An electromechanical stimulation regulating model with flexoelectric effect of piezoelectric laminated micro-beam for cell bionic culture.

Cell bionic culture requires the construction of cell growth microenvironments. In this paper, mechanical force and electrical stimulations are applied to the cells cultured on the surface of the piezoelectric laminated micro-beam driven by an excitation voltage. Based on the extended dielectric theory, the electromechanical microenvironment regulating model of the current piezoelectric laminated micro-beam is established. The variational principle is used to obtain the governing equations and boundary conditions. The differential quadrature method and the iterative method are used to solve two boundary value problems for cantilever beams and simply supported beams. In two cases, the mechanical force and electrical stimulations applied to the cells are analyzed in detail and the microscale effect is investigated. This study is meaningful for improving the quality of cell culture and promoting the cross-integration of mechanics and biomedicine.

Parameter Optimization for Printing Barium Titanate Piezoelectric Ceramics through Digital Light Processing.

Digital light processing (DLP) technology has emerged as a promising 3D printing technology with the potential for the efficient manufacturing of complex ceramic devices. However, the quality of printed products is highly dependent on various process parameters, including slurry formulation, heat treatment process, and poling process. This paper optimizes the printing process with respect to these key parameters, such as using a ceramic slurry with 75 wt% powder content. The employed degreasing heating rate is 4 °C/min, the carbon-removing heating rate is 4 °C/min, and the sintering heating rate is 2 °C/min for heat treatment of the printed green body. The resulting parts are polarized using a poling field of 10 kV/cm, a poling time of 50 min, and a poling temperature of 60 °C, which yields a piezoelectric device with a high piezoelectric constant of 211 pC/N. To demonstrate the practical application of the device, its use as a force sensor and magnetic sensor is validated.

Effect of Strontium Substitution on the Tribocatalytic Performance of Barium Titanate.

This study investigates the impact of Sr doping on the tribocatalytic performance of BaTiO3 in degrading organic pollutants. Ba1-xSrxTiO3 (x = 0-0.3) nanopowders are synthesized and their tribocatalytic performance evaluated. By doping Sr into BaTiO3, the tribocatalytic performance was enhanced, resulting in an approximately 35% improvement in the degradation efficiency of Rhodamine B using Ba0.8Sr0.2TiO3. Factors such as the friction contact area, stirring speed, and materials of the friction pairs also influenced the dye degradation. Electrochemical impedance spectroscopy revealed that Sr doping improved BaTiO3's charge transfer efficiency, thereby boosting its tribocatalytic performance. These findings indicate potential applications for Ba1-xSrxTiO3 in dye degradation processes.

Improved stacking ensemble learning based on feature selection to accurately predict warfarin dose.

Background: With the rapid development of artificial intelligence, prediction of warfarin dose via machine learning has received more and more attention. Since the dose prediction involve both linear and nonlinear problems, traditional machine learning algorithms are ineffective to solve such problems at one time. Objective: Based on the characteristics of clinical data of Chinese warfarin patients, an improved stacking ensemble learning can achieve higher prediction accuracy. Methods: Information of 641 patients from southern China who had reached a steady state on warfarin was collected, including demographic information, medical history, genotype, and co-medication status. The dataset was randomly divided into a training set (90%) and a test set (10%). The predictive capability is evaluated on a new test set generated by stacking ensemble learning. Additional factors associated with warfarin dose were discovered by feature selection methods. Results: A newly proposed heuristic-stacking ensemble learning performs better than traditional-stacking ensemble learning in key metrics such as accuracy of ideal dose (73.44%, 71.88%), mean absolute errors (0.11 mg/day, 0.13 mg/day), root mean square errors (0.18 mg/day, 0.20 mg/day) and R2 (0.87, 0.82). Conclusions: The developed heuristic-stacking ensemble learning can satisfactorily predict warfarin dose with high accuracy. A relationship between hypertension, a history of severe preoperative embolism, and warfarin dose is found, which provides a useful reference for the warfarin dose administration in the future.

Superfunctionalities in nanodispersive precipitation-hardened alloys.

Although nanodispersive precipitation-hardened alloys have been intensively studied over decades as important structural materials, the possibility that these alloys may have superfunctional properties has been completely overlooked. As shown in this Letter, they may have giant low-hysteretic strain responses to external stimuli if the nanosized single-domain precipitates can switch their orientation variants under applied fields. We demonstrate that the misfit-generated coherency stress can significantly reduce the variant switching barriers and may drastically decrease or even eliminate the hysteresis of the strain super responses to external stress and/or magnetic fields. These alloys can thus be functionalized as shape memory, superelastic, and/or supermagnetostrictive materials. The conditions of such functionalization are established by the interpretation-transparent analytical calculations, and confirmed by computer prototyping. In particular, the obtained results pave the way for the engineering of rare-earth free alloys with excellent magnetomechanical and good mechanical properties.

Giant nonhysteretic responses of two-phase nanostructured alloys.

A new class of functional materials with giant nonhysteretic strain responses to applied fields is considered. They are decomposed two-phase systems consisting of single-domain nanoprecipitates of a low-symmetry phase. Their strain response is caused by the field-induced change of structural orientation of the domain states of these precipitates. The superresponse follows from the novel concept of structural anisotropy that is analogous to the magnetic anisotropy. Its vanishing produces a new glasslike structural state. The developed phase field theory and modeling allow us to formulate criteria for searching superresponsive two-phase nanostructured alloys.