Theoretical study of the open-flavor tetraquark Tcsˉ(2900)T_{c\bar{s}}(2900) in the process Λb→K0D0Λ\Lambda_b\to K^0D^0\Lambda

Recently, the LHCb Collaboration has measured the processes $B^0\to\bar{D}^0D_s^+\pi^-$ and $B^+\to\bar{D}^0D_s^+\pi^+$, where the $D_s^+\pi^-$ and $D_s^+\pi^+$ invariant mass distributions show the significant signals of two new open-flavor tetraquark states $T_{c\bar{s}}(2900)^0$ and $T_{c\bar{s}}(2900)^{++}$, as the two of the isospin triplet. In this work, we have investigated the process $\Lambda_b\to K^0D^0\Lambda$ by taking into account the intermediate nucleon resonance $N^*(1535)$ and the tetraquark state $T_{c\bar{s}}(2900)^0$, which could be dynamically generated by the interactions of the $D^*K^*/D^*_s\rho$ and the pseoduscalar mesons-octet baryons, respectively. Our results show that a clear peak of the open-flavor tetraquark $T_{c\bar{s}}(2900)$ may appear in the $K^0D^0$ invariant mass distribution of the process $\Lambda_b\to K^0D^0\Lambda$, which could be tested by future experiments.Comment: 9 pages, 11 figures, 1 tabl

Equivariant Neural Network Force Fields for Magnetic Materials

Neural network force fields have significantly advanced ab initio atomistic simulations across diverse fields. However, their application in the realm of magnetic materials is still in its early stage due to challenges posed by the subtle magnetic energy landscape and the difficulty of obtaining training data. Here we introduce a data-efficient neural network architecture to represent density functional theory total energy, atomic forces, and magnetic forces as functions of atomic and magnetic structures. Our approach incorporates the principle of equivariance under the three-dimensional Euclidean group into the neural network model. Through systematic experiments on various systems, including monolayer magnets, curved nanotube magnets, and moir\'e-twisted bilayer magnets of $\text{CrI}_{3}$, we showcase the method's high efficiency and accuracy, as well as exceptional generalization ability. The work creates opportunities for exploring magnetic phenomena in large-scale materials systems.Comment: 10 pages, 4 figure

Nebulization using ZnO/Si surface acoustic wave devices with focused interdigitated transducers

Propagation of surface acoustic waves (SAWs) on bulk piezoelectric substrates such as LiNbO3 and quartz, exhibits an in-plane anisotropic effect due to their crystal cut orientations. Thin film SAW devices, such as those based on ZnO or AlN, offer potential advantages, including isotropic wave velocities in all in-plane directions, higher power handling capability, and potentially lower failure rates. This paper reports experimental and simulation results of nebulization behaviour for water droplets using ZnO/Si surface acoustic wave devices with focused interdigital transducers (IDTs). Post-deposition annealing of the films at various temperatures was applied to improve the quality of the sputtering-deposited ZnO films, and 500 °C was found to be the optimal annealing temperature. Thin film ZnO/Si focused SAW devices were fabricated using the IDT designs with arc angles ranging from 30° to 90°. Nebulization was significantly enhanced with increasing the arc angles of the IDTs, e.g., increased nebulization rate, reduced critical powers required to initialise nebulization, and concentration of the nebulised plume into a narrower size of spray. Effects of applied RF power and droplet size have been systematically studied, and increased RF power and reduced droplet size significantly enhanced the nebulization phenomena

Phase Control on Surface for the Stabilization of High Energy Cathode Materials of Lithium Ion Batteries.

The development of high energy electrode materials for lithium ion batteries is challenged by their inherent instabilities, which become more aggravated as the energy densities continue to climb, accordingly causing increasing concerns on battery safety and reliability. Here, taking the high voltage cathode of LiNi0.5Mn1.5O4 as an example, we demonstrate a protocol to stabilize this cathode through a systematic phase modulating on its particle surface. We are able to transfer the spinel surface into a 30 nm shell composed of two functional phases including a rock-salt one and a layered one. The former is electrochemically inert for surface stabilization while the latter is designated to provide necessary electrochemical activity. The precise synthesis control enables us to tune the ratio of these two phases, and achieve an optimized balance between improved stability against structural degradation without sacrificing its capacity. This study highlights the critical importance of well-tailored surface phase property for the cathode stabilization of high energy lithium ion batteries

Mass Flow Measurement of Gas-Liquid Two-Phase CO2_2 in CCS Transportation Pipelines using Coriolis Flowmeters

Carbon Capture and Storage (CCS) is a promising technology that stops the release of CO$_2$ from industrial processes such as electrical power generation. Accurate measurement of CO$_2$ flows in a CCS system where CO$_2$ flow is a gas, liquid, or gas-liquid two-phase mixture is essential for the fiscal purpose and potential leakage detection. This paper presents a novel method based on Coriolis mass flowmeters in conjunction with least squares support vector machine (LSSVM) models to measure gas-liquid two-phase CO$_2$ flow under CCS conditions. The method uses a classifier to identify the flow pattern and individual LSSVM models for the metering of CO2 mass flowrate and prediction of gas volume fraction of CO$_2$, respectively. Experimental work was undertaken on a multiphase CO$_2$ flow test facility. Performance comparisons between the general LSSVM and flow pattern based LSSVM models are conducted. Results demonstrate that Coriolis mass flowmeters with the LSSVM model incorporating flow pattern identification algorithms perform significantly better than those using the general LSSVM model. The mass flowrate measurement of gas-liquid CO$_2$ is found to yield errors less than ±2% on the horizontal pipeline and ±1.5% on the vertical pipeline, respectively, over flowrates from 250 kg/h to 3200 kg/h. The error in the estimation of CO$_2$ gas volume fraction is within ±10% over the same range of flow rates

Application of Soft Computing Techniques to Multiphase Flow Measurement: A Review

After extensive research and development over the past three decades, a range of techniques have been proposed and developed for online continuous measurement of multiphase flow. In recent years, with the rapid development of computer hardware and machine learning, soft computing techniques have been applied in many engineering disciplines, including indirect measurement of multiphase flow. This paper presents a comprehensive review of the soft computing techniques for multiphase flow metering with a particular focus on the measurement of individual phase flowrates and phase fractions. The paper describes the sensors used and the working principle, modelling and example applications of various soft computing techniques in addition to their merits and limitations. Trends and future developments of soft computing techniques in the field of multiphase flow measurement are also discussed

Mechanism for Selective Binding of Aromatic Compounds on Oxygen-Rich Graphene Nanosheets Based on Molecule Size/Polarity Matching

Selective binding of organic compounds is the cornerstone of many important industrial and pharmaceutical applications. Here, we achieved highly selective binding of aromatic compounds in aqueous solution and gas phase by oxygen-enriched graphene oxide (GO) nanosheets via a previously unknown mechanism based on size matching and polarity matching. Oxygen-containing functional groups (predominately epoxies and hydroxyls) on the nongraphitized aliphatic carbons of the basal plane of GO formed highly polar regions that encompass graphitic regions slightly larger than the benzene ring. This facilitated size match–based interactions between small apolar compounds and the isolated aromatic region of GO, resulting in high binding selectivity relative to larger apolar compounds. The interactions between the functional group(s) of polar aromatics and the epoxy/hydroxyl groups around the isolated aromatic region of GO enhanced binding selectivity relative to similar-sized apolar aromatics. These findings provide opportunities for precision separations and molecular recognition enabled by size/polarity match–based selectivity