Plasmonic Bubbles in n-Alkanes

In this paper we study the formation of microbubbles upon the irradiation of an array of plasmonic Au nanoparticles with a laser in n-alkanes ($C_{n}H_{2n+2}$, with n = 5-10). Two different phases in the evolution of the bubbles can be distinguished. In the first phase, which occurs after a delay time {\tau}d of about 100 {\mu}s, an explosive microbubble, reaching a diameter in the range from 10 {\mu}m to 100 {\mu}m, is formed. The exact size of this explosive microbubble barely depends on the carbon chain length of the alkane, but only on the laser power $P_l$. With increasing laser power, the delay time prior to bubble nucleation as well as the size of the microbubble both decrease. In the second phase, which sets in right after the collapse of the explosive microbubble, a new bubble forms and starts growing due to the vaporization of the surrounding liquid, which is highly gas rich. The final bubble size in this second phase strongly depends on the alkane chain length, namely it increases with decreasing number of carbon atoms. Our results have important implications for using plasmonic heating to control chemical reactions in organic solvents

cis-Diaqua­bis(2,2′,2′′-tripyridylamine)zinc(II) bis­(perchlorate)

In the title compound, [Zn(2,2′,2′′-tpa)2(H2O)2](ClO4)2 (2,2′,2′′-tpa is 2,2′,2′′-tripyridylamine, C15H12N4), the Zn center lies on a twofold axis and is coordinated octa­hedrally by two water mol­ecules and two bidentate 2,2′,2′′-tpa ligands. The perchlorate anions are linked to the coordinated water mol­ecules in the complex cations via O—H⋯O hydrogen bonds

Test-Sheet Composition Using Analytic Hierarchy Process and Hybrid Metaheuristic Algorithm TS/BBO

Due to the shortcomings in the traditional methods which dissatisfy the examination requirements in composing test sheet, a new method based on tabu search (TS) and biogeography-based optimization (BBO) is proposed. Firstly, according to the requirements of the test-sheet composition such as the total score, test time, chapter score, knowledge point score, question type score, cognitive level score, difficulty degree, and discrimination degree, a multi constrained multiobjective model of test-sheet composition is constructed. Secondly, analytic hierarchy process (AHP) is used to work out the weights of all the test objectives, and then the multiobjective model is turned into the single objective model by the linear weighted sum. Finally, an improved biogeography-based optimization—TS/BBO is proposed to solve test-sheet composition problem. To prove the performance of TS/BBO, TS/BBO is compared with BBO and other population-based optimization methods such as ACO, DE, ES, GA, PBIL, PSO, and SGA. The experiment illustrates that the proposed approach can effectively improve composition speed and success rate

Solvent Exchange in a Hele-Shaw Cell Universality of Surface Nanodroplet Nucleation

Solvent exchange (also called solvent shifting or Ouzo effect) is a generally used bottom-up process to mass-produce nanoscale droplets. In this process, a good solvent for some oil is displaced by a poor one, leading to oil nanodroplet nucleation and subsequent growth. Here we perform this process on a hydrophobic substrate so that sessile droplets so-called surface nanodroplets-develop, following the work of Zhang et al. [Zhang, X.; Lu, Z.; Tan, H.; Bao, L.; He, Y.; Sun, C.; Lohse, D. Proc. Natl. Acad. Sci. U.S.A. 2015, 122, 9253-9257]. In contrast to what was done in that paper, we chose a very well-controlled Hele-Shaw geometry with negligible gravitational effects, injecting the poor solvent in the center of the Hele-Shaw cell, and characterize the emerging nanodroplets as a function of radial distance and flow rates. We find that the mean droplet volume per area _area strongly depends on the local Peclet number Pe and follows a universal scaling law _area~Pe^(3/4). Moreover, the probability distribution function of the droplet volume strongly depends on the local Pe as well, regardless of the flow rates and radial distance, giving strong support to the theoretical model of the solvent exchange process developed in Zhang et al.'s work.Comment: 6 pages, 5 figure