Bin Tan

Biological systems often involve cascading molecular signals; for example, blood coagulation involves a cascade of serial and parallel reactions catalyzed by enzymes. The present study draws inspiration from such complex biological systems to demonstrate, through a simple example, the purposeful design of a cascade system that enables control over polymer degradation kinetics. Micron size fibers of polylactide (PLA), cellulose acetate (CA), and their mixtures are subjected to hydrolysis at varying temperatures. Cleavage of the PLA produces an organic acid functional group that catalyzes the CA hydrolysis, thus demonstrating the use of synthetic molecular signaling. Furthermore, the presence of CA inhibits the degradation of PLA thereby demonstrating molecular feedback, another hallmark of biological molecular cascades. The parallel reaction cascade causes the hydrolysis rate constant for CA to increase 3.1 times compared to CA alone (from 5.7 × 10^-4 to 1.78 × 10^-3 L² mol^-2 h^-1 at 125 °C); furthermore, due to molecular feedback, the hydrolysis rate constant for PLA decreases by 21% (from 2.40 × 10^-3 to 1.90 × 10^-3 L² mol^-2 h^-1). The results demonstrate that synthetic signaling enables exquisitely tunable degradation kinetics. Technological applications of such purposely designed biomimetic systems are wide ranging and include the design of polymer systems for hydraulic fracturing, for biomedical applications, and for facilitating the recycling of mixed plastic wastes.

While wearable self-powered electronic devices have shown promising improvements, substantial challenges persist in enhancing their electrical output and structural performance. In this work, a working mechanism involving simultaneous piezoelectric and triboelectric conversion within a monolayer-structured membrane is proposed. Single-layer binary fiber nanocomposite membranes (SBFNMs) (PVDF/CNT_X@PAN/CNT_X, DPCPC_X) with two distinct interpenetrating nanocomposite fibers were created through co-electrospinning, incorporating multiwalled carbon nanotubes (CNTs) into polyvinylidene fluoride (PVDF) and polyacrylonitrile (PAN), respectively. The resulting membrane demonstrated an exceptional synergistic effect of piezoelectricity and triboelectricity along with a high machine-to-electric conversion capability. The addition of CNTs increased the PVDF β-phase and the PAN planar zigzag conformation. As a result, the DPCPC_0.5-SBFNMs-based piezoelectric nanogenerator exhibited excellent electrical output (187 V, 8.0 μA, and 1.52 W m^-2), maintaining an exceptionally high level of output voltage compared with other piezoelectric nanogenerators. It successfully illuminated 50 commercial light-emitting diodes simultaneously. The output voltage of DPCPC_0.5-SBFNMs was 5.1 and 4.6 times higher than that of PAN or PVDF single-fiber membranes, respectively. Furthermore, the peak voltage of DPCPC_0.5-SBFNMs exceeded that of co-electrospinning PVDF/CNT_1.0@PAN (DPCP_1.0) and PVDF@PAN/CNT_1.0 (DPPC_1.0) by 20 and 10 V, respectively. The piezoelectric sensor made of DPCPC_0.5-SBFNMs accurately sensed human movement, ranging from tiny to large, and demonstrated utility as an alarm in medical treatment, fire fighting, and monitoring. Endogenous triboelectricity is proposed in SBFNM piezoelectric materials, enhancing electromechanical conversion and electrical output capacity, thereby promising a wide application potential in self-powered wearable electronic devices.

Current acoustic modeling methods face problems such as complex processes or inaccurate sound absorption coefficients, etc. Therefore, this paper studies the topic. Firstly, the material samples were prepared, and standing wave tube method experiments were conducted. Material acoustic data were obtained, while a model using improved genetic algorithm and neural network was subsequently proposed. Secondly, the acoustic data obtained from the experiment were analyzed; a neural network structure was designed; and the training, verification, and test data were all divided. In order to facilitate data processing, a symmetrical method was used to inversely normalize all the data. Thirdly, by the design of real coding scheme, fitness function, crossover, and mutation operators, an improved genetic algorithm was proposed to obtain the optimal solution, as the initial weight and threshold, which were then input into the neural network along with the training and verification data. Finally, the test data were input into the trained neural network in order to test the model. The test results and statistical analysis showed that compared with other algorithms, the proposed model has the lower root mean squared error (RMSE) value, the maximum coefficient of determination (R²) value, and shorter convergence time.

Polyvinylidene fluoride (PVDF) and poly(methyl methacrylate) (PMMA) blend films were prepared using biaxial stretching. The effects of PMMA content and stretching ratio on the crystallinity and β phase fraction of PVDF in blend films were investigated. The distributions of crystallinity and β phase fraction on variable locations were also studied. The results of FTIR and XRD showed that β phase appeared in PVDF/PMMA blends after extrusion and casting procedures. Although β phase fraction decreased after preheating, there was still an increasing trend during following biaxial stretching. More importantly, the increase in PMMA content improved β phase fraction, and the highest β phase fraction of 93% was achieved at PMMA content of 30 wt% and stretching ratio of 2×2. Besides, the reduction in PMMA content and the increase in stretching ratio improved the crystallinity of PVDF. The mechanical properties of the stretched films were significantly improved by increasing the stretching ratio as well. The uniform stress distribution on different regions of biaxial stretching films contributed to the uniform distribution of β phase fraction and crystallinity of PVDF with the aid of simulation. This work confirmed that biaxial stretching can be a candidate method to prepare PVDF/PMMA blend films with uniform distributions of comparable β phase and crystallinity of PVDF.