Publications

Showing 71 results for Author: Yongtao Liu

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  • Aug, 2026

    Journal

    Accelerating Structure–Property Relationship Discovery with Multimodal Machine Learning and Self-Driving Microscopy

    Microscopy combined with local spectroscopy is widely used to correlate nanoscale structure with functional properties in materials, but conventional measurements rely heavily on human-selected sampling locations and predefined targets, limiting data set diversity and the potential for discovery. Here, we present a framework that integrates autonomous microscopy with dual-…

  • Aug, 2026

    Journal

    Attention-based explainability for structure–property relationships

    Machine learning methods are emerging as a universal paradigm for constructing correlative structure–property relationships in materials science based on multimodal characterization. However, this necessitates the development of methods for the physical interpretability of the resulting correlative models. Here, we demonstrate the potential of attention-based neural networ…

  • Jul, 2026

    Journal

    Scan-Path- and Initial-State-Dependent Superdomain Switching in (111)-Oriented PZT

    Polarization switching in ferroelectric materials arises from the collective evolution of complex domain hierarchies, yet deterministic control over these processes remains challenging. Here, we investigate scan-path- and initial-state-dependent switching in epitaxial (111)-oriented PbZr0.2Ti0.8O3 thin films using automated AFM-based writing combined with quantitative 3D p…

  • May, 2026

    Journal

    Review on Perovskite Solar Cells: From Single-Junction Devices to Tandem Deployment in Space

    Perovskite solar cells (PSCs) have emerged as a transformative photovoltaic technology, offering high power conversion efficiency (PCE) and the potential for cost-effective manufacturing. However, stability and large-scale manufacturing remain critical challenges that must be addressed for widespread adoption. This review provides a roadmap from single-junction perovskite…

  • Nov, 2025

    Journal

    Beyond Optimization: Exploring Novelty Discovery in Autonomous Experiments

    Autonomous experiments (AEs) are transforming how scientific research is conducted by integrating artificial intelligence with automated experimental platforms. Current AEs primarily focus on the optimization of a predefined target; while accelerating this goal, such an approach limits the discovery of unexpected or unknown physical phenomena. Here, we introduce a novel fr…

  • Nov, 2025

    Journal

    Polarization Switching on the Open Surfaces of the Wurtzite Ferroelectric Nitrides: Ferroelectric Subsystems and Electrochemical Reactivity

    Binary ferroelectric nitrides are promising materials for information technologies and power electronics. However, polarization switching in these materials is highly unusual. From the structural perspective, polarization reversal is associated with the change of the effective polarity at the surfaces and interfaces from N-to-M terminated, suggesting strong coupling betwee…

  • Sep, 2025

    Journal

    Ferroelastic Domain-Induced Electronic Modulation in Halide Perovskites

    Lead halide perovskites have emerged as promising materials for optoelectronic applications due to their exceptional properties. In the all-inorganic CsPbBr3 perovskites, ferroelastic domains formed during phase transitions enhance bulk transport and emissive efficiency. However, the microscopic mechanisms governing carrier dynamics remain poorly understood. In this study,…

  • Sep, 2025

    Journal

    Curiosity driven exploration to optimize structure–property learning in microscopy

    Rapidly determining structure–property correlations in materials is an important challenge in better understanding fundamental mechanisms and greatly assists in materials design. In microscopy, imaging data provides a direct measurement of the local structure, while spectroscopic measurements provide relevant functional property information. Deep kernel active learning app…

  • Sep, 2025

    Journal

    Autonomous Multistate Nanoencoding Using Combinatorial Ferroelectric Closure Domains in BiFeO3

    Recent advances in ferroic materials have identified topological defects as promising candidates for enabling additional functionalities in future electronic systems. The generation of stable and customizable polar topologies is needed to achieve multistates that enable beyond-binary device architectures. In this study, we show how to autonomously pattern on-demand highly…

  • Jan, 2025

    Journal

    Active oversight and quality control in standard Bayesian optimization for autonomous experiments

    The fusion of experimental automation and machine learning has catalyzed a new era in materials research, prominently featuring Gaussian Process (GP) Bayesian Optimization (BO) driven autonomous experiments. Here we introduce a Dual-GP approach that enhances traditional GPBO by adding a secondary surrogate model to dynamically constrain the experimental space based on real…

  • Jan, 2025

    Journal

    Tailoring Molecular Space to Navigate Phase Complexity in Cs-Based Quasi-2D Perovskites via Gated-Gaussian-Driven High-Throughput Discovery

    Cesium-based quasi-2D halide perovskites (HPs) offer promising functionalities and low-temperature manufacturability, suited to stable tandem photovoltaics. However, the chemical interplays between the molecular spacers and the inorganic building blocks during crystallization cause substantial phase complexities in the resulting matrices. To successfully optimize and imple…

  • Dec, 2024

    ORNL Report

    Shaping the Future of Self-Driving Autonomous Laboratories Workshop

    The "Shaping the Future of Self-Driving Autonomous Laboratories" workshop, held in Denver on November 7-8, 2024, brought together leading experts from materials science and computing to address the growing need to revolutionize scientific research through AI-driven autonomous laboratories. The workshop identified critical challenges, including the integration of heterogene…

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