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中国石化海南炼油化工有限公司0.2 Mt/a C5/C6烷烃异构化装置以连续重整装置的拔头油为原料,使用NNI-1催化剂,采用一次通过流程,不设脱异戊烷塔和稳定塔,经设在连续重整装置内的脱丁烷塔稳定处理后作为汽油调合组分。该装置于2006年9月开工投产,截至2015年3月已连续运行3个周期。长周期运行分析结果表明:前两个周期中NNI-1催化剂具有较高的异构化活性及选择性,C5异构化率为60%左右,C6异构化率为80%左右,C6选择性为15%左右,产品辛烷值基本达到技术指标要求(RON≥78);而在第三周期运行中,催化剂积炭增加等原因导致其异构化活性及选择性降低,异构化产品辛烷值提升能力呈现逐步衰减的趋势,提高反应苛刻度已不能弥补催化剂活性下降造成的产品辛烷值降低。为保证装置长周期运行,建议择机停工对催化剂进行再生,或是直接换用与装置原料性质匹配的异构化催化剂。 相似文献
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Qi Yang Qilong Wu Yang Liu Shuiping Luo Xiaotong Wu Xixia Zhao Haiyuan Zou Baihua Long Wen Chen Yujia Liao Lanxi Li Pei Kang Shen Lele Duan Zewei Quan 《Advanced materials (Deerfield Beach, Fla.)》2020,32(36):2002822
Engineering novel Sn-based bimetallic materials could provide intriguing catalytic properties to boost the electrochemical CO2 reduction. Herein, the first synthesis of homogeneous Sn1−xBix alloy nanoparticles (x up to 0.20) with native Bi-doped amorphous SnOx shells for efficient CO2 reduction is reported. The Bi-SnOx nanoshells boost the production of formate with high Faradaic efficiencies (>90%) over a wide potential window (−0.67 to −0.92 V vs RHE) with low overpotentials, outperforming current tin oxide catalysts. The state-of-the-art Bi-SnOx nanoshells derived from Sn0.80Bi0.20 alloy nanoparticles exhibit a great partial current density of 74.6 mA cm−2 and high Faradaic efficiency of 95.8%. The detailed electrocatalytic analyses and corresponding density functional theory calculations simultaneously reveal that the incorporation of Bi atoms into Sn species facilitates formate production by suppressing the formation of H2 and CO. 相似文献
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Wenshu Chen Jiajun Gu Yongping Du Fang Song Fanxing Bu Jinghan Li Yang Yuan Ruichun Luo Qinglei Liu Di Zhang 《Advanced functional materials》2020,30(25)
Large‐scale production of hydrogen from water‐alkali electrolyzers is impeded by the sluggish kinetics of hydrogen evolution reaction (HER) electrocatalysts. The hybridization of an acid‐active HER catalyst with a cocatalyst at the nanoscale helps boost HER kinetics in alkaline media. Here, it is demonstrated that 1T–MoS2 nanosheet edges (instead of basal planes) decorated by metal hydroxides form highly active / heterostructures, which significantly enhance HER performance in alkaline media. Featured with rich / sites, the fabricated 1T–MoS2 QS/Ni(OH)2 hybrid (quantum sized 1T–MoS2 sheets decorated with Ni(OH)2 via interface engineering) only requires overpotentials of 57 and 112 mV to drive HER current densities of 10 and 100 mA cm?2, respectively, and has a low Tafel slope of 30 mV dec?1 in 1 m KOH. So far, this is the best performance for MoS2‐based electrocatalysts and the 1T–MoS2 QS/Ni(OH)2 hybrid is among the best‐performing non‐Pt alkaline HER electrocatalysts known. The HER process is durable for 100 h at current densities up to 500 mA cm?2. This work not only provides an active, cost‐effective, and robust alkaline HER electrocatalyst, but also demonstrates a design strategy for preparing high‐performance catalysts based on edge‐rich 2D quantum sheets for other catalytic reactions. 相似文献
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为了开发β受体阻断剂新药(S)-噻吗洛尔半水合物,采用3-吗啉-4-氯-1,2,5-噻二唑为起始原料,经水解反应得到中间体1(3-吗啉-4-羟基-1,2,5-噻二唑)。中间体1与R-环氧氯丙烷发生醚化反应,经后处理及重结晶得到中间体2 {(R)-4-[4-(环氧乙烷-2-基甲氧基)-1,2,5-噻二唑-3-基]吗啉}。中间体2经胺化反应、马来酸成盐及重结晶得到(S)-马来酸噻吗洛尔。(S)-马来酸噻吗洛尔经游离、纯水转晶得到符合药典标准的(S)-噻吗洛尔半水合物,总收率14.05%且e.e.值为99.66%。最终成品经IR、1H-NMR、13C-NMR、MS、TGA、DSC表征,并优化各步反应条件。结果表明:以三乙胺为醚化反应缚酸剂75 ℃反应最佳;以乙醇为胺化反应溶剂46 ℃反应16 h最佳;S-噻吗洛尔的转晶拆分以水作溶剂,比传统不对称合成工艺安全稳定,操作简单,适合工业化生产。 相似文献
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Protein databases used in research are huge and still grow at a fast pace. Many comparisons need to be done when searching similar (homologous) sequences for a given query sequence in these databases. Comparing a query sequence against all sequences of a huge database using the well-known Smith–Waterman algorithm is very time-consuming. Hidden Markov Models pose an opportunity for reducing the number of entries of a database and also enable to find distantly homologous sequences. Fewer entries are achieved by clustering similar sequences in a Hidden Markov Model. Such an approach is used by the bioinformatics tool HHblits. To further reduce the runtime, HHblits uses two-level prefiltering to reduce the number of time-consuming Viterbi comparisons. Still, prefiltering is very time-consuming. Highly parallel architectures and huge bandwidth are required for processing and transferring the massive amounts of data. In this article, we present an approach exploiting the reconfigurable, hybrid computer architecture Convey HC-1 for migrating the most time-consuming part. The Convey HC-1 with four FPGAs and high memory bandwidth of up to 76.8 GB/s serves as the platform of choice. Other bioinformatics applications have already been successfully supported by the HC-1. Limited by FPGA size only, we present a design that calculates four first-level prefiltering scores per FPGA concurrently, i.e. 16 calculations in total. This score calculation for the query profile against database sequences is done by a modified Smith–Waterman scheme that is internally parallelized 128 times in contrast to the original Streaming ‘Single Instruction Multiple Data (SIMD)’ Extensions (SSE)-supported implementation where only 16-fold parallelism can be exploited and where memory bandwidth poses the limiting factor. Preloading the query profile, we are able to transform the memory-bound implementation to a compute- and resource-bound FPGA design. We tightly integrated the FPGA-based coprocessor into the hybrid computing system by employing task-parallelism for the two-level prefiltering. Despite much lower clock rates, the FPGAs outperform SSE-based execution for the calculation of the prefiltering scores by a factor of 7.9. 相似文献