Structural Polymorphism Kinetics Promoted by Charged Oxygen Vacancy in HfO2_2

Defects such as oxygen vacancy are widely considered to be critical for the performance of HfO2-based devices, and yet atomistic mechanisms underlying various exotic effects such as wake-up and fluid imprint remain elusive. Here, guided by a lattice-mode-matching criterion, we systematically study the phase transitions between different polymorphs of hafnia under the influences of neutral and positively charged oxygen vacancies by mapping out the minimum energy pathways using a first-principles-based variable-cell nudged elastic band technique. We find that the positively charged oxygen vacancy can substantially promote the transition of various nonpolar phases to the polar phase kinetically, enabled by a transient high-energy tetragonal phase and extreme charge-carrier-inert ferroelectricity of the polar $Pca2_1$ phase. The intricate coupling between structural polymorphism kinetics and the charge state of the oxygen vacancy has important implications for the origin of ferroelectricity in HfO$_2$-based thin films as well as wake-up, fluid imprint, and inertial switching

Climatic Efficiency Analysis of Ten Leading UK Offshore Wind Farms: A Data-Driven Approach

As wind energy becomes increasingly important in globalenergy systems, accurately evaluating the performance of wind farms isessential for understanding wind generation efficiency and fostering sustainabledevelopment. The aim of this paper is to assess wind powergeneration efficiency under different climatic wind conditions. A datadrivenapproach is used to simulate the power generation of ten leadingwind farms in the UK, using real wind data and geographic informationwhile considering wake effects. Furthermore, to evaluate whetherthese wind farms perform optimally when climate-related wind patternschange, we modify the layouts of the wind farms and compare their performancewith the original designs. Extensive results from 15 years (2008to 2023) of wind data show that the originally designed layouts of theseten leading wind farms will no longer be optimal when the wind resourcechanges

Modular development of deep potential for complex solid solutions

The multicomponent oxide solid solution is a versatile platform to tune the delicate balance between competing spin, charge, orbital, and lattice degrees of freedom for materials design and discovery. The development of compositionally complex oxides with superior functional properties has been largely empirical and serendipitous, in part due to the exceedingly complex chemistry and structure of solid solutions that span a range of length scales. The classical molecular dynamics (MD), as a powerful statistical method to investigate materials properties over large spatial and temporal scales, often plays a secondary role in computer-aided materials discovery because of the limited availability and accuracy of classical force fields. Here, we introduce the strategy of ``modular developing deep potential" (ModDP) that enables a systematic development and improvement of deep neural network-based model potential, termed as deep potential, for complex solid solutions with minimum human intervention. The converged training database associated with an end-member material is treated as an independent module and is reused to train the deep potential of solid solutions via a concurrent learning procedure. We apply ModDP to obtain classical force fields of two technologically important solid solutions, Pb$_x$Sr$_{1-x}$TiO$_3$ and Hf$_x$Zr$_{1-x}$O$_2$. For both materials systems, a single model potential is capable of predicting various properties of solid solutions including temperature-driven and composition-driven phase transitions over a wide range of compositions. In particular, the deep potential of Pb$_x$Sr$_{1-x}$TiO$_3$ reproduces a few known topological textures such as polar vortex lattice and electric dipole waves in PbTiO$_3$/SrTiO$_3$ superlattices, paving the way for MD investigations on the dynamics of topological structures in response to external stimuli.Comment: 32 pages, 9 figure

Semiconducting nonperovskite ferroelectric oxynitride designed ab initio

Recent discovery of HfO2-based and nitride-based ferroelectrics that are compatible to the semiconductor manufacturing process have revitalized the field of ferroelectric-based nanoelectronics. Guided by a simple design principle of charge compensation and density functional theory calculations, we discover HfO2-like mixed-anion materials, TaON and NbON, can crystallize in the polar Pca21 phase with a strong thermodynamic driving force to adopt anion ordering spontaneously. Both oxynitrides possess large remnant polarization, low switching barriers, and unconventional negative piezoelectric effect, making them promising piezoelectrics and ferroelectrics. Distinct from HfO2 that has a wide band gap, both TaON and NbON can absorb visible light and have high charge carrier mobilities, suitable for ferroelectric photovoltaic and photocatalytic applications. This new class of multifunctional nonperovskite oxynitride containing economical and environmentally benign elements offer a platform to design and optimize high-performing ferroelectric semiconductors for integrated systems

Oxygen-vacancy Mediated Deterministic Domain Distribution at the Onset of Ferroelectricity

Ferroelectric domains are mesoscale structures that mediate between synchronized atomic-scale ion displacements and switchable macroscopic polarization. Here, we evaluated the randomness of the domain distribution at the onset of ferroelectricity. First-principle calculations combined with atomic-scale imaging demonstrate that oxygen vacancies that serve as pinning sites for the ferroic domain walls remain immobile above the Curie temperature. Thus, upon cooling to a ferroelectric state, these oxygen vacancies dictate reproducible domain-wall patterning. Domain-scale imaging with variable-temperature piezoresponse force microscopy confirmed the memory effect, questioning the spontaneity of domain distribution under thermotropic transitions

Potential Applications of Remote Limb Ischemic Conditioning for Chronic Cerebral Circulation Insufficiency

Chronic cerebral circulation insufficiency (CCCI) refers to a chronic decrease in cerebral blood perfusion, which may lead to cognitive impairment, psychiatric disorders such as depression, and acute ischemic stroke. Remote limb ischemic conditioning (RLIC), in which the limbs are subjected to a series of transient ischemic attacks, can activate multiple endogenous protective mechanisms to attenuate fatal ischemic injury to distant organs due to acute ischemia, such as ischemic stroke. Recent studies have also reported that RLIC can alleviate dysfunction in distant organs caused by chronic, non-fatal reductions in blood supply (e.g., CCCI). Indeed, research has indicated that RLIC may exert neuroprotective effects against CCCI through a variety of potential mechanisms, including attenuated glutamate excitotoxicity, improved endothelial function, increased cerebral blood flow, regulation of autophagy and immune responses, suppression of apoptosis, the production of protective humoral factors, and attenuated accumulation of amyloid-β. Verification of these findings is necessary to improve prognosis and reduce the incidence of acute ischemic stroke/cognitive impairment in patients with CCCI