Coupling boron-modulated bimetallic oxyhydroxide with photosensitive polymer enable highly-active and ultra-stable seawater splitting

Seawater photoelectrolysis is showing huge potential in green energy conversion field,yet it is still a formidable challenge to develop one catalyst that can drive the electrolysis reaction stably,economically and efficiently.Motivated by this point,the inorganic–organic hybridization strategy is proposed to insitu construct one hierarchical electrode via concurrent electroless plating and polymerization,which assures the growth of boron-modulated nickel–cobalt oxyhydroxide nanoballs and photosensitive polyaniline nanochains on the self-supporting Ti-based foil(B-Co Ni OOH/PANI@TiO_(2)/Ti).Upon inducing photoelectric effect(PEE),the designed target electrode delivers overpotentials as low as 196 and 398 mV at 100 mA cm^(-2)for hydrogen evolution reaction(HER)and oxygen evolution reaction(OER),respectively,corresponding to an activity enhancement by about 15%as compared to those without PEE.Inspiringly,when served as bifunctional electrocatalysts for overall seawater electrolysis,it can stably maintain at 200 mA cm^(-2)with negligible decay over 72 h.Further analysis reveals that the exceptional catalytic performance can be credit to the B-CoNiOOH,polyaniline(PANI)and TiO_(2)subunit coupling-induced physically and chemically synergistic catalysis effect such as admirable composition stability,photoelectric function and adhesion capability.The finding in this contribution may trigger much more broad interest to the novel hybrid catalysts consisting of photosensitive polymer and transition metal-based electrocatalysts.

Error-space estimate method for generalized synergic target tracking

To improve the tracking accuracy and stability of an optic-electronic target tracking system,the concept of generalized synergic target and an algorithm named error-space estimate method is presented.In this algorithm,the motion of target is described by guide data and guide errors,and then the maneuver of the target is separated into guide data and guide errors to reduce the maneuver level.Then state estimate is implemented in target state-space and error-space respectively,and the prediction data of target position are acquired by synthesizing the filtering data from target state-space according to kinematic model and the prediction data from errorspace according to guide error model.Differing from typical multi-model method,the kinematic and guide error models work concurrently rather than switch between models.Experiment results show that the performance of the algorithm is better than Kalman filter and strong tracking filter at the same maneuver level.