As implantable medical electronics (IMEs) developed for healthcare monitoring and biomedical therapy are extensively explored and deployed clinically, the demand for non-invasive implantable biomedical electronics is rapidly surging. Current rigid and bulky implantable microelectronic power sources are prone to immune rejection and incision, or cannot provide enough energy for long-term use, which greatly limits the development of miniaturized implantable medical devices. Herein, a comprehensive review of the historical development of IMEs and the applicable miniaturized power sources along with their advantages and limitations is given. Despite recent advances in microfabrication techniques, biocompatible materials have facilitated the development of IMEs system toward non-invasive, ultra-flexible, bioresorbable, wireless and multifunctional, progress in the development of minimally invasive power sources in implantable systems has remained limited. Here three promising minimally invasive power sources summarized, including energy storage devices (biodegradable primary batteries, rechargeable batteries and supercapacitors), human body energy harvesters (nanogenerators and biofuel cells) and wireless power transfer (far-field radiofrequency radiation, near-field wireless power transfer, ultrasonic and photovoltaic power transfer). The energy storage and energy harvesting mechanism, configurational design, material selection, output power and in vivo applications are also discussed. It is expected to give a comprehensive understanding of the minimally invasive power sources driven IMEs systemfor painless health monitoring and biomedical therapy with long-term stable functions.
Researchers have been seeking for the most technically-economical water electrolysis technology for entering the next-stage of industrial amplification for large-scale green hydrogen production. Various membrane-based electrolyzers have been developed to improve electric-efficiency, reduce the use of precious metals, enhance stability, and possibly realize direct seawater electrolysis. While electrode engineering is the key to approaching these goals by bridging the gap between catalysts design and electrolyzers development, nevertheless, as an emerging field, has not yet been systematically analyzed. Herein, this review is organized to comprehensively discuss the recent progresses of electrode engineering that have beenmade toward advancedmembrane-based electrolyzers. For the commercialized or near-commercialized membrane electrolyzer technologies, the electrode material design principles are interpreted and the interface engineering that have been put forward to improve catalytic sites utilization and reduce precious metal loading is summarized. Given the pressing issues of electrolyzer cost reduction and efficiency improvement, the electrode structure engineering toward applying precious metal free electrocatalysts is highlighted and sufficient accessible sites within the thick catalyst layers with rational electrode architectures and effective ions/mass transport interfaces are enabled. In addition, this review also discusses the innovative ways as proposed to break the barriers of current membrane electrolyzers, including the adjustments of electrode reaction environment, and the feasible cellvoltage-breakdown strategies for durable direct seawater electrolysis. Hopefully, this review may provide insightful information of membrane-based electrode engineering and inspire the future development of advanced membrane electrolyzer technologies for cost-effective green hydrogen production.
Numerous experiments have demonstrated improvements on the efficiency of perovskite solar cells by introducing plasmonic nanoparticles, however, the underlying mechanisms are still not clear: the particles may enhance light absorption and scattering, as well as charge separation and transfer, or the perovskite’s crystalline quality. Eventually, it can still be debated whether unambiguous plasmonic increase of light absorption has indeed been achieved.Here, various optical models are employed to provide a physical understanding of the relevant parameters in plasmonic perovskite cells and the conditions underwhich light absorption may be enhanced by plasmonic mechanisms. By applying the recent generalizedMie theory to gold nanospheres in perovskite, it is shown that their plasmon resonance is conveniently located in the 650–800 nm wavelength range, where absorption enhancement is most needed. It is evaluated for which active layer thickness and nanoparticle concentration a significant enhancement can be expected. Finally, the experimental literature on plasmonic perovskite solar cells is analyzed in light of this theoretical description. It is estimated that only a tiny portion of these reports can be associated with light absorption and point out the importance of reporting the perovskite thickness and nanoparticle concentration in order to assess the presence of plasmonic effects.
Halide perovskite solar cells are characterized by a hysteresis between current–voltage (J–V) curves recorded on the reverse and on the forward scan directions, and the suppression of this phenomenon has focused great attention. In the presentwork, it is shown that a special family of 3D perovskites, that are rendered lead -and iodide- deficient (d-HPs) by incorporating large organic cations, are characterized by a large hysteresis. The strategy of passivating defects by K+, which has been successful in reducing the hysteresis of 3Dperovskite perovskite solar cells, is inefficientwith the d-HPs. By glowdischarge optical emission spectroscopy (GD-OES), the existence of the classic iodide migration in these layers is unveiled, which is efficiently blocked by potassium cation insertion. However, it is also shown that it co-exists with themigration of the large organic cations characteristics of d-HPs which are not blocked by the alkali metal ion. The migration of those large cations is intrinsically linked to the special structure of the d-HP. It is suggested that it takes place through channels, present throughout the whole perovskite layer after the substitution of PbI+ units by the large cations, making this phenomenon intrinsic to the original structure of d-HPs.
In the biological nervous system, the integration and cooperation of parallel system of receptors, neurons, and synapses allow efficient detection and processing of intricate and disordered external information. Such systems acquire and process environmental data in real-time, efficiently handling complex tasks withminimal energy consumption. Memristors can mimic typical biological receptors, neurons, and synapses by implementing key features of neuronal signal-processing functions such as selective adaption in receptors, leaky integrate-and-fire in neurons, and synaptic plasticity in synapses. External stimuli are sensitively detected and filtered by “artificial receptors,” encoded into spike signals via “artificial neurons,” and integrated and stored through “artificial synapses.” The high operational speed, low power consumption, and superior scalability of memristive devices make their integration with high-performance sensors a promising approach for creating integrated artificial sensory systems. These integrated systems can extract useful data from a large volume of raw data, facilitating real-time detection and processing of environmental information. This review explores the recent advances in memristor-based artificial sensory systems. The authors begin with the requirements of artificial sensory elements and then present an in-depth review of such elements demonstrated by memristive devices. Finally, the major challenges and opportunities in the development of memristor-based artificial sensory systems are discussed.
Polyethylene glycol (PEG) is widely used as phase changematerials (PCM) due to their versatile working temperature and high latent heat. However, the low molecular weight of PEG prevents from the formation of flexible microfibers, and the common leakage problem associated with solid–liquid PCM further hinders their applications in various fields. To address these challenges, polyethylene oxide (PEO) is incorporated as the supporting matrix for PEG, leading to a successful electrospinning of fibrous mats. Due to the similar chemical nature of both PEG and PEO, the blended composites show great compatibility and produce uniform electrospun fibers. The thermal properties of these fibers are characterized by DSC and TGA, and supercooling for the PEG(1050) component is effectively reduced by 75–85%. The morphology changes before and after leakage test are analyzed by SEM. Tensile and DMA tests show that the presence of PEG(1050) component contributes to plasticization effect, improving mechanical and thermomechanical strength. The ratio of PEO(600K):PEG(1050) at 7:3 affords the optimal performance with good chemical and form-stability, least shrinkage, and uniformity. These fibrous mats have potential applications in areas of food packaging, flexible wearable devices, or textiles to aid in thermal regulation.
Calcium ions (Ca2+) are indispensable and versatile metal ions that play a pivotal role in regulating cell metabolism, encompassing cell survival, proliferation, migration, and gene expression. Aberrant Ca2+ levels are frequently linked to cell dysfunction and a variety of pathological conditions. Therefore, it is essential tomaintain Ca2+ homeostasis to coordinate body function. Disrupting the balance of Ca2+ levels has emerged as a potential therapeutic strategy for various diseases, and there has been extensive research on integrating this approach into nanoplatforms. In this review, the current nanoplatforms that regulate Ca2+ homeostasis for cancer therapy are first discussed, including both direct and indirect approaches tomanage Ca2+ overload or inhibit Ca2+ signalling. Then, the applications of these nanoplatforms in targeting different cells to regulate their Ca2+ homeostasis for achieving therapeutic effects in cancer treatment are systematically introduced, including tumour cells and immune cells. Finally, perspectives on the further development of nanoplatforms for regulating Ca2+ homeostasis, identifying scientific limitations and future directions for exploitation are offered.
Plasma etching treatment is an effective strategy to improve the electrocatalytic activity, but the improvement mechanism is still unclear. In this work, a nitrogen-doped carbon nanotube-encased iron nanoparticles (Fe@NCNT) catalyst is synthesized as the model catalyst, followed by plasma etching treatment with different parameters. The electrocatalytic activity improvement mechanism of the plasma etching treatment is revealed by combining the physicochemical characterizations and electrochemical results. As a result, highly activemetal–nitrogen species introduced by nitrogen plasma etching treatment are recognized as the main contribution to the improved electrocatalytic activity, and the defects induced by plasma etching treatment also contribute to the improvement of the electrocatalytic activity. In addition, the prepared catalyst also demonstrates superior ORR activity and stability than the commercial Pt/C catalyst.
Revealing and clarifying the chemical reaction processes andmechanisms inside the batteries will bring a great help to the controllable preparation and performancemodulation of batteries. Advanced characterization techniques based on synchrotron radiation (SR) have accelerated the development of various batteries over the past decade. In situ SR techniques have been widely used in the study of electrochemical reactions and mechanisms due to their excellent characteristics. Herein, the three most wide and important synchrotron radiation techniques used in battery research were systematically reviewed, namely X-ray absorption fine structure (XAFS) spectroscopy, small-angle X-ray scattering (SAXS), and X-ray diffraction (XRD). Special attention is paid to how these characterization techniques are used to understand the reactionmechanismof batteries and improve the practical characteristics of batteries. Moreover, the in situ combining techniques advance the acquisition of single scale structure information to the simultaneous characterization ofmultiscale structures,whichwill bring a newperspective to the research of batteries. Finally, the challenges and future opportunities of SR techniques for battery research are featured based on their current development.
Thromboelastography (TEG) remains a convenient and effective viscoelastic blood coagulation testing device for guiding blood component transfusion and assessing the risk of thrombosis. Here, a TEG enabled by a non-contact triboelectric angle sensor (NTAS) with a small size (∼7 cm3) is developed for assessing the blood coagulation system. With the assistance of a superelastic torsion wire structure, the NTAS-TEG realizes the detection of blood viscoelasticity. Benefiting from a grating and convex design, the NTAS holds a collection of compelling features, including accurate detection of rotation angles from -2.5° to 2.5°, high linearity (R2 = 0.999), and a resolution of 0.01°. Besides, the NTAS exhibits merits of low cost and simplified fabrication. Based on the NTAS-TEG, a viscoelastic blood coagulation detection and analysis system is successfully constructed, which can provide a graph and parameters associated with clot initiation, formation, and stability for clinicians by using 0.36 mL of whole blood. The system not only validates the feasibility of the triboelectric coagulation testing sensor, but also further expands the application of triboelectric sensors in healthcare.
Colorectal cancer (CRC) is generally characterized by a high prevalence of Fusobacterium nucleatum (F. nucleatum), a spindle-shaped, Gram-negative anaerobe pathogen derived from the oral cavity. This tumor-resident microorganism has been closely correlated with the occurrence, progression, chemoresistance and immunosuppressive microenvironment of CRC. Furthermore, F. nucleatum can specifically colonize CRC tissues through adhesion on its surface, forming biofilms that are highly resistant to commonly used antibiotics. Accordingly, it is crucial to develop efficacious non-antibiotic approaches to eradicate F. nucleatum and its biofilms for CRC treatment. In recent years, various antimicrobial strategies, such as natural extracts, inorganic chemicals, organic chemicals, polymers, inorganic-organic hybrid materials, bacteriophages, probiotics, and vaccines, have been proposed to combat F. nucleatum and F. nucleatum biofilms. This review summarizes the latest advancements in anti-F. nucleatum research, elucidates the antimicrobial mechanisms employed by these systems, and discusses the benefits and drawbacks of each antimicrobial technology. Additionally, this review also provides an outlook on the antimicrobial specificity, potential clinical implications, challenges, and future improvements of these antimicrobial strategies in the treatment of CRC.
Real-time foot pressure monitoring using wearable smart systems, with comprehensive foot health monitoring and analysis, can enhance quality of life and prevent foot-related diseases. However, traditional smart insole solutions that rely on basic data analysis methods of manual feature extraction are limited to real-time plantar pressure mapping and gait analysis, failing to meet the diverse needs of users for comprehensive foot healthcare. To address this, we propose a deep learning-enabled smart insole system comprising a plantar pressure sensing insole, portable circuit board, deep learning and data analysis blocks, and software interface. The capacitive sensing insole can map both static and dynamic plantar pressure with a wide range over 500 kPa and excellent sensitivity. Statistical tools are used to analyze long-term foot pressure usage data, providing indicators for early prevention of foot diseases and key data labels for deep learning algorithms to uncover insights into the relationship between plantar pressure patterns and foot issues. Additionally, a segmentation method assisted deep learning model is implemented for exercise-fatigue recognition as a proof of concept, achieving a high classification accuracy of 95%. The system also demonstrates various foot healthcare applications, including daily activity statistics, exercise injury avoidance, and diabetic foot ulcer prevention.