Superparaelectrics are considered promising candidate materials for achieving superior energy storage capabilities. However, due to the complicated local structural design, simultaneously achieving high recoverable energy density (W_rec) and energy storage efficiency (η) under high electric fields remains a challenge in bulk superparaelectrics. Here, we propose utilizing entropy engineering to disrupt long-range ferroic orders into local polymorphic distortion disorder with multiple BO₆ tilt types and diverse heterogeneous polarization configurations. This strategy reduces the switching barriers, thereby facilitating the emergence of superparaelectric behaviors with ideal polarization forms. Furthermore, it enables high polarization response, negligible remnant polarization, delayed polarization saturation, and enhanced breakdown electric fields (E_b) in high-entropy superparaelectrics. Consequently, an extraordinary W_rec of 15.48 J cm^–3 and an ultrahigh η of 90.02% are achieved at a high E_b of 710 kV cm^–1, surpassing the comprehensive energy storage performance of previously reported bulk superparaelectrics. This work demonstrates that entropy engineering is a viable strategy for designing high-performance superparaelectrics.

Ferroelectric materials have been a key research topic owing to their wide variety of modern electronic and photonic applications. For the quick exploration of higher operating speed, smaller size, and superior efficiencies of novel ferroelectric devices, the ultrafast dynamics of ferroelectrics that directly reflect their respond time and lifetimes have drawn considerable attention. Driven by time‐resolved pump‐probe spectroscopy that allows for probing, controlling, and modulating dynamic processes of ferroelectrics in real‐time, much research efforts have been made to understand and exploit the ultrafast dynamics of ferroelectric. Herein, the current state of ultrafast dynamic features of ferroelectrics tracked by time‐resolved pump‐probe spectroscopy is reviewed, which includes ferroelectrics order parameters of polarization, lattice, spin, electronic excitation, and their coupling. Several potential perspectives and possible further applications combining ultrafast pump‐probe spectroscopy and ferroelectrics are also presented. This review offers a clear guidance of ultrafast dynamics of ferroelectric orders, which may promote the rapid development of next‐generation devices.

Memristors offer great advantages as a new hardware solution for neuromorphic computing due to their fast and energy‐efficient matrix vector multiplication. However, the nonlinear weight updating property of memristors makes it difficult to be trained in a neural network learning process. Several compensation schemes have been proposed to mitigate the updating error caused by nonlinearity; nevertheless, they usually involve complex peripheral circuits design. Herein, stochastic and adaptive learning methods for weight updating are developed, in which the inaccuracy caused by the memristor nonlinearity can be effectively suppressed. In addition, compared with the traditional nonlinear stochastic gradient descent (SGD) updating algorithm or the piecewise linear (PL) method, which are most often used in memristor neural network, the design is more hardware friendly and energy efficient without the consideration of pulse numbers, duration, and directions. Effectiveness of the proposed method is investigated on the training of LeNet‐5 convolutional neural network. High accuracy, about 93.88%, on the Modified National Institute of Standards and Technology handwriting digits datasets is achieved (with typical memristor nonlinearity as ±1), which is close to the network with complex PL method (94.7%) and is higher than the original nonlinear SGD method (90.14%).

Domain orientations and their volume ratios in ferroelectrics are recognized as a compelling topic recently for domain switching dynamics and domain stability in devices application. Here, an optimized second harmonic generation method has been explored for ferroelectric domain characterization. Combing a unique theoretical model with azimuth-polarization-dependent second harmonic generation response, the complex domain components and their distributions can be rigidly determined in ferroelectric thin films. Using the proposed model, the domain structures of rhombohedral BiFeO₃ films with 71° and 109° domain wall, and, tetragonal BiFeO₃, Pb(Zr_0.2Ti_0.8)O₃, and BaTiO₃ ferroelectric thin films are analyzed and the corresponding polarization variants are determined. This work could provide a powerful and all-optical method to track and evaluate the evolution of ferroelectric domains in the ferroelectric-based devices.