Synthesis of MgFe2O4/Reduced Graphene Oxide Composite and Its Visible-Light Photocatalytic Performance for Organic Pollution

Recently, binary metal oxides have been proven to be the most investigated semiconductors due to their high activity for the removal of organic pollutants. In this paper, to improve the photocatalytic efficiency of MgFe2O4, a MgFe2O4/reduced graphene oxide (MFO/rGO) photocatalyst was synthesized by a facile generalized solvothermal method. The morphology, structure, and photocatalytic activities in the degradation of methyl orange (MO) reaction were systematically characterized by scanning electron microscopy, transmission electron microscopy, X-ray diffraction, and UV-vis absorption spectroscopy, respectively. The results showed that the MFO/rGO composite exhibited enhanced photocatalytic performance in the photodegradation of MO under visible-light irradiation and reached a maximum degradation rate of 99% within 60 min of irradiation. This excellent photocatalytic performance is attributed to the introduction of rGO in the composite, which can effectively reduce the photoproduction of the electron-hole pair recombination rate. The excellent photocatalytic activity reveals that the MFO/rGO composite photocatalyst is a promising photocatalyst with good visible-light response and has potential applications in the field of water treatment

Bioelectronic Neural Interfaces: Improving Neuromodulation Through Organic Conductive Coatings

Abstract Integration of bioelectronic devices in clinical practice is expanding rapidly, focusing on conditions ranging from sensory to neurological and mental health disorders. While platinum (Pt) electrodes in neuromodulation devices such as cochlear implants and deep brain stimulators have shown promising results, challenges still affect their long‐term performance. Key among these are electrode and device longevity in vivo, and formation of encapsulating fibrous tissue. To overcome these challenges, organic conductors with unique chemical and physical properties are being explored. They hold great promise as coatings for neural interfaces, offering more rapid regulatory pathways and clinical implementation than standalone bioelectronics. This study provides a comprehensive review of the potential benefits of organic coatings in neuromodulation electrodes and the challenges that limit their effective integration into existing devices. It discusses issues related to metallic electrode use and introduces physical, electrical, and biological properties of organic coatings applied in neuromodulation. Furthermore, previously reported challenges related to organic coating stability, durability, manufacturing, and biocompatibility are thoroughly reviewed and proposed coating adhesion mechanisms are summarized. Understanding organic coating properties, modifications, and current challenges of organic coatings in clinical and industrial settings is expected to provide valuable insights for their future development and integration into organic bioelectronics

Enhancing Wheat Gluten Content and Processing Quality: An Analysis of Drip Irrigation Nitrogen Frequency

Drip irrigation is a water-saving and fertilizer-saving application technology used in recent years, with which the frequency of drip irrigation nitrogen application has not yet been determined. In order to investigate the effects of different drip irrigation nitrogen application frequencies on the processing quality of medium-gluten wheat (Jimai22) and strong-gluten wheat (Jimai20 and Shiluan02-1), a two-year field experiment was carried out. Two frequencies of water and N application were set under the same conditions of total N application (210 kg·ha−1) and total irrigation (120 mm): DIF4, consisting of four equal applications of water and N (each of 30 kg·ha−1 of N application and 30 mm of irrigation) and DIF2, consisting of two equal applications of water and N (each of 60 kg·ha−1 of N application and 60 mm of irrigation). The results showed that IF4 significantly increased protein content by 2–8.6%, wet gluten content by 4.5–22.1%, and hardness value (p > 0.05), and PC2 was considered as a protein factor; the sedimentation value was highly significantly correlated with most of the parameters of the flour stretch (p < 0.01). DIF4 improved the stretching quality, and the flour quality of Jima22 was decreased, the flour quality of strong-gluten wheats Jimai20 and Shiluan02-1 was improved, and PC1 was considered to be the dough factor. In conclusion, although the frequency of nitrogen application by drip irrigation increased the protein factor and improved the tensile quality, the flour quality was not necessarily enhanced

JUNO Sensitivity to Invisible Decay Modes of Neutrons

International audienceWe explore the bound neutrons decay into invisible particles (e.g., $n\rightarrow 3 \nu$ or $nn \rightarrow 2 \nu$) in the JUNO liquid scintillator detector. The invisible decay includes two decay modes: $n \rightarrow { inv}$ and $nn \rightarrow { inv}$. The invisible decays of $s$-shell neutrons in $^{12}{\rm C}$ will leave a highly excited residual nucleus. Subsequently, some de-excitation modes of the excited residual nuclei can produce a time- and space-correlated triple coincidence signal in the JUNO detector. Based on a full Monte Carlo simulation informed with the latest available data, we estimate all backgrounds, including inverse beta decay events of the reactor antineutrino $\bar{\nu}_e$, natural radioactivity, cosmogenic isotopes and neutral current interactions of atmospheric neutrinos. Pulse shape discrimination and multivariate analysis techniques are employed to further suppress backgrounds. With two years of exposure, JUNO is expected to give an order of magnitude improvement compared to the current best limits. After 10 years of data taking, the JUNO expected sensitivities at a 90% confidence level are $\tau/B( n \rightarrow { inv} ) > 5.0 \times 10^{31} \, {\rm yr}$ and $\tau/B( nn \rightarrow { inv} ) > 1.4 \times 10^{32} \, {\rm yr}$

JUNO Sensitivity to Invisible Decay Modes of Neutrons

International audienceWe explore the bound neutrons decay into invisible particles (e.g., $n\rightarrow 3 \nu$ or $nn \rightarrow 2 \nu$) in the JUNO liquid scintillator detector. The invisible decay includes two decay modes: $n \rightarrow { inv}$ and $nn \rightarrow { inv}$. The invisible decays of $s$-shell neutrons in $^{12}{\rm C}$ will leave a highly excited residual nucleus. Subsequently, some de-excitation modes of the excited residual nuclei can produce a time- and space-correlated triple coincidence signal in the JUNO detector. Based on a full Monte Carlo simulation informed with the latest available data, we estimate all backgrounds, including inverse beta decay events of the reactor antineutrino $\bar{\nu}_e$, natural radioactivity, cosmogenic isotopes and neutral current interactions of atmospheric neutrinos. Pulse shape discrimination and multivariate analysis techniques are employed to further suppress backgrounds. With two years of exposure, JUNO is expected to give an order of magnitude improvement compared to the current best limits. After 10 years of data taking, the JUNO expected sensitivities at a 90% confidence level are $\tau/B( n \rightarrow { inv} ) > 5.0 \times 10^{31} \, {\rm yr}$ and $\tau/B( nn \rightarrow { inv} ) > 1.4 \times 10^{32} \, {\rm yr}$

JUNO Sensitivity to Invisible Decay Modes of Neutrons

International audienceWe explore the bound neutrons decay into invisible particles (e.g., $n\rightarrow 3 \nu$ or $nn \rightarrow 2 \nu$) in the JUNO liquid scintillator detector. The invisible decay includes two decay modes: $n \rightarrow { inv}$ and $nn \rightarrow { inv}$. The invisible decays of $s$-shell neutrons in $^{12}{\rm C}$ will leave a highly excited residual nucleus. Subsequently, some de-excitation modes of the excited residual nuclei can produce a time- and space-correlated triple coincidence signal in the JUNO detector. Based on a full Monte Carlo simulation informed with the latest available data, we estimate all backgrounds, including inverse beta decay events of the reactor antineutrino $\bar{\nu}_e$, natural radioactivity, cosmogenic isotopes and neutral current interactions of atmospheric neutrinos. Pulse shape discrimination and multivariate analysis techniques are employed to further suppress backgrounds. With two years of exposure, JUNO is expected to give an order of magnitude improvement compared to the current best limits. After 10 years of data taking, the JUNO expected sensitivities at a 90% confidence level are $\tau/B( n \rightarrow { inv} ) > 5.0 \times 10^{31} \, {\rm yr}$ and $\tau/B( nn \rightarrow { inv} ) > 1.4 \times 10^{32} \, {\rm yr}$