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Jan-Chi Yang

Publications and source records attributed to Jan-Chi Yang.

15 recordsLinked to original sources

Quantifying angular momentum of coherently driven circular phonons

The use of intense terahertz (THz) pulses to manipulate low-energy excitations offers a powerful approach for ultrafast control of electronic and magnetic properties in materials. Theory suggests that circular ionic motions driven by THz fields carry angular momentum, potentially generating internal magnetic fields. Recent experiments in nonmagnetic SrTiO3 (STO) have hinted at such THz-induced fields, but their origin remains debated. Here, we employ ultrafast x-ray diffraction to resolve the time-dependent ionic trajectories in STO following excitation by circularly polarized THz pulses. Our analysis reveals that oxygen ions, despite their lower mass, contribute around 90% of the phonon angular momentum. The resulting imbalance between the negatively and positively charged ions provides a clear explanation for the mechanism behind induced magnetism in STO. This work further provides the first quantitative measurement of circular ionic motions and their angular momentum and establishes a general methodology for the investigation of angular momentum transfer in solids, paving the way for new strategies to control topological phonon transport and phonon-driven magnetism in quantum materials.

cond-mat.mtrl-sci

Quality-Controlled Active Learning via Gaussian Processes for Robust Structure-Property Learning in Autonomous Microscopy

Autonomous experimental systems are increasingly used in materials research to accelerate scientific discovery, but their performance is often limited by low-quality, noisy data. This issue is especially problematic in data-intensive structure-property learning tasks such as Image-to-Spectrum (Im2Spec) and Spectrum-to-Image (Spec2Im) translations, where standard active learning strategies can mistakenly prioritize poor-quality measurements. We introduce a gated active learning framework that combines curiosity-driven sampling with a physics-informed quality control filter based on the Simple Harmonic Oscillator model fits, allowing the system to automatically exclude low-fidelity data during acquisition. Evaluations on a pre-acquired dataset of band-excitation piezoresponse spectroscopy (BEPS) data from PbTiO3 thin films with spatially localized noise show that the proposed method outperforms random sampling, standard active learning, and multitask learning strategies. The gated approach enhances both Im2Spec and Spec2Im by handling noise during training and acquisition, leading to more reliable forward and inverse predictions. In contrast, standard active learners often misinterpret noise as uncertainty and end up acquiring bad samples that hurt performance. Given its promising applicability, we further deployed the framework in real-time experiments on BiFeO3 thin films, demonstrating its effectiveness in real autonomous microscopy experiments. Overall, this work supports a shift toward hybrid autonomy in self-driving labs, where physics-informed quality assessment and active decision-making work hand-in-hand for more reliable discovery.

cs.LG

Electric field switching of chiral phonons

Lattice vibrations carrying angular momentum, known as chiral phonons, have emerged as a promising route to control and understand complex material properties, yet their deterministic manipulation remains largely unexplored. Here we demonstrate electric-field switching of phonon angular momentum in the technologically relevant ferroelectric BaTiO3. Using circularly dichroic resonant inelastic X-ray scattering (CD-RIXS) at the oxygen K edge, we directly probe the phonon angular momentum and compare the measured dichroism with first-principles predictions of phonon-mode chirality. We find excellent agreement, revealing a momentum-dependent circular-dichroism contrast that exhibits a reversible gyroelectric effect, stable for at least 15 hours. Our results establish a robust mechanism for non-volatile control of chiral phonons and point towards new opportunities for phonon-based information and energy technologies.

cond-mat.mtrl-sci

In-situ Straining of Epitaxial Freestanding Ferroic Films by a MEMS Device

Mechanical strain can be used to control physical properties in materials. The experimental investigation of strain-induced effects at the nanoscale is of importance not only for its fundamental aspects, but also for the development of device applications. Transmission X-ray microscopy is a particularly well-suited technique for nanoscale imaging of magnetic materials, but its compatibility with in-situ mechanical straining of samples is limited. In this work, we present a setup for applying tailored in-situ mechanical strains to freestanding thin films by means of a micro electromechanical system (MEMS) actuator. We then present a proof-of-concept experiment in which a freestanding 80 nm thick (001) BiFeO3 multiferroic thin film is strained with the MEMS device, allowing us to control the coupled ferroelectric/spin cycloidal configuration.

cond-mat.mes-hall

Atomic-Scale Roughness of Freestanding Oxide Membranes Revealed by Electron Ptychography

Freestanding oxide films offer significant potential for integrating exotic quantum functionalities with semiconductor technologies. However, their performance is critically limited by surface roughness and interfacial imperfection caused by dangling bonds, which disrupt coherent interactions and suppress quantum phenomena at heterointerfaces. To address the challenge of structural characterization of surfaces and interfaces, we develop a metrological approach achieving atomic-scale precision in mapping the topography of both free surfaces and buried interfaces within ultrathin oxide heterostructures leveraging three-dimensional structures reconstructed from multislice electron ptychography. This method also allows for counting the number of atoms, even including light elements such as oxygen, along the electron trajectory in electron microscopy, leading to the identification of surface termination in oxide films. The planar-view of measurement geometry, allowing for large field-of-view imaging, provides remarkably rich information and high statistics about the atomic-scale structural inhomogeneities in freestanding membranes. This quantitative analysis provides unprecedented capabilities for correlating structural imperfection with quantum device performance, offering critical insights for engineering robust heterointerfaces in next-generation oxide electronics.

cond-mat.mtrl-sci

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 approaches have been utilized to rapidly map local structure to functional properties in microscopy experiments, but are computationally expensive for multi-dimensional and correlated output spaces. Here, we present an alternative lightweight curiosity algorithm which actively samples regions with unexplored structure-property relations, utilizing a deep-learning based surrogate model for error prediction. We show that the algorithm outperforms random sampling for predicting properties from structures, and provides a convenient tool for efficient mapping of structure-property relationships in materials science.

cond-mat.mtrl-sci

Imaging ferroelectric domains with soft X-ray ptychography at the oxygen K-edge

The ferroelectric domain structure of a freestanding BiFeO$_3$ film was visualized by ptychographic dichroic imaging with linearly polarized X-rays at the O K-edge around 530 eV. The dichroic contrast is maximized at the energy of the hybridization of the O 2p state and the Fe 3d orbitals, which is split by the octahedral crystal field of the perovskite structure. The microscopy images thus obtained complement the ptychographic imaging of the antiferromagnetic contribution at the Fe L$_3$-edge. The approach can be extended to the separation of different ferroic contributions in other multiferroic oxides.

cond-mat.mtrl-sci

Machine Learning-Based Reward-Driven Tuning of Scanning Probe Microscopy: Towards Fully Automated Microscopy

Since the dawn of scanning probe microscopy (SPM), tapping or intermittent contact mode has been one of the most widely used imaging modes. Manual optimization of tapping mode not only takes a lot of instrument and operator time, but also often leads to frequent probe and sample damage, poor image quality and reproducibility issues for new types of samples or inexperienced users. Despite wide use, optimization of tapping mode imaging is an extremely hard problem, ill-suited to either classical control methods or machine learning. Here we introduce a reward-driven workflow to automate the optimization of SPM in the tapping mode. The reward function is defined based on multiple channels with physical and empirical knowledge of good scans encoded, representing a sample-agnostic measure of image quality and imitating the decision-making logic employed by human operators. This automated workflow gives optimal scanning parameters for different probes and samples and gives high-quality SPM images consistently in the attractive mode. This study broadens the application and accessibility of SPM and opens the door for fully automated SPM.

cond-mat.mes-hall

Sub-nanometer depth resolution and single dopant visualization achieved by tilt-coupled multislice electron ptychography

Real-space imaging of three-dimensional atomic structures is a critical yet challenging task in materials science. Although scanning transmission electron microscopy has achieved sub-angstrom lateral resolution through techniques like electron ptychography1,2, depth resolution remains limited to only 2 to 3 nanometers with a single projection setup3,4. Attaining better depth resolution typically necessitates large sample tilt angles and many projections, as seen in atomic electron tomography5,6. Here, we develop a new algorithm based on multislice electron ptychography which couples only a few projections at small tilt angles, but is sufficient to improve the depth resolution by more than threefold to the sub-nanometer scale, and potentially to the atomic level. This technique maintains high resolving power for both light and heavy atoms, and significantly improves the visibility of single dopants. We are thus able to experimentally detect dilute substitutional praseodymium dopants in a brownmillerite oxide, Ca2Co2O5, in three dimensions and observe the accompanying lattice distortion. This technique requires only a moderate level of data acquisition or processing, and can be seamlessly integrated into electron microscopes equipped with conventional components.

cond-mat.mtrl-sci

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 towards operationalization of 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 (HPC), 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. Our work provides a full infrastructure to build automated SPM workflows for both routine operations and autonomous scientific discovery with machine learning.

cond-mat.mtrl-sci

On-demand higher-harmonic generation through nonlinear Hall effects in curved nanomembranes

The high-order Hall effects, which go beyond the ordinary, unlock more possibilities of electronic transport properties and functionalities. Pioneer works focus on the manufacture of complex nanostructures with low lattice symmetry to produce them. In this paper, we theoretically show that such high-order Hall effects can alternatively be generated by curving a conducting nanomembrane which is highly tunable and also enables anisotropy. Its Hall response can be tuned from first to fourth order by simply varying the direction and magnitude of the applied magnetic field. The dominant Hall current frequency can also be altered from zero to double, or even four times that of the applied alternating electric field. This phenomenon is critically dependent on the occurrence of high-order snake orbits associated with the effective magnetic-field dipoles and quadruples induced by the curved geometry. Our results offer pathways for spatially engineering magnetotransport, current rectification, and frequency multiplication in the bent conducting nanomembrane.

cond-mat.mes-hall

Octahedral and polar phase transitions in freestanding films of SrTiO3

From extreme strain to bending, the possibilities in the manipulation of freestanding films of oxide perovskites bring a novel landscape to their properties and brings them one step closer to their application. It is therefore of great importance to fully understand the inherent properties of such films, in which dimensionality and surface effects can play a major role in defining the properties of the materials ground state. This paper reports the properties of freestanding (FS) films of the canonical oxide, SrTiO3 (STO) with thicknesses 20, 30, 40 and 80 nm. We show that the relaxed ultrathin STO FS films become polar at temperatures as high as 85 K, in contrast to the quantum paraelectric behavior of bulk. Our findings are based on the softening of the ferroelectric mode towards the ferroelectric transition temperature Tc and its consecutive hardening below Tc with further decreasing temperature, probed with THz time domain spectroscopy in transmission mode. We find almost no thickness dependence in Tc. Moreover, we characterize the antiferrodistortive (AFD) phase transition in STO FS by X-ray diffraction (XRD) probing superlattice reflections characteristic for the rotation of the TiO6 octahedra. Our results point to a higher phase transition temperature in comparison to bulk STO, as well as an unbalanced domain population favoring the rotation axis to be in plane. X-ray linear dichroism results further show a preferential Ti xz/yz orbital occupancy at the surface, but with a complete degeneracy in the t2g states in the inner part of the film indicating that the AFD distortion does not strongly affect the t2g splitting. These findings demonstrate that STO FS films have clearly different properties than bulk.

cond-mat.mtrl-sci

AEcroscoPy: A software-hardware framework empowering microscopy toward automated and autonomous experimentation

Microscopy, in particular scanning probe and electron microscopy, has been pivotal in improving our understanding of structure-function relationships at the nanoscale and is by now ubiquitous in most research characterization labs and facilities. However, traditional microscopy operations are still limited largely by a human-centric click-and-go paradigm utilizing vendor-provided software, which necessarily limits the scope, utility, efficiency, effectiveness, and at times reproducibility of microscopy experiments. Here, we develop a coupled hardware-software platform that consists of a field-programmable gate array (FPGA) device, with LabView-built customized acquisition scripts, along with a software package termed AEcroscoPy (short for Automated Experiments in Microscopy driven by Python) that overcome these limitations and provide the necessary abstractions towards full automation of microscopy platforms. The platform works across multiple vendor devices on scanning probe microscopes and scanning transmission electron microscopes. It enables customized scan trajectories, processing functions that can be triggered locally or remotely on processing servers, user-defined excitation waveforms, standardization of data models, and completely seamless operation through simple Python commands to enable a plethora of microscopy experiments to be performed in a reproducible, automated manner. This platform can be readily coupled with existing machine learning libraries as well as simulations, to provide automated decision-making and active theory-experiment optimization loops to turn microscopes from characterization tools to instruments capable of autonomous model refinement and physics discovery.

cond-mat.mtrl-sci

Ptychographic nanoscale imaging of the magnetoelectric coupling in freestanding BiFeO$_3$

Understanding the magnetic and ferroelectric ordering of magnetoelectric multiferroic materials at the nanoscale necessitates a versatile imaging method with high spatial resolution. Here, soft X-ray ptychography is employed to simultaneously image the ferroelectric and antiferromagnetic domains in an 80 nm thin freestanding film of the room-temperature multiferroic BiFeO$_3$ (BFO). The antiferromagnetic spin cycloid of period 64 nm is resolved by reconstructing the corresponding resonant elastic X-ray scattering in real space and visualized together with mosaic-like ferroelectric domains in a linear dichroic contrast image at the Fe L$_3$ edge. The measurements reveal a near perfect coupling between the antiferromagnetic and ferroelectric ordering by which the propagation direction of the spin cycloid is locked orthogonally to the ferroelectric polarization. In addition, the study evinces both a preference for in-plane propagation of the spin cycloid and changes of the ferroelectric polarization by 71{\deg} between multiferroic domains in the epitaxial strain-free, freestanding BFO film. The results provide a direct visualization of the strong magnetoelectric coupling in BFO and of its fine multiferroic domain structure, emphasizing the potential of ptychographic imaging for the study of multiferroics and non-collinear magnetic materials with soft X-rays.

cond-mat.mtrl-sci

A dynamic Bayesian optimized active recommender system for curiosity-driven 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 apriori with limited human feedback during operation. In contrast, here we present the development of a new type of human in the loop experimental workflow, via a Bayesian optimized active recommender system (BOARS), to shape targets on the fly, employing human feedback. We showcase examples of this framework applied to pre-acquired piezoresponse force spectroscopy of a ferroelectric thin film, and then implement this in real time on an atomic force microscope, where the optimization proceeds to find symmetric piezoresponse amplitude 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-augmented machine learning approaches for curiosity-driven exploration of systems across experimental domains. The analysis reported here is summarized in Colab Notebook for the purpose of tutorial and application to other data: https://github.com/arpanbiswas52/varTBO

cs.LG