Nowadays, oily wastewater and spilled oil have caused great threats on both ecosystem and human life. To address these severe problems, considerable efforts have been possessed on developing novel oil/water separation materials. The porous oil‐absorbent materials, especially the porous polydimethylsiloxane (PDMS) with excellent properties of easy fabrication and inherent hydrophobicity, have attracted tremendous attentions from worldwide. The conventional methods using salt or sugar as sacrificial template and water as solvent have been widely adopted to fabricate the porous PDMS sponge. Due to the inherent hydrophobicity of PDMS, the solvent of water hardly penetrates into the inside of PDMS, which results in the difficult and incomplete remove of the hard template. In this contribution, the 3D interconnected porous PDMS sponge is facilely prepared by utilizing a modified technique with the citric acid monohydrate as hard template and ethanol as solvent. The proposed approach is capable of removing the hard template efficiently and thoroughly, which demonstrates promising utilizations in practical applications.

Several theoretical and experimental aspects of sideband suppression in the nuclear magnetic resonance (NMR) spectra of rotating solids are considered. The principles of sideband suppression are explored using general symmetry arguments and previous treatments are examined critically. Analytical solutions are given for sideband suppression pulse sequences employing four, five, six, and nine P pulses. The analytical solutions for four r pulses are complete. Experimental demonstrations are given.

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Pixel-based optical proximity correction (PBOPC) methods have been developed as a leading-edge resolution enhancement technique (RET) for integrated circuit fabrication. PBOPC independently modulates each pixel on the reticle, which tremendously increases the mask's complexity and, at the same time, deteriorates its manufacturability. Most current PBOPC algorithms recur to regularization methods or a mask manufacturing rule check (MRC) to improve the mask manufacturability. Typically, these approaches either fail to satisfy manufacturing constraints on the practical product line, or lead to suboptimal mask patterns that may degrade the lithographic performance. This paper develops a block-based optical proximity correction (BBOPC) algorithm to pursue the optimal masks with manufacturability compliance, where the mask is shaped by a set of overlapped basis blocks rather than pixels. BBOPC optimization is formulated based on a vector imaging model, which is adequate for both dry lithography with lower numerical aperture (NA), and immersion lithography with hyper-NA. The BBOPC algorithm successively optimizes the main features (MF) and subresolution assist features (SRAF) based on a modified conjugate gradient method. It is effective at smoothing any unmanufacturable jogs along edges. A weight matrix is introduced in the cost function to preserve the edge fidelity of the printed images. Simulations show that the BBOPC algorithm can improve lithographic imaging performance while maintaining mask manufacturing constraints.