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Chemical Workbench––integrated environment for materials science
Computational Materials Science 28 (2003) 169–178 www.elsevier.com/locate/commatsci
Chemical Workbench––integrated environment for materials science M. Deminsky a,*, V. Chorkov b, G. Belov c, I. Cheshigin b, A. Knizhnik b, E. Shulakova b, M. Shulakov b, I. Iskandarova b, V. Alexandrov b, A. Petrusev a, I. Kirillov a, M. Strelkova a, S. Umanski d, B. Potapkin a a
c
RRC ‘‘Kurchatov Institute’’, Kurchatov Sq. 1, 123182 Moscow, Russia b Kinetic Technologies, Kurchatov Sq. 1, 123182 Moscow, Russia Thermocentre, IHED, IVTAN Association of RAS, Izhorskaya 13/19, 127412 Moscow, Russia d N.N. Semenov Institute of Chemical Physics of RAS, Kosygina 4, 117977 Moscow, Russia
Abstract Current environmental problems and industrial needs require the permanent modification and improvement of existing technologies or the implementation and design of new technological methods. One of the most effective and cheapest ways to meet real practical requests and needs and development of new methods is balanced combination of experimental investigation and computer-aided simulation and technology design. In turn, the best way to develop a simulation tool for a new chemical process is to use an integrated simulation environment, which incorporates all necessary functionality and thus can reduce the cost of the development of a new model. 2003 Elsevier B.V. All rights reserved. Keywords: Chemical kinetics; Thermodynamics; Computer-aided simulation; Database
1. Introduction Principal modeling demands for the integrated simulation platform can be formulated like: (1) flexibility of the model set, (2) built-in information support, (3) built-in instruments for sensitivity investigation,
*
Corresponding author. Address: Kinetic Technologies, Kurchatov Sq. 1, 123182 Moscow, Russia. E-mail address: [email protected] (M. Deminsky).
(4) user-friendly interface for model development and simulation control, (5) openness of the system for user modules and data. The first requirement means the adaptability of the system to simulate different chemical processes based on the integrated set of reactor models. Therefore, an integrated system should have a comprehensive set of basic reactor models, which should cover all possible chemical processes. This set usually includes thermodynamic and kinetic reactors, which describe chemical reactions in homoand heterogeneous systems. The key feature here is
0927-0256/$ - see front matter 2003 Elsevier B.V. All rights reserved. doi:10.1016/S0927-0256(03)00105-8
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the possibility to develop a more complex reactor model based on these basic models. This feature strongly enhances the adaptability of the integrated simulation environment to real chemical processes and permits construction of technology chains from basic reactor modules simulating the separate steps of processes. The reactor models use practically the same physicochemical data in simulations, such as the thermodynamic energies of individual species, rate constants of a chemical reaction, density of species, chemical activity, etc. Thus, an integrated simulation system should provide built-in information support for all reactor models. This means that an integrated system should have a comprehensive set of databases of physicochemical properties with a unified interface to it. Completeness of databases is a key feature for a wide range of applications, but in reality it cannot be achieved. Therefore, the built-in information support must have special tools for data recovery from some fundamental information. Due to the increase of computational power, important of quantum chemical calculations, as source of such fundamental information, are going to be more important. Thus data recovery tools should be ready to utilize the results of quantum chemical simulation programs. An important question of computer-aided process design is the reliability of the calculated results. An integrated simulation environment should provide special methods for investigating the dependence of simulation results on the calculation parameters and initial data. These methods can be used, for example, to construct and reduce chemical mechanisms, determine key chemical reactions, and investigate the influence of stochastic factors. The main idea of an integrated system is to reduce the cost of the development of new models. One way to reduce the time of model development is to provide the user with a convenient visual interface for the complete cycle of chemically centered simulation. The visual interface should provide tools to construct the simulation model of a real chemical process using technology chains of basic reactor modules. This is the main way of improving system flexibility, and therefore the vi-
sual interface should facilitate this process for the user. Another important feature of the visual interface is to facilitate work with the integrated database and provide the user with powerful tools for database management. The final step of process simulation is investigation of calculation results, and the visual interface should provide comprehensive tools for data analysis and post-processing. The integrated set of reactor models cannot, of course, give a detailed description of some highly specialized chemical applications, and therefore the extendibility of the system is a key feature of the integrated system from userÕs point of view. The extendibility of the system is related to the openness of the program system, which is the possibility for the end user to develop his/her own modules based on the available information about reactor and database interfaces and exchange data flow and data formats. The Chemical Workbench code described in this work is an example of such an integrated system with an open platform architecture for modeling, optimization, and design of a wide range of industrial chemical processes, reactors, and technologies. The structure of the code (see Fig. 1) reflects the modular structure of the environment, which can be easily adapted to complex research tasks using available models and integrated visualization and database support. The user is responsible only for the creation of a sim-
Fig. 1. Structure of Chemical Workbench environment.
M. Deminsky et al. / Computational Materials Science 28 (2003) 169–178
ulation model of the process of interest connecting the universal reactor models with the coupling elements in the program window, and all required data are supplied by the environment from built-in information support. The code includes extended databases of physicochemical properties, which can be accessed by all reactors through universal data objects. Unavailable physicochemical data can be estimated with special data recovery tool (CARAT) in the built-in information support block (which can use results of ab initio calculations). The visualization and post-processing module permits thorough investigation and verification of simulation results, which can be saved in a database for further study. In the following section, we will show in detail how the structure of the Chemical Workbench code meets the above-mentioned requirements for an integrated simulation system. Then we will present an example of the application of the Chemical Workbench code [1] in computational materials science.
2. Structure of Chemical Workbench code A simulation model in the Chemical Workbench environment is described in terms of several user-controlled objects: calculations, reactors, streams, substances, and reactions. The reactor in the Chemical Workbench environment can be considered as a stream-manipulating object: each reactor has several inputs and outputs, which are connected to streams. Each reactor model has a set of parameters that determine the relationship between input and output streams. The stream object in the Chemical Workbench environment is the homogeneous/heterogeneous mixture of substances at given physical conditions (pressure, temperature, velocity, etc.). Each substance in the code is uniquely identified by chemical formula, charge, isomeric formula, and phase. The structure of Chemical Workbench code is closely related to the above-mentioned objects and provides convenient manipulation with these objects. In what follows, we will give the most attention to the reactor objects and the construction of the whole simulation model within the Chemical
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Workbench environment. This will also show how this environment satisfies the requirements for the integrated simulation environment. 2.1. Flexibility of models The main feature of an integrated environment, as was mentioned above, is the flexibility of the reactor models to user tasks. In the framework of Chemical Workbench code, the flexibility of the models is achieved by several approaches. The first approach consists in the construction of reactors chains from the set of available reactors and organization of flow-sheet diagrams. The second approach is related to the generality of the integrated model set. This means adaptability of reactor models to different possible real reactors. The third approach is based on assimilation of user-created models and will be considered below. 2.1.1. Construction of flow-sheet diagram Each reactor in the Chemical Workbench environment can be connected to other reactors by input and output streams; thus, several reactors can be connected in one chain. Interaction between models is carried out not only via ‘‘material streams’’ on flow-sheet diagram but also by input parameters of each reactor being given as arbitrary function of the results of any previous calculations. For example, in the case of energy exchange between reactors, energy input in one reactor can depend on the heat loss in the previous reactor. This relationship between reactor parameters is managed in the Data Explorer window in the graphical user interface (GUI), which will be described later. Two ‘‘material streams’’ can be merged in one stream in the mixer reactor, and one stream can be subdivided into two separate streams in the divider model. 2.1.2. Universality of models The set of reactor models in Chemical Workbench code contains two types of reactor model: one type describes models of abstract reactors, while the models of the second type correspond to concrete chemical reactors and processes. The first type of reactor model can be used for a wide range of chemical applications due to the universal
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underlying mathematical models. These models include equilibrium thermodynamic models (ideal, nonideal), homogenous and heterogeneous kinetic models (well-stirred reactor model, plug-flow reactor, calorimetric bomb with possible surface chemistry), catalytic reactors with fixed pellet bed, combustion and detonation reactors, and plasma and electron beam reactors. Models of this type can be used under different experimental conditions; for example, the plug flow reactor model can be applied as an isothermal reactor, a reactor under adiabatic conditions, or as a reactor with a user-defined function of temperature as a function of time. The model of more complex reactors can easily be constructed by connecting these models of abstract reactors in a reactor chain. Reactors of the second type are specialized for specific chemical applications and processes and have a narrower range of experimental conditions. Examples of these reactors include the Fischer– Tropsch reactor, plasma arc reactor, etc. The set of these reactors can be expanded by user-defined models for specific chemical applications. 2.2. Sensitivity analysis The Chemical Workbench code has several builtin tools to estimate the reliability of the calculated results. It is possible to investigate the dependence of simulation results on the reactor parameters and on the rate constants of chemical reactions. The first dependence is obtained in parameterized calculation of the given reactor with different reactor parameters. The dependence on the reaction rates is calculated using global kinetic sensitivity analysis of kinetic mechanisms. Sensitivity analysis of a chemical kinetic task is an algorithm for calculation of logarithmic derivatives lnðni Þ= lnðAj Þ, where ni is the final concentration of the ith substance and Aj is the pre-exponential factor of the jth chemical reaction. The calculation of the sensitivity coefficient matrix presents an opportunity to recognize the most and the least significant chemical reactions in the reactions list, as well as to evaluate the effect of reaction pre-exponent uncertainty on the result of the kinetic task solution. This information can be directly used in development and reduction of chemical mechanisms.
2.3. User-friendly interface One of the important features of the rapid visual design of chemical systems is the possibility of rapidly completing the cycle of the development of the simulation model, starting from the construction of the reactor chain, up to the visualization of the calculation results, and to return to the editing of the simulation model (connections between reactors, chemical mechanism, reactor parameters). To meet this requirement, all program components, from the editor of the flow-sheet diagram to the graphic visualization window, are realized in the framework of one program and are tightly integrated. 2.3.1. Object-oriented interface Modern program systems for scientific and technical investigations, despite being in different application fields, are similar due to the presence of a GUI. Existing GUIs strongly restrict the user in utilization of software components. The development of a GUI of the next generation with an object-oriented interface gives the user wider possibilities for the solution of the required tasks. The object-oriented user interface (OOUI) gives the users the freedom to manipulate available objects, and the representation of objects in the software program approaches their representation in the real world, thus facilitating the understanding of the program by the user and expanding the number of program users among nonspecialists in computer science. The OOUI also permits the user to create his own classes of objects on the basis of available objects without programming and hence to adapt the program to his own needs. 2.3.2. Structure of program interface The interface of the Chemical Workbench code consists of four main windows: Model Explorer (editor of connections between reactors), Data Explorer (editor of chemical mechanisms, reactor parameters, table data editor), Calculation Explorer (block of calculation run), and Result Explorer (visualization and post-processing of the results). The Model Explorer (Fig. 2) window is designed for selection and building of process mod-
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Fig. 2. Model Explorer window.
els. The given module includes the library of reactor models, which consists of several groups of reactors (thermodynamic reactors, kinetic, etc.). In the Model Explore window, the user sequentially selects the required reactor models, places them on the program table, and connects them. The integrated environment makes it possible to easily switch and edit the properties of each element on the program table (reactor parameters, its chemical mechanism, parameters of species flux). The Data Explorer (Fig. 3) window is designed for entering initial data and parameters for a calculation and consists of two parts. The left part of the window displays the data structure for the given calculation on one side, and on the another side is additional assistance for entering these data. The right part of the window displays the actual data. The type of the displayed data corresponds
Fig. 3. Data Explorer window.
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to the open folder in the left part of the window. The window is automatically adjusted depending on the type of the data in the editor window (species properties, reaction list, etc.). For reactors, there are special data recovery tools for estimation of unavailable thermodynamic and kinetic data. The Calculation Explorer window displays the conflicts in the input data detected at run time and permits the user to control the calculation process. The Result Explorer (Fig. 4) window displays all results of a calculation. These results can be presented both in text style in the table and in graphic view. Moreover, the results of the calculation can be exported in xls, mdb, and txt formats. With the use of the post-processing module, it is possible to calculate complex functions of the calculated results, for example, to calculate the average reagent concentration in the outputs of several reactors. 2.4. Openness of the system The openness of the Chemical Workbench environment is achieved by several means. First, the Chemical Workbench code can easily integrate user-created reactor models. This possibility is supported by standardized reactor and database interfaces. The Chemical Workbench supports
Fig. 4. Result Explorer window.
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new object standards, such as Microsoft COM add .NET technologies, but also implements rudimentary file exchange support. All available system services, such as reagent list construction and mechanism builder, will be available for newly incorporated reactors. The second aspect of system openness is related to the possibility for the user to add new data sources to the integrated environment. This is achieved not only by importing data from external databases of physicochemical properties but also by integrating new data recovery tools (see description of CARAT module below). The program is also open for the addition of new elements of the user interface, such as post-processing tools or smart wizards for chemical mechanism construction.
Fig. 5. Structure of CWB database.
(2)
2.5. Built-in information support (3) Information support for physicochemical process modeling is one of the important demands for the modern computational environment. The capabilities of data mining, data conversion, and recovery provide the user with fast access to the data and significantly reduce the time of overall process calculation. A significant part of the Chemical Workbench program is its informational system: databases of physical and chemical properties and the CARAT module of recovery of unknown data (calculation of rate constants). This information system provides not only information support for the user but also information transfer between physicochemical models and the database. The database is multimodule system that includes several modules corresponding to different types of data collection (see Fig. 5). At the same time, the database is the source of initial information for modeling. The system contains the following databases: (1) THERMO––database of thermodynamic and thermophysical properties of substances (entropy, enthalpy, heat capacity of substances at room temperature, coefficients of Gibbs energy approximating polynomials, critical point parameters, Lennard–Jones potential para-
(4)
(5)
meters, dipole momentum, data on density, viscosity, and heat conductivity, etc.). The database contains information about 2500 substances of different phase compositions, isomeric forms, charges, etc. REACTIONS––database of rate constants of chemical reactions. The database contains information about more than 5000 reactions. MECHANISMS––database of mechanisms of chemical reactions. MOLECULE––the database of properties of particles (atoms and molecules), which are necessary for computation of thermodynamic functions of gaseous substances and for modeling of physicochemical processes in gas dynamics (data on electronic states of neutral atoms, molecules and their ions, vibration constants, vibration energy levels, rotational constants, thin structure constants of diatomic molecules, electronic transitions, etc.). The database of interaction parameters of particles contains interaction parameters for collisions of molecules in the gas phase, such as the parameters of the Lennard–Jones or Born– Mayer potentials. CATALYSTS––the database of catalyst properties.
Moreover, the database can be applied as a universal tool of data manipulation and data exchange. The main features of the software for data manipulation are as follows: (1) the data may be edited, deleted, or added; (2) the data may be visualized as charts, e.g., Cp ðT Þ (heat capacity) or KðT Þ (equilibrium constant) dependences may be plotted;
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(3) the required data may be extracted according to user-defined requests using the software functions or built-in SQL designer; (4) the selected data may be exported in XML or CSV formats; (5) the thermodynamic data may be exported to or imported from other well-known formats (JANAF [5], CHEMKIN [6]). The information is stored in one of the most popular relational database formats (Microsoft Access), so the data may be easily converted into another relational database format, such as Interbase, Microsoft SQL Server, etc. The database performs data exchange (see Fig. 6) with different external programs (programs that calculate molecular and substance properties, such as GAUSSIAN [7], and programs that calculate reactions parameters, such as CARAT), executable modules (to provide data support in the reactor calculation), and databases (binary files, ASCII, relational databases). The capability of reading, converting, and storing the results of calculation of molecular properties by quantum chemical codes and transferring these data in the special tool CARAT for recovery of unknown reaction parameters substantially increases the range of chemical processes that can be simulated in the environment.
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The module CARAT includes widely diversified numerical data on 88 models [8] of collision processes in gases and plasmas with the participation of atoms, molecules, ions, and electrons. The processes include elastic scattering, electronicvibration-rotation energy transfer between colliding molecules, and chemical and plasma-chemical reactions. Databases of recommended properties of particles and quantitative characteristics of collision processes are built in. The description of each model includes estimates of the accuracy of cross-sections and rate coefficients. Combining CARAT with the database permits one to save calculated results and initial data and to export or import kinetic data to and from the input data format of common kinetic programs. Each class of models contains a set of models that correspond to different approaches to the estimation of parameters of this reaction class. Various objective functions can be chosen within a given model for calculations of cross-sections, rate coefficients, collision frequencies, mean free paths, etc. All the components listed above are incorporated in the CARAT program by a user-friendly interface. The interface permits a user to choose a model suitable for calculations of reaction parameters, to define data for calculations (users can input their own data or take data from the database), to make calculations, and to present results in the necessary format (tabulated or graphical).
3. Application of Chemical Workbench for simulation of ZrO2 film growth in ALD reactor
Fig. 6. Peripheral environment of database and data exchange.
As mentioned before, the Chemical Workbench system is designed for the simulation of a wide spectrum of physical and chemical phenomena and the description and optimization of complex processes. As an example, we choose the process simulation of ZrO2 film growth in the ALD reactor, where practically all the above-mentioned advantages of integrated system application are used. Generally, the ALD installation consists of several chambers: ZrCl4 , H2 O effusion cells, tracts of precursors and purge gas (N2 ) transport, and a
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reaction chamber where ZrO2 deposition takes place. Nitrogen is used as a carrier gas to feed the reaction chamber with ZrCl4 vapor and steam. The precursors (ZrCl4 , H2 O) are introduced into the reaction chamber alternately. The film formation occurs due to the subsequent reaction of precursors with the reactor surface. To avoid gasphase reactions caused by mixing of precursors, the reactor chamber is purged with inert gas (nitrogen) between precursor pulses. The interpretation of the experimental installation in terms of reactor collections of CWB is shown in Fig. 7. In the framework of the CWB environment, the experimental installation was simulated by a sequence of the standard set of reactors (see Fig. 7): thermodynamic equilibrium reactors were used for calculation of the saturation pressure of precursors in effusion cells, the well-stirred reactor was applied for description of mixing of precursor with purge gas, and the special non-steady-state plug flow ALD reactor was used for simulation of ZrO2 film growth. Calculations were carried out for the following experimental ZrO2 ALD conditions [2]: carrier gas (N2 ) pressure, 250 Pa; temperature range, 180–600 C; reactor volume, 160 cm3 ; substrate surface, 220 cm2 ; reactor cross-section, 10.2 cm2 ; substrate length, 6 cm; and carrier gas flow rate, 150 cm3 /s. The durations of the ZrCl4 pulse, the water vapor pulse, and the purge gas pulse following the ZrCl4
pulse were each 20 s. The duration of the purge gas (N2 ) pulse following the water pulse was 10 s. The flow rates of precursors were estimated from the available data of their vapor pressure in the effusion cell: 1.8–3 cm3 /s for ZrCl4 and 2.4–3 cm3 /s for water vapor. The rate of the film growth and chemical composition of the film in the ALD reactor are determined not only by the reactor and input flow parameters but by the parameters of the reaction mechanism as well (see Fig. 8). This list was generated by the built-in procedure of the mechanism builder based on the chemical names of reactants and available collections of reactions of the reaction database. Although the environment supports automatic data access of substances and reactions parameters from the CWB reaction database, this reaction mechanism contains a large number of gas–surface reactions with unknown parameters. To determine the values of parameters, the built-in module of unknown data recovery CARAT was used. The Knowledge Base of the CARAT module permits us to estimate the pre-exponential factor and activation energies of reactions in framework of RRKM theory [3] based on reaction pathway parameters (energetic profile and structure of intermediate complex). The parameters of the reaction pathway were calculated earlier from first principles within the framework of density functional theory (DFT) with gradient corrections [4]. The results of cluster and slab calculations were used to provide sufficient precision of calculation of the energetic threshold and energetic state of reagents
Fig. 7. Flow sheet diagram of ALD installation representation in CWB environment.
Fig. 8. List of gas–surface reactions for description of film growth in ALD reactor.
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Fig. 9. Qualitative reaction path profile of the reaction Zr(OH)4 +ZrCl4 Zr(OH)4 fiZrCl4 Zr(OH)3 –OZrCl3 +HCl, which is analogue of surface reactions sequence (1)–(4) in the Fig. 8.
and reactants. Fig. 9 demonstrates the results of cluster calculation of the (1)–(4) reaction parameters of ZrCl4 reaction with the hydroxylated surface (see Fig. 8). In the case of cluster calculation, the analogue of surface state Zr(OH)2 /s/ was cluster Zr(OH)4 . The calculated pathway of reactions and parameters of intermediate complex were introduced in the model C14 of the CARAT module, which gave us the following temperature approximation of rate constants of adsorbed complex decomposition ZrCl4 Zr(OH)2 /s/ fi ZrCl4 + Zr(OH)2 /s/ (see Fig. 10). A similar procedure was applied for calculation of other gas–surface reactions with unknown rate parameters: reactions of ZrCl4 with hydroxylated surface, reactions of H2 O with chlorinated surface, and reactions of water desorption/adsorption. Further, the kinetic scheme was applied for simulation of a real experimental installation in the framework of the developed model (see Fig. 7). During simulation, it was found that the proposed model correctly describes the principal experimental features. Fig. 11 shows the dependence of growing film mass on process time. One can see that the model gives a reasonable agreement with experimental data.
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Fig. 10. Calculation of rate of reaction in the framework of the CARAT module. The parameters of the reaction, reactants, and result: dependence of the reaction rate on temperature.
Fig. 11. Increment of film mass vs. exposure time. Comparison of experimental data [1] (––) and model results (- - -). Conditions: ZrCl4 pulse duration is 20 s, H2 O pulse duration is 20 s, purge time is 10 s. Dm0 is film mass increment per one ALD cycle, Dm1 is mass increment of the film during ZrCl4 pulse.
However, further comparison shows that the model predicts a sharp (exponential) dependence in the film growth rate on process temperature, whereas experiments demonstrate a nearly linear dependence. Agreement was achieved by additional fitting of activation energies of several reactions (reactions of water adsorption/desorption). It was shown that coincidence of experimental results with the model can be achieved in
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the framework of the proposed mechanism if water adsorption/desorption energy is a function of surface coverage degree by OH groups [4].
4. Conclusions In this work, we specified the requirements for integrated simulation environment in the field of chemical kinetics. These requirements include
defined tasks. The important component of the CWB environment is the existence of information support for the integrated and user-created reactors. This built-in information support can also recover unavailable physicochemical data from quantum chemical calculations, and a corresponding example was presented for the simulation of zirconia film growth in the ALD process.
References (1) flexibility of the models, (2) built-in information support, (3) built-in tools for sensitivity analysis of calculated results, (4) user-friendliness, (5) openness of the system. We have shown how the structure of Chemical Workbench code helps to meet the corresponding requirements. The CWB environment operates with process-related objects, such as reactors, streams, and substances, and the GUI is specially designed to facilitate manipulation of these objects. The key feature of the CWB environment is the possibility to construct reactor chains with complex connections, which strongly increase the flexibility of this simulation environment for user-
[1] Web site: www.kintech.ru. [2] J. Aarik, A. Aidla, H. Mandar, T. Uustrate, V. Sammelselg, Thin Solid Films 408 (2002) 97. [3] E.E. Nikitin, Theory of Elementary Atomic and Molecular Processes in Gases, Clarendon, Oxford, 1974. [4] M. Deminsky, A. Knizhnik, I. Belov, S. Umanskii, E. Rykova, A. BagaturÕyants, B.V. Potapkin, A.A. Korkin, Surface Science, submitted for publication. [5] M.W. Chase Jr., C.A. Davies, J.R. Davies Jr., D.J. Fulrip, R.A. McDonald, A.N. Syverud, JANAF Thermochemical Tables, 3rd edition, Journal of Physical and Chemical Reference Data 4 (suppl. 1) (1985). [6] Web site: www.reactiondesign.com. [7] M.J. Frisch et al., Gaussian 98, rev A.7, Gaussian, Inc., Pittsburgh, PA, 1998. [8] G.G. Chernyi, S.A. Losev, S.O. Macheret, B.V. Potapkin, Physical and Chemical Processes and Gas Dynamics: Cross Sections and Rate Constants, in: Progress in Astronautics and Aeronautics, vol. 196, AIAA, 2002.
Chemical Workbench––integrated environment for materials science M. Deminsky a,*, V. Chorkov b, G. Belov c, I. Cheshigin b, A. Knizhnik b, E. Shulakova b, M. Shulakov b, I. Iskandarova b, V. Alexandrov b, A. Petrusev a, I. Kirillov a, M. Strelkova a, S. Umanski d, B. Potapkin a a
c
RRC ‘‘Kurchatov Institute’’, Kurchatov Sq. 1, 123182 Moscow, Russia b Kinetic Technologies, Kurchatov Sq. 1, 123182 Moscow, Russia Thermocentre, IHED, IVTAN Association of RAS, Izhorskaya 13/19, 127412 Moscow, Russia d N.N. Semenov Institute of Chemical Physics of RAS, Kosygina 4, 117977 Moscow, Russia
Abstract Current environmental problems and industrial needs require the permanent modification and improvement of existing technologies or the implementation and design of new technological methods. One of the most effective and cheapest ways to meet real practical requests and needs and development of new methods is balanced combination of experimental investigation and computer-aided simulation and technology design. In turn, the best way to develop a simulation tool for a new chemical process is to use an integrated simulation environment, which incorporates all necessary functionality and thus can reduce the cost of the development of a new model. 2003 Elsevier B.V. All rights reserved. Keywords: Chemical kinetics; Thermodynamics; Computer-aided simulation; Database
1. Introduction Principal modeling demands for the integrated simulation platform can be formulated like: (1) flexibility of the model set, (2) built-in information support, (3) built-in instruments for sensitivity investigation,
*
Corresponding author. Address: Kinetic Technologies, Kurchatov Sq. 1, 123182 Moscow, Russia. E-mail address: [email protected] (M. Deminsky).
(4) user-friendly interface for model development and simulation control, (5) openness of the system for user modules and data. The first requirement means the adaptability of the system to simulate different chemical processes based on the integrated set of reactor models. Therefore, an integrated system should have a comprehensive set of basic reactor models, which should cover all possible chemical processes. This set usually includes thermodynamic and kinetic reactors, which describe chemical reactions in homoand heterogeneous systems. The key feature here is
0927-0256/$ - see front matter 2003 Elsevier B.V. All rights reserved. doi:10.1016/S0927-0256(03)00105-8
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the possibility to develop a more complex reactor model based on these basic models. This feature strongly enhances the adaptability of the integrated simulation environment to real chemical processes and permits construction of technology chains from basic reactor modules simulating the separate steps of processes. The reactor models use practically the same physicochemical data in simulations, such as the thermodynamic energies of individual species, rate constants of a chemical reaction, density of species, chemical activity, etc. Thus, an integrated simulation system should provide built-in information support for all reactor models. This means that an integrated system should have a comprehensive set of databases of physicochemical properties with a unified interface to it. Completeness of databases is a key feature for a wide range of applications, but in reality it cannot be achieved. Therefore, the built-in information support must have special tools for data recovery from some fundamental information. Due to the increase of computational power, important of quantum chemical calculations, as source of such fundamental information, are going to be more important. Thus data recovery tools should be ready to utilize the results of quantum chemical simulation programs. An important question of computer-aided process design is the reliability of the calculated results. An integrated simulation environment should provide special methods for investigating the dependence of simulation results on the calculation parameters and initial data. These methods can be used, for example, to construct and reduce chemical mechanisms, determine key chemical reactions, and investigate the influence of stochastic factors. The main idea of an integrated system is to reduce the cost of the development of new models. One way to reduce the time of model development is to provide the user with a convenient visual interface for the complete cycle of chemically centered simulation. The visual interface should provide tools to construct the simulation model of a real chemical process using technology chains of basic reactor modules. This is the main way of improving system flexibility, and therefore the vi-
sual interface should facilitate this process for the user. Another important feature of the visual interface is to facilitate work with the integrated database and provide the user with powerful tools for database management. The final step of process simulation is investigation of calculation results, and the visual interface should provide comprehensive tools for data analysis and post-processing. The integrated set of reactor models cannot, of course, give a detailed description of some highly specialized chemical applications, and therefore the extendibility of the system is a key feature of the integrated system from userÕs point of view. The extendibility of the system is related to the openness of the program system, which is the possibility for the end user to develop his/her own modules based on the available information about reactor and database interfaces and exchange data flow and data formats. The Chemical Workbench code described in this work is an example of such an integrated system with an open platform architecture for modeling, optimization, and design of a wide range of industrial chemical processes, reactors, and technologies. The structure of the code (see Fig. 1) reflects the modular structure of the environment, which can be easily adapted to complex research tasks using available models and integrated visualization and database support. The user is responsible only for the creation of a sim-
Fig. 1. Structure of Chemical Workbench environment.
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ulation model of the process of interest connecting the universal reactor models with the coupling elements in the program window, and all required data are supplied by the environment from built-in information support. The code includes extended databases of physicochemical properties, which can be accessed by all reactors through universal data objects. Unavailable physicochemical data can be estimated with special data recovery tool (CARAT) in the built-in information support block (which can use results of ab initio calculations). The visualization and post-processing module permits thorough investigation and verification of simulation results, which can be saved in a database for further study. In the following section, we will show in detail how the structure of the Chemical Workbench code meets the above-mentioned requirements for an integrated simulation system. Then we will present an example of the application of the Chemical Workbench code [1] in computational materials science.
2. Structure of Chemical Workbench code A simulation model in the Chemical Workbench environment is described in terms of several user-controlled objects: calculations, reactors, streams, substances, and reactions. The reactor in the Chemical Workbench environment can be considered as a stream-manipulating object: each reactor has several inputs and outputs, which are connected to streams. Each reactor model has a set of parameters that determine the relationship between input and output streams. The stream object in the Chemical Workbench environment is the homogeneous/heterogeneous mixture of substances at given physical conditions (pressure, temperature, velocity, etc.). Each substance in the code is uniquely identified by chemical formula, charge, isomeric formula, and phase. The structure of Chemical Workbench code is closely related to the above-mentioned objects and provides convenient manipulation with these objects. In what follows, we will give the most attention to the reactor objects and the construction of the whole simulation model within the Chemical
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Workbench environment. This will also show how this environment satisfies the requirements for the integrated simulation environment. 2.1. Flexibility of models The main feature of an integrated environment, as was mentioned above, is the flexibility of the reactor models to user tasks. In the framework of Chemical Workbench code, the flexibility of the models is achieved by several approaches. The first approach consists in the construction of reactors chains from the set of available reactors and organization of flow-sheet diagrams. The second approach is related to the generality of the integrated model set. This means adaptability of reactor models to different possible real reactors. The third approach is based on assimilation of user-created models and will be considered below. 2.1.1. Construction of flow-sheet diagram Each reactor in the Chemical Workbench environment can be connected to other reactors by input and output streams; thus, several reactors can be connected in one chain. Interaction between models is carried out not only via ‘‘material streams’’ on flow-sheet diagram but also by input parameters of each reactor being given as arbitrary function of the results of any previous calculations. For example, in the case of energy exchange between reactors, energy input in one reactor can depend on the heat loss in the previous reactor. This relationship between reactor parameters is managed in the Data Explorer window in the graphical user interface (GUI), which will be described later. Two ‘‘material streams’’ can be merged in one stream in the mixer reactor, and one stream can be subdivided into two separate streams in the divider model. 2.1.2. Universality of models The set of reactor models in Chemical Workbench code contains two types of reactor model: one type describes models of abstract reactors, while the models of the second type correspond to concrete chemical reactors and processes. The first type of reactor model can be used for a wide range of chemical applications due to the universal
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underlying mathematical models. These models include equilibrium thermodynamic models (ideal, nonideal), homogenous and heterogeneous kinetic models (well-stirred reactor model, plug-flow reactor, calorimetric bomb with possible surface chemistry), catalytic reactors with fixed pellet bed, combustion and detonation reactors, and plasma and electron beam reactors. Models of this type can be used under different experimental conditions; for example, the plug flow reactor model can be applied as an isothermal reactor, a reactor under adiabatic conditions, or as a reactor with a user-defined function of temperature as a function of time. The model of more complex reactors can easily be constructed by connecting these models of abstract reactors in a reactor chain. Reactors of the second type are specialized for specific chemical applications and processes and have a narrower range of experimental conditions. Examples of these reactors include the Fischer– Tropsch reactor, plasma arc reactor, etc. The set of these reactors can be expanded by user-defined models for specific chemical applications. 2.2. Sensitivity analysis The Chemical Workbench code has several builtin tools to estimate the reliability of the calculated results. It is possible to investigate the dependence of simulation results on the reactor parameters and on the rate constants of chemical reactions. The first dependence is obtained in parameterized calculation of the given reactor with different reactor parameters. The dependence on the reaction rates is calculated using global kinetic sensitivity analysis of kinetic mechanisms. Sensitivity analysis of a chemical kinetic task is an algorithm for calculation of logarithmic derivatives lnðni Þ= lnðAj Þ, where ni is the final concentration of the ith substance and Aj is the pre-exponential factor of the jth chemical reaction. The calculation of the sensitivity coefficient matrix presents an opportunity to recognize the most and the least significant chemical reactions in the reactions list, as well as to evaluate the effect of reaction pre-exponent uncertainty on the result of the kinetic task solution. This information can be directly used in development and reduction of chemical mechanisms.
2.3. User-friendly interface One of the important features of the rapid visual design of chemical systems is the possibility of rapidly completing the cycle of the development of the simulation model, starting from the construction of the reactor chain, up to the visualization of the calculation results, and to return to the editing of the simulation model (connections between reactors, chemical mechanism, reactor parameters). To meet this requirement, all program components, from the editor of the flow-sheet diagram to the graphic visualization window, are realized in the framework of one program and are tightly integrated. 2.3.1. Object-oriented interface Modern program systems for scientific and technical investigations, despite being in different application fields, are similar due to the presence of a GUI. Existing GUIs strongly restrict the user in utilization of software components. The development of a GUI of the next generation with an object-oriented interface gives the user wider possibilities for the solution of the required tasks. The object-oriented user interface (OOUI) gives the users the freedom to manipulate available objects, and the representation of objects in the software program approaches their representation in the real world, thus facilitating the understanding of the program by the user and expanding the number of program users among nonspecialists in computer science. The OOUI also permits the user to create his own classes of objects on the basis of available objects without programming and hence to adapt the program to his own needs. 2.3.2. Structure of program interface The interface of the Chemical Workbench code consists of four main windows: Model Explorer (editor of connections between reactors), Data Explorer (editor of chemical mechanisms, reactor parameters, table data editor), Calculation Explorer (block of calculation run), and Result Explorer (visualization and post-processing of the results). The Model Explorer (Fig. 2) window is designed for selection and building of process mod-
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Fig. 2. Model Explorer window.
els. The given module includes the library of reactor models, which consists of several groups of reactors (thermodynamic reactors, kinetic, etc.). In the Model Explore window, the user sequentially selects the required reactor models, places them on the program table, and connects them. The integrated environment makes it possible to easily switch and edit the properties of each element on the program table (reactor parameters, its chemical mechanism, parameters of species flux). The Data Explorer (Fig. 3) window is designed for entering initial data and parameters for a calculation and consists of two parts. The left part of the window displays the data structure for the given calculation on one side, and on the another side is additional assistance for entering these data. The right part of the window displays the actual data. The type of the displayed data corresponds
Fig. 3. Data Explorer window.
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to the open folder in the left part of the window. The window is automatically adjusted depending on the type of the data in the editor window (species properties, reaction list, etc.). For reactors, there are special data recovery tools for estimation of unavailable thermodynamic and kinetic data. The Calculation Explorer window displays the conflicts in the input data detected at run time and permits the user to control the calculation process. The Result Explorer (Fig. 4) window displays all results of a calculation. These results can be presented both in text style in the table and in graphic view. Moreover, the results of the calculation can be exported in xls, mdb, and txt formats. With the use of the post-processing module, it is possible to calculate complex functions of the calculated results, for example, to calculate the average reagent concentration in the outputs of several reactors. 2.4. Openness of the system The openness of the Chemical Workbench environment is achieved by several means. First, the Chemical Workbench code can easily integrate user-created reactor models. This possibility is supported by standardized reactor and database interfaces. The Chemical Workbench supports
Fig. 4. Result Explorer window.
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new object standards, such as Microsoft COM add .NET technologies, but also implements rudimentary file exchange support. All available system services, such as reagent list construction and mechanism builder, will be available for newly incorporated reactors. The second aspect of system openness is related to the possibility for the user to add new data sources to the integrated environment. This is achieved not only by importing data from external databases of physicochemical properties but also by integrating new data recovery tools (see description of CARAT module below). The program is also open for the addition of new elements of the user interface, such as post-processing tools or smart wizards for chemical mechanism construction.
Fig. 5. Structure of CWB database.
(2)
2.5. Built-in information support (3) Information support for physicochemical process modeling is one of the important demands for the modern computational environment. The capabilities of data mining, data conversion, and recovery provide the user with fast access to the data and significantly reduce the time of overall process calculation. A significant part of the Chemical Workbench program is its informational system: databases of physical and chemical properties and the CARAT module of recovery of unknown data (calculation of rate constants). This information system provides not only information support for the user but also information transfer between physicochemical models and the database. The database is multimodule system that includes several modules corresponding to different types of data collection (see Fig. 5). At the same time, the database is the source of initial information for modeling. The system contains the following databases: (1) THERMO––database of thermodynamic and thermophysical properties of substances (entropy, enthalpy, heat capacity of substances at room temperature, coefficients of Gibbs energy approximating polynomials, critical point parameters, Lennard–Jones potential para-
(4)
(5)
meters, dipole momentum, data on density, viscosity, and heat conductivity, etc.). The database contains information about 2500 substances of different phase compositions, isomeric forms, charges, etc. REACTIONS––database of rate constants of chemical reactions. The database contains information about more than 5000 reactions. MECHANISMS––database of mechanisms of chemical reactions. MOLECULE––the database of properties of particles (atoms and molecules), which are necessary for computation of thermodynamic functions of gaseous substances and for modeling of physicochemical processes in gas dynamics (data on electronic states of neutral atoms, molecules and their ions, vibration constants, vibration energy levels, rotational constants, thin structure constants of diatomic molecules, electronic transitions, etc.). The database of interaction parameters of particles contains interaction parameters for collisions of molecules in the gas phase, such as the parameters of the Lennard–Jones or Born– Mayer potentials. CATALYSTS––the database of catalyst properties.
Moreover, the database can be applied as a universal tool of data manipulation and data exchange. The main features of the software for data manipulation are as follows: (1) the data may be edited, deleted, or added; (2) the data may be visualized as charts, e.g., Cp ðT Þ (heat capacity) or KðT Þ (equilibrium constant) dependences may be plotted;
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(3) the required data may be extracted according to user-defined requests using the software functions or built-in SQL designer; (4) the selected data may be exported in XML or CSV formats; (5) the thermodynamic data may be exported to or imported from other well-known formats (JANAF [5], CHEMKIN [6]). The information is stored in one of the most popular relational database formats (Microsoft Access), so the data may be easily converted into another relational database format, such as Interbase, Microsoft SQL Server, etc. The database performs data exchange (see Fig. 6) with different external programs (programs that calculate molecular and substance properties, such as GAUSSIAN [7], and programs that calculate reactions parameters, such as CARAT), executable modules (to provide data support in the reactor calculation), and databases (binary files, ASCII, relational databases). The capability of reading, converting, and storing the results of calculation of molecular properties by quantum chemical codes and transferring these data in the special tool CARAT for recovery of unknown reaction parameters substantially increases the range of chemical processes that can be simulated in the environment.
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The module CARAT includes widely diversified numerical data on 88 models [8] of collision processes in gases and plasmas with the participation of atoms, molecules, ions, and electrons. The processes include elastic scattering, electronicvibration-rotation energy transfer between colliding molecules, and chemical and plasma-chemical reactions. Databases of recommended properties of particles and quantitative characteristics of collision processes are built in. The description of each model includes estimates of the accuracy of cross-sections and rate coefficients. Combining CARAT with the database permits one to save calculated results and initial data and to export or import kinetic data to and from the input data format of common kinetic programs. Each class of models contains a set of models that correspond to different approaches to the estimation of parameters of this reaction class. Various objective functions can be chosen within a given model for calculations of cross-sections, rate coefficients, collision frequencies, mean free paths, etc. All the components listed above are incorporated in the CARAT program by a user-friendly interface. The interface permits a user to choose a model suitable for calculations of reaction parameters, to define data for calculations (users can input their own data or take data from the database), to make calculations, and to present results in the necessary format (tabulated or graphical).
3. Application of Chemical Workbench for simulation of ZrO2 film growth in ALD reactor
Fig. 6. Peripheral environment of database and data exchange.
As mentioned before, the Chemical Workbench system is designed for the simulation of a wide spectrum of physical and chemical phenomena and the description and optimization of complex processes. As an example, we choose the process simulation of ZrO2 film growth in the ALD reactor, where practically all the above-mentioned advantages of integrated system application are used. Generally, the ALD installation consists of several chambers: ZrCl4 , H2 O effusion cells, tracts of precursors and purge gas (N2 ) transport, and a
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reaction chamber where ZrO2 deposition takes place. Nitrogen is used as a carrier gas to feed the reaction chamber with ZrCl4 vapor and steam. The precursors (ZrCl4 , H2 O) are introduced into the reaction chamber alternately. The film formation occurs due to the subsequent reaction of precursors with the reactor surface. To avoid gasphase reactions caused by mixing of precursors, the reactor chamber is purged with inert gas (nitrogen) between precursor pulses. The interpretation of the experimental installation in terms of reactor collections of CWB is shown in Fig. 7. In the framework of the CWB environment, the experimental installation was simulated by a sequence of the standard set of reactors (see Fig. 7): thermodynamic equilibrium reactors were used for calculation of the saturation pressure of precursors in effusion cells, the well-stirred reactor was applied for description of mixing of precursor with purge gas, and the special non-steady-state plug flow ALD reactor was used for simulation of ZrO2 film growth. Calculations were carried out for the following experimental ZrO2 ALD conditions [2]: carrier gas (N2 ) pressure, 250 Pa; temperature range, 180–600 C; reactor volume, 160 cm3 ; substrate surface, 220 cm2 ; reactor cross-section, 10.2 cm2 ; substrate length, 6 cm; and carrier gas flow rate, 150 cm3 /s. The durations of the ZrCl4 pulse, the water vapor pulse, and the purge gas pulse following the ZrCl4
pulse were each 20 s. The duration of the purge gas (N2 ) pulse following the water pulse was 10 s. The flow rates of precursors were estimated from the available data of their vapor pressure in the effusion cell: 1.8–3 cm3 /s for ZrCl4 and 2.4–3 cm3 /s for water vapor. The rate of the film growth and chemical composition of the film in the ALD reactor are determined not only by the reactor and input flow parameters but by the parameters of the reaction mechanism as well (see Fig. 8). This list was generated by the built-in procedure of the mechanism builder based on the chemical names of reactants and available collections of reactions of the reaction database. Although the environment supports automatic data access of substances and reactions parameters from the CWB reaction database, this reaction mechanism contains a large number of gas–surface reactions with unknown parameters. To determine the values of parameters, the built-in module of unknown data recovery CARAT was used. The Knowledge Base of the CARAT module permits us to estimate the pre-exponential factor and activation energies of reactions in framework of RRKM theory [3] based on reaction pathway parameters (energetic profile and structure of intermediate complex). The parameters of the reaction pathway were calculated earlier from first principles within the framework of density functional theory (DFT) with gradient corrections [4]. The results of cluster and slab calculations were used to provide sufficient precision of calculation of the energetic threshold and energetic state of reagents
Fig. 7. Flow sheet diagram of ALD installation representation in CWB environment.
Fig. 8. List of gas–surface reactions for description of film growth in ALD reactor.
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Fig. 9. Qualitative reaction path profile of the reaction Zr(OH)4 +ZrCl4 Zr(OH)4 fiZrCl4 Zr(OH)3 –OZrCl3 +HCl, which is analogue of surface reactions sequence (1)–(4) in the Fig. 8.
and reactants. Fig. 9 demonstrates the results of cluster calculation of the (1)–(4) reaction parameters of ZrCl4 reaction with the hydroxylated surface (see Fig. 8). In the case of cluster calculation, the analogue of surface state Zr(OH)2 /s/ was cluster Zr(OH)4 . The calculated pathway of reactions and parameters of intermediate complex were introduced in the model C14 of the CARAT module, which gave us the following temperature approximation of rate constants of adsorbed complex decomposition ZrCl4 Zr(OH)2 /s/ fi ZrCl4 + Zr(OH)2 /s/ (see Fig. 10). A similar procedure was applied for calculation of other gas–surface reactions with unknown rate parameters: reactions of ZrCl4 with hydroxylated surface, reactions of H2 O with chlorinated surface, and reactions of water desorption/adsorption. Further, the kinetic scheme was applied for simulation of a real experimental installation in the framework of the developed model (see Fig. 7). During simulation, it was found that the proposed model correctly describes the principal experimental features. Fig. 11 shows the dependence of growing film mass on process time. One can see that the model gives a reasonable agreement with experimental data.
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Fig. 10. Calculation of rate of reaction in the framework of the CARAT module. The parameters of the reaction, reactants, and result: dependence of the reaction rate on temperature.
Fig. 11. Increment of film mass vs. exposure time. Comparison of experimental data [1] (––) and model results (- - -). Conditions: ZrCl4 pulse duration is 20 s, H2 O pulse duration is 20 s, purge time is 10 s. Dm0 is film mass increment per one ALD cycle, Dm1 is mass increment of the film during ZrCl4 pulse.
However, further comparison shows that the model predicts a sharp (exponential) dependence in the film growth rate on process temperature, whereas experiments demonstrate a nearly linear dependence. Agreement was achieved by additional fitting of activation energies of several reactions (reactions of water adsorption/desorption). It was shown that coincidence of experimental results with the model can be achieved in
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the framework of the proposed mechanism if water adsorption/desorption energy is a function of surface coverage degree by OH groups [4].
4. Conclusions In this work, we specified the requirements for integrated simulation environment in the field of chemical kinetics. These requirements include
defined tasks. The important component of the CWB environment is the existence of information support for the integrated and user-created reactors. This built-in information support can also recover unavailable physicochemical data from quantum chemical calculations, and a corresponding example was presented for the simulation of zirconia film growth in the ALD process.
References (1) flexibility of the models, (2) built-in information support, (3) built-in tools for sensitivity analysis of calculated results, (4) user-friendliness, (5) openness of the system. We have shown how the structure of Chemical Workbench code helps to meet the corresponding requirements. The CWB environment operates with process-related objects, such as reactors, streams, and substances, and the GUI is specially designed to facilitate manipulation of these objects. The key feature of the CWB environment is the possibility to construct reactor chains with complex connections, which strongly increase the flexibility of this simulation environment for user-
[1] Web site: www.kintech.ru. [2] J. Aarik, A. Aidla, H. Mandar, T. Uustrate, V. Sammelselg, Thin Solid Films 408 (2002) 97. [3] E.E. Nikitin, Theory of Elementary Atomic and Molecular Processes in Gases, Clarendon, Oxford, 1974. [4] M. Deminsky, A. Knizhnik, I. Belov, S. Umanskii, E. Rykova, A. BagaturÕyants, B.V. Potapkin, A.A. Korkin, Surface Science, submitted for publication. [5] M.W. Chase Jr., C.A. Davies, J.R. Davies Jr., D.J. Fulrip, R.A. McDonald, A.N. Syverud, JANAF Thermochemical Tables, 3rd edition, Journal of Physical and Chemical Reference Data 4 (suppl. 1) (1985). [6] Web site: www.reactiondesign.com. [7] M.J. Frisch et al., Gaussian 98, rev A.7, Gaussian, Inc., Pittsburgh, PA, 1998. [8] G.G. Chernyi, S.A. Losev, S.O. Macheret, B.V. Potapkin, Physical and Chemical Processes and Gas Dynamics: Cross Sections and Rate Constants, in: Progress in Astronautics and Aeronautics, vol. 196, AIAA, 2002.