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Ionic conductive elastomers (ICEs) are emerging stretchable and ionic conductive materials that are solvent-free and thus demonstrate excellent thermal stability. Three-dimensional (3D) printing that creates complex 3D structures in free forms is considered as an ideal approach to manufacture sophisticated ICE-based devices. However, the current technologies constrain 3D printed ICE structures in a single material, which greatly limits functionality and performance of ICE-based devices and machines. Here, we report a digital light processing (DLP)-based multimaterial 3D printing capability to seemly integrate ultraviolet-curable ICE (UV-ICE) with nonconductive materials to create ionic flexible electronic devices in 3D forms with enhanced performance. This unique capability allows us to readily manufacture various 3D flexible electronic devices. To demonstrate this, we printed UV-ICE circuits into polymer substrates with different mechanical properties to create resistive strain and force sensors; we printed flexible capacitive sensors with high sensitivity (2 kPa

Stretchable strain sensor detects a wide range of strain variation and is therefore a key component in various applications. Unlike traditional ones made of elastomers doped with conductive components or fabricated with liquid conductors, ionically conductive hydrogel-based strain sensors remain conductive under large deformations and are biocompatible. However, dehydration is a challenging issue for the latter. Researchers have developed hydrogel-elastomer-based strain sensors where an elastomer matrix encapsulates a hydrogel circuit to prevent its dehydration. However, the reported multi-step approaches are generally time-consuming. Our group recently reported a multimaterial 3D printing approach that enables fast fabrication of such sensors, yet requires a self-built digital-light-processing-based multimaterial 3D printer. Here, we report a simple projection lithography method to fabricate hydrogel-elastomer-based stretchable strain sensors within 5 minutes. This method only requires a UV projector/lamp with photomasks; the chemicals are commercially available; the protocols for preparing the polymer precursors are friendly to users without chemistry background. Moreover, the manufacturing flexibility allows users to readily pattern the sensor circuit and attach the sensor to a 3D printed soft pneumatic actuator to enable strain sensing on the latter. The proposed approach paves a simple and versatile way to fabricate hydrogel-elastomer-based stretchable strain sensors and flexible electronic devices.

Thermally responsive shape memory polymers (SMPs) used in 4D printing are often reported to be activated by external heat sources or embedded stiff heaters. However, such heating strategies impede the practical application of 4D printing due to the lack of precise control over heating or the limited ability to accommodate the stretching during shape programming. Herein, we propose a novel 4D printing paradigm by fabricating stretchable heating circuits with fractal motifs via electric-field-driven microscale 3D printing of conductive paste for seamless integration into 3D printed structures with SMP components. By regulating the fractal order and printing/processing parameters, the overall electrical resistance and areal coverage of the circuits can be tuned to produce an efficient and uniform heating performance. Compared with serpentine structures, the resistance of fractal-based circuits remains relatively stable under both uniaxial and biaxial stretching. In practice, steady-state and transient heating modes can be respectively used during the shape programming and actuation phases. We demonstrate that this approach is suitable for 4D printed structures with shape programming by either uniaxial or biaxial stretching. Notably, the biaxial stretchability of fractal-based heating circuits enables the shape change between a planar structure and a 3D one with double curvature. The proposed strategy would offer more freedom in designing 4D printed structures and enable the manipulation of the latter in a controlled and selective manner.

Shape reconfiguration is ubiquitous in nature and widely used in many applications such as soft robotics, metamaterials, energy absorption and tissue engineering. Shape reconfigurable soft actuators, due to their ability to adapt and adjust in complex and unpredictable working environment, have been designed by the use of various delicate structures and active materials. However, soft actuators that exhibit reconfigurable helical deformation have not been proposed; they have the advantage of integrating both bending and twisting actuations in one deformation mode. In this work, we present a thermal-induced shape reconfigurable soft actuator that shows reversible actuations with vastly shape differences under thermal stimulus. It exhibits helical deformation at lower temperature and mainly in-plane bending at relatively higher temperature. The reversible shape transition is controlled by a thermal stimulus that changes the anisotropy of the structure, which consists of shape memory polymer fibers embedded in a homogeneous elastic matrix. A theoretical model is proposed based on the minimum potential energy that incorporates the thermomechanical behavior of the shape memory polymer fibers. Experiments are conducted and the results agree well with the theoretical modeling. Using the theoretical model, we establish design principles for reconfigurable soft actuators whose functional response is programmable given the architecture and external stimulus. A six-handed helical soft actuator, constructed to demonstrate its programmable deformation, is utilized to catch a living fish in water.

Transparent glass with metal mesh is considered a promising strategy for high performance transparent glass heaters (TGHs). However, the realization of simple, low-cost manufacture of high performance TGHs still faces great challenges. Here, a technique for the fabrication of high performance TGHs is proposed using liquid sacrificial substrate electric-field-driven (LS-EFD) microscale 3D printing of thick film silver paste. The liquid sacrificial substrate not only significantly improves the aspect ratio (AR) of silver mesh, but also plays a positive role in printing stability. The fabricated TGHs with a line width of 35 µm, thickness of 12.3 µm, and pitch of 1000 µm exhibit a desirable optoelectronic performance with sheet resistance (R

Cylindrical microlens arrays (CMLAs) play a key role in many optoelectronic devices, and 100% fill-factor CMLAs also have the advantage of improving the signal-to-noise ratio and avoiding stray-light effects. However, the existing preparation technologies are complicated and costly, which are not suitable for mass production. Herein, we propose a simple, efficient, and low-cost manufacturing method for CMLAs with a high fill-factor via the electric-field-driven (EFD) microscale 3D printing of polydimethylsiloxane (PDMS). By adjusting the printing parameters, the profile and the fill-factor of the CMLAs can be controlled to improve their optical performance. The optical performance test results show that the printed PDMS CMLAs have good image-projecting and light-diffraction properties. Using the two printing modes of this EFD microscale 3D-printing technology, a cylindrical dual-microlens array with a double-focusing function is simply prepared. At the same time, we print a series of specially shaped microlenses, proving the flexible manufacturing capabilities of this technology. The results show that the prepared CMLAs have good morphology and optical properties. The proposed method may provide a viable route for manufacturing large-area CMLAs with 100% fill-factor in a very simple, efficient, and low-cost manner.

Conventional 4D printing technologies are realized by combining 3D printing with soft active materials such as shape memory polymers (SMPs) and hydrogels. However, the intrinsic material property limitations make the SMP or hydrogel-based 4D printing unsuitable to fabricate the actuators that need to exhibit fast-response, reversible actuations. Instead, pneumatic actuations have been widely adopted by the soft robotics community to achieve fast-response, reversible actuations, and many efforts have been made to apply the pneumatic actuation to 3D printed structures to realize passive 4D printing with fast-response, reversible actuation. However, the 3D printing of soft actuators/robots heavily relies on the commercially available UV curable elastomers the break strains of which are not sufficient for certain applications which require larger elastic deformation. In this paper, we present two simple approaches to tune the mechanical properties such as stretchability, stiffness, and durability of the commercially available UV curable elastomers by adding: (i) mono-acrylate based linear chain builder; (ii) urethane diacrylate-based crosslinker. Material property characterizations have been performed to investigate the effects of adding the two additives on the stretchability, stiffness, mechanical repeatability as well as viscosity. Demonstrations of fully printed robotic finger, grippers, and highly deformable 3D lattice structure are also presented.

In order to improve the accuracy of emotional recognition by end-to-end automatic learning of emotional features in spatial and temporal dimensions of electroencephalogram (EEG), an EEG emotional feature learning and classification method using deep convolution neural network (CNN) was proposed based on temporal features, frequential features, and their combinations of EEG signals in DEAP dataset. The shallow machine learning models including bagging tree (BT), support vector machine (SVM), linear discriminant analysis (LDA), and Bayesian linear discriminant analysis (BLDA) models and deep CNN models were used to make emotional binary classification experiments on DEAP datasets in valence and arousal dimensions. The experimental results showed that the deep CNN models which require no feature engineering achieved the best recognition performance on temporal and frequency combined features in both valence and arousal dimensions, which is 3.58% higher than the performance of the best traditional BT classifier in valence dimension and 3.29% higher than that of BT classifier in arousal dimension.

In this paper, we propose a hierarchical bidirectional Gated Recurrent Unit (GRU) network with attention for human emotion classification from continues electroencephalogram (EEG) signals. The structure of the model mirrors the hierarchical structure of EEG signals, and the attention mechanism is used at two levels of EEG samples and epochs. By paying different levels of attention to content with different importance, the model can learn more significant feature representation of EEG sequence which highlights the contribution of important samples and epochs to its emotional categories. We conduct the cross-subject emotion classification experiments on DEAP data set to evaluate the model performance. The experimental results show that in valence and arousal dimensions, our model on 1-s segmented EEG sequences outperforms the best deep baseline LSTM model by 4.2% and 4.6%, and outperforms the best shallow baseline model by 11.7% and 12% respectively. Moreover, with increase of the epoch’s length of EEG sequences, our model shows more robust classification performance than baseline models, which demonstrates that the proposed model can effectively reduce the impact of long-term non-stationarity of EEG sequences and improve the accuracy and robustness of EEG-based emotion classification.

Flexible transparent electrodes (FTEs) with embedded metal meshes play an indispensable role in many optoelectronic devices due to their excellent mechanical stability and environmental adaptability. However, low-cost, simple, efficient, and environmental friendly integrated manufacturing of high-performance embedded metal meshes remains a huge challenge. Here, a facile and novel fabrication method is proposed for FTEs with an embedded metal mesh via liquid substrateelectric-field-driven microscale 3D printing process. This direct printing strategy avoids tedious processes and offers low-cost and high-volume production, enabling the fabrication of high-resolution, high-aspect ratio embedded metal meshes without sacrificing transparency. The final manufactured FTEs with 80 mm × 80 mm embedded metal mesh offers excellent optoelectronic performance with a sheet resistance (R

Four-dimensional (4D) printing that enables 3D printed structures to change configurations over time has gained great attention because of its exciting potential in various applications. Among all the 4D printing materials, shape memory polymers (SMPs) possess higher stiffness and faster response rate and therefore are considered as one of most promising materials for 4D printing. However, most of the SMP-based 4D printing materials are (meth)acrylate thermosets which have permanently cross-linked covalent networks and cannot be repaired if any damage occurs. To address the unrepairable nature of SMP-based 4D printing materials, this paper reports a double-network self-healing SMP (SH-SMP) system for high-resolution self-healing 4D printing. In the SH-SMP system, the semicrystalline linear polymer polycaprolactone (PCL) is incorporated into a methacrylate-based SMP system which has good compatibility with the digital light processing-based 3D printing technology and can be used to fabricate complex 4D printing structures with high resolution (up to 30 μm). The PCL linear polymer imparts the self-healing ability to the 4D printing structures, and the mechanical properties of a damaged structure can be recovered to more than 90% after adding more than 20 wt % of PCL into the SH-SMP system. We investigated the effects of PCL concentration on the thermomechanical behavior, viscosity, and the self-healing capability of the SH-SMP system and performed the computational fluid dynamics simulations to study the effect of SH-SMP solution's viscosity on the 3D printing process. Finally, we demonstrated the self-healing 4D printing application examples to show the merits of the SH-SMP system.

4D printing is an emerging fabrication technology that enables 3D printed structures to change configuration over "time" in response to an environmental stimulus. Compared with other soft active materials used for 4D printing, shape-memory polymers (SMPs) have higher stiffness, and are compatible with various 3D printing technologies. Among them, ultraviolet (UV)-curable SMPs are compatible with Digital Light Processing (DLP)-based 3D printing to fabricate SMP-based structures with complex geometry and high-resolution. However, UV-curable SMPs have limitations in terms of mechanical performance, which significantly constrains their application ranges. Here, a mechanically robust and UV-curable SMP system is reported, which is highly deformable, fatigue resistant, and compatible with DLP-based 3D printing, to fabricate high-resolution (up to 2 µm), highly complex 3D structures that exhibit large shape change (up to 1240%) upon heating. More importantly, the developed SMP system exhibits excellent fatigue resistance and can be repeatedly loaded more than 10 000 times. The development of the mechanically robust and UV-curable SMPs significantly improves the mechanical performance of the SMP-based 4D printing structures, which allows them to be applied to engineering applications such as aerospace, smart furniture, and soft robots.

Flexible transparent electrodes (FTEs) with an embedded metal mesh are considered a promising alternative to traditional indium tin oxide (ITO) due to their excellent photoelectric performance, surface roughness, and mechanical and environmental stability. However, great challenges remain for achieving simple, cost-effective, and environmentally friendly manufacturing of high-performance FTEs with embedded metal mesh. Herein, a maskless, templateless, and plating-free fabrication technique is proposed for FTEs with embedded silver mesh by combining an electric-field-driven (EFD) microscale 3D printing technique and a newly developed hybrid hot-embossing process. The final fabricated FTE exhibits superior optoelectronic properties with a transmittance of 85.79%, a sheet resistance of 0.75 Ω sq-1 , a smooth surface of silver mesh (Ra ≈ 18.8 nm) without any polishing treatment, and remarkable mechanical stability and environmental adaptability with a negligible increase in sheet resistance under diverse cyclic tests and harsh working conditions (1000 bending cycles, 80 adhesion tests, 120 scratch tests, 100 min ultrasonic test, and 72 h chemical attack). The practical viability of this FTE is successfully demonstrated with a flexible transparent heater applied to deicing. The technique proposed offers a promising fabrication strategy with a cost-effective and environmentally friendly process for high-performance FTE.

Engineering multicomponent composite materials into tailored structure is of vital importance for developing advanced sodium ion batteries (SIBs). However, the mechanical stress intensification originating from severe volume expansion upon sodiation induces anisotropic swelling and anomalous structural changes, thus leading to electrode instability and inferior sodium storage performance. Herein, we propose a novel stress-release strategy by inserting of MoSe2 nanosheets onto the surface of yolk-shell Fe7Se8@C composite to accommodate the volume expansion and stabilize the electrode. Bestowed by the unique superiority, the Fe7Se8@C@MoSe2 composite manifests impressive sodium-storage performance in terms of high specific capacity (473.3 mAh g−1 at 0.1 A g−1), excellent rate capability (274.5 mAh g−1 at 5.0 A g−1) and long-term cycling stability (87.1% capacity retention after 600 cycles at 1.0 A g−1). Finite element (FE) simulations confirm that the exterior MoSe2 layer could significantly dissipate the stress caused by the sodiation-induced expansion of Fe7Se8 in the carbon layer. The primary sodium storage mechanisms and structural evolution are further revealed in details by in situ and ex situ investigations. More encouragingly, a practical sodium-ion full cell based on Fe7Se8@C@MoSe2 anode is demonstrated with remarkable performances. This work strengthens the fundamental understanding of mechanical effect for sodium-storage behaviors and sheds light onto designing smart multi-compositional hybrids toward advanced energy storage devices.

This paper proposes a novel experimental test apparatus that permits direct measurements of tyre/asperity normal contact forces under rolling conditions without interfacial layer. A reduced-sized pneumatic tyre is set rolling on the exterior surface of a cylindrical test rig simulating a smooth road surface except a single asperity of simple geometric shape connected to an embedded force transducer. Distinct asperity geometries lead to similar shapes of force signal but different magnitudes whose relationships with the indentation have exponents close to those in classical analytical solutions. By analyzing the time signals of the contact force and their frequency contents for different rolling speeds, the quasi-static nature of the contact, commonly assumed in numerical models, is verified.

The asymmetric unit of the title compound, [Ni(C(6)H(2)N(2)O(4))(C(10)H(8)N(2))(H(2)O)]·1.25H(2)O, contains two independent chemically identical Ni(II) complex cations and two and a half solvent water mol-ecules. The Ni(II) ions are in slightly distorted coordination environments. In the crystal structure, inter-molecular O-H⋯O and weak C-H⋯O hydrogen bonds link cations and water mol-ecules into a three-dimensional network. One of the three uncoordinated water molecules is half-occupied.