Julian Bent

Controlling the micellar morphology of binary PEO–PCL block copolymers in water–THF through controlled blending

We study both experimentally and theoretically the self-assembly of binary polycaprolactone–polyethylene oxide (PCL–PEO) block copolymers in dilute solution, where self-assembly is triggered by changing the solvent from the common good solvent THF to the selective solvent water, and where the two species on their own in water form vesicles and spherical micelles respectively. We find that in water the inter-micellar exchange of these block copolymers is extremely slow so that the resultant self-assembled structures are in local but not in global equilibrium (i.e., they are non-ergodic). This opens up the possibility of controlling micelle morphology both thermodynamically and kinetically. Specifically, when the two species are first molecularly dissolved in THF before mixing and self-assembly (‘pre-mixing’) by dilution with water, the morphology of the formed structures is found to depend on the mixing ratio of the two species, going gradually on a route of decreasing surface curvature from vesiclesvia an intermediate regime of micelles in the shape of ‘bulbed’ rods, rings, Y-junctions and finally to spherical micelles as we increase the proportion of the “sphere formers”. On the other hand, if the two species are first partially self-assembled (by partial exchange of the solvent with water) before mixing and further self-assembly (‘intermediate mixing’), novel metastable structures, including nanoscopic ‘pouches’, emerge. These experimental results are corroborated by Self-Consistent Field Theory (SCFT) calculations which reproduce the sequence of morphologies seen in the pre-mixing experiments. SCFT also reveals a clear coupling between polymer composition and aggregate curvature, with regions of positive and negative curvature being stabilized by an enrichment and depletion of sphere formers respectively. Our study demonstrates that both thermodynamic and kinetic blending of block copolymers are effective design parameters to control the resulting structures and allow us to access a much richer range of nano-morphologies than is possible with monomodal block copolymer solutions.

The long-chain dynamics in a model homopolymer blend under strong flow: small-angle neutron scattering and theory

We use small-angle neutron scattering (SANS) measurements to provide a detailed picture of the non-linear dynamics of the long chains in a model polystyrene blend. By a weighted subtraction of SANS measurements from two otherwise identical blends with different deuteration fractions, we isolate the single-chain form factor of the long-chain component of a model blend flowing through a 4 : 1 contraction–expansion flow. Complementary flow-birefringence also provides a measure of chain deformation on finer length-scales. In addition, higher flow Weissenberg numbers than in previous studies on monodisperse melts were achieved, leading to greater anisotropy in the measured single-chain structure factor. The short residence time inside the slit means that the chains are still oriented in the flow direction as they enter the contraction exit, leading to a rapid reversing flow. We compare these data to a simple generalisation of a non-linear tube model. Our model predictions are entirely ab initio, with all model parameters being determined from independent equilibrium measurements. The model shows very good agreement with the experimental data across the full range of length-scales for the contraction entrance and subsequent relaxation within the slit. However, there is conspicuous disagreement between theory and experiments at the contraction exit, in both the SANS and birefringence predictions, which we attribute to the reversing flow that occurs in this region.

Temporal sparsity exploiting nonlocal regularization for 4D computed tomography reconstruction.

X-ray imaging applications in medical and material sciences are frequently limited by the number of tomographic projections collected. The inversion of the limited projection data is an ill-posed problem and needs regularization. Traditional spatial regularization is not well adapted to the dynamic nature of time-lapse tomography since it discards the redundancy of the temporal information. In this paper, we propose a novel iterative reconstruction algorithm with a nonlocal regularization term to account for time-evolving datasets. The aim of the proposed nonlocal penalty is to collect the maximum relevant information in the spatial and temporal domains. With the proposed sparsity seeking approach in the temporal space, the computational complexity of the classical nonlocal regularizer is substantially reduced (at least by one order of magnitude). The presented reconstruction method can be directly applied to various big data 4D (x, y, z+time) tomographic experiments in many fields. We apply the proposed technique to modelled data and to real dynamic X-ray microtomography (XMT) data of high resolution. Compared to the classical spatio-temporal nonlocal regularization approach, the proposed method delivers reconstructed images of improved resolution and higher contrast while remaining significantly less computationally demanding.

Recirculation cell for the small-angle neutron scattering investigation of polymer melts in flow

A small-scale flow cell has been developed and used for small-angle neutron scattering (SANS) investigations of polymer melts in Poiseuille flow through a 4:1 contraction. The cell enables the investigation of polymer melt flow subject to a volumetric flow rate of up to 6 cm3 s−1, at pressures up to 10 MPa, temperatures up to 230 °C, and a melt viscosity up to 65 000 Pa s. The cell has recirculating flow path and a relatively small capacity (circa 200 g of polymer) so that polymers with novel and well-defined molecular architectures may be investigated. The details of its construction and operation are described. When two walls of the cell are composed of zero order birefringent sapphire, both small-angle neutron scattering and birefringence studies can be undertaken in the same cell providing a link between macroscopic and molecular level descriptions of the influence of melt flow. Both birefringence and the first melt flow SANS data for a monodisperse, linear polystyrene are presented. These demonstrate...

Synchrotron X-ray tomographic quantification of microstructural evolution in ice cream – a multi-phase soft solid

Microstructural evolution in soft matter directly influences not only the materials mechanical and functional properties, but also our perception of that materials taste. Using synchrotron X-ray tomography and cryo-SEM we investigated the time–temperature evolution of ice creams microstructure. This was enabled via three advances in synchrotron tomography: a bespoke tomography cold stage; improvements in pink beam in line phase contrast; and a novel image processing strategy for reconstructing and denoising in line phase contrast tomographic images. Using these three advances, we qualitatively and quantitatively investigated the effect of thermal changes on the ice creams microstructure after 0, 7 and 14 thermal cycles between −15 and −5 °C. The results demonstrate the effect of thermal cycling on the coarsening of both the air cells and ice crystals in ice cream. The growth of ice crystals almost ceases after 7 thermal cycles when they approach the size of the walls between air cells, while air cells continue to coarsen, forming interconnected channels. We demonstrate that the tomographic volumes provide a statistically more representative sample than cryo-SEM, and elucidate the three dimensional morphology and connectivity of phases. This resulted in new insights including the role of air cells in limiting ice crystal coarsening.

A 4-D dataset for validation of crystal growth in a complex three-phase material, ice cream

Four dimensional (4D, or 3D plus time) X-ray tomographic imaging of phase changes in materials is quickly becoming an accepted tool for quantifying the development of microstructures to both inform and validate models. However, most of the systems studied have been relatively simple binary compositions with only two phases. In this study we present a quantitative dataset of the phase evolution in a complex three-phase material, ice cream. The microstructure of ice cream is an important parameter in terms of sensorial perception, and therefore quantification and modelling of the evolution of the microstructure with time and temperature is key to understanding its fabrication and storage. The microstructure consists of three phases, air cells, ice crystals, and unfrozen matrix. We perform in situ synchrotron X-ray imaging of ice cream samples using in-line phase contrast tomography, housed within a purpose built cold-stage (-40 to +20oC) with finely controlled variation in specimen temperature. The size and distribution of ice crystals and air cells during programmed temperature cycling are determined using 3D quantification. The microstructural evolution of three-phase materials has many other important applications ranging from biological to structural and functional material, hence this dataset can act as a validation case for numerical investigations on faceted and non-faceted crystal growth in a range of materials.

Time-Resolved Tomographic Quantification of the Microstructural Evolution of Ice Cream

Ice cream is a complex multi-phase colloidal soft-solid and its three-dimensional microstructure plays a critical role in determining the oral sensory experience or mouthfeel. Using in-line phase contrast synchrotron X-ray tomography, we capture the rapid evolution of the ice cream microstructure during heat shock conditions in situ and operando, on a time scale of minutes. The further evolution of the ice cream microstructure during storage and abuse was captured using ex situ tomography on a time scale of days. The morphology of the ice crystals and unfrozen matrix during these thermal cycles was quantified as an indicator for the texture and oral sensory perception. Our results reveal that the coarsening is due to both Ostwald ripening and physical agglomeration, enhancing our understanding of the microstructural evolution of ice cream during both manufacturing and storage. The microstructural evolution of this complex material was quantified, providing new insights into the behavior of soft-solids and semi-solids, including many foodstuffs, and invaluable data to both inform and validate models of their processing.