Data

Tools

Indexes

Applications

Experiments

Open Source Science

https://github.com/aspuru-guzik-group/acdc_laser

https://github.com/aspuru-guzik-group/acdc_laser

Science Score: 57.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • ○
    CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
  • ✓
    .zenodo.json file
    Found .zenodo.json file
  • ✓
    DOI references
    Found 6 DOI reference(s) in README
  • ✓
    Academic publication links
    Links to: zenodo.org
  • ○
    Academic email domains
  • ✓
    Institutional organization owner
    Organization aspuru-guzik-group has institutional domain (aspuru.chem.harvard.edu)
  • ○
    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (5.5%) to scientific vocabulary
Last synced: 6 months ago · JSON representation

Repository

Basic Info
  • Host: GitHub
  • Owner: aspuru-guzik-group
  • Language: Python
  • Default Branch: main
  • Size: 90.2 MB
Statistics
  • Stars: 9
  • Watchers: 5
  • Forks: 1
  • Open Issues: 1
  • Releases: 1
Created over 3 years ago · Last pushed over 2 years ago
Metadata Files
Readme

readme.md

Delocalized, Asynchronous, Closed-Loop (ACDC) Discovery of Organic Laser Materials

F. Strieth-Kalthoff, H. Hao, et al.

Preprint available at: ChemRxiv 2023, DOI: 10.26434/chemrxiv.00000000.v1

Contents of this Repository

  • Workflows/: Higher-level workflow scripts used for running the optimization campaign (Data Processing, Analysis, Bayesian Optimization)
  • HighThroughputDFT/: Scripts and workflows for computational screening of excited-state properties
  • SupervisedLearning/: Workflows for training and evaluating supervised learning models for molecular propertiey prediction
  • GraphNeuralNetwork/: Graph neural network used for representation learning
  • BayesianOptimization/: Library for discrete, batch-wise, asynchronous Bayesian optimization
  • Data/: Training data required for reproducing the models shown in the paper. All data generated within this study is available on Zenodo (see below)

Data Availability

All data generated within this study has been deposited on Zenodo.

DOI

Owner

  • Name: Aspuru-Guzik group repo
  • Login: aspuru-guzik-group
  • Kind: organization

GitHub Events

Total
  • Fork event: 1
Last Year
  • Fork event: 1

Dependencies

BayesianOptimization/requirements.txt pypi
  • botorch *
  • gpytorch *
  • numpy *
  • scikit-learn *
  • torch *
  • tqdm *
GraphNeuralNetwork/requirements.txt pypi
  • deepchem *
  • dm-sonnet *
  • graph-nets *
  • joblib *
  • numpy *
  • rdkit *
  • scikit-learn *
  • tensorflow *
  • tqdm *
SupervisedLearning/requirements.txt pypi
  • deepchem *
  • gpytorch *
  • joblib *
  • mordred *
  • ngboost *
  • numpy *
  • pandas *
  • rdkit *
  • scikit-learn *
  • scipy *
  • torch *
  • xgboost *
Workflows/DatabaseInterface/requirements.txt pypi
  • molar ==0.4.4
  • pandas ==1.5.0
  • python-dotenv ==0.21.0
  • python-magic ==0.4.27
  • requests ==2.28.1
Workflows/requirements.txt pypi
  • chronos *
  • gnn *
  • joblib *
  • molarinterface *
  • numpy *
  • pandas *
  • rdchiral_cpp *
  • rdkit *
  • scipy *