Subscribe to the gold package and get unlimited access to Shamra Academy
Register a new userMultiple Aging Mechanisms in Ferroelectric Deuterated Potassium Dihydrogen Phosphate
406
0
0.0
(
0
)
Added by
Michael B. Weissman
Publication date
2018
fields
Physics
and research's language is
English
Ask ChatGPT about the research
No Arabic abstract
The anomalously large dielectric aging in ferroelectric partially deuterated potassium dihydrogen phosphate (DKDP) is found to have multiple distinct mechanisms. Two components cause decreases in dielectric response over a limited range of fields around the aging field. A large fraction of this aging occurs on time scales of ~1000s after a field change, as expected for a hydrogen/deuterium diffusion mechanism. A slower component can give almost complete loss of domain-wall dielectric response at the aging field after weeks of aging. There is also a particularly unusual aging in which the dielectric response increases with time after rapid cooling.
rate research
Read More
Transformation induced plasticity (TRIP) behavior was studied in steel with composition Fe-0.07C-2.85Si-15.3Mn-2.4Al-0.017N that exhibited two TRIP mechanisms. The initial microstructure consisted of both {epsilon}- and {alpha}-martensites with 27% retained austenite. TRIP behavior in the first 5% strain was predominately austenite transforming to {epsilon}-martensite (Stage I), but upon saturation of Stage I, the {epsilon}-martensite transformed to {alpha}-martensite (Stage II). Alloy segregation also affected the TRIP behavior with alloy rich regions producing TRIP just prior to necking. This behavior was explained by first principle calculations that revealed aluminum significantly affected the stacking fault energy in Fe-Mn-Al-C steels by decreasing the unstable stacking fault energy and promoting easy nucleation of {epsilon}-martensite. The addition of aluminum also raised the intrinsic stacking fault energy and caused the {epsilon}-martensite to be unstable and transform to {alpha}-martensite under further deformation. The two stage TRIP behavior produced a high strain hardening exponent of 1.4 and led to ultimate tensile strength of 1165 MPa and elongation to failure of 35%.
We present a full analysis of the contrast mechanisms for the detection of ferroelectric domains on all faces of bulk single crystals using scanning force microscopy exemplified on hexagonally poled lithium niobate. The domain contrast can be attributed to three different mechanisms: i) the thickness change of the sample due to an out-of-plane piezoelectric response (standard piezoresponse force microscopy), ii) the lateral displacement of the sample surface due to an in-plane piezoresponse, and iii) the electrostatic tip-sample interaction at the domain boundaries caused by surface charges on the crystallographic y- and z-faces. A careful analysis of the movement of the cantilever with respect to its orientation relative to the crystallographic axes of the sample allows a clear attribution of the observed domain contrast to the driving forces respectively.
The rich dynamics and phase structure of driven systems includes the recently described phenomenon of the discrete time crystal (DTC), a robust phase which spontaneously breaks the discrete time translation symmetry of its driving Hamiltonian. Experiments in trapped ions and diamond nitrogen vacancy centers have recently shown evidence for this DTC order. Here, we show nuclear magnetic resonance (NMR) data of DTC behavior in a third, strikingly different system: a highly ordered spatial crystal in three dimensions. We devise a DTC echo experiment to probe the coherence of the driven system. We examine potential decay mechanisms for the DTC oscillations, and demonstrate the important effect of the internal Hamiltonian during nonzero duration pulses.
By combining first principles calculations and experimental XPS measurements, we investigate the electronic structure of potential Li-ion battery cathode materials LiMPO4 (M=Mn,Fe,Co,Ni) to uncover the underlying mechanisms that determine small hole polaron formation and migration. We show that small hole polaron formation depends on features in the electronic structure near the valence-band maximum and that, calculationally, these features depend on the methodology chosen for dealing with the correlated nature of the transition-metal d-derived states in these systems. Comparison with experiment reveals that a hybrid functional approach is superior to GGA+U in correctly reproducing the XPS spectra. Using this approach we find that LiNiPO4 cannot support small hole polarons, but that the other three compounds can. The migration barrier is determined mainly by the strong or weak bonding nature of the states at the top of the valence band, resulting in a substantially higher barrier for LiMnPO4 than for LiCoPO4 or LiFePO4.
Machine learning has emerged as a powerful tool for the analysis of mesoscopic and atomically resolved images and spectroscopy in electron and scanning probe microscopy, with the applications ranging from feature extraction to information compression and elucidation of relevant order parameters to inversion of imaging data to reconstruct structural models. However, the fundamental limitation of machine learning methods is their correlative nature, leading to extreme susceptibility to confounding factors. Here, we implement the workflow for causal analysis of structural scanning transmission electron microscopy (STEM) data and explore the interplay between physical and chemical effects in ferroelectric perovskite across the ferroelectric-antiferroelectric phase transitions. The combinatorial library of the Sm-doped BiFeO3 is grown to cover the composition range from pure ferroelectric BFO to orthorhombic 20% Sm-doped BFO. Atomically resolved STEM images are acquired for selected compositions and are used to create a set of local compositional, structural, and polarization field descriptors. The information-geometric causal inference (IGCI) and additive noise model (ANM) analysis are used to establish the pairwise causal directions between the descriptors, ordering the data set in the causal direction. The causal chain for IGCI and ANM across the composition is compared and suggests the presence of common causal mechanisms across the composition series. Ultimately, we believe that the causal analysis of the multimodal data will allow exploring the causal links between multiple competing mechanisms that control the emergence of unique functionalities of morphotropic materials and ferroelectric relaxors.
Log in to be able to interact and post comments
comments
Fetching comments
Sign in to be able to follow your search criteria
