HIGH ENERGY ZINC BATTERY SYSTEM WITH AN EXTREMELY WIDE OPERATING TEMPERATURE RANGE

Military and planetary application requires high energy density rechargeable battery with an extremely wide operating temperature range. Current rechargeable batteries only operate in a narrow range from -20 ℃ to 60 ℃. Low ionic conductivity of electrolyte and sluggish lithium ion diffusion of electrode at a low temperature, the irreversible phase transition at elevated temperature limit broadening operating temperature range of battery. In this research, a novel zinc battery LiFePO4/Li2ZnCl4.9H2O/Zn with wide operating temperature range between -70 ℃ and 70 ℃ has been developed. The Li2ZnCl4.9H2O electrolyte has very high ionic conductivity at -70 ℃, while the PEDOT coating on LiFePO4 reduce the side reaction at 70 ℃. At 70 ℃, LiFePO4@PEDOT/Li2ZnCl4.9H2O/Zn cells provide a capacity of 130 mAh.g-1 achieved over 20 cycles at 0.3 C, with a high rate capability. It also showed a stable cycling at -70 ℃ with 133 mAh.g-1 for 50 cycles at 0.1 C

Phase Synchrony Analysis of Rolling Bearing Vibrations and Its Application to Failure Identification

As the failure-induced component (FIC) in the vibration signals of bearings transmits through housings and shafts, potential phase synchronization is excited among multichannel signals. As phase synchrony analysis (PSA) does not involve the chaotic behavior of signals, it is suitable for characterizing the operating state of bearings considering complicated vibration signals. Therefore, a novel PSA method was developed to identify and track the failure evolution of bearings. First, resonance demodulation and variational mode decomposition (VMD) were combined to extract the mono-component or band-limited FIC from signals. Then, the instantaneous phase of the FIC was analytically solved using Hilbert transformation. The generalized phase difference (GPD) was used to quantify the relationship between FICs extracted from different vibration signals. The entropy of the GPD was regarded as the indicator for quantifying failure evolution. The proposed method was applied to the vibration signals obtained from an accelerated failure experiment and a natural failure experiment. Results showed that phase synchronization in bearing failure evolution was detected and evaluated effectively. Despite the chaotic behavior of the signals, the phase synchronization indicator could identify bearing failure during the initial stage in a robust manner

Preparation of Graphene Materials and Their Applications in the Field of Electrochemistry

In the development of modern society, many new materials and technologies have been integrated into the development of various industries. As a new type of two-dimensional carbon nanomaterials, graphene has great advantages in physical and chemical properties and is widely used in various fields of development. Among them, the electrochemical method is one of the important ways to prepare graphene materials, which has the characteristics of quickness and environmental protection, and can effectively produce a large amount of high-quality graphene and its composite materials. Based on this, the paper introduces the preparation method of graphene materials and studies the application of graphene materials in the field of electrochemistry

2-(2,3-Dioxoindolin-1-yl)ethyl 4-(4-nitro­phen­yl)piperazine-1-carbodithio­ate

In the title compound, C21H20N4O4S2, the piperazine ring adopts a chair conformation. The 1-ethyl­indoline-2,3-dione system links to one N atom of the piperazine ring via a carbodithio­ate group. The indoline-2,3-dione ring and the nitro­benzene ring subtend adihedral angle of 37.27 (7)°. In the crystal structure, weak C—H⋯O and π–π stacking inter­actions [centroid–centroid distances = 3.534 (5) and 3.797 (5) Å] may help to establish the packing

3,3-Dichloro-1-(chloro­meth­yl)indolin-2-one

In the title compound, C9H6Cl3NO, the pyrrole ring is almost coplanar with the benzene ring [dihedral angle = 1.90 (9)°], while the Cl—C—N—C torsion angle is 98.78 (17)°. In the crystal, pairs of mol­ecules are inter­connected by pairs of Cl⋯Cl inter­actions [3.564 (5) Å], forming dimers, which are further peripherally connected through inter­molecular C—H⋯O=C and π–π inter­actions [centroid–centroid distances = 4.134 (7), 4.134 (6) and 4.238 (7) Å], forming a two-dimensional network

Spectral Adversarial Training for Robust Graph Neural Network

Recent studies demonstrate that Graph Neural Networks (GNNs) are vulnerable to slight but adversarially designed perturbations, known as adversarial examples. To address this issue, robust training methods against adversarial examples have received considerable attention in the literature. \emph{Adversarial Training (AT)} is a successful approach to learning a robust model using adversarially perturbed training samples. Existing AT methods on GNNs typically construct adversarial perturbations in terms of graph structures or node features. However, they are less effective and fraught with challenges on graph data due to the discreteness of graph structure and the relationships between connected examples. In this work, we seek to address these challenges and propose Spectral Adversarial Training (SAT), a simple yet effective adversarial training approach for GNNs. SAT first adopts a low-rank approximation of the graph structure based on spectral decomposition, and then constructs adversarial perturbations in the spectral domain rather than directly manipulating the original graph structure. To investigate its effectiveness, we employ SAT on three widely used GNNs. Experimental results on four public graph datasets demonstrate that SAT significantly improves the robustness of GNNs against adversarial attacks without sacrificing classification accuracy and training efficiency.Comment: Accepted by TKDE. Code availiable at https://github.com/EdisonLeeeee/SA

Design of Single-Molecule Multiferroics for Efficient Ultrahigh-Density Nonvolatile Memories

It is known that an isolated single-molecule magnet tends to become super- paramagnetic even at an ultralow temperature of a few Kelvin due to the low spin switching barrier. Herein, single-molecule ferroelectrics/multiferroics is proposed, as the ultimate size limit of memory, such that every molecule can store 1 bit data. The primary strategy is to identify polar molecules that possess bistable states, moderate switching barriers, and polarizations fixed along the vertical direction for high-density perpendicular recording. First- principles computation shows that several selected magnetic metal porphyrin molecules possess buckled structures with switchable vertical polarizations that are robust at ambient conditions. When intercalated within a bilayer of 2D materials such as bilayer MoS2 or CrI3, the magnetization can alter the spin distribution or can be even switched by 180° upon ferroelectric switching, rendering efficient electric writing and magnetic reading. It is found that the upper limit of areal storage density can be enhanced by four orders of magnitude, from the previous super-paramagnetic limit of ≈40 to ≈106 GB in.−2, on the basis of the design of cross-point multiferroic tunneling junction array and multiferroic hard drive