Layer thickness crossover of type-II multiferroic magnetism in NiI2

The discovery of atomically thin van der Waals ferroelectric and magnetic materials encourages the exploration of 2D multiferroics, which holds the promise to understand fascinating magnetoelectric interactions and fabricate advanced spintronic devices. In addition to building a heterostructure consisting of ferroelectric and magnetic ingredients, thinning down layered multiferroics of spin origin such as NiI2 becomes a natural route to realize 2D multiferroicity. However, the layer-dependent behavior, widely known in the community of 2D materials, necessitates a rigorous scrutiny of the multiferroic order in the few-layer limit. Here, we interrogate the layer thickness crossover of helimagnetism in NiI2 that drives the ferroelectricity and thereby type-II multiferroicity. By using wavelength-dependent polarization-resolved optical second harmonic generation (SHG) to probe the ferroic symmetry, we find that the SHG arises from the inversion-symmetry-breaking magnetic order, not previously assumed ferroelectricity. This magnetism-induced SHG is only observed in bilayer or thicker layers, and vanishes in monolayer, suggesting the critical role of interlayer exchange interaction in breaking the degeneracy of geometrically frustrated spin structures in triangular lattice and stabilizing the type-II multiferroic magnetism in few-layers. While the helimagnetic transition temperature is layer dependent, the few-layer NiI2 exhibits another thickness evolution and reaches the bulk-like behavior in trilayer, indicated by the intermediate centrosymmetric antiferromagnetic state as revealed in Raman spectroscopy. Our work therefore highlights the magnetic contribution to SHG and Raman spectroscopy in reduced dimension and guides the optical study of 2D multiferroics.Comment: 23 pages, 4 figures, 6 supplementary figure

Effects of rice or wheat residue retention on the quality of milled japonica rice in a rice–wheat rotation system in China

AbstractIn rice–wheat rotation systems, crop straw is usually retained in the field at land preparation in every, or every other, season. We conducted a 3-year-6-season experiment in the middle–lower Yangtze River Valley to compare the grain qualities of rice under straw retained after single or double seasons per year. Four treatments were designed as: both wheat and rice straw retained (WR), only rice straw retained (R), only wheat straw retained (W), and no straw retained (CK). The varieties were Yangmai 16 wheat and Wuyunjing 23 japonica rice. The results showed contrasting effects of W and R on rice quality. Amylopectin content, peak viscosity, cool viscosity, and breakdown viscosity of rice grain were significantly increased in W compared to the CK, whereas gelatinization temperature, setback viscosity, and protein content significantly decreased. In addition, the effect of WR on rice grain quality was similar to that of W, although soil fertility was enhanced in WR due to straw being retained in two cycles. The differences in protein and starch contents among the treatments might result from soil nitrogen supply. These results indicate that wheat straw retained in the field is more important for high rice quality than rice straw return, and straw from both seasons is recommended for positive effects on soil fertility

A multi-target prediction model for dam seepage field

Prediction of dam behavior based on monitoring data is important for dam safety and emergency management. It is crucial to analyze and predict the seepage field. Different from the mechanism-based physical models, machine learning models predict directly from data with high accuracy. However, current prediction models are generally based on environmental variables and single measurement point time series. Sometimes point-by-point modeling is used to obtain multi-point prediction values. In order to improve the prediction accuracy and efficiency of the seepage field, a novel multi-target prediction model (MPM) is proposed in which two deep learning methods are integrated into one frame. The MPM model can capture causal temporal features between environmental variables and target values, as well as latent correlation features between different measurement points at each moment. The features of these two parts are put into fully connected layers to establish the mapping relationship between the comprehensive feature vector and the multi-target outputs. Finally, the model is trained for prediction in the framework of a feed-forward neural network using standard back propagation. The MPM model can not only describe the variation pattern of measurement values with the change of load and time, but also reflect the spatial distribution relationship of measurement values. The effectiveness and accuracy of the MPM model are verified by two cases. The proposed MPM model is commonly applicable in prediction of other types of physical fields in dam safety besides the seepage field

Evolution of Maximum Bending Strain on Poisson's Ratio Distribution

In recent years, new flexible functional materials have attracted increasing interest, but there is a lack of the designing mechanisms of flexibility design with superstructures. In traditional engineering mechanics, the maximum bending strain (MBS) was considered universal for describing the bendable properties of a given material, leading to the universal designing method of lowering the dimension such as thin membranes designed flexible functional materials.In this work, the MBS was found only applicable for materials with uniformly distributed Poisson's ratio, while the MBS increases with the thickness of the given material in case there is a variation Poisson's ratio in different areas. This means the MBS can be enhanced by certain Poisson's ratio design in the future to achieve better flexibility of thick materials. Here, the inorganic freestanding nanofiber membranes, which have a nonconstant Poisson's ratio response on stress/strain for creating nonuniformly distributed Poisson's ratio were proven applicable for designing larger MBS and lower Young's modulus for thicker samples

Infrared Imaging of Magnetic Octupole Domains in Non-collinear Antiferromagnets

Magnetic structure plays a pivotal role in the functionality of antiferromagnets (AFMs), which not only can be employed to encode digital data but also yields novel phenomena. Despite its growing significance, visualizing the antiferromagnetic domain structure remains a challenge, particularly for non-collinear AFMs. Currently, the observation of magnetic domains in non-collinear antiferromagnetic materials is feasible only in Mn$_{3}$Sn, underscoring the limitations of existing techniques that necessitate distinct methods for in-plane and out-of-plane magnetic domain imaging. In this study, we present a versatile method for imaging the antiferromagnetic domain structure in a series of non-collinear antiferromagnetic materials by utilizing the anomalous Ettingshausen effect (AEE), which resolves both the magnetic octupole moments parallel and perpendicular to the sample surface. Temperature modulation due to the AEE originating from different magnetic domains is measured by the lock-in thermography, revealing distinct behaviors of octupole domains in different antiferromagnets. This work delivers an efficient technique for the visualization of magnetic domains in non-collinear AFMs, which enables comprehensive study of the magnetization process at the microscopic level and paves the way for potential advancements in applications.Comment: National Science Review in pres

Proximity effect induced intriguing superconductivity in van der Waals heterostructure of magnetic topological insulator and conventional superconductor

Nontrivial topological superconductivity has received enormous research attentions due to its potential for diverse applications in topological quantum computing. The intrinsic issue concerning the correlation between a topological insulator and a superconductor is, however, still widely open. Here, we systemically report an emergent superconductivity in a cross-junction composed of a magnetic topological insulator MnBi2Te4 and a conventional superconductor NbSe2. Remarkably, the interface indicates existence of a reduced superconductivity at surface of NbSe2 and a proximity-effectinduced superconductivity at surface of MnBi2Te4. Furthermore, the in-plane angular-dependent magnetoresistance measurements reveal the fingerprints of the paring symmetry behaviors for these superconducting gaps as a unconventional nature. Our findings extend our views and ideas of topological superconductivity in the superconducting heterostructures with time-reversal symmetry breaking, offering an exciting opportunity to elucidate the cooperative effects on the surface state of a topological insulator aligning a superconductor.Comment: 6 pages, 4 figure

Lack of Association of miR-146a rs2910164 Polymorphism with Gastrointestinal Cancers: Evidence from 10206 Subjects

BACKGROUND: Recent studies on the association between miR-146a rs2910164 polymorphism and risk of gastrointestinal (GI) cancers showed inconclusive results. Accordingly, we conducted a comprehensive literature search and a meta-analysis to clarify the association. METHODOLOGY/PRINCIPAL FINDINGS: Data were collected from the following electronic databases: Pubmed, Excerpta Medica Database (Embase), and Chinese Biomedical Literature Database (CBM), with the last report up to February 24, 2012. The odds ratio (OR) and its 95% confidence interval (95%CI) were used to assess the strength of association. Ultimately, a total of 12 studies (4,817 cases and 5,389 controls) were found to be eligible for meta-analysis. We summarized the data on the association between miR-146a rs2910164 polymorphism and risk of GI cancers in the overall population, and performed subgroup analyses by ethnicity, cancer types, and quality of studies. In the overall analysis, there was no evidence of association between miR-146a rs2910164 polymorphism and the risk of GI cancers (G versus C: OR = 1.07, 95%CI 0.98-1.16, P = 0.14; GG+GC versus CC: OR = 1.14, 95%CI 1.00-1.31, P = 0.05; GG versus GC+CC: OR = 1.06, 95%CI 0.91-1.23, P = 0.47; GG versus CC: OR = 1.17, 95%CI 0.95-1.44, P = 0.13; GC versus CC: OR = 1.14, 95%CI 1.00-1.31, P = 0.05). Similar results were found in the subgroup analyses by ethnicity, cancer types, and quality of studies. CONCLUSIONS/SIGNIFICANCE: This meta-analysis demonstrates that miR-146a rs2910164 polymorphism is not associated with GI cancers susceptibility. More well-designed studies based on larger sample sizes and homogeneous cancer patients are needed

An Introduction to Sphingolipid Metabolism and Analysis by New Technologies

Sphingolipids (SP) are a complex class of molecules found in essentially all eukaryotes and some prokaryotes and viruses where they influence membrane structure, intracellular signaling, and interactions with the extracellular environment. Because of the combinatorial nature of their biosynthesis, there are thousands of SP subspecies varying in the lipid backbones and complex phospho- and glycoheadgroups. Therefore, comprehensive or “sphingolipidomic” analyses (structure-specific, quantitative analyses of all SP, or at least all members of a critical subset) are needed to know which and how much of these subspecies are present in a system as a step toward understanding their functions. Mass spectrometry and related novel techniques are able to quantify a small fraction, but nonetheless a substantial number, of SP and are beginning to provide information about their localization. This review summarizes the basic metabolism of SP and state-of-art mass spectrometric techniques that are producing insights into SP structure, metabolism, functions, and some of the dysfunctions of relevance to neuromedicine