Establishment and Optimization of ISSR-PCR Reaction System for Salvia przewalskii Maxim.

Based on single-factor experiment and L9 （34 ） orthogonal experiment, a stable ISSR-PCR reaction system of Salvia przewalskii Maxim. was established and optimized. The resuhs indicated that the optimal concentrations of various components in a 20 ill ISSR-PCR reaction system of S. przewalskii Maxim. were ： 2 ul of 10 x buffer （ Mg2＋）, 0.4 mmol/L dNTPs, 1.0 U of Taq DNA polymerase, 0.3 umol/L ISSR primers and 30 ng of DNA template. This study laid the foun- dation for the utilization of S. przewalskii Maxim. germplasm resources.

Study on trifluoromethanesulfonic acid-promoted synthesis of daidzein: Process optimization and reaction mechanism

Daidzein has been widely used in pharmaceuticals,nutraceuticals,cosmetics,feed additives,etc.Its preparation process and related reaction mechanism need to be further investigated.A cost-effective process for synthesizing daidzein was developed in this work.In this article,a two-step synthesis of daidzein(Friedel–Crafts acylation and[5+1]cyclization)was developed via the employment of trifluoromethanesulfonic acid(TfOH)as an effective promoting reagent.The effect of reaction conditions such as solvent,the amount of TfOH,reaction temperature,and reactant ratio on the conversion rate and the yield of the reaction,respectively,was systematically investigated,and daidzein was obtained in 74.0%isolated yield under optimal conditions.Due to the facilitating effect of TfOH,the Friedel–Crafts acylation was completed within 10 min at 90℃ and the[5+1]cyclization was completed within 180 min at 25℃.In addition,a possible reaction mechanism for this process was proposed.The results of the study may provide useful guidance for industrial production of daidzein on a large scale.

Fundamental Understanding and Optimization Strategies for Dual‑Ion Batteries:A Review

There has been increasing demand for high-energy density and longcycle life rechargeable batteries to satisfy the ever-growing requirements for nextgeneration energy storage systems.Among all available candidates,dual-ion batteries(DIBs)have drawn tremendous attention in the past few years from both academic and industrial battery communities because of their fascinating advantages of high working voltage,excellent safety,and environmental friendliness.However,the dynamic imbalance between the electrodes and the mismatch of traditional electrolyte systems remain elusive.To fully employ the advantages of DIBs,the overall optimization of anode materials,cathode materials,and compatible electrolyte systems is urgently needed.Here,we review the development history and the reaction mechanisms involved in DIBs.Afterward,the optimization strategies toward DIB materials and electrolytes are highlighted.In addition,their energy-related applications are also provided.Lastly,the research challenges and possible development directions of DIBs are outlined.

Modeling and Optimization of Ethane Steam Cracking Process in An Industrial Tubular Reactor with Improved Reaction Scheme

Ethane steam cracking process in an industrial reactor was investigated.An one-demsional(1D)steady-state model was developed firstly by using an improved molecular reaction scheme and was then simulated in Aspen Plus.A comparison of model results with industrial data and previously reported results showed that the model can predict the process kinetics more accurately.In addition,the validated model was used to study the effects of different process variables,including coil outlet temperature(COT),steam-to-ethane ratio and residence time on ethane conversion,ethylene selectivity,products yields,and coking rate.Finally,steady-state optimization was conducted to the operation of industrial reactor.The COT and steam-to-ethane ratio were taken as decision variables to maximize the annual operational profit.

Extreme learning with chemical reaction optimization for stock volatility prediction

Extreme learning machine(ELM)allows for fast learning and better generalization performance than conventional gradient-based learning.However,the possible inclusion of non-optimal weight and bias due to random selection and the need for more hidden neurons adversely influence network usability.Further,choosing the optimal number of hidden nodes for a network usually requires intensive human intervention,which may lead to an ill-conditioned situation.In this context,chemical reaction optimization(CRO)is a meta-heuristic paradigm with increased success in a large number of application areas.It is characterized by faster convergence capability and requires fewer tunable parameters.This study develops a learning framework combining the advantages of ELM and CRO,called extreme learning with chemical reaction optimization(ELCRO).ELCRO simultaneously optimizes the weight and bias vector and number of hidden neurons of a single layer feed-forward neural network without compromising prediction accuracy.We evaluate its performance by predicting the daily volatility and closing prices of BSE indices.Additionally,its performance is compared with three other similarly developed models—ELM based on particle swarm optimization,genetic algorithm,and gradient descent—and find the performance of the proposed algorithm superior.Wilcoxon signed-rank and Diebold–Mariano tests are then conducted to verify the statistical significance of the proposed model.Hence,this model can be used as a promising tool for financial forecasting.

Optimization of reaction conditions for the electroleaching of manganese from low-grade pyrolusite

In the present study, a response surface methodology was used to optimize the electroleaching of Mn from low-grade pyrolusite. Ferrous sulfate heptahydrate was used in this reaction as a reducing agent in sulfuric acid solutions. The effect of six process variables, including the mass ratio of ferrous sulfate heptahydrate to pyrolusite, mass ratio of sulfuric acid to pyrolusite, liquid-to-solid ratio, current density, leaching temperature, and leaching time, as well as their binary interactions, were modeled. The results revealed that the order of these factors with respect to their effects on the leaching efficiency were mass ratio of ferrous sulfate heptahydrate to pyrolusite 〉 leaching time 〉 mass ratio of sulfuric acid to pyrolusite 〉 liquid-to-solid ratio 〉 leaching temperature 〉 current density. The optimum conditions were as follows： 1.10：1 mass ratio of ferrous sulfate heptahydrate to pyrolusite, 0.9：1 mass ratio of sulfuric acid to pyrolusite, liquid-to-solid ratio of 0.7：1, current density of 947 A/m^2, leaching time of 180 min, and leaching temperature of 73°C. Under these conditions, the predicted leaching efficiency for Mn was 94.1%; the obtained experimental result was 95.7%, which confirmed the validity of the model.

A chemical-reaction-optimization-based neuro-fuzzy hybrid network for stock closing price prediction

Accurate prediction of stock market behavior is a challenging issue for financial forecasting.Artificial neural networks,such as multilayer perceptron have been established as better approximation and classification models for this domain.This study proposes a chemical reaction optimization(CRO)based neuro-fuzzy network model for prediction of stock indices.The input vectors to the model are fuzzified by applying a Gaussian membership function,and each input is associated with a degree of membership to different classes.A multilayer perceptron with one hidden layer is used as the base model and CRO is used to the optimal weights and biases of this model.CRO was chosen because it requires fewer control parameters and has a faster convergence rate.Five statistical parameters are used to evaluate the performance of the model,and the model is validated by forecasting the daily closing indices for five major stock markets.The performance of the proposed model is compared with four state-of-art models that are trained similarly and was found to be superior.We conducted the Deibold-Mariano test to check the statistical significance of the proposed model,and it was found to be significant.This model can be used as a promising tool for financial forecasting.

Optimizing high-coordination shell of Co-based single-atom catalysts for efficient ORR and zinc-air batteries

Atom-level modulation of the coordination environment for single-atom catalysts(SACs)is considered as an effective strategy for elevating the catalytic performance.For the MNxsite,breaking the symmetrical geometry and charge distribution by introducing relatively weak electronegative atoms into the first/second shell is an efficient way,but it remains challenging for elucidating the underlying mechanism of interaction.Herein,a practical strategy was reported to rationally design single cobalt atoms coordinated with both phosphorus and nitrogen atoms in a hierarchically porous carbon derived from metal-organic frameworks.X-ray absorption spectrum reveals that atomically dispersed Co sites are coordinated with four N atoms in the first shell and varying numbers of P atoms in the second shell(denoted as Co-N/P-C).The prepared catalyst exhibits excellent oxygen reduction reaction(ORR)activity as well as zinc-air battery performance.The introduction of P atoms in the Co-SACs weakens the interaction between Co and N,significantly promoting the adsorption process of ^(*)OOH,resulting in the acceleration of reaction kinetics and reduction of thermodynamic barrier,responsible for the increased intrinsic activity.Our discovery provides insights into an ultimate design of single-atom catalysts with adjustable electrocatalytic activities for efficient electrochemical energy conversion.

Unveiling the geometric site dependent activity of spinel Co_(3)O_(4)for electrocatalytic chlorine evolution reaction

Spinel cobalt oxide(Co_(3)O_(4)),consisting of tetrahedral Co^(2+)(CoTd)and octahedral Co^(3+)(CoOh),is considered as promising earth-abundant electrocatalyst for chlorine evolution reaction(CER).Identifying the catalytic contribution of geometric Co site in the electrocatalytic CER plays a pivotal role to precisely modulate electronic configuration of active Co sites to boost CER.Herein,combining density functional theory calculations and experiment results assisted with operando analysis,we found that the Co_(Oh) site acts as the main active site for CER in spinel Co_(3)O_(4),which shows better Cl^(-)adsorption and more moderate intermediate adsorption toward CER than CoTd site,and does not undergo redox transition under CER condition at applied potentials.Guided by above findings,the oxygen vacancies were further introduced into the Co_(3)O_(4) to precisely manipulate the electronic configuration of Co_(Oh) to boost Cl^(-)adsorption and optimize the reaction path of CER and thus to enhance the intrinsic CER activity significantly.Our work figures out the importance of geometric configuration dependent CER activity,shedding light on the rational design of advanced electrocatalysts from geometric configuration optimization at the atomic level.

Solving Multi-Area Environmental/Economic Dispatch by Pareto-Based Chemical-Reaction Optimization Algorithm

In this study, we present a Pareto-based chemicalreaction optimization(PCRO) algorithm for solving the multiarea environmental/economic dispatch optimization problems.Two objectives are minimized simultaneously, i.e., total fuel cost and emission. In the proposed algorithm, each solution is represented by a chemical molecule. A novel encoding mechanism for solving the multi-area environmental/economic dispatch optimization problems is designed to dynamically enhance the performance of the proposed algorithm. Then, an ensemble of effective neighborhood approaches is developed, and a selfadaptive neighborhood structure selection mechanism is also embedded in PCRO to increase the search ability while maintaining population diversity. In addition, a grid-based crowding distance strategy is introduced, which can obviously enable the algorithm to easily converge near the Pareto front. Furthermore,a kinetic-energy-based search procedure is developed to enhance the global search ability. Finally, the proposed algorithm is tested on sets of the instances that are generated based on realistic production. Through the analysis of experimental results, the highly effective performance of the proposed PCRO algorithm is favorably compared with several algorithms, with regards to both solution quality and diversity.

Modulating Co-Co bonds average length in Co_(0.85)Se_(1-x)S_(x) to enhance conversion reaction for potassium storage

While alloying transition metal chalcogenides(TMCs)with other chalcogen elements can effectively improve their conductivity and electrochemical properties,the optimal alloying content is still uncertain.In this study,we study the influence of dopant concentration on the chemical bonds in TMC and reveal the associated stepwise conversion reaction mechanism for potassium ion storage.According to density function theory calculations,appropriate S-doping in Co0.85Se(Co_(0.85)Se_(1-x)S_(x))can reduce the average length of Co-Co bonds because of the electronegativity variation,which is thermodynamically favourable to the phase transition reactions.The optimal Se/S ratio(x=0.12)for the conductivity has been obtained from experimental results.When assembled as an anode in potassium-ion batteries(PIBs),the sample with optimized Se/S ratio exhibits extraordinary electrochemical performance.The rate performance(229.2 mA h g^(-1)at 10 A g^(-1))is superior to the state-of-the-art results.When assembled with Prussian blue(PB)as a cathode,the pouch cell exhibits excellent performance,demonstrating its great potential for applications.Moreover,the stepwise K+storage mechanism caused by the coexistence of S and Se is revealed by in-situ X-ray diffraction and ex-situ transmission electron microscopy techniques.Hence,this work not only provides an effective strategy to enhance the electrochemical performance of transition metal chalcogenides but also reveals the underlying mechanism for the construction of advanced electrode materials.

Optimization of ISSR-PCR System and Conditions for Portulaca oleracea L.

With Portulaca oleracea L. as an experimental material, its total DNA was extracted by the improved CTAB method, the ISSR-PCR primers were screened, and the ISSR-PCR reaction system and reaction conditions for P. oleracea were Optimized. The results showed that there were 8 primers suitable for ISSR-PCR of P. oleracea. The optimal reaction system had a volume of 25 μl, including 2 x Taq Platinum PCR Master Mix 12.5 μl, primer 2 μl, ddH20 9.5 μl, and DNA template 1μl. The optimized ISSR-PCR of P. oleracea was started with pre-denaturation at 94 ℃ for 360 s, followed by 30 cycles of denaturation at 94 ℃ for 60 s, annealing at 54 ℃ for 60 s and extension at 72 ℃ for 90 s, and completed by extension at 72 ℃ for 300 s.

Production and Characterization of Biodiesel from Rapeseed Oil through Optimization of Transesterification Reaction Conditions

In this study,biodiesel fuel was produced from rapeseed oil via transesterification method.The optimum reaction conditions were determined by varying alcohol type and its concentration considering their influence on the yield and properties of produced biodiesel.Methanol and ethanol were alcohol used in the transesterification process.The density of biodiesel was measured at 15℃according to EN ISO 12185 test method and its viscosity was determined at 40℃by using a Brookfield digital viscometer(DV-II+Pro).Shimadzu Auto-Calculating Bomb calorimeter CA-4AJ was used to measure the high heating value.The optimum transesterification conditions found were alcohol:oil ratio of 18:1,1%of potassium hydroxide as catalyst,60 min of reaction time,60℃of reaction temperature and stirring speed of 650 rpm.Biodiesel properties under these conditions satisfied the regulatory standards and are slightly similar to those of mineral diesel tested in same conditions.Using methanol gives better results compared to ethanol.

Reaction mode between Si and Fe and evaluation of optimal species in poly-silicic-ferric coagulant

A kind of Fe-polysilicate polymer, poly-silicic-ferric （PSF） coagulant was prepared by co-polymerization （hydroxylation of mixture of Fe^3＋ and fresh polysilicic acid （PS））, in which PSF0.5, PSF1 or PSF3 denotes Si/Fe molar ratio of 0.5, 1 or 3, respectively. The effects of Si/Fe ratio and reaction time （co-polymerization time or aging time） on the reaction mode between Si and Fe were studies, and the optimal species of PSF was evaluated by pH change during the preparation of PSF and coagulation tests. The results showed that the characteristics of PSF are largely affected by both reaction time and Si/Fe ratio. PSF is found to be a essential complex of Si, Fe, and many other ions. The reaction mode between Si and Fe differs with various Si/Fe ratios. The pH of PSF0.5, PSF1 or PSF3 tended to be stable when reaction time is 10, 25 or 55 rain, respectively, which is almost consistent with the time reaching the relative stable morphology that is just the optimal species of higher coagulation efficiency. The optimal reaction time reaching optimal species can be evaluated by measuring the pH change during the polymerization process.

Mechanical Behavior and Shape Optimization of Lining Structure for Subsea Tunnel Excavated in Weathered Slot

Subsea tunnel lining structures should be designed to sustain the loads transmitted from surrounding ground and groundwater during excavation. Extremely high pore-water pressure reduces the effective strength of the country rock that surrounds a tunnel, thereby lowering the arching effect and stratum stability of the structure. In this paper, the mechanical behavior and shape optimization of the lining structure for the Xiang＇an tunnel excavated in weathered slots are examined. Eight cross sections with different geometric parameters are adopted to study the mechanical behavior and shape optimization of the lining structure. The hyperstatic reaction method is used through finite element analysis software ANSYS. The mechanical behavior of the lining structure is evidently affected by the geometric parameters of crosssectional shape. The minimum safety factor of the lining structure elements is set to be the objective function. The efficient tunnel shape to maximize the minimum safety factor is identified. The minimum safety factor increases significantly after optimization. The optimized cross section significantly improves the mechanical characteristics of the lining structure and effectively reduces its deformation. Force analyses of optimization process and program are conducted parametrically so that the method can be applied to the optimization design of other similar structures. The results obtained from this study enhance our understanding of the mechanical behavior of the lining structure for subsea tunnels. These results are also beneficial to the optimal design of lining structures in general.

Integration strategies of hydrogen network in a refinery based on operational optimization of hydrotreating units

Inferior crude oil and fuel oil upgrading lead to escalating increase of hydrogen consumption in refineries.It is imperative to reduce the hydrogen consumption for energy-saving operations of refineries.An integration strategy of hydrogen network and an operational optimization model of hydrotreating(HDT)units are proposed based on the characteristics of reaction kinetics of HDT units.By solving the proposed model,the operating conditions of HDT units are optimized,and the parameters of hydrogen sinks are determined by coupling hydrodesulfurization(HDS),hydrodenitrification(HDN)and aromatic hydrogenation(HDA)kinetics.An example case of a refinery with annual processing capacity of eight million tons is adopted to demonstrate the feasibility of the proposed optimization strategies and the model.Results show that HDS,HDN and HDA reactions are the major source of hydrogen consumption in the refinery.The total hydrogen consumption can be reduced by 18.9%by applying conventional hydrogen network optimization model.When the hydrogen network is optimized after the operational optimization of HDT units is performed,the hydrogen consumption is reduced by28.2%.When the benefit of the fuel gas recovery is further considered,the total annual cost of hydrogen network can be reduced by 3.21×10~7CNY·a^(-1),decreased by 11.9%.Therefore,the operational optimization of the HDT units in refineries should be imposed to determine the parameters of hydrogen sinks base on the characteristics of reaction kinetics of the hydrogenation processes before the optimization of the hydrogen network is performed through the source-sink matching methods.

Study on Optimization of RAPD Conditions for Soil Microbe of Black Soil

Factors including Mg^2＋, dNTP and primer that affected RAPD were studied using orthogonal experimental design, and at the same time, anneal temperature, extending time and cycles were also studied. Finally, PCR reaction system that is feasible for black soil microbial PCR amplification was determined, containing 7 ng DNA template, 20 pM random primers, 1.5 U Taq DNA polymerase, 3.0 mM MgCl2 and 0.2 mmol ·L^-1 dNTP, with procedure： 40 cycles for 3 min at 94 ℃ （temperature）, 40 s at 37 ℃ （annealing）, 1.5 min at 72 ℃ （extension）, a final elongation step at 72 ℃ for 7 min.

Simultaneous optimization of transit network and public bicycle station network

The traditional manner to design public transportation system is to sequentially design the transit network and public bicycle network. A new public transportation system design problem that simultaneously considers both bus network design and public bicycle network design is proposed. The chemical reaction optimization(CRO) is designed to solve the problem. A shortcoming of CRO is that, when the two-molecule collisions take place, the molecules are randomly picked from the container.Hence, we improve CRO by employing different mating strategies. The computational results confirm the benefits of the mating strategies. Numerical experiments are conducted on the Sioux-Falls network. A comparison with the traditional sequential modeling framework indicates that the proposed approach has a better performance and is more robust. The practical applicability of the approach is proved by employing a real size network.

Preparation of Sodium Cobalt Tetracarbonyl and Optimization of Process Conditions for Hydroesterification of Ethylene Oxide

In this paper, sodium cobalt tetracarbonyl(NaCo(CO)_4) was synthesized by using sodium dithionite and zinc powder as the reduction system and cobalt hexahydrate acetate as the precursor in the presence of methanol solvent. Methyl 3-hydroxypropionate was synthesized via hydroesterification of ethylene oxide(EO) catalyzed by NaCo(CO)_4. The influencing factors on the reaction results were discussed, including the different ligands, the molar ratio of solvent and ethylene oxide, the reaction temperature, the reaction time, and the reaction pressure. An optimal catalytic system was obtained by using 3-hydroxypyridine as the ligand under reaction conditions covering a reaction temperature 65 °C, a reaction time of 7 h, a reaction pressure of 6 MPa, and a methanol/EO molar ratio of 3:2. Under the optimal conditions, the conversion of ethylene oxide was equal to 97.86%, while the selectivity and yield of methyl 3-hydroxypropionate reached 88.19% and 86.30%, respectively. Finally, the reaction mechanism of hydroesterification of ethylene oxide catalyzed by NaCo(CO)_4 was proposed.

土壤固碳微生物的绝对定量检测实验设计

为了定量检测土壤中的固碳微生物,设计以功能基因cbbL为靶标的固碳微生物微滴数字聚合酶链式反应(ddPCR)检测方法。选择合适的引物探针,从退火温度、探针浓度以及引物浓度进行反应条件的优化,分析ddPCR检测方法的线性范围、敏感性、重复性和特异性。结果显示,当退火温度为55.8℃、探针与引物浓度分别为350、750 nmol/L时,建立的cbbL-ddPCR扩增反应效率最高,阴阳性微滴分布界限最明显,平均拷贝数较高;检测的线性范围为2.3×10^(0)~2.3×10^(5)copies/μL-DNA,曲线方程y=0.1077x-95.562,相关系数R^(2)为0.9997,检出限为0.5 copy/μL-DNA,21个重复的变异系数仅为3.92%,与其他4种非固碳微生物DNA未发生交叉反应。所建立的cbbL-ddPCR方法可用于土壤微生物固碳潜能测定。