arXiv subjects

Jonghee Yang

Publications and source records attributed to Jonghee Yang.

6 recordsLinked to original sources

arXiv2025

Microsecond Bias Polarity Switching Reveals Hidden Charge Dynamics at Halide Perovskite Interfaces

We present a time-domain technique based on rapid bias polarity switching (BiPS) to probe charge transport and near-surface defects in halide perovskite single crystals. The method exploits interfacial extraction barriers, which cause carrier accumulation and subsequent release after bias reversal. BiPS combines surface sensitivity (200 nm-2 $\mu$m) with millimeter-scale reach, enabling reconstruction of internal field profiles, detection of bulk space charge down to $10^9$ cm$^{-3}$, and resolution of microsecond-millisecond trap dynamics. In our setup the surface-state detection limit is $10^9$ cm$^{-2}$, and could be further improved by optimized illumination and readout. Applied to melt-grown CsPbBr$_3$ (Cr/Cr) and solution-grown MAPbBr$_3$ (Cr/SnO$_2$/Cr), BiPS reveals interfacial barriers that drive hole accumulation and defect filling. CsPbBr$_3$ shows long-lived space charge ($\sim 3\times 10^{11}$ cm$^{-3}$) and $\sim 250\times$ faster hole extraction than MAPbBr$_3$, while trap analysis yields capture times of 1-100 $\mu$s, detrapping times of 20 $\mu$s-3 ms, and activation energies of 300-500 meV. BiPS thus provides direct access to buried interfacial processes, disentangles electronic and ionic contributions, and offers a robust platform for evaluating contacts and guiding defect engineering in perovskite optoelectronic devices.

cond-mat.mtrl-sci↗

arXiv2024

Coexistence and interplay of two ferroelectric mechanisms in Zn1-xMgxO

Ferroelectric materials promise exceptional attributes including low power dissipation, fast operational speeds, enhanced endurance, and superior retention to revolutionize information technology. However, the practical application of ferroelectric-semiconductor memory devices has been significantly challenged by the incompatibility of traditional perovskite oxide ferroelectrics with metal-oxide-semiconductor technology. Recent discoveries of ferroelectricity in binary oxides such as Zn1-xMgxO and Hf1-xZrxO have been a focal point of research in ferroelectric information technology. This work investigates the ferroelectric properties of Zn1-xMgxO utilizing automated band excitation piezoresponse force microscopy. Our findings reveal the coexistence of two ferroelectric subsystems within Zn1-xMgxO. We propose a "fringing-ridge mechanism" of polarization switching that is characterized by initial lateral expansion of nucleation without significant propagation in depth, contradicting the conventional domain growth process observed in ferroelectrics. This unique polarization dynamics in Zn1-xMgxO suggests a new understanding of ferroelectric behavior, contributing to both the fundamental science of ferroelectrics and their application in information technology.

cond-mat.mtrl-sci↗

arXiv2023

Physics-driven discovery and bandgap engineering of hybrid perovskites

The unique aspect of the hybrid perovskites is their tunability, allowing to engineer the bandgap via substitution. From application viewpoint, this allows creation of the tandem cells between perovskites and silicon, or two or more perovskites, with associated increase of efficiency beyond single-junction Schokley-Queisser limit. However, the concentration dependence of optical bandgap in the hybrid perovskite solid solutions can be non-linear and even non-monotonic, as determined by the band alignments between endmembers, presence of the defect states and Urbach tails, and phase separation. Exploring new compositions brings forth the joint problem of the discovery of the composition with the desired band gap, and establishing the physical model of the band gap concentration dependence. Here we report the development of the experimental workflow based on structured Gaussian Process (sGP) models and custom sGP (c-sGP) that allow the joint discovery of the experimental behavior and the underpinning physical model. This approach is verified with simulated data sets with known ground truth, and was found to accelerate the discovery of experimental behavior and the underlying physical model. The d/c-sGP approach utilizes a few calculated thin film bandgap data points to guide targeted explorations, minimizing the number of thin film preparations. Through iterative exploration, we demonstrate that the c-sGP algorithm that combined 5 bandgap models converges rapidly, revealing a relationship in the bandgap diagram of MA1-xGAxPb(I1-xBrx)3. This approach offers a promising method for efficiently understanding the physical model of band gap concentration dependence in the binary systems, this method can also be extended to ternary or higher dimensional systems.

cond-mat.mtrl-sci↗

arXiv2022

Exploring the microstructural origins of conductivity and hysteresis in metal halide perovskites via active learning driven automated scanning probe microscopy

Electronic transport and hysteresis in metal halide perovskites (MHPs) are key to the applications in photovoltaics, light emitting devices, and light and chemical sensors. These phenomena are strongly affected by the materials microstructure including grain boundaries, ferroic domain walls, and secondary phase inclusions. Here, we demonstrate an active machine learning framework for 'driving' an automated scanning probe microscope (SPM) to discover the microstructures responsible for specific aspects of transport behavior in MHPs. In our setup, the microscope can discover the microstructural elements that maximize the onset of conduction, hysteresis, or any other characteristic that can be derived from a set of current-voltage spectra. This approach opens new opportunities for exploring the origins of materials functionality in complex materials by SPM and can be integrated with other characterization techniques either before (prior knowledge) or after (identification of locations of interest for detail studies) functional probing.

cond-mat.mtrl-sci↗

arXiv2022

Disentangling electronic transport and hysteresis at individual grain boundaries in hybrid perovskites via automated scanning probe microscopy

Underlying the rapidly increasing photovoltaic efficiency and stability of metal halide perovskites (MHPs) is the advance in the understanding of the microstructure of polycrystalline MHP thin film. Over the past decade, intense efforts have aimed to understand the effect of microstructure on MHP properties, including chemical heterogeneity, strain disorder, phase impurity, etc. It has been found that grain and grain boundary (GB) are tightly related to lots of microscale and nanoscale behavior in MHP thin film. Atomic force microscopy (AFM) is widely used to observe grain and boundary structures in topography and subsequently to study the correlative surface potential and conductivity of these structures. For now, most AFM measurements have been performed in imaging mode to study the static behavior, in contrast, AFM spectroscopy mode allows us to investigate the dynamic behavior of materials, e.g. conductivity under sweeping voltage. However, a major limitation of AFM spectroscopy measurements is that it requests manual operation by human operators, as such only limited data can be obtained, hindering systematic investigations of these microstructures. In this work, we designed a workflow combining the conductive AFM measurement with a machine learning (ML) algorithm to systematically investigate grain boundaries in MHPs. The trained ML model can extract GBs locations from the topography image, and the workflow drives the AFM probe to each GB location to perform a current-voltage (IV) curve automatically. Then, we are able to IV curves at all GB locations, allowing us to systematically understand the property of GBs. Using this method, we discover that the GB junction points are more photoactive, while most previous works only focused on the difference between GB and grains.

cond-mat.mtrl-sci↗

arXiv2022

Dynamic control of ferroionic states in ferroelectric nanoparticles

The polar states of uniaxial ferroelectric nanoparticles interacting with a surface system of electronic and ionic charges with a broad distribution of mobilities is explored, which corresponds to the experimental case of nanoparticles in solution or ambient conditions. The nonlinear interactions between the ferroelectric dipoles and surface charges with slow relaxation dynamics in an external field lead to the emergence of a broad range of paraelectric-like, antiferroelectric-like ionic, and ferroelectric-like ferroionic states. The crossover between these states can be controlled not only by the static characteristics of the surface charges, but also by their relaxation dynamics in the applied field. Obtained results are not only promising for advanced applications of ferroelectric nanoparticles in nanoelectronics and optoelectronics, they also offer strategies for experimental verification.

cond-mat.mtrl-sci↗