Material innovation plays a very important role in technological progress and industrial development. Traditional experimental exploration and numerical simulation often require considerable time and ...resources. A new approach is urgently needed to accelerate the discovery and exploration of new materials. Machine learning can greatly reduce computational costs, shorten the development cycle, and improve computational accuracy. It has become one of the most promising research approaches in the process of novel material screening and material property prediction. In recent years, machine learning has been widely used in many fields of research, such as superconductivity, thermoelectrics, photovoltaics, catalysis, and high-entropy alloys. In this review, the basic principles of machine learning are briefly outlined. Several commonly used algorithms in machine learning models and their primary applications are then introduced. The research progress of machine learning in predicting material properties and guiding material synthesis is discussed. Finally, a future outlook on machine learning in the materials science field is presented.
An open-cell metal foam has excellent characteristics such as low density, high porosity, high specific surface area, high thermal conductivity, and low mass due to its unique internal ...three-dimensional network structure. It has gradually become a new material for enhanced heat transfer in industrial equipment, new compact heat exchangers, microelectronic device cooling, etc. This research established a comprehensive three-dimensional structural model of open-cell metal foams utilizing Laguerre–Voronoi tessellations and employed computational fluid dynamics to investigate its flow dynamics and coupled heat transfer performance. By exploring the impact of foam microstructure on flow resistance and heat transfer characteristics, the study provided insights into the overall convective heat transfer performance across a range of foam configurations with varying pore densities and porosities. The findings revealed a direct correlation between convective heat transfer coefficient (h) and pressure drop (ΔP) with increasing Reynolds number (Re), accompanied by notable changes in fluid turbulence kinetic energy (e) and temperature (T), ultimately influencing heat transfer efficiency. Furthermore, the analysis demonstrated that alterations in porosity (ε) and pore density significantly affected unit pressure drop (ΔP/L) and convective heat transfer coefficient (h). This study identified an optimal configuration, highlighting a metal foam with a pore density of 20 PPI and a porosity of 95% as exhibiting superior overall convective heat transfer performance.
Graphene has been regarded as a potential application material in the field of new energy conversion and storage because of its unique two-dimensional structure and excellent physical and chemical ...properties. However, traditional graphene preparation methods are complicated in-process and difficult to form patterned structures. In recent years, laser-induced graphene (LIG) technology has received a large amount of attention from scholars and has a wide range of applications in supercapacitors, batteries, sensors, air filters, water treatment, etc. In this paper, we summarized a variety of preparation methods for graphene. The effects of laser processing parameters, laser type, precursor materials, and process atmosphere on the properties of the prepared LIG were reviewed. Then, two strategies for large-scale production of LIG were briefly described. We also discussed the wide applications of LIG in the fields of signal sensing, environmental protection, and energy storage. Finally, we briefly outlined the future trends of this research direction.
Abstract
The chiral charge density wave is a many-body collective phenomenon in condensed matter that may play a role in unconventional superconductivity and topological physics. Two-dimensional ...chiral charge density waves provide the building blocks for the fabrication of various stacking structures and chiral homostructures, in which physical properties such as chiral currents and the anomalous Hall effect may emerge. Here, we demonstrate the phase manipulation of two-dimensional chiral charge density waves and the design of in-plane chiral homostructures in 1T-TaS
2
. We use chiral Raman spectroscopy to directly monitor the chirality switching of the charge density wave—revealing a temperature-mediated reversible chirality switching. We find that interlayer stacking favours homochirality configurations, which is confirmed by first-principles calculations. By exploiting the interlayer chirality-locking effect, we realise in-plane chiral homostructures in 1T-TaS
2
. Our results provide a versatile way to manipulate chiral collective phases by interlayer coupling in layered van der Waals semiconductors.
On‐skin sensors can precisely perceive important electrophysiological signals, including electroencephalogram (EEG), electrocardiogram (ECG), and electromyogram (EMG). Despite significant advances in ...the development of soft materials as electrode sensors, data acquisition (DAQ) unit—another indispensable component of on‐skin electronic sensory systems—typically exhibits bulkiness or unimodal sensing, which is detrimental to the portability of the sensory system or the comprehensiveness of the perceived information. Here, a portable and multimodal DAQ unit to tackle these challenges is designed. By assembling the DAQ unit with low‐impedance (<100 Ω) laser‐induced graphene on‐skin electrode sensors, a wireless communication module, a power supply module, and a 3D printed protective shell, the completed sensory system can realize three‐in‐one monitoring of EEG, ECG, and EMG with a light weight of 22 g and a low cost of $25. Moreover, a mobile App is developed to display the perceived electrophysiological signals in real time. Human–machine interface and embedded machine learning are demonstrated using the designed sensory system, indicating its potential applications in artificial intelligence. The success of this inexpensive three‐in‐one portable electronic sensory system sheds light on design, fabrication, and commercialization of multifunctional wearable electronics with wide applications in fitness tracking, medical diagnostics, and human–machine interface.
A three‐in‐one portable electronic system is developed for monitoring of EEG, ECG, and EMG signals. The system includes a self‐designed integrated circuit and low‐impedance laser‐induced graphene on‐skin electrode sensors. Besides multimodal electrophysiological signal monitoring, human–machine interface and embedded machine learning are demonstrated using the designed sensory system, indicating its potential applications in artificial intelligence.
Natural gas, whose primary constituent is methane, has been considered a convincing alternative for the growth of the energy supply worldwide. Adsorbed natural gas （ANG）, the most promising methane ...storage method, has been an active field of study in the past two decades. ANG constitutes a safe and low-cost way to store methane for natural gas vehicles at an acceptable energy density while working at substantially low pressures （3.5- 4.0 MPa）, allowing for conformable store tank. This work serves to review the state-of-the-art development reported in the scientific literature on adsorbents, adsorption theories, ANG conformable tanks, and related technolo- gies on ANG vehicles. Patent literature has also been searched and discussed. The review aims at illustrating both achievements and problems of the ANG technologies-based vehicles, as well as forecasting the development trends and critical issues to be resolved of these technologies.
The faults of rolling element bearings can result in the deterioration of machine operating conditions; how to assess the working condition and identify the fault of the rolling element bearing has ...become a key issue for ensuring the safe operation of modern rotating machineries. This paper presents a novel hybrid approach that detects bearing faults and monitors the operating status of rolling element bearings in modern rotating machineries. Based on redundant second-generation wavelet packet transform and local characteristic-scale decomposition, this method is implemented to extract the fault features, the vibration signal is adaptively decomposed into a number of desired intrinsic scale components by two-step screening processes based on the energy ratio, and reduce random noises and eliminate the pseudofrequency components. The fault features are then used to implement the identification classification of faults using singular value decomposition and extreme learning machine. The approach is evaluated by simulation and practical bearing vibration signals under different conditions. The experiment results show that the proposed approach is feasible and effective for the fault diagnosis of rolling element bearing.
•This work reviews the theoretical background of pressure drop for open cell foams.•Pressure drop was investigated on aluminum foams of a broad range of properties.•This work compares simulation ...result with theoretical predictions and experiments.•The heat transfer coefficients and friction factors of foams were evaluated.
This work reviews the theoretical backgrounds of pressure drop prediction for open cell foams. The pressure drop of open cell foams was investigated on aluminum foam structures of pore densities 10–50ppi and porosities 70–95%, with the commercial CFD analysis package: ANSYS Fluent, and performed over flow velocities ranging from 0.5m/s to 20m/s. The 3D foam structures were created by Laguerre-Voronoi tessellations. The numerical results for pressure drop were compared with the theoretical predictions by Inayat et al. and experimental data in the literature. The results show that the pressure drop of foams increases with increasing pore density and decreasing porosity. The numerical results are consistent with theoretical predictions and experimental data. The computed interfacial heat transfer coefficient was investigated. The Nusselt number increases with increasing Reynolds number, and increases with increasing porosity at constant pore density. The friction factor of foams was also evaluated.
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•Model can be used to analyze the effect of coefficient of variation on real foams.•The distribution of foam-cell volumes is dependent on sphere volumes distribution.•The statistical ...data of modeled foams is very close to that of real materials.•The average number of faces varies from 13.56 to 14.43 for different CVs.•Porosity decreases with ds/E(d), while surface area increases with ds/E(d).
This work proposes an original geometrical model based on randomly packed spheres using Laguerre-Voronoi tessellations to simulate geometrical and topological characteristics in the microstructure of open cell foams. The model can be used to analyze the effect of coefficient of variation on the pores distribution in real foams. The distribution of foam-cell volumes in foam structures generated in this work is dependent on the log-normal distribution of sphere volumes in corresponding randomly packed spheres. The statistical data of modeled foam structures, including distribution of the cell volume, face and edge number is very close to the characteristics of real materials. The results also show that a higher coefficient of variation in the sphere diameter would decrease the average number of faces per cell. The average number of faces varies from 13.56 to 14.43 for different coefficients of variation of sphere diameter, while the average number of faces in the Poisson-Voronoi tessellation structures is approximately 15.5. Furthermore, the porosity of foam structures, ε, decreases with the ratio of strut diameter to the average diameter of randomly packed spheres, ds/E(d), while the specific surface area of foams, SV, increases with ds/E(d).
The attitude parameters of the 3-D movement of an aircraft are indicators of an aircraft's operating state. A method of sequence screen-spot imaging based on the laser-aided cooperative target is ...presented to support the measurement of aircraft attitude parameters in ground test experiments. The laser-aided cooperative target is mounted on the aircraft surface and the laser spots are projected onto two fixed screen. High-speed cameras synchronously record the position of the laser spots on the screen. According to the position transformation relation between the coordinate systems, the aircraft attitude parameters can be calculated by analyzing the position of the sequence screen-spot image, which will change along with the aircraft attitude. A global calibration method based on the coplanar control points is proposed for the calibration of the measuring system. The experimental results show that the measurement accuracy of the attitude parameters for the proposed method is no more than 3' under the rotation angle from − 10° to + 10°. The proposed method can amplify the motion attitude of the aircraft by mounting the laser-aided cooperative target on the surface of the aircraft, which breaks the limitation of the geometric condition of the aircraft and improves the measurement accuracy.
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