Metadata-Version: 2.1
Name: SESAMI
Version: 2.4
Summary: Characterization Tools for Porous Materials Using Nitrogen/Argon Adsorption
Home-page: https://github.com/hjkgrp/SESAMI_web/
Author: Guobin Zhao
Author-email: sxmzhaogb@gmai.com
License: MIT
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: scipy
Requires-Dist: matplotlib
Requires-Dist: statsmodels
Requires-Dist: pandas
Requires-Dist: flask
Requires-Dist: pymongo[srv] ==4.1.1
Requires-Dist: numpy
Requires-Dist: scikit-learn ==1.3.2

<h1 align="center">SESAMI</h1>

<h4 align="center">

</h4>              

**SESAMI**: 

[![Requires Python 3.9](https://img.shields.io/badge/Python-3.9-blue.svg?logo=python&logoColor=white)](https://python.org/downloads) [![MIT](https://img.shields.io/badge/License-MIT-blue.svg)](https://github.com/mtap-research/PACMAN-charge/LICENSE)![Build Status](https://img.shields.io/badge/build-passing-brightgreen) [![Gmail](https://img.shields.io/badge/Gmail-D14836?style=for-the-badge&logo=gmail&logoColor=white)](mailto:sxmzhaogb@gmail.com) [![Linux](https://img.shields.io/badge/Linux-FCC624?style=for-the-badge&logo=linux&logoColor=black)]() [![Windows](https://img.shields.io/badge/Windows-0078D6?style=for-the-badge&logo=windows&logoColor=white)]()          


# Usage

```sh      
from SESAMI.run import calculation_bet

calculation_bet(csv_file="example.csv", columns=["Pressure","Loading"],
                    adsorbate="N2", p0=1e5, T=77,
                    R2_cutoff=0.9995, R2_min=0.998,
                    font_size=12, font_type="DejaVu Sans",
                    legend=True, dpi=600, save_fig=True)
```

*   csv_file: N2 isotherm csv file
*   columns: [Pressure, Loading], 2 columns, one for rpessure (unit: Pa), one for uptake (unit: mmol/g)
*   adsorbate: N2, Ar or other
*   p0: if other
*   T:  test temperature if other
*   R2_cutoff (default: 0.9995): The value of R2 beyond which we deem R2 ceases to have a bearing on the goodness of the linear region.                                                                            
*   R2_min (default: 0.998): R2 value a chosen region must have to be termed *linear*                       
*   font_size: word size in figure
*   font_type: word type in figure
*   legend: with legend in figure or not
*   dpi: dpi in figure
*   save_fig: save png or not
                                                        
```
from SESAMI.predict import betml

betml(csv_file="example.csv")
```
*   csv_file: N2 isotherm csv file, we recommend the columns name of pressure and uptake is *Pressure* and *Loading*, and the 1st column should be pressure with unit as *Pa* and 2nd column should be uptake with unit as *mmol/g*   



# Website
SESAMI-APP[link](https://sesami-web.org/)       

# Reference
SESAMI-APP: [SESAMI APP: An Accessible Interface for Surface Area Calculation of Materials from Adsorption Isotherms](https://joss.theoj.org/papers/10.21105/joss.05429)               
Algorithms: [Surface Area Determination of Porous Materials Using the Brunauer–Emmett–Teller (BET) Method: Limitations and Improvements](https://doi.org/10.1021/acs.jpcc.9b02116)               
Machine Learning Model: [Beyond the BET Analysis: The Surface Area Prediction of Nanoporous Materials Using a Machine Learning Method](https://doi.org/10.1021/acs.jpclett.0c01518)            


# Bugs

If you encounter any problem during using ***SESAMI***, please email ```sxmzhaogb@gmail.com```.                 
             
                                                          
**Group:**   [Molecular Thermodynamics & Advance Processes Laboratory](https://sites.google.com/view/mtap-lab)                                
