246 citations · 987 across the 26 of their papers we have counts for
6 papers · 1 filter
Deep learning-aided inverse design of porous metamaterials
Phu Thien Nguyen, Yousef Heider, Dennis M. Kochmann +1
The ultimate aim of the study is to explore the inverse design of porous metamaterials using a deep learning-based generative framework. Specifically, we develop a property-variati…
Predicting temperature-dependent failure and transformation zones in 2D silica glass through quasistatic Gaussian Phase Packets
Miguel Spínola, Shashank Saxena, Franz Bamer +1
The athermal quasistatic (AQS) method is a powerful technique to study the mechanical behavior of disordered systems. However, its applicability is limited to temperatures near zer…
Graded phononic metamaterials: Scalable design meets scalable microfabrication
Charles Dorn, Vignesh Kannan, Ute Drechsler +1
Metamaterials are a new generation of advanced materials, exhibiting engineered microstructures that enable customized material properties not found in nature. The dynamics of meta…
Algebraic Language Models for Inverse Design of Metamaterials via Diffusion Transformers
Li Zheng, Siddhant Kumar, Dennis M. Kochmann
Generative machine learning models have revolutionized material discovery by capturing complex structure-property relationships, yet extending these approaches to the inverse desig…
Microscale architected materials for elastic wave guiding: Fabrication and dynamic characterization across length and time scales
Vignesh Kannan, Charles Dorn, Ute Drechsler +1
We present an experimental protocol for the fabrication and characterization of scalable microarchitected elastic waveguides. Using silicon microfabrication techniques, we develop…
Long-term atomistic finite-temperature substitutional diffusion
Shashank Saxena, Prateek Gupta, Dennis M. Kochmann
Simulating long-term mass diffusion kinetics with atomic precision is important to predict chemical and mechanical properties of alloys over time scales of engineering interest in…