5 papers
Linking Electronic Bonding and Short-range Order to Strength in -Titanium Alloys: A First-Principles Study
Md Faiz Akhtar, Nilesh P. Gurao, Somnath Bhowmick
The development of accurate strength prediction models for titanium alloys is critical for advanced materials design. This study systematically examines how the mechanical properti…
Bridging Phase-Field Model and Deep Learning for Predicting 2D and 3D Microstructure Evolution in Ternary Alloys
Owais Ahmad, Aravind K, Naveen Kumar +3
We develop a hybrid framework that integrates a phase-field model (PFM) with an attention-enhanced deep learning (DL) architecture to study ternary spinodal dealloying, a sophistic…
Physics Aware Representation Learning on Electronic Charge Density for Materials Property Prediction
Kammampati Sai Kumar, Albert Linda, Shubham Kumar Maurya +1
The fundamental quantity governing the mechanical and thermodynamic properties of a crystalline solid is its electronic charge density. Yet, its direct use for the rapid prediction…
Deep Learning-Driven Prediction of Microstructure Evolution via Latent Space Interpolation
Sachin Gaikwad, Thejas Kasilingam, Owais Ahmad +2
Phase-field models accurately simulate microstructure evolution, but their dependence on solving complex differential equations makes them computationally expensive. This work achi…
Microstructural Studies Using Generative Adversarial Network (GAN): a Case Study
Owais Ahmad, Vishal Panwar, Kaushik Das +2
The generative adversarial network (GAN) is one of the most widely used deep generative models for synthesizing high-quality images with the same statistics as the training set. Fi…