Synthesis and Properties of La1−x_{1-x}Srx_xNiO3_3 and La1−x_{1-x}Srx_xNiO2_2

Superconductivity has been realized in films of La$_{1-x}$Sr$_x$NiO$_2$. Here we report synthesis and characterization of polycrystalline samples of La$_{1-x}$Sr$_x$NiO$_3$ and La$_{1-x}$Sr$_x$NiO$_2$ ($0\le x\le 0.2$). Magnetization and resistivity measurements reveal that La$_{1-x}$Sr$_x$NiO$_3$ are paramagnetic metals and La$_{1-x}$Sr$_x$NiO$_2$ exhibit insulating behavior. Superconductivity is not detected in bulk samples of La$_{1-x}$Sr$_x$NiO$_2$. The absence of superconductivity in bulk La$_{1-x}$Sr$_x$NiO$_2$ may be due to the generation of hydroxide during reduction or a small amount of nickel impurities. The effect of interface in films of La$_{1-x}$Sr$_x$NiO$_2$ may also play a role for superconductivity.Comment: 9 pages, 4 figure

Coexistence of ferromagnetism, antiferromagnetism, and superconductivity in magnetically anisotropic (Eu,La)FeAs2

Materials with exceptional magnetism and superconductivity usually conceive emergent physical phenomena. Here, we investigate the physical properties of the (Eu,La)FeAs2 system with double magnetic sublattices. The parent EuFeAs2 shows anisotropy-associated magnetic behaviors, such as Eu-related moment canting and exchange bias. Through La doping, the magnetic anisotropy is enhanced with ferromagnetism of Eu2+ realized in the overdoped region, and a special exchange bias of the superposed ferromagnetic/superconducting loop revealed in Eu0.8La0.2FeAs2. Meanwhile, the Fe-related antiferromagnetism shows unusual robustness against La doping. Theoretical calculation and 57Fe M\"ossbauer spectroscopy investigation reveal a doping-tunable dual itinerant/localized nature of the Fe-related antiferromagnetism. Coexistence of the Eu-related ferromagnetism, Fe-related robust antiferromagnetism, and superconductivity is further revealed in Eu0.8La0.2FeAs2, providing a platform for further exploration of potential applications and emergent physics. Finally, an electronic phase diagram is established for (Eu,La)FeAs2 with the whole superconducting dome adjacent to the Fe-related antiferromagnetic phase, which is of benefit for seeking underlying clues to high-temperature superconductivity.Comment: 13 pages, 6 figures for the main tex

Structural, magnetic, and electronic evolution of the spin-ladder system BaFe2_2S3−x_{3-x}Sex_x with isoelectronic substitution

We report experimental studies of a series of BaFe$_2$S$_{3-x}$Se$_x$ ($0\leq x\leq3$) single crystals and powder specimens using x-ray diffraction, neutron diffraction, muon spin relaxation, and electrical transport measurements. A structural transformation from Cmcm (BaFe$_2$S$_3$) to Pnma (BaFe$_2$Se$_3$) was identified around $x = 0.7\sim 1$. Neutron diffraction measurements on the samples with $x$ = 0.2, 0.4, and 0.7 reveal that the N$\'{e}$el temperature of the stripe antiferromagnetic order is gradually suppressed from $\sim$120 to 85 K, while the magnitude of the ordered Fe$^{2+}$ moments shows very little variation. Similarly, the block antiferromagnetic order in BaFe$_2$Se$_3$ remains robust for $1.5\leq x\leq3$ with negligible variation in the ordered moment and a slight decrease of the N$\'{e}$el temperature from 250 K ($x=3$) to 225 K ($x=1.5$). The sample with $x=1$ near the Cmcm and Pnma border shows coexisting, two-dimensional, short-range stripe- and block-type antiferromagnetic correlations. The system remains insulating for all $x$, but the thermal activation gap shows an abrupt increase when traversing the boundary from the Cmcm stripe phase to the Pnma block phase. The results demonstrate that the crystal structure, magnetic order, and electronic properties are strongly coupled in the BaFe$_2$S$_{3-x}$Se$_x$ system.Comment: 16 pages, 8 figure

Mechanism of bubble action in backfill slurry and the evolution of its rheological properties

Cemented paste backfill is a suspension composed of solid-liquid-gas three-phase. For a long time, the focus has been mostly on the rheological behavior of solid-liquid two-phase, while the effect of gas phase on slurry with complex rheological behavior remains obscure. The gaseous phase components can significantly reduce the yield stress and viscosity of high-concentration backfilling slurry, which plays a significant role on improving pipeline transportation performance and reducing pipeline wear. In order to reveal the mechanism of bubbles to its rheological properties of slurry, the gas content of slurry was controlled by adjusting the content of air entrainment agent (TTAB), and tests such as surface tension, air content and rheological properties were carried out to find out the influence of bubbles on the rheological behavior of slurry, and capillary force (Fcay) and the bubble evolution model of dimensionless yield stress (\begin{document}${\tau }_{{\mathrm{ref}}}/{\tau }_{{\mathrm{y}}}$\end{document}) were introduced to analyze the bubble evolution characteristics in the slurry and reveal the mechanism of bubbles on the rheological properties of slurry. The results showed that under the low gas content ( < 12.5%), the gas phase had little effect on the rheological behavior of the suspended slurry. As the increase of gas content, the effect of bubbles on the rheological behavior of backfilling slurry was immense. Under the action of the air-entraining, the bubble surface had a repulsive force on the fine particles in the slurry, and could reduce the adsorption capacity of cement and solid waste, resulting in a decreasing trend of slurry yield stress and increasing fluidity. Based on capillary force (Fcay) and dimensionless yield stress theory (\begin{document}${\tau }_{{\mathrm{ref}}}/{\tau }_{{\mathrm{y}}}$\end{document}), evolutional mechanism of rheological properties of slurry in different gas content was analyzed. It could be seen that as the gas content increased (12.5%−27.7%), the surface tension and yield stress of slurry decreased, and the bubble would be deformed by extrusion. When the gas content (28.6%) was high, the bubbles in the slurry were easy to burst. In addition, bubbles, retained inside the backfilling body, leading to strength degradation, so the effect of bubbles on the mechanical properties of the backfilling body and its solution were explored and three effective measures were proposed. By revealing the effect of bubbles on the rheological properties of suspension slurry and its evolution characteristics, it provides theoretical support for the development of high bubble filling, which can achieve the goal of drag reduction and friction reduction

Single crystal growth and superconductivity in RbNi2_2Se2_2

We report the synthesis and characterization of RbNi$_2$Se$_2$, an analog of the iron chalcogenide superconductor Rb$_x$Fe$_2$Se$_2$, via transport, angle resolved photoemission spectroscopy, and density functional theory calculations. A superconducting transition at $T_{c}$ = 1.20 K is identified. In normal state, RbNi$_2$Se$_2$ shows paramagnetic and Fermi liquid behaviors. A large Sommerfeld coefficient yields a heavy effective electron mass of $m^{*}\approx6m_{e}$. In the superconducting state, zero-field electronic specific-heat data $C_{es}$ can be described by a two-gap BCS model, indicating that RbNi$_2$Se$_2$ is a multi-gap superconductor. Our density functional theory calculations and angle resolved photoemission spectroscopy measurements demonstrate that RbNi$_2$Se$_2$ exhibits relatively weak correlations and multi-band characteristics, consistent with the multi-gap superconductivity.Comment: 7 pages, 4 figure

Lubricating Oil Pollution Detection Sensor Design

Metal abrasive particle content in lubricating oil is an important index to judge the degree of deterioration of lubricating oil. Established a spiral electrode capacitance sensor by the finite element software ANSYS, the simulation result shows that the sensor is sensitive to the content of metal abrasive particle in lubricating oil, not affect by the metal abrasive particle itself. According to the simulation optimization model to make the real sensor, and designed lubricating oil pollution degree measurement system with the MS3110 capacitance detection circuit and MCU. Experiments show that it can distinguish metal abrasive particle from the change of 0.1 %-0.5 % content, this change can determine the degree of pollution of metal abrasive particle in lubricating oil, provides a simple and feasible method for the oil pollution detection

Random Forest Slurry Pressure Loss Model Based on Loop Experiment

A reasonable arrangement of filling pipelines can solve the problems of low line magnification, a high flow rate, large pipe pressure, etc., in deep well filling slurry transportation. The transportation pressure loss value of filling slurry is the main parameter for the layout design of filling pipelines. At present, pressure loss data are mainly obtained through the loop pipe experiment, which has problems such as a large amount of labor, high cost, low efficiency, and a limited amount of experimental data. In this paper, combined with a new generation of artificial intelligence technology, the random forest machine learning algorithm is used to analyze and model the experimental data of a loop pipe to predict the pressure loss of slurry transportation. The degree of precision reaches 0.9747, which meets the design accuracy requirements, and it can replace the loop pipe experiment to assist with the filling design

Random Forest Slurry Pressure Loss Model Based on Loop Experiment

A reasonable arrangement of filling pipelines can solve the problems of low line magnification, a high flow rate, large pipe pressure, etc., in deep well filling slurry transportation. The transportation pressure loss value of filling slurry is the main parameter for the layout design of filling pipelines. At present, pressure loss data are mainly obtained through the loop pipe experiment, which has problems such as a large amount of labor, high cost, low efficiency, and a limited amount of experimental data. In this paper, combined with a new generation of artificial intelligence technology, the random forest machine learning algorithm is used to analyze and model the experimental data of a loop pipe to predict the pressure loss of slurry transportation. The degree of precision reaches 0.9747, which meets the design accuracy requirements, and it can replace the loop pipe experiment to assist with the filling design