts of
coordination chemistry and Fischer’s proposal that enzymes and their substrates interact similar to the way a key fits in a lock.52–57
The underlying principles of this postulation are molecular recognition and supramolecular function.58
From that point on, the realization sprung onto chemists that the combination of multiple weak non‐covalent interactions could yield molecular assemblies akin to biological structures. Early examples included the well‐ know cryptands59 , spherands60 , clathrates61–63 and crown ethers64 . The term supramolecular chemistry was introduced by Jean‐Marie Lehn in 1969 in his study of cryptands. Less than two decades later Lehn65 , Pedersen66 and Cram67 were awarded the Nobel Prize for their pioneering work in the field of molecular recognition. A great number of supramolecular complexes and structures have been discovered during the past decades (Figure 1.15), however, predicting their structure is often a great challenge due to the sheer numbers of possible interactions and often the many polymorphs that can coexist in some systems. In the next section we describe how a stepwise approach can be used to guide the self‐assembly process.
1.5 Better control over self‐assembly: stepwise self‐assembly
The way most self‐assembled structures are made nowadays is by adding the various building blocks together in a solvent to get the structure in one step (One‐pot approach in Figure 1.16). This approach works well for equilibrium systems where the building blocks can dissociate and recombine until the thermodynamically stable structure is obtained. Stepwise approach (Intermediate tecton) One-pot approach (polymorphs) Figure 1.16. Schematic representation of the proposed stepwise assembly approach. The common one‐ pot approach is to mix the building blocks together in a solvent, which often leads to many different polymorphs. A stepwise approach to first obtain a well‐defined self‐assembled intermediate, which is stabilized before proceeding to the next assembly step, could lead to hierarchically more complex and better defined structures in a controlled manner. More complicated structures like those encountered in Nature, however, are not likely to arise spontaneously from the simultaneous addition of all components to a solvent, since the many different components will be able to interact in a multitude of ways, leading to
polymorphs and not likely to a unique structure. In other words, the thermodynamically determined product is not always the desired one.
One approach to get more control over the obtained structure is to use a stepwise approach to kinetically trap only one of the polymorphs (Stepwise approach in Figure 1.16). Nature developed very elegant strategies to obtain kinetically stable structures. Chaperones for example are used to obtain the correctly folded bioactive secondary and tertiary protein structures starting from a random coil polypeptide (Figure 1.17). These kind of assisting structures are themselves proteins and can lower the free energy once bound to the unfolded peptide chain. Chaperones have also been found in protein multimerization, where they assist the assembly of multiple domains into larger superstructures. This chaperone strategy is very elegant, but requires a coordinated collaboration of many biological processes and is therefore not easy to mimic. TS-Chp TS N-Chp N Folding Δ G (kcal mol -1) U I I-Chp Figure 1.17. A free energy diagram of chaperone assisted protein folding. Folding from the unfolded (U) to the native state (N) via the intermediate (I) and transition state (TS) is not possible because the free energy of N is higher than that of U. Using the assisted pathway (lower one, where the states have the “Chp” addition), the unfolded state can go to the native protein structure after cleaving off the chaperone (dashed arrow). A cartoon‐like representation of the native state (with and without chaperone) is shown on the right.68
Kinetically stable and metastable structures have been reported for supramolecular systems based on metal‐coordination69–72
, hydrogen‐bonding73–76
, stacking77
or guest–host78–79 interactions. Hasenknopf et al. showed that a linear aliphatic ligand containing three bipyridine moieties self‐assembled mainly into a triple helix when mixed with FeCl2 in solution. In a second heating step, however, the helix could be converted into a pentagonal structure in time (Figure 1.18a). In a different system, researchers from the Reinhoudt laboratories showed that the structure of kinetically stable calix[4]arene rosettes can be templated using chiral molecules during the assembly process (Figure 1.18b).74,76,80–81
In a second step the chiral template could be removed yielding just one supramolecular enantiomer.
heat
Cl–
a b
Figure 1.18. Stepwise assembly in supramolecular systems. a) A triple helical assembly consisting of three trivalent bipyridine ligands and three Fe2+
ions transforms into a pentagonal structure upon heating.70
b) An enantiomerically pure calix[4]arene double rosette assembly, which is kinetically stable enough to preserve its chirality after removal of the chiral template.76
The latter two synthetic examples show that a stepwise approach can be used to preferentially obtain one of the different polymorphs compared to the mixture of polymorphs obtained by a one‐step methodology.
Organic solvent (o)
(neat state) (w/o/w emulsion) (solvent mix) w o w Vesicle / polymersome Evaporation (– o) – o ● Dialysis (− o) ● Evaporation (− o) ● Dilution (+ w)
● + w & Sonication / Stirring ● + w & Filtration
● + w & Electric field
emulsify w w + H2O (w) Figure 1.19. Stepwise strategies to obtain preferentially unilamellar surfactant vesicles. The surfactant is first dissolved in a good solvent, usually a volatile organic solvent. Next, three strategies are mainly used: the neat surfactant is mechanically processed (upper pathway), a double emulsion is used as a template (middle pathway) or a miscible mixture of water and the good organic solvent is used to form vesicles (or micelles), after which the organic solvent is removed (bottom pathway).
Such stepwise approaches are also commonly used to create surfactant vesicles, which are of great importance for drug‐dosage, cosmetic formulations and for use in the food industry.82
Formation of vesicles from surfactants in one step has been observed from mixtures of zwitterionic and anionic surfactants83
, from polyelectrolytes84
and from lipids85–86 . Often, however, multilamellar vesicles are formed with a broad size distribution, while for
many applications unilamellar monodisperse vesicles are necessary.87
To obtain predominantly the unilamellar architecture three stepwise strategies, depicted in Figure 1.19, have been developed:
i) A thin film or powder of the surfactant is added to an aqueous solution and mechanically treated by sonication88
, stirring89
, filtration90
under pressure or by alternating electric fields91
(upper pathway).
ii) A double water‐in‐oil‐in‐water (w/o/w) emulsion is made using sonication92
or more recently using microfluidic techniques93–94
. The latter gives rise to very monodisperse vesicles that can be loaded with very high efficiency (i.e. in the inner water phase). The organic solvent can be removed by evaporation, to yield the surfactant double layer. iii) The surfactant is dissolved in a good (organic) solvent, which is miscible with water. Stepwise addition of water (i.e. the bad solvent) to this solution induces the assembly of the hydrophobic part of the surfactant into vesicles and micelles.95–96
In the next step the organic solvent is removed using dialysis or evaporation.
The examples in this section show the viability of adopting a stepwise pathway to obtain preferentially one of the many polymorphs. In this thesis we show that a stepwise approach can also be used to obtain structures that cannot be obtained directly. The resulting self‐assembled tectons can in turn interact with each other giving rise to intriguing assembly behavior, which we outline in the next section.
1.6 Aim and outline of this thesis
The many aspects of self‐assembly and self‐organization of building blocks described in this chapter, such as the size of the building block, the directionality and strength of interactions between them, the rate of assembly and the pathway of steps taken towards the final product, have to be tuned to perfection in order to arrive at the desired structure. Here we use a stepwise approach to obtain new building blocks that are themselves self‐ assembled structures. These intermediate tectons consist of well‐defined molecules, held together by specific non‐covalent interactions. The key aspect of this approach is to kinetically trap the structure of the intermediate supramolecular tecton, which is done by preassembly of the components in the neat phase.
The aim of this research is to study the interactions between nanometer sized building blocks that are themselves supramolecular self‐assembled structures. Analysis techniques not commonly used in the field of supramolecular chemistry are explored to quantify these interactions.
Two kinds of self‐assembled building blocks are used: one consisting of a highly branched globular molecule (a dendrimer) and small guest molecules, and one based on a supramolecular polymer that self‐assembles into fibers. Chapter 2, 3 and 4 describe the steps needed to obtain the former building block capable of forming assemblies with a higher hierarchy (Figure 1.20). Chapter 6 and 7, describe the latter building block.
Chapter 2 deals with the interactions of monovalent and multivalent guest molecules capable of interacting specifically with a dendrimer host. Guest–guest interactions play an important role in determining the true equilibrium binding constant. Moreover, the binding strength can be increased by using multivalent guest molecules.
Once a complex of the dendrimer and multiple monovalent guest molecules is made in chloroform it is transferred to the neat state by evaporating the solvent. In Chapter 3 it is shown that the guest–host complex is still intact in the neat state. When the remaining thin film is redissolved in water the guest–host complex is still intact, which is not possible by simply adding the individual components (i.e. the host and multiple guest molecules) together in water (bottom pathway in Figure 1.20). These kinetically stable guest–host complexes undergo a remarkable self‐assembly process upon dilution, which is described in detail in Chapter 4. In Chapter 5, these dendrimer based guest–host complexes are equipped with bioactive moieties by using a guest molecule that has an arylpiperazine moiety that can interact both with a neural receptor as well as with the dendrimer host.
In Chapter 6, a stepwise non‐covalent approach is used to obtain supramolecular hydrogel materials. A hydrophilic polymer is functionalized with the quadruple hydrogen‐ bonding ureidopyrimidinone (UPy) unit and forms large fibrous assemblies in the bulk. Interestingly, these structures can be transferred to aqueous solution and at high concentration form stable hydrogels, which undergo a structural evolution in time.
In Chapter 7, the binding strength of one such UPy moiety in the large supramolecular assemblies is quantified using a microfluidic setup and fluorescence correlation spectroscopy. By working with micrometer‐sized liquid flows, new insights into supramolecular guest–host interactions are obtained, which are responsible for the macroscopic properties of the hydrogel materials.
The epilogue provides a broader perspective of the different stepwise non‐covalent synthetic methods described in this thesis and how these concepts can be used to obtain new materials.
Figure 1.20. The stepwise non‐covalent synthetic approach to obtain stable guest–host complexes in aqueous solution. First the hydrophobic dendrimer host and hydrophilic guest molecules are dissolved in chloroform. The resulting guest–host complex is transferred to water via the neat phase. The guest–host complex cannot be obtained by directly mixing the host and guest in water (bottom pathway). Dilution of these guest–host complexes in water leads to hierarchically more complicated assemblies. The fact that dilution leads to assembly is in contradiction with most other self‐assembling systems.
Figure 1.21. The stepwise non‐covalent approach taken to obtain supramolecular hydrogels. A hydrophilic polymer is equipped with self‐assembling moieties, which form fibrous assemblies in the bulk polymer material. These fibers can be transferred to aqueous solution and at high concentrations form hydrogels that strengthen in time.
1.7 References 1 Whitesides, G. M. & Grzybowski, B. Science 295, 2418‐2421 (2002). 2 Frenkel, D. Physica a‐Statistical Mechanics and Its Applications 313, 1‐31, Pii S0378‐4371(02)01032‐4 (2002). 3 Grzybowski, B. A. Soft Matter 5, 1109‐1109, DOI 10.1039/B902046m (2009). 4 Overbeek, T. Colloid Surface B 14, Vi‐Vii (1999). 5 Akashi, T. et al. Appl Phys Lett 81, 1922‐1924, DOI 10.1063/1.1505115 (2002). 6 Friedrich, H. et al. Nano Lett 9, 2719‐2724, DOI 10.1021/Nl901212m (2009). 7 Velikov, K. P., Christova, C. G., Dullens, R. P. A. & van Blaaderen, A. Science 296, 106‐109 (2002). 8 Bianchi, E., Largo, J., Tartaglia, P., Zaccarelli, E. & Sciortino, F. Phys Rev Lett 97, 16830, DOI 10.1103/Physrevlett.97.168301 (2006). 9 Doye, J. P. K. et al. Phys Chem Chem Phys 9, 2197‐2205, DOI 10.1039/B614955c (2007). 10 Huisman, B. A. H., Bolhuis, P. G. & Fasolino, A. Phys Rev Lett 100, 188301 DOI 10.1103/Physrevlett.100.188301 (2008). 11 Kern, N. & Frenkel, D. J Chem Phys 118, 9882‐9889, DOI 10.1063/1.1569473 (2003). 12 Zhang, Z. L. & Glotzer, S. C. Nano Lett 4, 1407‐1413, DOI 10.1021/Nl0493500 (2004). 13 Sijbesma, R. P. et al. Science 278, 1601‐1604 (1997). 14 Marsh, A., Silvestri, M. & Lehn, J. M. Chem Commun, 1527‐1528 (1996). 15 Mucic, R. C., Storhoff, J. J., Mirkin, C. A. & Letsinger, R. L. J Am Chem Soc 120, 12674‐12675 (1998). 16 Blum, A. S. et al. Nano Lett 4, 867‐870, DOI 10.1021/Nl0497474 (2004). 17 Zheng, R. H., Liu, G. J. & Yan, X. H. J Am Chem Soc 127, 15358‐15359, DOI 10.1021/Ja054937h (2005). 18 Salant, A., Amitay‐Sadovsky, E. & Banin, U. J Am Chem Soc 128, 10006‐10007, DOI 10.1021/Ja063192s (2006). 19 Manoharan, V. N., Elsesser, M. T. & Pine, D. J. Science 301, 483‐487 (2003). 20 Nie, Z. H., Li, W., Seo, M., Xu, S. Q. & Kumacheva, E. J Am Chem Soc 128, 9408‐9412, DOI 10.1021/Ja060882n (2006). 21 Hiemenz, P. C. & Rajagopalan, R. Principles of colloid and surface chemistry. (Marcel Dekker Inc. US, 1997). 22 Grzybowski, B. A., Wilmer, C. E., Kim, J., Browne, K. P. & Bishop, K. J. M. Soft Matter 5, 1110‐1128, DOI 10.1039/B819321p (2009). 23 Grzybowski, B. A., Stone, H. A. & Whitesides, G. M. Nature 405, 1033‐1036 (2000). 24 Grzybowski, B. A. & Whitesides, G. M. Science 296, 718‐721 (2002). 25 Haw, M. D., Sievwright, M., Poon, W. C. K. & Pusey, P. N. Physica A 217, 231‐260 (1995). 26 Weitz, D. A., Huang, J. S., Lin, M. Y. & Sung, J. Phys Rev Lett 54, 1416‐1419 (1985). 27 Weitz, D. A., Lin, M. Y., Lindsay, H. M. & Huang, J. S. Phys Rev Lett 58, 1052‐1052 (1987). 28 Babu, S., Rottereau, M., Nicolai, T., Gimel, J. C. & Durand, D. Eur Phys J E 19, 203‐211, DOI 10.1140/epje/e2006‐00022‐7 (2006). 29 Klein, W. Phys Rev Lett 65, 1462‐1465 (1990). 30 Kopelman, R. Science 241, 1620‐1626 (1988). 31 Murr, M. M. & Morse, D. E. P Natl Acad Sci USA 102, 11657‐11662, DOI 10.1073/pnas.0503968102 (2005). 32 Frommer, J. Angewandte Chemie‐International Edition in English 31, 1298‐1328 (1992). 33 Giessibl, F. J. Reviews of Modern Physics 75, 949‐983 (2003). 34 Hansma, P. K. & Tersoff, J. J Appl Phys 61, R1‐R23 (1987). 35 Putnam, C. D., Hammel, M., Hura, G. L. & Tainer, J. A. Q Rev Biophys 40, 191‐285, 10.1017/s0033583507004635 (2007). 36 Berry, G. C. in Polymer Analysis and Characterization Vol. 114 Advances in Polymer Science 233‐290 (1994). 37 Cao, A. Anal Lett 36, 3185‐3225, 10.1081/al‐120026567 (2003). 38 Plum, M. A., Steffen, W., Fytas, G., Knoll, W. & Menges, B. Opt Express 17, 10364‐10371 (2009). 39 Pastor, A. & Martinez‐Viviente, E. Coordination Chemistry Reviews 252, 2314‐2345, DOI 10.1016/j.ccr.2008.01.025 (2008). 40 Wuthrich, K. Acta Crystallogr D 51, 249‐270 (1995). 41 Abdulhalim, I., Zourob, M. & Lakhtakia, A. Electromagnetics 28, DOI 10.1080/02726340801921650 (2008). 42 Green, R. J. et al. Biomaterials 21, 1823‐1835 (2000). 43 Homola, J., Yee, S. S. & Gauglitz, G. Sensor Actuat B‐Chem 54, 3‐15 (1999). 44 Campbell, N. A. Biology. (St Laurent, 1995). 45 Lejon, S., Cramer, J. F. & Nordberg, P. Acta Crystallogr F 64, 64‐69, DOI 10.1107/S174430910706770x (2008). 46 US‐National‐library‐of‐medicine. DNA structure. 47 Hill, J. P. et al. Science 304, 1481‐1483 (2004).
48 Hartgerink, J. D., Beniash, E. & Stupp, S. I. Science 294, 1684‐1688 (2001). 49 Wurthner, F., Yao, S. & Beginn, U. Angew Chem Int Edit 42, 3247‐3250, DOI 10.1002/anie.200351414 (2003). 50 He, Y. et al. Nature 452, 198‐U141, DOI 10.1038/Nature06597 (2008). 51 Schmitt, J. L., Stadler, A. M., Kyritsakas, N. & Lehn, J. M. Helv Chim Acta 86, 1598‐1624 (2003). 52 Ehrlich, P. Studies on Immunity. (Wiley, 1906). 53 Fisher, E. Ber. Dtsch. Chem. Ges. 27, 2985 (1894). 54 Koshland, D. E. P Natl Acad Sci USA 44, 98‐104 (1958). 55 Steed, J. W. & Atwood, J. L. Supramolecular Chemistry. (Wiley, 2000). 56 Villiers, A. C. R. Hebd. Seances Acad. Sci. 112, 536 (1891). 57 Werner, A. Zeitschrift Fur Anorganische Und Allgemeine Chemie 3, 267 (1893). 58 Desiraju, G. R. Nature 412, 397‐400 (2001). 59 Lehn, J. M. Struct. Bonding (Berlin) 16, 1 (1973). 60 Cram, D. J., Kaneda, T., Lein, G. M. & Helgeson, R. C. J Chem Soc Chem Comm, 948‐950 (1979). 61 Muller, A., Reuter, H. & Dillinger, S. Angewandte Chemie‐International Edition in English 34, 2328‐2361 (1995). 62 Pope, M. T. & Muller, A. Angewandte Chemie‐International Edition in English 30, 34‐48 (1991). 63 Macnicol, D. D., McKendrick, J. J. & Wilson, D. R. Chem Soc Rev 7, 65‐87 (1978). 64 Patai, S. & Rappoport, Z. Crown ethers and analogues. (Wiley, 1989). 65 Dietrich, B., Lehn, J. M. & Sauvage, J. P. Tetrahedron Lett, 2889‐2892 (1969). 66 Pedersen, C. J. J Am Chem Soc 89, 7017‐7036 (1967). 67 Cram, D. J. & Cram, J. M. Science 183, 803‐809 (1974). 68 Cabrita, L. D. & Bottomley, S. P. Eur Biophys J Biophy 33, 83‐88, DOI 10.1007/s00249‐003‐0356‐1 (2004). 69 Cardenas, D. J. & Sauvage, J. P. Inorg Chem 36, 2777‐2783 (1997). 70 Hasenknopf, B., Lehn, J. M., Boumediene, N., Leize, E. & Van Dorsselaer, A. Angew Chem Int Edit 37, 3265‐ 3268 (1998). 71 Ibukuro, F., Kusukawa, T. & Fujita, M. J Am Chem Soc 120, 8561‐8562 (1998). 72 Hori, A., Yamashita, K. & Fujita, M. Angew Chem Int Edit 43, 5016‐5019, DOI 10.1002/anie.200460671 (2004). 73 Davis, J. T. et al. Org Lett 6, 4265‐4268, DOI 10.1021/Ol0483089 (2004). 74 Ishi‐i, T. et al. Angew Chem Int Edit 42, 2300‐2305, DOI 10.1002/anie.200350956 (2003). 75 Mathias, J. P., Simanek, E. E., Seto, C. T. & Whitesides, G. M. Angewandte Chemie‐International Edition in English 32, 1766‐1769 (1993). 76 Prins, L. J., De Jong, F., Timmerman, P. & Reinhoudt, D. N. Nature 408, 181‐184 (2000). 77 Lohr, A., Lysetska, M. & Wurthner, F. Angew Chem Int Edit 44, 5071‐5074, DOI 10.1002/aine.200500640 (2005). 78 Masson, E., Lu, X. Y., Ling, X. X. & Patchell, D. L. Org Lett 11, 3798‐3801, DOI 10.1021/Ol901237p (2009). 79 George, S. J. et al. Angew Chem Int Edit 46, 8206‐8211, DOI 10.1002/anie.200702730 (2007). 80 Paraschiv, V. et al. Adv Mater 14, 722‐726 (2002). 81 Reinhoudt, D. N. & Crego‐Calama, M. Science 295, 2403‐2407 (2002). 82 Segota, S. & Tezak, D. Adv Colloid Interfac 121, 51‐75, DOI 10.1016/j.cis.2006.01.002 (2006). 83 Limin, Z., Ganzuo, L. & Zhiwei, S. Colloid Surface A 190, 275‐283 (2001). 84 Cha, J. N. et al. J Am Chem Soc 125, 8285‐8289, DOI 10.1021/Ja0279601 (2003). 85 Afri, M. et al. Chem Phys Lipids 131, 107‐121, DOI 10.1016/j.chemphyslip.2004.04.007 (2004). 86 Weisman, S., Hirsch‐Lerner, D., Barenholz, Y. & Talmon, Y. Biophys J 87, 609‐614, DOI 10.1529/biophysj.103.033480 (2004). 87 Fendler, J. H. Chem Rev 87, 877‐899 (1987). 88 Edwards, K., Almgren, M., Bellare, J. & Brown, W. Langmuir 5, 473‐478 (1989). 89 Ahmed, F. & Discher, D. E. J Control Release 96, 37‐53, DOI 10.1016/j.jconrel.2003.12.021 (2004). 90 Peschka, R., Purmann, T. & Schubert, R. Int J Pharm 162, 177‐183 (1998). 91 Discher, B. M. et al. Science 284, 1143‐1146 (1999). 92 Tobio, M., Gref, R., Sanchez, A., Langer, R. & Alonso, M. J. Pharmaceutical Research 15, 270‐275 (1998). 93 Shum, H. C., Lee, D., Yoon, I., Kodger, T. & Weitz, D. A. Langmuir 24, 7651‐7653, DOI 10.1021/La801833a (2008). 94 Shum, H. C., Kim, J. W. & Weitz, D. A. J Am Chem Soc 130, 9543‐9549, DOI 10.1021/Ja802157y (2008). 95 Shen, H. W. & Eisenberg, A. J Phys Chem B 103, 9473‐9487 (1999). 96 Discher, D. E. & Eisenberg, A. Science 297, 967‐973 (2002).
