This readme.txt file was generated on 20220301 by Vaidyanathan M. Sethuraman ------------------- GENERAL INFORMATION ------------------- 1. Title of Dataset: Simulation data for Adsorption of Charge Sequence-Specific Polydisperse Polyelectrolytes. 2. Author Information Principal Investigator Contact Information Name: Kevin D. Dorfman Institution: Chemical Engineering and Materials Science, University of Minnesota Address: Email: dorfman@umn.edu ORCID: Associate or Co-investigator Contact Information Name: David C. Morse Institution: Chemical Engineering and Materials Science, University of Minnesota Address: Email: morse012@umn.edu ORCID: Associate or Co-investigator Contact Information Name: Vaidyanathan M. Sethuraman Institution: Chemical Engineering and Materials Science, University of Minnesota Address: Email: msvaidyanathan1729@gmail.com ORCID: 3. Date of data collection (single date, range, approximate date) From 20190801 to 20220301 4. Geographic location of data collection (where was data collected?): N/A 5. Information about funding sources that supported the collection of the data: This work was supported primarily by the National Science Foundation through the University of Minnesota Materials Science Research and Engineering Center under Award No. DMR-1420013 and DMR-2011401. -------------------------- SHARING/ACCESS INFORMATION -------------------------- 1. Licenses/restrictions placed on the data: None 2. Links to publications that cite or use the data: Under Review, Macromolecules 3. Links to other publicly accessible locations of the data: 4. Links/relationships to ancillary data sets: 5. Was data derived from another source? If yes, list source(s): 6. Recommended citation for the data: Under Review, Macromolecules --------------------- DATA & FILE OVERVIEW --------------------- All codes (with their modifications) are publicly available at https://github.com/vaidyanathanms/polydisperse_PE Code Details LAMMPS codes: Aug-11-2017 version (see src_lmp) FORTRAN codes: Requires ifort compiler (see src_f90) Python codes: Requires V3.0+ (see src_f90) MATLAB codes: Requires 2019b+ (see src_matlab) NOTE1: For the Python codes, check the directory paths and rename accordingly. The scratch (where the codes will be running) will be DIFFERENT and needs to be changed accordingly. Specifically, one needs to set "jobdir", "scratchdir" and "lmpdir" whenever necessary. Please do a grep command to find the points where they are defined. NOTE2: The path to the executable for LAMMPS - lmp_mesabi also needs to be changed. Please do a grep for "lmp_mesabi" to see where they needs to be changed. File Uses FORTRAN/Python Codes newparams_genconf2.py - To generate the input configurations. See "Inputs" within the code to see the kind of inputs required. ana.py - To compute the analysis of the data generated. copy_to_analyze.py - To copy all the analysis output files to a new directory for further analysis with MATLAB. my_python_functions.py - Supplemental functions for running python codes. NOTE1: The FORTRAN files are called within the python files to generate the SZ distribution (SZdist2.f90) and generating the LAMMPS inputs (params_inpconf.f90, inpconf_generator.f90, ran_numbers.f90). Analysis files are called using ana.py and the dependencies are pe_analyze.f90 and pe_params.f90 NOTE2: Some of the FORTRAN and input files may have a _var version which is used by the python codes to replace the inputs/parameters with user input versions. DO NOT delete this versions if the user is using the Python codes LAMMPS Codes in.init/in.init_var - Initialize system and move use NVE/limit in.run1 - First equilibration step in.run2 - Second equilibration step/Production cycle = in.longrun - Production cycle How to use the MATLAB files: ./ refers to directory where MATLAB files are Copy all output from Mesabi into the sim_results directory (make if it doesn't exist). If copy_to_analyze.py is used before copying the files to be analyzed, only ../../sim_results and ../../monads needs to be made MATLAB Codes ***** File 1: adsfrac.m ********************************************************************* Use adsfrac.m to compute the adsorbed fraction of CHAINS. Inputs should be in ../../sim_results/outresults_dir_n_* With ttestflag ON, this also writes the individual avg_f values for each case into ../../ttest_dir. Outputs to ../../outfiles and its subdirectory ***** File 2: basic_ttest.m ****************************************************************** Use basic_ttest.m to compute the tvalue between any two ref archs at a given pdi and n_pa value. Requires output from adsfrac.m. Run adsfrac.m before running this code. USE TAB as delimiters when using text to columns in EXCEL to view the file outputs (this may not be required. depends on the editor used). **** File 3: analyze_pdi_mw_dist.m *********************************************************** Use this to compute the pdi and mw distribution for any given configuration. Input requires the datafile generated by LAMMPS. Dependencies: compute_pdi.m, compute_mwdist.m **** File 4: out_mwdist.m ********************************************************************* Use this to compute the MW distribution of the adsorbed polymer fraction. Input requires the chainadsval_rcut_* for all the configurations. Use FORTRAN codes (pe_analyze.f90/pe_main.f90) to analyze the trajectories generated by LAMMPS to generate chainadsval_rcut_* files. Dependencies: extract_adschain.m, find_distribution_of_mw.m Output: generates the adsorbed fraction for the range of MWs. See the code for algorithm **** File 5: avg_and_coarsen_dist.m ********************************************************************* Plots the distribution of fraction of chains adsorbed after averaging/coarsening Run out_mwdist.m before doing this. ***** File 6: adsfrac_mons.m ********************************************************************* Use adsfrac.m to compute the adsorbed fraction of MONOMERS. Inputs should be in the directory ../../sim_results/outresults_dir_n__* Outputs to ../../monads and its subdirectory ***** File 7: plot_paper.m ********************************************************************* To plot the data for the paper. See code comments for instructions ***** File 8: netcharge_brush.m ********************************************************************* Input files required are ./../../data_all_dir/n_*/PEinitdata.txt and ./../../sim_results/outresults_dir_n_%d/%s/pdifree_%s_pdigraft_%s/Case_%d/dens_config*.lammpstrj Output files will be in ./../../net_charge Run plot_paper.m to obtain the plots after running this ***** File 8: compute_adsfrac_newdef.m ********************************************************************* Input files required are ./../../monads/outresults_dir_n_%d/%s/pdifree_%s_pdigraft_%s/Case_%d/adsfrac_chmw_config*.lammpstrj Computes the adsorbed fraction of monomers according to the definition that if a chain is adsorbed, the number of monomers adsorbed is equal to the MW of the chain. Output files will be in ./../../monads/overall/ Run plot_paper.m to obtain the plots after running this ***** File 9: generate_numavgMW.m ********************************************************************* Input files required are ./../../numavg_mw/outresults_dir_n_%d/%s/pdifree_%s_pdigraft_%s/Case_%d/adsfrac_chain_config*.lammpstrj AND ./../../numavg_mw/outresults_dir_n_%d/%s/pdifree_%s_pdigraft_%s/Case_%d/adsfrac_chmw_config*.lammpstrj NOTE: Make sure that the files have the same timestep prefixed to *.lammpstrj. Generates the time data for the number averaged MW. Output files will be in the same directory where input files are found with adsfrac_numavg_config*.lammpstrj. Run compute_numavgMW.m after this. ***** File 10: compute_numavgMW.m ********************************************************************* Input files required are ./../../numavgMW/outresults_dir_n_%d/%s/pdifree_%s_pdigraft_%s/Case_%d/adsfrac_numavg_rcut_*_config*.lammpstrj Output files will be in ./../../outfiles/overall/ Computes number averaged MW Run plot_paper.m to obtain the plots after running this ***** File 11: fit_to_theory_v2.m ********************************************************************* Input files required are ./../../Figs_Paper/fig7_*_distribution.fig (* corresponds to 'blbl' or 'alal' The code reads the distribution figure and analyzes Computes regression to the model presented in the paper and the output regression values Output files: '../../Figs_Paper/alal_panel*.eps' or '../../Figs_Paper/blb_panel*.eps' and all linear fit data. Regressed coefficients are found in '../../outfiles/overall/*_regression.dat' where * corresponds to blbl or alal. ***** File 12: *_seq.m ********************************************************************* Input files required are in ./../../seq_analysis The code does the corresponding postprocessing as for Files 1,3,4,7-10 except for different sequence at fixed npa Output files are in ./../../seq_analysis 2. Relationship between files: Order of Usage Use newparams_genconf2.py to create and run LAMMPS Use ana.py to analyze data Use copy_to_analyze.py to consolidate outputs See MATLAB folder to postprocess data. 3. Additional related data collected that was not included in the current data package: N/A 4. Are there multiple versions of the dataset? yes/no If yes, list versions: Name of file that was updated: i. Why was the file updated? ii. When was the file updated? Name of file that was updated: i. Why was the file updated? ii. When was the file updated? -------------------------- METHODOLOGICAL INFORMATION -------------------------- 1. Description of methods used for collection/generation of data: Computer Simulations Software used: LAMMPS Analysis Codes: Python 3+, FORTRAN90 and MATLAB 2. Methods for processing the data: Using Python 3+, FORTRAN90 and MATLAB Raw data used in the figures can be found in the Supplementary Information of the puiblication. 3. Instrument- or software-specific information needed to interpret the data: LAMMPS, Python 3+, FORTRAN90 and MATLAB 4. Standards and calibration information, if appropriate: N/A 5. Environmental/experimental conditions: N/A 6. Describe any quality-assurance procedures performed on the data: N/A 7. People involved with sample collection, processing, analysis and/or submission: ----------------------------------------- DATA-SPECIFIC INFORMATION FOR: [FILENAME] ----------------------------------------- 1. Number of variables: 2. Number of cases/rows: 3. Missing data codes: Code/symbol Definition Code/symbol Definition 4. Variable List Example. Name: Gender Description: Gender of respondent 1 = Male 2 = Female 3 = Other A. Name: Description: Value labels if appropriate B. Name: Description: Value labels if appropriate