End-to-end prediction and design of additively manufacturable alloys using a generative AlloyGPT model

Related articles

1. An interpretable learning framework for exploring superelastic degradation of NiTi shape memory alloys using multimodal data

   This article has 7 authors:

   1. Chuanjie Wang
   2. Yuejie Hu
   3. Haiyang Wang
   4. Ming Chen
   5. Gang Chen
   6. Bin Guo
   7. Mingwang Fu

2. AdditiveGDL: Generative deep learning for predicting local thermal distributions in metal 3D-printed layers

   This article has 3 authors:

   1. David Guirguis
   2. Conrad Tucker
   3. Jack Beuth

3. A Novel Genetic Optimized LSTM Algorithm for Stress-Strain Modeling of High Performance Cementitious Materials in Rock and Geotechnical Applications

   This article has 8 authors:

   1. Mahmoud AlJamal
   2. Qasim Aljamal
   3. Mohammad Q. Al-Jamal
   4. Bashar S. Khassawneh
   5. Mohammad Aljaidi
   6. Kaznah Alshammari
   7. Ali Fayez Alkoradees
   8. Duaa Telfah