Local dynamics and deformation of glass-forming polymers : modelling and atomistic simulations

The research described in the present thesis is about glassy phenomena and mechanical properties in vitrifiable polymer materials. Glasses are solid materials, but, in contrast to crystals, the structure is disordered. Polymers are macromolecular chains formed by covalently linking a very large number of repeating molecular building blocks or monomers. Polymeric materials are easy to reshape and reuse. Also they are lightweight and often transparent. These characteristics make them ideal materials for commodity products such as compact discs, safety helmets, or vandal-proof glazing. Some glassy polymers are also biocompatible, so that they can be used in medical applications. For a successful usage of polymer glasses it is necessary to understand and predict their behaviour under various circumstances. Although many new insights have been acquired over the last decades still a lot of questions remain open. Upon vitrifying a polymer melt the relaxation times and the viscosity increase dramatically. Accompanied with this increase various glassy phenomena are observed — in particular dynamical heterogeneities and non-Gaussian displacements of particles. The comprehension of the striking viscosity increase and the two phenomena mentioned above is still far from complete. During the straining of a polymer glass typical mechanical characteristics are observed, of which the magnitude can vary enormously between different types of polymers. A wellknown example of a polymer glass is atactic polystyrene. In its glassy state polystyrene is usually found to be very brittle. Within a few percent of elongation the material breaks. This behaviour is caused by a relatively high yield tooth in combination with a relatively low strain-hardening modulus. Other polymers, such as bisphenol-A polycarbonate, show a tough response; a test bar can easily be extended to twice its original length. In spite of much study, the physical (molecular) origin of this difference in mechanical behaviour is still not clear. Below the glass transition rubber-elasticity theory appears to be invalid, as it fails to explain the observation that the strain-hardening modulus of polystyrene in its glassy phase is about two orders of magnitude higher than its modulus in the rubbery state. Our main goals are to acquire a better understanding at the molecular scale of heterogeneous and non-Gaussian dynamics and mechanical deformation of glassy polymers and to differentiate chemistry-specific from more universal physical properties. These goals are achieved by carrying out molecular-dynamics simulations on glass-forming systems. In addition, the results are elucidated by the usage of simple physical models. The simulations consist of solving the equations of Newton, a coupled set of differential equations with a given force field and initial conditions. The force field describes the interactions between the various particles. As the main interest is in glassy polymers, most simulations are done for a united-atom model of polystyrene. In the simulation run several characteristics of the glass transition are identified. As is typical for other vitreous systems as well, anomalous, non-Gaussian displacements play an important role near the glass transition for polystyrene; the same observation has been made for a dendritic melt and a colloid-like system. For all these systems of different architecture we have described some essential features of this non-Gaussian behaviour with a simple one-particle model in an effective field. The non-Gaussian behaviour is mainly caused by the cage-to-cage motion of the constituent particles, whereby the cage is formed by interactions with neighbouring particles. By means of the model the height of the so-called non-Gaussian parameter can be interpreted as a measure for the ratio of the root-mean-square displacement within the cage and the effective jump length between cages, without the assumption of any heterogeneity of glassy dynamics in the sense of sitespecific relaxation times. The maximum of the non-Gaussian parameter occurs in each case at the crossover from the cage regime to the (sub)diffusive regime and is connected to the cage-escape time. For the colloid-like system also the shape of the time-dependent non-Gaussian parameter is described well by the model (chapter 3). Dynamical heterogeneity, a phenomenon observed in many experiments on glasses, is also found in the simulation result of the polystyrene phenyl-ring-flip movement (to which the mechanical gamma relaxation is ascribed). This means that some phenyl rings behave very differently than others within a typical simulation run. Different relaxation times and activation enthalpies associated with the flip are determined using various methods. A particular result of the study of the phenyl flip is that an enthalpy barrier determined solely from structural properties is in accordance with an activation enthalpy acquired by analyzing the dynamics of the phenyl rings, even in the presence of dynamical heterogeneity. The heterogeneity arises because of the following mechanism. The conformation of the backbone determines to a large extent the barrier of the phenyl-ring flip. Eventually the relaxation of the backbone is becoming so slow upon cooling down that the phenyl ring is unable to access the conformation-dependent state with the lowest flip barrier within the corresponding barrier-jump time. The phenyl rings are trapped instead in various other states with accompanying different energy barriers. These states are available because of the disordered nature of the material. The mechanism just described for the heterogeneous dynamics in the phenyl-ring flip movement becomes stronger upon cooling down towards the glass transition; eventually the relaxation becomes more Arrhenius-like below the glass transition temperature because only the fastest phenyl flips occur within the accessible observation time (chapter 4). By doing uniaxial-stress extension and compression simulations the stress-strain relation of polystyrene has been measured under various conditions. Although the cooling and deformation velocities in the simulations differ many orders of magnitude from their values in usual experiments, the characteristic features of the experimental stress-strain relation are well reproduced, which allows one to study the origin of the yield tooth and strain hardening. It is observed that the strain-hardening modulus increases with increasing pressure, an effect not described by rubber-elasticity theory. Also it is observed that the thermal history is not completely erased by the mechanical deformation. The picture arising from this study is that the yield peak in polystyrene is mostly mediated by interchain energetic interactions. A net debonding of these interactions is likely causing this yield peak and the subsequent strain softening. The positiveness of the strain-hardening modulus in polystyrene is mainly due to intrachain interactions (chapter 5). From our comparative study of polystyrene and polycarbonate it can be concluded that strain hardening in polymer glasses such as these two polymers is likely caused mainly by the following mechanism. During uniaxial extension a glassy chain adopts a more stretched and hence more inflexible state, also at a local scale. Due to interactions with other particles non-affine displacements take place. The non-affine response is stronger at shorter length scales, but as the deformation proceeds and the effective flexibility decreases also longer length scales are affected. This is accompanied with more bond-altering processes and implies an increase in the rate of energy dissipation, causing in turn an increase in stress upon straining the polymer material further (chapter 6). All these results show that simple physical models supported and tested by results of molecular-dynamics simulations (in which typical physical phenomena observed in real experiments can be reproduced) provide a fruitful approach in understanding glassy material

OPTIma:simplifying calorimetry for proton computed tomography in high proton flux environments

Objective. Proton computed tomography (pCT) offers a potential route to reducing range uncertainties for proton therapy treatment planning, however the current trend towards high current spot scanning treatment systems leads to high proton fluxes which are challenging for existing systems. Here we demonstrate a novel approach to energy reconstruction, referred to as ‘de-averaging’, which allows individual proton energies to be recovered using only a measurement of their integrated energy without the need for spatial information from the calorimeter. Approach. The method is evaluated in the context of the Optimising Proton Therapy through Imaging (OPTIma) system which uses a simple, relatively inexpensive, scintillator-based calorimeter that reports only the integrated energy deposited by all protons within a cyclotron period, alongside a silicon strip based tracking system capable of reconstructing individual protons in a high flux environment. GEANT4 simulations have been performed to examine the performance of such a system at a modern commercial cyclotron facility using a σ ≈ 10 mm beam for currents in the range 10–50 pA at the nozzle. Main results. Apart from low-density lung tissue, a discrepancy of less than 1% on the Relative Stopping Power is found for all other considered tissues when embedded within a 150 mm spherical Perspex phantom in the 10–30 pA current range, and for some tissues even up to 50 pA. Significance. By removing the need for the calorimeter system to provide spatial information, it is hoped that the de-averaging approach can facilitate clinically relevant, cost effective and less complex calorimeter systems for performing high current pCTs

Non-Gaussian nature of glassy dynamics by cage to cage motion

A model based on a single Brownian particle moving in a periodic effective field is used to understand the non-Gaussian dynamics in glassy systems of cage escape and subsequent recaging, often thought to be caused by a heterogeneous glass structure. The results are compared to molecular-dynamics simulations of systems with varying complexity: quasi-two-dimensional colloidlike particles, atactic polystyrene, and a dendritic glass. The model nicely describes generic features of all three topologically different systems, in particular around the maximum of the non-Gaussian parameter. This maximum is a measure for the average distance between cages

DenResCov-19: a deep transfer learning network for robust automatic classification of COVID-19, pneumonia, and tuberculosis from X-rays

The global pandemic of coronavirus disease 2019 (COVID-19) is continuing to have a significant effect on the well-being of the global population, thus increasing the demand for rapid testing, diagnosis, and treatment. As COVID-19 can cause severe pneumonia, early diagnosis is essential for correct treatment, as well as to reduce the stress on the healthcare system. Along with COVID-19, other etiologies of pneumonia and Tuberculosis (TB) constitute additional challenges to the medical system. Pneumonia (viral as well as bacterial) kills about 2 million infants every year and is consistently estimated as one of the most important factor of childhood mortality (according to the World Health Organization). Chest X-ray (CXR) and computed tomography (CT) scans are the primary imaging modalities for diagnosing respiratory diseases. Although CT scans are the gold standard, they are more expensive, time consuming, and are associated with a small but significant dose of radiation. Hence, CXR have become more widespread as a first line investigation. In this regard, the objective of this work is to develop a new deep transfer learning pipeline, named DenResCov-19, to diagnose patients with COVID-19, pneumonia, TB or healthy based on CXR images. The pipeline consists of the existing DenseNet-121 and the ResNet-50 networks. Since the DenseNet and ResNet have orthogonal performances in some instances, in the proposed model we have created an extra layer with convolutional neural network (CNN) blocks to join these two models together to establish superior performance as compared to the two individual networks. This strategy can be applied universally in cases where two competing networks are observed. We have tested the performance of our proposed network on two-class (pneumonia and healthy), three-class (COVID-19 positive, healthy, and pneumonia), as well as four-class (COVID-19 positive, healthy, TB, and pneumonia) classification problems. We have validated that our proposed network has been able to successfully classify these lung-diseases on our four datasets and this is one of our novel findings. In particular, the AUC-ROC are 99.60, 96.51, 93.70, 96.40% and the F1 values are 98.21, 87.29, 76.09, 83.17% on our Dataset X-Ray 1, 2, 3, and 4 (DXR1, DXR2, DXR3, DXR4), respectively

Turbulence anisotropy and the SO(3) description

We study strongly turbulent windtunnel flows with controlled anisotropy. Using a recent formalism based on angular momentum and the irreducible representations of the SO(3) rotation group, we attempt to extract this anisotropy from the angular dependence of second-order structure functions. Our instrumentation allows a measurement of both the separation and the angle dependence of the structure function. In axisymmetric turbulence which has a weak anisotropy, this more extended information produces ambiguous results. In more strongly anisotropic shear turbulence, the SO(3) description enables one to find the anisotropy scaling exponent. The key quality of the SO(3) description is that structure functions are a mixture of algebraic functions of the scale with exponents ordered such that the contribution of anisotropies diminishes at small scales. However, we find that in third-order structure functions of homogeneous shear turbulence the anisotropic contribution is always large and of the same order of magnitude as the isotropic part. Our results concern the minimum instrumentation needed to determine the parameters of the SO(3) description, and raise several questions about its ability to describe the angle dependence of high-order structure functions

Mechanical Properties of Glassy Polyethylene Nanofibers via Molecular Dynamics Simulations

The extent to which the intrinsic mechanical properties of polymer fibers depend on physical size has been a matter of dispute that is relevant to most nanofiber applications. Here, we report the elastic and plastic properties determined from molecular dynamics simulations of amorphous, glassy polymer nanofibers with diameter ranging from 3.7 to 17.7 nm. We find that, for a given temperature, the Young’s elastic modulus E decreases with fiber radius and can be as much as 52% lower than that of the corresponding bulk material. Poisson’s ratio ν of the polymer comprising these nanofibers was found to decrease from a value of 0.3 to 0.1 with decreasing fiber radius. Our findings also indicate that a small but finite stress exists on the simulated nanofibers prior to elongation, attributable to surface tension. When strained uniaxially up to a tensile strain of ε = 0.2 over the range of strain rates and temperatures considered, the nanofibers exhibit a yield stress σy between 40 and 72 MPa, which is not strongly dependent on fiber radius; this yield stress is approximately half that of the same polyethylene simulated in the amorphous bulk.DuPont MIT AllianceDuPont (Firm) (Young Professor Award

NaCl nucleation from brine in seeded simulations: Sources of uncertainty in rate estimates

This work reexamines seeded simulation results for NaCl nucleation from a supersaturated aqueous solution at 298.15 K and 1 bar pressure. We present a linear regression approach for analyzing seeded simulation data that provides both nucleation rates and uncertainty estimates. Our results show that rates obtained from seeded simulations rely critically on a precise driving force for the model system. The driving force vs. solute concentration curve need not exactly reproduce that of the real system, but it should accurately describe the thermodynamic properties of the model system. We also show that rate estimates depend strongly on the nucleus size metric. We show that the rate estimates systematically increase as more stringent local order parameters are used to count members of a cluster and provide tentative suggestions for appropriate clustering criteria

Local dynamics and deformation of glass-forming polymers : modelling and atomistic simulations

The research described in the present thesis is about glassy phenomena and mechanical properties in vitrifiable polymer materials. Glasses are solid materials, but, in contrast to crystals, the structure is disordered. Polymers are macromolecular chains formed by covalently linking a very large number of repeating molecular building blocks or monomers. Polymeric materials are easy to reshape and reuse. Also they are lightweight and often transparent. These characteristics make them ideal materials for commodity products such as compact discs, safety helmets, or vandal-proof glazing. Some glassy polymers are also biocompatible, so that they can be used in medical applications. For a successful usage of polymer glasses it is necessary to understand and predict their behaviour under various circumstances. Although many new insights have been acquired over the last decades still a lot of questions remain open. Upon vitrifying a polymer melt the relaxation times and the viscosity increase dramatically. Accompanied with this increase various glassy phenomena are observed — in particular dynamical heterogeneities and non-Gaussian displacements of particles. The comprehension of the striking viscosity increase and the two phenomena mentioned above is still far from complete. During the straining of a polymer glass typical mechanical characteristics are observed, of which the magnitude can vary enormously between different types of polymers. A wellknown example of a polymer glass is atactic polystyrene. In its glassy state polystyrene is usually found to be very brittle. Within a few percent of elongation the material breaks. This behaviour is caused by a relatively high yield tooth in combination with a relatively low strain-hardening modulus. Other polymers, such as bisphenol-A polycarbonate, show a tough response; a test bar can easily be extended to twice its original length. In spite of much study, the physical (molecular) origin of this difference in mechanical behaviour is still not clear. Below the glass transition rubber-elasticity theory appears to be invalid, as it fails to explain the observation that the strain-hardening modulus of polystyrene in its glassy phase is about two orders of magnitude higher than its modulus in the rubbery state. Our main goals are to acquire a better understanding at the molecular scale of heterogeneous and non-Gaussian dynamics and mechanical deformation of glassy polymers and to differentiate chemistry-specific from more universal physical properties. These goals are achieved by carrying out molecular-dynamics simulations on glass-forming systems. In addition, the results are elucidated by the usage of simple physical models. The simulations consist of solving the equations of Newton, a coupled set of differential equations with a given force field and initial conditions. The force field describes the interactions between the various particles. As the main interest is in glassy polymers, most simulations are done for a united-atom model of polystyrene. In the simulation run several characteristics of the glass transition are identified. As is typical for other vitreous systems as well, anomalous, non-Gaussian displacements play an important role near the glass transition for polystyrene; the same observation has been made for a dendritic melt and a colloid-like system. For all these systems of different architecture we have described some essential features of this non-Gaussian behaviour with a simple one-particle model in an effective field. The non-Gaussian behaviour is mainly caused by the cage-to-cage motion of the constituent particles, whereby the cage is formed by interactions with neighbouring particles. By means of the model the height of the so-called non-Gaussian parameter can be interpreted as a measure for the ratio of the root-mean-square displacement within the cage and the effective jump length between cages, without the assumption of any heterogeneity of glassy dynamics in the sense of sitespecific relaxation times. The maximum of the non-Gaussian parameter occurs in each case at the crossover from the cage regime to the (sub)diffusive regime and is connected to the cage-escape time. For the colloid-like system also the shape of the time-dependent non-Gaussian parameter is described well by the model (chapter 3). Dynamical heterogeneity, a phenomenon observed in many experiments on glasses, is also found in the simulation result of the polystyrene phenyl-ring-flip movement (to which the mechanical gamma relaxation is ascribed). This means that some phenyl rings behave very differently than others within a typical simulation run. Different relaxation times and activation enthalpies associated with the flip are determined using various methods. A particular result of the study of the phenyl flip is that an enthalpy barrier determined solely from structural properties is in accordance with an activation enthalpy acquired by analyzing the dynamics of the phenyl rings, even in the presence of dynamical heterogeneity. The heterogeneity arises because of the following mechanism. The conformation of the backbone determines to a large extent the barrier of the phenyl-ring flip. Eventually the relaxation of the backbone is becoming so slow upon cooling down that the phenyl ring is unable to access the conformation-dependent state with the lowest flip barrier within the corresponding barrier-jump time. The phenyl rings are trapped instead in various other states with accompanying different energy barriers. These states are available because of the disordered nature of the material. The mechanism just described for the heterogeneous dynamics in the phenyl-ring flip movement becomes stronger upon cooling down towards the glass transition; eventually the relaxation becomes more Arrhenius-like below the glass transition temperature because only the fastest phenyl flips occur within the accessible observation time (chapter 4). By doing uniaxial-stress extension and compression simulations the stress-strain relation of polystyrene has been measured under various conditions. Although the cooling and deformation velocities in the simulations differ many orders of magnitude from their values in usual experiments, the characteristic features of the experimental stress-strain relation are well reproduced, which allows one to study the origin of the yield tooth and strain hardening. It is observed that the strain-hardening modulus increases with increasing pressure, an effect not described by rubber-elasticity theory. Also it is observed that the thermal history is not completely erased by the mechanical deformation. The picture arising from this study is that the yield peak in polystyrene is mostly mediated by interchain energetic interactions. A net debonding of these interactions is likely causing this yield peak and the subsequent strain softening. The positiveness of the strain-hardening modulus in polystyrene is mainly due to intrachain interactions (chapter 5). From our comparative study of polystyrene and polycarbonate it can be concluded that strain hardening in polymer glasses such as these two polymers is likely caused mainly by the following mechanism. During uniaxial extension a glassy chain adopts a more stretched and hence more inflexible state, also at a local scale. Due to interactions with other particles non-affine displacements take place. The non-affine response is stronger at shorter length scales, but as the deformation proceeds and the effective flexibility decreases also longer length scales are affected. This is accompanied with more bond-altering processes and implies an increase in the rate of energy dissipation, causing in turn an increase in stress upon straining the polymer material further (chapter 6). All these results show that simple physical models supported and tested by results of molecular-dynamics simulations (in which typical physical phenomena observed in real experiments can be reproduced) provide a fruitful approach in understanding glassy material