Heterogeneity in supraglacial debris thickness and its role in glacier mass changes of the Mount Gongga

在西藏的高原，许多冰河在他们的脱离地区有 supraglacial 碎片的广泛的封面，它由改变冰融化和集体损失的空间模式影响冰河反应到气候变化。不够的碎片厚度数据使分析地区性的碎片封面效果困难。山 Gongga 的海上的冰河被实质的减小在最近的十年在冰河区域和冰质量描绘了。从遥远地察觉到的数据估计的碎片层的热性质表明盖住碎片的冰河在这个区域，到全部的冰河区域的碎片盖子的比例从 1.74% ～ 53.0% 在上变化是主导的。用一个身体上基于的碎片封面效果评价模型，我们发现尽管 supraglacial 碎片的存在在重重地盖住碎片的冰河上有重要绝缘效果，融化在~上加速冰10.2%全部的脱离地区并且生产~的快速的消耗量25%盖住碎片的冰河，导致在盖住碎片、没有碎片的冰河之间的类似的集体损失。普遍碎片盖子也便于活跃终点区域的发展。在碎片封面效果的地区性的差别是明显的，强调为冰河质量在全世界在西藏的高原和另外的山脉改变的理解的碎片盖子的重要性。

Insights into the efficiency and stability of Cu-based nanowires for electrocatalytic oxygen evolution

Copper oxide nanowires with varying oxidation states are prepared and their activity for water oxidation is studied. The nanowires with a CuO phase are found to be the most active, and their degree of crystallinity is important in achieving efficient water oxidation. For the crystalline CuO nanowires in a weakly basic Na2CO3 electrolyte, a Tafel slope of 41 mV/decade, an overpotential of approximately 500 mV at - 10 mA/crn2 （without compensation for the solution resistance）, and a faradaic efficiency of nearly 100% are obtained. This electrode maintains a stable current for over 15 lx The low overpotential of 500 mV at 10 mA/cm2, small Tafel slope, long-term stability, and low cost make CuO one of the most promising catalysts for water oxidation. Moreover, the evolution of the CuO nanowire morphology over time is studied by electron microscop）-revealing that the diffusion of Cu ions from the interior of the nanowires to their surface causes the aggregation of individual nanowires over time. However, despite this aggregation, the current density remains nearly constant, because the total electrochemically active surface area of CuO does not change.

Robust combined modeling of crystalline and amorphous silicon grain boundary conductance by machine learning

Knowledge in thermal and electric transport through grain boundary(GB)is crucial for designing nanostructured thermoelectric materials,where the transport greatly depends on GB atomistic structure.In this work,we employ machine learning(ML)techniques to study the relationship between silicon GB structure and its thermal and electric boundary conductance(TBC and EBC)calculated by Green’s function methods.We present a robust ML prediction model of TBC covering crystalline–crystalline and crystalline–amorphous interfaces,using disorder descriptors and atomic density.We also construct high-accuracy ML models for predicting both TBC and EBC and their ratio,using only small data of crystalline GBs.We found that the variations of interatomic angles and distance at GB are the most predictive descriptors for TBC and EBC,respectively.These results demonstrate the robustness of the black-box model and open the way to decouple thermal and electrical conductance,which is a key physical problem with engineering needs.

Analysis of molten metal spreading and solidification behaviors utilizing moving particle full-implicit method

To retrieve the fuel debris in Fukushima Daiichi Nuclear Power Plants(1F),it is essential to infer the fuel debris distribution.In particular,the molten metal spreading behavior is one of the vital phenomena in nuclear severe accidents because it determines the initial condition for further accident scenarios such as molten core concrete interaction(MCCI).In this study,the fundamental molten metal spreading experiments were performed with different outlet diameters and sample amounts to investigate the effect of the outlet for spreading-solidification behavior.In the numerical analysis,the moving particle full-implicit method(MPFI),which is one of the particle methods,was applied to simulate the spreading experiments.In the MPFI framework,the melting-solidification model including heat transfer,radiation heat loss,phase change,and solid fraction-dependent viscosity was developed and implemented.In addition,the difference in the spreading and solidification behavior due to the outlet diameters was reproduced in the calculation.The simulation results reveal the detailed solidification procedure during the molten metal spreading.It is found that the viscosity change and the solid fraction change during the spreading are key factors for the free surface condition and solidified materials.Overall,it is suggested that the MPFI method has the potential to simulate the actual nuclear melt-down phenomena in the future.

Efficient visible-light-driven water oxidation by single-crystal Ta_(3)N_(5)nanoparticles

Ta3N5 is regarded as a promising photocatalyst for solar water splitting because of its excellent visible light absorption characteristics and simple composition.Conventional Ta3N5 photocatalysts prepared from oxide precursors typically comprise aggregated polycrystalline particles with defects and grain boundaries that reduce the water oxidation activity of the material.In the present work,well-dispersed Ta3N5 nanoparticulate single crystals were synthesized via a mild nitridation process using pure Ta metal nanopowder or Ta nanopowder mixed with NaCl.The resulting high-quality Ta3N5 nanoparticles,after loading with an oxygen evolution cocatalyst,exhibited impressively high photocatalytic performance during O_(2)evolution from a sacrificial AgNO3 solution,with an apparent quantum yield of 9.4%at 420 nm.Our findings suggest a new approach to the facile fabrication of nanostructured single-crystal photocatalysts for efficient solar water splitting,based on the use of metal nanopowders.

Shedding new light on the dislocation-mediated plasticity in wurtzite ZnO single crystals by photoindentation

Dislocation-mediated plasticity in inorganic semiconductors and oxides has attracted increasing research interest because of the promising mechanical and functional properties tuned by dislocations.In this study,we investigated the effects of light illumination on the dislocation-mediated plasticity in hexagonal wurtzite ZnO,a representative third-generation semiconductor material.A(0001)45o off sample was specially designed to preferentially activate the basal slip on(0001)plane.Three types of nanoindentation tests were performed under four different light conditions(550 nm,334 nm,405 nm,and darkness),including low-load(60μN)pop-in tests,high-load(500μN)nanoindentation tests,and nanoindentation creep tests.The maximum shear stresses at pop-in were found to approximate the theoretical shear strength regardless of the light conditions.The activation volume at pop-ins was calculated to be larger in light than in darkness.Cross-sectional transmission electron microscope images taken from beneath the indentation imprints showed that all indentation-induced dislocations were located beneath the indentation imprint in a thin-plate shape along one basal slip plane.These indentation-induced dislocations could spread much deeper in darkness than in light,revealing the suppressive effect of light on dislocation behavior.An analytical model was adopted to estimate the elastoplastic stress field beneath the indenter.It was found that dislocation glide ceased at a higher stress level in light,indicating the increase in the Peierls barrier under light illumination.Furthermore,nanoindentation creep tests showed the suppression of both indentation depth and creep rate by light.Nanoindentation creep also yielded a larger activation volume in light than in darkness.

RadonPy:automated physical property calculation using all-atom classical molecular dynamics simulations for polymer informatics

The spread of data-driven materials research has increased the need for systematically designed materials property databases.However,the development of polymer databases has lagged far behind other material systems.We present RadonPy,an open-source library that can automate the complete process of all-atom classical molecular dynamics(MD)simulations applicable to a wide variety of polymeric materials.Herein,15 different properties were calculated for more than 1000 amorphous polymers.The MD-calculated properties were systematically compared with experimental data to validate the calculation conditions;the bias and variance in the MD-calculated properties were successfully calibrated by a machine learning technique.During the high-throughput data production,we identified eight amorphous polymers with extremely high thermal conductivity(>0.4 W∙m^(–1)∙K^(–1))and their underlying mechanisms.Similar to the advancement of materials informatics since the advent of computational property databases for inorganic crystals,database construction using RadonPy will promote the development of polymer informatics.