Three-dimensional (3D) printing of hydrogels is now an attractive area of research due to its capability to fabricate intricate, complex and highly customizable scaffold structures that can support cell adhesion and promote cell infiltration for tissue engineering. However, pure hydrogels alone lack the necessary mechanical stability and are too easily degraded to be used as printing ink. To overcome this problem, significant progress has been made in the 3D printing of hydrogel composites with improved mechanical performance and biofunctionality. Herein, we provide a brief overview of existing hydrogel composite 3D printing techniques including laser based-3D printing, nozzle based-3D printing, and inkjet printer based-3D printing systems. Based on the type of additives, we will discuss four main hydrogel composite systems in this review: polymer-or hydrogel-hydrogel composites, particle-reinforced hydrogel composites, fiber-reinforced hydrogel composites, and anisotropic filler-reinforced hydrogel composites. Additionally, several emerging potential applications of hydrogel composites in the field of tissue engineering and their accompanying challenges are discussed in parallel.

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An ocean wave contains various marine information, but it is generally difficult to obtain the high-precision quantification to meet the needs of ocean development and utilization. Here, we report a self-powered and high-performance triboelectric ocean-wave spectrum sensor (TOSS) fabricated using a tubular triboelectric nanogenerator (TENG) and hollow ball buoy, which not only can adapt to the measurement of ocean surface water waves in any direction but also can eliminate the influence of seawater on the performance of the sensor. Based on the high-sensitivity advantage of TENG, an ultrahigh sensitivity of 2530 mV mm–1 (which is 100 times higher than that of previous work) and a minimal monitoring error of 0.1% are achieved in monitoring wave height and wave period, respectively. Importantly, six basic ocean-wave parameters (wave height, wave period, wave frequency, wave velocity, wavelength, and wave steepness), wave velocity spectrum, and mechanical energy spectrum have been derived by the electrical signals of TOSS. Our finding not only can provide ocean-wave parameters but also can offer significant and accurate data support for cloud computing of ocean big data.