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Quantification of the amount of intermolecular hydrogen bonding between ferrocenemethanol and 3-mercaptopropanoic acid on gold was performed by cyclic voltammetry as well as by the finite element simulation, displaying a proof-of-concept that the slight changes of cyclic voltammetry features are used potentially for interpreting the weak molecular interactions. Ferrocenemethanol at a bulk concentration level of 0.5 mM adsorbs on the 3-mercaptopropanoic acid surface by hydrogen bonding, with the fractional surface coverage ranging from 0% to 14% of a monolayer in accordance with the surface coverage of 3-mercaptopropanoic acid which was explored by electrochemical quartz crystal microbalance. The intermolecular hydrogen bonding between ferrocenemethanol and the mercaptopropanoic acid was found to exhibit a Langmuir-type adsorption with the average value of K being 0.24 mM–1. The intermolecular hydrogen bonding between FcCH2OH and the artificial self-assembled monolayer (3-mercaptopropanoic acid) is evident, and the study on quantification of intermolecular hydrogen bonding with this artificial model is meaningful for understanding the molecular recognition events involved in the cell membrane.

In this work, a 3-mercaptopropionic acid self-assembled monolayer (3-MPA SAM) was constructed as a reliable artificial membrane to investigate the intermolecular forces between the SAM and the redox species using scanning electrochemical microscopy. The results presented here reveal that the redox species, FcCH 2 OH, is initially adsorbed on 3-MPA SAM by hydrogen bonding between the hydroxyl group of the former and the carboxyl group of the latter. Then, when FcCH 2 OH is transformed to Fc + CH 2 OH by electrochemical oxidation, the dominant intermolecular force in the reaction system changes from hydrogen bonding to electrostatic interaction. Increase in pH and surface coverage of the 3-MPA SAM can enhance the change behavior observed, however, adding ion strength will weaken this behavior. Our findings may help to improve the understanding of the interaction between effector proteins and phospholipid bilayer on cellular surface.

Floorplanning is an important problem in the very large integrated circuit (VLSI) design automation. It's an NP-hard combinatorial optimization problem. The Particle Swarm Optimization (PSO) has been proved to be a good optimization algorithm with outstanding global performance. However, PSO cannot be directly used in the combinatorial optimization problem due to its continuous characterisic. In this paper a novel floorplanning algorithm based on Discrete PSO (DPSO) algorithm is proposed, in which integer coding based on module number was adopted. The principles of mutation and crossover operator in the Genetic Algorithm (GA) are also incorporated into the proposed PSO algorithm to achieve better diversity and break away from local optima. Experiments employing MCN and GSRC benchmarks show that the performance of our proposed algorithm for placement is good. The proposed algorithm can avoid the solution from falling into local minimum and have good convergence performance.

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