Synthesis of Starch-Stabilized Ag Nanoparticles and Hg2+Recognition in Aqueous Media

The starch-stabilized Ag nanoparticles were successfully synthesized via a reduction approach and characterized with SPR UV/Vis spectroscopy, TEM, and HRTEM. By utilizing the redox reaction between Ag nanoparticles and Hg2+, and the resulted decrease in UV/Vis signal, we develop a colorimetric method for detection of Hg2+ion. A linear relationship stands between the absorbance intensity of the Ag nanoparticles and the concentration of Hg2+ion over the range from 10 ppb to 1 ppm at the absorption of 390 nm. The detection limit for Hg2+ions in homogeneous aqueous solutions is estimated to be ~5 ppb. This system shows excellent selectivity for Hg2+over other metal ions including Na+, K+, Ba2+, Mg2+, Ca2+, Fe3+, and Cd2+. The results shown herein have potential implications in the development of new colorimetric sensors for easy and selective detection and monitoring of mercuric ions in aqueous solutions

Feedback control algorithms for the dissipation of traffic waves with autonomous vehicles

International audienceThis article considers the problem of traffic control in which an autonomous vehicle is used to regulate human piloted traffic to dissipate stop and go traffic waves. We first investigate the controllability of well-known microscopic traffic flow models, namely i) the Bando model (also known as the optimal velocity model), ii) the follow-the-leader model, and iii) a combined optimal velocity follow the leader model. Based on the controllability results, we propose three control strategies for an autonomous vehicle to stabilize the other, human-piloted traffic. We subsequently simulate the control effects on the microscopic models of human drivers in numerical experiments to quantify the potential benefits of the controllers. Based on the simulations, finally we conduct a field experiment with 22 human drivers and a fully autonomous-capable vehicle, to assess the feasibility of autonomous vehicle based traffic control on real human piloted traffic. We show that both in simulation and in the field test that an autonomous vehicle is able to dampen waves generated by 22 cars, and that as a consequence, the total fuel consumption of all vehicles is reduced by up to 20%