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The effect of Ce substitution on the structural and magnetic properties of (Nd1-δCeδ)2Fe14B (0

Doping some elements on Li site of LLZO is an effective method to stabilize it as cubic phase and improve Li+ conductivity. The reported possible Li site elements calculated by first principle are Be, B, Al, Fe, Zn, Ga and the Ga-doped LLZO shows the a higher conductivity than other LLZO. However, whether these elements all can stable LLZO as cubic phase are needed to be verified and the reason of Ga exhibits higher conductivity is not clear enough. In this work, all these elements are tried to be doped on Li site and the results show that the Al, or Fe, or Ga can stable LLZO as cubic phase while the others does not. The Ga-doped LLZO exhibits the highest conductivity of 1.31×10−3 S•cm-1 due to the transform of group space from Ia-3d to I-43d, shorter distances between different Li+, and Ga can improve the grain size.

A large linear negative thermal expansion (NTE) and expanded NTE temperature range (ΔTNTE) were obtained in magnetoelastic CrTe1-xSex (0 ≤ x ≤ 0.15) compounds. For CrTe compound, its thermal expansion coefficient of volume (αV) was calculated to be -28.8 ppm K-1 with the temperature ranging from 280 to 340 K. Substituting Te with Se atoms, the NTE behavior and magnetic properties can be well manipulated. With increasing Se in CrTe1-xSex (0 ≤ x ≤ 0.15) compounds, the ΔTNTE increases from 60 K (280-340 K for x = 0), to 80 K (240-320 K for x = 0.05), to 95 K (200-295 K for x = 0.1), and finally to 100 K (170-270 K for x = 0.15). Furthermore, a linear NTE remains independent of temperature for samples with x ≤ 0.1. The relationship between tunable NTE and magnetic properties was analyzed in detail, indicating that the NTE in CrTe1-xSex compounds originates from the magnetovolume effect (MVE).

Layered cathodes have been recognized as potential advanced candidates for sodium-ion batteries (SIBs), but the poor electrochemical performance has seriously hindered their further development. Herein, an ordered Na

To understand what and how structural properties affect battery performance, and to optimize the structural properties accordingly are of crucial importance to improve the performance of cathode materials for advanced Li-ion batteries. Herein, we investigated the influence of Li-enrichment in Li1+x(Ni0.8Co0.2)1-xO2 transition metal (TM) oxide cathodes, obtained by sintering Ni0.8Co0.2(OH)2 precursor with different amount of Li sources. Compared with stoichiometric Li1+x(Ni0.8Co0.2)1-xO2 (i.e. x = 0, Li:TM = 1:1), the improvements of cycling stability and rate performance were observed in material with moderate degree of Li-enrichment with respect to TMs (i.e. x = 0.019, Li:TM = 1.04:1). Further increase in Li:TM ratio up to 1.07 diminishes the electrochemical performance. Multi-scale structural characterizations including neutron diffraction and aberration-corrected transmission electron microscopy measurements show that the Li-enrichment leads to a monotonical increase in both Li/Ni exchange ratio and Li slab space. Based on the results, we argue that, in material with moderate Li-enrichment, larger Li slab space can facilitate the diffusion of Li ions and a certain amount of Li/Ni disordering can also mitigate the contraction of layered structure, therefore resulting in an optimized electrochemical performance; while in material with excessive Li:TM ratio, the diffusion path can be partially blocked due to the presence of redundant Ni ions in Li layers.

Ni-rich layered oxides are very promising high energy density cathodes for lithium-ion batteries. A small amount of Ni, Co, and Mn is substituted by Al to study the structural evolution, electroche...

The crystal structure, dynamics, magnetic structure and property of orthochromites solid solution Ho1−xYxCrO3 (x = 0, 0.2,…,1.0) were systematically investigated by X-ray diffraction, Raman scattering, magnetometry and neutron powder diffraction. With increasing non-magnetic Y3+-substitution for Ho3+ throughout the whole range, the crystallographic parameters remain almost unchanged, so is Neel temperature (TN ≈ 141 K), which is closely related to the structure in these orthochromites. However, the Raman spectra demonstrates the lattice dynamics is influenced due to the mass difference between Ho3+ and Y3+. Moreover, the spin reorientation property is also strongly affected by Y-substitution revealed by neutron powder diffraction. For the composition of x ≤ 0.6, the magnetism of Cr3+ sublattice adopts Γ2 spin configuration in terms of Bertaut notation from low temperature (10 K) up to Neel temperature. With the doping concentration further increases to x = 0.7 and 0.8, the system exhibits a mixed structure of (Γ2 + Γ4) within a certain temperature range. Beyond and underneath of which, a single spin configuration is identified as Γ4 (GxAyFz) and Γ2 (FxCyGz), respectively. After x = 0.8, only Γ4 (GxAyFz) are observed below TN. These phenomena are attributed to the weakened Ho3+-Cr3+ interaction with Y-substitution, which causes a competition between Γ2 and Γ4 spin configurations.

P2-type layered oxides have been considered as promising cathode materials for Na-ion batteries, but the capacity decay resulting from the Na+/vacancy ordering and phase transformation limits their future large-scale applications. Herein, the impact of Li-doping in different layers on the structure and electrochemical performance of P2-type Na0.7Ni0.35Mn0.65O2 is investigated. It can be found that Li ions successfully enter both the Na and transition metal layers. The strategy of Li-doping can improve the cycling stability and rate capability of P2-type layered oxides, which promotes the development of high-performance Na-ion batteries.

Deep reinforcement learning (DRL) provides a promising way for learning navigation in complex autonomous driving scenarios. However, identifying the subtle cues that can indicate drastically different outcomes remains an open problem with designing autonomous systems that operate in human environments. In this work, we show that explicitly inferring the latent state and encoding spatial-temporal relationships in a reinforcement learning framework can help address this difficulty. We encode prior knowledge on the latent states of other drivers through a framework that combines the reinforcement learner with a supervised learner. In addition, we model the influence passing between different vehicles through graph neural networks (GNNs). The proposed framework significantly improves performance in the context of navigating T-intersections compared with state-of-the-art baseline approaches., ICRA 2021

This paper presents a decentralized motion planning method for multiple aerial vehicles moving among 3-D polygonal obstacles resembling an urbanlike environment. The algorithm combines a prioritized $A^\star$ algorithm for high-level planning, along with a coordination method based on barrier functions for low-level trajectory generation and vehicle control. To this end, we extend the barrier functions method developed in our earlier work so that it treats 2-D and 3-D polygonal obstacles, and generates collision-free trajectories for the multiagent system. We furthermore augment the low-level trajectory generation and control with a prioritized $A^\star$ path planning algorithm, in order to compute waypoints and paths that force the agents of lower priority to avoid the paths of the agents of higher priority, reducing thus congestion. This feature enhances further the performance of the barrier-based coordination, and results in shorter paths and time to the goal destinations. We finally extend the proposed control design to the agents of constrained double-integrator dynamics, compared with the single-integrator case in our earlier work. We assume that the obstacles are known to the agents, and that each agent knows the state of other agents lying in its sensing area. Simulation results in 2-D and 3-D polygonal environments, as well as experimental results with micro aerial vehicles (quadrotors) in an indoor lab environment demonstrate the efficacy of the proposed approach.

A novel green-yellow emitting Ca1.5Mg0.5Si1-xLixO4-δ:Ce3+ phosphor with high quantum efficiency and thermal stability was discovered for applications in near ultraviolet pumped white light-emitting diodes. Its crystal structure was determined with a single-particle diagnosis approach. The Si sites in the SiO4 tetrahedra are reported for the first time to accommodate Li+ ions. This substitution, confirmed by 6Li solid-state NMR and T.O.F. neutron powder diffraction, causes a disordered occupation of Ca/Mg in the Ca3MgSi2O8 host and favors a phase transformation at ∼330 °C, which results in the formation of the novel phosphor. The produced phosphor was efficiently excited by near UV light peaking at 365 and 410 nm and produced broad green-yellow emission with peaks at 500 and 560 nm, respectively. Its quantum efficiency reached 88.4% (internal) and 55.7% (external) under excitation at 365 nm, and 80.5% (internal) and 42.7% (external) under excitation at 410 nm, while the decrease of luminescence intensity at 200 °C was small (∼26%). A WLED lamp with a high color rendering index of Ra = 92.8 was produced with the combination of a 365 nm emitting chip with blue emitting BaMgAl10O17:Eu2+, green-yellow emitting CMSL:0.01Ce, and red emitting Sr2Si5N8:Eu2+ phosphors.

Mn-doped transition metal perovskites have shown versatile magnetic phenomena, and research on these materials has been revived in recent decades. Many controversies over the microscopic spin configuration remain unsolved, presumably due to the complicated spin and orbit interactions, which are strongly coupled with each other and sensitive to structural and chemical modulation. Here, the Mn-doped orthochromite YCrO3 was investigated to shed some light on this issue. The orthochromite YCr1-xMnxO3 (0 ≤ x ≤ 0.6) was synthesized and studied by X-ray diffraction, magnetometry and neutron powder diffraction. For x = 0.2–0.5 samples, the Cr3+ (Mn3+) sublattice adopts a Γ4 (Gx,Ay,Fz) antiferromagnetic structure with a canted ferromagnetic component. Negative magnetization behavior is observed for the x = 0.1 and 0.2 samples, which is suppressed and reversed by the applied magnetic field. As the doping concentration further increases to x = 0.6, the system exhibits a distinct spin-glass behavior below a spin-freezing temperature. These phenomena are attributed to the competition between weakened antiferromagnetic Cr3+-Cr3+ interactions and enhanced ferromagnetic Cr3+-Mn3+ interactions with Mn3+-doping. This work provides deep insights into understanding the complicated magnetic phenomena in Mn-doped correlated transition metal oxides.

The temperature dependent magnetism of Fe-doped rare earth orthochromite HoCr 1-x Fe x O 3 (x = 0, 0.2) was investigated by neutron powder diffraction. It is found that the magnetism of Cr(Fe) 3+ can be well understood within mean field theory, while the ordering of Ho 3+ was induced by the Cr(Fe) 3+ sublattice and can be satisfyingly described by an effective S = 1/2 model. The absences of both the most common G x F z configuration of Cr 3+ and the ordering of Ho 3+ caused by Ho-Ho interaction evidence a strong Ho 3+ -Cr 3+ interaction which dominates this system. On the other hand, a remarkable magnetoelastic strain was observed accompanying the Cr(Fe) 3+ ordering. An analysis based on the equation of state with a Gruneisen approximation was performed and revealed magnetic origin of this strain.

Stochastic policy gradient methods using neural representations have had considerable success in single-agent domains with continuous action spaces. These methods typically use networks that output the parameters of a diagonal Gaussian distribution from which the resulting action is sampled. In multi-agent contexts, however, better policies may require complex multimodal action distributions. Based on recent progress in density modeling, we propose an alternative for policy representation in the form of conditional normalizing flows. This approach allows for greater flexibility in action distribution representation beyond mixture models. We demonstrate their advantage over standard methods on a set of tasks including human behavior modeling and reinforcement learning in multi-agent settings.

Sr$_2$CuTeO$_6$ is a square-lattice N��el antiferromagnet with superexchange between first-neighbor $S=1/2$ Cu spins mediated by plaquette centered Te ions. Substituting Te by W, the affected impurity plaquettes have predominantly second-neighbor interactions, thus causing local magnetic frustration. Here we report a study of Sr$_2$CuTe$_{1-x}$W$_x$O$_6$ using neutron diffraction and $��$SR techniques, showing that the N��el order vanishes already at $x = 0.025 \pm 0.005$. We explain this extreme order suppression using a two-dimensional Heisenberg spin model, demonstrating that a W-type impurity induces a deformation of the order parameter that decays with distance as $1/r^2$ at temperature $T=0$. The associated logarithmic singularity leads to loss of order for any $x>0$. Order for small $x>0$ and $T>0$ is induced by weak interplane couplings. In the nonmagnetic phase of Sr$_2$CuTe$_{1-x}$W$_x$O$_6$, the $��$SR relaxation rate exhibits quantum critical scaling with a large dynamic exponent, $z \approx 3$, consistent with a random-singlet state., 6 pages + 6 pages supplemental material

$\mathrm{F}{\mathrm{e}}_{4}\mathrm{N}{\mathrm{b}}_{2}{\mathrm{O}}_{9}$ was recently reported to be a new magnetoelectric material with two distinct dielectric anomalies located at ${T}_{N}\ensuremath{\approx}90\phantom{\rule{0.16em}{0ex}}\mathrm{K}$ for an antiferromagnetic transition and ${T}_{\mathrm{str}}\ensuremath{\approx}77\phantom{\rule{0.16em}{0ex}}\mathrm{K}$ of unknown origin, respectively. By analyzing low-temperature neutron-powder-diffraction data, here we determined its magnetic structure below ${T}_{N}$ and uncovered the origin of the second dielectric anomaly as a structural phase transition across ${T}_{\mathrm{str}}$. In the antiferromagnetically ordered state below ${T}_{N}$, both Fe1 and Fe2 magnetic moments lying within the weakly and strongly buckled honeycomb layers are arranged in a fashion that the three nearest neighbors are directed oppositely. Upon cooling below ${T}_{\mathrm{str}}$, the symmetry of crystal structure is lowered from trigonal $P\ensuremath{-}3c1$ to monoclinic $C2/c$, in which a weak sliding of the metal octahedral planes introduces a monoclinic distortion of $\ensuremath{\sim}1.{7}^{\ensuremath{\circ}}$. The magnetic structure is preserved in the low-temperature monoclinic phase, and the Fe magnetic moment increases from $2.1(1){\ensuremath{\mu}}_{B}$ at 95 K to $3.83(4){\ensuremath{\mu}}_{B}$ at 10 K assuming an equal moment configuration at Fe1 and Fe2 sites. The magnetic point group and linear magnetoelectric tensor at each temperature region are determined. From a symmetry-related tensor analysis, the microscopic origins of the magnetoelectric effects between ${T}_{N}$ and ${T}_{\mathrm{str}}$ are proved to be spin-current and $d\ensuremath{-}p$ hybridization mechanisms.

Gradient-based methods are often used for policy optimization in deep reinforcement learning, despite being vulnerable to local optima and saddle points. Although gradient-free methods (e.g., genetic algorithms or evolution strategies) help mitigate these issues, poor initialization and local optima are still concerns in highly nonconvex spaces. This paper presents a method for policy optimization based on Monte-Carlo tree search and gradient-free optimization. Our method, called Monte-Carlo tree search for policy optimization (MCTSPO), provides a better exploration-exploitation trade-off through the use of the upper confidence bound heuristic. We demonstrate improved performance on reinforcement learning tasks with deceptive or sparse reward functions compared to popular gradient-based and deep genetic algorithm baselines.

Na-ion O3-type layered oxides have attracted wide attention as cathode materials for Na-ion batteries, owing to their high compositional diversity providing tunable electrochemical performance. However, such cathodes usually suffer from monoclinic phase transitions, resulted from TMO2 (TM = transition metal) slab gliding and local distortion upon Na+ (de)intercalation, which can lead to the serious structural degradation and compromising cycling stability. Herein, a five-components O3-type layered oxide cathode, Na0.94Ni0.29Cu0.1Fe0.16Mn0.3Ti0.15O2, is designed by rationally modulating transition metals and incorporating different functionalities of multiple components. This material presents a highly reversible O3-P3 phase transition during Na+ (de)intercalation, suppressing the unfavorable monoclinic phase transformation which commonly exists in the Na-ion O3-type layered materials. As a result, this as-prepared material delivers a reversible capacity of ~ 122 mAh/g in the voltage range of 2–4.0 V with enhanced cycling stability (more than 79% of capacity retention after 300 cycles). These findings of multicomponent layered oxide cathode provide new insights into the development of structure-performance relationship for advanced Na-ion batteries.

Orthoferrite solid solution HoFe1−xCrxO3 (x=0, 0.2,…,1.0) was synthesized via solid state reaction methods. The crystal structure, magnetism and spin reorientation properties of this system were investigated by X-ray diffraction, neutron powder diffraction and magnetic measurements. For compositions of x≤0.6, the system exhibits similar magnetic properties to HoFeO3. With increasing Cr-doping, the system adopts a Γ4(GxAyFz) magnetic configuration with a decreased Neel temperature from 640 K to 360 K. A Γ42 spin reorientation of Fe(Cr)3+ was also observed in this system with an increase in transition temperature from 56 K to about 200 K due to competition between the Fe(Cr)–Fe(Cr) and Ho–Fe(Cr) interactions. For the x≥0.8, the system behaves more like HoCrO3 which adopts a Γ2(FxCyGz) configuration with no spin reorientation below the Neel temperature TN. Throughout the whole substitution range, we found that the saturated moment of Fe(Cr) was less than the ideal value for a free ion, which implies the existence of spin fluctuation in this system. A systematic magnetic structure variation with Cr-substitution is revealed by Rietveld refinement. A phase diagram combining the results of the magnetic measurements and neutron powder diffraction results was obtained.

Hard carbons as promising anode materials for Na-ion batteries (NIBs) have captured extensive attention because of their low operation voltage, easy synthesis process, and competitive specific capacity. However, there are still several disadvantages, such as high cost and low initial coulombic efficiency, which limit their large-scale commercial applications. Herein, pine nut shells (PNSs), a low-cost biomass waste, are used as precursors to prepare hard carbon materials. Via a series of washing and heat treatment procedures, a pine nut shell hard carbon (PNSHC)-1400 sample has been obtained and delivers a reversible capacity of around 300 mAh/g, a high initial coulombic efficiency of 84%, and good cycling performance. These excellent Na storage properties indicate that PNSHC is one of the most promising candidates of hard carbon anodes for NIBs.

Using pulsed laser deposition, the (0 0 1)-oriented YBa 2 Cu 3 O 7− δ (YBCO) films were epitaxially grown on BiFeO 3 (BFO) films on SrTiO 3 substrates. The YBCO/BFO heterostructure retained the ferroelectricity of BFO layer and the superconductivity of the YBCO layer. A ferroelectric hysteresis loop was observed in the BFO layer and the remnant polarization was approximately 4.6 μC/cm 2 . The fabrication of YBCO layer resulted in a c -axis decrease of BFO layer, which affected its ferroelectric properties. Especially, as increasing the thickness of BFO film, the superconducting transition width of YBCO film increased. And the c -axis of YBCO film tended towards stability at 11.7 A which ensured that all the samples were superconductive. The YBCO/BFO heterostructure could be used to fabricate YBCO Josephson junctions and the YBCO and BFO multilayers.

This paper presents a decentralized multi-agent motion planning method for aerial robots moving among 3D polygonal obstacles. The algorithm combines a prioritized A∗ algorithm for high-level (global) planning along with a barrier functions-based method for low-level (local) coordination and control. We first extend the barriers function method developed in earlier work to treat arbitrary polygonal obstacles. We then combine the prioritized A∗ algorithm to compute waypoints and paths that facilitate the performance of the barrier-based coordination and collision avoidance. We assume that the obstacles are known to the agents, and that each agent knows the state of other agents lying in its sensing area. Simulation and experimental results with quadrotors in 2D and 3D environments demonstrate the efficacy of the proposed approach.

MgB 2 thin films were prepared by ex - situ annealing of Mg/B multilayers. Different precursor, substrate and annealing condition were investigated. After annealed in a flow of Mg vapor with reducing hydrogen ambient for 1–4 min, high quality 20 nm-thick c-oriented MgB 2 thin films with T c onset = 35.6 K and critical current density J C = 2 × 10 6 A cm −2 at 30 K were obtained. The mean roughness of the 20 nm-thick film was 2.68 nm.

Vision and mission are the basis of corporate strategy (Hill and Jones, 2004). Vision, the ideal view of corporate future development (Li, 2005), is a crucial starting point for strategic management (Palmer and Short, 2008). Scholars have analyzed the importance of mission statements from a variety of perspectives (Campbell, 1997; Stone, 1996). Thus, Pearce II (1982) claimed that mission statements point out the direction of the overall sustainable corporate development, make corporate values specific, and gain approval from the public.