Effects of Hf, B, Cr and Zr alloying on mechanical properties and oxidation resistance of Nb-Si based ultrahigh temperature alloy

Multi-component Nb-Si based ultrahigh temperature alloys were prepared by vacuum non-consumable arc melting. The effects of Hf, B, Zr and Cr alloying on the phase selection, phase stability, both non-equilibrium and equilibrium microstructure, room-temperature fracture toughness, hardness and oxidation resistance at 1250 oC of the alloys have been investigated and estimated systematically. The results show that the addition of B or Cr promotes the formation of hypereutectic structures. The alloying with both Hf and B suppresses the formation of β(Nb,X)5Si3 and promotes the formation of α(Nb,X)5Si3 and γ(Nb,X)5Si3, while the alloying with Cr has no effect on the crystal structures of 5-3 silicides. The room-temperature fracture toughness of the alloys is always degraded by the addition of Cr but almost not influenced by the combined additions of Hf and B. The hardness of 5-3 silicides exhibits a tendency of γ \u3e α \u3e β. The macrohardness of the alloys increases with Cr addition, and it obviously reduces in the presence of Hf after 1450 oC/50 h heat-treatment. The best oxidation-resistant performance has been obtained for the alloy with both B and Cr additions. However, in the presence of B and/or Cr, the oxidation resistance of the alloys has been degraded by further addition of Hf. Both sizes and amounts of primary γ-(Nb, X)5Si3 increase with Zr contents in the alloy. Both adhesion and compactness of the scales are improved effectively by increase in Zr content. The mass gain and thickness of the scale decrease with increase in Zr contents, indicating that Zr addition can improve the oxidation resistance of the alloys significantly. Please click Additional Files below to see the full abstract

Energy scaling law for nanostructured materials

The equilibrium binding energy is an important factor in the design of materials and devices. However, it presents great computational challenges for materials built up from nanostructures. Here we investigate the binding-energy scaling law from first-principles calculations. We show that the equilibrium binding energy per atom between identical nanostructures can scale up or down with nanostructure size. From the energy scaling law, we predict finite large-size limits of binding energy per atom. We find that there are two competing factors in the determination of the binding energy: Nonadditivities of van der Waals coefficients and center-to-center distance between nanostructures. To uncode the detail, the nonadditivity of the static multipole polarizability is investigated. We find that the higher-order multipole polarizability displays ultra-strong intrinsic nonadditivity, no matter if the dipole polarizability is additive or not.Comment: 13 pages, 4 figures, 7 table

Role of sea quarks in the nucleon transverse spin

We present a phenomenological extraction of transversity distribution functions and Collins fragmentation functions by simultaneously fitting to semi-inclusive deep inelastic scattering and electron-positron annihilation data. The analysis is performed within the transverse momentum dependent factorization formalism, and sea quark transversity distributions are taken into account for the first time. We find the $\bar u$ quark favors a negative transversity distribution while that of the $\bar d$ quark is consistent with zero according to the current accuracy. In addition, based on a combined analysis of world data and simulated data, we quantitatively demonstrate the impact of the proposed Electron-ion Collider in China on precise determinations of the transversity distributions, especially for sea quarks, and the Collins fragmentation functions

Preference-aware task assignment in on-demand taxi dispatching: An online stable matching approach

A central issue in on-demand taxi dispatching platforms is task assignment, which designs matching policies among dynamically arrived drivers (workers) and passengers (tasks). Previous matching policies maximize the profit of the platform without considering the preferences of workers and tasks (e.g., workers may prefer high-rewarding tasks while tasks may prefer nearby workers). Such ignorance of preferences impairs user experience and will decrease the profit of the platform in the long run. To address this problem, we propose preference-aware task assignment using online stable matching. Specifically, we define a new model, Online Stable Matching under Known Identical Independent Distributions (OSM-KIID). It not only maximizes the expected total profits (OBJ-1), but also tries to satisfy the preferences among workers and tasks by minimizing the expected total number of blocking pairs (OBJ-2). The model also features a practical arrival assumption validated on real-world dataset. Furthermore, we present a linear program based online algorithm LP-ALG, which achieves an online ratio of at least 1−1/e on OBJ-1 and has at most 0.6·|E| blocking pairs expectedly, where |E| is the total number of edges in the compatible graph. We also show that a natural Greedy can have an arbitrarily bad performance on OBJ-1 while maintaining around 0.5·|E| blocking pairs. Evaluations on both synthetic and real datasets confirm our theoretical analysis and demonstrate that LP-ALG strictly dominates all the baselines on both objectives when tasks notably outnumber workers

Halogen (F, Cl) concentrations and Sr-Nd-Pb-B isotopes of the basaltic andesites from the southern Okinawa Trough: implications for the recycling of subducted serpentinites

Author Posting. © American Geophysical Union, 2021. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research: Solid Earth 126(3), (2021): e2021JB021709, https://doi.org/10.1029/2021JB021709.Serpentinites are increasingly recognized as playing an important role in the global geochemical cycle. However, discriminating the contributions of serpentinites to arc magmas from those of other subduction components is challenging. The Okinawa Trough is a back-arc basin developed behind the Ryukyu subduction zone, where magmas are extensively affected by sediment subduction. In this study, we reported the F-Cl concentrations and Sr-Nd-Pb-B isotopes of basaltic andesites from the Yaeyama Graben, Yonaguni Graben, and Irabu Knoll in the southern Okinawa Trough. The Irabu Knoll lavas show the most enrichment of fluid-mobile elements and F ± Cl, and have the heaviest B isotopes (δ11B: +6.6 ± 1.5‰). They also have decoupled Sr-Nd isotopes: higher 87Sr/86Sr (∼0.7049) but have no obvious decrease of 143Nd/144Nd (∼0.5128). Results from slab dehydration modeling and mixing calculations suggest that the heavy δ11B in the Irabu Knoll lavas is not consistent with fluids derived from altered oceanic crust (AOC), sediments, or wedge serpentinites (formed in the mantle wedge), but rather from slab serpentinites (formed within the subducting plate); sediments control the subduction input of Nd, whereas the decoupled Sr-Nd isotopes are most likely due to the excess radiogenic Sr carried by AOC fluids. Our results imply that recycling of serpentinite fluids and AOC fluids are usually coupled in subduction zones, as the arc lavas influenced by subducted serpentinite generally show Sr-Nd isotopes decoupling. The large variation of Sr-Nd-B isotopes observed in a relatively localized area is consistent with a focused migration through the mantle wedge of components from multiple sources.This study was funded by the National Natural Science Foundation of China (91958213), the Strategic Priority Research Program of the Chinese Academy of Sciences (XDB42020402), the China Postdoctoral Science Foundation (2019M662454), the Shandong Provincial Natural Science Foundation, China (ZR2020QD068 and ZR2020MD068), the International Partnership Program of the Chinese Academy of Sciences (133137KYSB20170003), the Special Fund for the Taishan Scholar Program of Shandong Province (ts201511061), and the China Scholarship Council (201709410550).2021-09-1

Preserving Knowledge Invariance: Rethinking Robustness Evaluation of Open Information Extraction

The robustness to distribution changes ensures that NLP models can be successfully applied in the realistic world, especially for information extraction tasks. However, most prior evaluation benchmarks have been devoted to validating pairwise matching correctness, ignoring the crucial measurement of robustness. In this paper, we present the first benchmark that simulates the evaluation of open information extraction models in the real world, where the syntactic and expressive distributions under the same knowledge meaning may drift variously. We design and annotate a large-scale testbed in which each example is a knowledge-invariant clique that consists of sentences with structured knowledge of the same meaning but with different syntactic and expressive forms. By further elaborating the robustness metric, a model is judged to be robust if its performance is consistently accurate on the overall cliques. We perform experiments on typical models published in the last decade as well as a popular large language model, the results show that the existing successful models exhibit a frustrating degradation, with a maximum drop of 23.43 F1 score. Our resources and code are available at https://github.com/qijimrc/ROBUST.Comment: Accepted by EMNLP 2023 Main Conferenc