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33 results for “ferroelectric”
Phase Field Simulation of Morphotropic phase boundary of relaxor ferroelectrics
<p>Phase-field simulation of a mixed system of Tetragonal and Rhombohedral phases representing the morphotropic phase boundary of relaxor ferroelectrics</p>
Beyond Substrates: Strain Engineering of Ferroelectric Membranes
<p>Dataset for publication:</p> <p>Beyond Substrates: Strain Engineering of Ferroelectric Membranes</p> <p>D. Pesquera, E. Parsonnet, A. Qualls, R. Xu, A.J. Gubser, J. Kim, Y. Jiang, G. Velarde, Y. Huang, H.Y. Hwang, R. Ramesh, and L.W. Martin, Adv. Mater. <strong>32</strong>, 2003780 (2020).</p> <p> </p> <p>Matlab code for producing Fig.1d, Fig.2a and Fig.4b is given in .txt files</p>
Data for article "Theory of superconductivity mediated by Rashba coupling in incipient ferroelectrics"
<p>Ab initio frozen-phonon splitting of the electronic bands, normalized with the polar displacement. The data is plotted in figure 3 (b) of the article Phys. Rev. B <strong>105</strong>, 224503 (2022). </p>
Supplementary files for "Pressure-enhanced ferroelectric polarisation in polar perovskite-like [C2H5NH3]Na0.5Cr0.5(HCOO)3 metal-organic framework"
<p>DFT optimised structures for the paper: Pressure-enhanced ferroelectric polarisation in polar perovskite-like [C2H5NH3]Na0.5Cr0.5(HCOO)3 metal-organic framework. See the paper for additional information on the computational setup.</p> <p>Files are named HP or LP for high-pressure and low-pressure phases, followed by the pressure as calculated by DFT. The HP structure was optimized in two different space groups and are labelled accordingly. The DFT optimized structure without volume restrictions is found in opt-vol.POSCAR</p> <p> </p>
Dataset for DFT and one-step model results used in publication "Persistence of Structural Distortion and Bulk Band Rashba Splitting in SnTe above Its Ferroelectric Critical Temperature" in Nano Letters, 2024, 24, 1, 82–88
<p>Dataset for DFT and one-step model results used in publication DOI 10.1021/acs.nanolett.3c03280, "Persistence of Structural Distortion and Bulk Band Rashba Splitting in SnTe above Its Ferroelectric Critical Temperature" in Nano Letters, 2024, 24, 1, 82–88.</p> <p>Description of dataset is in the ReadMe.txt file in subdirectories.</p>
Datasets for 'Electron ptychography reveals a ferroelectricity dominated by anion displacements'
<p>4D-STEM datasets for the multislice electron ptychographic reconstructions reported in the paper 'Electron ptychography reveals a ferroelectricity dominated by anion displacements' <a href="https://doi.org/10.48550/arXiv.2408.14795" target="_blank" rel="noopener">arXiv.2408.14795</a>. The reconstruction code based on the <a href="https://github.com/yijiang1/fold_slice" target="_blank" rel="noopener">fold_slice</a> package is also provided along with the data.</p>
Revealing Ferroelectric Switching Character Using Deep Recurrent Neural Networks
<p><strong>The ability to manipulate domains and domain walls underpins function in a range of next-generation applications of ferroelectrics. While there have been demonstrations of controlled nanoscale manipulation of domain structures to drive emergent properties, such approaches lack an internal feedback loop required for automation. Here, using a deep sequence-to-sequence autoencoder we automate the extraction of features of nanoscale ferroelectric switching from multichannel hyperspectral band-excitation piezoresponse force microscopy of tensile-strained PbZr<sub>0.2</sub>Ti<sub>0.8</sub>O<sub>3</sub> with a hierarchical domain structure. Using this approach, we identify characteristic behavior in the piezoresponse and cantilever resonance hysteresis loops, which allows for the classification and quantification of nanoscale-switching mechanisms. Specifically, we are able to identify elastic hardening events which are associated with the nucleation and growth of charged domain walls. This work demonstrates the efficacy of unsupervised neural networks in <em>learning</em> features of the physical response of a material from nanoscale multichannel hyperspectral imagery and provides new capabilities in leveraging multimodal <em>in operando</em> spectroscopies and automated control for the manipulation of nanoscale structures in materials.</strong></p>
Ferroelectricity in layered bismuth oxide down to 1 nanometer
<p>Very recently, I found that there was a typo error in the atomic coordinates (O6 of Pmm2 structure in Table S6 should be changed to "0.500 0.500 0.351") in the Supplementary information of <a href="https://www.science.org/doi/10.1126/science.abm5134">Ferroelectricity in layered bismuth oxide down to 1 nanometer</a>. </p> <p>The crystal structures that best correspond to experimental observations are made publicly accessible to ensure proper access for everyone. I thank Chao Wang who brought my attention to the possible error in the Table S6.</p>
Out-of-plane ferroelectricity and robust magnetoelectricity in quasi two-dimensional materials
<p>Thin film ferroelectrics have been pursued for capacitive and nonvolatile memory devices. They rely on polarizations that are oriented in an out-of-plane direction to facilitate integration and addressability with CMOS architectures. The internal depolarization field, however, formed by surface charges can suppress the out-of-plane polarization in ultrathin ferroelectric films that could otherwise exhibit lower coercive fields and operate with lower power. Here we unveil stabilization of a polar longitudinal optical (LO) mode in the <em>n</em>=2 Ruddlesden–Popper family that produces out-of-plane ferroelectricity, persists under open-circuit boundary conditions, and is distinct from hyperferroelectricity. Our first-principles calculations show the stabilization of the LO mode is ubiquitous in chalcogenides and halides and relies on anharmonic trilinear mode coupling. We further show that the out-of-plane ferroelectricity can be predicted with a crystallographic tolerance factor, and we use these insights to design a room-temperature multiferroic with strong magnetoelectric coupling suitable for magneto-electric spin-orbit transistors. </p>
Electrostatically Driven Polarization Flop and strain-induced Curvature in free-standing Ferroelectric Superlattices
<p>Supporting data for publication: "Electrostatically Driven Polarization Flop and strain-induced Curvature in free-standing Ferroelectric Superlattices"</p> <p>DOI: 10.1002/adma.202106826</p> <p>This repository contains higher resolution STEM images published in the paper.</p>
Dataset: A phase field model combined with genetic algorithm for polycrystalline hafnium zirconium oxide ferroelectrics
<p>The folder includes generated data MATLAB scripts to read/plot the polarization-electric field (PE) hysteresis curves. The dataset contains phase field generated polycrystalline grain structure, simulated domain structures during polarization reversal, and symmetric PE curves (measured and simulated).</p> <p><strong>Polycrystalline grain structures</strong>: The output files are in the *.txt format, readable by MTEX to generate orientation maps.<br> Column(1) Column(2) Column(3) Column(4) Column(5)<br> X Y φ(rad) θ(rad) 𝜓(rad)<br> ... ... ... ... ...<br> ... ... ... ... ...<br> ... ... ... ... ...</p> <p><strong>Domain structures</strong>: The output files are in the *.csv format, which can be visualized by programs like ParaView.<br> Column(1) Column(2) Column(3) Column(4)<br> X Y Z P<br> ... ... ... ...<br> ... ... ... ...<br> ... ... ... ...</p> <p><br> <strong>PE curves</strong>: The output files are in the *.txt format, readable by MATLAB.<br> Column(1) Column(2)<br> E(MV/cm) P(μC/cm²)<br> ... ...<br> ... ...<br> ... ...</p> <p><strong>List of datasets:-</strong><br> Fig. 1: pecurves/calib_func1.txt (Calibrated p(e)), pecurves/measpe_hf50.txt (Measured PE curve), pecurves/simpe_calib.txt (Simulated PE curve).<br> Fig. 2(a): polcr_struc/xy_col.txt (XY top view), polcr_struc/yz_col.txt (YZ side view), polcr_struc/xz_col.txt (ZX side view)<br> Fig. 2(b): pecurves/simpe_gaopt.txt (Simulated PE curve), pecurves/measpe_hf50.txt (Measured PE curve).<br> Fig. 3: pecurves/calib_func.txt (Calibrated p(e)), pecurves/gaopt_func.txt (GA optimized p(e)).<br> Fig. 5: pecurves/simpe_gaopt.txt (Case 1), pecurves/simpe_elast.txt (Case 2).<br> Fig. 4(e): dom_struc/dom_profile1.csv, (f) dom_struc/dom_profile2.csv, (g) dom_struc/dom_profile3.csv, (h) dom_struc/dom_profile4.csv, (m) dom_struc/dom_profile5.csv, (n) dom_struc/dom_profile6.csv, (o) dom_struc/dom_profile7.csv, (p) dom_struc/dom_profile8.csv<br> Fig. 6: pecurves/simpe_gaopt.txt (GA fit coefficients), pecurves/simpe_ldc1.txt (Set 1), pecurves/simpe_ldc2.txt (Set 2).<br> Fig. 7(a): pecurves/simpe_gaopt.txt (𝝂₀ = 1.0), pecurves/simpe_fr80.txt (𝝂₀ = 0.8), pecurves/simpe_fr50.txt (𝝂₀ = 0.5).<br> Fig. 7(b): pecurves/measpe_hf50.txt (Hf₀.₅Zr₀.₅O₂), pecurves/measpe_hf75.txt (Hf₀.₇₅Zr₀.₂₅O₂).<br> Fig. 8: pecurves/simpe_fr38.txt (Simulated PE curve), pecurves/measpe_hf75.txt (Measured PE curve).<br> Fig. 9: pecurves/simpe_gaopt.txt (Random non-textured), pecurves/simpe_tex001.txt ([001] fiber textured), pecurves/simpe_tex111.txt ([111] fiber textured).<br> Fig. 10(a): polcr_struc/xy_equ.txt (XY top view), polcr_struc/yz_equ.txt (YZ side view), polcr_struc/xz_equ.txt (ZX side view)<br> Fig. 10(b): pecurves/simpe_colmor.txt (Columnar grain microstructure), pecurves/simpe_equmor.txt (Equiaxed grain microstructure).</p> <p><strong>List of MATLAB scripts:</strong><br> Fig 1: matlab_scripts/fig1.m<br> Fig 2(b): matlab_scripts/fig2b.m<br> Fig 3: matlab_scripts/fig3.m<br> Fig 5: matlab_scripts/fig5.m<br> Fig 6: matlab_scripts/fig6.m<br> Fig 7(a): matlab_scripts/fig7a.m<br> Fig 7(b): matlab_scripts/fig7b.m<br> Fig 8: matlab_scripts/fig8.m<br> Fig 9: matlab_scripts/fig9.m<br> Fig 10(b): matlab_scripts/fig10b.m<br> </p>
Raw Data for Control of Ferroelectricity in Solution-Processed Hafnia Films through Annealing Atmosphere
<p>The following raw data are the basis of the paper "Control of Ferroelectricity in Solution-Processed Hafnia Films through Annealing Atmosphere" published in Advanced Electronic Materials in 2024 (DOI 10.1002/aelm.202300893).</p> <p>BM and SG acknowledge Luxembourg National Research Fund (FNR) for supporting this work through the project TRICOLOR (INTER/NWO/20/15079143/TRICOLOR). We would like to thank Prof. Beatriz Noheda, Prof. Monica Acuautla, and Dr. Miguel Badillo for their inputs on the growth process used in this work and electrical characterization of the thin films.</p>
Supporting Data for Viscous Mechano-Electric Response of Ferroelectric Nematic Liquid
<p>These data correspond to the published publication entitled: Viscous Mechano-Electric Response of Ferroelectric Nematic Liquid </p>
Ultrafast high-endurance memory based on sliding ferroelectrics
<p>The persistence of voltage-switchable collective electronic phenomena down to the atomic scale has extensive implications for area-efficient and energy-efficient electronics, especially in emerging nonvolatile memory technology. In this study, we investigate the performance of a ferroelectric field-effect transistor (FeFET) based on sliding ferroelectricity in bilayer boron nitride at room temperature. Sliding ferroelectricity represents a novel form of atomically thin two-dimensional ferroelectrics, characterized by the switching of out-of-plane polarization through interlayer sliding motion. We examined the FeFET device employing monolayer graphene as the channel layer, which demonstrated ultrafast switching speeds on the nanosecond scale and high endurance exceeding 1011 switching cycles, comparable to state-of-the-art FeFET devices. These superior characteristics highlight the potential of two-dimensional sliding ferroelectrics for inspiring next-generation nonvolatile memory technology.</p>
Coexistence and coupling of ferroelectricity and ferromagnetism in an oxide two-dimensional electron gas
<p>The dataset contains X-ray absorption spectroscopy (XAS), electric polarization and magnetotransport measurements obtained on LaAlO3/EuTiO3/Ca:SrTiO3 heterostructures, at which interface a two-dimensional electron gas appears.</p> <p>X-ray magnetic circular dichroism (XMCD) extracted from the XAS data are also included, as well as X-ray linear dichroism (XLD) alongside atomic multiplet calculations for two sets of parameters corresponding to "up" and "down" remanent polarization states (data of Fig. 1 and 2).</p>
Atomic-scale polarization switching in wurtzite ferroelectrics - dDPC data
<p>Scanning transmission electron microscopy images in differenciated differential phase contrast (dDPC) mode for Al<sub>1-x</sub>B<sub>x</sub>N with x= 0 and 0.06. </p> <p>dDPC_AlN0 correspond to pure AlN</p> <p>dDPC_AlBN6 and dDPC_AlBN6_Cycled correspond to Al<sub>0.94</sub>B<sub>0.06</sub>N before and after waking up. </p>
Atomic-scale polarization switching in wurtzite ferroelectrics - DFT data
<p>Data and models include structure files, nudged-elastic-band input/output files, plots, and GIF files of the polarization reversal for AlN and (Al,B)N. </p>
Ultrafast high-endurance memory based on sliding ferroelectrics
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Out-of-plane ferroelectricity and robust magnetoelectricity in quasi two-dimensional materials
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Data from: Mapping ferroelectric fields reveals the origins of the coercivity distribution
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