4 papers
XMOL: Explainable Multi-property Optimization of Molecules
Aye Phyu Phyu Aung, Jay Chaudhary, Ji Wei Yoon +1
Molecular optimization is a key challenge in drug discovery and material science domain, involving the design of molecules with desired properties. Existing methods focus predomina…
SG-NNP: Species-separated Gaussian Neural Network Potential with Linear Elemental Scaling and Optimized Dimensions for Multi-component Materials
Ji Wei Yoon, Bangjian Zhou, J Senthilnath
Accurate simulations of materials at long-time and large-length scales have increasingly been enabled by Machine-learned Interatomic Potentials (MLIPs). There have been increasing…
Self-evolving Autoencoder Embedded Q-Network
J. Senthilnath, Bangjian Zhou, Zhen Wei Ng +7
In the realm of sequential decision-making tasks, the exploration capability of a reinforcement learning (RL) agent is paramount for achieving high rewards through interactions wit…
Generating Nanoporous Graphene from Point and Stone-Wales Defects: A Study with Dimensionally Restricted Molecular Dynamics (DR-MD)
Ji Wei Yoon
Defects in graphene are both a boon and a bane for applications - they can induce uncontrollable effects but can also provide novel ways to manipulate the properties of pristine gr…