FeSe layer-based superconductors exhibit exotic and distinctive properties. The undoped FeSe shows nematicity and superconductivity, while the heavily electron-doped KxFe2-ySe2 and single-layer ...FeSe/SrTiO3 possess high superconducting transition temperatures that pose theoretical challenges. However, a comprehensive study on the doping dependence of an FeSe layer-based superconductor is still lacking due to the lack of a clean means of doping control. Through angle-resolved photoemission spectroscopy studies on K-dosed thick FeSe films and FeSe0.93S0.07 bulk crystals, here we reveal the internal connections between these two types of FeSe-based superconductors, and obtain superconductivity below ∼ 46 K in an FeSe layer under electron doping without interfacial effects. Moreover, we discover an exotic phase diagram of FeSe with electron doping, including a nematic phase, a superconducting dome, a correlation-driven insulating phase and a metallic phase. Such an anomalous phase diagram unveils the remarkable complexity, and highlights the importance of correlations in FeSe layer-based superconductors.
The key physics of the spin valve involves spin-polarized conduction electrons propagating between two magnetic layers such that the device conductance is controlled by the relative magnetization ...orientation of two magnetic layers. Here, we report the effect of a magnon valve which is made of two ferromagnetic insulators (YIG) separated by a nonmagnetic spacer layer (Au). When a thermal gradient is applied perpendicular to the layers, the inverse spin Hall voltage output detected by a Pt bar placed on top of the magnon valve depends on the relative orientation of the magnetization of two YIG layers, indicating the magnon current induced by the spin Seebeck effect at one layer affects the magnon current in the other layer separated by Au. We interpret the magnon valve effect by the angular momentum conversion and propagation between magnons in two YIG layers and conduction electrons in the Au layer. The temperature dependence of the magnon valve ratio shows approximately a power law, supporting the above magnon-electron spin conversion mechanism. This work opens a new class of valve structures beyond the conventional spin valves.
Abstract Lithium and valproic acid (VPA) are two primary drugs used to treat bipolar disorder, and have been shown to have neuroprotective properties in vivo and in vitro . A recent study ...demonstrated that combined treatment with lithium and VPA elicits synergistic neuroprotective effects against glutamate excitotoxicity in cultured brain neurons, and the synergy involves potentiated inhibition of glycogen synthase kinase-3 (GSK-3) activity through enhanced GSK-3 serine phosphorylation Leng Y, Liang MH, Ren M, Marinova Z, Leeds P, Chuang DM (2008) Synergistic neuroprotective effects of lithium and valproic acid or other histone deacetylase inhibitors in neurons: roles of glycogen synthase kinase-3 inhibition. J Neurosci 28:2576–2588. We therefore investigated the effects of lithium and VPA cotreatment on the disease symptom onset, survival time and neurological deficits in cooper zinc superoxide dismutase (SOD1) G93A mutant mice, a commonly used mouse model of amyotrophic lateral sclerosis (ALS). The G93A ALS mice received twice daily i.p. injections with LiCl (60 mg/kg), VPA (300 mg/kg) or lithium plus VPA, starting from the 30th day after birth and continuing until death. We found that combined treatment with lithium and VPA produced a greater and more consistent effect in delaying the onset of disease symptoms, prolonging the lifespan and decreasing the neurological deficit scores, compared with the results of monotreatment with lithium or VPA. Moreover, lithium in conjunction with VPA was more effective than lithium or VPA alone in enhancing the immunostaining of phospho-GSK-3βSer9 in brain and lumbar spinal cord sections. To our knowledge, this is the first demonstration of enhanced neuroprotection by a combinatorial approach using mood stabilizers in a mouse ALS model. Our results suggest that clinical trials using lithium and VPA in combination for ALS patients are a rational strategy.
Abstract
The interactions between electrons and antiferromagnetic magnons (AFMMs) are important for a large class of correlated materials. For example, they are the most plausible pairing glues in ...high-temperature superconductors, such as cuprates and iron-based superconductors. However, unlike electron-phonon interactions (EPIs), clear-cut observations regarding how electron-AFMM interactions (EAIs) affect the band structure are still lacking. Consequently, critical information on the EAIs, such as its strength and doping dependence, remains elusive. Here we directly observe that EAIs induce a kink structure in the band dispersion of Ba
1−
x
K
x
Mn
2
As
2
, and subsequently unveil several key characteristics of EAIs. We found that the coupling constant of EAIs can be as large as 5.4, and it shows strong doping dependence and temperature dependence, all in stark contrast to the behaviors of EPIs. The colossal renormalization of electron bands by EAIs enhances the density of states at Fermi energy, which is likely driving the emergent ferromagnetic state in Ba
1−
x
K
x
Mn
2
As
2
through a Stoner-like mechanism with mixed itinerant-local character. Our results expand the current knowledge of EAIs, which may facilitate the further understanding of many correlated materials where EAIs play a critical role.
Abstract
At the interface between monolayer FeSe films and SrTiO
3
substrates the superconducting transition temperature (
T
c
) is unexpectedly high, triggering a surge of excitement. The mechanism ...for the
T
c
enhancement has been the central question, as it may present a new strategy for seeking out higher
T
c
materials. To reveal this enigmatic mechanism, by combining advances in high quality interface growth,
16
O
$$\leftrightarrow$$
↔
18
O isotope substitution, and extensive data from angle resolved photoemission spectroscopy, we provide striking evidence that the high
T
c
in FeSe/SrTiO
3
is the cooperative effect of the intrinsic pairing mechanism in the FeSe and interactions between the FeSe electrons and SrTiO
3
phonons. Furthermore, our results point to the promising prospect that similar cooperation between different Cooper pairing channels may be a general framework to understand and design high-temperature superconductors.
The interface between transition metal compounds provides a rich playground for emergent phenomena. Recently, significantly enhanced superconductivity has been reported for single-layer FeSe on ...Nb-doped SrTiO3 substrate. Yet it remains mysterious how the interface affects the superconductivity. Here we use in situ angle-resolved photoemission spectroscopy to investigate various FeSe-based heterostructures grown by molecular beam epitaxy, and uncover that electronic correlations and superconducting gap-closing temperature (Tg) are tuned by interfacial effects. Tg up to 75 K is observed in extremely tensile-strained single-layer FeSe on Nb-doped BaTiO3, which sets a record high pairing temperature for both Fe-based superconductor and monolayer-thick films, providing a promising prospect on realizing more cost-effective superconducting device. Moreover, our results exclude the direct correlation between superconductivity and tensile strain or the energy of an interfacial phonon mode, and highlight the critical and non-trivial role of FeSe/oxide interface on the high Tg, which provides new clues for understanding its origin.
The general relationships between vegetation and water yield under different climatic regimes are well established at a small watershed scale in the past century. However, applications of these basic ...theories to evaluate the regional effects of land cover change on water resources remain challenging due to the complex interactions of vegetation and climatic variability and hydrologic processes at the large scale. The objective of this study was to explore ways to examine the spatial and temporal effects of a large ecological restoration project on water yield across the Loess Plateau region in northern China. We estimated annual water yield as the difference between precipitation input and modelled actual evapotranspiration (ET) output. We constructed a monthly ET model using published ET data derived from eddy flux measurements and watershed streamflow data. We validated the ET models at a watershed and regional levels. The model was then applied to examine regional water yield under land cover change and climatic variability during the implementation of the Grain-for-Green (GFG) project during 1999-2007. We found that water yield in 38% of the Loess Plateau area might have decreased (1-48 mm per year) as a result of land cover change alone. However, combined with climatic variability, 37% of the study area might have seen a decrease in water yield with a range of 1-54 mm per year, and 35% of the study area might have seen an increase with a range of 1-10 mm per year. Across the study region, climate variability masked or strengthened the water yield response to vegetation restoration. The absolute annual water yield change due to vegetation restoration varied with precipitation regimes with the highest in wet years, but the relative water yield changes were most pronounced in dry years. We concluded that the effects of land cover change associated with ecological restoration varied greatly over time and space and were strongly influenced by climatic variability in the arid region. The current regional vegetation restoration projects have variable effects on local water resources across the region. Land management planning must consider the influences of spatial climate variability and long-term climate change on water yield to be more effective for achieving environmental sustainability.
Data privacy mechanisms are essential for rapidly scaling medical training databases to capture the heterogeneity of patient data distributions toward robust and generalizable machine learning ...systems. In the current COVID-19 pandemic, a major focus of artificial intelligence (AI) is interpreting chest CT, which can be readily used in the assessment and management of the disease. This paper demonstrates the feasibility of a federated learning method for detecting COVID-19 related CT abnormalities with external validation on patients from a multinational study. We recruited 132 patients from seven multinational different centers, with three internal hospitals from Hong Kong for training and testing, and four external, independent datasets from Mainland China and Germany, for validating model generalizability. We also conducted case studies on longitudinal scans for automated estimation of lesion burden for hospitalized COVID-19 patients. We explore the federated learning algorithms to develop a privacy-preserving AI model for COVID-19 medical image diagnosis with good generalization capability on unseen multinational datasets. Federated learning could provide an effective mechanism during pandemics to rapidly develop clinically useful AI across institutions and countries overcoming the burden of central aggregation of large amounts of sensitive data.
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