Boosting the sodium storage performance of iron selenides by a synergetic effect of vacancy engineering and spatial confinement

Recently, iron selenides have been considered as one of the most promising candidates for the anodes of sodium-ion batteries (SIBs) due to their cost-effectiveness and high theoretical capacity; however, their practical application is limited by poor conductivity, large volume variation and slow reaction kinetics during electrochemical reactions. In this work, spatially dual-carbon-confined Vₛₑ-Fe₃Se₄₋ₓSₓ/FeSe₂₋ₓSₓ nanohybrids with abundant Se vacancies (Vₛₑ-Fe₃Se₄₋ₓSₓ/FeSe₂₋ₓSₓ@NSC@rGO) are constructed via anion doping and carbon confinement engineering. The three-dimensional crosslinked carbon network composed of the nitrogen-doped carbon support derived from polyacrylic acid (PAA) and reduced graphene enhances the electronic conductivity, provides abundant channels for ion/electron transfer, ensures the structure integrity, and alleviates the agglomeration, pulverization and volume change of active material during the chemical reactions. Moreover, the introduction of S into iron selenides induces a large number of Se vacancies and regulates the electron density around iron atoms, synergistically improving the conductivity of the material and reducing the Na+ diffusion barrier. Based on the aforementioned features, the as-synthesized Vₛₑ-Fe₃Se₄₋ₓSₓ/FeSe₂₋ₓSₓ@NSC@rGO electrode possesses excellent electrochemical properties, exhibiting the satisfactory specific capacity of 630.1 mA h g−¹ after 160 cycles at 0.5 A/g and the reversible capacity of 319.8 mA h g−¹ after 500 cycles at 3 A/g with the low-capacity attenuation of 0.016 % per cycle. This investigation provides a feasible approach to develop high-performanc

Heterogeneous engineering and carbon confinement strategy to synergistically boost the sodium storage performance of transition metal selenides

Transition metal selenides (TMSs) stand out as a promising anode material for sodium-ion batteries (SIBs) owing to their natural resources and exceptional sodium storage capacity. Despite these advantages, their practical application faces challenges, such as poor electronic conductivity, sluggish reaction kinetics and severe agglomeration during electrochemical reactions, hindering their effective utilization. Herein, the dual-carbon-confined CoSe /FeSe @NC@C nanocubes with heterogeneous structure are synthesized using ZIF-67 as the template by ion exchange, resorcin-formaldehyde (RF) coating, and subsequent in situ carbonization and selenidation. The N-doped porous carbon promotes rapid electrolyte penetration and minimizes the agglomeration of active materials during charging and discharging, while the RF-derived carbon framework reduces the cycling stress and keeps the integrity of the material structure. More importantly, the built-in electric field at the heterogeneous boundary layer drives electron redistribution, optimizing the electronic structure and enhancing the reaction kinetics of the anode material. Based on this, the nanocubes of CoSe /FeSe @NC@C exhibits superb sodium storage performance, delivering a high discharge capacity of 512.6 mA h g at 0.5 A g after 150 cycles and giving a discharge capacity of 298.2 mA h g at 10 A g with a CE close to 100.0 % even after 1000 cycles. This study proposes a viable method to synthesize advanced anodes for SIBs by a synergy effect of heterogeneous interfacial engineering and a carbon confinement strategy. [Abstract copyright: Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.

Potential of Core-Collapse Supernova Neutrino Detection at JUNO

JUNO is an underground neutrino observatory under construction in Jiangmen, China. It uses 20kton liquid scintillator as target, which enables it to detect supernova burst neutrinos of a large statistics for the next galactic core-collapse supernova (CCSN) and also pre-supernova neutrinos from the nearby CCSN progenitors. All flavors of supernova burst neutrinos can be detected by JUNO via several interaction channels, including inverse beta decay, elastic scattering on electron and proton, interactions on C12 nuclei, etc. This retains the possibility for JUNO to reconstruct the energy spectra of supernova burst neutrinos of all flavors. The real time monitoring systems based on FPGA and DAQ are under development in JUNO, which allow prompt alert and trigger-less data acquisition of CCSN events. The alert performances of both monitoring systems have been thoroughly studied using simulations. Moreover, once a CCSN is tagged, the system can give fast characterizations, such as directionality and light curve

Detection of the Diffuse Supernova Neutrino Background with JUNO

As an underground multi-purpose neutrino detector with 20 kton liquid scintillator, Jiangmen Underground Neutrino Observatory (JUNO) is competitive with and complementary to the water-Cherenkov detectors on the search for the diffuse supernova neutrino background (DSNB). Typical supernova models predict 2-4 events per year within the optimal observation window in the JUNO detector. The dominant background is from the neutral-current (NC) interaction of atmospheric neutrinos with 12C nuclei, which surpasses the DSNB by more than one order of magnitude. We evaluated the systematic uncertainty of NC background from the spread of a variety of data-driven models and further developed a method to determine NC background within 15\% with {\it{in}} {\it{situ}} measurements after ten years of running. Besides, the NC-like backgrounds can be effectively suppressed by the intrinsic pulse-shape discrimination (PSD) capabilities of liquid scintillators. In this talk, I will present in detail the improvements on NC background uncertainty evaluation, PSD discriminator development, and finally, the potential of DSNB sensitivity in JUNO

Real-time Monitoring for the Next Core-Collapse Supernova in JUNO

Core-collapse supernova (CCSN) is one of the most energetic astrophysical events in the Universe. The early and prompt detection of neutrinos before (pre-SN) and during the SN burst is a unique opportunity to realize the multi-messenger observation of the CCSN events. In this work, we describe the monitoring concept and present the sensitivity of the system to the pre-SN and SN neutrinos at the Jiangmen Underground Neutrino Observatory (JUNO), which is a 20 kton liquid scintillator detector under construction in South China. The real-time monitoring system is designed with both the prompt monitors on the electronic board and online monitors at the data acquisition stage, in order to ensure both the alert speed and alert coverage of progenitor stars. By assuming a false alert rate of 1 per year, this monitoring system can be sensitive to the pre-SN neutrinos up to the distance of about 1.6 (0.9) kpc and SN neutrinos up to about 370 (360) kpc for a progenitor mass of 30$M_{\odot}$ for the case of normal (inverted) mass ordering. The pointing ability of the CCSN is evaluated by using the accumulated event anisotropy of the inverse beta decay interactions from pre-SN or SN neutrinos, which, along with the early alert, can play important roles for the followup multi-messenger observations of the next Galactic or nearby extragalactic CCSN.Comment: 24 pages, 9 figure

Co-Pigmentation Mechanism and Thermal Reaction Kinetics of Mulberry Anthocyanins with Different Phenolic Acids

Applying the intermolecular co-pigmentation to improve the stability of mulberry anthocyanins is an important co-pigment method. Seven co-pigments, ferulic acid (FA), caffeic acid (CA), p-hydroxybenzoic acid (HBA), protocatechuic acid (PA), gallic acid (GA), vanillic acid (VA) and vanillin (VN) were selected to investigate mulberry anthocyanin co-pigmentation thermal reaction kinetics. The strongest co-pigment reactions were observed for FA at a molar ratio of 1:20, pH 3.5 and 20 °C, with the highest hyperchromic effects (52.94%), equilibrium constant (K) values (3.51) and negative values of Gibbs free energy (ΔG°) (−3.06 KJ/mol). Co-pigments that contained more free hydroxyl groups facilitated the co-pigmentation, and methyl contributed more to color enhancement, with respect to the hydrogen group. Ultra Performance Liquid Chromatography-Quadrupole-Time Of Flight-Mass/Mass Spectrometry (UPLC-Q-TOF-MS/MS) results indicated that FA and CA formed different anthocyanin derivatives with mulberry anthocyanin. The Fourier Transform Infrared Spectroscopy (FTIR) and molecular docking confirmed that hydrogen bonding, π–π stacking and hydrophobic interaction were formed between anthocyanins and three prevalent co-pigments (FA, CA and VA). CA and C3G could form four hydrogen bonds and two π–π stackings; this was the most stable system among three phenolic acid–C3G complexes. Due to the functional effect of phenolic acids, the addition of FA and CA not only enhanced the stability and color intensity of mulberry anthocyanins but also the functionality of the processing product

Clustering Classes in Packages for Program Comprehension

During software maintenance and evolution, one of the important tasks faced by developers is to understand a system quickly and accurately. With the increasing size and complexity of an evolving system, program comprehension becomes an increasingly difficult activity. Given a target system for comprehension, developers may first focus on the package comprehension. The packages in the system are of different sizes. For small-sized packages in the system, developers can easily comprehend them. However, for large-sized packages, they are difficult to understand. In this article, we focus on understanding these large-sized packages and propose a novel program comprehension approach for large-sized packages, which utilizes the Latent Dirichlet Allocation (LDA) model to cluster large-sized packages. Thus, these large-sized packages are separated as small-sized clusters, which are easier for developers to comprehend. Empirical studies on four real-world software projects demonstrate the effectiveness of our approach. The results show that the effectiveness of our approach is better than Latent Semantic Indexing- (LSI-) and Probabilistic Latent Semantic Analysis- (PLSA-) based clustering approaches. In addition, we find that the topic that labels each cluster is useful for program comprehension

Rod-like Ni-CoS

Currently, conversion-type transition metal sulfides have been extensively favored as the anodes for sodium-ion batteries due to their excellent redox reversibility and high theoretical capacity; however, they generally suffer from large volume expansion and structural instability during repeatedly Na de/intercalation. Herein, spatially dual-confined Ni-doped CoS @NC@C microrods (Ni-CoS @NC@C) are developed via structural design, heteroatom doping and carbon confinement to boost sodium storage performance of the material. The morphology of one-dimensional-structured microrods effectively enlarges the electrode/electrolyte contact area, while the confinement of dual-carbon layers greatly alleviates the volume change-induced stress, pulverization, agglomeration of the material during charging and discharging. Moreover, the introduction of Ni improves the electrical conductivity of the material by modulating the electronic structure and enlarges the interlayer distance to accelerate Na diffusion. Accordingly, the as-prepared Ni-CoS @NC@C exhibits superb electrochemical properties, delivering the satisfactory cycling performance of 526.6 mA h g after 250 cycles at 1 A g , excellent rate performance of 410.9 mA h g at 5 A g and superior long cycling life of 502.5 mA h g after 1,500 cycles at 5 A g . This study provides an innovative idea to improve sodium storage performance of conversion-type transition metal sulfides through the comprehensive strategy of structural design, heteroatom doping and carbon confinement

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 $\tau/B( nn \rightarrow { inv} ) > 1.4 \times 10^{32} \, {\rm yr}$