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The organic light‐emitting diode (OLED) has gained widespread commercial use, yet there is a continuous need to identify innovative emitters that offer higher efficiency and a broader color gamut. To effectively screen out promising OLED molecules that are yet to be synthesized, representation learning aided high throughput virtual screening (HTVS) over millions of Ir(III) complexes, which are prototypical types of phosphorescent OLED material constructed via a random combination of 278 reported ligands. This study successfully screens out a decent amount of promising candidates for both display and lighting purposes, which are worth further experimental investigation. The high efficiency and accuracy of this model are largely attributed to the pioneering attempt of using representation learning to organic luminescent molecules, which is initiated by a pre‐training procedure with over 1.6 million 3D molecular structures and frontier orbital energies predicted via semi‐empirical methods, followed by a fine‐tuning scheme via the quantum mechanical computed properties over around 1500 candidates. Such workflow enables an effective model construction process that is otherwise hindered by the scarcity of labeled data and can be straightforwardly extended to the discovery of other novel materials. [ABSTRACT FROM AUTHOR]

In this paper, we study the discrete-time control problem for the refrigeration system with unmodeled dynamics. This paper proposes discrete adaptive neural network controllers for two refrigeration systems, including the water membrane evaporator cooling and compression refrigeration systems. The influence of model uncertainty on system performance can be eliminated effectively by designing the neural network and the corresponding discrete-time adaptive updating strategy. Thus, the model parameters in the refrigeration system are not required in our control algorithms. Simulation results show that the proposed strategy can effectively adjust the refrigeration system temperatures. Compared with the traditional PID control strategy, the system response overshoot under our method can be reduced by 0.3%, and the system settling time is reduced by at least 94.3%. • Discrete-time adaptive neural controller is proposed for refrigeration systems. • Uncertainty problems are solved by using the adaptive scheme and neural networks. • Compared with the PID method, the settling time is reduced by at least 94.3%. [ABSTRACT FROM AUTHOR]

We propose a preference-learning algorithm for uncovering Decision Makers' (DMs') contingent evaluation strategies in the context of multiple criteria sorting. We assume the preference information in the form of holistic assignment examples derived from the analysis of alternatives' performance vectors and textual descriptions. We characterize the decision policies using a mixture of threshold-based, value-driven preference models and associated latent topics. The latter serve as the stimuli underlying the contingency in decision behavior. Such a probabilistic model is constructed by using a flexible and nonparametric Bayesian framework. The proposed method adopts a hierarchical Dirichlet process as the prior so that a group of DMs can share a countably infinite number of contingent models and topics. For all DMs, it automatically identifies the components representing their evaluation strategies adequately. The posterior is summarized by using the Hamiltonian Monte Carlo sampling method. We demonstrate the method's practical usefulness in a real-world recruitment problem considered by a Chinese IT company. We also compare the approach with counterparts that use a single preference model, implement the parametric framework, or consider each DM's preferences individually. The results indicate that our approach performs favorably in both interpreting DMs' contingent decision behavior and recommending decisions on new alternatives. Furthermore, the approach's performance and robustness are investigated through a computational experiment involving real-world data sets. History: Accepted by Ram Ramesh, Area Editor for Data Science and Machine Learning. Funding: J. Liu received financial support from the National Natural Science Foundation of China [Grants 72071155 and 71701160]. M. Kadziński received financial support from the Polish National Science Center under the SONATA BIS project [Grant DEC-2019/34/E/HS4/00045]. X. Liao received financial support from the National Natural Science Foundation of China [Grant 71872144]. Supplemental Material: The software that supports the findings of this study is available within the paper and its Supplemental Information (https://pubsonline.informs.org/doi/suppl/10.1287/ijoc.2023.1292) as well as from the IJOC GitHub software repository (https://github.com/INFORMSJoC/2021.0328) at (http://dx.doi.org/10.5281/zenodo.7608750). [ABSTRACT FROM AUTHOR]

Perovskites have shown tremendous promise as functional materials for several energy conversion and storage technologies, including rechargeable batteries, (electro)catalysts, fuel cells, and solar cells. Due to their excellent operational stability and performance, high‐entropy perovskites (HEPs) have emerged as a new type of perovskite framework. Herein, this work reviews the recent progress in the development of HEPs, including synthesis methods and applications. Effective strategies for the design of HEPs through atomistic computations are also surveyed. Finally, an outlook of this field provides guidance for the development of new and improved HEPs. [ABSTRACT FROM AUTHOR]

Urea oxidation reaction (UOR) with a low equilibrium potential offers a promising route to replace the oxygen evolution reaction for energy‐saving hydrogen generation. However, the overpotential of the UOR is still high due to the complicated 6e− transfer process and adsorption/desorption of intermediate products. Herein, utilizing a cation exchange strategy, Ni‐doped CuO nanoarrays grown on 3D Cu foam are synthesized. Notably, Ni‐CuO NAs/CF requires a low potential of 1.366 V versus a reversible hydrogen electrode to drive a current density of 100 mA cm−2, outperforming various benchmark electrocatalysts and maintaining robust stability in alkaline media. Theoretical and experimental studies reveal that Ni as the driving force center can effectively enhance the urea adsorption and stabilize CO*/NH* intermediates toward the UOR. These findings suggest a new direction for constructing nanostructures and modulating electronic structures, ultimately developing promising Cu‐based electrode catalysts. [ABSTRACT FROM AUTHOR]

[Display omitted] Liquid organic electrolytes commonly employed in commercial Li-ion batteries suffer from safety issues such as flammability and explosions. Replacing liquid electrolytes with nonflammable electrolytes has become increasingly attractive in the development of safe, high-energy Li-metal batteries (LMBs). In this work, nonflammable, robust, and flexible composite polymer–polymer electrolytes (PPEs) were successfully fabricated by flame-retardant solution casting with polyimide (PI) and polyvinylidene fluoride (PVDF). The optimized nonflammable PPEs (e.g., PPE-50) demonstrate not only good mechanical properties (i.e., a high tensile strength of 29.6 MPa with an elongation at break of 87.2%), but also high Li salts dissolubility, the former of which ensures the suppression of Li dendrites, while the latter further improves the ionic conductivity (∼1.86 × 10−4 S cm−1 at 30 °C). The resulting symmetric cells (Li|PPE-50|Li) offer excellent Li stripping and plating stability for 1000 h at 0.5 mA cm−2/0.25 mAh cm−2 and 600 h at 2.0 mA cm−2/1.0 mAh cm−2. In addition, the LiFePO 4 |PPE-50|Li half cells show high cycling performance (e.g., a reversible discharge capacity of 135.9 mAh g−1 after 300 cycles at 1C) and rate capability (e.g., 117.2 mAh g−1 at 4C). The PPE-50 is also compatible with a high-voltage cathode (e.g., LiNi 0.5 Mn 0.3 Co 0.2 O 2), and the resulting batteries demonstrate long-term cycling stability with a high cut-off voltage of 4.5 V vs. Li/Li+. Because of the incorporation of a mechanically robust and thermally stable PI, a polar PVDF, and flame-retardant trimethyl phosphate (TMP) within PPEs, as well as the coordination between Li salts and TMP, and the interaction between Li salts and polymers (especially between Li bis(oxalato)borate) and PI, as well as the bis(oxalato)borate anion and PI), PPEs show great potential for practical and high-energy LMBs without safety concerns. [ABSTRACT FROM AUTHOR]

The corrugated p-base (CB) structure has been acknowledged as an effective method to improve the maximum controllable current (MCC) of asymmetric integrated gate-commutated thyristor (IGCT), but never clarified in symmetrical devices such as reverse blocking IGCT (RB-IGCT). This study focuses on the influence of the CB structure on the MCC and the failure mechanism of RB-IGCT. First of all, by employing the CB structure in the RB-IGCT samples, it is verified that the CB structure can improve MCC of the symmetrical devices by more than 50%, no matter under high or low dc-link voltages. Moreover, regarding the scenario under the high dc-link voltage, the effect of the CB structure on the dynamic avalanche is analyzed via simulation, and the improvement of MCC and the positive trend of MCC upon temperature are further clarified. As to the scenario under the low dc-link voltage, distinct failure phenomenon and negative temperature dependence of MCC are observed evidentially on the symmetric devices with CB structure. To explain these failure characteristics that are conflicting with the well-acknowledged dynamic avalanche failure, a novel failure mode named cathode retrigger failure is proposed in this study. It is believed that this study not only deciphers the fundamental mechanisms of the CB structure in RB-IGCT, but also provides practical strategy to optimize the symmetric IGCT devices. [ABSTRACT FROM AUTHOR]

In contrast to small‐molecule multiple resonance emitters processed via vacuum evaporation technology, the design of multiple resonance dendrimers is presented by introducing the first‐ and second‐generation carbazole dendrons in the periphery of boron, oxygen, nitrogen‐doped polycyclic aromatic skeleton, for efficient narrowband blue electroluminescence by a solution process. The multiple resonance dendrimers not only keep the narrowband emission of the polycyclic aromatic skeleton, but also can suppress their intermolecular aggregation by steric carbazole dendrons, overcoming the unwanted spectral broadening in the solid state. The resultant first‐generation carbazole dendrimer exhibits narrowband blue emission with promising photoluminescent quantum efficiency of 94% and delayed fluorescence with a lifetime of 139.1 µs in the solid‐state film. Solution‐processed organic light‐emitting diodes based on the dendrimers reveal electroluminescence at 488 nm with full‐width at half maximum of 39 nm, the maximum luminous efficiency of 29.2 cd A−1, and maximum external quantum efficiency of 13.4%. [ABSTRACT FROM AUTHOR]

Subsidence of the gob area is an important geological problem in coal mines. Such events not only pose potential safety risks, but also can seriously impair the subsequent mining of coal mines. Therefore, detection of gob subsidence is important to ensure sustainable coal mining. Due to the complex seismic and geological conditions in the gob subsidence area, it is difficult to accurately identify the gob area by using traditional three-dimensional (3-D) seismic detection method. Herein, a new, model-driven gob detection method based on four-dimensional (4-D) seismic data is proposed. According to the proposed strategy, geological models before and after coal seam mining are firstly established, and synthetic data are generated through forward modeling. Then, the prestack time migration (PSTM) sections of synthetic data are used to retrospectively analyze the seismic reflection characteristics of the gob area, and the gob area is identified according to the variations of reflection characteristics and velocity fields caused by the gobs. Next, the characteristics of gob areas in synthetic data are used to guide the identification of the gob area in real seismic data. Meanwhile, a 3-D stratum stripping technique is used to finely depict the gob area. According to the method, the scope of the caving zone, the height of the overburden fractured zone in the gob area, and the geological structure of the lower coal seam in the gob area can be ascertained. This article presents the successful use of the proposed method in detecting the gob area from a real coal mine. [ABSTRACT FROM AUTHOR]

As the core component of ejector refrigeration systems, the research of ejector mechanisms has always been a hot topic. Based on the compound-choking theory, this paper studies the relationship between the entrainment ratio and critical back pressure and designs a neural network-based online error compensation mechanism for supersonic ejectors. Firstly, a thermodynamic model of the ejector is developed by combining the ideal gas model, the compound-choking theory, and the constant-pressure mixing theory. Then, the thermodynamic relationship between the entrainment ratio and critical back pressure is derived by introducing the idea of a hypothetical mixing cross section. Compared with the existing results, our method is able to improve critical back pressure prediction accuracy by virtue of the actual entrainment ratio. Therefore, a new adaptive error compensation algorithm is proposed for supersonic ejectors based on neural networks. Thus, the proposed scheme can be regarded as a hybrid modeling method for supersonic ejectors, which combines thermodynamic laws and data-driven artificial intelligence algorithms. Experimental data from ejector refrigeration systems with R141b, R245fa, water vapor and R134a are used in this paper to verify the validity of the model. The simulation results show that our method can effectively predict the critical back pressure, and all the prediction errors are less than 10%. • A novel hybrid modeling method is proposed for supersonic ejectors based on the compound-choking theory. • The idea of hypothetical mixing cross section is introduced to develop the ejector model. • The predictive error of the thermodynamic model is compensated by using adaptive neural scheme. • The simulation results show that all prediction errors are less than 10%. [ABSTRACT FROM AUTHOR]

Owing to the low theoretical potential of the urea oxidation reaction (UOR), urea electrolysis is an energy‐saving technique for the generation of hydrogen. Herein, a hierarchical structure of CuO nanowires decorated with nickel hydroxide supported on 3D Cu foam is constructed. Combined theoretical and experimental analyses demonstrate the high reactivity and selectivity of CuO and Ni(OH)2 toward the UOR instead of the oxygen evolution reaction. The hierarchical structure creates a synergistic effect between the two highly active sites, enabling an exceptional UOR activity with a record low potential of 1.334 V (vs the reversible hydrogen electrode) to reach 100 mA cm−2 and a low Tafel slope of 14 mV dec−1 in 1 m KOH and 0.5 m urea electrolyte. Assembling full urea electrolysis driven by this developed UOR electrocatalyst as the anode and a commercial Pt/C electrocatalyst as the cathode provides a current density of 20 mA cm−2 at a cell voltage of ≈1.36 V with promising operational stability for at least 150 h. This work not only enriches the UOR material family but also significantly advances energy‐saving hydrogen production. [ABSTRACT FROM AUTHOR]

Reversible protonic ceramic cells (RePCCs) can facilitate the global transition to renewable energy sources by providing high efficiency, scalable, and fuel‐flexible energy generation and storage at the grid level. However, RePCC technology is limited by the lack of durable air electrode materials with high activity toward the oxygen reduction/evolution reaction and water formation/water‐splitting reaction. Herein, a novel nanocomposites concept for developing bifunctional RePCC electrodes with exceptional performance is reported. By harnessing the unique functionalities of nanoscale particles, nanocomposites can produce electrodes that simultaneously optimize reaction activity in both fuel cell/electrolysis operations. In this work, a nanocomposite electrode composed of tetragonal and Ruddlesden–Popper (RP) perovskite phases with a surface enriched by CeO2 and NiO nanoparticles is synthesized. Experiments and calculations identify that the RP phase promotes hydration and proton transfer, while NiO and CeO2 nanoparticles facilitate O2 surface exchange and O2‐ transfer from the surface to the major perovskite. This composite also ensures fast (H+/O2‐/e‐) triple‐conduction, thereby promoting oxygen reduction/evolution reaction activities. The as‐fabricated RePCC achieves an excellent peak power density of 531 mW cm‐2 and an electrolysis current of −364 mA cm‐2 at 1.3 V at 600 °C, while demonstrating exceptional reversible operation stability of 120 h at 550 °C. [ABSTRACT FROM AUTHOR]

Gate electrode inductance is a key factor for the controllable current capacity of unity-gain turn-off devices. However, the precise and credible measurement of this nH-level inductance is very difficult due to the compact structure of housing package. In this article, a precise measurement methodology of nH-level gate electrode inductance based on calculation-error-free algorithm for unity-gain turn-off devices is proposed. First, the turn-off process was modeled and discussed. Based on the feature of different stages, a customized extraction method is proposed for nH-level inductance measurement with ultrahigh accuracy. Then, a gate current measurement method for separate cathode rings with minimum inductance introduction was invented and discussed. After careful measurement and calculation, the gate electrode inductance for each region was derived and the abrupt change in gate contact region was observed and analyzed. The inductances measured in this article can be further utilized for housing structure optimization and lateral arrangement of segments on unity-gain turn-off chips. [ABSTRACT FROM AUTHOR]

The integrity of housing and feature of short circuit is hardly guaranteed for traditional power devices under overvoltage breakdown with following high surge energy. Thus, extra bypass thyristor is needed to achieve stable overvoltage bypass protection for submodules in modular multilevel converters at present. In this article, a novel controlled punch-through IGCT (CP-IGCT) is presented. Based on the punch-through breakdown principle instead of avalanche breakdown principle, the device can achieve breakdown at design voltage with uniformity, thermal stability, and robust package rupture-resilience. As a consequence, no extra sacrificial device is necessary. The fabricated sample proves a stable breakdown at 4000 V and a robust short-circuit feature after energy release of a 18 mF capacitor under 4500 V. [ABSTRACT FROM AUTHOR]

The turn-off capability test for the single cell of power devices is of great significance to both the safe operation assurance and the destruction mechanism research. However, with present techniques, the device under test is supposed to be destroyed once the turn-off fault occurs. In this article, a robust nondestructive test scheme based on the multistage anode voltage detection for 4500 V single-cell turn-off capability of press-packed devices is proposed. Based on the proposed scheme, a single cell of IGCT is tested until a fault occurs. The result proves that a total bypass time is less than 100 ns for the 2200 V/5 A turn-off fault, and thus, the aim of nondestructive tests can be achieved with the proposed method. [ABSTRACT FROM AUTHOR]

The learning of predictive models for data-driven decision support has been a prevalent topic in many fields. However, construction of models that would capture interactions among input variables is a challenging task. In this paper, we present a new preference learning approach for multiple criteria sorting with potentially interacting criteria. It employs an additive piecewise-linear value function as the basic preference model, which is augmented with components for handling the interactions. To construct such a model from a given set of assignment examples concerning reference alternatives, we develop a convex quadratic programming model. Because its complexity does not depend on the number of training samples, the proposed approach is capable for dealing with data-intensive tasks. To improve the generalization of the constructed model on new instances and to overcome the problem of overfitting, we employ the regularization techniques. We also propose a few novel methods for classifying nonreference alternatives in order to enhance the applicability of our approach to different data sets. The practical usefulness of the proposed approach is demonstrated on a problem of parametric evaluation of research units, whereas its predictive performance is studied on several monotone classification problems. The experimental results indicate that our approach compares favourably with the classical UTilités Additives DIScriminantes (UTADIS) method and the Choquet integral-based sorting model. Summary of Contribution. The paper tackles vital challenges at the intersections of multiple criteria decision analysis and machine learning, showing how computationally advanced techniques can be used for faithfully representing human preferences and dealing with complex decision problems. Specifically, we propose a novel preference learning method for multiple criteria sorting problems. The introduced approach incorporates convex quadratic programming to construct a value-based preference model based on large sets of preference statements. In this way, we extend the applicability of decision analysis methods to preferences derived from historical data or observation of users' behavior in addition to the preference judgments explicitly revealed by the decision-makers. The method's practical usefulness is illustrated on a variety of real-world datasets from fields such as higher education, medicine, human resources, and housing market. Its potential for supporting better decision-making is enhanced by both an interpretable form of the assumed model handling interactions between criteria as well as a high predictive performance demonstrated in the extensive computational experiments. [ABSTRACT FROM AUTHOR]

The performance of solid-state dc circuit breaker (SS-DCCB) is mainly determined by the on-state feature of power device. In this article, an optimized low on-state voltage integrated gate-commutated thyristor (LO-IGCT) for SS-DCCB is developed. First, the impacts of device parameters, including base length, carrier lifetime, and emitter injection efficiencies, on on-state voltage are presented. The boundary conditions raised by blocking voltage and safe operation area (SOA) are analyzed. Based on that, a three-step blocking-SOA-emitter optimization routine is proposed. Then, the optimization methodology for doping profiles in different regions, especially in n-drift, n buffer, p+ base, n+ emitter, and p+ emitter regions, is presented. The optimal values are derived with theoretical deduction or numerical calculation. After that, based the optimization result, samples of LO-IGCTs are fabricated and tested. The fabricated LO-IGCT sample shows a blocking voltage capability over 4500 V and an on-state voltage of 1.11 V at the current of 2000 A. The commercialized IGCT and IGBT optimized for high-frequency applications exhibits 1.23 and 1.85 times the on-state voltage under the same test configuration. [ABSTRACT FROM AUTHOR]

Thermal degradation of lignin in hydrogen donor solvent (HDS) has been reported to be an efficient method to generate aromatics and phenols. High pressure H 2 and catalyst are not required which simplifies this degradation method. This work aims to advance the knowledge of reaction pathway with depolymerization of enzymatic hydrolysis lignin (EHL) in 9,10-dihydroanthracene (DHA) as an example. For this purpose, the liquid products were characterized in detail by GC, GPC, 31P NMR and 2D-HSQC NMR. Results indicate that the yield of monomeric phenols is up to 20.2 wt% at 375–400 °C. This yield is comparable to literature results with high-pressure H 2 and catalysts at 220–320 °C. The depolymerization starts with the cleavage of ether linkages and decarboxylation of acrylate linkages, which are followed by the removal of aliphatic-OH, hydrogenation of C al = C al , decarbonylation of C al = O, dealkylation of alkyl substituents and demethylation of aromatic-methoxy groups. The amount of phenolic-OH is about 2.78 mmol/g in the liquid product obtained at 400 °C: 36% from the cleavage of β-O-4 and α-O-4 linkages and about 16% from the demethylation of aromatic-methoxy group. The number-average molecular weight is roughly inversely proportional to the amount of bond cleavage. [Display omitted] • Lignin is efficiently depolymerized in H-donor solvent without H 2 and catalyst. • The optimal conditions are 400 °C for 10 min or 375 °C for 30 min. • Monomeric phenols' yield is up to 20.2% and comparable to the results with H 2. • A comprehensive depolymerization pathway of lignin for phenols is proposed. [ABSTRACT FROM AUTHOR]

In the current study, two similar substituted imidazo[1,2-α]pyridine ligands with different coordination groups were facilely synthesized, and were further used for construction of two novel Cu(II)-based coordination complexes with the chemical formulae of Cu(L1)2(H2O)4 (1, HL1 = (E)−4-(3-(2-chloroimidazo[1,2-a]pyridin-3-yl)acryloyl)benzoic acid) and [Cu(L2)2]n (2, HL2 = (E)−4-(2-chloroimidazo[1,2-α]pyridin-3-yl)−2-oxobut-3-enoic acid) via a one pot solvothermal reaction. In addition, their inhibitory effect on human myocardial aneurysm cells were evaluated. Firstly, to explore the inhibitory effect of complexes on cancer cell viability and proliferation, the Cell Counting Kit-8 (CCK-8) assay was performed. Next, to evaluate the influence of the compounds on the cell migration and invasion ability, the transwell assay was conducted. In addition to this, for the cancer cell apoptosis evaluation after compounds treatment, the flow cytometry was carried out in this research. [ABSTRACT FROM AUTHOR]

The discrete-time fault-tolerant control method for permanent magnet synchronous motors (PMSMs) is investigated for the first time in this paper based on adaptive fuzzy theory, where the designed controllers consider faults containing both loss of effectiveness and bias. Firstly, with the help of Euler method, the discrete-time model of PMSMs is obtained. Secondly, adaptive fuzzy theory is used to realize fault-tolerant control of PMSMs. Next, dynamic surface control is used to resolve the problems of "explosion of complexity" and noncausal in discrete-time systems caused by backstepping. It is proved that the proposed method can guarantee all signals and states in the closed-loop system are semi-global uniform ultimate bounded when the faults occur and the position tracking error can converge to a small neighborhood of the origin. Finally, simulation results show that the proposed control method has strong fault-tolerant performance and robustness. [ABSTRACT FROM AUTHOR]

This paper focuses on the adaptive asymptotic tracking control problem for an autonomous underwater vehicle (AUV) with un-modeled dynamics and unknown input saturation by combining the backstepping control strategy and the neural network (NN) method. In our controller, a novel single neural network-based backstepping control method is proposed to address the uncertain problem, and the input saturation issue is overcome in virtue of a hyperbolic tangent function. The approximation error of the neural network is also compensated by a new adaptive mechanism in order to achieve the zero-error regulation. Furthermore, the nonlinear transformation is incorporated into the backstepping-based framework to improve the AUV performance. And then, the performance analysis illustrates that the designed controller can realize the asymptotic stability of the AUV system. Finally, the effectiveness of our control strategy is validated through simulation results. • A single neural network-based asymptotic adaptive backstepping control strategy is proposed for the trajectory tracking of autonomous underwater vehicles. • The approximation error of the neural network is compensated by using the adaptive mechanism to achieve the zero-error regulation. • The nonlinear transformation is incorporated into the adaptive backstepping scheme to improve the AUV performance. • The asymptotic stability of the AUV system is proven based on the Lyapunov stability theorem. [ABSTRACT FROM AUTHOR]

The calculation complex problem is one of the significant obstacles in the real-time implementation of traditional backstepping controllers. In this paper, we consider the simplification problem of the adaptive backstepping tracking controller for uncertain nonlinear systems with unknown input saturation. Compared with traditional backstepping controllers, virtual stabilizing functions and their derivatives are needless in our controller, which effectively reduces the computation burden. And then the one-order compensation subsystem is employed to eliminate the effect of nonlinear uncertainties based on the adaptive control scheme and the congelation of variables technique. Next, the performance of the closed-loop nonlinear system is analyzed based on the Lyapunov stability theorem. In the final, simulation and experimental results are given to show the effectiveness of our controller. • We propose a simplified backstepping control for uncertain nonlinear systems. • One-order compensation subsystem is employed to eliminate uncertain problems. • Simulation and experimental results are given to validate our control strategy. • Virtual stabilizing functions and their derivatives are needless in our controller. [ABSTRACT FROM AUTHOR]

High-throughput virtual screening, OLED, quantum mechanical calculation, representation learning Keywords: high-throughput virtual screening; OLED; quantum mechanical calculation; representation learning EN high-throughput virtual screening OLED quantum mechanical calculation representation learning 1 1 1 09/20/23 20230915 NES 230915 In article number number 2301093, Zifeng Zhao, Qi Ou, and co-workers carry out an automatic high-throughput virtual screening for light-emitting Ir(III) complexes based on accurately benchmarked quantum chemistry methodology and an advanced molecular representation learning technique. Automatic Screen-out of Ir(III) Complex Emitters by Combined Machine Learning and Computational Analysis (Advanced Optical Materials 18/2023). [Extracted from the article]

• Banana melatonin biosynthesis related genes were identified and characterized. • Some MaTDC and MaASMT genes contribute to the banana cold resistance by influencing melatonin biosynthesis. • Nine TDC, one T5H, one SNAT and twenty-four ASMT genes were identified from M. acuminata genome. • The expression of MaTDC and MaASMT members are influenced by many environmental factors and transcription factors. • Some MaTDC and MaASMT genes contribute to the banana cold resistance by influencing melatonin biosynthesis. The melatonin biosynthesis in plant is mainly catalyzed by tryptophan decarboxylase (TDC), tryptamine 5-hydroxylase (T5H), serotonin N-acetyltransferase (SNAT) and N-acetylserotonin methyltransferase (ASMT). In this study, nine MaTDCs , one MaT5H , one MaSNAT , and twenty-four MaASMTs were identified from Musa acuminate genome. The MaTDC and MaASMT gene families were further studied through bioinformatics analysis and expression pattern analysis under low temperature and exogenous melatonin treatments. MaTDCs and MaASMTs could be classified into two and five subfamilies, respectively. These classifications were strongly supported by their gene structures and protein conserved motifs. The expression of MaTDC4–1, MaTDC7–1, MaTDC8–2, MaTDC10–1 and MaASMT10–1 and the content of endogenous melatonin in banana leaf were significantly promoted by low temperature. Moreover, the promoting effects of combined low temperature and exogenous melatonin treatment were more significant. Notably, the expression of MaTDC4–1, MaTDC8–2, MaTDC10–1 and MaASMT10–1 was not only low temperature inducible but also very significantly or significantly positively correlated with the melatonin content. Moreover, transient overexpression of MaTDC4–1 and MaASMT4–2 greatly increased the melatonin accumulation in tobacco leaf. Our study revealed the contributions of MaTDC and MaASMT genes and melatonin to the banana cold resistance. [Display omitted] [ABSTRACT FROM AUTHOR]

Graphical abstract Highlights • Hierarchical "nanoroll" like MoS 2 /Ti 3 C 2 T x hybrid was prepared by combining liquid nitrogen-freezing and subsequent annealing. • The hierarchical MoS 2 /Ti 3 C 2 Tx hybrid exhibit excellent HER catalytic activity with a small onset overpotential of 30 mV. • More than 25-fold increase in the exchange current density of the MoS 2 /Ti 3 C 2 T x hybrid compared with MoS 2 was observed. Abstract Developing highly efficient noble-metal-free electrocatalysts for hydrogen evolution reaction (HER) has attracted increasing attentions. Here, we report a simple strategy to synthesize the hierarchical "nanoroll" like MoS 2 /Ti 3 C 2 T x hybrid by combining liquid nitrogen-freezing and subsequent annealing. The quick freezing of the Ti 3 C 2 T x nanosheets and ammonium tetrathiomolybdate mixture causes a sudden change in the strain of Ti 3 C 2 T x , which leads to an interesting "nanoroll" like hierarchical structure. After annealing at H 2 /Ar atmosphere, vertically aligned molybdenum sulfide (MoS 2) crystallites are in situ formed in and on the nanoroll like Ti 3 C 2 T x. Notably, this hierarchical MoS 2 /Ti 3 C 2 T x hybrid exhibits excellent HER catalytic activity with a small onset overpotential of 30 mV, and a more than 25-fold increase in the exchange current density compared with MoS 2 was observed. [ABSTRACT FROM AUTHOR]

Abstract The search for next-generation solid-state superionic conductors has attracted significant attention. Among Na superionic conductors, Na 11 Sn 2 PS 12 has been reported to have a room temperature ionic conductivity of 1.4 mS/cm. In this study, we employ density functional theory to study the stability of Na 11 Sn 2 PS 12 and further explore the substitution of Sn with Ge. Our results indicate that Na 11 Ge 2 PS 12 is more stable than Na 11 Sn 2 PS 12. Furthermore, substituting Sn with Ge increases the band gap, improves the room temperature ionic conductivity by a factor of 2, and lowers the activation energy of Na hopping. Statistical analysis suggests that Na 11 Ge 2 PS 12 has a faster diffusion along the ab -plane compared to the c -axis. The Na diffusion in Na 11 Ge 2 PS 12 appears to occur with two different mechanisms depending on temperature: 1) an ion hopping process at lower temperatures (<800 K); 2) a fluid-like distribution of Na ions at higher temperatures (>1000 K). The computations suggest that Na 11 Ge 2 PS 12 is a promising candidate as a solid Na electrolyte due to its high room temperature ionic conductivity and phase stability. In light of these simulation results, we expect to stimulate further experimental studies on Na 11 Ge 2 PS 12. Highlights • Superionic conductors Na 11 M 2 PS 12 (M = Sn, Ge) have been investigated using DFT. • Na 11 Ge 2 PS 12 is predicted to be more stable than Na 11 Sn 2 PS 12. • Substitution of Sn with Ge increases the bandgap and improves the Na conductivity. • Na 11 Ge 2 PS 12 shows the highest RT ionic conductivity in the Na-Ge-P-S family. • Two types of Na diffusion mechanism in Na 11 Ge 2 PS 12 have been discovered. [ABSTRACT FROM AUTHOR]

Abstract The effect of thermal cycling on the mechanical properties of metal matrix composites (MMCs) reinforced with micro-fillers have been studied for a long time, but that for nano-size-reinforcements remains largely unexplored, such as carbon nanotubes (CNTs). We have fabricated CNTs/Cu laminated MMCs with well-balanced tensile strength and elongation via flake powder metallurgy. In this work, the effect of thermal cycling on their mechanical properties are investigated in a temperature range of –196/+ 200 °C. The thermal cycling results in reductions in strength and elongation and modulus, but the strengthening role of CNTs remains in some extents as compared to the pure Cu counterpart. Tensile tests at room temperature show that high strain hardening ability can be regained even after a sharp stress drop in the thermally cycled composites. The observations on transmission electron microscope (TEM) and scanning electron microscope (SEM) show that the amount of crack increases gradually in the composites upon thermal cycling. Nevertheless, CNT bridges are often found bestriding the cracks and impeding their propagating. The TEM results indicate high density of dislocation in the Cu matrix after thermal cycling, but it decreases after enough thermal cycles, which might be attributed to the stress releasing caused by crack propagation. The failure mode is dominated by the inter-carbon-layer fracture of the multi-walled CNTs in the composites subjected to thermal cycling and tensile loading. [ABSTRACT FROM AUTHOR]

Highlights • All modes model is proposed to analyze the ejector performance. • The non-uniform distribution of the flow field is considered. • Influences of component efficiencies on the ejector performance are discussed. • Experimental results are used to validate the effectiveness of the model. Abstract This paper focuses on the problem of the modeling of the supersonic ejector under both critical and subcritical mode. Unlike the traditional 1D mathematical model, the proposed model takes into account the non-uniform distribution of the flow field in the radial direction. For the critical point, it is assumed that the mixing progress occurs in the constant area mixing chamber under a uniform mixing pressure which is between the stagnation pressure and choking pressure of the secondary flow. However, a constant area mixing assumption is made when the ejector operates under the subcritical mode. By using an exponential relationship to approximate the velocity distribution of the secondary flow in the radial direction, both the entrainment ratio and back pressure can be calculated. The influence of component efficiencies on the ejector performance for different working fluids is presented and analyzed. Finally, experimental results are used to validate the effectiveness of the proposed model. [ABSTRACT FROM AUTHOR]

Highlights • A new thermodynamic model is proposed to evaluate the ejector performance. • The adjoint sensitivity method is used to analyze the ejector sensitivity. • Geometric parameters have the most influences on the entrainment ratio. • The sensitivity coefficient of entrainment ratio to At is −2.43%. • The sensitivity coefficient of the critical back pressure to ϕ is 2.59%. Abstract This paper focuses on the problems of thermodynamic modeling and sensitivity analysis of the ejector in refrigeration. Firstly, a new thermodynamic model is proposed based on the assumptions of constant pressure mixing and constant area mixing. The proposed model contains fewer parameters and simpler structure compared with the traditional ejector models. Later, the sensitivity analysis of the ejector is carried out based on the adjoint sensitivity method. Three different sensitivity coefficients are given to reveal the relation between design parameters and ejector performance. The result shows that geometric parameters have the most influences on the entrainment ratio of the ejector. For the ejector using R600a, the sensitivity coefficients of entrainment ratio to A t and A m are - 2.43 % and 2.40 % respectively. [ABSTRACT FROM AUTHOR]

Abstract In this paper, an auto-tuning AR (area ratio) ejector and an auto-tuning NXP (nozzle exit position) ejector are designed to solve the contradictions between the fixed structure and the dynamic primary pressure driven by multi-condition low-grade heat energy. A CFD (Computational Fluid Dynamics) model is used to calculate the performance of the ejector under different operational conditions. The effects of both AR and NXP on the performance of the ejector are systematically studied. The optimal area ratio increases linearly along with the primary pressure, and the optimum NXP decreases as the primary flow pressure increases. Following this, auto-tuning AR and NXP ejectors are designed to enhance the performance of the ejector by self-adjusting the AR and NXP with a variation in primary flow pressure. Simulation results show that the auto-tuning ejector has a strong ability to improve the ejector performance compared with the constant structure ejector. Highlights • Two types of novel auto-tuning ejectors are proposed. • The correlation between the optimum AR/NXP and primary flow pressure is developed. • The entrainment ratios between the auto-tuning ejector and traditional ejector are compared. • Adjusting AR has a better ability to improve the ejector performance than changing NXP. [ABSTRACT FROM AUTHOR]

This article provides an adaptive asymptotic backstepping-based tracking control algorithm for autonomous underwater vehicles (AUVs) under the situation of non-vanishing uncertainties and input saturation. Firstly, the adaptive asymptotic control algorithm is developed to compensate the non-vanishing uncertainties. And then, virtual control stabilizing functions are reconstructed to improve the system performance by virtue of variable substitutions. Next, the hyperbolic tangent function is applied to handle the unknown input saturation problem. Based on the Lyapunov stability theory, the asymptotic stability of AUVs is proven. Finally, simulation results illustrate that the control strategy can effectively inhibit the effect of unknown model dynamics on the system. • A novel adaptive backstepping control strategy is proposed for autonomous underwater vehicles. • The proposed control strategy achieves the asymptotic tracking control. • Compared with other works, the proposed control strategy has higher control precision. [ABSTRACT FROM AUTHOR]

Porous graphene (P-rGO) was synthesized from graphene oxide (GO) via a one-pot calcination method with CO 2 as an activation agent at 800 °C. Due to the special porous structure, the surface area of P-rGO can be increased to ∼759 m 2 /g. The P-rGO was then used as a support to incorporate with chemical exfoliated molybdenum disulfide (MoS 2 ) for the fabrication of MoS 2 /P-rGO composite. Compared to bulk MoS 2 , the exfoliated MoS 2 is in the 1T phase with a metallic property and smaller charge transfer resistance, thus has a better activity in electrochemical hydrogen evolution reaction (HER). The HER activity of 1T MoS 2 could be further increased after the combination with P-rGO. The overpotential of 1T MoS 2 /P-rGO was only ∼130 mV vs. RHE, and the corresponding Tafel slope was ∼75 mV Dec −1 . The special porous structure and good electric conductivity of P-rGO decrease the charge transfer resistance of the composite without sheltering too many active sites of MoS 2 , thus leading to the enhanced HER activity. As an efficient noble metal free HER catalyst, the 1T MoS 2 /P-rGO has great potential for large-scale hydrogen production. [ABSTRACT FROM AUTHOR]

Camera calibration is a key step in three-dimensional (3-D) reconstruction; however, the calibration accuracy and stability often suffer from complicated illumination in real applications. The camera calibration method using the checkerboard pattern is improved for high-precision calibration under complicated illumination. First, an improved Harris corner detector based on color constancy, as well as a subpixel optimization method based on prior knowledge of the checkerboard, are proposed to overcome the influence of bad lighting. Second, a checkerboard pattern with a central circle point is designed for better reference point location for uneven illumination. The checkerboard identification by Delaunay triangulation is also improved for the situation of discontinuity caused by over-saturation. Finally, the camera parameter optimization process is improved to reduce the calibration error produced by complicated illumination. Experimental results show that the improvements achieve more accurate and stable calibration results in complicated lighting conditions compared with traditional methods. ©2018 SPIE and IS&T[DOI: 10.1117/1.JEI.27.4.043038] [ABSTRACT FROM AUTHOR]

Multiwalled carbon nanotubes/copper (MWCNTs/Cu) composites with a nanolaminated structure have been successfully prepared via flake powder metallurgy. The key strategies are to achieve uniform dispersion of carbon nanotubes in copper matrix and laminated structure, leading to high strengthening efficiencies and architecture toughening. As a result, the composites show balanced failure strength and elongation and high electrical conductivity. The tensile strength of 1.0 vol% MWCNTs/Cu laminated composite is 395 MPa, 87% higher than that of coarse-grained Cu. At the same time, the enhancement on strength does not cause serious deterioration in failure elongation and electrical conductivity. A satisfied uniform elongation in excess of 20% and an electrical conductivity more than 90% International Annealed Copper Standard (IACS) are retained in the composite. Characterizations by in-situ digital image correlation and X-ray tomography indicate efficient stress transferring during loading as well as laminated structure guiding crack propagation, contributing to the good strength-elongation balance. Additionally, the electrical conductivity of the composites is anisotropic because of the laminated structure. [ABSTRACT FROM AUTHOR]

Ejectors are widely used in the refrigeration system and the evaluation of the ejector performance is important for the refrigeration system real time control. In this paper, a simple model is proposed to predict the performance of the ejector in the refrigeration system. A theoretical model is developed based on the thermodynamic principles and ideal gas property firstly. And then the proposed model is simplified to linear equations with four unknown parameters which can be determined by traditional identification methods easily. The accuracy of the model is validated by literature and experimental data. The results show that the model has a strong ability to predict the ejector entrainment ratio and critical back pressure. Furthermore, the proposed method is more accuracy and simpler than the previously published models. It is hoped that the proposed model is useful for the real time control of the ejector refrigeration system. [ABSTRACT FROM AUTHOR]

In this paper, an axi-symmetric computational fluid dynamics (CFD) model is used to investigate the effect of the area ratio on ejector component efficiencies. The geometrical parameters and operating conditions are designed for thermal vapor compression (TVC) used in multi-effect distillation (MED) desalination system. By changing the primary nozzle throat diameter and ejector throat diameter, two groups of ejectors are tested under different operating conditions. The results show that the mixing efficiency plays a more important role in ejector performance than other efficiencies such as primary nozzle efficiency, suction efficiency and diffuser efficiency with the changing of the area ratio. The mixing efficiency can be improved as much as 200% by adjusting the area ratio, and the entrainment ratio is increased from 0.025 to 0.8. Finally empirical correlations are summarized to estimate ejector component efficiencies. [ABSTRACT FROM AUTHOR]

Combined compression-ejector refrigeration systems have attracted lots of attention in recent years. In order to improve the running stability of the complex refrigeration system, it is necessary to obtain a simple and accuracy mathematical model for system control. In this paper, a control oriental model for combined compression ejector system is proposed. By analyzing the inner relationship between compressor and ejector, a hybrid model is built based on thermodynamic principles and lumped parameter method. Comparing with traditional theoretical models, the model is more suitable for system control due to its simpler structure and less parameters. Then the pressure pulsating phenomenon inside the piping system between compressor and ejector is investigated based on the model. The effectiveness of the proposed model is validated by experimental data. It is shown that the model can reflect the system performance under variable operating conditions. [ABSTRACT FROM AUTHOR]

In this study, the fatigue spalling process and mechanism of the white etched area (WEA) caused by the laser quenching surface treatment of U71MnG rail material were investigated. The results demonstrate that the surface pearlite is visibly deformed under normal stress and creep force during the initial wear stage, whereas the WEA is not deformed. Discordant plastic deformation results in the formation of cracks at the contact between the initial position of the WEA and the substrate, which then propagates into the WEA. As the number of rolling cycles increases, the formation and propagation of cracks gradually shift into the middle of the WEA and branch cracks form, which eventually intersect and cause spalling. The substrate's plastic flow covers the WEA terminal position surface; the WEA edge fracture is formed due to bending under normal stress. Plastic deformation enhances the surface hardness of WEA. The substrate's apparent plastic deformation beneath the WEA suggests that the WEA flows under the influence of creep forces. • WEA spalling mechanism was studied. • The mechanism of crack initiation and propagation near WEA was studied. • The plastic flow of the matrix covered the end position WEA, and WEA edge fractured. • The surface hardness of WEA is improved by plastic deformation. • The plastic deformation of the substrate below WEA indicates that the WEA flows. [ABSTRACT FROM AUTHOR]

Texture information plays an important role in rendering true objects, especially with the wide application of image-based three-dimensional (3-D) reconstruction and 3-D laser scanning. This paper proposes a seamless texture mapping algorithm to achieve a high-quality visual effect for 3-D reconstruction. At first, a series of image sets is produced by analyzing the visibility of triangular facets, the image sets are clustered and segmented into a number of optimal reference texture patches. Second, the generated texture patches are sequenced to create a rough texture map, then a weighting process is adopted to reduce the color discrepancies between adjacent patches. Finally, a multiresolution decomposition and fusion technique is used to generate the transition section and eliminate the boundary effect. Experiments show that the proposed algorithm is effective and practical for obtaining high-quality 3-D texture mapping for 3-D reconstruction. Compared with traditional methods, it maintains the texture clarity while eliminating the color seams, in addition, it also supports 3-D texture mapping for big data application. © 2016 SPIE and IS&T [DOI: 10.1117/1.JEI.25.5.053025] [ABSTRACT FROM AUTHOR]

The wear damage and fatigue spalling behaviors of the martensite strip white etched area (WEA) prepared by subjecting the U71MnG steel to laser quenching were studied. The results showed that the wear mechanism of the strip WEA surface changed from a combination of oxidation wear and adhesive wear to oxidation wear with increasing number of cycles. The uncoordinated deformation of the substrate and strip WEA initiated the formation of cracks at their interface. Moreover, the low thickness of WEA at the initial position and plastic deformation of the substrate in front and below accelerated the WEA spalling. At the middle position, the increase in the WEA bulge made it bear a larger load, leading to a more significant rheological displacement of the strip WEA than that of the substrate. The cracks were preferentially initiated at the interface and then propagated to the surface and depth of WEA to form branch cracks. The main crack propagated through WEA to the underlying substrate, causing severe spalling. At the end position, the plastic flow of the substrate formed the sheet metal on the strip WEA surface. [ABSTRACT FROM AUTHOR]

Liquefaction of alkaline lignin in three hydrogen donor solvents (HDSs) was studied at temperatures of 300–440 °C in a high-throughput micro-reactor system capable for 20 parallel micro-reactors. The reactors can be heated to a designated temperature in less than 1 min without overshooting. The HDS 9,10-dihydroanthracene (DHA) was found to be better than 9,10-dihydrophenanthrene (DHP) and 1,2,3,4-tetrahydrocarbazole (THCA) in terms of monophenols yield (Y phenols). The effects of DHA loading, reaction time and temperature on the yields of liquid product (Y liquid) and monophenols were evaluated. Distribution of monophenols, DHA conversion and the quantity of hydrogen donated by DHA (Q H) were elaborated to understand the reaction matrix. Results indicate that the HDSs significantly promote the lignin liquefaction and monophenols formation, and the liquid products and the phenols are formed via two routes. The optimal reaction conditions are 400 °C for 1–2 min or 350 °C for 8–10 min with the Y phenols of 10.3–10.7%. The maximum theoretical monophenols yield is about 12.7% for the lignin under the conditions studied. • 9,10-dihydroanthracene (DHA) is superior to other H-donor solvents for monophenols. • The optimal conditions are 400 °C for 1–2 min or 350 °C for 8–10 min • The maximum yield of monophenols is 10.7% and comparable to the literature reports. • Liquid yield is linearly correlated with the quantity of hydrogen donation. • The yields of liquid product and monophenols are formed via two routes. [ABSTRACT FROM AUTHOR]

• The fraction of edges of MoS 2 (WS 2) can be increased by partial etching strategy. • High-yield MoS 2 (WS 2) monolayers were obtained by liquid phase exfoliation. • The semiconducting 2H phase was retained in the MoS 2 (WS 2) monolayers. • Exfoliated MoS 2 (WS 2) monolayers exhibited superior cocatalytic performance. Monolayer MoS 2 (WS 2) nanosheets have triggered tremendous interest due to their fascinating unique properties, but high-yield production of single-layer MoS 2 (WS 2) still remains an enormous challenge and of great interest. Herein, we report a facile efficient partial etching strategy to tailor thickness and lateral size of MoS 2 (WS 2) so as to increase the fraction of edges, which remarkably enhanced the yield of monolayer MoS 2 (20%) and WS 2 (12%) nanosheets by liquid phase exfoliation. As a proof of concept, the exfoliated monolayer MoS 2 (WS 2) nanosheets were applied as the cocatalysts for photocatalytic hydrogen evolution. Notably, the optimized hybrids exhibit excellent hydrogen evolution performance, which are over 31-fold (MoS 2 /CdS) and 47-fold (WS 2 /CdS) higher that of bare CdS counterpart, respectively. Hence, this work not only may pave the new way for the high-yield production of transition-metal dichalcogenides monolayers by liquid phase exfoliation, but also provide the possibility for the further efficiently exfoliating other two-dimension layered materials. [ABSTRACT FROM AUTHOR]

[Display omitted] • Ag precipitation in particle surface is dependent on size at low temperature. • Ag precipitation was independent on particle size at high temperature. • Ag diffusion at low temperature is dominated by surface and GB diffusion. • Ag network in particle surface improve the oxidation resistance of powders. Ag precipitation and the resultant oxidation behavior of Cu-5wt.%Ag powder of various particle sizes were investigated. During low-temperature aging (250 ℃), Ag precipitation along grain boundaries (GBs) in particle surface is closely dependent on particle size. The depth of Ag precipitation-free area (Ag-PFA) are 0 μm, 1.17 μm and 2.78 μm for S, M and L samples, respectively. While for high-temperature aging (550 ℃), the Ag precipitation was independent on particle size. This is ascribed to that Ag diffusion in particles at low temperature is dominated by both surface diffusion and GB diffusion, while at the higher temperature, the volume diffusion also becomes dominant. The formation of a continuous 3D-Ag network along GBs in particle surface can significantly improve the oxidation resistance of powders. [ABSTRACT FROM AUTHOR]

• Vertically aligned 1 T phase MoS 2 nanosheet array was prepared by a simple method. • Synergistic effect of 1 T phase and unique structure endows outstanding properties. • The cathode shows excellent specific capacity and outstanding cycling stability. • The mechanism was clarified by combining characterizations and DFT calculations. Recently, low-cost and environment-friendly rechargeable aqueous Zn-ion batteries have attracted extensive attention. However, the development of excellent performance cathode is still one of major challenge. Herein, for the first time, we successfully fabricated a free-standing cathode with vertically aligned 1 T phase MoS 2 nanosheet array on carbon cloth and comprehensively investigated its rechargeable aqueous Zn-ion batteries performance. Benefiting from the synergistic effect of vertically aligned 1 T phase MoS 2 nanosheet array and free-standing structure, the free-standing cathode displays a outstanding specific capacity of 198 mA h g−1 at the current density of 100 mA g−1. Impressively, it exhibits distinguished cycling stability, even when cycled at current density of 2000 mA g−1, that the specific capacity retention of 97.2% and 87.8% can be obtained after 1000 and 2000 cycles, respectively. Furthermore, the mechanisms involved were clarfied by combining systematical characterizations and density functional theory calculations. This work will bring new insights for preparing high-performance rechargeable aqueous Zn-ion batteries cathode materials for large-scale energy storage. [ABSTRACT FROM AUTHOR]

Mesoporous silica nanocarriers with tunable particlesizes and different loadings of pendent carboxylic groups were successfullyprepared by a straightforward and reproducible strategy, in whichcarboxyethylsilanetriol sodium salt was co-condensed with tetraethoxyorthosilicateto introduce the carboxylic groups. The key in this strategy was toseparate the synthesis process into two steps of the nuclei formationand particle growth. The uniform particle size and ordered structureof the synthesized nanocarriers were manifested by several techniquessuch as XRD, TEM, SEM, and BET. DLS measurement illustrated that nanocarrierscould be well suspended in aqueous solution. The integration and contenttunability of the carboxylic groups within mesoporous silica nanoparticles(MSNs) were verified by FT-IR and 29Si NMR. The inherentcarboxylic units on the obtained carboxylic group modified MSNs (MSNs-C)effectively enhanced the capture and tailored the release propertiesof the anticancer drug of cisplatin. The accumulation of drug in theHeLa cells was greatly enhanced due to the highly efficient platinumuptake efficiency transported by the synthesized nanocarriers. Thedrug encapsulated in the MSNs-C exhibited a higher antitumor activitythan free cisplatin against both MCF-7 and HeLa cells. [ABSTRACT FROM AUTHOR]

Two-dimensional/three-dimensional hierarchical self-supporting potassium ammonium vanadate@MXene hybrid films exhibit excellent electrochemical performance. [Display omitted] Currently, aqueous zinc ion batteries (AZIBs) have grown to be a good choice for large-scale energy storage systems due to their high theoretical specific capacity, low redox potential, low cost, and non-toxicity of the aqueous electrolyte. However, it is still challenging to obtain high specific capacity and stability suitable cathodes. Herein, hierarchical self-supporting potassium ammonium vanadate@MXene (KNVO@MXene) hybrid films were prepared by vacuum filtration method. Due to the three-dimensional nanoflower structure of KNVO with dual ions intercalation, high conductivity of two-dimensional Ti 3 C 2 T x MXene, and the hierarchical self-supporting structure, the AZIB based on the KNVO@MXene hybrid film cathode possessed superior specific capacity (481 mAh/g at 0.3 A/g) and cycling stability (retaining 125 mAh/g after 1000 cycles at a high current density of 10 A/g). In addition, the storage mechanism was revealed by various ex-situ characterizations. Hence, a new viewpoint for the preparation of AZIB self-supporting cathode materials is presented. [ABSTRACT FROM AUTHOR]

This study aims to deeply understand the effect of contact stress and slip ratio on wear performances of bainitic rail steels. The results showed that the wear loss increased as the contact stress and slip ratio increased. Based on the surface damage morphology and microstructural analyses, it revealed that the rolling contact fatigue wear mechanism played a significant role under the low slip ratio, but the dominant wear mechanism transferred to the abrasive wear at the high slip ratio. Meanwhile, the bainitic steel specifically presented worse wear resistance under the abrasive wear mode. Compared with the influence of a slip ratio, the increase in contact stress led to severer plastic flows and contributed to the propagation of cracks. In addition, the contact stress and slip ratio had the opposite effect on the friction coefficient, that is, the friction coefficient of bainitic steels behaved the inverse proportion with the contact stress, but positive proportion with the slip ratio. At last, the increase in slip ratio had more significant effect on the reduction of retained austenite (RA) than the enlargement of contact stress due to the fact that the RA would probably be removed before the martensitic transformation occurred under the abrasive wear mechanism. [ABSTRACT FROM AUTHOR]

Electrochemical impedance spectroscopy (EIS) is one of the most widely used experimental tools in electrochemistry and has applications ranging from energy storage and power generation to medicine. Considering the broad applicability of the EIS technique, it is critical to validate the EIS data against the Hilbert transform (HT) or, equivalently, the Kramers–Kronig relations. These mathematical relations allow one to assess the self-consistency of obtained spectra. However, the use of validation tests is still uncommon. In the present article, we aim at bridging this gap by reformulating the HT under a Bayesian framework. In particular, we developed the Bayesian Hilbert transform (BHT) method that interprets the HT probabilistically. Leveraging the BHT, we proposed several scores that provide quick metrics for the evaluation of the EIS data quality. [ABSTRACT FROM AUTHOR]