Brittany Hoard | Western Governors University (original) (raw)
Thesis Chapters by Brittany Hoard
The study addresses the problem of the inadequacy of conventional software testing methods to det... more The study addresses the problem of the inadequacy of conventional software testing methods to detect all software defects. This problem affects software users and researchers due to poor software performance, reduced precision or accuracy of software output, and retractions of research publications. Detecting software defects may also be challenging due to the oracle problem. Existing research supports the metamorphic testing method's effectiveness for handling the oracle problem and finding software defects that conventional testing methods cannot detect. The research questions ask about the relationships among the use and acceptance of the metamorphic testing method among open-source developers and the constructs of performance expectancy and effort expectancy. The study's purpose was to examine these relationships. Another objective of the study was to understand how the variables of age, gender, and experience moderate these relationships. The guiding theoretical framework of the study was the unified theory of acceptance and use of technology. In this study, a quantitative methodology with a correlational design was employed. The participants were contributors to open-source software projects contained in the GitHub “Software in science” collection. The data was collected via an online survey instrument. The data were analyzed using Spearman’s rank-order correlation tests and moderated multiple regression analysis. Moderate to strong positive relationships were found between both the performance expectancy and effort expectancy and the acceptance and use of metamorphic testing. This finding suggests that increasing the extent to which developers believe that metamorphic testing will improve their job performance and improving its ease of use will increase the adoption of metamorphic testing. The creation of interventions to educate developers on the use of metamorphic testing is recommended. The study results support the applicability of the unified theory of acceptance and use of technology to software testing methods. Future research could involve studying the relationship between metamorphic testing adoption and other factors, such as social influence and facilitating conditions.
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The allergic response is produced by the release of immune mediators by mast cells and basophils.... more The allergic response is produced by the release of immune mediators by mast cells and basophils. This process, in turn, is initiated by the aggregation of antigens and IgE-FceRI antibody-receptor complexes. Computational modeling of antibody-antigen aggregate formation as well as the size and structure of these aggregates is an important tool for greater understanding of the allergic response. In addition, the incorporation of molecular geometry into aggregation models can more accurately capture details of the aggregation process, and may lead to insights into how geometry affects aggregate formation. However, it is challenging to simulate aggregation due to the computational cost of simulating large molecules. Methods to geometrically model antibody aggregation inspired by rigid body robotic motion simulations have previously been developed; however, high computational cost mandates that the resolution of the 3D molecular models be reduced, which affects the results of the simulation. Rule-based modeling can be used to model aggregation with low computational cost, but traditional rule-based modeling approaches do not include details of molecular geometry.
In this work, we propose a novel implementation of rule-based modeling that encodes details of molecular geometry into the rules and the binding rate constant associated with each rule. We demonstrate how the set of rules is constructed according to the curvature of the molecule. We then perform a study of antigen-antibody aggregation using our proposed method combined with a previously developed 3D rigid-body Monte Carlo simulation. We first simulate the binding of IgE antibodies bound to cell surface receptors FceRI to various binding regions of the allergen Pen a 1 using the aforementioned Monte Carlo simulation, and we analyze the distribution of the sizes of the aggregates that form during the simulation. Then, using our novel rule-based approach, we optimize a rule-based model according to the geometry of the Pen a 1 molecule and the data from the Monte Carlo simulation. In particular, we use the distances between the binding regions of the Pen a 1 molecule to optimize the rules and associated binding rate constants. The optimized rule-based models provide information about the average steric hindrance between binding regions and
the probability that IgE-FceRI receptor complexes will bind to these regions. In addition, the optimized rule-based models provide a means of quantifying the variation in aggregate size distribution that results from differences in molecular geometry. We perform this procedure for seven resolutions and three molecular conformations of Pen a 1. We then analyze the impact of resolution and conformation on the aggregate size distribution and on the optimal rule-based model. In addition, we develop a predictive model by first fixing the rule set and varying only the binding rate constant for each resolution, and then fitting the resulting data to a function. This model is intended to enable the prediction of the aggregate size distribution for higher resolutions while requiring only data for lower resolution Monte Carlo models, thus enhancing computational efficiency. Finally, we use a simple rule-based model to fit experimental cell degranulation data for various concentrations of the shrimp allergen Pen a 1 and the IgE antibody.
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Papers by Brittany Hoard
OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information), Apr 10, 2018
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The allergic response is produced by the release of immune mediators by mast cells and basophils.... more The allergic response is produced by the release of immune mediators by mast cells and basophils. This process, in turn, is initiated by the aggregation of antigens and IgE-FcǫRI antibody-receptor complexes. Computational modeling of antibodyantigen aggregate formation as well as the size and structure of these aggregates is an important tool for greater understanding of the allergic response. In addition, the incorporation of molecular geometry into aggregation models can more accurately capture details of the aggregation process, and may lead to insights into how geometry affects aggregate formation. However, it is challenging to simulate aggregation due to the computational cost of simulating large molecules. Methods to geometrically model antibody aggregation inspired by rigid body robotic motion simulations have previously been developed; however, high computational cost mandates that the resolution of the 3D molecular models be reduced, which affects the results of the simulat...
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2020 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)
The allergic response in humans results from the crosslinking of IgE-Fc< RI receptor complexes... more The allergic response in humans results from the crosslinking of IgE-Fc< RI receptor complexes via the binding of IgE antibodies to antigens, which results in cell degranulation. The relationship between cell degranulation and antigen-antibody aggregation was investigated for the shrimp allergen Pen a 1. A biological rule-based model was developed to simulate aggregation of IgE antibodies and the Pen a 1 antigen. The forward rate constant and the crosslinking factor were varied to demonstrate how the model output changes as these model parameters are changed. It was found that the peak of the dose-response curve becomes greater and more defined as the crosslinking factor increases, and that the peak shifts to lower doses as the forward rate constant increases. Parameter scanning was performed to fit the model output to experimental cell secretion data obtained by collaborators, assuming a directly proportional relationship between the two quantities. Four concentrations of allergenspecific IgE were examined: 15 ng/mL, 30 ng/mL, 60 ng/mL, and 120 ng/mL. For each IgE concentration, nine doses of Pen a 1 were examined ranging from 0.0001 ng/mL to 10,000 ng/mL. The average aggregate size was used as the measure of aggregation to compare to the experimental data. It was found that the output of the biological rule-based model fit well to the cell degranulation data.
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2019 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2019
Previously, we proposed a method for incorporating molecular geometry in a biological rule-based ... more Previously, we proposed a method for incorporating molecular geometry in a biological rule-based model by encoding molecular curvature into the rules and associated binding rate constants. We combined this method with a 3D rigid-body Monte Carlo simulation to model antigen-antibody aggregation. In this work, we use our geometric rule-based method to develop a model for predicting the output of the full-resolution Monte Carlo simulation given the output of lower resolution simulations. The purpose of this predictive model is to reduce the computational cost of the Monte Carlo simulation. We develop this model by first choosing a rule set for each molecular geometry and varying only the binding rate constant for each Monte Carlo resolution, and then fitting the resulting data to a function. We examine the calculation time needed for each predictive model to demonstrate how this model is more efficient than running a full-resolution simulation. We find that this method can reduce the c...
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Optics express, Jan 26, 2016
We introduce a new approach to systematically break the symmetry in periodic nanostructures on a ... more We introduce a new approach to systematically break the symmetry in periodic nanostructures on a crystalline silicon surface. Our focus is inverted nanopyramid arrays with a prescribed symmetry. The arrangement and symmetry of nanopyramids are determined by etch mask design and its rotation with respect to the [110] orientation of the Si(001) substrate. This approach eliminates the need for using expensive off-cut silicon wafers. We also make use of low-cost, manufacturable, wet etching steps to fabricate the nanopyramids. Our experiment and computational modeling demonstrate that the symmetry breaking can increase the photovoltaic efficiency in thin-film silicon solar cells. For a 10-micron-thick active layer, the efficiency improves from 27.0 to 27.9% by enhanced light trapping over the broad sunlight spectrum. Our computation further reveals that this improvement would increase from 28.1 to 30.0% in the case of a 20-micron-thick active layer, when the unetched area between nanopy...
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2016 IEEE 43rd Photovoltaic Specialists Conference (PVSC), 2016
We experimentally demonstrate highly efficient light-trapping structures that is achieved by brea... more We experimentally demonstrate highly efficient light-trapping structures that is achieved by breaking the symmetry in inverted nanopyramids on c-Si. The fabrication of these structures is cost-effective and scalable. Our optical measurement for the structures on 10-μm-thick c-Si cells shows the Shockley-Queisser efficiency of 27.9%. We further fabricate plasmonic metal structures on the symmetry-breaking inverted nanopyramids. When a light-absorbing polymer layer is deposited on top of the plasmonic structures, we observe that the plasmonic light trapping exceeds the Lambertian limit. The remarkable light trapping increases the short circuit current by 2.5 times. We expect the symmetry-breaking structures to be broadly applicable to thin-film solar cells.
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Robotica, 2016
SUMMARYIt is estimated that allergies afflict up to 40% of the world's population. A primary ... more SUMMARYIt is estimated that allergies afflict up to 40% of the world's population. A primary mediator for allergies is the aggregation of antigens and IgE antibodies bound to cell-surface receptors, FcεRI. Antibody/antigen aggregate formation causes stimulation of mast cells and basophils, initiating cellular degranulation and releasing immune mediators which produce an allergic or anaphylactic response. Understanding the shape and structure of these aggregates can provide critical insights into the allergic response. We have previously developed methods to geometrically model, simulate and analyze antibody aggregation inspired by rigid body robotic motion simulations. Our technique handles the large size and number of molecules involved in aggregation, providing an advantage over traditional simulations such as molecular dynamics (MD) and coarse-grained energetic models. In this paper, we study the impact of model resolution on simulations of geometric structures using both our...
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Advanced Optical Materials, 2016
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2015 IEEE 42nd Photovoltaic Specialist Conference (PVSC), 2015
We introduce a manufacturable method to break the symmetry in inverted nanopyramids on c-Si. This... more We introduce a manufacturable method to break the symmetry in inverted nanopyramids on c-Si. This method broadly enhances light trapping and would increase the efficiency from 25 to 26.4% for thick c-Si cells. We further use the nanopyramids as a template to deposit plasmonic metal structures and demonstrate enhanced light absorption in organic solar cells. The enhancement exceeds 100% in some cases by concentrating the plasmonic bands tuned to the polymer absorption. The result agrees well with our measured surface plasmon polariton band structures. We expect our approach to be broadly applicable to thin-film solar cells.
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2015 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2015
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We previously developed a method for encoding steric effects in a BioNetGen model via the optimiz... more We previously developed a method for encoding steric effects in a BioNetGen model via the optimization of the cutoff distance and the rule rate. We optimized them by fitting the output to that generated by a 3D Monte Carlo simulation that represents molecular geometry. We optimize the parameters for our model using a fuzzy inference system. We develop fuzzy systems for predicting the rule rate and cutoff distance given an RSS value or probability distribution. We construct these systems using data from BioNetGen parameter scans. We create systems with various input data and numbers of clusters, and analyze their performance with regard to the optimization of our BioNetGen model. We find that the system that uses a residual-sum-of-squares value as the input value performs acceptably well. However, the performance of the fuzzy systems that use probabilities as their input values perform inconsistently in our tests. The results of this study suggest that the system that uses a residual...
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Advanced materials (Deerfield Beach, Fla.), 2015
Crystalline silicon solar cells, only 10 μm thick, with a peak conversion efficiency of 15.7% are... more Crystalline silicon solar cells, only 10 μm thick, with a peak conversion efficiency of 15.7% are reported by G. Chen and co-workers on page 2182. Efficient crystalline silicon photovoltaics of such thinness are enabled by an advanced light-trapping design incorporating a two-dimensional inverted pyramid photonic crystal.
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Advanced materials (Deerfield Beach, Fla.), Jan 18, 2015
Only ten micrometer thick crystalline silicon solar cells deliver a short-circuit current of 34.5... more Only ten micrometer thick crystalline silicon solar cells deliver a short-circuit current of 34.5 mA cm(-2) and power conversion efficiency of 15.7%. The record performance for a crystalline silicon solar cell of such thinness is enabled by an advanced light-trapping design incorporating a 2D inverted pyramid photonic crystal and a rear dielectric/reflector stack.
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Photovoltaic Specialist Conference (PVSC), 2015 IEEE 42nd, 2015
We introduce a manufacturable method to break the symmetry in inverted nanopyramids on c-Si. This... more We introduce a manufacturable method to break the symmetry in inverted nanopyramids on c-Si. This method broadly enhances light trapping and would increase the efficiency from 25 to 26.4% for thick c-Si cells. We further use the nanopyramids as a template to deposit plasmonic metal structures and demonstrate enhanced light absorption in organic solar cells. The enhancement exceeds 100% in some cases by concentrating the plasmonic bands tuned to the polymer absorption. The result agrees well with our measured surface plasmon polariton band structures. We expect our approach to be broadly applicable to thin-film solar cells.
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2016 IEEE 43rd Photovoltaic Specialists Conference (PVSC), 2016
We experimentally demonstrate highly efficient light-trapping structures that is achieved by brea... more We experimentally demonstrate highly efficient light-trapping structures that is achieved by breaking the symmetry in inverted nanopyramids on c-Si. The fabrication of these structures is cost-effective and scalable. Our optical measurement for the structures on 10-m-thick c-Si cells shows the Shockley-Queisser efficiency of 27.9%. We further fabricate plasmonic metal structures on the symmetry-breaking inverted nanopyramids. When a light-absorbing polymer layer is deposited on top of the plasmonic structures, we observe that the plasmonic light trapping exceeds the Lambertian limit. The remarkable light trapping increases the short circuit current by 2.5 times. We expect the symmetry-breaking structures to be broadly applicable to thin-film solar cells.
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Patent
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2020 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2020
The allergic response in humans results from the crosslinking of IgE-Fc RI receptor complexes via... more The allergic response in humans results from the crosslinking of IgE-Fc RI receptor complexes via the binding of IgE antibodies to antigens, which results in cell degranulation. The relationship between cell degranulation and antigen-antibody aggregation was investigated for the shrimp allergen Pen a 1. A biological rule-based model was developed to simulate aggregation of IgE antibodies and the Pen a 1 antigen. The forward rate constant and the crosslinking factor were varied to demonstrate how the model output changes as these model parameters are changed. It was found that the peak of the dose-response curve becomes greater and more defined as the crosslinking factor increases, and that the peak shifts to lower doses as the forward rate constant increases. Parameter scanning was performed to fit the model output to experimental cell secretion data obtained by collaborators, assuming a directly proportional relationship between the two quantities. Four concentrations of allergenspecific IgE were examined: 15 ng/mL, 30 ng/mL, 60 ng/mL, and 120 ng/mL. For each IgE concentration, nine doses of Pen a 1 were examined ranging from 0.0001 ng/mL to 10,000 ng/mL. The average aggregate size was used as the measure of aggregation to compare to the experimental data. It was found that the output of the biological rule-based model fit well to the cell degranulation data.
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The study addresses the problem of the inadequacy of conventional software testing methods to det... more The study addresses the problem of the inadequacy of conventional software testing methods to detect all software defects. This problem affects software users and researchers due to poor software performance, reduced precision or accuracy of software output, and retractions of research publications. Detecting software defects may also be challenging due to the oracle problem. Existing research supports the metamorphic testing method's effectiveness for handling the oracle problem and finding software defects that conventional testing methods cannot detect. The research questions ask about the relationships among the use and acceptance of the metamorphic testing method among open-source developers and the constructs of performance expectancy and effort expectancy. The study's purpose was to examine these relationships. Another objective of the study was to understand how the variables of age, gender, and experience moderate these relationships. The guiding theoretical framework of the study was the unified theory of acceptance and use of technology. In this study, a quantitative methodology with a correlational design was employed. The participants were contributors to open-source software projects contained in the GitHub “Software in science” collection. The data was collected via an online survey instrument. The data were analyzed using Spearman’s rank-order correlation tests and moderated multiple regression analysis. Moderate to strong positive relationships were found between both the performance expectancy and effort expectancy and the acceptance and use of metamorphic testing. This finding suggests that increasing the extent to which developers believe that metamorphic testing will improve their job performance and improving its ease of use will increase the adoption of metamorphic testing. The creation of interventions to educate developers on the use of metamorphic testing is recommended. The study results support the applicability of the unified theory of acceptance and use of technology to software testing methods. Future research could involve studying the relationship between metamorphic testing adoption and other factors, such as social influence and facilitating conditions.
Bookmarks Related papers MentionsView impact
The allergic response is produced by the release of immune mediators by mast cells and basophils.... more The allergic response is produced by the release of immune mediators by mast cells and basophils. This process, in turn, is initiated by the aggregation of antigens and IgE-FceRI antibody-receptor complexes. Computational modeling of antibody-antigen aggregate formation as well as the size and structure of these aggregates is an important tool for greater understanding of the allergic response. In addition, the incorporation of molecular geometry into aggregation models can more accurately capture details of the aggregation process, and may lead to insights into how geometry affects aggregate formation. However, it is challenging to simulate aggregation due to the computational cost of simulating large molecules. Methods to geometrically model antibody aggregation inspired by rigid body robotic motion simulations have previously been developed; however, high computational cost mandates that the resolution of the 3D molecular models be reduced, which affects the results of the simulation. Rule-based modeling can be used to model aggregation with low computational cost, but traditional rule-based modeling approaches do not include details of molecular geometry.
In this work, we propose a novel implementation of rule-based modeling that encodes details of molecular geometry into the rules and the binding rate constant associated with each rule. We demonstrate how the set of rules is constructed according to the curvature of the molecule. We then perform a study of antigen-antibody aggregation using our proposed method combined with a previously developed 3D rigid-body Monte Carlo simulation. We first simulate the binding of IgE antibodies bound to cell surface receptors FceRI to various binding regions of the allergen Pen a 1 using the aforementioned Monte Carlo simulation, and we analyze the distribution of the sizes of the aggregates that form during the simulation. Then, using our novel rule-based approach, we optimize a rule-based model according to the geometry of the Pen a 1 molecule and the data from the Monte Carlo simulation. In particular, we use the distances between the binding regions of the Pen a 1 molecule to optimize the rules and associated binding rate constants. The optimized rule-based models provide information about the average steric hindrance between binding regions and
the probability that IgE-FceRI receptor complexes will bind to these regions. In addition, the optimized rule-based models provide a means of quantifying the variation in aggregate size distribution that results from differences in molecular geometry. We perform this procedure for seven resolutions and three molecular conformations of Pen a 1. We then analyze the impact of resolution and conformation on the aggregate size distribution and on the optimal rule-based model. In addition, we develop a predictive model by first fixing the rule set and varying only the binding rate constant for each resolution, and then fitting the resulting data to a function. This model is intended to enable the prediction of the aggregate size distribution for higher resolutions while requiring only data for lower resolution Monte Carlo models, thus enhancing computational efficiency. Finally, we use a simple rule-based model to fit experimental cell degranulation data for various concentrations of the shrimp allergen Pen a 1 and the IgE antibody.
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OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information), Apr 10, 2018
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The allergic response is produced by the release of immune mediators by mast cells and basophils.... more The allergic response is produced by the release of immune mediators by mast cells and basophils. This process, in turn, is initiated by the aggregation of antigens and IgE-FcǫRI antibody-receptor complexes. Computational modeling of antibodyantigen aggregate formation as well as the size and structure of these aggregates is an important tool for greater understanding of the allergic response. In addition, the incorporation of molecular geometry into aggregation models can more accurately capture details of the aggregation process, and may lead to insights into how geometry affects aggregate formation. However, it is challenging to simulate aggregation due to the computational cost of simulating large molecules. Methods to geometrically model antibody aggregation inspired by rigid body robotic motion simulations have previously been developed; however, high computational cost mandates that the resolution of the 3D molecular models be reduced, which affects the results of the simulat...
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2020 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)
The allergic response in humans results from the crosslinking of IgE-Fc< RI receptor complexes... more The allergic response in humans results from the crosslinking of IgE-Fc< RI receptor complexes via the binding of IgE antibodies to antigens, which results in cell degranulation. The relationship between cell degranulation and antigen-antibody aggregation was investigated for the shrimp allergen Pen a 1. A biological rule-based model was developed to simulate aggregation of IgE antibodies and the Pen a 1 antigen. The forward rate constant and the crosslinking factor were varied to demonstrate how the model output changes as these model parameters are changed. It was found that the peak of the dose-response curve becomes greater and more defined as the crosslinking factor increases, and that the peak shifts to lower doses as the forward rate constant increases. Parameter scanning was performed to fit the model output to experimental cell secretion data obtained by collaborators, assuming a directly proportional relationship between the two quantities. Four concentrations of allergenspecific IgE were examined: 15 ng/mL, 30 ng/mL, 60 ng/mL, and 120 ng/mL. For each IgE concentration, nine doses of Pen a 1 were examined ranging from 0.0001 ng/mL to 10,000 ng/mL. The average aggregate size was used as the measure of aggregation to compare to the experimental data. It was found that the output of the biological rule-based model fit well to the cell degranulation data.
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2019 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2019
Previously, we proposed a method for incorporating molecular geometry in a biological rule-based ... more Previously, we proposed a method for incorporating molecular geometry in a biological rule-based model by encoding molecular curvature into the rules and associated binding rate constants. We combined this method with a 3D rigid-body Monte Carlo simulation to model antigen-antibody aggregation. In this work, we use our geometric rule-based method to develop a model for predicting the output of the full-resolution Monte Carlo simulation given the output of lower resolution simulations. The purpose of this predictive model is to reduce the computational cost of the Monte Carlo simulation. We develop this model by first choosing a rule set for each molecular geometry and varying only the binding rate constant for each Monte Carlo resolution, and then fitting the resulting data to a function. We examine the calculation time needed for each predictive model to demonstrate how this model is more efficient than running a full-resolution simulation. We find that this method can reduce the c...
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Optics express, Jan 26, 2016
We introduce a new approach to systematically break the symmetry in periodic nanostructures on a ... more We introduce a new approach to systematically break the symmetry in periodic nanostructures on a crystalline silicon surface. Our focus is inverted nanopyramid arrays with a prescribed symmetry. The arrangement and symmetry of nanopyramids are determined by etch mask design and its rotation with respect to the [110] orientation of the Si(001) substrate. This approach eliminates the need for using expensive off-cut silicon wafers. We also make use of low-cost, manufacturable, wet etching steps to fabricate the nanopyramids. Our experiment and computational modeling demonstrate that the symmetry breaking can increase the photovoltaic efficiency in thin-film silicon solar cells. For a 10-micron-thick active layer, the efficiency improves from 27.0 to 27.9% by enhanced light trapping over the broad sunlight spectrum. Our computation further reveals that this improvement would increase from 28.1 to 30.0% in the case of a 20-micron-thick active layer, when the unetched area between nanopy...
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2016 IEEE 43rd Photovoltaic Specialists Conference (PVSC), 2016
We experimentally demonstrate highly efficient light-trapping structures that is achieved by brea... more We experimentally demonstrate highly efficient light-trapping structures that is achieved by breaking the symmetry in inverted nanopyramids on c-Si. The fabrication of these structures is cost-effective and scalable. Our optical measurement for the structures on 10-μm-thick c-Si cells shows the Shockley-Queisser efficiency of 27.9%. We further fabricate plasmonic metal structures on the symmetry-breaking inverted nanopyramids. When a light-absorbing polymer layer is deposited on top of the plasmonic structures, we observe that the plasmonic light trapping exceeds the Lambertian limit. The remarkable light trapping increases the short circuit current by 2.5 times. We expect the symmetry-breaking structures to be broadly applicable to thin-film solar cells.
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Robotica, 2016
SUMMARYIt is estimated that allergies afflict up to 40% of the world's population. A primary ... more SUMMARYIt is estimated that allergies afflict up to 40% of the world's population. A primary mediator for allergies is the aggregation of antigens and IgE antibodies bound to cell-surface receptors, FcεRI. Antibody/antigen aggregate formation causes stimulation of mast cells and basophils, initiating cellular degranulation and releasing immune mediators which produce an allergic or anaphylactic response. Understanding the shape and structure of these aggregates can provide critical insights into the allergic response. We have previously developed methods to geometrically model, simulate and analyze antibody aggregation inspired by rigid body robotic motion simulations. Our technique handles the large size and number of molecules involved in aggregation, providing an advantage over traditional simulations such as molecular dynamics (MD) and coarse-grained energetic models. In this paper, we study the impact of model resolution on simulations of geometric structures using both our...
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Advanced Optical Materials, 2016
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2015 IEEE 42nd Photovoltaic Specialist Conference (PVSC), 2015
We introduce a manufacturable method to break the symmetry in inverted nanopyramids on c-Si. This... more We introduce a manufacturable method to break the symmetry in inverted nanopyramids on c-Si. This method broadly enhances light trapping and would increase the efficiency from 25 to 26.4% for thick c-Si cells. We further use the nanopyramids as a template to deposit plasmonic metal structures and demonstrate enhanced light absorption in organic solar cells. The enhancement exceeds 100% in some cases by concentrating the plasmonic bands tuned to the polymer absorption. The result agrees well with our measured surface plasmon polariton band structures. We expect our approach to be broadly applicable to thin-film solar cells.
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2015 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2015
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We previously developed a method for encoding steric effects in a BioNetGen model via the optimiz... more We previously developed a method for encoding steric effects in a BioNetGen model via the optimization of the cutoff distance and the rule rate. We optimized them by fitting the output to that generated by a 3D Monte Carlo simulation that represents molecular geometry. We optimize the parameters for our model using a fuzzy inference system. We develop fuzzy systems for predicting the rule rate and cutoff distance given an RSS value or probability distribution. We construct these systems using data from BioNetGen parameter scans. We create systems with various input data and numbers of clusters, and analyze their performance with regard to the optimization of our BioNetGen model. We find that the system that uses a residual-sum-of-squares value as the input value performs acceptably well. However, the performance of the fuzzy systems that use probabilities as their input values perform inconsistently in our tests. The results of this study suggest that the system that uses a residual...
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Bookmarks Related papers MentionsView impact
Advanced materials (Deerfield Beach, Fla.), 2015
Crystalline silicon solar cells, only 10 μm thick, with a peak conversion efficiency of 15.7% are... more Crystalline silicon solar cells, only 10 μm thick, with a peak conversion efficiency of 15.7% are reported by G. Chen and co-workers on page 2182. Efficient crystalline silicon photovoltaics of such thinness are enabled by an advanced light-trapping design incorporating a two-dimensional inverted pyramid photonic crystal.
Bookmarks Related papers MentionsView impact
Advanced materials (Deerfield Beach, Fla.), Jan 18, 2015
Only ten micrometer thick crystalline silicon solar cells deliver a short-circuit current of 34.5... more Only ten micrometer thick crystalline silicon solar cells deliver a short-circuit current of 34.5 mA cm(-2) and power conversion efficiency of 15.7%. The record performance for a crystalline silicon solar cell of such thinness is enabled by an advanced light-trapping design incorporating a 2D inverted pyramid photonic crystal and a rear dielectric/reflector stack.
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Photovoltaic Specialist Conference (PVSC), 2015 IEEE 42nd, 2015
We introduce a manufacturable method to break the symmetry in inverted nanopyramids on c-Si. This... more We introduce a manufacturable method to break the symmetry in inverted nanopyramids on c-Si. This method broadly enhances light trapping and would increase the efficiency from 25 to 26.4% for thick c-Si cells. We further use the nanopyramids as a template to deposit plasmonic metal structures and demonstrate enhanced light absorption in organic solar cells. The enhancement exceeds 100% in some cases by concentrating the plasmonic bands tuned to the polymer absorption. The result agrees well with our measured surface plasmon polariton band structures. We expect our approach to be broadly applicable to thin-film solar cells.
Bookmarks Related papers MentionsView impact
2016 IEEE 43rd Photovoltaic Specialists Conference (PVSC), 2016
We experimentally demonstrate highly efficient light-trapping structures that is achieved by brea... more We experimentally demonstrate highly efficient light-trapping structures that is achieved by breaking the symmetry in inverted nanopyramids on c-Si. The fabrication of these structures is cost-effective and scalable. Our optical measurement for the structures on 10-m-thick c-Si cells shows the Shockley-Queisser efficiency of 27.9%. We further fabricate plasmonic metal structures on the symmetry-breaking inverted nanopyramids. When a light-absorbing polymer layer is deposited on top of the plasmonic structures, we observe that the plasmonic light trapping exceeds the Lambertian limit. The remarkable light trapping increases the short circuit current by 2.5 times. We expect the symmetry-breaking structures to be broadly applicable to thin-film solar cells.
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Patent
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2020 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2020
The allergic response in humans results from the crosslinking of IgE-Fc RI receptor complexes via... more The allergic response in humans results from the crosslinking of IgE-Fc RI receptor complexes via the binding of IgE antibodies to antigens, which results in cell degranulation. The relationship between cell degranulation and antigen-antibody aggregation was investigated for the shrimp allergen Pen a 1. A biological rule-based model was developed to simulate aggregation of IgE antibodies and the Pen a 1 antigen. The forward rate constant and the crosslinking factor were varied to demonstrate how the model output changes as these model parameters are changed. It was found that the peak of the dose-response curve becomes greater and more defined as the crosslinking factor increases, and that the peak shifts to lower doses as the forward rate constant increases. Parameter scanning was performed to fit the model output to experimental cell secretion data obtained by collaborators, assuming a directly proportional relationship between the two quantities. Four concentrations of allergenspecific IgE were examined: 15 ng/mL, 30 ng/mL, 60 ng/mL, and 120 ng/mL. For each IgE concentration, nine doses of Pen a 1 were examined ranging from 0.0001 ng/mL to 10,000 ng/mL. The average aggregate size was used as the measure of aggregation to compare to the experimental data. It was found that the output of the biological rule-based model fit well to the cell degranulation data.
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Computers in Biology and Medicine, 2019
In this study, the binding of allergens to antibody-receptor complexes was investigated. This pro... more In this study, the binding of allergens to antibody-receptor complexes was investigated. This process is important in understanding the allergic response. A BioNetGen model that simulates this process, combined with a novel method for encoding steric effects via the optimization of the cutoff distance and the rule binding rate, was previously developed. These parameters were optimized by fitting the model output to the output of a 3D simulation that explicitly represents molecular geometry. In this work, the parameters for the BioNetGen model were optimized using an adaptive-network-based fuzzy inference system in order to predict the rule rate and cutoff distance given a residual-sum-of-squares value or a probability distribution. The fuzzy systems were constructed using fuzzy c-means clustering with existing data from BioNetGen model parameter scans used as the training data. Fuzzy systems with various input data and number of clusters were created and tested. Their performance was analyzed with regard to the effective optimization of the rule-based model. The study found that the fuzzy system that uses a residual-sum-of-squares value as the input value performs acceptably well. However, the performance of the fuzzy systems that use probabilities as their input values performed inconsistently in the tests and need further development. This methodology could potentially be
modified for use in fitting other biological models.
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2019 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2019
Previously, we proposed a method for incorporating molecular geometry in a biological rule-based ... more Previously, we proposed a method for incorporating molecular geometry in a biological rule-based model by encoding molecular curvature into the rules and associated binding rate constants. We combined this method with a 3D rigid-body Monte Carlo simulation to model antigen-antibody aggregation. In this work, we use our geometric rule-based method to develop a model for predicting the output of the full-resolution Monte Carlo simulation given the output of lower resolution simulations. The purpose of this predictive model is to reduce the computational
cost of the Monte Carlo simulation. We develop this model by first choosing a rule set for each molecular geometry and varying only the binding rate constant for each Monte Carlo resolution, and then fitting the resulting data to a function. We examine the calculation time needed for each predictive model to demonstrate how this model is more efficient than running a full-resolution simulation. We find that this method can reduce the computational time of the Monte Carlo simulation by up to 20%.
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