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NISTCOLLECT: NIST/ARPA-E dataset composer

1. Project Overview

NISTCOLLECT is a python application developed to extract adsorption isotherms data from the NIST/ARPA-E Database of Novel and Emerging Adsorbent Materials (https://adsorption.nist.gov/index.php#home) through their dedicated API. The user can either collect data regarding adsorbent materials and adsorbate species or fetch adsorption isotherm experimental data directly. Experiments are identified by name upon building the entire database experiments index from the API endpoint. Furthermore, NISTADS exploits the PUG REST API (see https://pubchempy.readthedocs.io/en/latest/ for more information) to enrich the adsorbate species dataset with molecular properties (such as molecular weight, canonical smiles, complexity, heavy atoms, etc.). Eventually, the adsorption isotherm dataset is split into two datasets, one containing data on single component adsorption and the other including experiments with binary mixtures.

Adsorbent material

2. Adsorption datasets

The collected data is saved locally in 4 different .csv files. Adsorption isotherm datasets are saved in resources/adsorption, while the adsorbents and adsorbates datasets are saved into resources/materials. The former will include the experiments datasets for both single component and binary mixture measurements, while the latter will host datasets on guest and host species.

2. Installation

The installation process is designed for simplicity, using .bat scripts to automatically create a virtual environment with all necessary dependencies. Please ensure that Anaconda or Miniconda is installed on your system before proceeding.

  • The scripts/environment_setup.bat file, located in the scripts folder, offers a convenient one-click solution to set up your virtual environment.
  • IMPORTANT: run scripts/package_setup.bat if the path to the project folder is changed for any reason after installation, or the app won't work!

3. How to use

Within the main project folder (NISTCOLLECT) you will find other folders, each designated to specific tasks.

Resources

This folder is used to organize the main data for the project, including all collected data from the NIST database. Experimental measurements are saved in .csv format in resources/adsorption, while the data regarding guest and host materials will be saved in resources/materials. Eventually, the app logs are saved in resources/logs.

Datasets

Contains the scripts developed to extract data from the NIST DB and organise them into a readable .csv format. Data is collected through the NIST API in a concurrent fashion, allowing for fast data retrieval by selecting a maximum number of parallel HTTP requests.

  • Run retrieve_experiments_dataset.py to fetch data for adsorption experiments
  • Run retrieve_materials_dataset.py to respectively fetch data for adsorption experiments or for the guest/host entries. The data collection operation may take long time due to the large number of queries to perform, and it heavily depends on your internet connection performance (more than 30k experiments are available as of now). You can select a fraction of data that you wish to extract (guest, host, or experiments data), and you can also split the total number of adsorption isotherm experiments in chunks, so that each chunk will be collected and saved as file iteratively. Use the notebook dataset_analysis.ipynb to perform explorative data analysis on the collected datasets.

Experimental

Contains experimental features to integrate further information into the dataset. Description of chemicals (both adsorbate species and adsorbent materials) can be generated using the pretrained GPT2 model using gpt_enhancement.py. Due to the model limitations, description may not be very accurate and lack context for more complex molecules and materials.

3.1 Configurations

For customization, you can modify the main configuration parameters using settings/configurations.json

General Configuration

The script is able to perform parallel data fetching through asynchronous HTML requests. However, too many calls may lead to server busy errors, especially when collecting adsorption isotherm data. Try to keep the number of parallel calls for the experiments data below 50 concurrent calls and you should not see any error!

| Setting | Description | |-------------------------------------------------------------------------------| | GUEST_FRACTION | fraction of adsorbate species data to fetch | | HOST_FRACTION | fraction of adsorbent materials data to fetch | | EXP_FRACTION | fraction of adsorption isotherm data to fetch | | PARALLEL_TASKS_GH | parallel calls to get guest/host data | | PARALLEL_TASKS_EXP | parallel calls to get experiment data |

License

This project is licensed under the terms of the MIT license. See the LICENSE file for details.