• MINFIT: Simply Use MINEQL+ to Fit Data

    A Spreadsheet-based Tool for Parameter Estimation in an Equilibrium Speciation Software Program

  • Features

    MINFIT has the lowest activation barrier and takes the full advantage of the easiness and robustness of MINEQL+

    Free of Non-Convergence

    Compared with other inverse modeling software programs, MINFIT is free of non-convergence problems. As long as the forward model can be run on MINEQL+, then MINFIT can perform any parameter estimation tasks within that model. It avoids the pitfalls related to problematic initial guesses, and MINFIT is unlikely to return local minimum solutions as the equidistant grid search is exhaustive.

    Flexibility and Transparency

    MINFIT can generate “”Field Data” files according to the user-defined experimental results in any format such as adsorption isotherms or even randomly organized data sets. The transparent structure of MINFIT also allows for the user to define any objective function that may be calculated from metrics that MINEQL+ outputs. The users can modify the formula in calculating the individual residual on the “Calibration” tab.

    Convenient Interface for Graphics

    The “Review Residual” button in the “Calibration” tab sorts the results and generates hyperlinks to each simulation. Those hyperlinks paste the corresponding simulation results together with the experimental conditions and results into the “Summary” tab. This feature allows users to customize graphic visualization of the goodness of the fit as well as the progress of optimization using built-in graphing functions of Excel that can be automatically updated upon each click of the hyperlinks.

    Weighting Factors and Sensitivity Analysis 

    The information generated by MINFIT can calculate several useful statistical metrics that are reported by other software programs. MINFIT allows the use of a weighing factor table that is assigned to each data point. MINFIT also enables convenient evaluation of sensitivity of the object function in response to the variation of the individual fitting parameter.

     

  • How MINFIT Works

    MINFIT enables automatic generation of the “Field Data” text file and convenient screening of a large number of parameter sets towards the optimal solutions by calling MINEQL+ to perform iterative forward calculations following either exhaustive equidistant grid search or randomized search algorithms.

  • Spreadsheet Based Interface

    • Simple interface based on Microsoft Excel that only require basic knowledge of spreadsheet calculator.
    • Fully transparent and user-supervised operation.

  • Download

    If you have any problem accessing the files, feel free to contact Zimeng Wang.

    Microsoft Excel Based Program

    V1.1 Oct 2016

    • Download the program MINFIT 1.1 (2016/10/11) here
    • MINFIT is Free Software licensed under the Gnu General Public License (GPL).

    Example-based Tutorials

    V1.0 June 2016​

    • A step-by-step tutorial with three illustrative examples. (Download it here.)
    • The .mif files (MINEQL+ 4.6 ) for the examples. (Please request from Prof. Zimeng Wang.)
    • Additional tutorials for MINEQL+. (Download them here.)
  • Authors

    Please contact the corresponding author, Zimeng Wang (zimengw@lsu.edu)

    Professor

    Fudan University

    Hydraulic Engineer

    Pinellas County Utilities, Tampa, Florida

    Walter E. Browne Professor

    Washington University in St. Louis

  • Publications

    A research article describing the idea and approach of MINFIT

    Xie, X.; Giammar, D.E.; Wang, Z.* MINFIT: A spreadsheet-based tool for parameter estimation in an equilibrium speciation software program. Environmental Science & Technology 2016 DOI: 10.1021/acs.est.6b03399 (Open Access PDF)

     

    If you used MINFIT in your research, please cite the Xie et al. ES&T paper so that we can track the use of this tool.

     

    Peer-reviewed publications that used or cited MINFIT:

    1. Gu, C., Wang, Z., Kubicki, J. D., Wang, X., & Zhu, M. (2016). X-ray absorption spectroscopic quantification and speciation modeling of sulfate adsorption on ferrihydrite surfaces. Environmental science & technology50(15), 8067-8076.
    2. Fang, L., Shi, Q., Nguyen, J., Wu, B., Wang, Z., & Lo, I. M. (2017). Removal mechanisms of phosphate by lanthanum hydroxide nanorods: investigations using EXAFS, ATR-FTIR, DFT, and surface complexation modeling approaches. Environmental science & technology51(21), 12377-12384.
    3. Pan, Z., Li, W., Fortner, J. D., & Giammar, D. E. (2017). Measurement and surface complexation modeling of U (VI) adsorption to engineered iron oxide nanoparticles. Environmental science & technology51(16), 9219-9226.
    4. Wang, X., Wang, Z., Peak, D., Tang, Y., Feng, X., & Zhu, M. (2018). Quantification of coexisting inner-and outer-sphere complexation of sulfate on hematite surfaces. ACS Earth and Space Chemistry2(4), 387-398.
    5. Burch, S. (2018). Evaluating Biochar for the Sustainable Treatment of Heavy Metals in Stormwater: Characteristics, Mechanisms, and Barriers.
    6. Bompoti, N. M., Chrysochoou, M., & Machesky, M. L. (2018). Assessment of Modeling Uncertainties Using a Multistart Optimization Tool for Surface Complexation Equilibrium Parameters (MUSE). ACS Earth and Space Chemistry.
    7. Qian, A., Zhang, W., Shi, C., Pan, C., Giammar, D. E., Yuan, S., ... & Wang, Z. (2019). Geochemical Stability of Dissolved Mn (III) in the Presence of Pyrophosphate as a Model Ligand: Complexation and Disproportionation. Environmental science & technology.
    8. Zhao, W., Liu, Z., Yuan, Y., Liu, F., Zhu, C., Ling, C., & Li, A. M. (2019). Insight into Cu (II) Adsorption on Polyamine Resin in Presence of HEDP by Tracking the Evolution of Amino Groups and Cu (II)-HEDP Complexes. ACS Sustainable Chemistry & Engineering.
    9. Xie, X., Schluender, D., Mattiacci, T., & Wang, Z. (2017). Simulation of wastewater hydraulics in force main with local highest point. Journal of Water Resources Planning and Management143(5), 05017001.