Energy storage efficiency (η) and large recoverable energy density (W_re) are necessary for antiferroelectric materials in order to develop antiferroelectric-based dielectric capacitors with exceptional energy storage capacity. In the present paper, the effect of doping La³⁺ on the energy storage capacity of Pb_1−xLa_x(Hf_0.45Sn_0.55)_0.995O₃ antiferroelectric ceramics was studied. Adjusting the content of La and changing the phase structure of PLHS from antiferroelectric to relaxor ferroelectric gradually, which narrowed its hysteresis loop, yielded a high energy storage efficiency of 81.9% and the maximum breakdown field strength of 200 kV/cm when x = 2 mol%. In addition, the recoverable energy density and energy storage efficiency both showed excellent temperature stability and frequency stability in the temperature range of 10–110 °C and the frequency range of 10–100 Hz, suggesting that Pb_0.98La_0.02(Hf_0.45Sn_0.55)_0.995O₃ are favorable materials candidates for the preparation of pulsed-power capacitors that can be used in a wide range of conditions.

Dielectric capacitors with a high density of recoverable energy storage are extremely desirable for a variety of uses. However, these capacitors often exhibit lower breakdown strengths and energy efficiency compared to other materials, which poses significant challenges for their practical use. We report on a novel antiferroelectric ceramic system in the present study, (1 − x){0.97[0.985(0.93Bi_0.5Na_0.5TiO₃–0.07BaTiO₃)–0.015Er)]–0.03AlN}–xNaNbO₃ (x = 0, 10 wt%, 20 wt%, 30 wt%, and 40 wt%), synthesized via a conventional solid-state reaction approach. Here, (Bi_0.5Na_0.5TiO₃–BaTiO₃) is denoted as BNT–BT. We observed that varying the NaNbO₃ (NN) content gradually refined the grain size of the ceramics, narrowed their hysteresis loops, and transformed their phase structure from antiferroelectric to relaxor ferroelectric. These changes enhanced breakdown strength (E_b), thus increasing the performance of energy storage. Specifically, the recoverable energy density (W_rec) and energy storage efficiency (η), respectively, reached 0.67–1.06 J/cm³ and 44–88% at electric fields of 110–155 kV/cm, with the highest performance observed at 30 wt% NN doping. Additionally, over a broad range of temperature and frequency, the 70 wt% {0.97[0.985(BNT–BT)–0.015Er]–0.03AlN}–30 wt% NN ceramic demonstrated exceptional stability in energy storage. These results demonstrate the significant potential of lead-free(1 − x)({0.97[0.985(BNT–BT)–0.015Er]–0.03AlN}–xNN ceramics for the applications of high-performance energy storage.

NaNbO₃-based ferroelectric composites are regarded as a highly promising typical energy storage material. In this work, 0.02xMnO₂−(1−x)NaNbO₃−xBi0.5Na_0.5TiO₃ composites were prepared by the solid-state sintering method and their microstructure, energy storage performance, and temperature stability were analyzed. As observed by the SEM images, the addition of Bi_0.5Na_0.5TiO₃ to NaNbO₃ in appropriate amounts can effectively suppress grain growth, which is beneficial for improving the breakdown field strength. When x = 0.3, an optimal value of 210 kV/cm is achieved. Meanwhile, as 2θ = 33.2°, the most intense XRD peak can be observed, indicating excellent solid solubility between the phase components. Consequently, 0.006MnO₂–0.7NaNbO₃–0.3Bi_0.5Na_0.5TiO₃ composites demonstrated an impressive discharging storage density of 2.464 J/cm³ and a considerable energy storage efficiency of 85.8%. In addition, within the temperature range of 30–80 °C, the fluctuation in energy storage density remains below 10%. All the above performances indicate that this type of material exhibits excellent practicality in the field of pulse power supply.

(Bi_0.5Na_0.5)TiO₃-based lead-free ferroelectric ceramics are among the most extensively researched energy storage materials today. In this paper, (1 − x)Bi_0.46Sr_0.06Na_0.5TiO_3−xCaTiO₃ ceramics were synthesized through a solid-phase sintering method by synergistically adjusting CaTiO₃ components after introducing Sr²⁺ at the A-site. The XRD patterns revealed that all samples formed a single perovskite solid solution, with the 111 and 200 peaks shifting to higher levels as the CaTiO₃ increased, indicating a gradual decrease in cell volume. The SEM images exhibited dense crystals without any apparent porosity, which were formed by the different components of the ceramics. Through energy storage, dielectric, and charge–discharge performance tests, it was found that with a 10%mol CaTiO₃ addition, the samples obtained a maximum breakdown field strength of 260 kV/cm and corresponding saturation polarization strength of 32.80 μC/cm² and thereby exhibited a reversible energy storage density valued 3.52 J/cm³. In addition, the dielectric constant varied by less than 10% within the temperature range of 63.7 °C to 132.7 °C and presented good frequency (10–250 Hz) stability at 180 kV/cm. Moreover, the ceramics demonstrated a maximum current density reaching 349.58 A/cm² and a maximum power density of 18.90 MW/cm³ for their charge–discharge performance, all of which makes them suitable for pulse system applications.

Imaginary handwriting is an important research paradigm in the field of brain-controlled typing. Neural signals exhibit high complexity, low signal-to-noise ratio, and strong temporal and environmental variability, leading to significant inter-trial differences in the temporal dynamics of character-related signals. These factors pose significant challenges for segmenting character-related signals and accurately decoding imaginary handwriting. To address these issues, this study proposes a Dynamic Time Warping Independent Component Analysis (DTWICA) framework. This framework employs FastDTW to construct individualized warping functions for each trial, followed by FastICA-based decomposition to separate the signal into distinct temporal and neuronal factors. The decomposed temporal factors are then mapped and transformed using the warping function and subsequently merged with the neuronal factors to reconstruct the signal. A sliding time window is then applied for adaptive processing, yielding the transformed signal. Finally, the transformed signals from multiple trials are averaged to generate a template for each character. Results based on a publicly available neural signals dataset for imaginary handwriting indicate that, compared with mainstream time warping models such as Shift, Linear, Piecewise, and TWPCA, the proposed model improves the character decoding accuracy for 31 characters by 14%, 13%, 7%, and 2%, respectively. This study not only constructs effective character signal templates but also facilitates accurate character segmentation during unlabeled imagined typing in an offline setting, providing a promising methodological basis for future real-time imagined typing decoding systems.