Wafer-scale quasi-layered tungstate-doped polypyrrole film with high volumetric capacitance

Layered materials are particularly attractive for supercapacitors because of their unique physical,electrical and chemical properties.Here,we demonstrate a facile and scalable electrochemical deposition method for wafer-scale synthesis of quasilayered tungstate-doped polypyrrole films(named TALPy)with controllable thickness and size.The as-prepared TALPy film exhibits a high gravimetric density and excellent volumetric capacitance,exceeding many high-performing carbon-and polymerbased film electrodes.Based on combined results of ex-situ X-ray diffraction(XRD),Raman and X-ray photoelectron spectroscopy(XPS),it is determined that TALPy stores charge through an ion intercalation process accompanied by change in oxidation states of polypyrrole backbone,which is referred as intercalation pseudocapacitance.All these results suggest the great promise of electrochemical deposition as a scalable and controllable bottom-up approach for synthesizing quasi-layered conductive organic-inorganic hybrid films for electrochemical energy storage applications with high volumetric performance.

Robust state estimation for uncertain linear discrete systems with d-step measurement delay and deterministic input signals

In this study,the state estimation problems for linear discrete systems with uncertain parameters,deterministic input signals and d-step measurement delay are investigated.A robust state estimator with a similar iterative form and comparable computational complexity to the Kalman filter is derived based on the state augmentation method and the sensitivity penalisation of the innovation process.It is discussed that the steady-state properties such as boundedness and convergence of the robust state estimator under the assumptions that the system parameters are time invariant.Numerical simulation results show that compared with the Kalman filter,the obtained state estimator is more robust to modelling errors and has nice estimation accuracy.

An integrated nanocarbon–cellulose membrane for solid-state supercapacitors

In this work, we demonstrate the assembly of oxidised carbon nanohybrids(o CNHs) with a commercial cellulose membrane for solid-state supercapacitors. The o CNHs–cellulose membranes were prepared by filtering a water dispersion of o CNHs through the cellulose membrane. The o CNHs were derived from carbon nanotubes via a modified Hummer's method and contained both closed tubes and unzipped tubes, which indicated a hybrid geometrical structure. The solid-state supercapacitor based on the o CNHs–cellulose membranes showed a high areal capacitance of *75 m F/cm^2 at a low scan rate(5 m V/s)and excellent stability for 1,000 cycles.

Robust state estimation for uncertain linear systems with deterministic input signals

In this paper, we investigate state estimations of a dynamical system in which not only process and measurement noise, but also parameter uncertainties and deterministic input signals are involved. The sensitivity penalization based robust state estimation is extended to uncertain linear systems with deterministic input signals and parametric uncertainties which may nonlinearly affect a state-space plant model. The form of the derived robust estimator is similar to that of the well-known Kalman filter with a comparable computational complexity. Under a few weak assumptions, it is proved that though the derived state estimator is biased, the bound of estimation errors is finite and the covariance matrix of estimation errors is bounded. Numerical simulations show that the obtained robust filter has relatively nice estimation performances.

An event-triggered approach to robust state estimation for wireless sensor networks

Robust state estimation problem for wireless sensor networks consisting of multiple remote units and a fusion unit is investigated subject to a limitation on the communication rate.An analytical robust fusion estimator based on an event-triggered transmission approach is derived to reduce the network traffic congestion and save the energy consumption of the sensor units.Some conditions guaranteeing the uniformly bounded estimation errors of the robust fusion estimator are investigated.Numerical simulations are provided to show the effectiveness of the proposed approach.