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Enhanced Self-Biased Magnetoelectric Coupling in Laser-Annealed Pb(Zr,Ti)O 3 Thick Film Deposited on Ni Foil
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Ultrafast Zero-Bias Surface Photocurrent in Germanium Selenide: Promise for Terahertz Devices and Photovoltaics
Theory predicts that a large spontaneous electric polarization and concomitant inversion symmetry breaking in GeSe monolayers result in a strong shift current in response to their excitation in the visible range. Shift current is a coherent displacement of electron density on the order of a lattice constant upon above-bandgap photoexcitation. A second-order nonlinear effect, it is forbidden by the inversion symmetry in the bulk GeSe crystals. In our paper, we use terahertz (THz) emission spectroscopy to demonstrate that ultrafast photoexcitation with wavelengths straddling both edges of the visible spectrum, 400 and 800 nm, launches a shift current in the surface layer of a bulk GeSe crystal, where the inversion symmetry is broken. The direction of the surface shift current determined from the observed polarity of the emitted THz pulses depends only on the orientation of the sample and not on the linear polarization direction of the excitation. Strong absorption by the low-frequency infrared-active phonons in the bulk of GeSe limits the bandwidth and the amplitude of the emitted THz pulses. We predict that reducing GeSe thickness to a monolayer or a few layers will result in a highly efficient broadband THz emission. Experimental demonstration of THz emission by the surface shift current in bulk GeSe crystals puts this 2D material forward as a candidate for next-generation shift current photovoltaics, nonlinear photonic devices, and THz sources.
Improved Catalyst Performance for the Oxygen Evolution Reaction under a Chiral Bias
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Tuning the Excited-State Dynamics of CuI Films with Electrochemical Bias
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Electro-Absorptive Quantum Dot Antenna Resolves Terahertz Lightwaves via Biased Stark Effect
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Near Room-Temperature Intrinsic Exchange Bias in an Fe Intercalated ZrSe 2 Spin Glass
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Biased Multicomponent Reactions to Develop Novel Bromodomain Inhibitors
Abstract not provided
Using Large Ensembles to Identify Regions of Systematic Biases in Moderate-to-Heavy Daily Precipitation
Because of internal variability in both the real-world and global climate models, it is unclear whether disagreement between models and observations reflects true systematic differences, or different phasing of internal variability in the short observational period. Here, we address this issue through an examination of moderate-to-heavy precipitation in large ensembles of global climate models. We find that model inconsistency with a global observational product is lowest for extratropical precipitation in northern hemisphere winter. The inconsistency is systematically greater for the southern hemisphere winter, but the difference between hemispheres could be due to observational quality. Moderate-to-heavy extratropical winter precipitation is less inconsistent than moderate-to-heavy tropical precipitation in most models. Within the tropics, moderate-to-heavy precipitation is particularly inconsistent with the reference in regions including the Caribbean (especially during JJA), the northern and southern flanks of the Pacific and Atlantic ITCZ, and the Indian Ocean.
Biased Estimates of Equilibrium Climate Sensitivity and Transient Climate Response Derived From Historical CMIP6 Simulations
Abstract This study assesses the effective climate sensitivity (EffCS) and transient climate response (TCR) derived from global energy budget constraints within historical simulations of eight CMIP6 global climate models (GCMs). These calculations are enabled by use of the Radiative Forcing Model Intercomparison Project (RFMIP) simulations, which permit accurate quantification of the radiative forcing. Long‐term historical energy budget constraints generally underestimate EffCS from CO 2 quadrupling and TCR from CO 2 ramping, owing to changes in radiative feedbacks and changes in ocean heat uptake efficiency. Atmospheric GCMs forced by observed warming patterns produce lower values of EffCS that are more in line with those inferred from observed historical energy budget changes. The differences in the EffCS estimates from historical energy budget constraints of models and observations are traced to discrepancies between modeled and observed historical surface warming patterns.
Understanding Precipitation Bias Sensitivities in E3SM-Multi-Scale Modeling Framework From a Dilution Framework
We investigate a set of Energy Exascale Earth System Model Multi-scale modeling framework (MMF) (E3SM-MMF) simulations that vary the dimensionality and momentum transport configurations of the embedded cloud-resolving models (CRMs), including unusually ambitious 3D configurations. Issues endemic to all MMF simulations include too much Intertropical Convergence Zone rainfall and too little over the Amazon. Systematic MMF improvements include more on-equatorial rainfall across the Warm Pool. Interesting sensitivities to the CRM domain are found in the regional time-mean precipitation pattern over the tropics. The 2D E3SM-MMF produces an unrealistically rainy region over the northwestern tropical Pacific; this is reduced in computationally ambitious 3D configurations that use 1,024 embedded CRM grid columns per host cell. Trajectory analysis indicates that these regional improvements are associated with desirably fewer tropical cyclones and less extreme precipitation rates. To understand why and how the representation of precipitation improved in 3D, we propose a framework that dilution is stronger in 3D. This viewpoint is supported by multiple indirect lines of evidence, including a delayed moisture-precipitation pickup, smaller precipitation efficiency, and amplified convective mass flux profiles and more high clouds. We also demonstrate that the effects of varying embedded CRM dimensionality and momentum transport on precipitation can be identified during the first few simulated days, providing an opportunity for rapid model tuning without high computational cost. Meanwhile the results imply that other less computationally intensive ways to enhance dilution within MMF CRMs may also be strategic tuning targets.
Modelling breast cancer requires identification and correction of a critical cell lineage-dependent transduction bias
When trying to explore the biology and etiology of human cancers, clinically relevant human culture models are essential. Current breast tumour models, such as those from oncogenically transformed primary breast cells, produce predominantly basal-like properties, whereas the more common phenotype expressed by the vast majority of breast tumours are luminal. Reasons for this puzzling, yet important phenomenon, are not understood. We show here that luminal epithelial cells are significantly more resistant to viral transduction than their myoepithelial counterparts. Here, we suggest that this is a significant barrier to generating luminal cell lines and experimental tumours in vivo and to accurate interpretation of results. We show that the resistance is due to lower affinity of luminal cells for virus attachment, which can be overcome by pretreating cells—or virus—with neuraminidase. We present an analytical method for quantifying transductional differences between cell types and an optimized protocol for transducing unsorted primary human breast cells in context.
Global leaf trait estimates biased due to plasticity in the shade
The study of leaf functional trait relationships, the so-called leaf economics spectrum , is based on the assumption of high-light conditions (as experienced by sunlit leaves). Owing to the exponential decrease of light availability through canopies, however, the vast majority of the world's vegetation exists in at least partial shade. Plant functional traits vary in direct dependence of light availability, with different traits varying to different degrees, sometimes in conflict with expectations from the economic spectrum. This means that the derived trait relationships of the global leaf economic spectrum are probably dependent on the extent to which observed data in existing large-scale plant databases represent high-light conditions. Here, using an extensive worldwide database of within-canopy gradients of key physiological, structural and chemical traits, along with three different global trait databases we show that: (1) accounting for light-driven trait plasticity can reveal novel trait relationships, particularly for highly plastic traits (for example, the relationship between net assimilation rate per area (A a ) and leaf mass per area (LMA)); and (2) a large proportion of leaf traits in current global plant databases reported as measured in full sun were probably measured in the shade. Our results show that even though the majority of leaves exist in the shade, along with a large proportion of observations, our current understanding is too focused on conditions in the sun.
Exchange-biasing topological charges by antiferromagnetism
Geometric Hall effect is induced by the emergent gauge field experienced by the carriers adiabatically passing through certain real-space topological spin textures, which is a probe to non-trivial spin textures, such as magnetic skyrmions. We report experimental indications of spin-texture topological charges induced in heterostructures of a topological insulator (Bi,Sb) 2 Te 3 coupled to an antiferromagnet MnTe. Through a seeding effect, the pinned spins at the interface leads to a tunable modification of the averaged real-space topological charge. This effect experimentally manifests as a modification of the field-dependent geometric Hall effect when the system is field-cooled along different directions. This heterostructure represents a platform for manipulating magnetic topological transitions using antiferromagnetic order.