In-situ reaction has become one of the mainstream methods for preparing high performance MgB2 (Magnesium diboride) wire due to the good grain connectivity and small particle size of in-situ reaction MgB2. However, a large number of pores inside the in-situ MgB2 wire seriously hinders the further performance improvement of MgB2 wire since it decreases the volume fraction of superconducting phase in the wire. In this article, a rapid-hot-rolling-quenching (RHRQ) technology is developed to effectively improve this problem through ohmic self-heating and hot-rolling wire. Comparative experiments were conducted on a 30 core in-situ MgB2 precursor wire prepared by powder-in-tube method. Microstructure analysis shows that RHRQ treatment effectively squeezes out a large number of pores left by Mg-B diffusion reaction, and the effective area ratio of the strip-shaped particle region in the optimal sample can reach about 88%, thereby significantly improving its current carrying performance throughout the entire testing temperature and magnetic field range. For the optimal sample, under a 1 T field, the magnetic Jc value at 4.2 K and 20 K reached Jc@(4.2 K,1 T) = 1.36 & times; 105 A cm-2 and Jc@(20 K,1 T) = 4.52 & times; 104 A cm-2, improved by 23.6% and 25.2%, respectively, compared with the conventional in-situ MgB2 samples. Under a 4 T field, Jc@(4.2 K,4 T) = 3.05 & times; 104 A cm-2 and Jc@(20 K,4 T) = 3.90 & times; 103 A cm-2, with a performance improvement of 32.1% and 148%, respectively. Transport measurement reveals that core- JcTr of the optimal sample can reach 7.17 & times; 105 A cm-2 and 1.16 & times; 105 A cm-2 at 4.2 K under 2 T and 6 T respectively. Furthermore, the irreversibility field and flux pinning force were also comprehensively enhanced. Our research demonstrated that RHRQ technology can effectively combine hot pressing sintering, Ohmic-self-heating, and reel-to-reel processes while retaining the inherent advantages of in-situ reactions, thereby significantly increasing the volume fraction of superconducting phases in wires and improving performance. Therefore, it can serve as an effective new approach for continuously preparing high-performance in-situ MgB2 wire.

The pinning force of traditional pinning centers is relatively weak, which cannot further meet the application needs of MgB2 superconductors. Therefore, it is crucial to construct more efficient pinning center with high pinning strength and collaborative with the intrinsic pinning centers of the MgB2 system. In this paper, FeGa alloy with magnetostrictive effect is chosen as a dopant for this purpose. By preparing a series of (MgB2)1-x(FeGa)x samples (0 ≤ x ≤ 10 wt%) and characterizing their structural and physical properties, the magnetic flux pinning force of MgB2 superconductors and the superconducting current carrying capacity under external magnetic fields were found significantly improved. For the best sample (x = 3 wt%), the values of Jc@(4.2 K, 8 T), Jc @(10 K, 6 T), and Jc @(20 K, 2 T) reach 3 × 103A/cm2, 7.16 × 103 A/cm2, and 9.53 × 104A/cm2, with the improvements of 757%, 275%, and 143%, respectively, compared with the undoped samples. Meanwhile, the x = 3 wt% sample delivers Hirr values of 6.86 T and 5.31 T at 15 K and 20 K respectively, alongside an Hc2 of 11.17 T at 20 K, with all parameters notably improved. The magnetostriction effect of FeGa alloy under magnetic field is considered to be the main reason for the enhanced superconducting current carrying capacity of MgB2, as the magnetostriction effect generates strong stress-type pinning centers in the MgB2 matrix around FeGa particles.

An in-situ fiber laser-induced breakdown spectroscopy (IF-LIBS) system was designed for in-situ analysis of the same-base alloys. First, the stability of the output laser energy was evaluated. By coordinating the adjustments of the laser energy using a half-wave plate and polarization splitter prism, the stability of the laser energy was ensured, with the relative standard deviation (RSD) being less than 2%. The intensities, signal-to-noise ratio (SNR), signal-to-background ratio (SBR), and RSD variations of four emission lines—Ni I 313.411, Ni I 352.468, Cr I 357.862, and Cr I 425.435 nm—were further studied under different laser energies. Based on the comprehensive consideration of emission line intensity, SNR, SBR, and RSD, a laser energy of 35 mJ was selected for subsequent analysis. The multivariate scatter correction (MSC) method was applied to stabilize the IF-LIBS output spectra, with the RSD of the corrected emission line intensities being less than 5%. Finally, a classification study of six standard nickel alloys was conducted using four machine learning classification algorithms: support vector machine (SVM), K-nearest neighbors (KNN), random forest (RF), and decision tree (DT). After optimizing the hyperparameters, all four algorithms achieved classification accuracies above 95%, with SVM achieving the highest accuracy of 99.8%.

The pollution level of silicone rubber insulators critically impacts power transmission reliability. This study proposes an automated recognition system combining Laser-Induced Breakdown Spectroscopy (LIBS) and machine learning for efficient, non-destructive assessment of insulator contamination, overcoming limitations of conventional laboratory-based methods. Spectral data from insulator sheds were collected via LIBS. Five machine learning models—Backpropagation Neural Network (BPNN), Genetic Algorithm-optimized BPNN (GA-BPNN), Convolutional Neural Network (CNN), Radial Basis Function Neural Network (RBFNN), and Random Forest (RF)—were trained for pollution classification. Results demonstrate that spectral data from the second and third laser pulses yield optimal detection accuracy, overcoming surface heterogeneity limitations of the first pulse. Among the models, the RF algorithm achieves the best balance of high accuracy and computational efficiency, attaining overall accuracies of 97.00% (combined 2nd+3rd pulses), 96.60% (2nd pulse alone), and 96.20% (3rd pulse alone) with processing times of 4.72 s, 4.41 s, and 4.40 s, respectively. While CNN achieved the highest accuracy (98.30% for 2nd+3rd pulses), its computational time (73.75 s) was significantly longer. This integrated LIBS-machine learning framework provides a real-time, field-deployable solution for precise pollution classification on transmission line insulators.

Although introducing second phase particles as additional pinning centers is an effective method to improve the current carrying capacity of MgB2, the thermal strain caused by second phase particles in MgB2 and their impact on flux pinning have not received much attention. In this paper, flux pinning behavior of the thermal strain induced by the second phase particles in the MgB2 bulk materials was studied by doping ZrW2O8 particles which have negative thermal expansion (NTE) characteristics. Due to the significant difference in thermal expansion characters between ZrW2O8 and MgB2, drastic thermal strain was induced in the lattice of MgB2 by doping the NTE-ZrW2O8 particles. These strains work as additional flux pinning centers and significantly enhance the irreversibility field, Hirr, and critical current density, Jc, of the MgB2. Taking Jc as an example, at 4.2 K and 5 T, its Jc value reaches 4.1 × 104 A/cm2, which is a 105 % performance improvement compared to the 2.0 × 104 A/cm2 of the pure MgB2 sample W-0; at 20 K and 2 T, its Jc also reaches 1.3 × 105 A/cm2, which is 1.78 times of the 7.3 × 104 A/cm2 for the pure MgB2 sample under the same conditions. It is interesting that doping ZrW2O8 does not significantly change the scaling behavior of the pinning force, indicating that the lattice strain work like surficial pinning center, while the point defect pinning center initiated by ZrW2O8 particles themselves may only contribute to the high field region, causing the peak in the pinning force scaling curve to shift towards higher fields.

As the most promising green hydrogen production technology to address the global energy crisis, electrolysis of water for hydrogen production requires highly active electrocatalysts. Building heterostructures is the most promising material design strategy to break through the limitations of oxygen evolution reaction (OER) kinetics and promote efficient hydrolysis. This review focuses on nickel-based heterostructured electrocatalysts, whose interface synergy between different components significantly improves catalytic performance. First, the three basic OER mechanisms were discussed, elucidating the relationship between micro interfaces and mechanisms. Then, the latest developments in different nickel-based material systems reveal how interfacial synergistic effects accelerate charge transfer and regulate intermediate adsorption. In addition, we focused on advanced performance optimization strategies, such as the latest advances in optimizing oxygen evolution performance through doping, defect control, and crystal phase engineering. Finally, we identified the challenges faced by this field in industrial applications and pointed out the integration of in situ characterization, theoretical calculations, and artificial intelligence design to achieve controllable preparation of interface active sites. This review provides important theoretical references for the design and development of a new generation of high-performance and scalable OER electrocatalysts, helping to promote the high-quality development of the green hydrogen energy industry.

Traditional computing systems struggle to keep pace with the development of artificial intelligence, as well as the development of the economy and continuous innovation in science and technology. Therefore, there is an urgent need for a new generation of powerful yet low-power computing technologies to replace them. Quantum dots have been incorporated into memristors due to their unique electrical properties, and the development of quantum dot memristors is expected to solve the problems faced by traditional memristors, including cycle stability, high energy consumption, and conductivity uniformity. This article reviews the research progress of quantum dot memristors and their simulation applications in artificial synapses. It summarizes some of the current challenges faced in the development of quantum dot memristors and discusses the potential future applications of these memristors in the field of artificial intelligence.

Carbon doping has always played an irreplaceable and important role in improving the performance of MgB2 superconductors. However, the excessive suppression of T-c by carbon elements and its excessive accumulation at grain boundaries make it difficult to realize its potential to enhance the performance of MgB2 in the preparation of practical materials. In addition, introducing magnetic flux pinning centers that are more effective than interface pinning is another challenge faced by MgB2. In this study, a mixture of carbon nanoparticles and trace rare-earth elements (CNPs/REEs) obtained from high-temperature calcination of Dicranopteris pedata waste was used as a dopant, which can effectively introduce an appropriate amount of carbon into the MgB2 lattice in short-term low-temperature reactions to enhance the irreversibility field (H-irr) of MgB2. Moreover, the residual CNPs and rare-earth impurities that have not entered the lattice can be highly dispersed in MgB2, serving as point pinning centers, and at the same time, limiting the growth of MgB2 particles, which further strengthens the role of the grain boundary pinning force. The synergistic consequence of these doping effects leads to a significant increase in J(c) throughout the entire magnetic field range (0-10 T) at 4.2 and 20 K. As a result, J(c)@3 T at 4.2, 10, and 20 K increased from 90, 41, and 10 kA cm(-2) for the undoped MgB2 to 230, 87, and 20 kA cm(-2) for the C-005 sample, respectively. At 20 K, the H-irr value reached more than 5 T (doping amount x = 0.05). It was also found that the irreversibility field is governed by the giant flux creep characteristic as the dopant concentration increases, and the main pinning mechanism of the doped samples is still the grain boundary pinning.

Carbon doping has always played an irreplaceable and important role in improving the performance of MgB2 superconductors. However, the excessive suppression of Tc by carbon element and its excessive accumulation at grain boundaries make it difficult to realize its potential to enhance the performance of MgB2 in the preparation of practical materials. In addition, introducing magnetic flux pinning centers that are more effective than interface pinning is another challenge faced by MgB2. In this study, a mixture of carbon nanoparticles and trace rare earth elements (CNPs/REEs) obtained from high-temperature calcination of dicranopteris pedate waste was used as a dopant, which can effectively introduce an appropriate amount of carbon into the MgB2 lattice in short-term low-temperature reactions to enhance the irreversibility field (Hirr) of MgB2. Moreover, the residual carbon nanoparticles and rare earth impurities that have not entered the lattice can be highly dispersed in MgB2, serving as point pinning centers, and at the same time, limiting the growth of MgB2 particles, which further strengthens the role of grain boundary pinning force. The synergistic consequence of these doping effects leads to a significant increase in Jc throughout the entire magnetic field range (0-10 T) at 4.2 and 20 K. As a result, Jc@3T at 4.2, 10 and 20 K increased from 90, 41, and 10 kA/cm2 of the undoped MgB2 to 230, 87, and 20 kA/cm2 of the C-005 sample, respectively. At 20K, the Hirr value reached more than 5T (doping amount x=0.05). It was also found that the irreversibility field is governed by the giant flux creep characteristic as the dopant concentration increases and the main pinning mechanism of the doped samples is still the grain boundary pinning.

As far as current interest is concerned, the pinning centers of non-ideal type II superconductors are mainly structural defects that apply attractive potential wells to the motion of magnetic flux lines, including nonsuperconducting second phase particles, grain boundaries, etc. In this paper, high-temperature superconductor Bi2212 particles are introduced into MgB2 to explores the behavior of superconducting pinning centers played by superconducting particles that apply repulsive potential barriers to the motion of magnetic flux lines. By mixing ground Bi2212 single crystal with Mg and B powders, (MgB2)1-x(Bi2212)x (x = 0, 3, 5, 7, and 10 wt%) composites were prepared and characterized with XRD, SEM, TEM, and physical property measurements. The irreversible magnetic field Hirr, critical current density Jc, and flux pinning force Fp were enhanced at x = 3 wt%. The best infield-Jc@( 4.2 K, 6 T) reaches 8.1 x 103 A/cm2, which improved the performance by 55.8 % compared to 5.2 x 103 A/cm2 of pure MgB2 sample; and the Jc@(20 K,2 T) reaches 8.0 x 104 A/cm2, which is 1.60 times of the 5.0 x 104 A/cm2 for the pure MgB2 sample under the same conditions. Although the addition of Bi2212 enhances the pinning strength of MgB2, it has no qualitative effect on the flux pinning characteristics, i.e., the flux pinning behavior is still dominated by grain boundary pinning mechanism. It is argued that in this study, Bi2212 particles are likely to exist in the form of nanoparticles in the MgB2 matrix, which contribute to the collective pinning as weak pinning centers.

Recently, the coexistence and competition of superconductivity (SC) and charge density wave (CDW) have emerged in Kagome superconductor AV(3)Sb(5) (A = K, Rb, Cs) under pressure, which has aroused widespread interest. Here, chemical substitution is used to introduce chemical pressure to further investigate the coexistence and competition between CDW and SC states. By preparing CsV3(Sb1-xSx)(5) series single crystals and studying their crystal structure, chemical valence states, SC, and electronic transport behavior, it is found that S doping causes significant chemical pressure that is similar to axial mechanical pressure, resulting in suppression on the CDW and enhancement on SC. The T-c-x relationship exhibits a double dome SC, similar to the behavior observed in the CsV3Sb5 under mechanical pressure. In addition, a negative correlation between T-CDW and the disorder degree (measured by residual resistivity) is observed. This correlation is consistent with the observed translational jump in the rho(T) curve before and after the CDW transition, that is, the temperature coefficient of resistivity does not change before and after the CDW phase transition, but only the resistivity curve shifts to a certain value. This phenomenon reveals that disorder is an important factor affecting the CDW transition of the system. Further, S doping also induces hole band filling effect that results in a decrease in the DOS at E-F and consequently counterbalances the T-c enhancement effect from chemical pressure to a certain extent. The electronic phase diagram of the CsV3(Sb1-xSx)(5) system is accordingly established, which demonstrates the correlation between the SC, CDW, disorder degree, and other electronic nature of the system.

Improving the automation and accuracy of remote laser-induced breakdown spectroscopy (remote-LIBS) is of great significance in the field of remote, noncontact, and in situ instrument detection. We report on a remote-LIBS device with laser auto-focusing and automatic spectral signal focusing [automatic focusing remote-LIBS (AR-LIBS)], combined with support vector regression (SVR) algorithm to enhance the system's analytical accuracy. This system, based on a Galilean telescope (laser emission path) and a Cassegrain telescope system (plasma optical signal acquisition), enables remote noncontact component analysis within 7 m. For samples at different distances, the laser emission path automatically adjusts focus and excites plasma, while the plasma signal collection system adjusts automatically. Using 19 alloy steel samples as the training set to establish a calibration model and seven samples as the validation set for verification. In order to improve the analysis performance of LIBS, four models for determining the content of Mn, Ni, Cr, and Si elements in alloy steel samples were established based on feature peak intensity as input, using univariate regression (UR) and SVR. The linear fitting degree (R-2), root-mean-square error of calibration (RMSEC), root-mean-square error of prediction (RMSEP), mean absolute percentage error (MAPE), and relative standard deviation (RSD) of Mn, Ni, Cr, and Si elements in different quantitative models were evaluated. The results show that the SVR model based on the internal standard method-SVR (IS-SVR) has higher accuracy and precision. The R-2 of the Mn, Ni, Cr, and Si elements training sets is all above 0.95, with predicted MAPEs of 4.49%, 5.19%, 4.59%, and 11.54%, and predicted RSDs of 3.26%, 7.58%, 3.09%, and 3.06%, respectively.

It is well known that the multi-mode responsive memristor has a great application prospect in the complex environment. The CaTiO3-based memristor was prepared under different NaOH concentrations, which exhibited an obvious resistive switching (RS) behavior at the working voltage of 1 V. The experimental results indicate that the purity of CaTiO3 is affected by different NaOH concentrations, leading to changes in its microstructure. Interestingly, moisture as an electrical stimulus can change the RS behavior. By comparison, a large memory window with stable cycling performance can be observed at the relative humidity (RH) of 60%. A physical model, which involves Ag+ ions, oxygen vacancy (Vo) and OH- ions, was proposed to explain the charge transport mechanism of the moisture-modulated RS behavior. As an effective method to improve the memristive characteristics, the moisture-modulated RS behavior provides a great application for multi-mode-controlled memristor in physiological monitoring, such as sweat and infant urine monitoring.

MgB2 superconductors have the potential for application at 20 K, and improving their superconducting current carrying capacity is the key to achieving this application. In this article, the doping effects of organic carbon (citric acid, C6H8O7) on the critical temperature (Tc), critical current density (Jc), and irreversible field (Hirr) of MgB2 was studied, in order to explore the path of improving its superconducting performance at 20 K. Combing hot -pressing sintering and chemical solution route for making the samples, it was observed that a moderate level of doping (10 wt%) significantly improved the Jc of MgB2 at 20 K: the 2 T -infield Jc of 10 wt% doped sample reaches a value of 30400 A/cm2, increased by 56.7% compared to the undoped sample. The mechanism beneath the improved performance is studied and attributed to the rapidly enhanced delta l-type flux pinning force brought about by partial substitution of C for B. In addition, the grain refinement effect caused by C doping strengthens the surface pinning force, resulting in a better agreement between the scaling behavior of the pinning force density and the theoretical model of surface pinning.

The potential applications of memristors in the post-Moore era of rapidly developing next-generation artificial intelligence and high-frequency communication technologies are immense. The effects on the resistive switching (RS) characteristics based on Ag Salt@TiO2 memristive device with a nano core-shell structure under different relative humidity (RH) environments have been investigated in this work. Negative-set/reset phenomena occurs in negative voltage region due to excessive growth of conductive filaments (CFs). When the CF returns to normal growth, the current suddenly decreases in the positive high voltage area at lower humidity, which can be explained by the dissolution and growth hindrance of the CFs. Furthermore, the coexistence of negative differential resistance (NDR) and bipolar RS at room temperature can be regulated by adjusting humidity. The current conduction mechanism of the device in both dry and humid environments were fitted using the ohmic conduction mechanism, space charge-limited current (SCLC) conduction mechanism, and Schottky emission mechanism.

Compared with traditional low-temperature superconductors, the advantage of MgB2 lies in its critical temperature close to 40 K, which provides potential application at 20 K. In order to further improve its superconducting current carrying capacity at 20 K, a series of PEG polymer (including PEG2000, PEG4000, and PEG6000) doped MgB2 with doping level of 15 wt% were prepared by combining hot-pressing sintering with chemical solution route. The best result is achieved in PEG4000 doped sample, with a Jc at 20 K and 2 T reaching 51,000 A/cm2, increased by 42.8 % in comparison with the undoped sample. Study on the mechanism of the improvement reveals that organic carbon doping enhances the irreversibility field and consequently the flux pinning force. In response to the deviation of MgB2 pinning characteristics from Kramer theory, an irreversibility field increment (IFI) model was proposed which provides a satisfactory explanation for the experimental results. Our results demonstrate that the combination of hot-pressing sintering and organic carbon doping is an effective means to enhance the superconducting performance of MgB2 at 20 K for practical applications.

The coupling of resistance switching (RS) behavior and N-type negative differential resistance (NDR) effect provides a promising physical basis for the preparation of low-power and multifunctional electronic devices. N-type NDR effect can be expressed by the relationship between peak voltage (VP), valley voltage (VV) and the homologous current (IP, IV). In this work, a memristive device with Ag/BFO@EA/FTO structure was prepared by inserting BiFeO3 (BFO) nanoparticles into egg albumen (EA) as the functional layer, and observed the evolution between RS and NDR coupled RS (NRS) behaviors with the regulation of applied voltage window. Besides, it can be observed a wide current gap of 18.6 mA between IP and IV in the narrow voltage gap (about 0.4 V) between VP and VV, indicating that the device has low power consumption and fast reading/writing speed when it is applied to information processing. Finally, based on the obtained data, it was deeply analyzed the mechanism of NRS effect in the Ag/BFO@EA/FTO memristive device. Therefore, this work provides a new perspective for realizing multi-level storage and multifunctional advanced applications in the memristive device.

Due to its powerful brain-like parallel computing and efficient data processing capabilities, memristors are considered to be the core components for building the next generation of artificial intelligence systems. In this study, the CeOx/WOy heterojunction is employed as the functional layer, and various metal materials are utilized as the top electrode to fabricate the memristor. The results indicate that the memristive performance of the Ag/CeOx/WOy/ITO device can be improved by using Ag as the top electrode. By studying the conductivity mechanism of the device, a conductivity model is established that regulates oxygen vacancies and Ag conductive filaments. Furthermore, using the as-prepared memristor, it is constructed four basic digital logic circuits: OR, AND, XOR, and XNOR, as well as a half adder and a full adder that can be used for digital arithmetic operations. Specifically, an odd/even checker is developed based on XOR and XNOR logic circuits to verify the correctness of data transmission. Finally, it is also designed and implemented a cryptographic array based on a memristor, which can be applied to encrypt and decrypt a series of numbers and images. Therefore, this work extends the application of memristor toward digital circuits, information transmission, data processing and image security encryption.

In order to investigate the corrosion behavior of Magnesium alloy in salt spray corrosion experiments, the LA103Z Magnesium-lithium alloy was characterized by SEM, EDS and XRD after salt spray corrosion experiments, the relationship between the number of laser pulses and the depth of laser ablation was investigated by a 3D profile scanner. The relative content distribution of Na, Ca corrosive elements and Mg, Al substrate elements at longitudinal depth were investigated by laser induced breakdown spectroscopy（LIBS） technique. The results showed that corrosion products such as Mg（OH） 2 , Al 2 O 3 and Li 2 CO 3 were formed on the alloy surface. The corrosion depths of Na and Ca in the samples at 96 h were about 24.48 μm, 13.6 μm respectively. Meanwhile, Na and Ca were found to be involved in the reaction to generate corrosion products NaAlCO 3 （OH） 2 and CaAl 2 O 4 .