Mechanical rolling formation of interpenetrated lithium metal/lithium tin alloy foil for ultrahigh-rate battery anode

To achieve good rate capability of lithium metal anodes for high-energy-density batteries, one fundamental challenge is the slow lithium diffusion at the interface. Here we report an interpenetrated, three-dimensional lithium metal/lithium tin alloy nanocomposite foil realized by a simple calendering and folding process of lithium and tin foils, and spontaneous alloying reactions. The strong affinity between the metallic lithium and lithium tin alloy as mixed electronic and ionic conducting networks, and their abundant interfaces enable ultrafast charger diffusion across the entire electrode. We demonstrate that a lithium/lithium tin alloy foil electrode sustains stable lithium stripping/plating under 30mAcm(-2) and 5mAhcm(-2) with a very low overpotential of 20mV for 200 cycles in a commercial carbonate electrolyte. Cycled under 6C (6.6mAcm(-2)), a 1.0mAhcm(-2) LiNi0.6Co0.2Mn0.2O2 electrode maintains a substantial 74% of its capacity by pairing with such anode

Protective effects of asiatic acid in a spontaneous type 2 diabetic mouse model

Asiatic acid (AA) has been demonstrated to exhibit anti‑diabetic activity. However, the mechanisms and underlying signaling pathways remain to be elucidated. The present study was performed to confirm the protective effect of AA and demonstrate its ability to regulate the phosphatidylinositol 3‑kinase (PI3K)/protein kinase B (AKT)/glycogen synthase kinase‑3β (GSK‑3β) signaling pathway in db/db mice. Db/db mice fed on a high‑fat diet were used to model diabetes mellitus. Modeled mice were divided randomly into the model control, pioglitazone hydrochloride tablet (PH) and AA groups. Age‑matched C57 BL/6J mice served as normal controls

VGOS: Voxel Grid Optimization for View Synthesis from Sparse Inputs

Neural Radiance Fields (NeRF) has shown great success in novel view synthesis due to its state-of-the-art quality and flexibility. However, NeRF requires dense input views (tens to hundreds) and a long training time (hours to days) for a single scene to generate high-fidelity images. Although using the voxel grids to represent the radiance field can significantly accelerate the optimization process, we observe that for sparse inputs, the voxel grids are more prone to overfitting to the training views and will have holes and floaters, which leads to artifacts. In this paper, we propose VGOS, an approach for fast (3-5 minutes) radiance field reconstruction from sparse inputs (3-10 views) to address these issues. To improve the performance of voxel-based radiance field in sparse input scenarios, we propose two methods: (a) We introduce an incremental voxel training strategy, which prevents overfitting by suppressing the optimization of peripheral voxels in the early stage of reconstruction. (b) We use several regularization techniques to smooth the voxels, which avoids degenerate solutions. Experiments demonstrate that VGOS achieves state-of-the-art performance for sparse inputs with super-fast convergence. Code will be available at https://github.com/SJoJoK/VGOS.Comment: IJCAI 2023 Accepted (Main Track

Identification and comprehensive analyses of the CBL and CIPK gene families in wheat (Triticum aestivum L.)

The interaction analysis of wheat TaCBL and TaCIPK proteins were performed by Y2H method. (PDF 191 kb

Research progress on the impact of mineral surface roughness on particle-bubble interaction

Mineral surface roughness is an important factor affecting flotation efficiency. Surface roughness can affect the hydrophobicity of minerals, the adsorption of reagents, and the rupture of liquid films between particles and bubbles, resulting in a significant impact on the interaction process between particles and bubbles. However, there is currently a lack of systematic review work on the influence of roughness on particle-bubble interaction process. Therefore, the authors firstly reviewed the surface roughening modification techniques and roughness testing methods. Secondly, the influence of roughness on the particle-bubble interaction process was systematically discussed from four aspects: flotation kinetics, contact angle, formation time of triple-phase contact line, and interaction force between particles and bubbles. The concept of roughness scale was proposed for its importance in the research of particle-bubble interactions. Thirdly, based on the coupling mechanism between roughness scale and mineral surface hydrophobicity in the particle-bubble interaction process, the importance of mineral surface wetting state in the interaction process between rough surfaces and bubbles was emphasized. The reasons for the inconsistent research conclusions on the impact of roughness on contact angle and flotation performance were also analyzed and discussed. Finally, the conclusions were drawn through critical analysis and literature review, and the prospects for future research directions were outlined. This paper contributes to a better understanding of the influence of mineral surface roughness on the flotation process, and can provide a theoretical support for regulating mineral surface roughness to create favorable flotation conditions and improve the flotation efficiency and selectivity

Polymer flooding – Does Microscopic Displacement Efficiency Matter?

Polymer flooding is an enhanced oil recovery (EOR) technique that aims to enhance the stability of the flood front in order to increase sweep efficiency and thereby increase hydrocarbon recovery. Polymer flooding studies often focus on large-scale sweep efficiency and neglect the impact of the pore-scale displacement efficiency of the multi-phase flow. This work explores the pore-scale behavior of water vs polymer flooding, and examines the impact of rock surface wettability on the microscopic displacement efficiency using digital rock physics. In this study, a micro-CT image of a sandstone rock sample was numerically simulated for both water and polymer flooding under oil-wet and water-wet conditions. All simulations were performed at a capillary number of 1E-5, corresponding to a capillary dominated flow regime. Results of the four two-phase flow imbibition simulations are analyzed with respect to displacement character, water phase break-through, viscous/capillary fingering, and trapped oil. In the water-wet scenario, differences between water flood and polymer flood are small, with the flood front giving a piston-like displacement and breakthrough occurring at about 0.4 pore volume (PV) for both types of injected fluid. On the other hand, for the oil-wet scenario, water flood and polymer flood show significant differences. In the water flood, fingering occurs and much of the oil is bypassed early on, whereas the polymer flood displaces more oil and thereby provides better microscopic sweep efficiency throughout the flood and especially around breakthrough. Overall the results for this rock sample indicate that water flood and polymer flood provide similar recovery for a water-wet condition, while the reduced mobility ratio of polymer flood gives significantly improved recovery for an oil-wet condition by avoiding the onset of microscopic (pore-scale) fingering that occurs in the water flood. This study suggests that depending on the rock-fluid conditions, the use of polymer can impact microscopic sweep efficiency, in addition to the well-known effect on macroscopic sweep behavior.La inyección de polímeros es una técnica de recobro mejorado de petróleo (EOR) que tiene como objetivo mejorar la estabilidad del frente de inyección para aumentar la eficiencia del desplazamiento de hidrocarburos y, por lo tanto, incrementar el factor de recobro. Lo estudios de inyección de polímeros a menudo se centran en la eficiencia del desplazamiento a gran escala e ignoran el impacto de los mecanismos de desplazamiento a escala microscópica, y rara vez evalúan la variabilidad de parámetros de flujo multifásico en el medio poroso. Este trabajo explora el comportamiento del agua contra la inyección de polímeros en el medio poroso, y examina el impacto de la humectabilidad de la superficie de la roca en la eficiencia de desplazamiento microscópico, utilizando tomografía computarizada de rayos X en muestras de roca. En este estudio, se simuló numéricamente una imagen de microtomografía computarizada de una muestra de roca arenisca, para un proceso de inyección de agua y polímeros en condiciones de mojabilidad al aceite y al agua. Todas las simulaciones se realizaron a un número capilar de 1E-5, correspondiente a un régimen de flujo dominado por fuerzas capilares y que es típico del flujo en yacimientos de hidrocarburos. Los resultados de las cuatro simulaciones de imbibición de flujo de dos fases se analizan con respecto al carácter desplazante, el avance de la fase acuosa, la digitación viscosa y capilar, y el aceite atrapado. En el escenario de mojabilidad al agua, las diferencias entre la inyección de agua y la inyección de polímeros son pequeñas, dado que el frente de inyección produce un  desplazamiento en forma de pistón y un avance que se produce a aproximadamente 0,4 volúmenes porosos para ambos tipos de fluido inyectado. Por otro lado, para el escenario de mojabilidad al petróleo, la inyección de agua y la inyección de polímeros muestran diferencias significativas. En la inyección de agua, se produce digitación y gran parte del petróleo se pasa por alto al principio; mientras que la inyección de polímeros desplaza más aceite y, por lo tanto, proporciona una mejor eficiencia de desplazamiento microscópico durante la inyección, especialmente alrededor de la ruptura. En general, los resultados para esta muestra de roca indican que la inyección de agua y la inyección de polímeros proporcionan un efecto de recobro similar para una condición de mojabilidad al agua, mientras que la relación de movilidad reducida de la inyección de polímeros proporciona un efecto de recobro significativamente mejorado para una condición de mojabilidad al aceite, al evitar la aparición de digitación microscópica (a escala de poro) que se produce en la inyección de agua. Este estudio sugiere que, dependiendo de las condiciones roca-fluido, el uso del polímero puede impactar la eficiencia de desplazamiento microscópico, además del efecto conocido sobre el comportamiento del desplazamiento macroscópico

Deep learning driven real time topology optimisation based on initial stress learning

Topology optimisation can facilitate engineers in proposing efficient and novel conceptual design schemes, but the traditional FEM based optimization demands significant computing power and makes the real time optimization impossible. Based on the convolutional neural network (CNN) method, a new deep learning approximate algorithm for real time topology optimisation is proposed. The algorithm learns from the initial stress (LIS), which is defined as the major principal stress matrix obtained from finite element analysis in the first iteration of classical topology optimisation. The initial major principal stress matrix of the structure is used to replace the load cases and boundary conditions of the structure as independent variables, which can produce topological prediction results with high accuracy based on a relatively small number of samples. Compared with the traditional topology optimisation method, the new method can produce a similar result in real time without repeated iterations. A classic short cantilever problem was used as an example, and the optimized topology of the cantilever structure is predicted successfully by the established approximate algorithm. By comparing the prediction results to the structural optimisation results obtained by the classical topology optimisation method, it is discovered that the two results are highly approximate, which verifies the validity of the established algorithm. Furthermore, a new algorithm evaluation method is proposed to evaluate the effects of using different methods to select samples on the prediction performance of the optimized topology, and the results were promising and concluded in the end