Search Results (76)

To enhance the mechanical properties of NbMoTaW refractory high-entropy alloys (RHEAs), Si was added at varying concentrations (x = 0, 0.25, and 0.5) via vacuum induction levitation melting (re-melted six times for homogeneity). The microstructure and mechanical properties of NbMoTaWSi_x (x = 0, 0.25, and 0.5) RHEAs were characterized using scanning electron microscopy (SEM), universal testing, microhardness testing, and tribological equipment. Experimental results manifested that Si addition induces the formation of the (Nb,Ta)₅Si₃ phase, and the volume fraction of the silicide phase increases with higher Si content, which significantly improves the alloy’s strength and hardness but deteriorates its plasticity. Enhanced wear resistance with Si addition is attributed to improved hardness and oxidation resistance. Tribological tests confirm that Si₃N₄ counterfaces are optimal for evaluating RHEA wear mechanisms. This work can provide guidance for the fabrication of RHEAs with excellent performance. Full article

Hyperbolic plasmons are a highly desired property in optoelectronics and biomolecular sensing. The necessary condition to realize hyperbolic plasmons is a significant anisotropy of the principal components of the dielectric function, such that at a certain frequency range, one component is negative and the other is positive, i.e., one component is metallic, and the other one is dielectric. Here, we study the effect of anisotropy in ${\mathrm{ReS}}_2$, and our theory shows that ${\mathrm{ReS}}_2$ can host hyperbolic plasmons in the ultraviolet frequency range. The operating frequency range of the hyperbolic plasmons can be tuned with the number of ${\mathrm{ReS}}_2$ layers. However, we note that the significantly large imaginary part of the macroscopic dielectric response in all layered variants of ReS₂ can result in substantial losses for the hyperbolic plasmons, as in the case with other known hyperbolic materials, with the exception of MoOCl₂. We also note that ReS₂ hosts ultraviolet hyperbolic plasmons while ZrSiSe, WTe₂, and CuS nanocrystals host infrared plasmons, providing a novel platform for optoelectronics in the ultraviolet range. Full article

One of the key challenges in commercializing proton exchange membrane (PEM) electrolyzer technology is reducing the production costs while maintaining high efficiency and operational stability. Significant contributors to the overall cost of the device are the electrode catalysts with IrO₂ and Pt/C. Due to the high cost and limited availability of noble metals, there is growing interest in developing alternative, low-cost catalytic materials. In recent years, two-dimensional transition metal dichalcogenides (2D TMDCs), such as molybdenum disulfide (MoS₂) and rhenium disulfide (ReS₂), have attracted considerable attention due to their promising electrochemical properties for hydrogen evolution reactions (HERs). These materials exhibit unique properties, such as a high surface area or catalytic activity localized at the edges of the layered structure, which can be further enhanced through defect engineering or phase modulation. To increase the catalytically active surface area, the investigated materials were deposited on a carbon-based support—Vulcan XC-72R—selected for its high electrical conductivity and large specific surface area. This study investigated the physicochemical and electrochemical properties of six catalyst samples with varying MoS₂ and ReS₂ to carbon support ratios. Among the composites analyzed, the best sample on MoS₂ (containing the most carbon soot) and the best sample on ReS₂ (containing the least carbon soot) were selected. These were then used as cathode catalysts in an experimental PEM electrolyzer setup. The results confirmed satisfactory catalytic activity of the tested materials, indicating their potential as alternatives to conventional noble metal-based catalysts and providing a foundation for further research in this area. Full article

Background: Limited availability of high-quality labeled biomedical image datasets presents a significant challenge for training deep learning models in medical diagnostics. This study proposes a novel image generation framework combining conditional generative adversarial networks (cGANs) with a Mixture-of-Experts (MoE) architecture and color histogram-aware loss functions to enhance synthetic blood cell image quality. Methods: RGB microscopic images from the BloodMNIST dataset (eight blood cell types, resolution 3 × 128 × 128) underwent preprocessing with k-means clustering to extract the dominant colors and UMAP for visualizing class similarity. Spearman correlation-based distance matrices were used to evaluate the discriminative power of each RGB channel. A MoE–cGAN architecture was developed with residual blocks and LeakyReLU activations. Expert generators were conditioned on cell type, and the generator’s loss was augmented with a Wasserstein distance-based term comparing red and green channel histograms, which were found most relevant for class separation. Results: The red and green channels contributed most to class discrimination; the blue channel had minimal impact. The proposed model achieved 0.97 classification accuracy on generated images (ResNet50), with 0.96 precision, 0.97 recall, and a 0.96 F1-score. The best Fréchet Inception Distance (FID) was 52.1. Misclassifications occurred mainly among visually similar cell types. Conclusions: Integrating histogram alignment into the MoE–cGAN training significantly improves the realism and class-specific variability of synthetic images, supporting robust model development under data scarcity in hematological imaging. Full article

Compared to traditional temperature measurement methods, ultrasonic temperature measurement technology based on the principle of resonance offers advantages such as shorter section lengths, higher signal amplitude, and reduced signal attenuation. First, the type of sensor-sensitive element was determined, with a resonant design chosen to improve measurement performance; using magnetostrictive and resonant temperature measurement principles, the length, diameter, and resonator dimensions of the waveguide rod were designed, and a molybdenum–rhenium alloy (Mo-5%Re) material suitable for high-temperature environments was selected; COMSOL finite element simulation was used to simulate the propagation characteristics of acoustic signals in the waveguide rod, observing the distribution of sound pressure and energy attenuation, verifying the applicability of the model in high-temperature testing environments. Second, a resonant temperature sensor consistent with the simulation parameters was prepared using a molybdenum–rhenium alloy waveguide rod, and an ultrasonic resonant temperature-sensing system suitable for high-temperature environments up to 1800 °C was constructed using the molybdenum–rhenium alloy waveguide rod. The experiment used a tungsten–rhenium calibration furnace to perform static calibration of the sensor. The temperature range was set from room temperature to 1800 °C, with the temperature increased by 100 °C at a time, and it was maintained at each temperature point for 5 to 10 min to ensure thermal stability. This was conducted to verify the performance of the sensor and obtain the functional relationship between temperature and resonance frequency. Experimental results show that during the heating process, the average resonance frequency of the sensor decreased from 341.8 kHz to 310.37 kHz, with an average sensitivity of 17.66 Hz/°C. During the cooling process, the frequency increased from 309 kHz to 341.8 kHz, with an average sensitivity of 18.43 Hz/°C. After cooling to room temperature, the sensor’s resonant frequency returned to its initial value of 341.8 kHz, demonstrating excellent repeatability and thermal stability. This provides a reliable technical foundation for its application in actual high-temperature environments. Full article

One-dimensional (1D) nanomaterials have attracted considerable attention in the fabrication of nano-scale optoelectronic devices owing to their large specific surface areas, high surface-to-volume ratios, and directional electron transport channels. Compared to 1D metal oxide nanostructures, 1D metal sulfides have emerged as promising candidates for high-efficiency photodetectors due to their abundant surface vacancies and trap states, which facilitate oxygen adsorption and dissociation on their surfaces, thereby suppressing intrinsic carrier recombination while achieving enhanced optoelectronic performance. This review focuses on recent advancements in the performance of photodetectors fabricated using 1D binary metal sulfides as primary photosensitive layers, including nanowires, nanorods, nanotubes, and their heterostructures. Initially, the working principles of photodetectors are outlined, along with the key parameters and device types that influence their performance. Subsequently, the synthesis methods, device fabrication, and photoelectric properties of several extensively studied 1D metal sulfides and their composites, such as ZnS, CdS, SnS, Bi₂S₃, Sb₂S₃, WS₂, and SnS₂, are examined. Additionally, the current research status of 1D nanostructures of MoS₂, TiS₃, ReS₂, and In₂S₃, which are predominantly utilized as 2D materials, is explored and summarized. For systematic performance evaluation, standardized metrics encompassing responsivity, detectivity, external quantum efficiency, and response speed are comprehensively tabulated in dedicated sub-sections. The review culminates in proposing targeted research trajectories for advancing photodetection systems employing 1D binary metal sulfides. Full article

sEMG is a non-invasive biomedical engineering technique that can detect and record electrical signals generated by muscles, reflecting both motor intentions and the degree of muscle contraction. This study aims to classify and recognize nine types of upper limb motor intentions based on surface electromyography (sEMG) and apply them to the interactive control of an end-effector rehabilitation robot. The research begins with selecting muscles and data preprocessing, incorporating the generation mechanism of sEMG along with the anatomical and kinesiological principles of upper limb muscles. Next, a musculoskeletal model of the upper limb is established and validated through simulations in OpenSim. To avoid the drawbacks of modeling methods, traditional machine learning and deep learning methods are employed to perform a nine-class classification task on the sEMG data, comparing the classification accuracy of different approaches. Finally, the motor intentions extracted using a multi-stream convolutional neural network (MLCNN) are utilized to control the iReMo^® end-effector rehabilitation robot, with the system’s motion smoothness and accuracy evaluated through tests involving different trajectories. Full article

Molybdenite Re–Os and zircon U–Pb isotopic data are first obtained from the stockwork and disseminated-style gold-bearing ores and the fine-grained granite hosting these ores in the Xiawolong gold mine, respectively, which is located within the Muping–Rushan gold metallogenic belt, eastern Jiaodong Peninsula, so as to illustrate the genesis of gold mineralization and its implication for exploration. Four molybdenite samples yield a well-defined Re–Os isochron age of 118.4 ± 2.5 Ma (2σ), which is identical to the weighted average Re–Os model age of 118 ± 1.7 Ma (2σ). Integration of the new geochronologic data with those reported recently from the other gold mines in the Muping–Rushan gold metallogenic belt suggests that a discrete gold event occurred in Xiawolong ca. 4 m.y. older than that for the other gold mineralization at ca. 114 Ma in eastern Jiaodong. In addition, two fine-grained granite samples, measured using the LA-ICP-MS zircon U–Pb method, produce the first precise ages of 118 ± 2 to 117 ± 2 Ma (2σ), identical to the molybdenite Re–Os ages, within the margin of error and obtained in this study. The fine-grained granite has a similar lithology and emplacement age as those of the medium-grained monzogranite consisting of the marginal facies of the Sanfoshan batholith, and is considered to be the crystallization products of Sanfoshan granitic magma in the late stage. Combined with the previous S-Pb-D-O isotope, fluid inclusion and geological studies, which suggest that the ore-forming fluid of Xiawolong gold mineralization is from magmatic water, and the identification that the magnetite coexists with the gold-bearing pyrite and molybdenite in the gold ores, which indicates a high oxygen fugacity (fO₂) of both the magma and resultant hydrothermal fluids, it is logical to infer that the Xiawolong gold deposit is genetically in relation to the Sanfoshan granitic magmatism, which is high in fO₂ and rich in Au at the magmatic–hydrothermal transition stage, and the change in fO₂ mostly likely makes a significant contribution to the precipitation of Au. This result reveals that the late-stage granitic magma with high fO₂, which is crystallized into the fine-grained granite, probably is also rich in Au, except the W–Mo–Cu–Zn–U–Be–Li–Nb–Ta–Sn–Bi-elements. Therefore, based on the extensional tectonic regime for the early Cretaceous Jiaodong gold deposits, we propose that gold exploration in the Jiaodong should not only focus on the fault-hosted Au but also on the fine-grained granite-hosted Au around the apical portions of the late Early Cretaceous small-granitic intrusions with high fO₂. This model could also be important for prospecting in other gold ore districts, which have a similar tectonic setting. Full article

The 1500 km-long Gangdese magmatic belt is a crucial region for copper polymetallic mineralization, offering valuable insights into collisional porphyry copper systems. This study focuses on the Demingding deposit, a newly identified occurrence of molybdenum–copper (Mo-Cu) mineralization within the eastern segment of the belt. While the mineralization age, magmatic characteristics, and tectonic context are still under investigation, we examine the deposit’s petrology, zircon U-Pb geochronology, whole-rock chemistry, and Re-Os isotopic data. The Demingding deposit exhibits a typical alteration zoning, transitioning from an inner potassic zone to an outer propylitic zone, which is significantly overprinted by phyllic alteration closely associated with Mo and Cu mineralization. Zircon U-Pb dating of the ore-forming monzogranite porphyries reveals crystallization ages ranging from 21 to 19 Ma, which is indistinguishable within error from the mean Re-Os age of 21.3 ± 0.4 Ma for Mo veins and veinlets hosted by these porphyries. This alignment suggests a late Miocene magmatic event characterized by Mo-dominated mineralization, coinciding with the continuous thickening of the continental crust during the collision of the Indian and Asian continents. The ore-forming porphyries range in composition from granodiorite to monzogranite and are classified as high-K calc-alkaline with adakite-like features, primarily resulting from the partial melting of subduction-modified thickened mafic lower crust. Notably, the ore-forming porphyries exhibit higher fO₂ and H₂O levels than barren porphyries in this area during crustal thickening, highlighting the significant contributions of hydrous and oxidized fluids from their source to the Mo-Cu mineralization process. Regional data indicate that the Gangdese porphyry metallogenic belt experienced concentrated Cu-Mo mineralization between 17 and 13 Ma. The formation of Mo-dominated deposits such as Demingding and Tangbula in the eastern segment of the belt, with slightly older ages around 20 Ma, underscores the presence of a significant porphyry Mo metallogenic event during this critical post-collision mineralization period. Full article

Strain engineering provides an attractive approach to enhance device performance by modulating the intrinsic electrical properties of materials. This is especially applicable to 2D materials, which exhibit high sensitivity to mechanical stress. However, conventional methods, such as using polymer substrates, to apply strain have limitations in that the strain is temporary and global. Here, we introduce a novel approach to induce permanent localized strain by fabricating a stressor on SiO₂/Si substrates using fiber laser irradiation, thereby enabling precise control of the surface topography. MoS₂ is transferred onto this stressor, which results in the application of ~0.8% tensile strain. To assess the impact of the internal strain on the operation of ReRAM devices, the flat-MoS₂-based and the strained-MoS₂-based devices are compared. Both devices demonstrate forming-free, bipolar, and non-volatile switching characteristics. The strained devices exhibit a 30% reduction in the operating voltage, which can be attributed to bandgap narrowing and enhanced carrier mobility. Furthermore, the strained devices exhibit nearly a two-fold improvement in endurance, presumably because of the enhanced stability from lattice release effect. These results emphasize the potential of strain engineering for advancing the performance and durability of next-generation memory devices. Full article

Steam turbine blades may crack, break, or suffer other failures due to high temperatures, high pressures, and high-speed rotation, which seriously threatens the safety and reliability of the equipment. The signal characteristics of different fault types are slightly different, making it difficult to accurately classify the faults of rotating blades directly through vibration signals. This method combines a one-dimensional convolutional neural network (1DCNN) and a channel attention mechanism (CAM). 1DCNN can effectively extract local features of time series data, while CAM assigns different weights to each channel to highlight key features. To further enhance the efficacy of feature extraction and classification accuracy, a projection head is introduced in this paper to systematically map all sample features into a normalized space, thereby improving the model’s capacity to distinguish between distinct fault types. Finally, through the optimization of a supervised contrastive learning (SCL) strategy, the model can better capture the subtle differences between different fault types. Experimental results show that the proposed method has an accuracy of 99.61%, 97.48%, and 96.22% in the classification task of multiple crack fault types at three speeds, which is significantly better than Multilayer Perceptron (MLP), Residual Network (ResNet), Momentum Contrast (MoCo), and Transformer methods. Full article

The Waxing Mo polymetallic deposit is located in the central part of the Lesser Xing’an–Zhangguangcai Range (LXZR), NE China. The Mo (Cu) mineralization in the deposit is dominantly hosted by quartz veinlets and stockworks and is closely related to silicification and potassic alteration, while the W mineralization is most closely related to greisenization. Zircon samples from granodiorite, biotite monzogranite, granodiorite porphyry, and syenogranite in the Waxing deposit yielded U-Pb ages of 172.3 Ma, 172.8 Ma, 173.0 Ma, and 171.4 Ma, respectively. Six molybdenite samples from porphyry Mo ores yielded a Re-Os isochron age of 172.0 ± 1.1 Ma. The granitoids in the ore district are relatively high in total alkali (Na₂O + K₂O), are metaluminous to weakly peraluminous, and are classified as I-type granitoids. The zircon samples from all granitoids showed a relatively consistent Hf isotopic composition, as shown by positive ε_Hf(t) values (3.1–8.3) and young T_DM2 ages (0.69–1.25 Ga). These results, combined with the whole-rock geochemistry, suggest that the magma source of these rocks most likely derived from partial melting of a juvenile middle-lower continental crust, with a minor contribution from the mantle. These granitoids have compositional characteristics of adakites such as relatively high Sr contents (e.g., >400 ppm) and Sr/Y ratios (e.g., >33), as well as weak Eu anomalies (e.g., Eu/Eu* = 0.8–1.1), indicating extensive fractionation crystallization of a hydrous magma. The apatite geochemistry indicates that the ore-related magma in Waxing is F-rich and has a relatively low content of sulfur. The zircon geochemistry reveals that the granodiorite, biotite monzogranite, and granodiorite porphyry have relatively high oxygen fugacity (i.e., ΔFMQ = +1.1~1.3), whereas the fO₂ values of the granite porphyry and syenogranite are relatively low (i.e., ΔFMQ = +0.1~0.5). The whole-rock and mineral geochemistry suggest that the Mo mineralization in Waxing is probably genetically related to granitoids (i.e., granodiorite, biotite monzogranite, and granodiorite porphyry), with higher oxygen fugacity and a high water content, whereas the magmatic S concentration is not the key factor controlling the mineralization. A comparison of the geochemical compositions of ore-forming and barren stocks for porphyry Mo deposits in the LXZR showed that geochemical ratios, including Eu/Eu* (>0.8), 10,000*(Eu/Eu*)/Y (>600), Sr/Y (>33), and V/Sc (>8), could be effective indicators in discriminating fertile granitoids for porphyry Mo deposits from barren ones in the region. Full article

Nowadays, disruptive events pose significant threats to organizations, making resilience a critical focus. Evaluating supply chain resilience is essential to avoid escalating disruptions. However, the literature on this topic is fragmented, and the assessment of resilience remains an open gap due to the lack of a clear definition of the dimensions and elements for its evaluation. To fill this gap, this study integrates a systematic literature review (SLR) and a systematic literature network analysis (SLNA) to propose a MAturity MOdel for REsilient Supply Chains (MaMoReS). Through content analysis and stringent selection of 15 resilience maturity models (ResMMs) via SLR, along with an SLNA on 6,474 sources, this method defines dimensions and sub-dimensions. The proposed MaMoReS is framed around five levels and five dimensions: risk management, agility, flexibility and adaptability, redundancy and robustness, transparency and visibility, and collaboration and relationships. The MaMoReS is applied to two case studies, pinpointing the practicality of the MaMoReS for measuring the resilience maturity level of the two companies along with their dimensions and sub-dimensions scoring. Thus, the MaMoReS can be used as an assessment tool by supply chain managers and researchers to evaluate the resilience of a supply chain. Full article

Greek giant beans, also known as “Gigantes Elefantes” (elephant beans, Phaseolus vulgaris L.,) are a traditional and highly cherished culinary delight in Greek cuisine, contributing significantly to the economic prosperity of local producers. However, the issue of food fraud associated with these products poses substantial risks to both consumer safety and economic stability. In the present study, multi-elemental analysis combined with decision tree learning algorithms were investigated for their potential to determine the multi-elemental profile and discriminate the origin of beans collected from the two geographical areas. Ensuring the authenticity of agricultural products is increasingly crucial in the global food industry, particularly in the fight against food fraud, which poses significant risks to consumer safety and economic stability. To ascertain this, an extensive multi-elemental analysis (Ag, Al, As, B, Ba, Be, Ca, Cd, Co, Cr, Cs, Cu, Fe, Ga, Ge, K, Li, Mg, Mn, Mo, Na, Nb, Ni, P, Pb, Rb, Re, Se, Sr, Ta, Ti, Tl, U, V, W, Zn, and Zr) was performed using Inductively Coupled Plasma Mass Spectrometry (ICP-MS). Bean samples originating from Kastoria and Prespes (products with Protected Geographical Indication (PGI) status) were studied, focusing on the determination of elemental profiles or fingerprints, which are directly related to the geographical origin of the growing area. In this study, we employed a decision tree algorithm to classify Greek “Gigantes Elefantes” beans based on their multi-elemental composition, achieving high performance metrics, including an accuracy of 92.86%, sensitivity of 87.50%, and specificity of 96.88%. These results demonstrate the model’s effectiveness in accurately distinguishing beans from different geographical regions based on their elemental profiles. The trained model accomplished the discrimination of Greek “Gigantes Elefantes” beans from Kastoria and Prespes, with remarkable accuracy, based on their multi-elemental composition. Full article

Energy harvesting systems fabricated from rubber composite materials are promising due to their ability to produce green energy with no environmental pollution. Thus, the present work investigated energy harvesting through piezoelectricity using rubber composites. These composites were fabricated by mixing titanium carbide (TiC) and molybdenum disulfide (MoS₂) as reinforcing and electrically conductive fillers into a silicone rubber matrix. Excellent mechanical and electromechanical properties were produced by these composites. For example, the compressive modulus was 1.55 ± 0.08 MPa (control) and increased to 1.95 ± 0.07 MPa (6 phr or per hundred parts of rubber of TiC) and 2.02 ± 0.09 MPa (6 phr of MoS₂). Similarly, the stretchability was 133 ± 7% (control) and increased to 153 ± 9% (6 phr of TiC) and 165 ± 12% (6 phr of MoS₂). The reinforcing efficiency (R.E.) and reinforcing factor (R.F.) were also determined theoretically. These results agree well with those of the mechanical property tests and thus validate the experimental work. Finally, the electromechanical tests showed that at 30% strain, the output voltage was 3.5 mV (6 phr of TiC) and 6.7 mV (6 phr of MoS₂). Overall, the results show that TiC and MoS₂ added to silicone rubber lead to robust and versatile composite materials. These composite materials can be useful in achieving higher energy generation, high stretchability, and optimum stiffness and are in line with existing theoretical models. Full article