Porous Nano-Fiber Structure of Modified Electrospun Chitosan GBR Membranes Improve Osteoblast Calcium Phosphate Deposition in Osteoblast-Fibroblast Co-Cultures.

Desirable characteristics of electrospun chitosan membranes (ESCM) for guided bone regeneration are their nanofiber structure that mimics the extracellular fiber matrix and porosity for the exchange of signals between bone and soft tissue compartments. However, ESCM are susceptible to swelling and loss of nanofiber and porous structure in physiological environments. A novel post-electrospinning method using di-tert-butyl dicarbonate (tBOC) prevents swelling and loss of nanofibrous structure better than sodium carbonate treatments. This study aimed to evaluate the hypothesis that retention of nanofiber morphology and high porosity of tBOC-modified ESCM (tBOC-ESCM) would support more bone mineralization in osteoblast-fibroblast co-cultures compared to Na2CO3 treated membranes (Na2CO3-ESCM) and solution-cast chitosan solid films (CM-film). The results showed that only the tBOC-ESCM retained the nanofibrous structure and had approximately 14 times more pore volume than Na2CO3-ESCM and thousands of times more pore volume than CM-films, respectively. In co-cultures, the tBOC-ESCM resulted in a significantly greater calcium-phosphate deposition by osteoblasts than either the Na2CO3-ESCM or CM-film (p < 0.05). This work supports the study hypothesis that tBOC-ESCM with nanofiber structure and high porosity promotes the exchange of signals between osteoblasts and fibroblasts, leading to improved mineralization in vitro and thus potentially improved bone healing and regeneration in guided bone regeneration applications.

Configurable direction sensitivity of skin-mounted microfluidic strain sensor with auxetic metamaterial.

Electromechanical coupling plays a key role in determining the performance of stretchable strain sensor. Current regulation of the electromechanical coupling in stretchable strain sensor is largely restricted by the intrinsic mechanical properties of the device. In this study, a microfluidic strain sensor based on the core-shell package design with the auxetic metamaterial (AM) is presented. By overriding the mechanical properties of the device, the AM in the package effectively tunes the deformation of the microfluidic channel with the applied strain and configures the directional strain sensitivity with a large modulation range. The gauge factor (GF) of the strain sensor in the radial direction of the channel can be gradually shifted from the intrinsically negative value to a positive one by adopting the AMs with different designs. By simply replacing the AM in the package, the microfluidic strain sensor with the core-shell package can be configurated as an omnidirectional or directional stretchable strain sensor. With the directional sensitivity brought by the rational AM design, the application of the AM-integrated strain sensor in the skin-mounted tactile detection is demonstrated with high tolerance to unintended wrist movements.

Reconfigurable, Stretchable Strain Sensor with the Localized Controlling of Substrate Modulus by Two-Phase Liquid Metal Cells.

Strain modulation based on the heterogeneous design of soft substrates is an effective method to improve the sensitivity of stretchable resistive strain sensors. In this study, a novel design for reconfigurable strain modulation in the soft substrate with two-phase liquid cells is proposed. The modulatory strain distribution induced by the reversible phase transition of the liquid metal provides reconfigurable strain sensing capabilities with multiple combinations of operating range and sensitivity. The effectiveness of our strategy is validated by theoretical simulations and experiments on a hybrid carbonous film-based resistive strain sensor. The strain sensor can be gradually switched between a highly sensitive one and a wide-range one by selectively controlling the phases of liquid metal in the cell array with a external heating source. The relative change of sensitivity and operating range reaches a maximum of 59% and 44%, respectively. This reversible heterogeneous design shows great potential to facilitate the fabrication of strain sensors and might play a promising role in the future applications of stretchable strain sensors.

A programmable and skin temperature-activated electromechanical synergistic dressing for effective wound healing.

Mechanical regulation and electric stimulation hold great promise in skin tissue engineering for manipulating wound healing. However, the complexity of equipment operation and stimulation implementation remains an ongoing challenge in clinical applications. Here, we propose a programmable and skin temperature-activated electromechanical synergistic wound dressing composed of a shape memory alloy-based mechanical metamaterial for wound contraction and an antibacterial electret thin film for electric field generation. This strategy is successfully demonstrated on rats to achieve effective wound healing in as short as 4 and 8 days for linear and circular wounds, respectively, with a statistically significant over 50% improvement in wound closure rate versus the blank control group. The optimally designed electromechanical synergistic stimulation could regulate the wound microenvironment to accelerate healing metabolism, promote wound closure, and inhibit infection. This work provided an effective wound healing strategy in the context of a programmable temperature-responsive, battery-free electromechanical synergistic biomedical device.

Hybrid strategy of graphene/carbon nanotube hierarchical networks for highly sensitive, flexible wearable strain sensors.

One-dimensional and two-dimensional materials are widely used to compose the conductive network atop soft substrate to form flexible strain sensors for several wearable electronic applications. However, limited contact area and layer misplacement hinder the rapid development of flexible strain sensors based on 1D or 2D materials. To overcome these drawbacks above, we proposed a hybrid strategy by combining 1D carbon nanotubes (CNTs) and 2D graphene nanoplatelets (GNPs), and the developed strain sensor based on CNT-GNP hierarchical networks showed remarkable sensitivity and tenability. The strain sensor can be stretched in excess of 50% of its original length, showing high sensitivity (gauge factor 197 at 10% strain) and tenability (recoverable after 50% strain) due to the enhanced resistive behavior upon stretching. Moreover, the GNP-CNT hybrid thin film shows highly reproducible response for more than 1000 loading cycles, exhibiting long-term durability, which could be attributed to the GNPs conductive networks significantly strengthened by the hybridization with CNTs. Human activities such as finger bending and throat swallowing were monitored by the GNP-CNT thin film strain sensor, indicating that the stretchable sensor could lead to promising applications in wearable devices for human motion monitoring.

An Artificial Electrical-Chemical Mixed Synapse Based on Ion-Gated MoS2 Nanosheets for Real-Time Facilitation Index Tuning.

Tunability of facilitation in short-term memory (STM) provides great potential in bioinspired computing. Recently, several doping strategies were proposed to modify the intrinsic features of materials, resulting in the optimization of the facilitation index (FI). However, real-time scale tuning, which is implemented on the same synaptic device, has not yet been demonstrated. Inspired by the chemical-electrical mixed synapse structure in the brain, we propose a three-terminal artificial synapse based on an ion-gated MoS2 memristor. The gate terminal serves as a nonvolatile ionic pump via chemical intercalation, which effectively affects both the conductance baseline and the hysteresis degree of the STM effect of the memristor. We further modeled the postsynaptic current (PSC) behavior and used it for reservoir computing. Simulation results show that, due to the real-time tuning ability, the built reservoir can be programmed for specific handwritten recognition tasks with the pruning of neurons from 784 to 50. The developed artificial mixed synapse is promising for a downsampling module in neural network design.