Subscriber access provided by UNIV OF BARCELONA
Invited Feature Article
Dynamical Landscape in Self-Assembled Surfactant Aggregates Veerendra Kumar Sharma, Subhankur Mitra, and Ramaprosad Mukhopadhyay Langmuir, Just Accepted Manuscript • DOI: 10.1021/acs.langmuir.8b03596 • Publication Date (Web): 07 Feb 2019 Downloaded from http://pubs.acs.org on February 7, 2019
Just Accepted “Just Accepted” manuscripts have been peer-reviewed and accepted for publication. They are posted online prior to technical editing, formatting for publication and author proofing. The American Chemical Society provides “Just Accepted” as a service to the research community to expedite the dissemination of scientific material as soon as possible after acceptance. “Just Accepted” manuscripts appear in full in PDF format accompanied by an HTML abstract. “Just Accepted” manuscripts have been fully peer reviewed, but should not be considered the official version of record. They are citable by the Digital Object Identifier (DOI®). “Just Accepted” is an optional service offered to authors. Therefore, the “Just Accepted” Web site may not include all articles that will be published in the journal. After a manuscript is technically edited and formatted, it will be removed from the “Just Accepted” Web site and published as an ASAP article. Note that technical editing may introduce minor changes to the manuscript text and/or graphics which could affect content, and all legal disclaimers and ethical guidelines that apply to the journal pertain. ACS cannot be held responsible for errors or consequences arising from the use of information contained in these “Just Accepted” manuscripts.
is published by the American Chemical Society. 1155 Sixteenth Street N.W., Washington, DC 20036 Published by American Chemical Society. Copyright © American Chemical Society. However, no copyright claim is made to original U.S. Government works, or works produced by employees of any Commonwealth realm Crown government in the course of their duties.
Page 1 of 56 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60
Langmuir
Dynamical Landscape in Self-Assembled Surfactant Aggregates Veerendra Kumar Sharma1*, Subhankur Mitra1,2 and Ramaprosad Mukhopadhyay1,2* 1Solid State Physics Division, Bhabha Atomic Research Centre, Mumbai 400085, India. 2Homi Bhabha National Institute, Anushaktinagar, Mumbai 400094, India
Abstract A process in which a disordered system of pre-existing molecules generates an organized structure through specific, local interactions among the molecules themselves is termed as molecular self-assembly. Micelles, microemulsions, vesicles are examples of such selfassembled systems where amphiphilic molecules are involved. As the functional properties of these systems (such as wetting and emulsification, release of solubilized drugs, etc.) are dictated by the dynamical behaviour of the surfactants at molecular level, it is of immense interest to investigate these system for the same. Dynamics in soft matter systems is quite complex, involving different time and length scales. We used combination of neutron scattering and molecular dynamics simulation studies in probing the dynamical landscape in various self-assembled surfactant aggregates. Neutron scattering experiments were carried out using several spectrometers covering a wide dynamic range to probe motions in different time scales. Interaction between the surfactants can be varied by changing the molecular architecture, concentration of counterion, temperature, etc. It is important to study the effect of these parameters on the dynamics of surfactants in these aggregates. We have carried out experiments on various ionic (anionic as well as cationic) micelles with varied counterion concentrations, vesicles, lipid bilayer to unravel the complex dynamical features present in these systems. In this feature article, we will discuss some important results of our recent work on dynamics in these self-assembled surfactant aggregates.
*Corresponding Authors:
[email protected] Emails:
[email protected]/
[email protected] 1 ACS Paragon Plus Environment
&
Langmuir 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60
Page 2 of 56
INTRODUCTION Surface active agents, popularly known as ‘Surfactants’ are among the class of compounds that have been studied quite extensively over the last century, not just with a motive to rationalise their interesting properties but also with a prospect of widening the scope of their applications. Surfactants are being used in a wide range of applications, for example, detergent, cosmetic, pharmaceutical, food processing, material synthesis and so forth [1-4]. They are amphiphilic molecules typically made of a polar hydrophilic group, generally called the head, which is connected to a nonpolar hydrophobic moiety, the tail, as shown in Fig.1. Surfactants can be classified according to different criteria, including the charge of the head group
(in
aqueous
solution),
the
number
and
kinds
of
connection
of
polar
head(s)/hydrophobic tail(s), etc. (Fig.1). For example, based on the charge of the head group, surfactants are categorized as ionic (cationic or anionic), non-ionic, catanionic, and zwitterionic. Depending on the number of hydrophobic tail(s), surfactants are classified as single chained, double chained, etc. Due to the amphiphilic nature, surfactant molecules undergo self-association in water under specific conditions to form aggregates in which the hydrophilic groups are exposed at the surface while the hydrophobic tails remain inside the aggregate. This self-association is a cooperative phenomena and starts at a certain concentration, the so-called ‘critical micellization concentration’ (CMC). This process of self-association results in various kinds of nano-aggregates such as spherical micelles, wormlike micelles, vesicles, microemulsion, etc. The hydrophobic interaction is mainly responsible for the aggregation and the electrostatic and steric repulsion between head groups limit the size of the aggregates. These aggregates are in thermodynamic equilibrium but are dynamically active. They rearrange themselves in response to change in environmental conditions. The size and shape of aggregates depend on various parameters including molecular architecture, charge, concentration of the surfactant, temperature, ionic strength etc. By tailoring these parameters, discrete structures with specific size, shape and order can be created [1,3,5]. The shape of the aggregates can be quantitatively described [1] using surfactant packing parameter defined as, C pp v / a0lc , where v is the hydrocarbon chain volume, a0 is the effective head group area and lc is the chain length. Surfactants with small Cpp ( 1/3) prefer to form spherical aggregates while rod-like aggregates are formed with value between 1/3 and 1/2. Vesicles or lamellar like aggregates are found to form with Cpp value between 1/2 and 1, while reverse micelles or bicontinous microemulsions are formed with Cpp >1 [1]. In general single chain surfactants prefer to form micelles like structure 2 ACS Paragon Plus Environment
Page 3 of 56 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60
Langmuir
whereas double chain surfactants tend to form lamellar or vesicles like structure. Information about the size and shape of these aggregates can be obtained using small angle scattering technique [6, 7], and has been used widely. For example, it has been shown that addition of electrolyte in ionic micelles induces the transition from spherical to rod-like structures [8-10]. Although structure and macroscopic behaviour of these self- assembled aggregates have been studied quite well, the dynamical behaviour of these aggregates and their correlation with the microstructure has not been investigated in detail. A good knowledge of the dynamics of selfassembled surfactant aggregates is essential in understanding various properties including wetting and emulsification, the mechanism of solubilized drugs release, micellar breaking time, and rheology of surfactant solution [11].
Fig.1 Schematics of different (a) types of surfactant and (b) self-assembled structures of the surfactant molecules for different values of the critical packing parameter (CPP). Figure is modified from ref.12.
3 ACS Paragon Plus Environment
Langmuir 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60
Dynamical features in these self-assembled surfactant aggregates (micelles, vesicles, etc.) involve multiple relaxation processes over a wide spatial and temporal ranges [13-19]. Primarily, based on their spatial extent, dynamics can be classified into two categories – mobility of the entire aggregate and molecular motion within an aggregate. While the diffusion of the entire aggregate, bending of the surfactant membrane, are some of the examples of the first category, the later comprise the lateral, segmental and torsional motions of the surfactant. Dynamics of the surfactant aggregates can be probed using various experimental methods including dynamic light scattering (DLS) [20-21], nuclear magnetic resonance (NMR) [22-24], fluorescence correlation spectroscopy (FCS) [25,26], tracer diffusion [27] and quasielastic neutron scattering (QENS) [13, 28-49]. Despite the fact that various experimental methods have been employed to study the dynamics of these selfassembled aggregates, the majority of these are only capable of observing the motions on limited ranges in space and time. Hence, it is important to combine the information obtained from these techniques to consolidate the understanding of the underlying mechanisms of molecular motions in the surfactant aggregates. NMR technique measures molecular motions on the time scale from nanoseconds to picoseconds [14]. NMR relaxation data on the micelles have been successfully explained using "two-step model" considering two kinds of motions; a slower motion (in nanoseconds), corresponding to the tumbling of whole aggregates and/or lateral diffusion of the surfactant along the surface and a faster motion (in picoseconds) associated with the internal motion of alkyl chain within the aggregates [23-24]. A review by Macháň and Hof [25] discuss the results of the diffusion in the lipid membranes as studied using fluorescence spectroscopy technique. They have also described the influence of several factors such as the presence of membrane inhomogeneities, ionic strength, and protein insertion, on the dynamics of membrane. It may be noted that the fluorescence technique requires the surfactant aggregates to be labelled with a probe and therefore one needs to consider the problems of probe localization and perturbation within the surfactant aggregates. Scattering techniques (DLS, QENS, etc) have a significant advantage over these complementary experimental techniques (NMR, fluorescence spectroscopy, etc.) as it directly provides the spatial information about the dynamics in the form of wave-vector transfer, Q, dependence. DLS is a suitable method to study the diffusion of the whole aggregates on the micrometer length scale and time scales longer than sub-microseconds [20-21]. One can estimate hydrodynamic radius of the whole aggregates from the observed diffusion coefficient using Stokes-Einstein relation. On the 4 ACS Paragon Plus Environment
Page 4 of 56
Page 5 of 56 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60
Langmuir
other hand, QENS is suitable for observing the motions of surfactant aggregates at a molecular level on a time scale from picoseconds to nanoseconds [28-49]. It simultaneously probes the time scale as well as the length scale of the existing dynamical motion. We have successfully used QENS technique to study dynamics in various self-assembled surfactant aggregates such as micelles [39-45], microemulsions [30] and vesicles [46-49]. Molecular dynamics (MD) simulation is a computational technique that provides information about the system on the same spatial and temporal regimes as QENS [15,17,47,49-51]. Thus, there is a great advantage in combining results from these two methods; while QENS data can be used as a gauge for the force field of the MD simulation studies, the trajectories obtained from the simulation can be employed to interpret the data from experiments providing atomistic insights of the dynamical processes. Further, MD simulation does not suffer from the limitations of an experimental set up. There exist a large number of reports in the literature examining various aspects of dynamics in various surfactant aggregates. A literature review summarizing some of these aspects is presented in Table 1. Table-I An overview of the dynamics in different self-assembled surfactant aggregates, investigated features and techniques employed.a Type of Aggregates
Surfactant
Features
Method
Ref.
NMR
52
SDS
Tumbling of whole aggregates, lateral and internal motions of the surfactant Occurrence of chain folding
NMR and fluorescence life time measurements DLS and Rheology
53
MD simulation
54
DLS and QENS
40
QENS
43
QENS QENS
36 42
QENS
44-45
MD simulation
55
Micelles
CTAB TTAB SDS, SDBS
Effects of organic electrolytes on the dynamics of whole micelles Structural and dynamic properties of micelle, chain folding, Fluidity of micelles interior and comparison with pure liquid alkenes Diffusion of entire micelles, Lateral and segmental motion of the monomers Lateral and two distinct internal motions of the surfactant; segmental and torsional Monomer motion in aggregates Lateral and segmental motions of the monomers Effects of additional phenyl ring on the lateral and segmental motions of the monomers Packing of dodecyl chains in SDS and SDBS micelles and its correlation with the mobility of alkyl chain
5 ACS Paragon Plus Environment
8
Langmuir 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60
CnTAB (Alkyltrimethy lammonium bromide; n=10, 12, 14 & 16) DTAB (C12TAB) SDS, CnTAB
Ganglioside Block copolymer E92B18 Reverse Micelles
AOT
Bicontinous Microemulsio ns (BE)
SDS (water/SDS/1pentanol/dode cane) SDS+CTAB
DODAB
Vesicles
DMPC
DOPC DPPC Hydrated powders/Lipid bilayer/ Supported bilayers
DMPC
Page 6 of 56
Effects of chain length of the surfactant on the lateral and segmental motions
QENS
42
Effects of electrolytes on the motion of whole micelles, lateral and segmental motions of the surfactant Effects of chain length, forms of the head group on the lateral, segmental and torsional motion of the surfactant, Strongly fluctuating surface of micelles Segmental motion of surfactant Two distinct modes; slow mode corresponds to translational diffusion of the micelles and fast mode ascribed to internal “blob scattering” Monomer motion Effects of hydration on the internal dynamics of surfactant
DLS, QENS and MD simulation
15
MD simulation and QENS
17
QENS Neutron Spin Echo (NSE)
37 38
QENS QENS
36 31
Effects of membrane associated protein on the lateral and internal motions of surfactant
Small angle scattering, QENS
30
Multilamellar to unilamellar transition and effects of this transition on the lateral and internal motions of the surfactant
Elastic Fixed Window Scan (EFWS), Differential Scanning Calorimetry (DSC), QENS QENS
46
Phase behaviour of lipid bilayer, Effects of phase transition on the lateral and internal motions of the lipid Dynamical heterogeneity in the membrane Solvation dynamics and effects of an antituberculosis drug rifampicin Effects of gel to fluid phase transition on lateral and internal motions of the lipid Effects of antimicrobial peptides on the dynamical and phase behaviour of the membrane: role of cholesterol and physical state of the membrane Effects of aspirin on the lateral, internal and bending motions of the membrane Thickness fluctuation of the membrane Effects of pore forming peptides on the bending motion of membrane Effects of temperature on the lateral motion of lipid Mechanism of lateral diffusion at short and long length scale Partitioning of ethanol into lipid membranes and its effect on fluidity and permeability Collective flow like motion
6 ACS Paragon Plus Environment
47 MD and QENS
51
Fluorescence spectroscopy
56
EFWS, QENS
33
EFWS, QENS, SANS
29,32
EFWS, DSC, QENS, NSE NSE DLS, SANS, NSE
16
QENS
58
QENS
59
X-ray scattering and QENS
60
MD Simulation
61
18 57
Page 7 of 56 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60
Langmuir
DOPC, DMPC
Dynamical heterogeneity at nanoscale due to lipid-lipid and lipid-protein interactions
Super-resolution stimulated emission depletion -FCS
26
DPPC
lateral, rotational, and librational motion of the lipids In-plane and out of plane motion of lipids
QENS
62
QENS
63
DPPC
aAbbreviations:
Sodium Dodecyl Sulfate (SDS) n-Alkyltrimethylammonium bromide (CnTAB) Dodecyl trimethyl ammonium bromide (DTAB=C12TAB) Tetradecyl trimethyl ammonium bromide (TTAB= C14TAB) Cetyltrimethylammonium Bromide (CTAB= C16TAB) Sodium dodecyl benzene sulfonate (SDBS) Sodium bis (2 ethyl hexyl) sulfosuccinate (AOT) Dimyristoylphosphatidylcholine (DMPC) Dioctadecyldimethylammonium bromide (DODAB) 1,2-dioleoyl-sn-glycero-3-phosphocholin (DOPC) Dipalmitoylphosphatidylcholine (DPPC) E92B18; E=OCH2CH2 : oxyethylene, B=OCH2CH(C2H5): oxybutylene)
The dynamics of surfactant in micelles and vesicles have been studied over the last three decades using the QENS technique [28-49, 57-60, 62-63]. QENS studies were carried out to investigate the effects of hydration on the dynamics in sodium bis (2 ethylhexyl) sulfosuccinate (AOT) reverse micelles [31]. It was found that for the anhydrous sample, only global motion of AOT reverse micelles contributes to the QENS data. However, with increase in the hydration above a threshold, internal motion of the micelles starts to contribute along with the global motion. Tabony et al [36] had studied monomer dynamics in direct micelles of tetradecyl trimethyl ammonium bromide (TTAB) in D2O and reverse micelles of AOT in deuterated cyclohexane with varying content of D2O using QENS technique. It was shown that monomer motion in the aggregates gives rise to quasielastic broadening. For AOT reverse micelles, monomer dynamics was observed to be independent of the interfacial curvature. Dynamics of TTAB molecule in micelles was found to be slower than that of AOT. It was inferred that in the reverse micelles, monomers are diffusing in a shell and in direct micelle the monomers are diffusing around a sphere. Internal dynamics of ganglioside micellar solutions had been studied and described using localised translational diffusion (LTD) model [37]. Castelletto et al [38] have shown presence of two dynamical modes, fast and slow in block copolymer micelles. The slow mode is ascribed to translational 7 ACS Paragon Plus Environment
Langmuir 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60
diffusion of micelles whereas the fast mode corresponds to the internal motion of micelles. Pfeiffer et al. [62] had observed different motions of DPPC lipid in a supported membrane. Tabony et al [58] had studied the effects of temperature on the lateral motion of lipid in DPPC bilayer. Inspite of a large number of studies [14,58,59,64-66] reported on the dynamics of surfactants in their self-assembled aggregates, a comprehensive description of surfactant motion that extends from a few micrometers to nanometers is still lacking. In fact, the issue of lateral diffusion of the surfactants has been a matter of debate since a decade [59,65-66]. While, it is tenable to consider that the thermally activated lateral motion of lipids follow Fickian/Brownian diffusion, Unruh group [66] reported a ballistic flow-like motion of the lipids as found in their QENS study. However, Armstrong et al [59] had shown that the validity of ballistic flow-like motion of lipid was restricted to length scales lesser than the closest neighbours (~2.4 Å) in the membrane. Further, they also found that, beyond this length (2.4 Å), the lipids follow the surmised Fickian diffusion. More recently, studies by Wanderling et. al. [65] suggest that localised translation of lipids in a cylindrical volume is also a possible mechanism. In addition to discordant conclusions from the same experimental technique (like QENS in the above mentioned examples), the diffusion coefficients measured using different techniques (such as, NMR, QENS, fluorescence spectroscopy) differ by one or two orders of magnitudes [14,64]. This discrepancy could be explained based on the sensitivity of the dynamical measurements in different time and length scales and have been discussed in the literature [14,64]. Fluorescence spectroscopy or NMR techniques generally measure diffusion on the length scale of over a micrometer. However, QENS is more suitable to measure motions on a length scale from Angstroms to few nanometers. According to free volume theory of the membranes, the lipid molecules undergo rattling motion within a cage of neighbours until a free volume of the size of the lipid is created and the molecule can slip through it [64]. QENS technique measures mean displacement of the order of 1 nm which is the size of about two lipid diameters. However, fluorescence spectroscopy or NMR technique involves measurements of large number of such effective displacement steps [64] which results in different diffusion coefficient compared to that observed by QENS technique. In this feature article, we would provide an overview of the dynamical landscape observed in the self-assembled surfactant aggregates mainly using QENS and MD simulation techniques. We shall start with the simple micellar aggregates and provide details of the methodology developed to describe the observed dynamical behaviour. Thereafter, the effects of the surfactant architecture, addition of electrolytes on the dynamics of micelles, and their correlation with the microstructure, will be discussed. Mixing of oppositely charged 8 ACS Paragon Plus Environment
Page 8 of 56
Page 9 of 56 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60
Langmuir
surfactants in suitable condition can form liposome like structures which have numerous practical applications including delivery of drugs and genetic material in the human body. Multilameller or unilamellar vesicles are two types of liposome, which can be tuned from one structure to another by varying different physical parameters like, temperature or concentration of surfactant. Unilamellar vesicles being an alluring model structure for biomembranes, their dynamical features will be discussed in this article. Effect of multilamellar to unilamellar transition on the dynamics of vesicles was also studied in detail and will be discussed here as well. Double chain surfactants and/or lipids form bilayer in the aqueous media exhibiting rich phase behaviour. We shall also discuss the dynamics of the double chain surfactants in different phases across transition. This feature article is organized as follows. In the next section, a brief overview of experimental and computational methods that are employed to study dynamics in selfassembled surfactant aggregates is given. In the next section, the results on the dynamics in different surfactant based systems are discussed. This section is divided mainly in two subsections (i) micelles and (ii) vesicles, each of these is further divided into three subsections. In micelles, we have started with the study of dynamical landscape in anionic SDS and cationic DTAB micelles. After that we have discussed the effects of surfactant architecture and addition of electrolytes on it. In vesicles, we shall first discuss dynamics of catanionic vesicles which are formed by mixing oppositely charged single chain surfactants. Then we would discuss the study of dynamics of double chain surfactants/lipids which prefer to form bilayer structure. These lipid bilayers have rich phase behaviour depending on the various parameters including structure of the surfactant, temperature, and hydration. We begin with the discussion on the dynamics of a phosphatidylcholine lipid across the gel to fluid phase transition. It is followed by the effects of ionic liquids, a potential green solvent, on the dynamical and phase behaviour of the phospholipid membrane. Afterwards, we would discuss dynamics of a cationic lipid bilayer based on a synthetic lipid, across its different phases and show that anti-inflammatory drugs strongly interact with the lipid bilayer. The summary and a future outlook of the work are provided at the end.
EXPERIMENTAL AND COMPUTATIONAL METHODS Dynamics in self-assembled surfactant aggregates can be studied using various experimental and computational methods as mentioned in the introduction. This section presents a brief
9 ACS Paragon Plus Environment
Langmuir 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60
Page 10 of 56
overview of the experimental and computational techniques that were used by us to study the dynamics in these systems. Dynamic Light Scattering DLS is a convenient tool to study the dynamics of colloidal systems and has been used extensively to measure the diffusion of the whole surfactant aggregates in time scales longer than sub-microseconds [20-21]. In DLS, one measures the fluctuations in the scattered intensity, which depend on the mobility of the diffusing particle. The intensity autocorrelation function, g2 (τ) of a monodispersive system is related to translational diffusion coefficient, DDLS of the aggregates [20-21], g 2 ( ) 1 C exp( DDLS Q 2 )
2
(1)
where C is a spatial coherence factor governed by the instrument optics, is the delay time in autocorrelation function and Q is the magnitude of the scattering vector given as (4 nm / ) sin( / 2) . Here, nm and are the refractive index of the medium and the scattering
angle respectively. For light scattering, the accessible range of Q is between 10-5 and 10-3 Å-1, due to the large wavelength of light (4000 to 7000 Å). As a result, it does not provide information of the geometrical details of motions at the molecular level. Using Eq. (1), diffusion coefficient of the whole aggregate can be obtained. It may be noted that Eq. (1) is strictly valid for monodispersive system. However, for a polydispersive system, different methods (e.g. cumulant, CONTIN) are used to obtain average diffusion coefficient [20-21].
Quasielastic Neutron Scattering QENS is an excellent technique to study the stochastic dynamics in condensed matter at length scale of few angstroms to nanometers and timescale of few picoseconds to nanoseconds [28]. Stochastic dynamics of atoms/molecules lead to broadening of the elastic peak (∆E=0), known as quasi elastic (QE) broadening, which is inversely proportional to the time scale of the motion. In a QENS experiment, one analyzes the scattered intensity as a function of energy and momentum transfer. The measured quantity is the double differential scattering cross section,
2 , which gives the probability that a neutron with incident Ω
energy Ei, leaves the solid angle element d in the direction , after scattering from the
10 ACS Paragon Plus Environment
Page 11 of 56 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60
Langmuir
sample with an energy Ef undergoing exchange of energy between ħ=Ef-Ei and ħ(+d), can be written as [28] kf 2 coh Scoh (Q, ) inc Sinc (Q, ) Ω ki
(2)
where S(Q,) is the scattering law and is the scattering cross-section . The subscripts coh and inc denote the coherent and incoherent components. ki and kf are the initial and final wavevectors and Q= ki-kf is the wave vector transfer. Scattering from a hydrogenous system is primarily incoherent due to the fact that the
inc
of H-atom is much higher than the
scattering cross section of any other atom (σincH>> σany
atom).
Hence, in the case of such
systems, one can write Eq. (2) as,
kf 2 inc Sinc (Q, ) ki Ω
(3)
The incoherent scattering law, Sinc(Q,), is the space-time Fourier transform of the self part of van-Hove correlation function [28]. Hence, QENS is one of the best suited techniques to study (single particle motion) the self diffusion of hydrogen atoms in a given system. In this feature article, as the focus is mainly on hydrogenous systems, only incoherent scattering law Sinc(Q,) shall be considered, not mentioning this explicitly hereafter. Our system of interest is the surfactant aggregates; therefore deuterated water has been used to minimize the scattering contribution from the solvent. The contribution from the surfactant aggregates was obtained by subtracting the data of the solvent (deuterated water) which was measured under exactly the same conditions. The scattered intensity from the aggregates, Iagg(Q,), can be obtained from the following equation, I agg Q, I solution Q, I solvent (Q, )
(4)
where is the volume fraction of the solvent (D2O here) and can be calculated as
(Vsolution M surf ) / Vsolution ; where Vsolution, Msurf and v are the volume of the solution, mass and specific volume of the surfactant respectively. Subtracted QENS spectra should correspond to the surfactant aggregates only. Presence of quasielastic broadening over the instrument resolution indicates existence of stochastic motion of the surfactant. The instrument resolution is obtained by measuring the QENS spectra from vanadium. Different kinds of surfactant motion in these aggregates such as (i) lateral, (ii) localized segmental and (iii) fast torsional could contribute to the QENS spectra. Assuming that these motions are decoupled, the effective scattering law for the surfactant aggregates [17,43] can be given by, 11 ACS Paragon Plus Environment
Langmuir 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60
Page 12 of 56
S agg Q, Slat Q, S seg Q, Stor Q,
(5)
where Slat (Q,ω) , Sseg (Q,ω) and Stor (Q,ω) are the scattering laws correspond to the lateral, segmental and fast torsional motions respectively. Lateral motion of the surfactant is described by a continuous diffusion model. The corresponding scattering law is given by Slat Q, Llat lat ,
lat 2 1
2 lat
(6)
where lat is the half width at half maxima (HWHM) of the Lorentzian function representing lateral motion of the surfactant. The scattering law corresponding to the segmental and torsional motions of the surfactant, which being localised, would have a elastic and a quasielastic component. Hence, the scattering law for segmental and torsional motions can be written as [17,18,43] S seg Q, A(Q) ( ) (1 A(Q)) Lseg ( seg , )
(7)
Stor Q, B(Q) ( ) (1 B(Q)) Ltor (tor , )
(8)
where the first and second terms correspond to the elastic and quasielastic components respectively. The fraction of elastic scattering with respect to total scattering is called the Elastic Incoherent Structure Factor (EISF). Therefore, A(Q) and B(Q) in Eqs. (7) and (8) are the EISF for segmental and torsional motions, respectively. Variation of EISF with Q gives information about the geometry of the molecular motion. seg and tor are the HWHMs of the Lorentzian functions corresponding to the segmental and torsional motions, respectively. Classical Molecular Dynamics Simulation In classical molecular dynamics (MD) simulation, particle trajectories are obtained by integrating equations of motion of a system with a given set of interaction potentials. Aforementioned in the introduction section, MD simulation and neutron spectroscopy are complementary due to a nice overlap between length and time scales accessible by these techniques. Trajectories obtained from MD simulation can be analyzed in detail and provide information that might not be experimentally accessible. Moreover, for surfactant aggregates, dynamical processes are complex and exist in a wide range of time scale. In such cases, MD simulations are very useful for providing deep insight on the dynamical processes. The link 12 ACS Paragon Plus Environment
Page 13 of 56 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60
Langmuir
between the MD simulation and experimental data is established by a specific time correlation function, which is measured either directly or indirectly in form of a Fourier spectrum. Several relevant time correlation functions can be calculated from the simulation trajectories. Among them, incoherent intermediate scattering function (IISF), I(Q,t), which is the time Fourier transform of the incoherent scattering law, S(Q,), observed in QENS experiments, can be calculated from simulation trajectories using the following equation, I (Q, t ) exp iQ.(r (t t0 ) r (t0 ))
(9)
where r is the position vector of the hydrogen atom in the surfactants. The angular brackets show an ensemble average and the bar represent the average over possible orientations of the Q vectors. DYNAMICS IN SELF-ASSEMBLED SURFACTANT AGGREGATES
Dynamical landscape in various micelles, vesicles, lipid bilayer etc. has been investigated by us and some are discussed here. Micelles Dynamics in surfactant based systems are probed beginning with the simplest system of its kind – micelles. Various anionic and cationic micelles with different tails and head groups were used to understand the effects of chain length and ionic strength [39-45]. Micelles based on sodium doedecyl sulphate, (SDS; C12H25OSO3-Na+) and dodecyltrimethyl ammonium bromide (DTAB; (C12H25)N+(CH3)3Br-) are the examples of an anionic and a cationic micelles, chosen to discuss here. Both SDS and DTAB surfactants have the same dodecyl alkyl chain (C12H25) but head groups are very different. SDS has SO4- in the head group whereas DTAB has N+(CH3)3. The detailed dynamical landscapes in SDS and DTAB micelles were investigated by us using QENS and MD simulation studies [17, 40, 42]. QENS experiments were carried out with two different spectrometers having different energy resolutions and dynamic ranges, which enabled us to cover a wide range of time scale. As mentioned before, structure of the micelles is a consequence of a delicate balance between two opposing forces; (i) tail−tail attractive hydrophobic interaction and (ii) electrostatic/steric repulsion between head groups. Hence, these interactions can be tuned by varying the hydrophilic and hydrophobic part of the surfactant, addition of electrolytes, etc. Effects of the variation in the parameters like, molecular architecture, addition of electrolytes, temperatures etc. on the dynamics of micelles have been investigated and results are discussed below. 13 ACS Paragon Plus Environment
Langmuir 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60
Page 14 of 56
Anionic SDS and Cationic DTAB Micelles QENS data from the anionic 0.3 M and 0.6 M SDS micelles measured using IRIS spectrometer [40] (E=17eV) showed significant quasielastic broadening over the instrument resolution indicating presence of stochastic molecular motions of the surfactant. Data analysis clearly demonstrated the presence of two distinct motions of the surfactants, namely, (i) lateral and (ii) segmental motions. In this case, resultant scattering law could be written as, S Q, Slat lat , S seg seg ,
(10)
Using the scattering laws for lateral and segmental motions (given in Eqs. (6) and (7)), Eq. (10) can be written as S Q, Llat lat , A(Q) ( ) (1 A(Q)) Lseg ( seg , )
S Q, A(Q) Llat lat , ( ) (1 A(Q)) Llat lat , Lseg ( seg , )
The convolution of a Lorentzian and a delta function is a Lorentzian function and convolution of two Lorentzian functions is a Lorentzian function, whose HWHM is the sum of the HWHMs of the two individual Lorentzian functions. Hence, the effective scattering law can be written as,
S Q, A Q Llat lat , 1 A Q Ltot (lat seg , )
(11)
Eq. (11) could describe the QENS data for SDS micelles using IRIS spectrometer quite well. Typical fitted QENS spectra for SDS micelles using Eq. (11) along with two components corresponding to lateral and segmental motion are shown in Fig. 2(a) for Q=1.0 Å-1. To understand the nature of the dynamical processes, the behaviour of the parameters, A(Q), lat and seg, were investigated. Variations of the HWHMs of the Lorentzian function corresponding to the lateral motion, lat, at different temperatures are shown in Fig. 2 (b). It is evident that lat varies linearly with Q2 at different temperatures, indicating continuous diffusion following Fick’s law, lat = DlatQ2, as shown by the lines. Here, Dlat is the lateral diffusion coefficient and can be obtained from the slope of the fitted lines. At 300K, Dlat of SDS was found to be 2.510-6 cm2/s and increases to 3.110-6 cm2/s at 330 K. EISF (A(Q)) and HWHM (seg) corresponding to segmental motion, are shown in Fig. 2 (c) and (d), 14 ACS Paragon Plus Environment
Page 15 of 56 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60
Langmuir
respectively. The particular feature of HWHM corresponding to segmental motion asymptotically taking a finite nonzero value in the zero-Q limit and monotonically increasing with increasing Q is a typical signature of localized translational diffusion (LTD) [67]. The scattering law for translational diffusion of a particle confined in a sphere, can be written as [67] S (Q, ) A (QR) ( ) 0 0
1
2l 1 A (QR) l n
l , n0,0
( xnl ) 2 D / R 2 2
( xnl ) 2 D / R 2 2
(12)
where A00 (QR) is the EISF and can be written as
3 j (QR) EISF A (QR) 1 QR 0 0
2
(13)
where R is the radius of the sphere and j1 is the first order spherical Bessel function. Anl (QR) (n,l 0,0) is the quasielastic structure factor and can be calculated for n and l by using the values of xnl given in ref. 67. Due to the flexibility of the alkyl chain, all the hydrogen atoms may not have the same size of spherical domain and diffusivity. Therefore, distributions in radii of spheres and diffusivities for the hydrogen atoms along the alkyl chain can be envisaged. One can consider various distributions for the radii and diffusivities, such as linear [68], log-normal [69], etc. Here we have adopted a linear distribution for the radii of the spherical domains and associated diffusivities along the alkyl chain [40]. Based on this model, the CH2 units closest to the head group experience the highest restriction and therefore have the minimum radius (Rmin) and diffusivity (Dmin). Likewise, the radius and diffusivity would increase linearly along the alkyl chain and attain the maximum value of radius (Rseg) and diffusivity (Dseg) at the last (CH3) unit of the chain [40]. Hence, resultant scattering law will be averaged over the total number of CH2 sites in the alkyl chain having different size of spherical domains and associated diffusivities [40]. This model could describe the EISFs corresponding to the segmental motion quite well at different temperatures as indicated by the solid lines in Fig. 2(c) and the value of Rmin and Rseg are obtained. One can calculate the HWHM of the quasielastic part [40] for a given value of Dmin and Dseg. Dmin and Dseg are obtained from the experimentally extracted seg by using the least squares fitting method. As can be seen from the Figs. 2 (c) and (d) that the model provides a very good description of the data. A schematic of the proposed model for the segmental motion of the surfactant is shown in the inset of Fig. 2(d). Values for Rmin and Dmin were found to be very small, which indicates negligible movement of the hydrogen atoms in the 15 ACS Paragon Plus Environment
Langmuir 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60
Page 16 of 56
first CH2 unit near the head group. At 300K, the largest radius, Rseg and associated diffusivity, Dseg were found to be 3.4 Å and 910-6 cm2/s respectively. As the temperature increases, Rseg and Dseg increase to 4.4 Å and 1510-6 cm2/s respectively at 330K.
Fig. 2 (a) Typical fitted QENS spectra for 0.6 M SDS micelles observed using IRIS spectrometer (E~ 17eV) at Q=1.0 Å-1 and T=300 K. Components correspond to lateral and segmental motions are also shown. (b) Variation of HWHMs of the Lorentzian corresponding to the lateral motion with Q2 at different temperatures. Behaviour of, (c) EISF (A(Q)) and (d) HWHMs of the Lorentzian function representing the segmental motion at different temperatures. Solid lines are the fits assuming the models described in the text. Schematic of the model is shown in the right bottom panel.
Adapted with permission from ref 40.
Copyright 2010 American Chemical Society. To get detailed insight of the diffusion processes, MD simulation was carried out on SDS micelles [17] at 300 K using the NAMD simulation software [70] with CHARMM 22 force-field parameters and the TIP3P water model [71]. Snapshot of a SDS micelle is shown 16 ACS Paragon Plus Environment
Page 17 of 56 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60
Langmuir
in Fig. 3(a). Some monomers are highlighted to show the different orientations. Incoherent intermediate scattering functions, I(Q,t), corresponding to the H-atoms of the SDS molecule were calculated from the trajectories of the MD simulation (Eq. (9)). This could be compared with QENS results directly. It was found that obtained I(Q,t) could be described by a linear sum of three exponential decay functions over the entire Q and t range
Fig. 3 (a) Snapshot of a SDS micelle at 300K. Some molecules are highlighted to show the different orientations. (b) Incoherent intermediate scattering function calculated from MD simulation for SDS at Q = 1.0 Å-1. (c) Typical fitted QENS spectra for SDS micelles observed with IN5 spectrometer (E~ 60eV) at Q=1.1 Å-1. (d) Variations of decay constants/HWHMs as obtained from MD simulation and QENS experiments correspond to different motions at T=300K. Adapted with permission from ref 17. Copyright 2015 American Chemical Society. [17]. This indicated that three distinct motions exist in the SDS micelles occurring in different time scales. Typical fitted I(Q,t) for SDS micelles at 300K at Q=1.0 Å-1 along with three components are shown in Fig. 3 (b). It is found that the slowest and the intermediate 17 ACS Paragon Plus Environment
Langmuir 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60
components correspond to the lateral and segmental motions respectively, which were observed in the QENS data obtained from the IRIS spectrometer (E=17eV). The faster component observed in MD simulation, should correspond to the torsional motion. This was not discernible in the experimental data, being too fast (~1.5 meV) to be observed within the dynamic range of the IRIS spectrometer. To observe this motion, QENS measurements were carried out on IN5 spectrometer (E~60eV), at ILL, Grenoble, France, having much wider dynamic range compared to IRIS. The observed data could be consistently described by taking into account the dynamics observed with IRIS and an additional faster dynamical component indicated in MD simulation [17]. Typical fitted QENS spectra along with the three components corresponding to lateral, segmental and torsional motions are shown in Fig. 3 (c) at Q =1.1 Å-1. Variation of the obtained decay constants (by analysing I(Q,t) calculated from MD simulation) and HWHM (from the analysis of QENS data), corresponding to different motions, with Q, are shown in the Fig. 3 (d). HWHM corresponding to the torsional motion is found to be independent of Q. It was found that the torsional motion follows the 2fold reorientation with associated radius of gyration and reorientation time of 2.0 Å and 0.8 ps respectively. It is evident that the decay constants/HWHMs obtained from simulation and experiments are in good agreement indicating consistency of the model. It was of interest to investigate whether these surfactant molecules in the solid phase show any dynamical motion as observed in the micellar form. Elastic fixed window scan (EFWS) and QENS experiments were carried out to investigate the molecular mobility in SDS powder [41]. EFWS or elastic intensity scan is a suitable technique to investigate the phase transitions related to temperature activated microscopic mobility. It can monitor the thermal evolution of the microscopic dynamics in the system due to its sensitivity towards the mobility of atoms/molecules. A sharp/discontinuous decrease or increase in elastic intensity with temperature scan is a strong indicator of a phase change correlated to the dynamics. EFWS and QENS data showed that the dynamics evolves monotonically with increasing temperature and a dynamical transition takes place above 360 K [41]. This was consistent with the differential scanning calorimetry (DSC) data, which showed a sharp peak around 370 K [41]. Detailed analysis of the QENS data showed that for T < 360 K, SDS molecules undergo fractional dynamics following uniaxial rotational diffusion (URD) [72] about the chain axis with an activation energy ~3.8 KJ/mol. The dynamical contribution is found to evolve with increase in temperature. The fraction of chain participates in the dynamics increase from 10 % to 60 % on increasing the temperature from 210 to 360 K. It started from 18 ACS Paragon Plus Environment
Page 18 of 56
Page 19 of 56 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60
Langmuir
the end of the chain, which is expected to be relatively free and progresses toward the head. Above the dynamical transition (T > 360 K), the observed dynamics was found to be describable by LTD of the alkyl chain of the SDS molecule [41]. Schematics of the motion in solid SDS below and above the transitions are shown in Fig. 4. It is interesting to note that the dynamical behaviour of SDS above the dynamical transitions is very similar to that observed in the micellar form.
Fig. 4 Schematic of the molecular motion in solid SDS, (a) below the transition temperature (T≤360 K), the molecules perform uniaxial rotation diffusion (URD) along the molecular axis, and (b) localized translational diffusion (LTD) model above 360 K. Adapted with permission from ref 41. Copyright 2011 American Chemical Society. Subsequent to the study of anionic micelles, dynamics of cationic 0.3 M DTAB (C12TAB) micelles [17,42] was investigated. DTAB molecule has 3 methyl units in the head group in contrast to SDS where the head group (SO4) does not contain any hydrogen. Hence, the head group of DTAB will also contribute to the QENS data in addition to the alkyl chain. QENS experiments and MD simulations were carried out on DTAB micelles to investigate detailed dynamical landscape [17, 42]. Lateral motion of DTAB was found to be Fickian in nature, similar to SDS micelles. In the segmental motion, apart from the alkyl chain, head group also contributed. It was found that a model in which the CH3 units in the head group undergoes a 3-fold rotation and the alkyl chain performing LTD, could describe the segmental motion of the DTAB molecules. Fast torsional motion of DTAB molecule is 19 ACS Paragon Plus Environment
Langmuir 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60
described by 2-fold reorientation similar to the SDS molecule. Therefore, a complete description of the dynamical features in both anionic and cationic micelles is established in nanoseconds to picoseconds regime by using QENS and MD simulation studies. Next section deals with the effect of various parameters such as molecular architecture of the surfactant, addition of electrolytes on the dynamics of the micelles [15, 42, 44, 45]. Effects of Molecular Architecture of the Surfactant Additional Phenyl Ring near the Head Group Molecular architecture of the surfactant is an important parameter that controls the structural arrangement of the monomers in the micelles and by this, one can tailor a micellar system for different applications. In general, structural variations comprise the relative sizes of the alkyl chain and head group, single-versus multiple-tailed, the presence of single and multiple head groups and so on. One aspect of variation in the molecular architecture investigated by us is the effect due to the presence of additional group (e.g. phenyl) in the surfactant. Sodium dodecyl benzene sulfonate (SDBS;C12H25C6H4SO3Na) molecule which contains hydrophobic dodecyl alkyl chain similar to SDS (C12H25OSO3Na) molecule but with an additional phenyl ring attached to the hydrophilic sulfonate group [44-45]. SDBS is a major constituent of the synthetic detergents and widely used in emerging field of nano technology for graphene exfoliation, the synthesis of nanoparticles, etc. [73-74]. To investigate dynamical behaviour in these surfactants, QENS experiments were carried out on 0.3 M SDS and SDBS micelles [44-45]. All other conditions such as concentration of surfactant, temperature, etc. were kept same, so that effect of the surfactant architecture could be quantified. It was found that for SDBS micelles, there was a significant reduction in quasielastic broadening in comparison to SDS micelles indicating presence of phenyl group near the head group does affect the dynamics of the micelles [44, 45]. Our data analysis showed that not only the lateral motion but also the segmental motion of SDBS was restricted compared to SDS [45]. For SDBS micelles, the Dlat at 300K was found to be 1.910-6 cm2/s, which is about half of that obtained for SDS micelles [45]. Dodecyl chains in SDBS micelles were found to be less flexible than SDS micelles [44, 45]. These observations were consistent with the MD simulation study [55] which had shown that the dynamics in SDBS micelles are restricted compared to SDS.
20 ACS Paragon Plus Environment
Page 20 of 56
Page 21 of 56 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60
Langmuir
Varied Chain Length Other aspect of variation in the molecular architecture of surfactant is the length of alkyl chain . It is reported that with the increase in alkyl chain length the aggregation number and the size of the micelles increase whereas CMC decreases because of the fact that the larger hydrophobic part of the surfactant favors micellization [75-77]. For nalkyltrimethylammonium bromide, CnH2n+1N(CH3)3Br, (CnTAB) micelles, it had been shown [77] that C12TAB and C14TAB are roughly spherical. However, for longer alkyl chain length (higher n), like C16TAB, with the same experimental conditions, the micelles adopt an ellipsoidal shape to accommodate the additional non-polar tails in the core. The fractional charge of the micelles decreases with the increase in n [76-77]. Our interest here was to investigate the effects of the molecular architecture with varied chain length of the surfactant on the dynamics of the micelles. Effects of chain length on the dynamics of 0.3 M cationic CnTAB micelles (with n = 10,12,14,16) were investigated using QENS technique [42]. Typical QENS spectra for 0.3 M CnTAB (n = 10,12,14,16) micelles are shown in Fig. 5(a). Observed QENS data clearly show that with increasing chain length (n), dynamics of CnTAB (with n = 10,12,14,16) is greatly affected, quasielastic broadening decreases with increase in n. Detailed data analysis showed that both the lateral and segmental motions of the surfactant get constrained with increase in the chain length [42]. Effects of temperature on the dynamics of micelles were also investigated and found that with increase in temperature both lateral and segmental motions of the surfactant become faster. For all the CnTAB micelles, lateral diffusion was found to be Fickian in nature. Variation of Dlat of CnTAB with the chain length (n) at 300K is shown in Fig. 5(b). While for C10TAB, Dlat is found to be 3.210-6 cm2/s at 300K, it decreases with chain length to 2.010-6 cm2/s for C16TAB. However, with the increase in temperature, Dlat is found to increase for all CnTAB micelles. Variation of Dlat for C14TAB is shown in the Fig. 5(b). For segmental motion, the size of the spherical domain and the associated diffusion coefficients got reduced and the residence time of the CH3 units in the head group was increased with increase in the chain length. Variations of Dseg of the alkyl chain of CnTAB with the chain length at 300K and with temperature for C14TAB are shown in Fig. 5(c). While for C10TAB, Dseg is found to be 1.610-5 cm2/s at 300K, it decreases with the chain length to 1.010-5 cm2/s for C16TAB. Observed hindrance in lateral and segmental
21 ACS Paragon Plus Environment
Langmuir
S(Q,) in arb unit
(a) C10TAB C12TAB
0.01
C14TAB C16TAB Resolution
1E-3
-0.3
0.0
0.3
0.6
0.9
E (meV) T (K) 250
275
300
325
Dseg(10-6 cm2/s)
2 -6
T (K)
275
300
325
12
14
16
(c)
4
3
2 10
250
27
(b) Dlat (10 cm /s)
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60
Page 22 of 56
12
14
18
9
16
10
Chain length (n)
Chain length (n)
Fig. 5 (a) Typical fitted QENS spectra assuming both lateral and segmental motions for 0.3M CnTAB micelles. Variation of diffusion coefficient corresponding to, (b) lateral motion (Dlat) and (c) segmental motion (Dseg) of CnTAB with chain length at 300K. Temperature dependences of Dlat and Dseg for C14TAB micelles are also shown. Adapted with permission from ref 42. Copyright 2012 American Chemical Society.
motions with increase in chain length could be explained on the basis of size of the surfactant and enhancement in counterion condensation. For ionic micelles, counterions reside near the oppositely charged micellar surface, and experience significant electrostatic attraction compared to the thermal energy and therefore these counterions are stated as ‘condensed on’ the micelles. As the chain length increases, there is an enhancement in the counterion condensation which results in decrease of the micellar fractional charge [76-77]. The increased counterion condensation screens the electrostatic repulsion between the head groups and permits them to move closer. This enhances the packing density of the surfactants within the micelles. Therefore, in case of C16TAB micelles, the surfactants are more closely 22 ACS Paragon Plus Environment
Page 23 of 56 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60
Langmuir
packed in comparison to C10TAB micelles. Enhancement in packing of the surfactants also results in the expulsion of water molecules within the micelles and therefore hydration level inside the micelles decreases with the increase of the chain length. All these factors result in the hindrance of the lateral and segmental motions of the longer chain surfactants in the micelles. Effects of Addition of Electrolytes In the previous section, it is shown that with the increase in chain length of the CnTAB micelles, both lateral and segmental motions are restricted. There are two major factors, (i) size of surfactant and (ii) counterion condensation that play important roles on the dynamics of micelles. To investigate counterion condensation alone, QENS experiments were carried out on 0.3 M C12TAB micelles in the absence and presence of salts, which enhances counterion condensation while keeping surfactant size same. It is known that due to addition of salt, additional counterions condense near the charged surface of the micelles, which screens repulsive interaction between the charged head groups and allow them to come closer. This enhances the critical packing parameter, Cpp, and modifies the structure of the micelles significantly. Spherical micelles can undergo transformation to rod like micelles in the presence of electrolytes. Our interest was to investigate the effects of addition of electrolytes or counterion condensation towards dynamics of the micelles. It had been shown [8,78] that organic salts are more effective in the screening of the repulsive interaction compared to inorganic salts. Sodium salicylate (NaSal) is an organic salt in the family of salicylates to which the most common anti-infllammatory drug aspirin belongs. In fact, NaSal is a key ingredient in manufacturing process of aspirin. It has been reported [79,80] that addition of NaSal initiates the transformation of spherical micelle to cylindrical wormlike micelles. It was of interest to probe the changes in the dynamical profile of the surfactants in the micelle and correlate it with the effects of salicylate compounds on surfactant/lipid aggregates. In pursuit of this objective, QENS, DLS and MD simulation studies were carried out on DTAB micelles in the presence/absence of NaSal [15]. DLS measurements [15] showed that incorporation of NaSal reduces apparent diffusion coefficient of the whole micelle which indicates growth of the micelles. MD simulations [15] carried out on cylindrical C12TAB micelles in absence and presence of NaSal provided some interesting observations. CHARMM 36 force field parameters were used in the simulation [81]. It is found that in the absence of NaSal the cylindrical micelle breaks into smaller spherical micelles within a short time, while the presence of NaSal, cylindrical C12TAB micelle 23 ACS Paragon Plus Environment
Langmuir 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60
remained stable even up to 20 ns as shown in the snapshot given in Fig.6. These observations were consistent with small angle neutron scattering and DLS measurements which showed that in the presence of salt, spherical micelles grew into an ellipsoidal one.
Fig. 6 Snapshots of cylindrical pure C12TAB micelle at 0 ns, 2 ns and 3 ns (top panels) and C12TAB micelles in presence of NaSal at 0 ns, 5 ns and 20 ns (bottom panels). Adapted with permission from ref 15. Copyright 2017 American Chemical Society.
Typical calculated I(Q,t) obtained from the MD simulation trajectories for DTAB C12TAB micelles in absence and presence of NaSal are shown in Fig.7 (a). As can be seen from the figure, the addition of NaSal salt constraints the dynamics in C12TAB micelles. QENS data were analysed based on the lateral and segmental components as mentioned before. The analysis reveals that the presence of NaSal slows down the lateral diffusion significantly at all temperatures (Fig.7 (b)), while the segmental dynamics remain unaffected. The underlying mechanism could be propounded from the atomistic details offered by MD simulation trajectories, which showed that the salicylate ions were predominantly located at the surface of the cylindrical micelles. Further, the orientation of the salicylate ions were explicitly captured by calculating the frequency distribution of angles between the molecular axis of DTA+ (angle pointing in the direction of head group which is proton rich) ion and salicylate (angle pointing in the direction of carboxylate moiety which is electron rich) ion. 24 ACS Paragon Plus Environment
Page 24 of 56
Page 25 of 56 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60
Langmuir
The angular frequency distribution (Fig. 7(c)) showed that salicylate ions have a preferred orientation such that hydrophilic group reside at the surfactant head group region, and the hydrophobic group is partially goes into the micellar core. This observation suggests that the most of salicylate ions are interacting strongly with the oppositely charged head group of DTAB. This strong interaction with the salicylate ions effectively increase the inertia of DTAB surfactants leading to the restricted lateral diffusion. Given the premise, it can also be inferred that the location of salicylate ions mostly near the head group, leaves the segmental motion of DTAB (mainly contributed by the tail) unaffected.
Fig. 7 (a) Typical calculated I(Q,t) for C12TAB micelles in absence and presence of NaSal at Q=1.2 Å-1 and T=300K. (b) Dlat of C12TAB in micelles in absence and presence of NaSal salt obtained from QENS experiment. (c) Distribution of the angle between the axis of the C12TAB and nearby salicylate ions. Adapted with permission from ref 15. Copyright 2017 American Chemical Society.
25 ACS Paragon Plus Environment
Langmuir 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60
Vesicles Vesicles have closed bilayer structures that encompass a water pool and are surrounded by an aqueous solution as shown in Fig.1. Vesicles are not only important from the prospect of their practical applications in drug delivery and nanotechnology but also from the fact that they mimic biological membranes. As mentioned before, geometry of the self-assembled aggregates depends on the Cpp which strongly depends on the molecular architecture of the surfactant. Generally double tailed surfactants (or lipids) having large hydrocarbon chain volume (v) prefer to form vesicle kind of structures. Dynamics of different vesicles had been studied by us and will be discussed in this section. First, the dynamical behaviour in a catanionic vesicle, in particular, effects of the transition from mutilamellar vesicles to unilamellar will be discussed.
In the next section, dynamical and phase behaviour of
dimyristoylphosphatidylcholine (DMPC) phospholipid and dioctadecyldimethylammonium bromide (DODAB) lipid will be presented. Effects of different additives (drugs, ionic liquids) on the dynamical and phase behaviour of the lipid membrane will also be discussed. Catanionic Vesicles Mixing of unequal quantities of anionic and cationic single-tailed surfactants in aqueous media can spontaneously form catanionic vesicles [82-84]. First catanionic vesicle was reported by Kaler et al. [82] about three decades ago. In the catanionic vesicle, the anioniccationic single chained surfactant pair acts with double-tailed zwitterionic attitude. These vesicles possess a number of unique physical and chemical properties that make them attractive for diagnostic and drug delivery applications [82, 83]. Andreozzi et al [84] had shown temperature induced multilamellar-to-unilamellar transition in catanionic vesicles based on anionic SDS and cationic C16TAB surfactants. It was shown that upon heating SDS/C16TAB catanionic vesicle, the state changes from multilamellar-to-unilamellar subsequent to fusion of vesicles. Combination of various terms (e.g entropic, osmotic, etc.) drive the transition from multi- to unilamellar vesicles. It was shown [84] that the used method leads to kinetically stable monolayer dispersions that can be employed in various biomedical applications. Our interest was to investigate the dynamical behaviour of surfactants in SDS/C16TAB catanionic vesicles across the multilamellar-to-unilamellar transition. Calorimetric and EFWS measurements were carried out on 0.16 M SDS/C16TAB (molar ratio=1.6) catanionic vesicles to investigate multilamellar-to-unilamellar transition [46]. DSC data [46] showed a transition at 307K on heating and at 294K in the cooling cycle 26 ACS Paragon Plus Environment
Page 26 of 56
Page 27 of 56 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60
Langmuir
indicating the presence of a hysteresis effect (inset of Fig. 8 (a)) in this system. This transition is attributed to a structural reorganization from multilamellar vesicles (MLV) to unilamellar vesicles (ULV) [84]. EFWS data obtained using IN16B, ILL, Grenoble, was found to be consistent with DSC measurement as shown in Fig. 8(a). It is evident that upon heating, the elastic intensity decreases continuously with increase in temperature and a sharp fall occurs at 307K. on the other hand, in the cooling cycle, the reverse transition occurred at ~294K. The sudden fall and gain observed in the EFWS correspond to change in the microscopic dynamics related to the transition from MLV to ULV. Presence of hysteresis provided a unique opportunity to delink the temperature dependence and investigate solely the effects of MLV to ULV transition on the dynamics of vesicles. QENS data were first measured at 300K where vesicles were in MLV phase and then heated at 340K (well above the transition temperature) and then cooled back to 300K where vesicles were still in ULV phase [46] and QENS measurements were carried out. Typical measured QENS data at Q=1.01 Å-1 for SDS/C16TAB catanionic vesicles in MLV and ULV state at 300K are shown in Fig. 8 (b). Observed QENS data showed that the dynamics in the MLV phase is much slower compared to that in the ULV phase. QENS data also indicated that all the surfactant molecules are not participating in the lateral motion especially in the MLV phase. To take this in to account, the generalized scattering law for catanionic vesicles could be written as [46] S Q, Px ( ) (1 Px ) Llat lat , A(Q) ( ) (1 A(Q)) Lseg ( seg , )
(14)
where Px is the fraction of the surfactant which are not performing the lateral motion. Eq. (14) can be rewritten as with the approximation that lat
