Keynote lecture
“Industrial Biotechnology – the Crossroads of Engineering and Biology”
Oral Presentations
1UH Department of Chemical and Biomolecular Engineering, 2UH Department of Electrical and Computer Engineering
Micro-fabricated retroreflectors, which are designed to return reflected light directly back to its source, potentially represent an attractive and economical new form of label for immunoassays and other biomedical assays. They are readily detectable, the returned signal can be easily measured with simple, cheap optics, and they are fabricated in vast numbers using scalable, inexpensive lithographic techniques.
One way to use retroreflectors in assays is to modulate their brightness in the presence of analyte, particles, etc. Silver staining, which utilizes chemistry similar to black and white photography, is adapted in an antigen-detection assay based on micro-retroreflectors, where reflector brightness is modulated by silver particles formed only in the presence of antigen, which can be a virus, pathogenic bacterium, biomarker, etc. Conventionally, silver staining is done using immunogold particles and a solution containing silver ions and a reducing agent (i.e. hydroquinone). But this method offers a problem in an assay integrated in a microfluidic system. Clogging of small tubings in microfluidics might happen since it only takes a few minutes before silver particles start to form from hydroquinone reductant even in the absence of gold nanoparticles. To address this issue, an alternative method of silver staining was implemented where one of the reagents used is not an active reductant unless acted upon by an enzyme. In this method, a solution of silver acetate and ascorbic acid phosphate was used, where the latter is dephosphorylated in the presence of antibody-conjugated alkaline phosphatase producing ascorbic acid, which is a reducing agent. Results showed the selective formation of silver particles at sites where alkaline phosphatase was present.
1Department of Chemical and Biomolecular Engineering, 2Department of Biomedical Engineering, 3Department of Chemistry, Rice University, 4Department of Biology and Biochemistry
Ion-exchange chromatography is widely used for separation of biomolecules. Traditionally, charged ligands are introduced into ion-exchange matrices by random chemical processes, producing a heterogeneous charge distribution. In previous work we demonstrated that improved protein-binding capacity and selectivity of ion-exchange adsorbents displaying a nanostructured “clustered” rather than random, distribution of surface charges. We also found that clustered adsorbents selectively favor proteins with inherent charge clustering.
The current work shows that “clustered” penta-arginamide adsorbents show DNA binding capacity comparable to that of conventional dispersed adsorbents with 10- to 100-fold higher ligand density. At moderate ionic strength the DNA affinity of all adsorbents tested increased with salt while RNA affinity decreased, so that selectivity for DNA over RNA was enhanced as salt concentration increased. Early results of single-molecule fluorescence studies of protein ion-exchange adsorption are also presented
Association of membrane proteins is central in material and information flow across the cellular membranes with current drug designing efforts targeting regulation of this process. The amino-acid sequence and the membrane environment are critical factors controlling association, however, quantitative knowledge of such contributions is limited. Probing membrane-mediated and protein-protein interactions is a challenging task both for experimental and simulation methods. Herein we present a study on the dimerization of helices in lipid bilayers using extensive parallel Monte Carlo simulations with recently developed algorithms [1].
The dimerization of Glycophorin A was examined employing a coarse-grain model that retains amino-acid specificity, in three different phospholipid bilayers. Association is driven by a balance of protein-protein and lipid-induced interactions with the latter playing a major role at short separations. However, during protein recognition an ensemble of dimers is found, controlled by the free energy of tilting in the specific membrane environment. In all bilayers, sequence-specificity is evident by the formation of a clear interface as suggested in literature studies. Furthermore, the extracted estimates on the dimerization affinity of Glycophorin A are in excellent agreement with experimental data [2].
Following a different approach, the effect of amino-acid sequence was studied using the four transmembrane domains of the epidermal growth factor receptor family in identical lipid environments. Detailed characterization of dimer formation and estimates of the free energy of association reveal that these transmembrane domains present significant affinity to self-associate in qualitative agreement with experimental findings. However, certain dimers form non-specific interfaces with helices aligning parallel to the membrane normal. Lipid-mediated entropic contributions present a more-complex character than anticipated, favoring a decrease of protein separation or a parallel orientation depending on the interfacial residues. This result has major implications on the activity of the formed dimers; several studies support activity is a function of the interface formed.
Our studies provide significant insight into the dimerization of proteins in a single component lipid bilayer. Mammalian cell membranes are rich and diverse in proteins, lipids and carbohydrates. Future studies will aim to address the effect of lipid composition of multi-component membranes on the association of transmembrane proteins.
References
1. Janosi L. and Doxastakis M., “Accelerating flat-histogram methods for potential of mean force calculations”, J. Chem. Phys., 131, 054105 (2009)
2. Janosi L., Prakash A. and Doxastakis M., “Lipid-Modulated sequence-specific association of Glycophorin A in membranes”, Biophys. J., 99, 284-292 (2010)
1Chemical and Biomolecular Engineering; 2Materials Engineering; 3Chemistry; 4Electrical and Computer Engineering
Various transducers of biomolecular signals have attracted the attention of the scientific and engineering communities for their potential applications in proteomics, medical diagnostics, and molecular cell biology. Biomolecular sensors need to be tailored for specific applications, be stable under the given test conditions, and be robust against false-positive interactions. A continuing challenge in many clinical applications is the extremely small size of many biopsy samples, requiring great sensitivity for detection of analytes such as DNA, RNA, and proteins.
The giant magnetoresistance (GMR) phenomenon is manifested by a large change of the magnetic material’s resistance under the application of an external magnetic field. GMR sensor materials are magnetic multilayers where the relative orientations of the magnetization in the individual magnetic layers control the sensor resistance. GMR sensors have been used extensively in magnetic hard-drive technology and have sensitivity sufficient to detect individual magnetic bits with sub-100nm dimensions. As such, GMR sensors are well suited for magnetic nanoparticle- based assays tailored for biomolecular recognition.
Applying nanomagnetic device engineering to biosensing technology, we have developed a GMR sensor that is extremely sensitive to external magnetic fields and is capable of detecting individual magnetic biolabels. Electron beam lithography was used to pattern the 500nm-wide GMR sensors where a pair of copper contacts, also patterned by e-beam lithography, defines the length of the sensing area (about 1um). GMR multilayers (Co/Cu/Co) were deposited by UHV magnetron sputtering with the base pressure of 1.0 x 10-8 torr. The sensors were conformally coated with 20nm alumina thin films to electrically insulate the device and protect it from highly corrosive biological media. Such coatings enable reliable sensor operation in a PBS (phosphate-buffered saline) solution commonly used in biological research for up to 48 hours. Magnetic particles attached to the sensor surface are detected by the change in magnetoresistance due to stray fields generated by the particles.
This presentation will focus on the challenges of GMR sensor design, fabrication, and biofunctionalization to enable the production of a highly sensitive, specific device for the detection of early stage cancer biomarkers, which is the long-term goal of our research.
1Department of Chemical and Biomolecular Engineering, 2Department of Physics and Astronomy, University of Texas at Brownsville, Brownsville
Major progress has been made during the past two decades in developing energetic materials that can rapidly release temperature and pressure waves and have extensive potential applications. Nanoenergetic thermite materials have various potential military applications and are likely to become the next-generation explosive materials such as aircraft fuels, rocket propellants, explosives, and primes. Decreasing the particle size of thermite components lead to reduce the diffusion and mass transport limitation between the reactants, consequently it increase thermite reaction and energy release rate up to 3 orders of magnitude.
Our experiments revealed that Al-I2O5 nanothermite reaction generated the high pressure pulse among common nanothermite reactions and can potentially be used as a Nanoenergetic Gas Generator (NGG). The reactants were thoroughly mixed in hexane and nitrogen environment for up to 8 h in a rotary mixing/grinding machine. The hexane was used as a mixing agent to prevent buildup of electrostatic charge on the particles surface that may lead to ignition and/or explosion of the powders during the mixing and handling. The mixing of the reactants in hexane under nitrogen environment avoids the partial oxidation of Al nano particles and averts the need to reduce the active metal. In most experiments we used aluminum nanoparticles with an average particle size of ~100 nm. This powder is not very active in air and can be safely mixed with metal oxides to prepare the thermite reactions mixtures. The mixture of Al/I2O5 ignited in the range of 605-620 °C and generated a thermal front that propagated through the sample with a velocity of ~2000 m/s. The maximum pressure x volume (PV)-value for a 0.5 g sample was ~4 kPa.m3 is comparable to that generated by the same sample mass of the Bi2O3/Al system. The study of gas generation dynamics, detonation shock wave velocity and activation energy will be presented as well.
NOx, emitted from diesel vehicles is highly responsible for number of respiratory diseases and is a major cause of ground-level ozone. Hence NOx emission needs to be controlled. Thus selective catalytic reduction (SCR) of NOx (NO + NO2) using ammonia is gaining a lot of attention for mobile applications. In this study a comprehensive steady-state and transient SCR on Fe-zeolite monolithic catalysts was carried out in a bench-flow with the goal to develop mechanistically-based kinetic models for SCR reactor design and optimization.
Fe-ZSM-5 catalyst was synthesized by sequential ion exchange step and the resulting zeolite/alumina slurry was coated onto a cordierite monolith support. Adsorption and reaction experiments were performed on these catalysts and compared to a commercial sample. These experiments included NH3 and NOx uptake and temperature-programmed desorption (TPD), NO and NH3 oxidation, standard SCR (NO+NH3), fast SCR (NO+NO2+NH3), and NO2 SCR (NO2+NH3). An inhibiting effect of NH3 on the SCR reaction was observed due to ammonia blocking the sites required for SCR at low temperatures and ammonia oxidation at higher temperatures NOx removal efficiency was studied over the complete range of NO2/NOx ratio and is found to be maximum at NO2/NOx=0.5. At lower temperatures a pathway via ammonium nitrate was confirmed during NO2 SCR due in part to N2O formation during a temperature ramp. The kinetics of standard SCR and fast SCR reaction, and NO and NH3 oxidation were studied in the temperature range of 200 – 300 C to determine the reaction orders and activation energies of these reactions. Agreement in the kinetics for both the standard SCR and the NO oxidation reaction systems suggests that the oxidation of NO is the rate determining step, in line with recent literature studies. Both external mass transfer limitations and washcoat diffusion limitations were ruled out for moderate temperature conditions (
The plethora of information that a combustion model provides can help understand the complex sub-processes occurring in an internal combustion engine and especially the various interdependencies between these processes. The combustion process is of prime importance as it couples directly with the engine operating characteristics, power and efficiency as well as emissions. Thus it is imperative to have a good physics based model of combustion process in order to satisfy the current trend toward simultaneously increasing fuel to wheel efficiency while reducing emissions. The detailed computational fluid dynamics (CFD) based models, although good for physical understanding of the process are not good for optimization and parametric studies as they are computationally very expensive. While the empirical zeroth order models needs re-calibration with changes in operating conditions. Thus in this work we propose to extend the recently developed low-dimensional model for combustion process that retains all the essential physics of the system and is yet computationally very efficient so as to be solved in real time. The low-dimensional model was derived by spatially averaging the detailed three-dimensional convection-diffusion-reaction (CDR) model employing the Lyapunov-Schmidt (LS) technique of classical bifurcation theory which retains all the parameters of the original equations in the low-dimensional models, and all the qualitative features subsequently. For a given fuel inlet conditions, the model predicts the exhaust composition of regulated gases (total unburned HC’s, CO, and NOx ) as well as the in-cylinder pressure and temperature. The model is able to capture the qualitative trends observed with change in fuel composition (gasoline and ethanol blending), air/fuel ratio, spark timing, engine load and speed. The results show good qualitative and fair quantitative agreement with the experimental results published in the literature and demonstrate the possibility of such low-dimensional model for real-time control.
Projection lithography is the primary technology used for patterning semiconductor devices. High-throughput manufacturing requires imaging materials (resists) that are highly sensitive to radiation, and this demand is satisfied through a process termed chemical amplification (CA). CA resists are comprised of a polymer resin (reactant) and photoacid generator (catalyst); A coupled reaction-diffusion mechanism drives image formation, where image resolution is limited by slow diffusion of the acid catalyst. There is evidence that thin film reaction rates deviate from the bulk behaviour, and current models for image formation do not capture such effects. We use Grazing-Incidence Small-Angle X-Ray Diffraction to measure spatial extent-of-reaction in ultrathin films of a nanopatterned poly(4-hydroxystyrene-co-tertbutylacrylate) CA resist. This research effort is a work-in-progress; Preliminary results and experimental challenges will be discussed. Our long-term aim is to use feedback acquired with X-Ray Diffraction to construct predictive models for the coupled reaction-diffusion processes in ultrathin films.
Layered silicates (LS) modified by alkyl chain (C14 – C18) was introduced in immiscible PS-PMMA blends. The LS planar surface prefers PS phase over PMMA phase and the hydroxyl edges favor PMMA phase. Hence, when PS dominates in the blends, electron micrographs show the LS stay in PS phase, and melt-state rheological behavior of the blends, especially the relaxation behavior of discrete phase at low frequency region, is not affected by the added LS. However, when volume fraction of PMMA increases and PS becomes discrete phase, LS tend to segregate at the interface between PS and PMMA. Electron micrographs reveal well dispersed silicate sheets locating at the interface between small PS domains in the PMMA phase. Linear dynamic rheological data of these samples show significant increase in the low-frequency modulus of the blends with added LS. A thermodynamic model for estimating the interfacial modulus is proposed and the results agree well with the interfacial modulus calculated by Palierne’s emulsion model. Mechanical properties show plasticizing effects at low LS content, converting to brittle behaviors when increasing LS loading.
Poster Presentations
A low-dimensional model of the three-way catalytic converter (TWC) that includes oxygen storage on ceria has been developed and validated with experimental results. The model is derived using fundamental conservation laws and averaging to reduce the system to set of few ODE’s which are more amicable for real time control and optimization. The model incorporates the oxygen storage on ceria as well as the main catalytic reactions occurring on the precious metal sites. The advantage of the low-dimensional model lies in its computational efficiency and at the same time retaining essential physics of the system. Kinetic parameters of the various reactions occurring in the TWC are estimated using genetic algorithm (GA) based optimization. GA advantage lies in its stochasticity, so that it becomes an efficient tool for a system having multiple solutions in avoiding the local minima. Apart from emissions, the model can also predict the fractional oxidation state (‘the bucket level’) and the total oxygen storage capacity (‘the bucket size’) of the catalyst which can be used for outer loop controller design and diagnosis. A regression based model to map the standard system parameters like air-mass, temperature and phi (φ) to the engine emissions is also developed, so as to estimate the input to the low-dimensional TWC model from the measurable quantity with the present sensor sets. The results obtained show good qualitative and quantitative agreement with the experimental data.
We present accurate correlations for the local Nusselt and Sherwood numbers for the case of constant flux (slow reaction) and constant wall concentration or temperature (fast reaction) cases for a channel of arbitrary shape. These new correlations need only a single parameter, namely, the asymptotic value, which depends only on the channel geometric shape. We establish the accuracy of the proposed correlations by comparing the predicted values with the exact numerical values available for a few cases. We use the new correlations to analyze the effect of flow conditions near the inlet to the channel on the ignition and extinction behavior of catalytic monoliths used in combustion and after-treatment applications. It is shown that the bifurcation behavior, such as the number and location of the ignition/extinction points and the number of stable steady-states is sensitive to the flow conditions in the entry region, and hence the heat and mass transfer correlations used, especially for large values of the activation energy or adiabatic temperature rise or when the catalyst axial loading is not uniform.
A crystallite-scale model is incorporated into a reactor-scale model to study the effect of Pt dispersion and temperature during the regeneration of a lean NOx trap (LNT) comprising a Pt/BaO catalyst. The current study is based on a recent experimental study [R.D. Clayton, M.P. Harold, V. Balakotaiah, C.Z. Wan, Appl. Catal. B 90 (2009) 662]. The model shows that an increase in the Pt dispersion for a fixed Pt loading increases the interfacial perimeter between Pt and Ba, and has a significant effect on the storage and regeneration kinetics. The use of temperature dependent diffusivity of stored NOx is able to predict the breakthrough of NO and NO2 during the storage and H2, N2 and NH3 during the regeneration over a range of catalyst temperatures. Further, the storage model predicts the gradient of stored NOx in the barium phase. It also eliminates the need of two different storage sites (fast and slow, based on the proximity to the Pt) which has been previously used to explain the asymmetric NOx breakthrough curve. A rate determining process during the regeneration at low temperature and low dispersion is found to be the diffusion of stored NOx within the Ba phase towards the Pt/Ba interface. The regeneration model predicts that the highest amount of NH3 is produced by the low dispersion catalyst (3.2% dispersion) at high temperatures, by the high dispersion catalyst (50% dispersion) at low temperatures, and by the intermediate dispersion catalyst (8% dispersion) at intermediate temperatures, consistent with the experimental data. Finally, a novel design is proposed to maximize the amount of NH3 in the effluent of a LNT, which can be used as a feed to a selective catalytic reduction (SCR) unit placed downstream of the LNT.
D. Bhatia, R.W. McCabe, M.P. Harold, V. Balakotaiah, Journal of Catalysis, 266 (2009) 106.
D. Bhatia, M.P. Harold, V. Balakotaiah, Catalysis Today, 155 (2010) 314
D. Bhatia, R.D. Clayton, M.P. Harold, V. Balakotaiah, Catalysis Today, 147 (1) (2009) S250
The placement of wells for production of natural gas from reservoirs with very low permeability has a significant effect on the expected recovery and associated cost. The difficulty of the problem lies in the inherent uncertainty associated with formulating the well placement problem as a numerical optimization problem, along with the large number of possible placement scenarios that have to be examined and which require inordinately large time for computations before an optimal solution is found. Well placement is a fundamental problem and many different approaches have appeared in literature towards its solution. The main target of these approaches is to address the two main issues named above, namely uncertainty and large number of alternatives. In this work, we present a methodology for well placement based on numerical optimization that relies on the combination of two interrelated methods: Design and Analysis of Computer Experiments (DACE) and Efficient Global Optimization (EGO).
The proposed approach addresses both the uncertainty and computational time issues. In the numerical optimization proposed, the objective function is taken to be either recovery or net present value. The decision variables are the number of wells and their corresponding coordinates. The optimization is performed for the starting point of the development of a field and at later points, as more wells are added. All available information (such as seismic data, past production data) is assumed to have been translated to reservoir properties that are used in a (rigorous or short-cut) reservoir simulator to provide estimates of future production given well location, geometry, and stimulation. The optimization proceeds by (a) running the simulator at a few points to perform corresponding evaluations of the objective function, (b) using the (computationally inexpensive) DACE approximation for evaluation of the objective function at several intermediate points to identify well coordinates with the maximum expected improvement in the objective, (c) running the simulator for well coordinates chosen in part b, and (d) repeating the process from step b, until convergence. Uncertainty is naturally incorporated in the preceding search as an integral ingredient of the DACE modeling approach.
To illustrate the proposed method, we show computer simulations based on simulated data for a tight gas field. The work presented is done in collaboration with Texas A&M University, Lawrence Berkeley Lab, and Anadarko under funding from RPSEA.
Layered silicates (LS) modified by alkyl chain (C14 – C18) was introduced in immiscible PS-PMMA blends. The LS planar surface prefers PS phase over PMMA phase and the hydroxyl edges favor PMMA phase. Hence, when PS dominates in the blends, electron micrographs show the LS stay in PS phase, and melt-state rheological behavior of the blends, especially the relaxation behavior of discrete phase at low frequency region, is not affected by the added LS. However, when volume fraction of PMMA increases and PS becomes discrete phase, LS tend to segregate at the interface between PS and PMMA. Electron micrographs reveal well dispersed silicate sheets locating at the interface between small PS domains in the PMMA phase. Linear dynamic rheological data of these samples show significant increase in the low-frequency modulus of the blends with added LS. A thermodynamic model for estimating the interfacial modulus is proposed and the results agree well with the interfacial modulus calculated by Palierne’s emulsion model. Mechanical properties show plasticizing effects at low LS content, converting to brittle behaviors when increasing LS loading.
Diesel fueled, compression ignition engines are more efficient than their gasoline powered, spark ignition counterparts. This has led to their use in most heavy duty vehicles for transportation and construction, and an increasing presence in passenger vehicles. The emissions produced by diesel engines contribute to pollution problems, especially particulate matter (PM) and oxides of nitrogen (NOx). Carbon monoxide (CO) and volatile hydrocarbons are also present in exhaust. The production of carbon dioxide (CO2) by fossil fuel combustion is also of concern due to its potential role in climate change. One approach to reducing emissions is to change the fuel source. Alternative diesel fuels, including biodiesel made from various feedstocks (soy, canola, palm, and tallow) and gas-to-liquids (GTL) fuel, were compared to petroleum-based Texas Low Emission Diesel (TxLED) in terms of emissions and fuel consumption. The chemical structure of the fuels, as well as parameters such as density and heat of combustion can help to explain the differing performance. At high power output, NOx emissions decreased for GTL diesel and for biodiesel made from palm and tallow feedstocks, while a small increase remained for biodiesel made from the soy and canola feedstocks. Emissions of CO and hydrocarbons decreased for all alternative diesel fuels at both low and high power outputs. Determining the hydrocarbon species present in real exhaust is important because it can affect the catalytic activity of emissions control systems. Ethene, pentane, formaldehyde, and acetaldehyde had the highest concentration of the hydrocarbon species detected.
Many diagnostic technologies rely upon labels attached to biomolecules or pathogens to make them easily detectable. Although widely useful and well-developed, such systems can suffer from low signal strength and label instability, and elaborate instrumentation is often required for detection. We are developing a potentially-superior label system based upon arrays of corner-cube micro-retroreflectors which reflect incident light in a narrow beam directly back to its source, making them extremely detectable. Microfabrication of such a system would allow for the fabrication of labels with potentially superior performance in immunoassay and microarray applications, detectable with simple, inexpensive low-NA instrumentation. We have fabricated arrays of micron-sized corner-cube retro-reflectors on silicon wafers where one of the reflective surfaces is decorated with antibodies that capture the target, and the remainder of the surface is passivated against adsorption. Magnetic sample-prep particles or gold nanoparticles, also decorated with anti-target antibodies, can assemble on the surface in the presence of the target and substantially reduce reflectivity; this effect can be further enhanced by silver intensification. Single bacteria produce an optical signal detectable with high statistical confidence, though ROC calculation will be required to choose the detection threshold. Specificity is enhanced by magnetic and shear force discrimination against non-specifically adsorbed reporters. For further discrimination against non-specific signals, retroreflectors are arranged in tetrads of three always-on reference control retroreflectors surrounding one analyte-responsive active reflector. The microfabrication process also can incorporate bar-coding for identification of multiple analytes. Shear force discrimination, reproducibility, and convenience are enhanced by the implementation of the technology in a microfluidic cartridge format.
1Research Experience for Teachers (RET) Program. 2Graduate Student, Department of Chemical Engineering, University of Houston. 3KIPP Houston High School Student. 4Asst. Professor, Department of Chemical Engineering, University of Houston
The effect of selected organic amine additives on silicalite-1 crystals is investigated in this research through aspect ratio measurements and SEM image analysis. Though various silicalite-1 synthesis procedures have been explored, the effect of a variety of organic amines in crystal structure formation of zeolites has not been investigated in depth. Tailored organoamines: branched and linear polyethyleneimine, diethanolamine, and spermine, were used as additives in the hydrothermal synthesis of silicalite-1 crystals.
The study revealed the potential influence of organoamines on the dimensions of silicalite-1 crystals. In particular, the use of spermine resulted in a monodispersed crystal–size, and decreased thickness, while maintaining overall crystal morphology and aspect ratio.
1. Department of Chemical and Biomolecular Engineering, University of Houston, Houston, TX
2. National Institute of Standards and Technology (NIST), Gaithersburg, MD
Observations of changes in the Tg of ultra thin films have been explained by two main theories. The first points to molecule-surface interactions as the cause of changes in dynamics, while the second indicates that confinement by substrates and the effect of the free surface are key. The expansive surface area of nanoparticles provides a way to modify dynamics in the bulk in a similar way as that observed in thin films. In order to directly compare the proposed theories, nanocomposites (NCs) were made using C60 Buckminsterfullerene and single-walled carbon nanotubes (SWNTs) in the epoxy Bis[4-(glycidyloxy)phenyl]methane, a glass-forming liquid. We take carbon C60 spheres and SWNTs to represent high surface-area materials and high volume (volumeconfinement) materials, respectively. C60 nanoparticles have 1.5 times more surface area per unit volume than nanotubes yet quasielastic neutron scattering (QENS) measurements reveal that the local dynamics of glass-forming liquids dispersed with SWNTs are more retarded than those made with C60, indicating that nanoscale confinement is at the crux of the observed changes in the dynamics of bulk and thin film nanocomposites of glassforming liquids above the glass-transition temperature.
Piezoelectric polymers are of great interest for advancing the field of smart and active materials systems. Piezoelectric polymers offer the benefits of low power requirements, high voltage sensitivity, fast electro-mechanical response, mechanical strength, and ease of processing. The right combination of material properties would garner the potential to greatly affect work in the fields of integrated smart structures that would not only provide lightweight mechanical reinforcement, but also shape control as well as embedded sensing and energy harvesting functionality.
Calorimetric as well as wide and small angle X-ray scattering techniques are used to observe the effects of different nanoparticles on the crystallization of PVDF in order to understand the impact of such additions on the material’s morphology as part of a larger effort moving toward truly active, multi-functional, smart materials with intelligently tailored properties.
We develop a semi-empirical complete rheological model for diverting acids that accounts for the effects of change in temperature, shear rate/pressure drop, and pH/concentration on its viscosity. We also modify a previously developed two-scale continuum model to include diverting behaviors and analyze the stimulation of single/dual core set-ups with both Newtonian and diverting acids at constant injection rate and constant pressure drop. We show that when dual core set-ups are stimulated with diverting acids, flow is diverted from high-perm core to low-perm core and from low-perm core to high-perm core until the exit concentration exceeds a certain value that depends on the fluid characteristics. Finally, we show that the acidization curve for the case of constant injection rate is independent of initial permeability while for the case of constant pressure drop it becomes shallower with the decrease in initial permeability.