The p-n heterojunction constructed by NiMnO3 nanoparticles and Ni3S4 to promote charge separation and efficient catalytic hydrogen evolution

Using sunlight to catalyze water to produce H₂ is a key technology to solve the problem of energy shortage. In this research, perovskite-type NiMnO₃ and Ni₃S₄ was recombined through secondary hydrothermal treatment. The optimal hydrogen evolution for composite materials NiMnO₃/Ni₃S₄is 3.76 μmol mg^?1 h^?1, that 3.7 and 4 times more than that of two monomer materials, respectively. After four cycles of catalytic experiments, proving the high efficiency and stability of the composite catalyst. The characteristics of fluorescence spectroscopy and electrochemistry have confirmed the existence of p-n heterostructures, the excellent catalytic performance is related to the built-in electric field (accelerating the separation and utilization of photocharges) generated by the combination of NiMnO₃ and Ni₃S₄. Strengthening the performance of the catalyst by constructing a heterostructure is an effective modification strategy and has positive application value in the fields of sensors and optoelectronics.     

Distributed two‐stage state estimation with event‐triggered strategy for multirate sensor networks

This paper investigates the state estimation issue for a class of wireless sensor networks (WSNs) with the consideration of limited energy resources. First, a multirate estimation model is established, and then, a new event‐triggered two‐stage information fusion algorithm is developed based on the optimal fusion criterion weighted by matrices. Compared with the existing methods, the presented fusion algorithm can significantly reduce the communication cost in WSNs and save energy resources of sensors efficiently. Furthermore, by presetting a desired containment probability over the interval [0,1] with the developed event‐triggered mechanism, one can obtain a suitable compromise between the communication cost and the estimation accuracy. Finally, a numerical simulation for the WSN tracking system is given to demonstrate the effectiveness of the proposed method.     

Ultra-Robust Flexible Electronics by Laser-Driven Polymer-Nanomaterials Integration

Polyethylene terephthalate (PET) is the most widely used polymer in the world. For the first time, the laser-driven integration of aluminum nanoparticles (Al NPs) into PET to realize a laser-induced graphene/Al NPs/polymer composite, which demonstrates excellent toughness and high electrical conductivity with the formation of aluminum carbide into the polymer is shown. The conductive structures show an impressive mechanical resistance against >10000 bending cycles, projectile impact, hammering, abrasion, and structural and chemical stability when in contact with different solvents (ethanol, water, and aqueous electrolytes). Devices including thermal heaters, carbon electrodes for energy storage, electrochemical and bending sensors show this technology's practical application for ultra-robust polymer electronics. This laser-based technology can be extended to integrating other nanomaterials and create hybrid graphene-based structures with excellent properties in a wide range of flexible electronics’ applications.     

Co?N graphene encapsulated cobalt catalyst for H2O2 decomposition under acidic conditions

Hydrogen peroxide (H₂O₂) has been listed as one of the 100 most important chemicals in the world. However, huge amount of residual H₂O₂ is hard to timely decomposed into O₂ and H₂O under acidic condition, easily resulting in explosion hazard. Here, we reported a core–shell structure catalyst, that is graphene with Co N structure encapsulated Co nanoparticles. Co N graphene shell serves as the active site for the H₂O₂ decomposition, and Co core further enhance this decomposition. Benefiting from it, the H₂O₂ decomposition were close to 100% after 6 cycles without pH adjustment, which increased 6 orders of magnitude compared with no catalyst. At the same time, the O₂ generation reached 99.67% in 2 h with little metal leaching, and ·OH has been greatly inhibited to only 0.08%. This work can cleanly remove H₂O₂ with little deep oxidation and protect the process of H₂O₂ utilization to achieve a safer world.     

Electrostatic-lenses position-sensitive TOF MCP detector for beam diagnostics and new scheme for mass measurements at HIAF

A foil–microchannel plate(MCP) detector,which uses electrostatic lenses and possesses both good position and timing resolutions, has been designed and simulated for beam diagnostics and mass measurements at the next-generation heavy-ion-beam facility HIAF in China. Characterized by low energy loss and good performances of timing and position measurements, it would be located at focal planes in fragment separator HFRS for position monitoring, beam turning, Bρ measurement, and trajectory reconstruction. Moreover, it will benefit the building-up of a magnetic-rigidity–energy-loss–time-offlight(Bρ-△E-TOF) method at HFRS for high-precision in-flight particle identification of radioactive isotope beams on an event-by-event basis. Most importantly, the detector can be utilized for in-ring TOF and position measurements,beam-line TOF measurements at two achromatic foci, and position measurements at a dispersive focus of HFRS, thus making it possible to use two complementary mass measurement methods [isochronous mass spectrometry at the storage ring SRing and magnetic-rigidity–time-of-flight(Bρ-TOF) at the beam-line HFRS] in one single experimental run.     

Weighted power means of q-rung orthopair fuzzy information and their applications in multiattribute decision making

Weighted power means with weights and exponents serving as their parameters are generalizations of arithmetic means. Taking into account decision makers' flexibility in decision making, each attribute value is usually expressed by a $q$-rung orthopair fuzzy value ($q$-ROFV, $q\ge 1$), where the former indicates the support for membership, the latter support against membership, and the sum of their $q$th powers is bounded by one. In this paper, we propose the weighted power means of $q$-rung orthopair fuzzy values to enrich and flourish aggregations on $q$-ROFVs. First, the $q$-rung orthopair fuzzy weighted power mean operator is presented, and its boundedness is precisely characterized in terms of the power exponent. Then, the $q$-rung orthopair fuzzy ordered weighted power mean operator is introduced, and some of its fundamental properties are investigated in detail. Finally, a novel multiattribute decision making method is explored based on developed operators under the $q$-rung orthopair fuzzy environment. A numerical example is given to illustrate the feasibility and validity of the proposed approach, and it is shown that the power exponent is an index suggesting the degree of the optimism of decision makers.     

Enhanced Sensitivity in Nanopore Sensing of Cancer Biomarkers in Human Blood via Click Chemistry

Cancer biomarkers are expected to be indicative of the occurrence of certain cancer diseases before the tumors form and metastasize. However, many biomarkers can only be acquired in extremely low concentrations, which are often beyond the limit of detection (LOD) of current instruments and technologies. A practical strategy for nanopore sensing of cancer biomarkers in raw human blood down to the femtomolar level is developed here. This strategy first converts the detection of cancer biomarkers to the quantification of copper ions by conducting a sandwich assay involving copper oxide nanoparticles. The released Cu²⁺ is then taken to catalyze the “click” reaction which ligates a host–guest modified DNA probe. Finally, this DNA probe is subjected to single‐channel recordings to afford the translocation events that can be used to derive the concentrations of the original biomarkers. Due to the amplification effects of nanoparticle loadings and the “click” reaction, the LOD of this strategy can be as low as the subfemtomolar level. Further, the acid treatment step could effectively eliminate the interferences from plasma proteins in raw human blood and make the strategy highly suitable for the detection of cancer biomarkers in clinical samples.