Effect of Ionic Liquids with Different Structures on Rheological Properties of Water-Based Drilling Fluids and Mechanism Research at Ultra-High Temperatures.

The rheology control of water-based drilling fluids at ultra-high temperatures has been one of the major challenges in deep or ultra-deep resource exploration. In this paper, the effects of 1-ethyl-3-methylimidazolium bis(trifluoromethanesulfonimide) (ILA), 1-ethyl-3-methylimidazolium tetrafluoroborate (ILB) and N-methyl, butylpyrrolidinium bis(trifluoromethanesulfonimide) (ILC) on the rheological properties and filtration loss of polymer-based slurries at ultra-high temperatures (200 °C and 240 °C) are investigated by the American Petroleum Institute (API) standards. The results show that ionic liquids with different structures could improve the high-temperature rheological properties of polymer-based drilling fluids. The rheological parameter value (YP/PV) of the polymer-based slurry formulated with ILC is slightly higher than that with ILA at the same concentration, while the YP/PV value of the polymer-based slurry with ILA is slightly higher than that with ILB, which is consistent with the TGA thermal stability of ILA, ILB, and ILC; the thermal stability of ILC with pyrrolidine cations is higher than that of ILA with imidazole cations, and the thermal stability of ILA with bis(trifluorosulfonyl)amide anions is higher than that of ILB with tetrafluoroborate anions. Cation interlayer exchange between organic cation and sodium montmorillonite can improve the rheological properties of water-based drilling fluids. And meantime, the S=O bond in bis(trifluorosulfonyl)amide ions and the hydroxyl group of sodium montmorillonite may form hydrogen bonds, which also may increase the rheological properties of water-based drilling fluids. ILA, ILB, and ILC cannot reduce the filtration loss of polymer-based drilling fluids at ultra-high temperatures.

Palladium-Catalyzed Asymmetric Hydrogenation of Unprotected 3-Substituted Indoles.

A palladium-catalyzed asymmetric hydrogenation of unprotected 3-substituted indoles was developed, providing a series of 3-substituted indolines in excellent yields with ≤94.4:5.6 er. The large sterically hindered bisphosphine ligand played a crucial role in the enantioselective control. In addition, the gram-scale hydrogenation experiment and product derivatizations were performed successfully.

Kinetic Resolution of [2.2]Paracyclophane-Derived Cyclic N-Sulfonylimines via Palladium-Catalyzed Addition of Arylboronic Acids.

A facile method for kinetic resolution of [2.2]paracyclophane-derived cyclic N-sulfonylimines based on palladium-catalyzed addition of arylboronic acids was developed, giving two kinds of planar chiral [2.2]paracyclophane derivatives in excellent diastereoselectivities and up to 99% of enantioselectivities with high selectivity factors (s up to 128).

High-precision fiber Bragg gratings inscription by infrared femtosecond laser direct-writing method assisted with image recognition.

For achieving high efficiency fiber Bragg gratings (FBGs) utilizing infrared femtosecond laser point-by-point inscription method, it is crucial to make the inscribed periodic structure perfectly in phase. It requires a perfect alignment between the micrometer-sized laser spot with the fiber along the length. Here we report the highly precise fabrication of FBGs by infrared femtosecond laser point-by-point direct-writing method. Image recognition technique is applied to for automatically aligning the trace of the laser spot with the referenced central axis of the fiber along the whole FBG length. FBGs inscription with high spatial precision is confirmed by multiple approaches, including microscopic photographing and FBG spectroscopic measurement. 50 mm-long uniform FBGs with high reflectivity have been successfully demonstrated in a small-core single-mode silica fiber using auto-aligning technique.

Nickel(0)-Catalyzed Enantioselective [3+2] Annulation of Cyclopropenones and α,ß-Unsaturated Ketones/Imines.

Ni0 -catalyzed chemo- and enantioselective [3+2] cycloaddition of cyclopropenones and α,ß-unsaturated ketones/imines is described. This reaction integrates C-C bond cleavage of cyclopropenones and enantioselective functionalization by carbonyl/imine group, offering a mild approach to γ-alkenyl butenolides and lactams in excellent enantioselectivity (88-98 % ee) through intermolecular C-C activation.

Manganese Pentacarbonyl Bromide as Regeneration Catalyst Enabled Biomimetic Asymmetric Reduction.

Using readily available manganese pentacarbonyl bromide as a regeneration catalyst, biomimetic asymmetric reduction of imines including quinoxalinones, benzoxazinones, and benzoxazine has been successfully developed in the presence of transfer catalyst chiral phosphoric acids, providing the chiral amines with high yields and enantioselectivities.

Multiprior Learning via Neural Architecture Search for Blind Face Restoration.

Blind face restoration (BFR) aims to recover high-quality (HQ) face images from low-quality (LQ) ones and usually resorts to facial priors for improving restoration performance. However, current methods still suffer from two major difficulties: 1) how to derive a powerful network architecture without extensive hand tuning and 2) how to capture complementary information from multiple facial priors in one network to improve restoration performance. To this end, we propose a face restoration searching network (FRSNet) to adaptively search the suitable feature extraction architecture within our specified search space, which can directly contribute to the restoration quality. On the basis of FRSNet, we further design our multiple facial prior searching network (MFPSNet) with a multiprior learning scheme. MFPSNet optimally extracts information from diverse facial priors and fuses the information into image features, ensuring that both external guidance and internal features are reserved. In this way, MFPSNet takes full advantage of semantic-level (parsing maps), geometric-level (facial heat maps), reference-level (facial dictionaries), and pixel-level (degraded images) information and, thus, generates faithful and realistic images. Quantitative and qualitative experiments show that the MFPSNet performs favorably on both synthetic and real-world datasets against the state-of-the-art (SOTA) BFR methods. The codes are publicly available at: https://github.com/YYJ1anG/MFPSNet.

Shear Performance of Epoxy Joints in a Precast Bridge Deck Considering Constraint Effects.

The joint form plays a vital role in the rapid assembly of precast bridge decks for steel-concrete composite bridges. Existing research primarily focuses on studying the shear performance of joints through direct shear tests, which is insufficient to fully reflect the mechanical behavior of joints under the constraint of prefabricated bridge deck panels during actual vehicular traffic. Considering situations such as vehicle loads and external forces acting on precast bridge decks, this study investigates the shear performance of epoxy joints under constraint through an improved shear test. The influence of constraint force, shear key details and interface defects on the shear performance of epoxy joints is investigated. The results reveal that the shear test method employed in this study can realistically reflect the shear performance of epoxy joints in precast bridge decks. Both active and passive constrained epoxy joint specimens exhibited no interface cracks, and their failure modes were identified as shear failure between mid-span supports. Compared with passive constraint, the shear-bearing capacity of epoxy joint specimens under active constraint was increased by 86.1~130.6%. Among the epoxy joint specimens with depth-height ratios of 15/110, 25/110, 35/110 and 45/110, the joint with a depth of 35 mm demonstrated the highest shear strength. Furthermore, the shear performance of epoxy joints significantly deteriorated when the interface defects exceeded 30%, resulting in the failure mode transforming from shear failure to interface failure.

Deep Dense Multi-Scale Network for Snow Removal Using Semantic and Depth Priors.

Images captured in snowy days suffer from noticeable degradation of scene visibility, which degenerates the performance of current vision-based intelligent systems. Removing snow from images thus is an important topic in computer vision. In this paper, we propose a Deep Dense Multi-Scale Network (DDMSNet) for snow removal by exploiting semantic and depth priors. As images captured in outdoor often share similar scenes and their visibility varies with depth from camera, such semantic and depth information provides a strong prior for snowy image restoration. We incorporate the semantic and depth maps as input and learn the semantic-aware and geometry-aware representation to remove snow. In particular, we first create a coarse network to remove snow from the input images. Then, the coarsely desnowed images are fed into another network to obtain the semantic and depth labels. Finally, we design a DDMSNet to learn semantic-aware and geometry-aware representation via a self-attention mechanism to produce the final clean images. Experiments evaluated on public synthetic and real-world snowy images verify the superiority of the proposed method, offering better results both quantitatively and qualitatively. https://github.com/HDCVLab/Deep-Dense-Multi-scale-Network https://github.com/HDCVLab/Deep-Dense-Multi-scale-Network.

Visible-Light-Induced Oxidation/[3 + 2] Cycloaddition/Oxidative Aromatization to Construct Benzo[a]carbazoles from 1,2,3,4-Tetrahydronaphthalene and Arylhydrazine Hydrochlorides.

An efficient synthesis of benzo[a]carbazoles via visible-light-induced tandem oxidation/[3 + 2] cycloaddition/oxidative aromatization reactions was reported. The benzylic C(sp3)-H of tetrahydronaphthalene was activated through visible-light photoredox catalyst with oxygen as the clean oxidant under mild reaction conditions. This protocol proceeds efficiently with broad substrate scope, and the mechanism study was performed.