2 citations · 4 across the 7 of their papers we have counts for
7 papers
An LLM agent for end-to-end computational materials discovery
Chen Yuntong, Huang Ju, Liu Yu +8
Coordinating multi-scale tasks is an effective strategy for computational materials discovery, yet the diverse algorithms and tools involved make this process highly challenging. H…
Multitask Scanning Probe Microscopy
Aditya Raghavan, Yu Liu, Ian Mercer +2
Scanning probe microscopy provides nanoscale access to structural, electrical, electromechanical, magnetic, and mechanical properties of materials. Its increasing use for wafer-sca…
From Closed-Loop Optimization to Open Decision Making: Coupled Digital Twins for Predictive and Autonomous Microscopy
Yu Liu, Boris Slautin, Ian Mercer +2
Automated experimentation is moving from closed-loop optimization toward open decision-making, where human or AI planners must forecast the consequences of candidate actions before…
Bayesian Co-Navigation of a Computational Physical Model and AFM Experiment to Autonomously Survey a Combinatorial Materials Library
Boris N. Slautin, Kamyar Barakati, Yu Liu +3
Building autonomous experiment workflows requires transcending beyond the data-driven surrogate models to incorporate and dynamically refine physical theory during exploration. Her…
Materials Discovery in Combinatorial and High-throughput Synthesis and Processing: A New Frontier for SPM
Boris N. Slautin, Yongtao Liu, Kamyar Barakati +13
For over three decades, scanning probe microscopy (SPM) has been a key method for exploring material structures and functionalities at nanometer and often atomic scales in ambient,…
Automated Materials Discovery Platform Realized: Scanning Probe Microscopy of Combinatorial Libraries
Yu Liu, Aditya Raghavan, Utkarsh Pratiush +13
Combinatorial materials libraries provide a powerful platform for mapping how physical properties evolve across binary and ternary cross-sections of multicomponent phase diagrams.…
Measurements with Noise: Bayesian Optimization for Co-optimizing Noise and Property Discovery in Automated Experiments
Boris N. Slautin, Yu Liu, Jan Dec +4
We have developed a Bayesian optimization (BO) workflow that integrates intra-step noise optimization into automated experimental cycles. Traditional BO approaches in automated exp…