5 papers
Comprehensive Workflow for Uncertainty-Aware Ionic Liquid Solvent Discovery
Alexander Lobo, Urvi Awasthi, Leonid Zhukov
Designing synthesizable materials with targeted properties remains one of the central objectives in materials sciences. Ionic liquids (ILs) are well suited to this goal due to thei…
tidyHEBO: Improving the Robustness of Heteroskedastic Evolutionary Bayesian Optimization
L. A. Zhukov, E. V. Shaburova, D. V. Antonets
Bayesian optimization is widely used for expensive black-box optimization problems. While methodological advances often focus on individual components, practical performance depend…
Hierarchy-Guided Topology Latent Flow for Molecular Graph Generation
Urvi Awasthi, Alexander Arjun Lobo, Leonid Zhukov
Generating chemically valid 3D molecules is hindered by discrete bond topology: small local bond errors can cause global failures (valence violations, disconnections, implausible r…
Property-Guided Molecular Generation and Optimization via Latent Flows
Alexander Arjun Lobo, Urvi Awasthi, Leonid Zhukov
Molecular discovery is increasingly framed as an inverse design problem: identifying molecular structures that satisfy desired property profiles under feasibility constraints. Whil…
AI-Guided Discovery of Novel Ionic Liquid Solvents for Industrial CO2 Capture
Davide Garbelotto, Alexander Lobo, Urvi Awasthi +8
We present an AI-driven approach to discover compounds with optimal properties for CO2 capture from flue gas-refinery emissions' primary source. Focusing on ionic liquids (ILs) as…