Harvesting biomechanical energy in vivo is an important route in obtaining sustainable electric energy for powering implantable medical devices. Here, we demonstrate an innovative implantable triboelectric nanogenerator (iTENG) for in vivo biomechanical energy harvesting. Driven by the heartbeat of adult swine, the output voltage and the corresponding current were improved by factors of 3.5 and 25, respectively, compared with the reported in vivo output performance of biomechanical energy conversion devices. In addition, the in vivo evaluation of the iTENG was demonstrated for over 72 h of implantation, during which the iTENG generated electricity continuously in the active animal. Due to its excellent in vivo performance, a self-powered wireless transmission system was fabricated for real-time wireless cardiac monitoring. Given its outstanding in vivo output and stability, iTENG can be applied not only to power implantable medical devices but also possibly to fabricate a self-powered, wireless healthcare monitoring system.

The development of flexible and stretchable electronics has attracted intensive attention for their promising applications in next‐generation wearable functional devices. However, these stretchable devices that are made in a conventional planar format have largely hindered their development, especially in highly stretchable conditions. Herein, a novel type of highly stretchable, fiber‐based triboelectric nanogenerator (fiber‐like TENG) for power generation is developed. Owing to the advanced structural designs, including the fiber‐convolving fiber and the stretchable electrodes on elastic silicone rubber fiber, the fiber‐like TENG can be operated at stretching mode with high strains up to 70% and is demonstrated for a broad range of applications such as powering a commercial capacitor, LCD screen, digital watch/calculator, and self‐powered acceleration sensor. This work verifies the promising potential of a novel fiber‐based structure for both power generation and self‐powered sensing.

Rapid progress in nanotechnology allows us to develop a large number of innovative wearables such as activity trackers, advanced textiles, and healthcare devices. However, manufacturing processes for desirable nanostructure are usually complex and expensive. Moreover, materials used for these devices are mainly derived from nonrenewable resources. Therefore, it poses growing problems for living environment, and causes incompatible discomfort for human beings with long‐time wearing. Here, a self‐powered cellulose fiber based triboelectric nanogenerator (cf‐TENG) system is presented through developing 1D eco‐friendly cellulose microfibers/nanofibers (CMFs/CNFs) into 2D CMFs/CNFs/Ag hierarchical nanostructure. Silver nanofibers membrane is successfully introduced into the cf‐TENG system by using CMFs/CNFs as template, which shows excellent antibacterial activity. Enabled by its desirable porous nanostructure and unique electricity generation feature, the cf‐TENG system is capable of removing PM2.5 with high efficiency of 98.83% and monitoring breathing status without using an external power supply. This work provides a novel and sustainable strategy for self‐powered wearable electronics in healthcare applications, and furthermore paves a way for next‐generation flexible, biocompatible electronics.

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Single-crystal α-MnO2 nanorods were prepared by hydrothermal reaction of single KMnO4 under acidic conditions. The nanorods have a diameter of 30–70 nm and a length up to 2 µm. The formation mechanism for the α-MnO2 nanorods was investigated. Electrochemical properties of the MnO2 nanomaterials prepared for different hydrothermal times were characterized by galvanostatic charge/discharge tests and cyclic voltammetry (CV) studies. The results indicate that the MnO2 nanorods prepared for 5 and 8 h show fine capacitive behaviour with high specific capacitances of 71.1 and 70.9 F g−1, respectively.

Tacrolimus has a narrow therapeutic window and considerable variability in clinical use. Our goal was to compare the performance of multiple linear regression (MLR) and eight machine learning techniques in pharmacogenetic algorithm-based prediction of tacrolimus stable dose (TSD) in a large Chinese cohort. A total of 1,045 renal transplant patients were recruited, 80% of which were randomly selected as the “derivation cohort” to develop dose-prediction algorithm, while the remaining 20% constituted the “validation cohort” to test the final selected algorithm. MLR, artificial neural network (ANN), regression tree (RT), multivariate adaptive regression splines (MARS), boosted regression tree (BRT), support vector regression (SVR), random forest regression (RFR), lasso regression (LAR) and Bayesian additive regression trees (BART) were applied and their performances were compared in this work. Among all the machine learning models, RT performed best in both derivation [0.71 (0.67–0.76)] and validation cohorts [0.73 (0.63–0.82)]. In addition, the ideal rate of RT was 4% higher than that of MLR. To our knowledge, this is the first study to use machine learning models to predict TSD, which will further facilitate personalized medicine in tacrolimus administration in the future.

etc., is essentially crucial to help combat these hazards and build a sustainable society. Among them, rechargeable battery has been regarded as a key technology. In the past decade, we have witnessed that the prevailing lithium-ion batteries (LIBs) made our society more portable, intelligent, and cleaner. [17][18][19] Nevertheless, the limited lithium resources and rising cost hinder their applications in the long run, especially in the field of large-scale stationary energy storage for renewable energy resources (e.g., solar, tide, and wind power). Thus, it is a huge stimulus for researchers to explore more sustainable rechargeable battery systems, which are expected to involve abundant and nontoxic metals to reduce the cost and impacts on environment.Diversified rechargeable batteries such as, the monovalent sodium-ion batteries (SIBs), [20][21][22][23][24] potassium-ion batteries (PIBs), [25][26][27] bivalent zinc-ion batteries (ZIBs), [28][29][30][31] magnesium-ion batteries (MIBs), [32][33][34][35] calcium-ion batteries (CIBs), [36][37][38][39] and trivalent aluminum-ion batteries (AIBs), [40][41][42] have emerged and shown great energy storage promise. As depicted in Figure 1a, those nonlithium metals are much more abundant than Li, especially Al, Ca, Na, K, and Mg, all of which rank the top-8 abundant elements in earth crust. For SIBs and PIBs, since Al would not form alloys with Na and K, Al foil can be used as anode collector, which further lowers the prices of SIBs and PIBs. On the other hand, the higher standard potential of Na/Na + (−2.71 V vs standard hydrogen electrode, SHE) and K/K + (−2.93 V) and their heavier atomic weights make energy densities of SIBs and PIBs intrinsically lower than that of LIBs. For multivalent-ion batteries, the multielectron transfer enables their volumetric capacities (e.g., 5857 and 8056 mA h cm −3 for Zn and Al, respectively) higher than that of Li (2042 mA h cm −3 ). [43,44] Additionally, the small cation radius of Zn 2+ (0.74 Å), Mg 2+ (0.72 Å), and Al 3+ (0.54 Å) indicate that many intercalation electrode materials typical in LIBs may be also potential hosts for reversible intercalation of these multivalent ions. Combining all the above merits, one can anticipate that these emerging rechargeable batteries would be considered as promising alternatives to LIBs.In quest of safe, cost-effective, and high-performance rechargeable batteries, two technical routes have been

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