Foretelling microstructural interface with multi-generational convolutional-LSTM framework

The dataset is arranged within folders inside the "microstructure-model-computer-vision.zip" zip folder in such a way that they holistically represent a step-by-step workflow for integrating phase-field simulations with machine learning methodologies. Thus the overall methodology is organized into seven structured steps, each represented by corresponding dataset type contained within a dedicated folder.The instructions are provided in each folder sequentially to promote the understandability of the codes/data contained therein. The seven steps represented by seven dataset folders are as following: Contents: Step 0: Phase-Field SimulationsInstructions and data for running initial phase-field simulations.Folder: Step_0_phase_field_simulations Step 1: Train-Test Data PreparationScripts and guidance for generating and organizing training/testing datasets.Folder: Step_1_train_test_data Step 2: Model DevelopmentTools and models for training machine learning algorithms using simulation data.Folder: Step_2_model_development Step 3: PredictionsApplication of trained models to generate predictions on unseen data.Folder: Step_3_predictions Step 4: Quantification and AnalysisEvaluation of model outputs, including error quantification and comparative metrics.Folder: Step_4_quantification Step 5: Engineering Alloys ApplicationsCase studies and use-cases focused on engineering alloy systems.Folder: Step_5_Engg_Alloys Step 6: Appendix and Graphical AbstractSupporting materials, visual summaries, and appendix content.Folder: Step_6_Appendix_And_Graphical_Abstract Usage:Each folder (corresponding to each of the steps above) again contains a README.txt or instruction file detailing how to run the code or interpret the data within that step.