Materials Today Nano最新文献

In the age of IoT, the wave energy harvester has been rapidly developed for smart ocean and cross-sea bridge, it is like a bond that links the ocean and bridge. In this study, we proposed a self-powered and self-sensing wave energy harvesting system (SS-WEHS) for smart ocean and cross-sea bridges. The SS-WEHS achieves self-powered characteristics through a coaxial counter-rotating electromagnetic generator (CC-EMG). The experiments show that the voltage of CC-EMG increases synchronously with the frequency and amplitude of the external excitation. At 0.7 Hz and 25 mm excitation, the system's average power generation can reach up to 316 mW, enough to power the bridge sensors. In the water tank, stable power supply of temperature and humidity sensors by CC-EMG verifies the self-powering capability of SS-WEHS in a water environment. In addition, we used the voltage captured by the triboelectric nanogenerator (TENG) in the LSTM deep learning model, which can recognize the hydrological information of waves. The accuracy of recognizing wave amplitude is 98.17 %, and the accuracy of recognizing wave frequency is 99.33 %. Four sets of recognition tests were conducted in a water tank, with different excitation amplitudes and frequencies. The lowest recognition rate achieved was 91 %, which reflecting the self-sensing capability of SS-WEHS in the water environment. Therefore, the system has high-efficiency self-powering and high-precision self-sensing characteristics, which has a great potential for the future development of the smart ocean.

Constructing multicomponent electrocatalysts towards efficient energy conversion is widely adopted strategy, in this regard, high performance metal/nonmetal codoped carbon electrode materials have attained great consideration. Still, the electroacatalytic susceptibility, abundant intrinsic active sites, and stable electrochemical performance in different electrolytes are considered as underline challenges, which can be addressed by rational structural modifications to build a hybrid electroactive material. In this work, unique Sn based multicomponent carbon nanospheres are firstly developed as highly efficient bi-functional electrocatalysts in solar cells and hydrogen evolution. The designed electrocatalysts feature the combined effect of dispersed bimetal active sites and sufficient nitrogen components within spherical carbon framework, which readily enhanced the charge transfer rate via multiple channels, boosting the triiodide reduction reaction (IRR) and hydrogen evolution reaction (HER). As a result, solar cell with Mn/Sn-NC based counter electrodes (CEs) exhibited an excellent power conversion efficiency (PCE) of 8.39 %, outperforming Pt (7.67 %). Moreover, superior HER kinetics are also demonstrated by Mn/Sn-NC with a small overpotential of 127.8 mV at 10 mA cm⁻² and tafel slope of 77 mV dec⁻¹. The rational design of the carbon nanospheres with MnSn₂ bimetal nanoparticles and N doping promotes a high electrochemically active surface area, low charge-transfer resistance, excellent electrochemical stability, and superior electrocatalytic activity, providing a promising route to construct highly efficient materials towards multiple energy conversion applications.

As a p-type semiconductor, layered SnSe has attracted more and more attention because of its great potential application in the field of optoelectronics. However, the strong phonon scattering caused by abundant intrinsic vacancy defects dramatically reduces the performance of carrier transport. It is significant to effectively compensate for the intrinsic defects and reduce the phonon scattering for photodetection materials. In this letter, a novel and simple method is used to reduce the scattering and thus improve the detector performance. The inhibition effect of doping on phonon scattering is systematically studied by experiments and theoretical calculations. The Bi-doped SnSe photodetector exhibits great responsivities of 2.13 A W⁻¹ (447 nm), 1.35 A W⁻¹ (655 nm) and 1.91 A W⁻¹ (980 nm) at 5 V, which are about 2∼3 folds better than those of the undoped device. Furthermore, for the Bi-doped SnSe photodetector, the I_on/I_off are about 46.7, 20.3 and 30.3 for 447 nm, 655 nm and 980 nm, respectively, which are much higher than those of the SnSe photodetector. The photoluminescence and absorption are performed to confirm the bandgap and defects energy level. Meanwhile, the temperature-dependent current-voltage curves measurement is utilized to prove that the enhancement in response performance is because of the decrease in intensity of phonon scattering, which is attributed to the reduction of scattering centers and the weakening of the effect of vacancy defects on the structural translational asymmetry. All these results evidently illustrate that adjustment in phonon scattering is an effective way to achieve high-performance SnSe photodetectors.

Manganese carbonate nanoparticles (NPs) have been developed as pH-triggered responsive magnetic resonance imaging (MRI) contrast agents for tumor diagnosis, but the signal amplification of MRI is still limited due to the lack of response to other pathological parameters of tumors. Here, random single-stranded deoxyribonucleic acid (ssDNA) was explored as a biomimetic template to prepare manganese carbonate superparticles (MnCO₃ SPs) assembled from ultrasmall particles. We focused on the degradation ability of DNA-MnCO₃ SPs triggered by DNA and its trigger mechanism. The results show that different sequences of DNA could trigger the disassembly of these DNA-MnCO₃ SPs and result in MR signal amplification. Further investigations show the DNA-MnCO₃ SPs possess good physiological stability, but increased degradation sensitivity under dual triggering of DNA and low pH. In vivo MR and FL dual-modal imaging for tumor region display T₁-signal rapid amplification, suggesting rapid responsiveness of DNA-MnCO₃ SPs to DNA. Therefore, the design of DNA- and pH-triggered DNA-MnCO₃ SPs may provide a new idea for the construction of next-generation activatable contrast agents with high specificity and high sensitivity.

The sluggish ion transport and mechanical decay caused by K⁺ intercalation can hinder the K⁺ storage ability of Prussian blue analogs (PBAs), potential cathode materials for potassium-ion batteries (PIBs). The construction of composite materials using adjustable chemical components of PB is an effective method to improve cycling stability. In this study, a core–shell structure of KNiCoFe(CN)₆@NiFe(CN)₆ (KNCHCF@NiHCF) was prepared to utilize the inertness of Ni²⁺ and the stability of Fe–CN–Ni bonds and enhance the performance of PBAs. Different concentrations of NiHCF coating (Ni-0, Ni-2, Ni-5, and Ni-60) were introduced into the outer layer of KNCHCF using a simple solution precipitation method. The aforementioned core–shell structure and the corresponding built-in electric field enhanced the structural stability and K⁺/e⁻ transport kinetics of the fabricated materials. And Ni-5 exhibited the best electrochemical performance with excellent durable cycling stability and rate performance. Furthermore, the reversible single-phase insertion and extraction reaction of K⁺ storage mechanism within the Ni-5 cathode was revealed using ex-/in-situ characterization techniques. This strategy may facilitate the development of other cathode materials for rechargeable metal ion batteries.

Reservoir computing (RC) system is a simple and cost-efficient neuromorphic computing system mainly consisting of a reservoir layer and a readout layer. The reservoir layer comprises nonlinear nodes with short-term plasticity (STP), while the readout layer comprises linear nodes with long-term plasticity (LTP). Here, we propose a self-rectifying (>10²) memristor based on CuO_x/p⁺-Si heterojunction that exhibits both nonlinear STP and linear LTP characteristics with high uniformity (σ/μ = 2.8 %). The resistive switching of the device is mainly based on electron trapping/detrapping in CuO_x film. The trapping before relaxation is very unstable and less capable of long-term trapping, which leads to STP. The trapping after relaxation is relatively stable for the lowered trap barrier, which induces LTP. Utilizing its dynamic STP characteristics for the reservoir layer and LTP properties for the readout layer, a CuO_x/p⁺-Si memristor-based homogeneous dynamic RC system was constructed for a spoken-digital recognition task, yielding an accuracy rate of 95.33 %. These results affirm the tremendous potential of our device in establishing a highly compact and full-memristor-based homogeneous RC system.

The field of superlubricity is garnering significant global interest amid the ongoing energy crisis. Various liquids can achieve superlubricity under ambient conditions; however, this limits their applications, such as in acidic environments. Consequently, enhancing anti-wear properties and reducing the coefficient of friction (COF) have become pressing challenges. Graphene-based materials are being extensively studied for tribological applications, attributed to their unique molecular structures and lubricating properties, often serving as lubricating additives to significantly reduce COF. In this study, graphene oxide (GO) nanosheets were utilized as lubricating additives in phosphoric acid (H₃PO₄; pH = 1.5) to explore lubrication enhancement in acidic environments. An ultralow COF of 0.001 was achieved, accompanied by reduced surface roughness and increased contact pressure (by 96.42 %), following the lubrication with GO-H₃PO₄. The reduction in COF post-lubrication with GO-H₃PO₄ is ascribed to three primary factors: the formation of a tribofilm via chemical reactions (comprising silica and phosphorus oxide layers), the hydrogen bond effect leading to a hydrated water layer with low shear strength, and the adsorption of GO nanosheets on the friction surface, facilitating friction transfer from Si₃N₄/Si₃N₄ to GO/GO.

A biological nociceptor functions as a sensory neuron receptor that detects external stimuli and transforms information to the central nervous system, prompting an appropriate response in the human body. In this study, we introduce and experimentally demonstrate a biological receptor system by integrating an IGZO-memristor with a temperature sensor to mimic the dynamics of biological thermoreceptors, including responses to innocuous and noxious stimuli. The IGZO-memristor exhibits a stable bipolar switching response with excellent endurance and retention properties, also revealing biological synaptic functionalities such as hyperalgesia and allodynia. Through our biological receptor system, we placed the temperature sensor on a hot plate and successfully emulated the biological responses of innocuous and noxious functions at different temperature levels 40 °C and 70 °C at the memristor end, respectively. This innovative approach introduces artificial nociceptor devices into artificial intelligence systems, providing a novel platform for the development of intelligent systems capable of mimicking human sensory responses.

Hepatocellular carcinoma (HCC) is a highly malignant tumor with unsatisfactory response to immunotherapy. Pyroptosis, a recently discovered form of regulated cell death (RCD), possesses a huge potential to enhance the immunotherapy efficiency against HCC. To achieve efficient drug delivery and ideal activation of antitumor immunity, an E-selectin modified liposomal nanoplatform co-loading gemcitabine elaidate and BMS-202 (a small molecule programmed cell death protein 1 (PD-1)/programmed death ligand 1 (PD-L1) inhibitor) was designed. Following intravenous injection, the liposomal nanoplatform could efficiently bind to sialylated carbohydrates on the surface of peripheral blood leucocytes via E-selectin, subsequently hitchhiking with leucocytes to realize substantial accumulation in the HCC tissue. After cellular uptake by HCC cells, the released gemcitabine could trigger gasdermin E (GSDME)-dependent pyroptosis with the release of danger-associated molecular patterns (DAMPs) and pro-inflammatory cytokines, thus generating antitumor immunity. The released BMS-202 could further relieve immune suppression by blocking the formation of PD-1/PD-L1 complex. More importantly, gemcitabine-triggered tumor pyroptosis enhanced natural orientation of leucocytes to inflammatory tumor site, further increasing the nanoplatform delivery by facilitating tumor leucocyte infiltration through a positive feedback loop. The in vivo efficacy of the fabricated liposomes demonstrated a favorable antitumor immunity by promoting dendritic cell maturation and T cell activation. In summary, this pyroptosis-enhanced leucocyte-hitchhiking liposomal nanoplatform suggests synergistic antitumor activity and unique ability to modulate drug delivery, showing promise as a highly efficient strategy for potentiated tumor immunotherapy, with a potential for clinical translation.

The utilization of heterogeneous architecture presents a promising approach to bolster the reliability of memristors and achieve high-density memory with synaptic properties. The preparation of P(VDF-TrFE-CTFE)/sodium alginate heterojunction memristors was accomplished through the rotary coating method. The investigation was conducted on the electrical properties and synaptic behavior of the heterojunction memristors. The memristor exhibits the potential to emulate crucial synaptic behaviors, such as paired-pulse facilitation, long-term potentiation, long-term depression, excited postsynaptic current and inhibitory postsynaptic current, as well as learning behavior. This highlights its prospective applicability in neuromorphic devices. A distance sensing system is established utilizing the P(VDF-TrFE-CTFE)/sodium alginate heterojunction memristor artificial synaptic device in conjunction with the Al/sodium alginate/ITO threshold memristor artificial neuron. The detection of distance is achieved through the transmission of signals from the synaptic device and triggering of thresholds in the threshold device. This system enables distance detection ranging from 0.5 cm to 14 cm. This research is crucial for advancing the development of biomimetic sensing systems and facilitating the utilization of memristors in the field of sensing.