Realization of multiple charge density waves in NbTe2 at the monolayer limit

Abstract: Layered transition-metal dichalcogenides (TMDCs) down to the monolayer (ML) limit provide a fertile platform for exploring charge-density waves (CDWs). Though bulk NbTe2 is known to harbor a single axis 3*1 CDW coexisting with non-trivial quantum properties, the scenario in the ML limit is still experimentally unknown. In this study, we unveil the richness of the CDW phases in ML NbTe2, where not only the theoretically predicted 4*4 and 4*1 phases, but also two unexpected sqrt(28)*sqrt(28) and sqrt(19)*sqrt(19) phases, can be realized. For such a complex CDW system, we establish an exhaustive growth phase diagram via systematic efforts in the material synthesis and scanning tunneling microscope characterization. Moreover, we report that the energetically stable phase is the larger scale order (sqrt(19)*sqrt(19)), which is surprisingly in contradiction to the prior prediction (4*4). These findings are confirmed using two different kinetic pathways, i.e., direct growth at proper growth temperatures (T), and low-T growth followed by high-T annealing. Our results provide a comprehensive diagram of the "zoo" of CDW orders in ML 1T-NbTe2 for the first time and offer a new material platform for studying novel quantum phases in the 2D limit

Mining the candidate genes of rice panicle traits via a genome-wide association study

Panicle traits are important for improving the panicle architecture and grain yield of rice. Therefore, we performed a genome-wide association study (GWAS) to analyze and determine the genetic determinants of five panicle traits. A total of 1.29 million single nucleotide polymorphism (SNP) loci were detected in 162 rice materials. We carried out a GWAS of panicle length (PL), total grain number per panicle (TGP), filled grain number per panicle (FGP), seed setting rate (SSR) and grain weight per panicle (GWP) in 2019, 2020 and 2021. Four quantitative trait loci (QTLs) for PL were detected on chromosomes 1, 6, and 9; one QTL for TGP, FGP, and GWP was detected on chromosome 4; two QTLs for FGP were detected on chromosomes 4 and 7; and one QTL for SSR was detected on chromosome 1. These QTLs were detected via a general linear model (GLM) and mixed linear model (MLM) in both years of the study period. In this study, the genomic best linear unbiased prediction (BLUP) method was used to verify the accuracy of the GWAS results. There are nine QTLs were both detected by the multi-environment GWAS method and the BLUP method. Moreover, further analysis revealed that three candidate genes, LOC_Os01g43700, LOC_Os09g25784, and LOC_Os04g47890, may be significantly related to panicle traits of rice. Haplotype analysis indicated that LOC_Os01g43700 and LOC_Os09g25784 are highly associated with PL and that LOC_Os04g47890 is highly associated with TGP, FGP, and GWP. Our results offer essential genetic information for the molecular improvement of panicle traits. The identified candidate genes and elite haplotypes could be used in marker-assisted selection to improve rice yield through pyramid breeding

PTCDA molecular monolayer on Pb thin films: An unusual π-electron Kondo system and its interplay with a quantum-confined superconductor

The hybridization of magnetism and superconductivity has been an intriguing playground for correlated electron systems, hosting various novel physical phenomena. Usually, localized d- or f-electrons are central to magnetism. In this study, by placing a PTCDA (3,4,9,10-perylene tetracarboxylic dianhydride) molecular monolayer on ultra-thin Pb films, we built a hybrid magnetism/superconductivity (M/SC) system consisting of only sp electronic levels. The magnetic moments reside in the unpaired molecular orbital originating from interfacial charge-transfers. We reported distinctive tunneling spectroscopic features of such a Kondo screened pi-electron impurity lattice on a superconductor in the regime of TK>>delta suggesting the formation of a two-dimensional bound states band. Moreover, moiré superlattices with tunable twist angle and the quantum confinement in the ultra-thin Pb films provide easy and flexible implementations to tune the interplay between the Kondo physics and the superconductivity, which are rarely present in M/SC hybrid systems.Center for Dynamics and Control of Material

Study on ventilation scheme and application during construction of high altitude gas tunnel

It is the key and difficult point to ensure the safety of tunnel construction by ventilation in high gas tunnel construction in high altitude and cold area. Taking ning-chan high gas tunnel as the research object, the ventilation of the tunnel is calculated, the ventilation parameters are optimized, the ventilation equipment is selected according to the calculation results, the location of the ventilation equipment is optimized, and the reasonable construction ventilation scheme is determined. The results show that through the design of the above ventilation scheme and the control of the site, it can not only ensure the ventilation demand of the super long and high gas tunnel construction in the high cold and high altitude area, but also ensure the tunnel construction in winter, and effectively save the construction ventilation cost

Optimization of Operation Parameters of the Garlic Plant Divider and Lifter Mechanisms

The technology of the divider and lifter mechanisms of a garlic harvester using the depth limit, straw divide, and straw lift modes was studied in Lanling County, Shandong Province, China, according to the characteristics of high hardness, good uprightness and narrow row spacing of garlic planting. A test prototype of the divider and lifter mechanisms of the garlic harvester was designed and manufactured. Single-factor experiments and orthogonal regression experiments were carried out using the experimental factors of working speed, the angle of the divider, the height of the tip of the divider’s tooth from the ground, the ratio of the lifter’s speed to working speed and the length of the lifter’s tooth. The index was the success rate of feed. The results showed that the working speed, the angle of the divider and the length of the lifter’s tooth had a significant influence on the success rate of feed (p p > 0.05). The effects of the angle of the divider, the working speed, and the length of the divider’s tooth on the success rate of feed decreased in significance. When the working speed was 0.72 km·h−1, the length of the lifter’s tooth was 343.5 mm and the angle of the divider was 20°, the success rate of feed was the highest (98.18%). The research results are conducive to promoting high-quality and efficient combined harvesting of garlic in Lanling County, Shandong Province, China

The Spatiotemporal Characteristics of Wildfires across Australia and Their Connections to Extreme Climate Based on a Combined Hydrological Drought Index

With the frequent occurrence of extreme climates around the world, the frequency of regional wildfires is also on the rise, which poses a serious threat to the safety of human life, property, and regional ecosystems. To investigate the role of extreme climates in the occurrence and spread of wildfires, we combined precipitation, evapotranspiration, soil moisture (SM), maximum temperature (MT), relative humidity, plant canopy water, vapor pressure deficit, and a combined hydrological drought index based on six Gravity Recovery and Climate Experiment (GRACE) and its follow-on (GRACE-FO) products to study the relationship between climate change and wildfires across Australia between 2003 and 2020. The results show that Australia’s wildfires are mainly concentrated in the northern region, with a small number being distributed along the southeastern coast. The high burned months are September (2.5941 × 106 ha), October (4.9939 × 106 ha), and November (3.8781 × 106 ha), while the years with a larger burned area are 2011 (79.95 × 106 ha) and 2012 (78.33 × 106 ha) during the study period. On a seasonal scale, the terrestrial water storage change and the hydrometeorological factors have the strong correlations with burned area, while for only the drought index, SM and MT are strongly related to burned area on an interannual scale. By comparing the data between the high burned and normal years, the impact of droughts on wildfires is achieved through two aspects: (1) the creation of a dry atmospheric environment, and (2) the accumulation of natural combustibles. Extreme climates affect wildfires through the occurrence of droughts. Among them, the El Niño–Southern Oscillation has the greatest impact on drought in Australia, followed by the Pacific Decadal Oscillation and the Indian Ocean Dipole (correlation coefficients are −0.33, −0.31, and −0.23, respectively), but there is little difference among the three. The proposed hydrological drought index in our study has the potential to provide an early warning of regional wildfires. Our results have a certain reference significance for comprehensively understanding the impact mechanism of extreme climates on regional wildfires and for establishing an early warning system for regional wildfires

Controllable dimensionality conversion between 1D and 2D CrCl3 magnetic nanostructures

Abstract The fabrication of one-dimensional (1D) magnetic systems on solid surfaces, although of high fundamental interest, has yet to be achieved for a crossover between two-dimensional (2D) magnetic layers and their associated 1D spin chain systems. In this study, we report the fabrication of 1D single-unit-cell-width CrCl3 atomic wires and their stacked few-wire arrays on the surface of a van der Waals (vdW) superconductor NbSe2. Scanning tunneling microscopy/spectroscopy and first-principles calculations jointly revealed that the single wire shows an antiferromagnetic large-bandgap semiconducting state in an unexplored structure different from the well-known 2D CrCl3 phase. Competition among the total energies and nanostructure-substrate interfacial interactions of these two phases result in the appearance of the 1D phase. This phase was transformable to the 2D phase either prior to or after the growth for in situ or ex situ manipulations, in which the electronic interactions at the vdW interface play a nontrivial role that could regulate the dimensionality conversion and structural transformation between the 1D-2D CrCl3 phases

3D Mineral Prospectivity Mapping of Zaozigou Gold Deposit, West Qinling, China: Machine Learning-Based Mineral Prediction

This paper focuses on researching the scientific problem of deep extraction and inference of favorable geological and geochemical information about mineralization at depth, based on which a deep mineral resources prediction model is established and machine learning approaches are used to carry out deep quantitative mineral resources prediction. The main contents include: (i) discussing the method of 3D geochemical anomaly extraction under the multi-fractal content-volume (C-V) models, extracting the 12 element anomalies and constructing a 3D geochemical anomaly data volume model for laying the data foundation for researching geochemical element distribution and association; (ii) extracting the element association characteristics of primary geochemical halos and inferring deep metallogenic factors based on compositional data analysis (CoDA), including quantitatively extracting the geochemical element associations corresponding to ore-bearing structures (Sb-Hg) based on a data-driven CoDA framework, quantitatively identifying the front halo element association (As-Sb-Hg), near-ore halo element association (Au-Ag-Cu-Pb-Zn) and tail halo element association (W-Mo-Co-Bi), which provide quantitative indicators for the primary haloes’ structural analysis at depth; (iii) establishing a deep geological and geochemical mineral resources prediction model, which is constructed by five quantitative mineralization indicators as input variables: fracture buffer zone, element association (Sb-Hg) of ore-bearing structures, metallogenic element Au anomaly, near-ore halo element association Au-Ag-Cu-Pb-Zn and the ratio of front halo to tail halo (As-Sb-Hg)/(W-Mo-Bi); and (iv) three-dimensional MPM based on the maximum entropy model (MaxEnt) and Gaussian mixture model (GMM), and delineating exploration targets at depth. The results show that the C-V model can identify the geological element distribution and the CoDA method can extract geochemical element associations in 3D space reliably, and the machine learning methods of MaxEnt and GMM have high performance in 3D MPM