Subscribe to the gold package and get unlimited access to Shamra Academy
Register a new userPiezoresponse phase as variable in electromechanical characterization
189
0
0.0
(
0
)
Ask ChatGPT about the research
No Arabic abstract
Piezoresponse force microscopy (PFM) is a powerful characterization technique to readily image and manipulate ferroelectrics domains. PFM gives insight into the strength of local piezoelectric coupling as well as polarization direction through PFM amplitude and phase, respectively. Converting measured arbitrary units to physical material parameters, however, remains a challenge. While much effort has been spent on quantifying the PFM amplitude signal, little attention has been given to the PFM phase and it is often arbitrarily adjusted to fit expectations or processed as recorded. This is problematic when investigating materials with unknown or potentially negative sign of the probed effective electrostrictive coefficient or strong frequency dispersion of electromechanical responses since assumptions about the phase cannot be reliably made. The PFM phase can, however, provide important information on the polarization orientation and the sign of the electrostrictive coefficient. Most notably, the orientation of the PFM hysteresis loop is determined by the PFM phase. Moreover, when presenting PFM data as a combined signal, the resulting response can be artificially lowered or asymmetric if the phase data has not been correctly processed. Here, we demonstrate a path to identify the phase offset required to extract correct meaning from PFM phase data. We explore different sources of phase offsets including the experimental setup, instrumental contributions, and data analysis. We discuss the physical working principles of PFM and develop a strategy to extract physical meaning from the PFM phase. The proposed procedures are verified on two materials with positive and negative piezoelectric coefficients.
rate research
Read More
Domains walls and topological defects in ferroelectric materials have emerged as a powerful new paradigm for functional electronic devices including memory and logic. Similarly, wall interactions and dynamics underpin a broad range of mesoscale phenomena ranging from giant electromechanical responses to memory effects. Exploring the functionalities of individual domain walls, their interactions, and controlled modifications of the domain structures is crucial for applications and fundamental physical studies. However, the dynamic nature of these features severely limits studies of their local physics since application of local biases or pressures in piezoresponse force microscopy induce wall displacement as a primary response. Here, we introduce a fundamentally new approach for the control and modification of domain structures based on automated experimentation whereby real space image-based feedback is used to control the tip bias during ferroelectric switching, allowing for modification routes conditioned on domain states under the tip. This automated experiment approach is demonstrated for the exploration of domain wall dynamics and creation of metastable phases with large electromechanical response.
Hafnium oxide (HfO2)-based ferroelectrics offer remarkable promise for memory and logic devices in view of their compatibility with traditional silicon CMOS technology, high switchable polarization, good endurance and thickness scalability. These factors have led to steep rise in research on this class of materials over the past number of years. At the same time, only a few reports on the direct sensing of nanoscale ferroelectric properties exist, with many questions remaining regarding the emergence of ferroelectricity in these materials. While piezoresponse force microscopy (PFM) is ideally suited to probe piezo- and ferro-electricity on the nanoscale, it is known to suffer artifacts which complicate quantitative interpretation of results and can even lead to claims of ferroelectricity in materials which are not ferroelectric. In this paper we explore the possibility of using an improved PFM method based on interferometric displacement sensing (IDS) to study nanoscale ferroelectricity in bare Si doped HfO2. Our results indicate a clear difference in the local remnant state of various HfO2 crystallites with reported values for the piezoelectric coupling in range 0.6-1.5 pm/V. In addition, we report unusual ferroelectric polarization switching including possible contributions from electrostriction and Vegard effect, which may indicate oxygen vacancies or interfacial effects influence the emergence of nanoscale ferroelectricity in HfO2.
Piezoresponse Force Microscopy (PFM), as a powerful nanoscale characterization technique, has been extensively utilized to elucidate diverse underlying physics of ferroelectricity. However, the intensive study of conventional PFM has revealed a growing number of concerns and limitations which are largely challenging its validity and application. Herein, we developed a new advanced PFM technique, named Heterodyne Megasonic Piezoresponse Force Microscopy (HM-PFM), which uniquely uses 106 to 108 Hz high-frequency excitation and heterodyne method to measure the piezoelectric strain at nanoscale. We report that HM-PFM can unambiguously provide standard ferroelectric domain and hysteresis loop measurements, and an effective domain characterization with excitation frequency up to ~110 MHz has been realized. Most importantly, owing to the high-frequency and heterodyne scheme, the contributions from both electrostatic force and electrochemical strain can be significantly minimized in HM-PFM. Furthermore, a special difference-frequency piezoresponse frequency spectrum (DFPFS) measurement is developed on HM-PFM and a distinct DFPFS characteristic is observed on the materials with piezoelectricity. It is believed that HM-PFM can be an excellent candidate for the piezoelectric or ferroelectric studies where the conventional PFM results are highly controversial.
Neuro-inspired computing architectures are one of the leading candidates to solve complex, large-scale associative learning problems. The two key building blocks for neuromorphic computing are the synapse and the neuron, which form the distributed computing and memory units. Solid state implementations of these units remain an active area of research. Specifically, voltage or current controlled oscillators are considered a minimal representation of neurons for hardware implementations. Such oscillators should demonstrate synchronization and coupling dynamics for demonstrating collective learning behavior, besides the desirable individual characteristics such as scaling, power, and performance. To this end, we propose the use of nanoscale, epitaxial heterostructures of phase change oxides and oxides with metallic conductivity as a fundamental unit of an ultralow power, tunable electrical oscillator capable of operating in the microwave regime. Our simulations show that optimized heterostructure design with low thermal boundary resistance can result in operation frequency of up to 3 GHz and power consumption as low as 15 fJ/cycle with rich coupling dynamics between the oscillators.
We report on the growth and characterization of metalorganic vapor-phase epitaxy-grown b{eta}-(AlxGa1-x)2O3/b{eta}-Ga2O3 modulation-doped heterostructures. Electron channel is realized in the heterostructure by utilizing a delta-doped b{eta}-(AlxGa1-x)2O3 barrier. Electron channel characteristics are studied using transfer length method, capacitance-voltage and Hall measurements. Hall sheet charge density of 1.06 x 1013 cm-2 and mobility of 111 cm2/Vs is measured at room temperature. Fabricated transistor showed peak current of 22 mA/mm and on-off ratio of 8 x 106. Sheet resistance of 5.3 k{Omega}/Square is measured at room temperature, which includes contribution from a parallel channel in b{eta}-(AlxGa1-x)2O3.
Log in to be able to interact and post comments
comments
Fetching comments
Sign in to be able to follow your search criteria
