Nano-additive manufacturing of multilevel strengthened aluminum matrix composites

Nanostructured materials are being actively developed, while it remains an open question how to rapidly scale them up to bulk engineering materials for broad industrial applications. This study propose an industrial approach to rapidly fabricate high-strength large-size nanostructured metal matrix composites and attempts to investigate and optimize the deposition process and strengthening mechanism. Here, advanced nanocrystalline aluminum matrix composites (nanoAMCs) were assembled for the first time by a novel nano-additive manufacturing method that was guided by numerical simulations (i.e. the in-flight particle model and the porefree deposition model). The present nanoAMC with a mean grain size <50 nm in matrix exhibited hardness eight times higher than the bulk aluminum and shows the highest hardness among all Al–Al2O3 composites reported to date in the literature, which are the outcome of controlling multiscale strengthening mechanisms from tailoring solution atoms, dislocations, grain boundaries, precipitates, and externally introduced reinforcing particles. The present high-throughput strategy and method can be extended to design and architect advanced coatings or bulk materials in a highly efficient (synthesizing a nanostructured bulk with dimensions of 50 × 20 × 4 mm3 in 9 min) and highly flexible (regulating the gradient microstructures in bulk) way, which is conducive to industrial production and application

FISEdit: Accelerating Text-to-image Editing via Cache-enabled Sparse Diffusion Inference

Due to the recent success of diffusion models, text-to-image generation is becoming increasingly popular and achieves a wide range of applications. Among them, text-to-image editing, or continuous text-to-image generation, attracts lots of attention and can potentially improve the quality of generated images. It's common to see that users may want to slightly edit the generated image by making minor modifications to their input textual descriptions for several rounds of diffusion inference. However, such an image editing process suffers from the low inference efficiency of many existing diffusion models even using GPU accelerators. To solve this problem, we introduce Fast Image Semantically Edit (FISEdit), a cached-enabled sparse diffusion model inference engine for efficient text-to-image editing. The key intuition behind our approach is to utilize the semantic mapping between the minor modifications on the input text and the affected regions on the output image. For each text editing step, FISEdit can automatically identify the affected image regions and utilize the cached unchanged regions' feature map to accelerate the inference process. Extensive empirical results show that FISEdit can be $3.4\times$ and $4.4\times$ faster than existing methods on NVIDIA TITAN RTX and A100 GPUs respectively, and even generates more satisfactory images.Comment: 12 pages, 7 figure

Construction of Nahm data and BPS monopoles with continuous symmetries

We study solutions to Nahm's equations with continuous symmetries and, under certain (mild) hypotheses, we classify the corresponding Ans\"atze. Using our classification, we construct novel Nahm data, and prescribe methods for generating further solutions. Finally, we use these results to construct new BPS monopoles with spherical symmetry.Comment: 36 pages, 1 table, 2 figures. Submitted version. Comments are welcome

Copula approach to exchange-correlation hole in many-electron systems with strong correlations

Electronic correlation is a fundamental topic in many-electron systems. To characterize this correlation, one may introduce the concept of exchange-correlation hole. In this paper, we first briefly revisit its definition and relation to electron and geminal densities, followed by their intimate relations to copula functions in probability theory and statistics. We then propose a copula-based approach to estimate the exchange-correlation hole from the electron density. It is anticipated that the proposed scheme would become a promising ingredient towards the future development of strongly correlated electronic structure calculations.Comment: 5 page

Lithium niobate-enhanced laser photoacoustic spectroscopy

In this paper, the photoacoustic spectroscopy technique based on lithium niobate crystals is initially reported, to our knowledge. A novel dual-cantilever tuning fork structure and new electrodes have been designed using Y-cut 128{\deg} blackened lithium niobate wafers. The tuning fork, with a resonant frequency of only 10.46 kHz and a prong gap of 1 mm, is engineered to achieve superior performance in photoacoustic spectroscopy. In the demonstration experiment, acetylene was detected using a 1.53 um semiconductor laser, achieving a detection limit of about 9 ppb within a one-second integration time.Comment: 8 pages, 4 figure