Related papers: Imaging Ferroelectric Domains via Charge Gradient …
Charge manipulation and fabrication of stable domain patterns in ferroelectric materials by scanning probe microscopy open up broad avenues for the development of tunable electronics. Harnessing the polarization energy and electrostatic…
Thin-film lithium niobate (TFLN) is a widely used platform for nonlinear frequency conversion, as its strong nonlinear susceptibility and enhanced modal confinement intensify nonlinear interactions. Frequency doubling from NIR to visible…
Piezoresponse force microscopy (PFM) is a powerful tool widely used to characterize piezoelectricity and ferroelectricity at the nanoscale. However, it is necessary to distinguish microscopic mechanisms between piezoelectricity and…
Piezoresponse force microscopy (PFM) was used to investigate the ferroelectric properties of sol-gel derived LiNbO$_3$ nanoparticles. To determine the degree of ferroelectricity we took large-area images and performed statistical…
We present the results of a study to optimize the principal component analysis (PCA) algorithm for planet detection, a new algorithm complementing ADI and LOCI for increasing the contrast achievable next to a bright star. The stellar PSF is…
Our main objective is to develop a denoising strategy to increase the signal to noise ratio of individual spectral lines of stellar spectropolarimetric observations. We use a multivariate statistics technique called Principal Component…
Piezoresponse Force Microscopy (PFM) has emerged as a primary tool for imaging, domain engineering, and switching spectroscopy on ferroelectric materials. Quantitative interpretation of PFM data including measurements of the intrinsic width…
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…
Principal component analysis (PCA) is a widely used method for dimension reduction. In high dimensional data, the "signal" eigenvalues corresponding to weak principal components (PCs) do not necessarily separate from the bulk of the "noise"…
Ferroelectric thin films present a powerful platform for next generation computing and memory applications. However, domain morphology and dynamics in buried ferroelectric stacks have remained underexplored, despite the importance for real…
Measuring local magnetization dynamics and its spatial variation is essential for advancements in spintronics and relevant applications. Here we demonstrate a phase-sensitive imaging technique for studying patterned magnetic structures…
Contact electrification (CE) remains a critical challenge in advanced material technologies where uncontrolled surface charging can compromise manufacturability, reliability, and performance in practical applications. Ultrathin glass with…
Ferroelectric domain structure evolution induced by an external electric field was investigated by means of nematic liquid crystal (NLC) method in two strontium-barium niobate single crystals of nominal composition:…
We introduce the notion of Principal Component Analysis (PCA) of image gradient orientations. As image data is typically noisy, but noise is substantially different from Gaussian, traditional PCA of pixel intensities very often fails to…
Ferroelectric nanostructures can be formed by local switching of domains using techniques such as piezo-force microscopy (PFM). Understanding lateral size effects is important to determine the minimum feature size for writing ferroelectric…
Ferroelectric belongs to an important class of materials showing very interesting nonlinear optical properties that have a variety of application in photonic devices In a discrete Hamiltonian, if we consider the space and time dependence of…
Principal component analysis (PCA) is largely adopted for chemical process monitoring and numerous PCA-based systems have been developed to solve various fault detection and diagnosis problems. Since PCA-based methods assume that the…
We present a method for performing Principal Component Analysis (PCA) on noisy datasets with missing values. Estimates of the measurement error are used to weight the input data such that compared to classic PCA, the resulting eigenvectors…
Compute-in-memory (CiM) is a promising approach to alleviating the memory wall problem for domain-specific applications. Compared to current-domain CiM solutions, charge-domain CiM shows the opportunity for higher energy efficiency and…
We report on low-energy electron microscopy imaging of ferroelectric domains with submicron resolution. Periodic strips of 'up' and 'down'-polarized ferroelectric domains in bismuth ferrite -a room temperature multiferroic- serve as a model…