Kimberley McAuley

Queen's University | QueensU · Department of Chemical Engineering

A dynamic model is proposed for photopolymerization of 1,6-hexane-diol diacrylate (HDDA) with bifunctional initiator bis-acylphosphine oxide (BAPO) in the presence of oxygen. This partial-differential-equation (PDE) model predicts time- and spatially-varying vinyl-group conversion as well as concentrations of monomer, initiator, oxygen, and seven t...

A two-dimensional mathematical model was developed to simulate naphtha reforming in a series of three industrial continuous catalytic regeneration (CCR) reactors. Discretization of the resulting partial differential equations (PDEs) in the vertical direction and a coordinate transformation in the radial direction were performed to make the model so...

A methodology is proposed to aid parameter estimation in fundamental models of pharmaceutical processes. This methodology addresses situations with insufficient data to reliably estimate all parameters, when the estimation is complicated by uncertain independent variables. The proposed method uses an augmented sensitivity matrix to rank the combine...

A review of uncertainty quantification techniques is provided for a variety of situations involving uncertainties in model inputs (independent variables). The situations of interest are divided into three categories: (i) when model prediction uncertainties are quantified based on uncertainties in uncertain inputs, (ii) when parameter estimate uncer...

A methodology is proposed to aid parameter estimation in fundamental models of pharmaceutical processes. This methodology addresses situations with insufficient data to reliably estimate all parameters, when the estimation is complicated by uncertain independent variables. The proposed method uses an augmented sensitivity matrix to rank the combine...

Error‐in‐variables model (EVM) methods are used for parameter estimation when independent variables are uncertain. During EVM parameter estimation, output measurement variances are required as weighting factors in the objective function. These variances can be estimated based on data from replicate experiments. However, conducting replicates is com...

Models are developed for gas‐phase ethylene/1‐hexene copolymerization using a 3‐site hafnocene catalyst. The models accurately predict joint molecular weight distribution and copolymer composition data for 15 semi‐batch lab‐scale copolymerization runs and 6 steady‐state pilot‐plant copolymerization runs, respectively. Kinetic rate constants and act...

A 3‐site metallocene catalyst is used in a gas‐phase semi‐batch reactor to produce ethylene/hexene copolymers. At the end of each batch, polyethylene (PE) is collected and analyzed to determine the 13C‐NMR triad sequence distribution. Joint molecular weight (MW) and composition distribution data are obtained using GPC‐IR. Data from 10 experimental...

Error-in-variables model (EVM) methods are used for parameter estimation when independent variables are uncertain. During EVM parameter estimation, output measurement variances are required as weighting factors in the objective function. These variances can be estimated based on data from replicate experiments. However, conducting replicates is com...

A dynamic model is proposed for photopolymerization of 1,6‐hexanediol diacrylate (HDDA) with the bifunctional initiator bis‐acylphosphine oxide (BAPO) in the presence of oxygen. The model tracks time‐varying concentrations of monomer, oxygen, and different radical end groups using ordinary differential equations. An analytical expression is derived...

A dynamic model is proposed for photopolymerization of 1,6-hexanediol diacrylate (HDDA) using bifunctional initiator bis-acylphosphine oxide (BAPO). The proposed model accounts for branching, backbiting and cyclization reactions, and for diffusion-dependent reaction rates during photopolymerization. The proposed model contains 40 adjustable kinetic...

A dynamic model is developed for gas‐phase ethylene/1‐hexene polymerization with a three‐site hafnocene catalyst. The model accurately predicts molecular weight and comonomer composition distributions for fifteen lab‐scale copolymerization runs performed at different temperatures. The experimental runs used to fit this model were performed at tempe...

Updated methods are proposed for estimating model parameters and error-covariance matrices in stochastic differential equation (SDE) models. New expressions, based on the LAMLE (Laplace Approximation Maximum Likelihood Estimation) and LAB (Laplace Approximation Bayesian) SDE estimation methods are derived so that LAMLE and LAB can be used for syste...

Error‐in‐variables model (EVM) methods require information about variances of input and output measured variables when estimating the parameters in mathematical models for chemical processes. In EVM, using replicate experiments for estimating output measurement variances is complicated because true values of inputs may be different when multiple at...

Error-in-variables model (EVM) methods require information about input and output measurement variances when estimating model parameters. In EVM, using replicate experiments for estimating output measurement variances is complicated, because true values of inputs may be different when multiple attempts are made to repeat an experiment. To address t...

The controlled reactive degradation of polypropylene (CPP) in a twin-screw extruder has been investigated from the perspective of tacticity. CPP is initiated by the decomposition of a peroxide producing radicals that abstract hydrogen from the chain backbone creating tertiary radicals. Since C atoms with tertiary radicals have no longer sp³ configu...

Sequential Model‐Based Design of Experiments (MDBOE) accounts for information from previous experiments when selecting conditions for new experiments. In the current study, sequential MBDOE is used to select operating conditions for experiments in a batch‐reactor that produces bio‐based polytrimethylene ether glycol (PO3G). These Bayesian A‐optimal...

To understand why some parameters are difficult to estimate in polymerization models, a new diagnostic methodology is proposed. This method is then used to investigate whether parameter estimability difficulties arise from the small influence of certain parameters on model predictions or from correlated effects with other parameters. The proposed m...

Sequential model-based design of experiments (MBDOE) is used to select operating conditions for new experiments in a batch-reactor that produces bio-based poly(trimethylene) ether glycol (PO3G). These Bayesian A-optimal experiments are designed to obtain improved estimates of the 70 fundamental-model parameter estimates, while accounting for the mo...

A dynamic model is developed to predict detailed chain‐length and comonomer incorporation behavior during gas‐phase ethylene/hexene copolymerization using a supported hafnocene catalyst. The multi‐site catalyst results in a copolymer with a broad orthogonal composition distribution (BOCD) where the high molecular‐weight tail has high hexene incorpo...

Many model‐based online process monitoring and control applications rely on state estimation techniques that use noisy process data to update states, thereby ensuring that imperfect model predictions are consistent with process behavior. Techniques for tuning state estimators are reviewed, and their effectiveness and limitations are summarized in t...

A comprehensive dataset containing 1779 measured values, collected from seven experimental runs, is used for parameter estimation in a model for batch polycondensation of biobased 1,3‐propanediol. The data are from dynamic experiments conducted between 160 and 180 °C using a super‐acid catalyst with concentrations between 0.1 and 0.25 wt%. The mode...

Sequential model‐based design of experiments (MBDoE) uses information from previous experiments to select new experimental conditions. Computation of MBDoE objective functions can be impossible due to a non‐invertible Fisher Information Matrix (FIM). Previously, we evaluated a leave‐out (LO) approach that designed experiments by removing problemati...

A comprehensive model is developed for polycondensation of 1,3‐propanediol in a batch reactor. The model accounts for formation, consumption, and evaporation of cyclic oligomers. Measurements of species and end‐group concentrations in the reactor and collected condensate are used to estimate 36 kinetic and mass‐transfer parameters. The model and pa...

A dynamic mathematical model is developed for production of Cerenol polyether from 1,3‐propanediol in a batch reactor system. The model accounts for polycondensation reactions and side reactions in the liquid phase and for mass transfer of volatile species to the vapor. Parameters are estimated using measured liquid‐phase concentrations of monomer,...

Nylon 6 and 6,6 literature data are collected over a wide range of water concentrations and temperatures (0 ≤ [W]0 ≤ 40.8 wt%, 200 ≤ T ≤300 °C) and used to fit parameters in an updated batch reactor model. The resulting copolymerization model uses side reactions to account for the complex influence of water on kinetics and reaction equilibria. The...

An overview is provided of commercially-available biolubricants, along with the manufacturing technologies used to make them, and emerging production technologies that show promise. Ester-based biolubricants enjoy the most widespread commercial use, even though complex chemical modifications are required to improve their physicochemical properties....

Some thermodynamic and mechanical properties of a polyolefin, such as the melting temperature and the rigidity, are dependent on the nature of its sequence distribution. Accurate modeling of sequence length distribution (SLD) is important in precisely tuning and optimizing the properties of polymers produced. In this paper, we proposed a model to p...

The development of a model for predicting coke formation in an industrial ethylene cracking furnace is described. Expressions for predicting the rates of catalytic and pyrolytic coke formation are developed and a differential equation is derived to predict changes in coke thickness with time and position. An expression is developed to account for a...

Sequential model-based A- and V-optimal experimental designs are known to be effective for maximizing the information content of data, leading to reliable parameter estimates and model predictions. A- and V-optimal designs require inversion of the Fisher Information Matrix (FIM), which may be noninvertible especially for fundamental models with man...

Front Cover: In this image, the collaboration between mechanistic modeling and process reaction conditions that results in targeted polymeric structure and morphology, the intertwined themes within this issue, is described. The molecular structures shown highlight compositions of several of the included manuscripts; PSA ter‐polymers, Nylon 6, branc...

Nylon 6 and nylon 6,6 reaction equilibria depend in a complex way on water concentration and temperature. For example, data sets from six research groups reveal that the apparent equilibrium constant for polycondensation increases with water at low water concentrations, reaches a maximum, and then decreases as the water concentration rises further....

Sequential model-based optimal design of experiments (e.g., A-, D-, and E- optimal design) is a well-known technique for selecting experimental conditions that lead to informative data for obtaining reliable parameter estimates and model predictions. An important computational step for selecting new model-based experiments is to compute the inverse...

An Approximate Bayesian Expectation Maximization (ABEM) methodology and a Laplace Approximation Bayesian (LAB) methodology are developed for estimating parameters in nonlinear stochastic differential equation (SDE) models of chemical processes. These new methodologies are more powerful than previous maximum-likelihood methodologies for SDEs because...

A dynamic model is developed to simulate arborescent polyisobutylene (arbPIB) production via self‐condensing vinyl copolymerization in a continuous stirred tank reactor (CSTR). A kinetic Monte Carlo algorithm is proposed that discretizes inflow and outflow separately from reaction steps. The model predicts dynamic changes in monomer and inimer (IM)...

A continuous stirred‐tank reactor (CSTR) model is developed to produce arborescent polyisobutylene via carbocationic copolymerization of isobutylene and inimer using multidimensional method of moments. The model is used to predict dynamic changes in average branching level (Bkin) and number‐average and weight‐average molecular weights (). Simulatio...

A methodology is proposed for parameter ranking and parameter subset selection for nonlinear ordinary differential equation (ODE) models with time delay, in which delay is treated as an unknown model parameter. The methodology builds on earlier algorithms for ranking model parameters in systems without time delay (Yao et al., 2003; Thompson et al.,...

A model is used to simulate batch copolymerization of caprolactam with hexamethylene diamine (HMD) and adipic acid (ADA) to produce nylon 6/6,6. Four different recipes are considered: a recipe containing caprolactam and an aqueous solution of HMD and ADA, a recipe containing caprolactam and dry HMD/ADA salt, and two recipes with a portion of the ca...

A deterministic modelling approach is developed to predict the internal structure of gradient copolymer chains. A key innovation of the modelling approach is the introduction of a positional variable that gives direct access to quantitative gradient characteristics: the ensemble average composition and the gradient deviation. This positional variab...

A model is developed for hydrolytic copolymerization of caprolactam with hexamethylene diamine (HMD) and adipic acid (ADA) in a batch reactor to produce nylon 6/6,6 copolymer. The reaction mechanism includes hydrolysis of caprolactam and cyclic dimer, polycondensation, polyaddition, transamidation, and ring formation via end biting and back biting....

Designed experiments were performed to produce empirical models for the dose sensitivity, initial absorbance, and dose-rate dependence respectively for leucocrystal violet (LCV) micelle gel dosimeters containing cetyltrimethylammonium bromide (CTAB) and 2,2,2-trichloroethanol (TCE). Previous gels of this type showed dose-rate dependent behaviour, p...

The development of a relatively simple mechanistic model for an industrial ethylene cracking furnace is described, including the estimation of selected model parameters to improve model predictions. Energy balance equations are developed to account for radiative, conductive, and convective heat transfer in the radiant section and for convection and...

A Bayesian algorithm is developed for estimating measurement noise variances, disturbance intensities and model parameters in nonlinear stochastic differential equation (SDE) models of interest to chemical engineers. The proposed Bayesian algorithm uses prior knowledge about parameters and builds on the Laplace Approximation Maximum Likelihood Esti...

A model for industrial top-fired dry reforming of methane (DRM) and for combined dry reforming and steam reforming of methane was developed for the first time. The model calculates and gives predictions on the temperature profiles for fuel gas, tube walls and process gas, as well as the process gas composition profiles over the length of the tubes....

This paper investigates the novel use of elemental sulfur as a fuel in a combined cycle power plant wherein the sulfur is oxidized in the combustion chamber to produce work from a gas turbine. The produced sulfur dioxide is then reacted with calcite to produce anhydrite (CaSO4) in a Flue Gas Desulfurization unit. The desulfurization reaction is exo...

A mathematical model is developed for the arborescent poly­isobutylene system in a batch reactor, using multidimensional method of moments, to predict the concentrations of monomer and inimer as well as number and weight average molecular weight. This model is significantly efficient in computation, making parameter estimation practical. Simulation...

A point-of-Care (POC) pCO2 device is a small electrochemical sensor for determining the partial pressure of dissolved carbon dioxide in blood samples from patients. A mathematical model is developed to predict the voltage response in a pCO2 sensor when it is subjected to different CO2 concentrations in a calibration fluid and in blood samples or co...

An advanced Monte Carlo (MC) method is developed, using weight-based selection of polymer chains, to predict the molecular weight distribution (MWD) and branching level for arborescent polyisobutylene (arbPIB) at the end of a batch reaction. This new weight-based MC method uses differential equations and random numbers to determine the detailed str...

A Bayesian algorithm is developed for estimating measurement noise variances, disturbance intensities and model parameters in nonlinear stochastic differential equation (SDE) models of interest to chemical engineers. The proposed Bayesian algorithm uses prior knowledge about parameters and builds on the Laplace Approximation Maximum Likelihood Esti...

Two approaches are developed to rank and select model parameters for estimation in complex models when data are limited, the Fisher information matrix (FIM) is noninvertible, and accurate predictions are desired at key operating conditions. These approaches are evaluated using synthetic data sets in a linear regression example to examine the influe...

A mathematical model is developed to simulate the production of bio-based polytrimethylene ether glycol (PO3G) using 1,3-propanediol. The effect of super-acid catalyst is accounted for in the model, as is mass transfer of small species (water, monomer, and propanal) and linear oligomers (dimer to heptamer). This model correctly predicts dynamic tre...

Radiochromic leuco crystal violet (LCV) micelle gel dosimeters are promising three-dimensional radiation dosimeters because of their spatial stability and suitability for optical readout. The effects of surfactant type and surfactant concentration on dose sensitivity of LCV micelle gels are tested, demonstrating that dose sensitivity and initial co...

In this study, recipe optimization of Leuco Crystal Violet (LCV) micelle gels made with the surfactant Cetyl Trimethyl Ammonium Bromide (CTAB) and the chemical sensitizer 2,2,2-trichloroethanol (TCE) was aided by a two-level three-factor designed experiment. The optimized recipe contains 0.75 mM LCV, 17.0 mM CTAB, 120 mM TCE, 25.0 mM tri-chloro ace...

The effects of the various components of leuco crystal violet (LCV) micelle gels on dose sensitivity and initial colour are tested. Dose sensitivity and gel turbidity are influenced by tri-chloro acetic acid (TCAA) concentration, with the highest dose sensitivity obtained at ~21.5 mM. Increasing Triton x-100 (Txl00) concentration improved dose sens...

Designed experiments and empirical models are used to optimize a Leuco Crystal Violet (LCV) micelle gel recipe to improve dose sensitivity and initial colour. The optimized recipe contains 0.75 mM LCV, 17.0 mM Cetyl Trimethyl Ammonium Bromide (CTAB), 120 mM 2,2,2-trichloroethanol (TCE), 25.0 mM tri-chloro acetic acid (TCAA), 4 wt% gelatin and ~96 w...

A mathematical model is developed for estimating kinetic parameters that influence the production of arborescent polyisobutylene via carbocationic copolymerization of inimer and isobutylene. Six different propagation rate constants arise due to the two types of vinyl groups and three types of carbocations. These six parameters are estimated using p...

An improved approximate maximum likelihood algorithm is developed for estimating measurement noise variances along with model parameters and disturbance intensities in nonlinear stochastic differential equation (SDE) models. This algorithm uses a Laplace approximation and B-spline basis functions for approximating the likelihood function of the par...

A mathematical model was developed for the multi-tank stripping section of industrial EPDM (Ethylene Propylene Diene Monomer) rubber processes. Experiments were conducted to determine Henry's law coefficients and diffusivities for hexane solvent and 5-ethylidene-2-norbornene (ENB) comonomer in EPDM particles. Equivalent radii for diffusion within t...

A mathematical model is developed to simulate condensation polymerization of 1,3-propanediol to produce polytrimethylene glycol (PO3G) polyether. The model includes improved mass-transfer expressions that account for nonzero concentrations of water and monomer inside nitrogen bubbles and for increasing overall bubble surface area due to increases i...

Stochastic terms are included in fundamental dynamic models of chemical processes to account for disturbances, input uncertainties and model mismatch. The resulting equations are called stochastic differential equations (SDEs). An approximate expectation maximisation (AEM) algorithm using B-splines is developed for estimating parameters in SDE mode...

An improved approximate maximum likelihood algorithm is developed for estimating measurement noise variances along with model parameters and disturbance intensities in nonlinear stochastic differential equation (SDE) models. This algorithm uses a Laplace approximation and B-spline basis functions for approximating the likelihood function of the par...

A mean-squared-error-based forward selection methodology is proposed for simultaneous parameter ranking and selection based on the critical ratio rCCW [Eghtesadi, Z.; Wu, S.; McAuley, K. B. Ind. Eng. Chem. Res. 2013, 52, 12297]. This new technique employs information in the available data set and the operating region of interest to determine the be...

An advanced Monte Carlo (MC) model is developed to predict the molecular weight distribution and branching level for arborescent polyisobutylene produced in a batch reactor via carbocationic copolymerization of isobutylene and an inimer. This new MC model uses differential equations and random numbers to determine the detailed structure of dendriti...

An algorithm is proposed for simultaneous estimation of model parameters, process disturbance intensities, and measurement noise variances for nonlinear dynamic systems that are described by stochastic differential equations. The proposed fully-Laplace approximation expectation maximization (FLAEM) algorithm uses an iterative approach wherein, in t...

A Monte Carlo (MC) model is developed to predict molecular weight distribution and branching during the production of arborescent polyisobutylene. The model describes self-condensing vinyl copolymerization (SCVCP) of isobutylene and inimer via living carbocationic polymerization. Six different propagation rate constants are required to account for...

Styrene polymerization literature is reviewed and a model with dicumyl peroxide and benzoyl peroxide initiators is developed. Nine parameters are selected for estimation using statistical methods that account for the influence of parameters on model predictions, correlated effects of parameters and uncertainties of initial literature values. Update...

A mathematical model is developed for condensation polymerization of 1,3-propanediol to produce Cerenol polyether. The effect of the super-acid catalyst is considered explicitly in the proposed reaction mechanism. The main reactions include protonation/deprotonation equilibrium, polycondensation, carbocation formation, end degradation, and transeth...

Emulsified diacetylenes as reporter molecules in micelle gel dosimeters were evaluated in the current article. It was observed that gels containing PCDA emulsified in deionized water using SDS changed from colourless to blue upon irradiation. Unfortunately, recipes that led to turbid gels resulted in a colour change, but transparent gels did not ch...

Fundamental chemical and physical phenomena that occur in Fricke gel dosimeters, polymer gel dosimeters, micelle gel dosimeters and genipin gel dosimeters are discussed. Fricke gel dosimeters are effective even though their radiation sensitivity depends on oxygen concentration. Oxygen contamination can cause severe problems in polymer gel dosimeter...

A novel model describes copolymerization of isobutylene and inimer (initiator-monomer) via living carbocationic polymerization. Six different propagation rate constants and two types of equilibrium reactions are considered. Simplifying assumptions are made to enable implementation in PREDICI, so that the molecular weight distribution (MWD) could be...

In this paper, we compare Kalman update based filters with particle filters using simulations on polymerization processes. In particular, we compare the unscented Kalman filter (UKF) and the particle filter (PF) for the case of significant plant–model mismatch. The sequential importance resampling particle filter is shown to be less robust than the...

A methodology is proposed for selecting parameters to estimate when data are too limited to estimate all kinetic, thermodynamic, and mass-transfer parameters in complex models of chemical processes. When data are sparse, noisy, or correlated, it is often better to obtain predictions from a simplified model (SM) where a few parameters have been remo...

Radiochromic micelle gel dosimeters are promising for three-dimensional (3D) radiation dosimetry because they can be read out by optical CT techniques and they have superior spatial stability compared to polymer and Fricke gel dosimeters. This study evaluates the use of diacetylenes as reporter molecules in micelle gel dosimeters. Several gels cont...

We introduce a method to estimate parameters and states from a differential equation model while enforcing interpretability constraints such as monotone or non‐negative states. We motivate the methodology using a real data chemical engineering example and show that a variety of restrictive constraints from earlier analyses do not address the proble...

Engineers who develop fundamental models for chemical processes are often unable to estimate all of the parameters, especially when available data are limited or noisy. In these situations, modelers may decide to select only a subset of the parameters for estimation. An orthogonalization algorithm combined with a mean squared error (MSE) based sele...

Chemical engineers who develop fundamental models often have difficulties estimating all model parameters due to problems with parameter identifiability and estimability. These two concepts are reviewed, as are techniques for assessing identifiability and estimability. When some parameters are not estimable from the data, modellers must decide whet...

A model is developed to predict rates of undesirable reactions in the low-moisture, high-temperature finishing stage of nylon 66 production. The model contains 56 unknown parameters and initial conditions, which are ranked based on their influence on model predictions, correlation with other parameters and uncertainty in their initial guesses. A me...

A model is developed to simulate the response of polyacrylamide gel (PAG) dosimeters to single spherical brachytherapy seeds. The model predicts the amount of polymer formed and crosslink density as a function of radial distance and time, using either a HDR Ir192 seed or a LDR I125 seed. Results indicate that PAG dosimeters should provide accurate...

A model is developed to describe thermally-initiated polymerization of styrene between 100 and 170 degrees C. The model accounts for generation and consumption of styrene adduct. Chain transfer to adduct is the only transfer reaction used. Autoacceleration is modeled using the break-point method of Hui and Hamielec. Using formal ranking and paramet...

A dynamic PDE model is developed to simulate the effects of radiation depth doses on polymer formation in polyacrylamide gel dosimeters. Depth doses are simulated using different types of radiation including Co60 g and 6 and 15 MV X-ray photon beams, along with 6, 9, 12, 16 and 20 MeV electron beams. Effects of monomer diffusion (edge enhancement)...

A mathematical model of an industrial steam-methane reformer (SMR) is developed for use in monitoring tube-wall temperatures. The model calculates temperature profiles for the outer-tube wall, inner-tube wall, furnace gas and process gas. Inputs are the reformer inlet-stream conditions, the furnace geometry and material properties of the furnace an...

Performance of in vitro diagnostics biosensors may change over lifetime, particularly if environmental storage conditions such as temperature are not controlled. Biosensors are composed of diverse multiple components such as salts, polymers and biological components which may be differentially impacted by chemical and physical transformations induc...

Simplified models (SMs) with a reduced set of parameters are used in many practical situations, especially when the available data for parameter estimation are limited. A variety of candidate models are often considered during the model formulation, simplification, and parameter estimation processes. We propose a new criterion to help modellers sel...

This study reports new N-isopropylacrylamide (NIPAM) polymer gel recipes with increased dose sensitivity and improved dose resolution for x-ray CT readout. NIPAM can be used to increase the solubility of N, N'-methylenebisacrylamide (Bis) in aqueous solutions from approximately 3% to 5.5% by weight, enabling the manufacture of dosimeters containing...

This paper explores the combination of cone beam optical computed tomography with an N-isopropylacrylamide (NIPAM)-based polymer gel dosimeter for three-dimensional dose imaging of small field deliveries. Initial investigations indicate that cone beam optical imaging of polymer gels is complicated by scattered stray light perturbation. This can lea...

Mean-squared error (MSE) is used to analyse nine commonly used model-selection criteria (MSC) for their performance when selecting simplified models (SMs). Expressions are derived to enable exact calculations of the probability that a particular MSC will select a SM. For several common MSC, the relative propensities to select SMs are independent of...

Parameter estimation in complex mathematical models is difficult, especially when there are too many unknown parameters to estimate, and the available data for parameter estimation are limited. Estimability analysis ranks parameters from most estimable to least estimable based on the model structure, uncertainties in initial parameter guesses, meas...

Polymer gels are chemical dosimeters based on dose dependent radiation-induced polymerization and cross-linking of monomers in an irradiated volume. The changes are spatially localized in the volume by incorporating the initial monomers in an aqueous gel matrix in the dosimeter and can be probed by various imaging techniques such as magnetic resona...

A dynamic partial differential equation (PDE) model is used to simulate effects of a single Ir192 brachytherapy seed on the amount and composition of polymer formed during polyacrylamide gel (PAG) dosimetry. Simulations are conducted for a point-source brachytherapy seed placed at the center of a 6%T 50% C anoxic PAG phantom. The seed is removed af...

A dynamic partial differential equation (PDE) model is used to simulate the effects of radiation depth-doses on polymer formation in Polyacrylamide Gel (PAG) dosimeters. Depth-doses are simulated using different types of radiation including Co60 gamma and 6 and 15 MV X-ray photon beams, along with 6, 9, 12, 16 and 20 MeV electron beams. Effects of...

We report on investigations aimed at increasing the dose response sensitivity and resolution in x-ray CT imaging of polymer gel dosimeters (PGD). We incorporate isopropanol as co-solvent into the gel formulation and show that this incorporation increases dose sensitivity and dose resolution of x-ray CT imaged gel dosimeters. These gels are reproduc...

A primary limitation of current x-ray CT polymer gel dosimetry is the low contrast, and hence poor dose resolution, of dose images produced by the system. The low contrast is largely due to the low-dose sensitivity of current formulations of polymer gel for x-ray CT imaging. This study reports on the investigation of new dosimeter formulations with...