Adaptive Lag Smoother for State Estimation.

Fixed-lag smoothing has been used across different disciplines for offline analysis in many applications. With rising computational power and parallel processing architectures, fixed-lag smoothers are increasingly integrated into online processing system with small delays. This delay is directly related to the lag-length used in system design, which needs to be chosen appropriately. In this work, an adaptive approach is devised to choose an appropriate lag-length that provides a good trade-off between accuracy and computational requirements. The analysis shown in this paper for the error dynamics of the fixed-lag smoother over the lags helps in understanding its saturation over increasing lags. In order to provide the empirical results, simulations are carried out over a second-order Newtonian system, single-axis attitude estimation, Van der Pol's oscillator, and three-axis attitude estimation. The simulation results demonstrate the performance achieved with an adaptive-lag smoother as compared to a fixed-lag smoother with very high lag-length.

Incremental learning of LSTM framework for sensor fusion in attitude estimation.

This paper presents a novel method for attitude estimation of an object in 3D space by incremental learning of the Long-Short Term Memory (LSTM) network. Gyroscope, accelerometer, and magnetometer are few widely used sensors in attitude estimation applications. Traditionally, multi-sensor fusion methods such as the Extended Kalman Filter and Complementary Filter are employed to fuse the measurements from these sensors. However, these methods exhibit limitations in accounting for the uncertainty, unpredictability, and dynamic nature of the motion in real-world situations. In this paper, the inertial sensors data are fed to the LSTM network which are then updated incrementally to incorporate the dynamic changes in motion occurring in the run time. The robustness and efficiency of the proposed framework is demonstrated on the dataset collected from a commercially available inertial measurement unit. The proposed framework offers a significant improvement in the results compared to the traditional method, even in the case of a highly dynamic environment. The LSTM framework-based attitude estimation approach can be deployed on a standard AI-supported processing module for real-time applications.

Cascaded Complementary Filter Architecture for Sensor Fusion in Attitude Estimation.

Attitude estimation is the process of computing the orientation angles of an object with respect to a fixed frame of reference. Gyroscope, accelerometer, and magnetometer are some of the fundamental sensors used in attitude estimation. The orientation angles computed from these sensors are combined using the sensor fusion methodologies to obtain accurate estimates. The complementary filter is one of the widely adopted techniques whose performance is highly dependent on the appropriate selection of its gain parameters. This paper presents a novel cascaded architecture of the complementary filter that employs a nonlinear and linear version of the complementary filter within one framework. The nonlinear version is used to correct the gyroscope bias, while the linear version estimates the attitude angle. The significant advantage of the proposed architecture is its independence of the filter parameters, thereby avoiding tuning the filter's gain parameters. The proposed architecture does not require any mathematical modeling of the system and is computationally inexpensive. The proposed methodology is applied to the real-world datasets, and the estimation results were found to be promising compared to the other state-of-the-art algorithms.

Perpendicular magnetic anisotropy in half-metallic thin-film Co2CrAl.

Magnetocrystalline anisotropy (MCA) is one of the key parameters investigated in spin-based electronics (spintronics), e.g. for memory applications. Here, we employ first-principles calculations to study MCA in thin film full Heusler alloy Co2CrAl. This material was studied in the past, and has been reported to exhibit half-metallic electronic structure in bulk geometry. In our recent work, we showed that it retains a 100% spin-polarization in thin-film geometry, at CrAl atomic surface termination. Here, we show that the same termination results in a perpendicular magnetic anisotropy, while Co surface termination not only destroys the half-metallicity, but also results in in-plane magnetization orientation. In addition, for films thicker than around 20 nm the contribution from magnetic shape anisotropy may become decisive, resulting in in-plane magnetization orientation. To the best of our knowledge, this is one of the first reports of half-metallic thin-film surfaces with perpendicular magnetic anisotropy. This result may be of interest for potential nano-device applications, and may stimulate a further experimental study of this and similar materials.

Room-Temperature Magnetic Switching of the Electric Polarization in Ferroelectric Nanopillars.

Magnetoelectric layers with a strong coupling between ferroelectricity and ferromagnetism offer attractive opportunities for the design of new device architectures such as dual-channel memory and multiresponsive sensors and actuators. However, materials in which a magnetic field can switch an electric polarization are extremely rare, work most often only at very low temperatures, and/or comprise complex materials difficult to integrate. Here, we show that magnetostriction and flexoelectricity can be harnessed to strongly couple electric polarization and magnetism in a regularly nanopatterned magnetic metal/ferroelectric polymer layer, to the point that full reversal of the electric polarization can occur at room temperature by the sole application of a magnetic field. Experiments supported by finite element simulations demonstrate that magnetostriction produces large strain gradients at the base of the ferroelectric nanopillars in the magnetoelectric hybrid layer, translating by flexoelectricity into equivalent electric fields larger than the coercive field of the ferroelectric polymer. Our study shows that flexoelectricity can be advantageously used to create a very strong magnetoelectric coupling in a nanopatterned hybrid layer.

Statics and Dynamics of Ferroelectric Domains in Diisopropylammonium Bromide.

An electrically written domain structure formed by a biased tip, and visualized in the piezoresponse force microscopy mode, shows stable charged domain walls in the organic ferroelectric diisopropylammonium chloride microcrystal.

Acute polyradiculoneuropathy following honey bee sting.

Neurological complications following honey bee sting are rare. We report a case of a 3-year-old girl who developed acute polyradiculoneuropathy following honey bee sting, which was diagnosed by nerve conduction studies.

Tuning the energy level offset between donor and acceptor with ferroelectric dipole layers for increased efficiency in bilayer organic photovoltaic cells.

Ultrathin ferroelectric polyvinylidene fluoride (70%)-tetrafluoroethylene (30%) copolymer film is inserted between the poly3(hexylthiophene) (P3HT) donor and [6,6]-phenyl-C61-butyric acid methylester (PCBM) acceptor layers as the dipole layer to tune the relative energy levels, which can potentially maximize the open circuit voltage of bilayer organic solar cells. In this work, the power conversion efficiency of P3HT/PCBM bilayer solar cells is demonstrated to be doubled with the inserted dipoles.

Efficiency enhancement in organic solar cells with ferroelectric polymers.

The recombination of electrons and holes in semiconducting polymer-fullerene blends has been identified as a main cause of energy loss in organic photovoltaic devices. Generally, an external bias voltage is required to efficiently separate the electrons and holes and thus prevent their recombination. Here we show that a large, permanent, internal electric field can be ensured by incorporating a ferroelectric polymer layer into the device, which eliminates the need for an external bias. The electric field, of the order of 50 V µm(-1), potentially induced by the ferroelectric layer is tens of times larger than that achievable by the use of electrodes with different work functions. We show that ferroelectric polymer layers enhanced the efficiency of several types of organic photovoltaic device from 1-2% without layers to 4-5% with layers. These enhanced efficiencies are 10-20% higher than those achieved by other methods, such as morphology and electrode work-function optimization. The devices show the unique characteristics of ferroelectric photovoltaic devices with switchable diode polarity and tunable efficiency.