NNI-1型C_5/C_6烷烃异构化催化剂长周期运行分析及建议

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。     

SDN中基于KMOBPSO的高可靠性控制器部署算法

针对SDN中控制器系统的单节点故障问题,兼顾系统成本和系统时延,应用N+1冗余备份模型来提高SDN控制器部署的可靠性,并将其抽象为多目标优化问题.同时,提出了一种融合K-means聚类算法和遗传算子的多目标二进制粒子群算法——KMOBPSO算法,以求解SDN控制器高可靠性部署问题的解.仿真结果表明,所提算法具有求解精度高、分布均匀、沿Pareto前沿面覆盖广的特点,能够显著提高SDN中控制器部署的可靠性.     

Achieving Rich and Active Alkaline Hydrogen Evolution Heterostructures via Interface Engineering on 2D 1T‐MoS2 Quantum Sheets

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 ${\text{edge}}_{{\text{1T‐MoS}}_{\text{2}}}$/ ${\text{edge}}_{\text{Ni}{(\text{OH})}_{\text{2}}}$ heterostructures, which significantly enhance HER performance in alkaline media. Featured with rich ${\text{edge}}_{{\text{1T‐MoS}}_{\text{2}}}$/ ${\text{edge}}_{\text{Ni}{(\text{OH})}_{\text{2}}}$ 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.     

Effects of SO2 on selective catalytic reduction of NO with NH3 over a TiO2 photocatalyst

The effect of SO₂ gas was investigated on the activity of the photo-assisted selective catalytic reduction of nitrogen monoxide (NO) with ammonia (NH₃) over a TiO₂ photocatalyst in the presence of excess oxygen (photo-SCR). The introduction of SO₂ (300 ppm) greatly decreased the activity of the photo-SCR at 373 K. The increment of the reaction temperature enhanced the resistance to SO₂ gas, and at 553 K the conversion of NO was stable for at least 300 min of the reaction. X-ray diffraction, FTIR spectroscopy, thermogravimetry and differential thermal analysis, x-ray photoelectron spectroscopy (XPS), elemental analysis and N₂ adsorption measurement revealed that the ammonium sulfate species were generated after the reaction. There was a strong negative correlation between the deposition amount of the ammonium sulfate species and the specific surface area. Based on the above relationship, we concluded that the deposition of the ammonium sulfate species decreased the specific surface area by plugging the pore structure of the catalyst, and the decrease of the specific surface area resulted in the deactivation of the catalyst.     

Assessment of the different sources of uncertainty in a SWAT model of the River Senne (Belgium)

Although rainfall input uncertainties are widely identified as being a key factor in hydrological models, the rainfall uncertainty is typically not included in the parameter identification and model output uncertainty analysis of complex distributed models such as SWAT and in maritime climate zones. This paper presents a methodology to assess the uncertainty of semi-distributed hydrological models by including, in addition to a list of model parameters, additional unknown factors in the calibration algorithm to account for the rainfall uncertainty (using multiplication factors for each separately identified rainfall event) and for the heteroscedastic nature of the errors of the stream flow. We used the Differential Evolution Adaptive Metropolis algorithm (DREAM_(zs)) to infer the parameter posterior distributions and the output uncertainties of a SWAT model of the River Senne (Belgium). Explicitly considering heteroscedasticity and rainfall uncertainty leads to more realistic parameter values, better representation of water balance components and prediction uncertainty intervals.     

Combined hardware–software multi-parallel prefiltering on the Convey HC-1 for fast homology detection

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.     

The Interplay of Modulus,Strength, and Ductility in Adhesive Design Using Biomimetic Polymer Chemistry

High‐performance adhesives require mechanical properties tuned to demands of the surroundings. A mismatch in stiffness between substrate and adhesive leads to stress concentrations and fracture when the bonding is subjected to mechanical load. Balancing material strength versus ductility, as well as considering the relationship between adhesive modulus and substrate modulus, creates stronger joints. However, a detailed understanding of how these properties interplay is lacking. Here, a biomimetic terpolymer is altered systematically to identify regions of optimal bonding. Mechanical properties of these terpolymers are tailored by controlling the amount of a methyl methacrylate stiff monomer versus a similar monomer containing flexible poly(ethylene glycol) chains. Dopamine methacrylamide, the cross‐linking monomer, is a catechol moiety analogous to 3,4‐dihydroxyphenylalanine, a key component in the adhesive proteins of marine mussels. Bulk adhesion of this family of terpolymers is tested on metal and plastic substrates. Incorporating higher amounts of poly(ethylene glycol) into the terpolymer introduces flexibility and ductility. By taking a systematic approach to polymer design, the region in which material strength and ductility are balanced in relation to the substrate modulus is found, thereby yielding the most robust joints.     

The control of sea lice in Atlantic salmon by selective breeding

Sea lice threaten the welfare of farmed Atlantic salmon and the sustainability of fish farming across the world. Chemical treatments are the major method of control but drug resistance means that alternatives are urgently needed. Selective breeding can be a cheap and effective alternative. Here, we combine experimental trials and diagnostics to provide a practical protocol for quantifying resistance to sea lice. We then combined quantitative genetics with epidemiological modelling to make the first prediction of the response to selection, quantified in terms of reduced need for chemical treatments. We infected over 1400 young fish with Lepeophtheirus salmonis, the most important species in the Northern Hemisphere. Mechanisms of resistance were expressed early in infection. Consequently, the number of lice per fish and the ranking of families were very similar at 7 and 17 days post infection, providing a stable window for assessing susceptibility to infection. The heritability of lice numbers within this time window was moderately high at 0.3, confirming that selective breeding is viable. We combined an epidemiological model of sea lice infection and control on a salmon farm with genetic variation in susceptibility among individuals. We simulated 10 generations of selective breeding and examined the frequency of treatments needed to control infection. Our model predicted that substantially fewer chemical treatments are needed to control lice outbreaks in selected populations and chemical treatment could be unnecessary after 10 generations of selection. Selective breeding for sea lice resistance should reduce the impact of sea lice on fish health and thus substantially improve the sustainability of Atlantic salmon production.