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        "author": "Gabriel S. Gusmao",
        "author_email": "gusmaogabriels@gmail.com",
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        "description": "==============\r\n**mkin4py** \r\n==============\r\n\r\n*mkin(microkinetics) 4 py(thon)*\r\n\r\n|star| |watch| |fork| |github|\r\n\r\n.. image:: https://img.shields.io/pypi/l/mkin4py.svg\r\n   :height: 100px\r\n   :width: 200 px\r\n   :scale: 50 %\r\n   :alt: alternate text\r\n   :align: right\r\n\r\n.. image:: https://img.shields.io/pypi/v/mkin4py.svg\r\n   :height: 100px\r\n   :width: 200 px\r\n   :scale: 50 %\r\n   :alt: alternate text\r\n   :align: right\r\n\r\nA package for linearly defining and solving micr\r\nokinetic catalytic systems.\r\n\r\n----------------\r\n**Description**\r\n----------------\r\n\r\n  A microkinetic package translated from the Linearized Microkinetic Catalytic System Solver\r\n\r\n  By the author:\r\n\r\n  *Gabriel S. Gusm\u00e3o* <gusmaogabriels@gmail.com>\r\n  \r\n  |ld|\r\n\r\n  |rg|\r\n    \r\n  under *Dr. Phillip Christopher* <christopher@engr.ucr.edu> advisement.\r\n\r\n  For detailed information, refer to code comments or associated publication.\r\n  Gusm\u00e3o, G. S. & Christopher, P., **A general and robust approach for defining and solving \r\n  microkinetic catalytic systems.** AIChE J. 00, (2014).; http://dx.doi.org/10.1002/aic.14627\r\n\r\n  The 17-Step Ethylene Epoxidation by Stegelmann et al. has been used as example.\r\n  Stegelmann, C., Schi\u00f8dt, N. C., Campbell, C. T. & Stoltze, P.\r\n  **Microkinetic modeling of ethylene oxidation over silver**. J. Catal. 221, 630\u2013649 (2004).\r\n\r\n  1. Set-up the environment conditions (temperature, pressure, gas constant)\r\n  2. Create a MK (microkinetic model object)\r\n     - Define its dimensions: number of reactants (rows) and elementary reactions (columns) involved in the stoichiometry matrix, and parse the rows that refer to *free*-species (non-adsorbed)\r\n     - Parse the stoichiometry matrix (must be of size number of reactants \u00d7 number of elementary reactions)\r\n     - Set the kinetic parameters: Activation Energies and Pre-exponential factors (must be of the size of the involved elementary reactions)\r\n     - Set the fixed concentration of *free*-species (molar fraction in non-adsorbed phase)\r\n     - Parse the string-labels of involved species (array of size of number of species) \r\n  3. Solve the ensuing LP (linear problem)\r\n     - For now, there is only a *Newton*-type method available.\r\n     - Standard iterative-procedure adopted for solving the inner-loop LP (Quasi-minimum residue)\r\n\r\n  The convergence parameters are set as default in the module `solver` in `.params`\r\n\r\n----------------\r\n**Features**\r\n----------------\r\n\r\n    - **Linearization**\r\n\r\n    The project makes use of explicit routines for the calculation of the MK model derivatives\r\n        \r\n        - *Jacobian*: Available as standard.\r\n        - *Hessian*: Used in the convex two-step method (details in the aforementioned reference)\r\n\r\n----------------\r\n**On the way**\r\n----------------\r\n\r\n  1. Additional LP solvers in \"switchable\" fashion.\r\n  2. Evolutionary methods for the definition of best convergence parameters for *stiff* problems (when TOF`s are close to the machine precision)\r\n\r\n----------------\r\n**Instructions**\r\n----------------\r\n\r\n  - **Installation**\r\n\r\n     .. code-block:: python\r\n\r\n        pip install mkin4py==version_no\r\n\r\n  - **Example**: Stoltze's 17-Step Ethylene Epoxidation MK system\r\n\r\n     .. code-block:: python\r\n\r\n        import mkin4py\r\n        import numpy as np\r\n        \r\n        # Environment Conditions\r\n        T = 500; #K\r\n        P = 2; #bar\r\n        gas_constant = 8.31456e-3 # Gas Constant - kJ/(mol\u00d7K)\r\n        \r\n        # Set the environment conditions\r\n        mkin4py.environment.set_temperature(T)\r\n        mkin4py.environment.set_gas_constant(gas_constant)\r\n        mkin4py.environment. set_pressure(P)\r\n        \r\n        # Stoichiometric Matrix\r\n        ms = [\r\n        [-1, 1, 0, 0,-1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],\\\r\n        [ 0, 0, 0, 0, 0, 0,-1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,-1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],\\\r\n        [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,-1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],\\\r\n        [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1,-1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],\\\r\n        [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1,-1, 0, 0],\\\r\n        [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1,-1],\\\r\n        [-1, 1,-1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1,-1,-1, 1, 1,-1, 0, 0, 1,-1, 0, 0, 1,-1, 1,-1],\\\r\n        [ 1,-1,-1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],\\\r\n        [ 0, 0, 2,-2,-2, 2,-1, 1, 1,-1,-1, 1, 0, 0, 0, 0, 1,-1,-6, 6, 0, 0,-1, 1,-1, 1,-5, 5, 1,-1, 0, 0, 0, 0],\\\r\n        [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 4,-4, 0, 0, 0, 0, 1,-1, 3,-3,-2, 2, 0, 0, 0, 0],\\\r\n        [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1,-1, 0, 0,-1, 1],\\\r\n        [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2,-2, 0, 0, 0, 0, 0, 0, 2,-2, 0, 0,-1, 1, 0, 0],\\\r\n        [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1,-1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],\\\r\n        [ 0, 0, 0, 0, 2,-2, 0, 0,-1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],\\\r\n        [ 0, 0, 0, 0, 0, 0, 1,-1,-1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,-1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],\\\r\n        [ 0, 0, 0, 0, 0, 0, 0, 0, 1,-1, 0, 0,-1, 1,-1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],\\\r\n        [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1,-1, 1,-1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],\\\r\n        [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1,-1,-1, 1,-1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],\\\r\n        [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1,-1,-1, 1, 0, 0, 0, 0, 0, 0, 0, 0],\\\r\n        [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1,-1,-1, 1, 0, 0, 0, 0, 0, 0],\\\r\n        ];\r\n        \r\n        nreac = [0, 1] # Reactant Rows in mS\r\n        nprod = [2, 3, 4, 5] # Product Rows in mS\r\n        stoichs = np.concatenate((nreac,nprod)) # Reactants and Products are not under PSSH\r\n        mkin4py.mkmodel.create(np.shape(ms)[0],np.shape(ms)[1],stoichs) # Initialize the model\r\n        mkin4py.mkmodel.set_ms(ms) # Set the stoichiometry matrix\r\n        \r\n        # Species labels \r\n        splabels = ['O2','C2H4','C2H4O','CH3CHO','CO2','H2O','*','O2*','O*','OH*',\\\r\n        'H2O*','CO2*','C2H4*','O\u00b7O*','C2H4\u00b7O*','CH2CH2O\u00b7O*','C2H4O\u00b7O*','CH3CHO\u00b7O*',\\\r\n        'CH2CHOH\u00b7O*','CH2CHO\u00b7O*']\r\n        \r\n        mkin4py.mkmodel.set_splabels(splabels) # Set species labels\r\n        \r\n        # Pre-exponential Factors of Eelementary Reactions (1/s)\r\n        va =[2.71e5, 1.1e12, 4.0e12, 8.0e14, 2.0e7, 1.3e15, 7.2e7,\\\r\n        2.2e11, 9.0e14, 5.3e14, 1.95e8, 4.8e12, 1.13e13, 2.11e12,\\\r\n        9.0e12, 4.5e10, 2.9e13, 2.6e9, 2.0e20, 5.3e13, 7.2e7, 2.2e11,\\\r\n        4.0e11, 3.1e14, 2.6e13, 1.3e9, 1.0e20, 5.5e13, 1.4e10, 1.0e11,\\\r\n        3.6e14, 1.0e8, 5.9e14, 1.4e9]\r\n        \r\n        # Activation Barriers for Elementary ReactionS (kJ/mol)\r\n        vea = [5.7000, 47.3000, 75.0000, 157.5000, 20.0000, 96.9000, 0, 37.1000, 112.0000,\\\r\n        183.3000, 0, 39.1000, 95.0000, 93.5000, 95.0000, 204.3000, 41.9000, 4.4000,\\\r\n        11.0000, 791.6000, 0, 30.1000, 32.0000, 42.8000, 86.0000, 106.1000, 0, 906.6000,\\\r\n        65.6000, 50.0000, 38.9000, 0, 46.6000, 0]\r\n        \r\n        # Set the kinetic parameters\r\n        mkin4py.mkmodel.set_kinetic_params(np.array(va,ndmin=2).T,np.array(vea,ndmin=2).T)\r\n        \r\n        y = [0.5, 0.5, 0, 0, 0, 0] # Reactants and Products Initial Fraction\r\n        mkin4py.mkmodel.set_concentrations(y) # Set the *free*-species concentrations\r\n        \r\n  - **Evaluation**:\r\n       \r\n     .. code-block:: python\r\n\r\n        sol = mkin4py.solver.solve.rk4() # 4th-order Runge-Kutta method coupled within the LP solved via QMR\r\n        # Outupts\r\n        print '...'\r\n        print sol['msg'], 'time: ', sol['time']\r\n        print 'Coverage'\r\n        print sol['coverage']\r\n        print 'Rates'\r\n        print sol['rates']\r\n\r\n  - **Output**:\r\n\r\n     .. code-block:: python\r\n\r\n        ...\r\n        Convergence achieved time:  2.25999999046\r\n        Coverage\r\n        [[  5.00000000e-01]\r\n        [  5.00000000e-01]\r\n        [  0.00000000e+00]\r\n        [  0.00000000e+00]\r\n        [  0.00000000e+00]\r\n        [  0.00000000e+00]\r\n        [  4.39342950e-01]\r\n        [  1.19743307e-03]\r\n        [  1.07992516e-01]\r\n        [  1.10447591e-01]\r\n        [  2.99730332e-09]\r\n        [  7.70711567e-10]\r\n        [  1.00256049e-01]\r\n        [  9.78269843e-02]\r\n        [  1.32727193e-01]\r\n        [  9.64368428e-03]\r\n        [  3.28419897e-08]\r\n        [  4.59118359e-13]\r\n        [  5.65562897e-04]\r\n        [  1.12150752e-15]]\r\n        Rates\r\n        [[ -4.24252190e+01]\r\n        [ -2.49532633e+01]\r\n        [  1.29732696e+01]\r\n        [  5.58723011e-04]\r\n        [  2.39588699e+01]\r\n        [  2.39588699e+01]\r\n        [  0.00000000e+00]\r\n        [  3.65929509e-13]\r\n        [  0.00000000e+00]\r\n        [  4.32857086e-11]\r\n        [  2.76796815e-16]\r\n        [  2.87485591e-11]\r\n        [  0.00000000e+00]\r\n        [ -2.27373675e-13]\r\n        [ -4.65661287e-10]\r\n        [  9.86479981e-16]\r\n        [  0.00000000e+00]\r\n        [ -1.60491195e-13]\r\n        [  4.65661287e-10]\r\n        [ -1.42115222e-11]]\r\n\r\n.. |github| image:: https://img.shields.io/github/followers/gusmaogabriels.svg?style=social&label=Follow\r\n   :scale: 25%\r\n   :target: https://github.com/gusmaogabriels\r\n\r\n.. |fork| image:: https://img.shields.io/github/forks/gusmaogabriels/mkin4py.svg?style=social&label=Fork\r\n   :scale: 25%\r\n   :target: https://github.com/gusmaogabriels/mkin4py/fork\r\n\r\n.. |star| image:: https://img.shields.io/github/stars/gusmaogabriels/mkin4py.svg?style=social&label=Star\r\n   :scale: 25%\r\n   :target: https://github.com/gusmaogabriels/mkin4py/stargazers\r\n\r\n.. |watch| image:: https://img.shields.io/github/watchers/gusmaogabriels/mkin4py.svg?style=social&label=Watch\r\n   :scale: 25%\r\n   :target: https://github.com/gusmaogabriels/mkin4py/watchers\r\n\r\n.. |rg| image:: https://www.researchgate.net/images/public/profile_share_badge.png\r\n   :height: 55 px\r\n   :width: 166 px\r\n   :scale: 30 %\r\n   :target: https://www.researchgate.net/profile/Gabriel_Gusmao?cp=shp\r\n\r\n.. |ld| image:: https://static.licdn.com/scds/common/u/img/webpromo/btn_viewmy_160x25.png\r\n   :height: 25 px\r\n   :width: 160 px\r\n   :scale: 50 %\r\n   :target: https://br.linkedin.com/pub/gabriel-saben%C3%A7a-gusm%C3%A3o/115/aa6/aa8",
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        "keywords": "python,microkinetics,linearized,solver,chemical,kinetics,power-law",
        "license": "The MIT License (MIT)",
        "maintainer": "Gabriel Saben\u00e7a Gusm\u00e3o",
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