The development of sapphire slurry follows the requirements of environmental friendliness, low cost and high efficiency. Therefore, the effects of KOH, aminomethyl propanol (AMP) and arginine (ARG) ...as pH regulators on the chemical mechanical polishing (CMP) performance of C-, A- and R-plane sapphire were investigated. The results showed that ARG was the most effective, which could increase the removal rates of C-, A- and R-plane sapphire to 5.65 µm/h, 2.80 µm/h and 3.59 µm/h, and reduce the surface roughness Sq to 0.194 nm, 0.161 nm and 0.173 nm, respectively. Mechanical action analysis, XPS, UV-Vis, and theoretical calculations revealed that ARG could improve the mechanical action of CMP and chemical action by acting as a complexing agent to complex with AlOH4−.
•Combination of experiments and theoretical calculations.•A comprehensive study of pH regulators in terms of mechanical and chemical action.•Organic base ARG is a multi-purpose agent that simplifies slurry components.
Deep learning has achieved a preliminary success in image compression due to the ability to learn the nonlinear spaces with compact features that training samples belong to. Unfortunately, it is not ...straightforward for the network based image compression methods to code multiple highly related images. In this paper, we propose a co-prediction based image compression (CPIC) which uses the multi-stream autoencoders to collaboratively code the multiple highly correlated images by enforcing the co-reference constraint on the multi-stream features. Patch samples fed into the multi-stream autoencoder, are generated through corresponding patch matching under permutation, which helps the autoencoder to learn the relationship among corresponding patches from the correlated images. Each stream network consists of encoder, decoder, importance map network and binarizer. In order to guide the allocation of local bit rate of the binary features, the important map network is employed to guarantee the compactness of learned features. A proxy function is used to make the binary operation for the code layer of the autoencoder differentiable. Finally, the network optimization is formulated as a rate distortion optimization. Experimental results prove that the proposed compression method outperforms JPEG2000 up to 1.5 dB in terms of PSNR.
PPy/PANI double-layer nanotubes anchored reduced graphene oxide (rGO) nanosheets with three-dimensional architecture (3DGP) have been obtained for supercapacitors applications. The freestanding ...electrode yields specific capacitance (542 F g
−1
at current density of 1 A/g) and excellent cycle stability (92.1% capacitance retention after 2000 cycles in a three-electrode cell configuration). The further assembled symmetric supercapacitor device exhibits a high energy density of 20.8 W h kg
−1
at a power density of 250 W kg
−1
and good cycle stability (capacitance loss of 7% up to 2000 cycles). The exceptional electrochemical performance of 3DGP can be ascribed to the unique structure and the synergistic effects of the components: (1) Integrating the highly capacitance matrix PPy/PANI coaxial nanotubes hybrid in rGO to enhance the reversible faradic reactions can boost the utilization rate of the electrode materials and circumventing the predicament of pseudo materials. (2) The desirable
π
–
π
interactions between highly conductive rGO films and polymer chains construct a high-performance network, which facilitates rapid transport of the electrolyte ions in the electrode. (3) The as-prepared electrode materials fabricated into electrodes directly decrease the “dead weight,” for the addition of binder and conductive agents can be avoided.
The edge information plays a key role in the restoration of a depth map. Most conventional methods assume that the color image and depth map are consistent in edge areas. However, complex texture ...regions in the color image do not match exactly with edges in the depth map. In this paper, firstly, we point out that in most cases the consistency between normal map and depth map is much higher than that between RGB-D pairs. Then we propose a dual normal-depth regularization term to guide the restoration of depth map, which constrains the edge consistency between normal map and depth map back and forth. Moreover, considering the bimodal characteristic of weight distribution that exists in depth discontinuous areas, a reweighted graph Laplacian regularizer is proposed to promote this bimodal characteristic. And this regularization is incorporated into a unified optimization framework to effectively protect the piece-wise smoothness(PWS) characteristics of depth map. By treating depth image as graph signal, the weight between two nodes is adapted according to its content. The proposed method is tested for both noise-free and noisy cases, and is compared against the state-of-the-art methods on both synthesis and real captured datasets. Extensive experimental results demonstrate the superior performance of our method compared with most state-of-the-art works in terms of both objective and subjective quality evaluations. Specifically, our method is more effective on edge areas and more robust to noises.
3D depth cameras have become more and more popular in recent years. However, depth maps captured by these cameras can hardly be used in 3D reconstruction directly because they often suffer from low ...resolution and blurring depth discontinuities. Super resolution of depth maps is necessary. In depth maps, the edge areas play more important role and demonstrate distinct geometry directions compared with natural images. However, most existing super-resolution methods ignore this fact, and they can not handle depth edges properly. Motivated by this, we propose a compound method that combines multi-direction dictionary sparse representation and autoregressive (AR) models, so that the depth edges are presented precisely at different levels. In the patch level, the depth edge patches with geometry directions are well represented by the pre-trained multi-directional dictionaries. Compared with a universal dictionary, multiple dictionaries trained from different directional patches can represent the directional depth patch much better. In the finer pixel level, we utilize an adaptive AR model to represent the local correlation patterns in small areas. Extensive experimental results on both synthetic and real datasets demonstrate that, the proposed model outperforms state-of-the-art depth map super-resolution methods in terms of both quantitative metrics and subjective visual quality.
Guided depth map super-resolution (GDSR) is one of the mainstream methods in depth map super-resolution, as high-resolution color images can guide the reconstruction of the depth maps and are often ...easy to obtain. However, how to make full use of extracted guidance information of the color image to improve the depth map reconstruction remains a challenging problem. In this paper, we first design a multi-scale feedback module (MF) that extracts multi-scale features and alleviates the information loss in network propagation. We further propose a novel multi-scale feedback network (MSF-Net) for guided depth map super-resolution, which can better extract and refine the features by sequentially joining MF blocks. Specifically, our MF block uses parallel sampling layers and feedback links between multiple time steps to better learn information at different scales. Moreover, an inter-scale attention module (IA) is proposed to adaptively select and fuse important features at different scales. Meanwhile, depth features and corresponding color features are interacted using cross-domain attention conciliation module (CAC) after each MF block. We evaluate the performance of our proposed method on both synthetic and real captured datasets. Extensive experimental results validate that the proposed method achieves state-of-the-art performance in both objective and subjective quality.
•Potassium oleate (PO) can inhibit corrosion of copper (Cu) and cobalt (Co).•A small amount of PO can increase the removal rate of Co.•PO can work in synergy with fatty alcohol polyoxy ethylene ...ether.
As the feature size of integrated circuit drops down to 20–14 nm, cobalt (Co) is used as the barrier layer material for multilayer copper (Cu) wiring. The chemical mechanical polishing (CMP) process of Cu film has developed from a combined rough polishing and fine polishing to a one-step polishing, which needs to stop on the Co barrier layer. So the removal rate (RR) of Co should approach zero to meet the requirement of higher RR selection ratio of Cu and Co. Inhibitors in the Cu film slurry play an important role for controlling the RR during CMP process. In this paper, the anionic surfactant potassium oleate (PO) was selected as a key corrosion inhibitor in Cu film CMP to enhance the RR selection ratio of Cu and Co. The complexation and corrosion inhibition mechanisms between PO and Cu or Co were revealed by electrochemical measurements, X-ray photoelectron spectroscopy and scanning electron microscopy measurements. It was found that the rapid complexation of a small amount of PO with Co2+ could increase the Co RR. However, with a higher concentration of PO, the effective catalysis caused the conversion of cobaltous hydroxide to tricobalt tetraoxide, and thus resulted in a lower Co RR. With the addition of the nonionic surfactant called fatty alcohol polyoxy ethylene ether (JFCE), the morphology of the PO aggregates changes to spherical, which weakened the inhibiting effect of PO on Cu RR, and thus a higher Cu RR and RR selection ratio of Cu and Co was achieved. The synergistic action mechanism of PO and JFCE on Cu and Co surfaces was analyzed systematically. The present work provides an idea that surfactants are excellent candidates for metal inhibitors.
As a wide band gap semiconductor, gallium nitride (GaN) is widely used in kinds of electronic devices. With the improvement of device accuracy, the requirements for GaN surface processing efficiency ...and quality are getting higher and higher. However, due to the high hardness and high chemical stability of GaN, the processing is very difficult. Chemical mechanical polishing (CMP) is one of the high-precision processing method. The slurry plays a vital role in the GaN CMP process, especially the oxidant. As common oxidants, hydrogen peroxide (H2O2) and potassium persulfate (K2S2O8) are widely used, but their efficiency on typical GaN CMP still need to be promoted. A novel oxidant potassium peroxomonosulfate sulfate (2KHSO5·KHSO4·K2SO4) known as Oxone was also used to promote polishing efficiency and achieve a balance between efficiency and surface roughness (Sq). In order to explore the influence trend and mechanism of these three oxidants on polishing efficiency under different pH conditions and the same pH conditions after optimization on GaN CMP, a series of polishing, electrochemical and related test experiments as X-ray photoelectron spectroscopy (XPS) and atomic force microscopy (AFM) were carried out. The results indicated that the CMP efficiency of these oxidants extremely affected by the pH values and their concentrations in alkaline slurry. The best pH values for CMP efficiency are 10, 10 and 8 for Oxone, H2O2 and K2S2O8, respectively. In addition, comparing the chemical characteristics of H2O2 and K2S2O8 with Oxone, mixed oxidants of H2O2 and K2S2O8 with different proportions were used and the results indicated that the mixed oxidant of H2O2 and K2S2O8 had better CMP efficiency than either H2O2 or K2S2O8. Sorting from largest to smallest, the polishing efficiency was Oxone, mixed oxidant, K2S2O8 and H2O2 while the surface roughness was K2S2O8, mixed oxidant, Oxone and H2O2. Considering typical CMP efficiency and average surface roughness, when Oxone concentration was 0.5 wt% at pH 10, the material removal rate of 247.92 nm/h and surface roughness of 0.547 nm was obtained simultaneously. Such results have important industrial application value for GaN CMP.
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Incompletely condensed tetra-silanol-phenyl-polyhedral oligomeric silsesquioxane (TOPO) was synthesized first and then copolymerized with hydroxy terminated polydimethylsiloxane (HPDMS) as a cross ...linking agent to prepare room temperature vulcanized (RTV) silicone rubber (TOPO–PDMS). The structure of TOPO was characterized by matrix-assisted laser desorption/ionization time of flight mass spectrometry (MALDI-TOF MS) and nuclear magnetic resonance (NMR). The Fourier transform infrared spectroscopy (FT-IR) spectra suggested successful bonding of TOPO silanols and HPDMS. Scanning electron microscopy (SEM) and wide angle X-ray diffraction (WAXD) analysis showed that POSS could dissolve in silicone rubber at the molecular level. Thermal stability of TOPO–PDMS was investigated by thermogravimetric analysis (TGA) and the results demonstrated that the chemical incorporation of POSS into polydimethylsiloxane (PDMS) networks significantly enhanced the thermal stability of the modified RTV silicon rubber. The degradation mechanism(s) was further monitored by TGA coupled with FTIR. The results suggest that the remarkable improvement in thermal stability can be attributed to (a) the consumption of OH in the condensation reaction between TOPO and HPDMS which decreases the ‘back biting’ reaction and (b) the nanoreinforcement effect of the POSS cage that retards polymer chain motion. Additionally, the characteristic temperatures of 5%, 20% and the maximal rate of weight loss exhibit different trends with content increase of the cross-linker TOPO and the cause has been discussed in detail.
