activity
20212026
most citedGenerative deep learning as a tool for inverse design of high-entropy refractory alloys

52 citations · 64 across the 7 of their papers we have counts for

collaborators

7 papers

cond-mat.mtrl-sci2026

Phase stability and mechanical response of Ag-interlayered Al/Cu resistance spot-welded joints

Shuang Lin, Kyubok Lee, Jiahui Ye +6

Dissimilar Al/Cu joints are essential to battery-pack assemblies; however, their mechanical strength is limited by brittle Al-Cu intermetallic compounds (IMCs) such as Al2Cu and Al…

cond-mat.mtrl-sci2025

Thermodynamic modeling of binaries in Cr-Fe-Mo-Nb-Ni supported by first-principles calculations

Hui Sun, Shun-Li Shang, Shuang Lin +3

Thermodynamic descriptions of all binaries within the Cr-Fe-Mo-Nb-Ni system have been complied and, where necessary, remodeled. Notably, the Cr-Fe and Fe-Mo systems have been remod…

cond-mat.mtrl-sci2024★ 7 cited

Investigation of ideal shear strength of dilute binary and ternary Ni-based alloys using first-principles calculations, CALPHAD modeling and correlation analysis

Shuang Lin, Shun-Li Shang, John D. Shimanek +3

In the present work, the ideal shear strength (τ_is) of dilute Ni34XZ ternary alloys (X or Z = Al, Co, Cr, Fe, Mn, Mo, Nb, Si, Ti) are predicted by first-principles calculations ba…

cond-mat.mtrl-sci2024★ 1 cited

Temperature-dependent thermodynamic properties of CrNbO4 and CrTaO4 by first-principles calculations

Shuang Lin, Shun-Li Shang, Allison M. Beese +1

In the present work, the density functional theory (DFT) in the generalized-gradient approximation developed by Perdew, Burke, and Ernzerhof (PBE) +U method, i.e., PBE+U, was emplo…

cond-mat.mtrl-sci2023★ 3 cited

Predictions and correlation analyses of Ellingham diagrams in binary oxides

Shun-Li Shang, Shuang Lin, Michael C. Gao +2

Knowing oxide-forming ability is vital to gain desired or avoid deleterious oxides formation through tuning oxidizing environment and materials chemistry. Here, we have conducted a…

cond-mat.mtrl-sci2023★ 1 cited

Comparing Forward and Inverse Design Paradigms: A Case Study on Refractory High-Entropy Alloys

Arindam Debnath, Lavanya Raman, Wenjie Li +7

The rapid design of advanced materials is a topic of great scientific interest. The conventional, ``forward'' paradigm of materials design involves evaluating multiple candidates t…

cond-mat.mtrl-sci2021★ 52 cited

Generative deep learning as a tool for inverse design of high-entropy refractory alloys

Arindam Debnath, Adam M. Krajewski, Hui Sun +9

Generative deep learning is powering a wave of new innovations in materials design. In this article, we discuss the basic operating principles of these methods and their advantages…