Engineering topics

Liu, Yu-Chen

Publications and source records attributed to Liu, Yu-Chen.

4 records

DOE OSTI2024

Integration of scanning probe microscope with high-performance computing: Fixed-policy and reward-driven workflows implementation

The rapid development of computation power and machine learning algorithms has paved the way for automating scientific discovery with a scanning probe microscope (SPM). The key elements toward operationalization of the automated SPM are the interface to enable SPM control from Python codes, availability of high computing power, and development of workflows for scientific discovery. Here, we build a Python interface library that enables controlling an SPM from either a local computer or a remote high-performance computer, which satisfies the high computation power need of machine learning algorithms in autonomous workflows. We further introduce a general platform to abstract the operations of SPM in scientific discovery into fixed-policy or reward-driven workflows. Furthermore, our work provides a full infrastructure to build automated SPM workflows for both routine operations and autonomous scientific discovery with machine learning.

47 OTHER INSTRUMENTATION↗

DOE OSTI2024

Physics-informed models of domain wall dynamics as a route for autonomous domain wall design via reinforcement learning

Prompted by limited available data, we explore data-aggregation strategies for material datasets, aiming to boost machine learning performance. Our findings suggest that intuitive aggregation schemes are ineffective in enhancing predictive accuracy.

42 ENGINEERING↗

DOE OSTI2024

A dynamic Bayesian optimized active recommender system for curiosity-driven partially Human-in-the-loop automated experiments

Optimization of experimental materials synthesis and characterization through active learning methods has been growing over the last decade, with examples ranging from measurements of diffraction on combinatorial alloys at synchrotrons, to searches through chemical space with automated synthesis robots for perovskites. In virtually all cases, the target property of interest for optimization is defined a priori with the ability to shift the trajectory of the optimization based on human-identified findings during the experiment is lacking. Thus, to highlight the best of both human operators and AI-driven experiments, here we present the development of a human–AI collaborated experimental workflow, via a Bayesian optimized active recommender system (BOARS), to shape targets on the fly with human real-time feedback. Here, the human guidance overpowers AI at early iteration when prior knowledge (uncertainty) is minimal (higher), while the AI overpowers the human during later iterations to accelerate the process with the human-assessed goal. We showcase examples of this framework applied to pre-acquired piezoresponse force spectroscopy of a ferroelectric thin film, and in real-time on an atomic force microscope, with human assessment to find symmetric hysteresis loops. It is found that such features appear more affected by subsurface defects than the local domain structure. This work shows the utility of human–AI approaches for curiosity driven exploration of systems across experimental domains.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Cofactorless oxygenases guide anthraquinone-fused enediyne biosynthesis

The anthraquinone-fused enediynes (AFEs) combine an anthraquinone moiety and a ten-membered enediyne core capable of generating a cytotoxic diradical species. AFE cyclization is triggered by opening the F-ring epoxide, which is also the site of the most structural diversity. Previous studies of tiancimycin A, a heavily modified AFE, have revealed a cryptic aldehyde blocking installation of the epoxide, and no unassigned oxidases could be predicted within the tnm biosynthetic gene cluster. Here, in this study, we identify two consecutively acting cofactorless oxygenases derived from methyltransferase and α/β-hydrolase protein folds, TnmJ and TnmK2, respectively, that are responsible for F-ring tailoring in tiancimycin biosynthesis by comparative genomics. Further biochemical and structural characterizations reveal that the electron-rich AFE anthraquinone moiety assists in catalyzing deformylation, epoxidation and oxidative ring cleavage without exogenous cofactors. These enzymes therefore fill important knowledge gaps for the biosynthesis of this class of molecules and the underappreciated family of cofactorless oxygenases. Cofactorless oxygenases are rare in nature and natural product biosynthesis. Here the authors describe the biochemical and structural characterization of two such oxygenases catalyzing deformylation, ring cleavage and epoxidation in the biosynthesis of the enediyne natural product tiancimycin A.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗