Browsing by Department "Chemical Engineering"

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The 2017 Arkema Plant Explosion following Hurricane Harvey in Crosby, Texas
(2018) Garza, Emily; Saad, Joseph; Kulhanek, Makenzie
In August of 2017, Hurricane Harvey brought destruction to southeast Texas. With the hurricane came extremely high water levels that the Crosby plant was not prepared for. In addition to underestimating the floodwaters, Arkema had not anticipated a total power outage at the plant. The Crosby plant housed thousands of pounds of organic peroxides, a chemical that is highly reactive and instable at temperatures above freezing. As water surrounded the emergency refrigeration trailers where organic peroxides had been moved to, temperatures inside the trailers increased and the peroxides began to self-heat, decompose, and combust. The combustion of three trailers caused an explosion whose effects are still felt in the Crosby community. The purpose of this report is to examine the decisions made by Arkema Chemical, using the AIChE code of ethics. Their decisions in preparation for Hurricane Harvey, during the hurricane and explosion, and after the explosion will be analyzed. Arkema acted unethically by not having the right preparations for Hurricane Harvey and not dealing with any after- effects on the community. If Arkema had reexamined their safety protocols after receiving ten OSHA violations, the result may have been different. Although Arkema employees acted ethically during their emergency response to Hurricane Harvey, they neither prepared sufficiently for intense flooding nor responded adequately to the after- effects on the community. Today, the Crosby plant is still running, but the explosion has not only made Arkema review their plans for natural disasters and general safety, but has made the entire chemical industry more aware of the need to be prepared for disasters no matter how improbable they may seem.
A design model for dividing wall distillation columns
(2017-10-03) Roach, Bailee Jeanee; Baldea, Michael; Eldridge, R. Bruce; Seibert, Albert F; Bonnecaze, Roger T; Rochelle, Gary T; Owens, Scott A
Traditionally, the production of three high purity products from a three component mixture requires the use of two distillation columns. A Dividing Wall Column (DWC) offers an alternative to this approach. The DWC contains a vertical partition, dividing the column into two sides. The feed side separates the lowest and highest boiling products, while the product side separates the intermediate component. This configuration reduces capital costs by utilizing only one column, reboiler, and condenser and reduces the thermodynamic losses by partitioning the feed and side product. Previous theoretical studies have found that a DWC can also produce as high as 30-50 percent energy savings over a traditional multi-column scheme. Despite these advantages, validated predictive models, which will facilitate widespread adoption of the technology, are lacking. In this research, experimental results were obtained over a wide range of operating conditions using a constructed six inch diameter pilot plant data is used to develop a fully validated DWC. The pilot DWC ran several experimental tests with both an alcohol and hydrocarbon feed. Both systems were tested with an equimolar and a 10/80/10 feed composition. Internal flow rate and composition data were available that has not been published in research, allowing for a complete model validation, including heat loss and heat transfer across the dividing wall. Both Model Predictive Control and traditional PID control was tested and resulted in high quality steady state data obtained. An extensive hydraulic study was conducted for both structured and random packing. Mass transfer studies and air-water experiments were conducted to fundamentally characterize the column hydraulics. These studies included confirming the vapor split is determined by the wall location and not impacted by the pressure drop. Pressure drop and wetted area studies were performed on circular and dividing wall column structures. The dry pressure drop, irrigated pressure drop, and hold-up were compared with existing correlations. Additionally, the dividing wall wetted area was determined. A DWC model was validated with the experimental pilot data obtained as well as comparing with open literature data. With the results from the validated model, optimizations were conducted to aid in DWC design. It was shown that feed temperature is an important variable to consider in design. The vapor split did not have as much of an impact on energy savings as the liquid split. An accurate energy calculation was performed on a pilot scale column and a scale-up to industrial column diameters. The scale-up shows that the impacts from heat loss and heat transfer are not as significant in a large scale column for product purities and column liquid and vapor loads. DWC columns averaged approximately 30% energy savings. The comprehensive validated model lays the groundwork for DWC industrial expansion.
A mathematical model for magnetically-assisted delivery of thrombolytics in occluded blood vessels for ischemic stroke treatment
(2016-02-23) Clements, Michael Jeffrey; Bonnecaze, R. T. (Roger T.); Creighton, Francis; Ganesan, Venkat; Heller, Adam; Peppas, Nicholas A
Currently, the most popular method of ischemic stroke treatment is intravenous administration of thrombolytics like alteplase. Once administered, the rate of thrombolytic delivery to a clot in a fully occluded vessel is limited by the slow process of diffusion. This is problematic as increased duration of the hypoxic state due to a thrombus or embolus increases the likelihood of severe disability and death. The transport of the drug could be improved by inducing fluid flow within the blocked vessel. This could be accomplished by utilizing a methodology invented by Pulse Therapeutics. Ferroparticles are administered along with the thrombolytic, and a rotating magnetic field with a gradient is applied to the affected region of the stroke victim’s brain. The presence of the magnetic field causes the ferroparticles to aggregate. Its rotation causes the aggregates to rotate, and its gradient causes the rotating aggregates to produce a net unidirectional flow within the blocked vessel. A general analytical model describing this process is developed to assist prediction of the qualitative effect of changing various system parameters like the magnetic field strength or rotation rate. Increasingly complex two-dimensional models are developed and computationally analyzed to quantitatively predict the resulting velocity profile in a blocked vessel. Computational analyses were also performed to simulate the diffusion-limited and magnetically-enhanced transport of thrombolytics. As anticipated, utilizing the rotating magnetic field with a gradient significantly improves transport in a blocked vessel.
A parallel eigensolver for real-space pseudopotential density functional theory calculations
(2022-06-23) Liou, Kai-Hsin; Chelikowsky, James R.; Demkov, Alexander A.; Hwang, Gyeong S.; Korgel, Brian A.
First-principles electronic structure calculations are a popular tool for understanding and predicting properties of materials. Among such methods, the combination of real-space density functional theory and pseudopotentials to solve the Kohn–Sham equation has several advantages. Real-space methods, such as finite differences and finite elements, avoid the global communication needed in fast Fourier transformation and offer better scalability for large calculations on hundreds or thousands of compute nodes. Besides, finite-difference methods with a uniform real-space grid are easy to implement, e.g., the convergence of a Kohn–Sham solution is controlled by a single parameter – the grid spacing. One promising algorithm for solving the Kohn–Sham eigenvalue problem in real space is the Chebyshev-filtered subspace iteration method (CheFSI). Within this algorithm, the charge density is constructed without regard to a solution for individual eigenvalues. However, for large systems CheFSI may suffer from super-linear scaling operations such as orthonormalization and the Rayleigh–Ritz procedure. In the dissertation I will present two improvements in CheFSI to enhance its scalability and accelerate calculation. The first one is a hybrid method that combines a spectrum slicing method and CheFSI. The spectrum slicing method divides a Kohn–Sham eigenvalue problem into subproblems, wherein each subproblem can be solved in parallel using CheFSI. We will show that, by the simulations of confined systems with thousands of atoms, this hybrid method can be faster and possesses better scalability than CheFSI. The second improvement is a grid partitioning method based on space-filling curves. Space-filling curves based grid partitioning improves the efficiency of the sparse matrix–vector multiplication, which is the key component of CheFSI. We will show that, by computations of confined systems with 50,000 atoms or 200,000 electrons, this method effectively reduces the communication overhead and improves the utilization of the vector processing capabilities provided by most modern parallel computers. Along with the improvements, I will also present three applications. One is the study of the evolution of density of states of silicon nanocrystals from small ones to their bulk limit. The simulations can hardly be performed without the improvement in sparse matrix–vector multiplication enhanced by space-filling curves based grid partitioning. The other two applications are the studies of proton transfer in liquid water and the adsorption of water on titanium dioxide surfaces.
A system for humid CO2 sorption for direct air capture
(2024) Lopez-Marques, Horacio; Gleason, Kristofer L.; Kumar, Manish; Freeman, Benny
Direct Air Capture (DAC) is gaining attention for reducing CO2 concentration in the atmosphere to limit global warming. In DAC, sorbents are exposed to ambient air with a CO2 concentration of approximately 400 ppm and different levels of relative humidity (%RH). There are many reports on pure water and pure CO2 sorption in sorbents, but reports on mixed water and CO2 sorption are very limited due to the difficulty of obtaining accurate experimental data, and the need for careful design of custom-made equipment. However, humidity can impact the sorption capacity of sorbents in different ways depending on the type of sorbent used, and such effects must be considered in the modeling and design of DAC systems. Here, we describe the construction and operation of a multicomponent closed system to determine CO2 sorption in sorbent materials as a function of water activity, CO2 partial pressure, and temperature. An Infrared Gas Analyzer (IRGA), with a CO2 concentration measurement range of 0 to 20,000 ppm, which is relevant for DAC conditions, was incorporated into the system to measure CO2 and water concentration in real time without altering experimental conditions due to gas sampling. Blank experiments were successfully conducted to show that no CO2 and/or water adsorb in the system itself, and any change in gas concentration is due to sorption in the sorbent. To validate system operation, CO2 sorption capacities in a commercial material were conducted, and the results were compared to a literature report, yielding satisfactory agreement.
Ab initio simulation methods for the electronic and structural properties of materials applied to molecules, clusters, nanocrystals, and liquids
(2014-05) Kim, Minjung, active 21st century; Chelikowsky, James R.
Computational approaches play an important role in today's materials science owing to the remarkable advances in modern supercomputing architecture and algorithms. Ab initio simulations solely based on a quantum description of matter are now very able to tackle materials problems in which the system contains up to a few thousands atoms. This dissertation aims to address the modern electronic structure calculation methods applied to a range of various materials such as liquid and amorphous phase materials, nanostructures, and small organic molecules. Our simulations were performed within the density functional theory framework, emphasizing the use of real-space ab initio pseudopotentials. On the first part of our study, we performed liquid and amorphous phase simulations by employing a molecular dynamics technique accelerated by a Chebyshev-subspace filtering algorithm. We applied this technique to find l- and a- SiO₂ structural properties that were in a good agreement with experiments. On the second part, we studied nanostructured semiconducting oxide materials, i.e., SnO₂ and TiO₂, focusing on the electronic structures and optical properties. Lastly, we developed an efficient simulation method for non-contact atomic force microscopy. This fast and simple method was found to be a very powerful tool for predicting AFM images for many surface and molecular systems.
Absorber and aerosol modeling in amine scrubbing for carbon capture
(2018-08) Zhang, Yue, 1992-; Rochelle, Gary T.; Hildebrandt Ruiz, Lea; Bonnecaze, Roger; Svendsen , Hallvard
A rate-based PZ aerosol growth model was developed in gPROMS [superscript ®] ModelBuilder. Amine Aerosol growth was simulated at the unique conditions of piperazine (PZ) and the pilot plant absorber configurations at the National Carbon Capture Center. Amine aerosol growth is driven by amine-limited diffusion. As aerosol concentration increases, aerosol growth decreases due to the depletion of the amine driving force in the gas phase. Aerosol growth can be increased by enhancing the gas-film mass transfer coefficient of packing. A solvent with moderate volatility, like PZ, will produce aerosol that grows to larger size and is easier to collect. Solvents with low volatility should be avoided as they produce aerosol that is hard to collect. Process configurations that provide greater water partial pressure in the water wash, such as higher operating temperature and pre-humidified empty space, will help aerosol grow. Two pilot plant campaigns were designed and conducted in this work. 5 molal (m) PZ was operated for the first time and provided significant absorber performance benefits over 8 m PZ due to enhanced mass transfer rates from lower solvent viscosity. Parametric tests were performed with a wide range of absorber operating conditions. With the existing model correction, the pilot plant absorber model could reasonably capture the measured absorber performance. For future campaigns, this work recommended that the pilot plant absorber should be operated at both pinched and not pinched conditions. Both equilibrium correction (correct for errors in solvent loading measurements and effects of degradation) and packing correction (correct for effects of rivulets and drop and additional mass transfer caused by distributors and chimney trays) should be utilized in the data reconciliation process. A membrane-amine hybrid carbon capture system for natural gas combined cycle (NGCC) power plants was proposed and evaluated. When the inlet CO2 increases from 4% to 18%, the total absorption costs decrease by 60% and the total regeneration costs remain the same. Amine scrubbing without the direct contact cooler was found to be a superior design for NGCC carbon capture. The absorber gas inlet must be designed to avoid excessive localized temperature and solvent evaporation.
Absorber modeling and design in amine scrubbing for carbon capture
(2021-08-13) Gao, Tianyu; Rochelle, Gary T.; Baldea, Michael; Bonnecaze, Roger T; Bun, Betty K
Absorber design is associated with the most important trade-off between capital and operating cost for CO₂ capture by amine scrubbing process. A rate-based absorber model using aqueous piperazine (PZ) has been developed prior to this work. The model is built from bench-scale or small pilot-scale experiments using “bottom-up” strategies and can be improved by larger scale pilot plant experiments. Three pilot plant campaigns were designed and conducted in this work for model validation and improvement. By identifying the systematic bias of solvent equilibrium and applying one adjustable parameter on PZ concentration (8% for NCCC 2019 and SRP 2018, 3% for NCCC 2018), the model can predict the absorber number of transfer units (NTU) and temperature profile with good accuracy. The packing performance model was also validated using experiments running with less packing area that are away from mass transfer pinch. With pilot plant experiments and process modeling, the absorber design using pump-around absorber with hot flue gas inlet was demonstrated as a superior configuration for flue gas with 4% CO₂. The pump-around increases the liquid flow and provides effective cooling to the absorber. This configuration was used to design the first-of-its-kind commercial scale absorber in west Texas. The design requires only 25 ft packing, eliminates direct contact cooler and trim cooler to reduce capital cost, and uses 0.2 lean loading, low pump-around temperature (30 °C), and high pump-around rate to improve the performance and to reduce the operating cost. The hybrid and crossflow absorbers were proposed and simulated as an intensification of the pump-around absorber. The hybrid absorber can be as effective as the pump-around absorber but is constrained by intercooling temperature and water balance. The crossflow absorber features small size and high velocity and is favored when the capital cost is relatively high. Achieving higher removal using amine scrubbing was studied using both PZ and MEA solvent, and the optimal CO₂ removal was found above 90% (95% for coal and 93% for gas). Zero emission of power plant was feasible using amine scrubbing with an overall cost of 50.4 $/tonne and should be considered before deploying other direct air capture technologies.
Absorber performance and configurations for CO2 capture using aqueous piperazine
(2016-05) Sachde, Darshan Jitendra; Rochelle, Gary T.; Baldea, Michael; Bhown, Abhoyjit; Chen, Eric; Hwang, Gyeong
Absorber design for CO2 capture with amine solvents is complicated by the presence of temperature gradients and multiple rate controlling mechanisms (chemical reaction and convective mass transfer). The development of rigorous rate-based models has created the opportunity to study the performance limiting mechanisms in detail. A structured approach was developed to validate absorber models, identify limiting phenomena, and develop configurations that specifically address limiting mechanisms. A rate-based model utilizing concentrated aqueous piperazine (PZ) was the focus of model validation and process development. The model was validated using pilot plant data, matching the number of transfer units (NTU) within + 1% while identifying a systematic bias (loading measurement) between the model and pilot plant data. The validated model was used to define limiting cases (isothermal and adiabatic absorbers) to study the effects of operating conditions on the formation of temperature-induced mass transfer pinches. The method allowed for screening of intercooling benefits – high CO2 applications (15% - 27% CO2) require intercooling over the entire practical loading range for PZ and benefit significantly from simple in-and-out intercooling with limited additional benefit expected from advanced design. Low CO2 (4% CO2) applications are expected to benefit the most from improved intercooling, but also have the largest operating window without the need for intercooling (< 0.22 mol CO2/mol alkalinity for 8 m PZ). An analogous approach was developed to study rate mechanisms. A mass transfer parameter sensitivity analysis approach was developed to identify the relative contribution to overall mass transfer resistance of each mechanism as a function of operating conditions and position in the absorber column. The pseudo-first order and instantaneous reaction asymptotic solutions to the reaction-diffusion problem were used to define a dimensionless parameter that quantifies the approach of the modeling results to the limiting conditions and was found to be predictive of the relative liquid film resistance (diffusion vs. reaction) at all conditions. The results of the analysis indicated that the absorber is strongly diffusion controlled, has limited gas-film resistance, and that equilibrium constraints at the rich end of the absorber (depletion of free amine) significantly increase diffusion limitations. Finally, the validation and mechanistic studies provided the basis for four new absorber configurations: 1) integration of a spray nozzle in the intercooling loop, 2) solvent recycle intercooling, 3) integrated flue gas and solvent cooling functions, 4) hybrid intercooling (high intensity contacting with intercooling). Each approach coupled mass transfer enhancement with intercooling and provided new degrees of freedom for operation and design of absorbers for CO2 capture.
Absorption of chlorine and mercury in sulfite solutions
(2002-08) Roy, Sharmistha; Rochelle, Gary T.
Accounting for Ion Pairing Effects on Sulfate Salt Sorption in Cation Exchange Membranes
(American Chemical Society, 2023) Sujanani, Rahul; Nordness, Oscar; Miranda, Andres; Katz, Lynn E.; Brennecke, Joan F.; Freeman, Benny D.
Ion exchange membranes (IEMs) are frequently used in water treatment and electrochemical applications, with their ion separation properties largely governed by equilibrium ion partitioning between a membrane and contiguous solution. Despite an expansive literature on IEMs, the influence of electrolyte association (i.e., ion pairing) on ion sorption remains relatively unexplored. In this study, salt sorption in two commercial cation exchange membranes equilibrated with 0.01−1.0 M MgSO4 and Na2SO4 is investigated experimentally and theoretically. Association measurements of salt solutions using conductometric experiments and the Stokes−Einstein approximation show significant concentrations of ion pairs in MgSO4 and Na2SO4 relative to those in simple electrolytes (i.e., NaCl), which is consistent with prior studies of sulfate salts. The Manning/Donnan model, developed and validated for halide salts in previous studies, substantially underpredicts sulfate sorption measurements, presumably due to ion pairing effects not accounted for in this established theory. These findings suggest that ion pairing can enhance salt sorption in IEMs due to partitioning of reduced valence species. By reformulating the Donnan and Manning models, a theoretical framework for predicting salt sorption in IEMs that explicitly considers electrolyte association is developed. Remarkably, theoretical predictions of sulfate sorption are improved by over an order of magnitude by accounting for ion speciation. In some cases, good quantitative agreement is observed between theoretical and experimental values for external salt concentrations between 0.1 and 1.0 M using no adjustable parameters.
Activity coefficients and Distex equilibria of some C₆ and C₇ hydrocarbons in aniline
(1946) Randall, Bill R., 1919-; Griswold, John, 1906-
Adaptive run-to-run control of overlay in semiconductor manufacturing
(2002) Martinez, Victor Manuel; Edgar, Thomas F.
Addressing intrinsic challenges for next generation sequencing of immunoglobulin repertoires.
(2014-05) Chrysostomou, Constantine; Georgiou, George; Iverson, Brent L; Maynard, Jennifer A; Alper, Hal S; Mullins, Charles B
Antibodies are essential molecules that help to provide immunity against a vast population of environmental pathogens. This antibody conferred protection is dependent upon genetic diversification mechanisms that produce an impressive repertoire of lymphocytes expressing unique B-cell receptors. The advent of high throughput sequencing has enabled researchers to sequence populations of B-cell receptors at an unprecedented depth. Such investigations can be used to expand our understanding of mechanistic processes governing adaptive immunity, characterization of immunity related disorders, and the discovery of antibodies specific to antigens of interest. However, next generation sequencing of immunological repertoires is not without its challenges. For example, it is especially difficult to identify biologically relevant features within large datasets. Additionally, within the immunology community, there is a severe lack of standardized and easily accessible bioinformatics analysis pipelines. In this work, we present methods which address many of these concerns. First, we present robust statistical methods for the comparison of immunoglobulin repertoires. Specifically, we quantified the overlap between the antibody heavy chain variable domain (V H ) repertoire of antibody secreting plasma cells isolated from the bone marrow, lymph nodes, and spleen lymphoid tissues of immunized mice. Statistical analysis showed significantly more overlap between the bone marrow and spleen VH repertoires as compared to the lymph node repertoires. Moreover, we identified and synthesized antigen-specific antibodies from the repertoire of a mouse that showed a convergence of highly frequent VH sequences in all three tissues. Second, we introduce a novel algorithm for the rapid and accurate alignment of VH sequences to their respective germline genes. Our tests show that gene assignments reported from this algorithm were more than 99% identical to assignments determined using the well-validated IMGT software, and yet the algorithm is five times faster than an IgBlast based analysis. Finally, in an effort to introduce methods for the standardization, transparency, and replication of future repertoire studies, we have built a cloud-based pipeline of bioinformatics tools specific to immunoglobulin repertoire studies. These tools provide solutions for data curation and long-term storage of immunological sequencing data in a database, annotation of sequences with biologically relevant features, and analysis of repertoire experiments.
Addressing uncertainty and modeling error in the design and control of process systems : methods and applications
(2016-08) Wang, Siyun, Ph.D.; Baldea, Michael; Edgar, Thomas F.; Rochelle, Gary T.; Truskett, Thomas M.; Biros, George
A process system faces the challenge of uncertainty throughout its lifetime. At the design stage, uncertainty originates from inaccurate knowledge of design parameters and unmeasured or unmeasurable ambient disturbances. Oftentimes, designers choose to increase system size to account for uncertainty and fluctuations; however, this approach has an economic limit, past which the capital expenditure outweighs the potential operational benefits. In the operational stage, uncertainty is manifest, amongst others, in fluctuations in operating conditions, market demand and raw material availability. Another type of uncertainty in (modern) process operations is related to the quality of process models that are used for making control and operational decisions. Of particular importance is the quality of the dynamic models that are used in real-time optimal control computations. The chemical industry has been the pioneer (and is currently the leader) of model predictive control (MPC) implementations, whereby the control moves are computed, over a receding time horizon, by solving an optimal control problem at each time step. While uniquely able to deal with large-scale, non-square constrained systems, MPC is vitally dependent on the predictive abilities of the built-in model. Changes in plant conditions are a a source of uncertainty in this case as-well, leading to a discrepancy (mismatch) between the model predictions and the true plant behavior. In this dissertation, I address the problems of design under uncertainty and plant-model mismatch. For the former, identification-based optimization (IBO) framework is proposed as a new, computationally efficient framework for optimizing the design of dynamic systems under uncertainty problem. The framework uses properly designed pseudo-random multilevel signals (PRMS) to represent time-varying uncertain variables. This allows us to formulate the design under uncertainty problem as a dynamic optimization problem. A solution algorithm is proposed using a sequential approach. Several application examples are discussed, demonstrating the superior computational performance of the IBO approach. Furthermore, an extension of the method that explicitly considers the tradeoff between conservativeness and dynamic performance is introduced. The latter, plant-model mismatch problem, is addressed using a novel autocovariance-based approach. Under appropriate assumptions, an explicit relation is established between the autocovariance of the process output and the plant-model mismatch terms, represented either in a step response model or a transfer function model. It is demonstrated that an asymptotically correct set of estimates of the values of plant-model mismatch for each model parameters is the global minimizer of the discrepancy between the autocovariance predicted using the relation and the autocovariance calculated from a data set collected from closed-loop operating data. Extensions of this approach handle cases where the active set of the MPC is changing over time and there are setpoint change and measurable disturbances occur in the control loop.
Advanced analysis of structured packing via computational fluid dynamics simulation
(2010-12) Owens, Scott Allen, 1982-; Eldridge, R. Bruce; Bonnecaze, R. T. (Roger T.); Rochelle, Gary; Ganesan, Venkat; Seibert, Frank; Loescher, Mitch
This research explored the use of CFD simulations to study single phase flows through structured packing. Flow rates were chosen to approximate those used in the vapor phase of industrial distillation columns. The results were evaluated against experimental results obtained with the same packing model and packed height. Several novel methods were employed to quickly obtain high validity results. A high-fidelity, digital copy of an actual packing element was created in seven hours through CT scanning. The meshing strategy employed adaptive, polyhedral meshing algorithms which resulted in high quality volume meshes with 80 percent less mesh elements than would be required with traditional tetrahedral meshing. Meshing and computation were performed on the TACC clusters. The permitted meshing with up to 57 million volume cells in less than 30 hours while simulations employing a realizable k-[epsilon] model converged in approximately two days using up to 544 processors. Nitrogen simulation predictions were found to be, on average, 7 percent below experimental measurements with water simulations showing considerably more error (~40%). The error is likely attributable a discrepancy between the simulation and experimental geometries. This discrepancy is due to an oversight in sample preparation and not a flaw in the CT scanning process of geometry creation. The volume of data generated in CFD simulation was found to be very valuable for understanding and benchmarking packing performance. Streamlines and contour plots were used to analyze the variation in performance both locally and throughout the packing stack. Significant variation was observed in flow pattern, velocity distribution, and pressure profiles throughout the column. However, the joint regions were found to be most adverse to column energy efficiency.
Advanced lithographic patterning technologies : materials and processes
(2007-05) Taylor, James Christopher, 1980-; Willson, C. G. (C. Grant), 1939-
Immersion lithography has emerged as the next technology to achieve the resolution improvement needed to produce smaller and faster microelectronic devices. It involves filling the air gap between the lens and photoresist-coated silicon wafer in a lithographic exposure tool with a higher refractive index medium. This improves the coupling of light into the resist and allows for better resolution. At the current exposure wavelength of 193 nm, water has been identified as the most promising immersion medium. Several potential issues had to be resolved before the process would be adopted. One was the unknown consequence of intimate contact between water and a photoresist. Any extraction of small molecule photoresist components by water could lead to a degradation of imaging performance and/or contamination. To address this, the possible extraction of several examples of these components from model 193 nm photoresists was studied by multiple experimental techniques including liquid chromatography/mass spectroscopy, scanning electrochemical microscopy and radiochemical analysis. It was found that both a photoacid generator and a base additive were extracted in small quantities. A study of the optical properties of water-based solutions with ionic additives was then undertaken. This study was intended to identify fluids with a higher index than water for greater resolution improvement. The solutions had higher index values, though typically with prohibitively high absorbance. The survey did lead to a series of methylsulfonate salts with some of the highest index values paired with low absorbance found for these materials. However, none of the target fluid properties were reached, so a theoretical approach was then used to model the properties of an ideal additive. This model served as a guide to identify a new type of additive with both a high index and low absorbance. The principles used for a high index/low absorbance additive were then applied to fabricate a polymer photonic device. A photonic crystal structure was designed for a polymer with an additive. A process for fabricating it was then developed using step and flash imprint lithography. The process development included a demonstration of a template created with a negative tone electron beam lithography process.
Advanced lithographic patterning technologies: materials and processes
(2007) Taylor, James Christopher; Willson, C. G. (C. Grant), 1939-
Immersion lithography has emerged as the next technology to achieve the resolution improvement needed to produce smaller and faster microelectronic devices. It involves filling the air gap between the lens and photoresist-coated silicon wafer in a lithographic exposure tool with a higher refractive index medium. This improves the coupling of light into the resist and allows for better resolution. At the current exposure wavelength of 193 nm, water has been identified as the most promising immersion medium. Several potential issues had to be resolved before the process would be adopted. One was the unknown consequence of intimate contact between water and a photoresist. Any extraction of small molecule photoresist components by water could lead to a degradation of imaging performance and/or contamination. To address this, the possible extraction of several examples of these components from model 193 nm photoresists was studied by multiple experimental techniques including liquid chromatography/mass spectroscopy, scanning electrochemical microscopy and radiochemical analysis. It was found that both a photoacid generator and a base additive were extracted in small quantities. A study of the optical properties of water-based solutions with ionic additives was then undertaken. This study was intended to identify fluids with a higher index than water for greater resolution improvement. The solutions had higher index values, though typically with prohibitively high absorbance. The survey did lead to a series of methylsulfonate salts with some of the highest index values paired with low absorbance found for these materials. However, none of the target fluid properties were reached, so a theoretical approach was then used to model the properties of an ideal additive. This model served as a guide to identify a new type of additive with both a high index and low absorbance. The principles used for a high index/low absorbance additive were then applied to fabricate a polymer photonic device. A photonic crystal structure was designed for a polymer with an additive. A process for fabricating it was then developed using step and flash imprint lithography. The process development included a demonstration of a template created with a negative tone electron beam lithography process.
Advanced process control and optimal sampling in semiconductor manufacturing
(2008-08) Lee, Hyung Joo, 1979-; Edgar, Thomas F.
Semiconductor manufacturing is characterized by a dynamic, varying environment and the technology to produce integrated circuits is always shifting in response to the demand for faster and new products, and the time between the development of a new profitable method of manufacturing and its transfer to tangible production is very short. The semiconductor industry has adopted the use of advanced process control (APC), namely a set of automated methodologies to reach desired process goals in operating individual process steps. That is because the ultimate motivation for APC is improved device yield and a typical semiconductor manufacturing process can have several hundred unit processes, any of which could be a yield limiter if a given unit procedure is out of control. APC uses information about the materials to be processed, metrology data, and the desired output results to choose which model and control plan to employ. The current focus of APC for semiconductor manufacturers is run-to-run control. Many metrology applications have become key enablers for the conventionally labeled “value-added” processing steps in lithography and etch and are now integral parts of these processes. The economic advantage of effective metrology applications increases with the difficulty of the manufacturing process. Frequent measurement facilitates products reaching its target but it increases the cost and cycle time. If lots of measurements are skipped, the product quality does not be guaranteed due to process error from uncompensated drift and step disturbance. Thus, it is necessary to optimize the sampling plan in order to quickly identify the sources of prediction errors and decrease the metrology cost and cycle time. The goal of this research intend to understand the relationship between metrology and advanced process control (APC) in semiconductor manufacturing and develop an enhanced sampling strategy in order to maximize the value of metrology and control for critical wafer features.
Advanced tabulation techniques for faster dynamic simulation, state estimation and flowsheet optimization
(2009-08) Abrol, Sidharth; Edgar, Thomas F.
Large-scale processes that are modeled using differential algebraic equations based on mass and energy balance calculations at times require excessive computation time to simulate. Depending on the complexity of the model, these simulations may require many iterations to converge and in some cases they may not converge at all. Application of a storage and retrieval technique, named in situ adaptive tabulation or ISAT is proposed for faster convergence of process simulation models. Comparison with neural networks is performed, and better performance using ISAT for extrapolation is shown. In particular, the requirement of real-time dynamic simulation is discussed for operating training simulators (OTS). Integration of ISAT to a process simulator (CHEMCAD®) using the input-output data only is shown. A regression technique based on partial least squares (PLS) is suggested to approximate the sensitivity without accessing the first-principles model. Different record distribution strategies to build an ISAT database are proposed and better performance using the suggested techniques is shown for different case studies. A modified ISAT algorithm (mISAT) is described to improve the retrieval rate, and its performance is compared with the original approach in a case study. State estimation is a key requirement of many process control and monitoring strategies. Different nonlinear state estimation techniques studied in the past are discussed with their relative advantages/disadvantages. A robust state estimation technique like moving horizon estimation (MHE) has a trade-off between accuracy of state estimates and the computational cost. Implementation of MHE based ISAT is shown for faster state estimation, with an accuracy same as that of MHE. Flowsheet optimization aims to optimize an objective or cost function by changing various independent process variables, subject to design and model constraints. Depending on the nonlinearity of the process units, an optimization routine can make a number of calls for flowsheet (simulation) convergence, thereby making the computation time prohibitive. Storage and retrieval of the simulation trajectories can speed-up process optimization, which is shown using a CHEMCAD® flowsheet. Online integration of an ISAT database to solve the simulation problem along with an outer-loop consisting of the optimization routine is shown using the sequential-modular approach.