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Understanding the magnetization reversal and temperature characteristics of synthetic antiferromagnets (SAFs) is helpful for optimizing the magnetic properties. In this study, a series of synthetic antiferromagnets with perpendicular magnetic anisotropy are deposited. The four stable magnetic states of the SAF are determined by the mutual alignment of magnetic moments in the layers and are controlled by both the magnetic interlayer exchange interaction and Zeeman energy. First order reversal curves were employed to investigate magnetization reversal behaviors and distinguish between reversible and irreversible components. An innovative approach to enhancing the antiferromagnetic coupling field and thermal stability involves introducing a Ru insertion and increasing the thickness of the adjacent magnetic layer. [ABSTRACT FROM AUTHOR]

Optimizing the delivery and penetration of nano-sized drugs within liver cancer sites, along with remodeling the tumor microenvironment, is crucial for enhancing the efficacy of chemotherapeutic agents. For this study, a platelet (PLT)-mediated nanodrug delivery system (DASA+ATO@PLT) was developed to improve the effectiveness of chemotherapy. This system delivers nano-sized dasatinib and atovaquone specifically to liver tumor sites and facilitates intra-tumoral permeation upon release. Through JC-1, immunohistochemistry, and DNA damage analyses, the therapeutic effect of DASA+ATO@PLT was assessed. In vitro simulation and intravital imaging were carried out to determine the accumulation of dasatinib and atovaquone in liver tumor sites. The experiment demonstrated the accumulation of dasatinib and atovaquone in tumor sites, followed by deep permeation in the tumor microenvironment with the assistance of PLTs, while simultaneously revealing the ability of DASA+ATO@PLT to remodel the liver cancer microenvironment (overcoming hypoxia) and enhance chemotherapeutic efficacy. This system utilizes the natural tumor recognition ability of PLTs and enhances the chemo-immunotherapeutic effect through targeted delivery of nano-chemotherapeutic drugs to the tumor, resulting in effective accumulation and infiltration. The PLT-mediated nanodrug delivery system serves as a "Trojan horse" to carry therapeutic drugs as cargo and deliver them to target cells, leading to favorable outcomes. [ABSTRACT FROM AUTHOR]

Based on ABAQUS mechanical simulation software and the same bending radius, this paper simulated and an alyzed the strain change trends of metal wires on the different schemes for other key influencing films, such as BPL, PI and TPOC. On the basis of the simulation results, the conclusions are follows: PI thickness thinn ing or TPOC thickness increases can decrease the stra in of the metal wires at bending region. However, the change of BPL thickness has no significant effect. [ABSTRACT FROM AUTHOR]

AMOLED (Active‐matrix organic light‐emitting diode) is a new type of display technology, mainly used in the field of smartphones. Temperature is an important environmental factor for AMOLED displays on their function and performance. Temperature difference can cause changes in the material characteristics of AMOLED displays. It will occur touch failure and inability to respond to users' operations. In order to reduce the adverse effects caused by temperature difference on touch, this paper studied the stability and reliability of different module materials in different temperature environments. The results showed that the module materials had a close relationship with the touch pattern during temperature changed. This paper further explored the pattern design parameter indicators to improve the touch performance of AMOLED through simulation experiments. This study provided a theoretical basis for optimizing the touch function and performance of AMOLED. [ABSTRACT FROM AUTHOR]

With the increasing application and demand of flexible AOLED display modules in the global market, improving the strength performance of display modules has important guiding significance for the development of OLED technology. In this paper, the height of the falling ball is used as the test index of strength performance, and the influence of the composite structure on the strength of the falling ball is studied through the combination of composite structure with different thicknesses and materials. It is found that in the composite structure with the same thickness, using foam instead of PI structure can obtain better ball falling results. The falling result of silica gel material is better than that of foam material, and the overall thickness of silica gel is thinner. [ABSTRACT FROM AUTHOR]

Based on ABAQUS mechanical simulation software and different types of falling ball test jigs, this paper analyzes in detail the influence of different falling ball test jig on test results from the factor of the stress size of the display layer and the distribution of falling ball energy. The final conclusion is as follows: Increasing the gap between the AMOLED display module and the falling ball test jig can effectively reduce the force on the display layer and reduce the damage effect of the ball on the display layer. [ABSTRACT FROM AUTHOR]

In this study, a novel driving circuit which could extend scan pulse width was proposed and integrated into AMOLED panel. Each scan circuit in gate‐in‐panel region contains four groups of clock signals, while the pixel circuit in active area incorporates dual data line design, in combination with a 1:4 demux circuit in the down border. The measured just noticeable difference values of short‐term and medium‐term image sticking were decreased by more than 25% in LTPS AMOLED modules. This work offers a feasible and effective method to improve the image quality in future flexible AMOLED displays. [ABSTRACT FROM AUTHOR]

Since the concept of Augmented Reality and Virtual Reality was put forward, the experience of using AR/VR devices comparable to the real world has become the motivation and target of the related industries. However, to get better visual immersion, the display module resolution needs to be retina level, i.e., 3000~4000 PPI, or else it will produce a screen door effect, which will degrade the user experience. Since higher PPI means smaller pixel pitch and PDL GAP, the balance between product lifetime and manufacturing cost will be difficult to maintain, which challenges the existing fine‐metal mask version (FMM)‐based AMOLED process steps. To meet the requirements of PPI, we fabricated periodically repeating microstructures to form a grating layer above the light‐emitting area to realize the resolution enhancement, and analyzed the effects of refractive index, thickness, and other parameters. [ABSTRACT FROM AUTHOR]

The module stack of trifold display was simulated and G‐type trifold modules were prepared. Surface waviness and mechanical properties were tested under room temperature. Cycle folding reliability of both in‐folding and out‐folding was tested simultaneously under room temperature, 60°/90% and ‐20° test environment (RA test). Waviness and reliability improvement of the G‐type trifold display by optimizing test jig, module material and stack. Finally, the failure of module peeling problem during cycle folding test under room temperature was analyzed. [ABSTRACT FROM AUTHOR]

Magnetic configurations play a paramount role in determining magnetic reversal and unusual configurations and therefore could lead to novel magnetic behaviors and new applications. Here, we demonstrate that the unusual magnetic configurations can be adjusted via the synergy of a perfect conical shape and large magnetocrystalline anisotropy. The near-perfect conical shape with a progressively diminishing size is achieved via depositing cobalt in the ion-tracking template. The magnetocrystalline anisotropy is then modulated by tailoring the crystalline texture. The first-order-reversal-curve analysis discloses that the magnetic configurations of cobalt nanocones are distinctive from cobalt nanowires. Because of the conical shape and large magnetocrystalline anisotropy, the magnetic anisotropy and exchange interaction change from the tip and the base, yielding exceptional switching field distributions. [ABSTRACT FROM AUTHOR]

High frequency properties of exchange-coupled multilayers are important to develop future fast switching spintronic devices. Here, we report an experimental investigation of temperature-dependent high frequency properties in [Co/Pd]n/Py multilayer thin films. The results demonstrate that the linewidth varies with the number of cycles at room temperature. However, the damping slightly decreases with increasing repetitions of Co/Pd. By fitting the relationship between the linewidth and the angle (the out-of-plane azimuthal angle of the external magnetic field), we found that a similar two-magnetron scattering effect becomes stronger when the number of Co/Pd cycles increases. For the (Co/Pd)10/NiFe sample, the linewidth became larger at 9 GHz and 16 GHz with the decrease of temperature. Our findings help comprehend the high frequency properties of exchange-coupled multilayer thin films and are useful for fast switching magnetic devices. [ABSTRACT FROM AUTHOR]

Due to the emission of carbon dioxide and other greenhouse gases, the global climate is warming. As the world's biggest emitter of carbon emissions, China faces a more severe challenge in reducing carbon emissions than developed countries. A reasonable prediction of the carbon peak in China will help the government to formulate effective emission reduction paths. This paper analyzes the changes in carbon emissions in China from 2004 to 2020, uses the STIRPAT model and scenario analysis method to predict carbon emissions from 2021 to 2030, and then calculates the carbon efficiency during carbon peaking to select the most effective carbon peak path for China. The results show that China's carbon emissions increased year by year from 2004 to 2020. Under the baseline scenario, China is unlikely to reach its carbon peak before 2030. Under the regulatory scenarios, China can reach its carbon peak before 2030. The peak values from high to low are seen with the rapid development-weak carbon control scenario, rapid development-intensified carbon control scenario, slow development-weak carbon control scenario and slow development-intensified carbon control scenario, respectively. Correspondingly, China will peak its carbon emissions in 2029, 2028, 2028 and 2028, respectively, according to these scenarios. The carbon efficiency under the rapid development-weak carbon control scenario is the highest, which means that accelerating the growth rate of population, GDP and urbanization while moderately carrying out the transformation of industrial structure and energy structure is an effective way to achieve the goal of "carbon peak by 2030". [ABSTRACT FROM AUTHOR]

Clarifying the influencing factors of energy consumption in underground production processes of coal mine is the premise and foundation for the coal mining industry to control the energy consumption and intensity to achieve the goal of carbon peak and carbon neutrality. This paper aims to investigate and compare the differences in energy consumption and carbon emissions between a mining‐separating‐backfilling integrated coal mine (MSBICM) and a traditional coal mine and explore the effects of the main production links underground on carbon emission intensity in coal mines. Hence, taking an MSBICM in Henan province as an example, this study constructed an energy consumption and carbon emission model of the mine using system dynamics (SD) method. Based on this model, the energy consumption of the main production logistics system and auxiliary production system in MSBICM was simulated and analyzed. In addition, this study made a comparative analysis of the energy consumption of the different production links in the two types of coal mines. The results showed that: (1) the comprehensive mechanized coal mining with solid filling system and ventilation system were the subsystems with the highest and lowest energy consumption in MSBICM respectively. (2) The influence rates of raw coal mining, gangue filling, coal‐gangue separating, and material transportation on carbon emission intensity in coal mine were 1.09%, 1.34%, 1.09%, and 5.13%, respectively. (3) Under the same production and filling targets, energy consumption of underground transportation systems in MSBICM was found to be 336.66 tons of standard coal less than that in traditional coal mine. This study has helped clarify the complex relationships among the factors that influence energy consumption in coal mines and provided a reference for implementing dual control of energy consumption to promote low‐carbon mining of coal resources. [ABSTRACT FROM AUTHOR]

It is well known that CsCl‐type FeRh undergoes from antiferromagnetic (AFM) to ferromagnetic (FM) phase transition near room temperature with large thermal hysteresis. Therefore, it is particularly essential to find new methods to manipulate the magnetic order of FeRh and reduce thermal hysteresis. Herein, the magnetic phase transition of FeRh film by applying a low‐frequency in‐plane alternating current (AC) magnetic field is successfully manipulated. It is found that under the AC magnetic field, the phase transition of the FM–AFM is promoted, and the heating branch shifts at a rate of −8 K T−1, which causes the thermal hysteresis of FeRh reduction of about 2 K. These phenomena may be attributed to the Zeeman energy and the periodic vibration of domain walls. This work provides the possibility for the realization of low‐power spintronic devices. [ABSTRACT FROM AUTHOR]

Open set recognition (OSR), aiming to simultaneously classify the seen classes and identify the unseen classes as ’unknown’, is essential for reliable machine learning. The key challenge of OSR is how to reduce the empirical classification risk on the labeled known data and the open space risk on the potential unknown data simultaneously. To handle the challenge, we formulate the open space risk problem from the perspective of multi-class integration, and model the unexploited extra-class space with a novel concept Reciprocal Point. Follow this, a novel learning framework, termed Adversarial Reciprocal Point Learning (ARPL), is proposed to minimize the overlap of known distribution and unknown distributions without loss of known classification accuracy. Specifically, each reciprocal point is learned by the extra-class space with the corresponding known category, and the confrontation among multiple known categories are employed to reduce the empirical classification risk. Then, an adversarial margin constraint is proposed to reduce the open space risk by limiting the latent open space constructed by reciprocal points. To further estimate the unknown distribution from open space, an instantiated adversarial enhancement method is designed to generate diverse and confusing training samples, based on the adversarial mechanism between the reciprocal points and known classes. This can effectively enhance the model distinguishability to the unknown classes. Extensive experimental results on various benchmark datasets indicate that the proposed method is significantly superior to other existing approaches and achieves state-of-the-art performance. The code is released on github.com/iCGY96/ARPL. [ABSTRACT FROM AUTHOR]

In this paper, the influence of the type of interface treatment on the p‐Si surface (H2 or O2 plasma) and the SiH4 flow rate of SiOx on the characteristics stability of low‐temperature poly‐crystalline thin film transistors (LTPS‐TFT) has been investigated. The results indicate that H2 plasma is more effective than O2 plasma to repair low‐energy‐level defects at the interface of p‐Si layer and gate insulator layer (GI), and thus the threshold voltage (Vth) and subthreshold swing (ss) are smaller. And increasing the SiH4 flow rate of SiOx from 1900sccm to 3900sccm helps to form a defect‐reduced and more stable p‐Si film. Finally, the brightness degradation test shows that after aging for 24H with L255, the L3 brightness of base sample decreased by almost 32%, while improved sample decreased by only 8%. [ABSTRACT FROM AUTHOR]

In this study, the structural evolution of the CdTe/ZnS composite passivation films on the surface of infrared HgCdTe material before and after annealing was comparatively explored. The surface morphology and microstructure of the passive films before and after annealing were characterized by scanning electron microscope, X-ray diffraction, atomic force microscopy, and Raman and X-ray photoelectron spectroscopy to determine the effects of the annealing process on the surface crystal defects of the films. The results show that annealing at 320 °C for three hours can improve crystal quality, ameliorate the surface density, and reduce the dislocation density of grains, while the Hg grains inhibited by tellurium-rich growth during the annealing process return to the normal growth state, and the S signal can be detected near the surface after annealing. This finding indicates that high-temperature annealing promotes the inhibited grain growth and also causes diffusion of surface elements, thus smoothing the compositional gradient at the passivation interface of the films. [ABSTRACT FROM AUTHOR]

At present, the theory of supporting the surrounding rock small structure of gob-side entry driving has been widely used, but there is no specific quantitative analytical formula for the bearing strength and bearing characteristics of the structure. Construct a small structural stress arch mechanical model based on the arch axis equation, and divide the width of coal pillars (fractured zone-plastic softening zone-plastic hardening zone) and small structural stress arch height. According to the relationship between the stress arch height and the size of the roadway, the anchor cable length is determined to be 7.3 m, and the "anchor mesh + ordinary long anchor cable + grouting anchor cable" coordinated support plan is proposed: anchor net support is used for the first support, and long anchor cable and grouting anchor cable are used for the second support. Combined with the supporting parameters, a mechanical model of the surrounding rock composite bearing stress arch is proposed, and the composite bearing stress arch structure is derived using elastoplastic mechanics to obtain the ultimate bearing strength relationship expression. The results show that the ultimate bearing capacity of the haulage gateway of 17236 island working-face in the north of Zhangji coal mine can reach 29.193 MPa after the composite bearing stress arch support. The feasibility of the supporting scheme is verified, and field monitoring showed that the deformation zone of the surrounding rock of the transportation haulage gateway is stable after being supported by the composite bearing stress arch structure, the maximum shrinkage of the top and bottom of the roadway is 287 mm, and the distance between the two sides is 640 mm. [ABSTRACT FROM AUTHOR]

In this study, to further improve the prediction accuracy of coal mine gas concentration and thereby preventing gas accidents and improving coal mine safety management, the standard whale optimisation algorithm's (WOA) susceptibility to falling into local optima, slow convergence speed, and low prediction accuracy of the single-factor long short-term memory (LSTM) neural network residual correction model are addressed. A new IWOA-LSTM-CEEMDAN model is constructed based on the improved whale optimisation algorithm (IWOA) to improve the IWOA-LSTM one-factor residual correction model through the use of the complete ensemble empirical model decomposition with adaptive noise (CEEMDAN) method. The population diversity of the WOA is enhanced through multiple strategies and its ability to exit local optima and perform global search is improved. In addition, the optimal weight combination model for subsequence is determined by analysing the prediction error of the intrinsic mode function (IMF) of the residual sequence. The experimental results show that the prediction accuracy of the IWOA-LSTM-CEEMDAN model is higher than that of the BP neural network and the GRU, LSTM, WOA-LSTM, and IWOA-LSTM residual correction models by 47.48%, 36.48%, 30.71%, 27.38%, and 12.96%, respectively. The IWOA-LSTM-CEEMDAN model also achieves the highest prediction accuracy in multi-step prediction. [ABSTRACT FROM AUTHOR]

Methane is one of the most dangerous gases encountered in the mining industry. During mining operations, methane can be broadly classified into three states: mining excavation, stoppage safety check, and abnormal methane concentration, which is usually a precursor to a gas accident, such as a coal and gas outburst. Consequently, it is vital to accurately predict methane concentrations. Herein, we apply three deep learning methods—a recurrent neural network (RNN), long short-term memory (LSTM), and a gated recurrent unit (GRU)—to the problem of methane concentration prediction and evaluate their efficacy. In addition, we propose a novel prediction method that combines classical time series analysis with these deep learning models. The results revealed that GRU has the least root mean square error (RMSE) loss of the three models. The RMSE loss can be further reduced by approximately 35% by using the proposed combined approach, and the models are also less likely to result in overfitting. Therefore, combining deep learning methods with classical time series analysis can provide accurate methane concentration prediction and improve mining safety. [ABSTRACT FROM AUTHOR]

Two feasible and convenient S−S bond cleaving/cyclization reactions for the synthesis of 2‐arylbenzothiazoles catalyzed by CuCl2 or I2/DMSO via 2,2′‐disulfanediyldianilines and aromatic aldehydes have been reported. The reactions are compatible with a range of substrates and could successfully generate 2‐arylbenzothiazoles in moderate to excellent yields, respectively. For the reactions, 'one‐pot' conditions were applied and readily available starting materials were employed. The importance of the protocols were attractive for synthetic method. [ABSTRACT FROM AUTHOR]

Traditional machine learning algorithms are susceptible to objective factors such as video quality and weather environment in the vehicle detection of Unmanned Aerial Vehicle (UAV) videos, resulting in poor detection results. A vehicle image detection method using deep learning in UAV video is proposed. The algorithm in this paper treats surveillance video as many frames of images for vehicle detection in the image. First, perform HSV (Hue-Saturation-Value) spatial brightness translation operation on the original sample to increase the adaptability to different light conditions and sample diversity. Then, the Single Shot MultiBox Detector (SSD) model framework is used as the basis for vehicle detection. In order to obtain a better feature extraction effect, focus loss is added to the basic SSD for optimization. Finally, the trained network model is used to analyze the UAV video, and the detection performance is analyzed experimentally. The results show that the vehicle detection rate of this algorithm has reached 96.49%. It can ensure that the vehicle is accurately detected from the drone video. [ABSTRACT FROM AUTHOR]