We theoretically investigate strong-filed electron vortices in time-delayed circularly polarized laser pulses by a generalized quantum-trajectory Monte Carlo (GQTMC) model. Vortex interference patterns in photoelectron momentum distributions (PMDs) with various laser parameters can be well reproduced by the semiclassical simulation. The phase difference responsible for the interference structures is analytically identified through trajectory-based analysis and simple-man theory, which reveal the underlying mechanism of electron vortex phenomena for both co-rotating and counter-rotating component. This semiclassical analysis can also demonstrate the influences of laser intensity and wavelength on the number of arms of vortices. Furthermore, we show the influence of the Coulomb effect on the PMDs. Finally, the controlling of the ionization time intervals in the tens to hundreds of attosecond magnitude is qualitatively discussed.
Ferrihydrite (Fh) is a major Fe(III)-(oxyhydr)oxide nanomineral distinguished by its poor crystallinity and thermodynamic metastability. While it is well known that in suboxic conditions aqueous Fe(II) rapidly catalyzes Fh transformation to more stable crystalline Fe(III) phases such as lepidocrocite (Lp) and goethite (Gt), because of the low solubility of Fe(III) the mass transfer pathways enabling these rapid transformations have remained unclear for decades. Here, using a selective extractant, we isolated and quantified a critical labile Fe(III) species, one that is more reactive than Fe(III) in Fh, formed by the oxidation of aqueous Fe(II) on the Fh surface. Experiments that compared time-dependent concentrations of solid-associated Fe(II) and this labile Fe(III) against the kinetics of phase transformation showed that its accumulation is directly related to Lp/Gt formation in a manner consistent with the classical nucleation theory. 57Fe isotope tracer experiments confirm the oxidized Fe(II) origin of labile Fe(III). The transformation pathway as well as the accelerating effect of Fe(II) can now all be explained on a unified basis of the kinetics of Fe(III) olation and oxolation reactions necessary to nucleate and sustain growth of Lp/Gt products, rates of which are greatly accelerated by labile Fe(III).
espite successful modeling of graphene as a 0.34-nm-thick optical film synthesized by exfoliation or chemical vapor deposition (CVD), graphene-induced shift of surface-plasmon resonance (SPR) of gold films has remained controversial. Here we report the resolution of this controversy by developing a clean CVD graphene transfer method and extending Maxwell-Garnett effective-medium theory (EMT) to two-dimensional (2D) materials. A SPR shift of 0.24° is obtained and it agrees well with 2D EMT in which wrinkled graphene is treated as a 3-nm graphene/air layered composite, in agreement with the average roughness measured by atomic force microscopy. Because the anisotropic built-in boundary condition of 2D EMT is compatible with graphene's optical anisotropy, graphene can be modeled as a film thicker than 0.34 nm without changing its optical property; however, its actual roughness, i.e., effective thickness, will significantly alter its response to strong out-of-plane fields, leading to a larger SPR shift.
Abstract A key challenge in ecology is to understand the relationships between organismal traits and ecosystem processes. Here, with a novel dataset of leaf length and width for 10 480 woody dicots in China and 2374 in North America, we show that the variation in community mean leaf size is highly correlated with the variation in climate and ecosystem primary productivity, independent of plant life form. These relationships likely reflect how natural selection modifies leaf size across varying climates in conjunction with how climate influences canopy total leaf area. We find that the leaf size‒primary productivity functions based on the Chinese dataset can predict productivity in North America and vice-versa. In addition to advancing understanding of the relationship between a climate-driven trait and ecosystem functioning, our findings suggest that leaf size can also be a promising tool in palaeoecology for scaling from fossil leaves to palaeo-primary productivity of woody ecosystems.
Microbial carbon has recently been highlighted to play a key role in the formation and persistence of soil organic carbon, bearing significant implications for regulating ecosystem carbon stocks under global changes. However, microbial carbon distribution and the link between biomass and necromass components are poorly understood in natural soils, especially at depth. Here, we employ various microbial biomarkers, including phospholipid fatty acids (PLFAs), amino sugars and glycerol dialkyl glycerol tetraethers (GDGTs), to investigate the spatial distribution patterns of microbial biomass and necromass components in the top- (0–10 cm) versus subsoils (30–50 cm) across Chinese temperate grasslands along an aridity gradient. We find that bacterial necromass components are better preserved relative to bacterial biomass in the sub- than topsoil, possibly due to a stronger association of microbial necromass with calcium and/or lower nitrogen competition between plants and microbes at depth in these neutral-to-alkaline soils. As a result, there is a stronger link between bacterial necromass components (especially for core lipid branched GDGTs and muramic acid) and their producers (reflected by intact polar lipid-derived branched GDGTs) in the sub- than topsoil, while such a trend is not observed for fungi- or archaea-derived components. Furthermore, using linear mixed effect model analyses, we find that aridity index best explains the concentration variance of most microbial biomarkers in the topsoil, whereas edaphic properties (i.e., pH and macronutrients) also contribute significantly to their variance in the subsoil. These findings highlight different links between microbial necromass and biomass components and distinct preservation mechanisms for microbial carbon at different soil depths, which is crucial for improved understanding of microbial carbon sequestration potentials at different depths in a changing environment.
Modeling and optimization of a large-scale urban energy-water nexus system with sufficient spatial resolutions is a complex challenge. By proper clustering technique, a large-scale problem could possibly be divided into small ones with high spatial resolution and accuracy. Existing literature tends to lower the complexity of large-scale urban energy system problem by accumulating demand profiles on the spatial dimension. This study proposes a flexible clustering approach based on density clustering method with combined index assessment process. The flexible approach considers not only the spatial dimensions but also the complementarity effect of different demand profile and control the computational time of system design and optimization. The approach can increase the clustering flexibility by providing more clustering options than conventional method, take advantages of complementarity effect to further improve the system economic performance and control the solving time in an acceptable range. The proposed approach is evaluated by a case study of a new business district in Shanghai, China with a proposed future energy-water nexus system. After three combined index assessment, 45 new clustering maps are generated by the flexible clustering approach and the final optimal solution obtained by the proposed approach can further obtain 6.74% cost savings compared with conventional clustering approach.