University of Science and Technology Liaoning

The durability and reactivity of catalysts can be effectively and precisely controlled through the careful design and engineering of their surface structures and morphologies. Herein, we develop a novel “adsorption–calcination–reduction” strategy to synthesize spinel transitional metal oxides with a unique necklace-like multishelled hollow structure exploiting sacrificial templates of carbonaceous microspheres, including NiCo 2 O 4 (NCO), CoMn 2 O 4, and NiMn 2 O 4 . Importantly, benefiting from the unique structures and reduction treatment to offer rich oxygen vacancies, the unique reduced NCO (R-NCO) as a bifunctional electrocatalyst exhibits the dual characteristics of good stability as well as high electrocatalytic activity for both the hydrogen evolution reaction (HER) and oxygen evolution reaction (OER). At 1.61 V cell voltage, a 10 mA cm –2 water splitting current density is obtained from the dual-electrode, alkaline water electrolyzer. Calculations based on density functional theory (DFT) reveal a mechanism for the promotion of the catalytic reactions based on a decrease in the energy barrier for the formation of intermediates resulting from the introduction of oxygen vacancies through the reduction process. This method could prove to be an effective general strategy for the preparation of complex, hollow structures and functionalities.

A salty route to an all-nitrogen ring The flip side of the robust stability of N 2 is the instability of any larger molecules composed exclusively of nitrogen. These molecules nonetheless remain enticing targets for explosive and propellant applications. Zhang et al. successfully prepared the pentazolate ion, a negatively charged ring of five nitrogens, by oxidative cleavage of a C–N bond in an aryl-substituted precursor (see the Perspective by Christe). The molecule was stabilized and isolated in the solid state as a hydrated ammonium chloride salt. Spectroscopic and crystallographic characterization confirmed the ring's planar geometry. Science , this issue p. 374 ; see also p. 351

This article investigates an adaptive practical fixed-time control strategy for the output tracking control of a class of strict feedback nonlinear systems. By utilizing a backstepping algorithm, finite-time Lyapunov stable theory, and fuzzy logic control, a novel adaptive practical fixed-time controller is constructed. Fuzzy logic systems are introduced to approximate the unknown items of the system. Theoretical analysis proves that under the presented control strategy, the closed-loop system is practically fixed-time stable, and the tracking error converges to a small neighborhood of the origin within a fixed-time interval, in which the convergence time has no connection with the initial states of the system. In the meantime, all the signals of the closed-loop system are bounded. Finally, a numerical example is presented to indicate the feasibility and effectiveness of the proposed method.

Rechargeable batteries are considered promising replacements for environmentally hazardous fossil fuel-based energy technologies. High-energy lithium-metal batteries have received tremendous attention for use in portable electronic devices and electric vehicles. However, the low Coulombic efficiency, short life cycle, huge volume expansion, uncontrolled dendrite growth, and endless interfacial reactions of the metallic lithium anode are major obstacles in their commercialization. Extensive research efforts have been devoted to address these issues and significant progress has been made by tuning electrolyte chemistry, designing electrode frameworks, discovering nanotechnology-based solutions, etc. This Review aims to provide a conceptual understanding of the current issues involved in using a lithium metal anode and to unveil its electrochemistry. The most recent advancements in lithium metal battery technology are outlined and suggestions for future research to develop a safe and stable lithium anode are presented.

The effective separation of photogenerated carriers plays a vital role in photocatalytic reactions. In addition to the intrinsic driving force of photocatalysis, an external field generating an enhancement effect can provide extra energy to the photocatalytic system, acting as an additional impetus to separate photogenerated charges and thus improving the overall catalytic efficiency. Under the favorable noncontact conditions, exploring the effect of the external field, different from pure photocatalysis or photoelectrocatalysis, could widen the applications of photocatalysis technology. In this review, four typical noncontact external fields (i.e., thermal, magnetic, microwave, and ultrasonic fields) and their coupling effects on photocatalysis are summarized. Specifically, the review focuses on the mechanism and characteristics of each external field’s synergistic effect and their coupling effects on the performance of the catalytic system. The charge separation driving forces provided by the noncontact external field and the traditional one are distinguished and defined for the first time. The challenges and future prospects of noncontact external-field-driven photocatalysis are discussed. We hope that this review will provide a reference for the research and development of external-field-assisted photocatalysis and give insights for the in-depth study of external-field-coupling-enhanced photocatalysis toward improvement of the catalytic efficiency.

Abstract The spatial distribution and transport characteristics of lithium ions (Li + ) in the electrochemical interface region of a lithium anode in a lithium ion battery directly determine Li + deposition behavior. The regulation of the Li + solvation sheath on the solid electrolyte interphase (SEI) by electrolyte chemistry is key but challenging. Here, 1 m lithium trifluoroacetate (LiTFA) is induced to the electrolyte to regulate the Li + solvation sheath, which significantly suppresses Li dendrite formation and enables a high Coulombic efficiency of 98.8% over 500 cycles. With its strong coordination between the carbonyl groups (CO) and Li + , TFA − modulates the environment of the Li + solvation sheath and facilitates fast desolvation kinetics. In addition, due to relatively smaller lowest unoccupied molecular orbital energy than solvents, TFA − has a preferential reduction to produce a stable SEI with uniform distribution of LiF and Li 2 O. Such stable SEI effectively reduces the energy barrier for Li + diffusion, contributing to low nucleation overpotential, fast ion transfer kinetics, and uniform Li + deposition with high cycling stability. This work provides an alternative insight into the design of interface chemistry in terms of regulating anions in the Li + solvation sheath. It is anticipated that this anion‐tuned strategy will pave the way to construct stable SEIs for other battery systems.

Abstract Multiferroic nanomaterials have attracted great interest due to simultaneous two or more properties such as ferroelectricity, ferromagnetism, and ferroelasticity, which can promise a broad application in multifunctional, low-power consumption, environmentally friendly devices. Bismuth ferrite (BiFeO 3 , BFO) exhibits both (anti)ferromagnetic and ferroelectric properties at room temperature. Thus, it has played an increasingly important role in multiferroic system. In this review, we systematically discussed the developments of BFO nanomaterials including morphology, structures, properties, and potential applications in multiferroic devices with novel functions. Even the opportunities and challenges were all analyzed and summarized. We hope this review can act as an updating and encourage more researchers to push on the development of BFO nanomaterials in the future.

Long non-coding RNA (lncRNA) and microRNA (miRNA) are two typical types of non-coding RNAs (ncRNAs), their interaction plays an important regulatory role in many biological processes. Exploring the interactions between unknown lncRNA and miRNA can help us better understand the functional expression between lncRNA and miRNA. At present, the interactions between lncRNA and miRNA are mainly obtained through biological experiments, but such experiments are often time-consuming and labor-intensive, it is necessary to design a computational method that can predict the interactions between lncRNA and miRNA. In this paper, we propose a method based on graph convolutional neural (GCN) network and conditional random field (CRF) for predicting human lncRNA-miRNA interactions, named GCNCRF. First, we construct a heterogeneous network using the known interactions of lncRNA and miRNA in the LncRNASNP2 database, the lncRNA/miRNA integration similarity network, and the lncRNA/miRNA feature matrix. Second, the initial embedding of nodes is obtained using a GCN network. A CRF set in the GCN hidden layer can update the obtained preliminary embeddings so that similar nodes have similar embeddings. At the same time, an attention mechanism is added to the CRF layer to reassign weights to nodes to better grasp the feature information of important nodes and ignore some nodes with less influence. Finally, the final embedding is decoded and scored through the decoding layer. Through a 5-fold cross-validation experiment, GCNCRF has an area under the receiver operating characteristic curve value of 0.947 on the main dataset, which has higher prediction accuracy than the other six state-of-the-art methods.

Metabolism is the process by which an organism continuously replaces old substances with new substances. It plays an important role in maintaining human life, body growth and reproduction. More and more researchers have shown that the concentrations of some metabolites in patients are different from those in healthy people. Traditional biological experiments can test some hypotheses and verify their relationships but usually take a considerable amount of time and money. Therefore, it is urgent to develop a new computational method to identify the relationships between metabolites and diseases. In this work, we present a new deep learning algorithm named as graph convolutional network with graph attention network (GCNAT) to predict the potential associations of disease-related metabolites. First, we construct a heterogeneous network based on known metabolite-disease associations, metabolite-metabolite similarities and disease-disease similarities. Metabolite and disease features are encoded and learned through the graph convolutional neural network. Then, a graph attention layer is used to combine the embeddings of multiple convolutional layers, and the corresponding attention coefficients are calculated to assign different weights to the embeddings of each layer. Further, the prediction result is obtained by decoding and scoring the final synthetic embeddings. Finally, GCNAT achieves a reliable area under the receiver operating characteristic curve of 0.95 and the precision-recall curve of 0.405, which are better than the results of existing five state-of-the-art predictive methods in 5-fold cross-validation, and the case studies show that the metabolite-disease correlations predicted by our method can be successfully demonstrated by relevant experiments. We hope that GCNAT could be a useful biomedical research tool for predicting potential metabolite-disease associations in the future.

Cryptographic technique is one of the principal means to protect information security. Not only has it to ensure the information confidential, but also provides digital signature, authentication, secret sub-storage, system security and other functions. Therefore, the encryption and decryption solution can ensure the confidentiality of the information, as well as the integrity of information and certainty, to prevent information from tampering, forgery and counterfeiting. Encryption and decryption algorithm's security depends on the algorithm while the internal structure of the rigor of mathematics, it also depends on the key confidentiality. Key in the encryption algorithm has a pivotal position, once the key was leaked, it means that anyone can be in the encryption system to encrypt and decrypt information, it means the encryption algorithm is useless. Therefore, what kind of data you choose to be a key, how to distribute the private key, and how to save both data transmission keys are very important issues in the encryption and decryption algorithm. This paper proposed an implementation of a complete and practical RSA encrypt/decrypt solution based on the study of RSA public key algorithm. In addition, the encrypt procedure and code implementation is provided in details.

Iodine ion is one of the most indispensable anions in living organisms, particularly being an important substance for the synthesis of thyroid hormones. Curcumin is a yellow-orange polyphenol compound derived from the rhizome of Curcuma longa L., which has been commonly used as a spice and natural coloring agent, food additives, cosmetics as well as Chinese medicine. However, excess curcumin may cause DNA inactivation, lead to a decrease in intracellular ATP levels, and trigger the tissue necrosis. Therefore, quantitative detection of iodine and curcumin is of great significance in the fields of food and life sciences. Herein, we develop nitrogen-doped fluorescent carbon dots (NCDs) as a multi-mechanism detection for iodide and curcumin in actual complex biological and food samples, which was prepared by a one-step solid-phase synthesis using tartaric acid and urea as precursors without adding any other reagents. An assembled NCDs-Hg2+ fluorescence-enhanced sensor for the quantitative detection of I− was established based on a fluorescence “turn-off-on” mechanism in a linear range of 0.3–15 μM with a detection limit of 69.4 nM and successfully quantified trace amounts of I− in water samples and urine sample. Meanwhile, the as-synthesized NCDs also can be used as a fluorescent quenched sensor for curcumin detection based on the synergistic internal filtration effect (IFE) and static quenching, achieving a good linear range of 0.1–20 μM with a satisfactory detection limit of 29.8 nM. These results indicate that carbon dots are potential sensing materials for iodine and curcumin detection for the good of our health.

The cross section for the process ${e}^{+}{e}^{\ensuremath{-}}\ensuremath{\rightarrow}{\ensuremath{\pi}}^{+}{\ensuremath{\pi}}^{\ensuremath{-}}J/\ensuremath{\psi}$ is measured precisely at center-of-mass energies from 3.77 to 4.60 GeV using $9\text{ }\text{ }{\mathrm{fb}}^{\ensuremath{-}1}$ of data collected with the BESIII detector operating at the BEPCII storage ring. Two resonant structures are observed in a fit to the cross section. The first resonance has a mass of $(4222.0\ifmmode\pm\else\textpm\fi{}3.1\ifmmode\pm\else\textpm\fi{}1.4)\text{ }\text{ }\mathrm{MeV}/{c}^{2}$ and a width of $(44.1\ifmmode\pm\else\textpm\fi{}4.3\ifmmode\pm\else\textpm\fi{}2.0)\text{ }\text{ }\mathrm{MeV}$, while the second one has a mass of $(4320.0\ifmmode\pm\else\textpm\fi{}10.4\ifmmode\pm\else\textpm\fi{}7.0)\text{ }\text{ }\mathrm{MeV}/{c}^{2}$ and a width of $(101.{4}_{\ensuremath{-}19.7}^{+25.3}\ifmmode\pm\else\textpm\fi{}10.2)\text{ }\text{ }\mathrm{MeV}$, where the first errors are statistical and second ones are systematic. The first resonance agrees with the $Y(4260)$ resonance reported by previous experiments. The precision of its resonant parameters is improved significantly. The second resonance is observed in ${e}^{+}{e}^{\ensuremath{-}}\ensuremath{\rightarrow}{\ensuremath{\pi}}^{+}{\ensuremath{\pi}}^{\ensuremath{-}}J/\ensuremath{\psi}$ for the first time. The statistical significance of this resonance is estimated to be larger than $7.6\ensuremath{\sigma}$. The mass and width of the second resonance agree with the $Y(4360)$ resonance reported by the BABAR and Belle experiments within errors. Finally, the $Y(4008)$ resonance previously observed by the Belle experiment is not confirmed in the description of the BESIII data.

Abstract The CIECAM02 color‐appearance model enjoys popularity in scientific research and industrial applications since it was recommended by the CIE in 2002. However, it has been found that computational failures can occur in certain cases such as during the image processing of cross‐media color reproduction applications. Some proposals have been developed to repair the CIECAM02 model. However, all the proposals developed have the same structure as the original CIECAM02 model and solve the problems concerned at the expense of losing accuracy of predicted visual data compared with the original model. In this article, the structure of the CIECAM02 model is changed and the color and luminance adaptations to the illuminant are completed in the same space rather than in two different spaces, as in the original CIECAM02 model. It has been found that the new model (named CAM16) not only overcomes the previous problems, but also the performance in predicting the visual results is as good as if not better than that of the original CIECAM02 model. Furthermore the new CAM16 model is simpler than the original CIECAM02 model. In addition, if considering only chromatic adaptation, a new transformation, CAT16, is proposed to replace the previous CAT02 transformation. Finally, the new CAM16‐UCS uniform color space is proposed to replace the previous CAM02‐UCS space. A new complete solution for color‐appearance prediction and color‐difference evaluation can now be offered.

We extract the e + e − → π + π − cross section in the energy range between 600 and 900 MeV, exploiting the method of initial state radiation. A data set with an integrated luminosity of 2.93 fb − 1 taken at a center-of-mass energy of 3.773 GeV with the BESIII detector at the BEPCII collider is used. The cross section is measured with a systematic uncertainty of 0.9%. We extract the pion form factor | F π | 2 as well as the contribution of the measured cross section to the leading-order hadronic vacuum polarization contribution to ( g − 2 ) μ . We find this value to be a μ π π , LO ( 600 – 900 MeV ) = ( 368.2 ± 2.5 stat ± 3.3 sys ) ⋅ 10 − 10 , which is between the corresponding values using the BaBar or KLOE data.

Lithium (Li) is the lightest and most electronegative metallic element and has been considered the ultimate anode choice for energy storage systems with high energy density. However, uncontrollable dendrite formation caused by high ion transfer resistance and low Li atom diffusion, and dendrite growth with large volume expansion and high electronegative activity, result in severe safety concerns and poor coulombic efficiency. In this review, the latest progress is presented from the viewpoint of dendrite evolution (from dendrite formation to growth) as the main line to understand the factors that influence the deposition chemistry. For the dendrite formation, specific attention is focused on the four distinct but interdependent factors: (a) how the dielectric constant, donor number, viscosity and salt concentration affect the movement of solvated Li+ in nonaqueous electrolyte. (b) The effect of non-polar solvents and anions with polar groups or high concentration on the Li+ desolvation step. (c) The effect of the formation of solid electrolyte interphase (SEI), along with its specific adsorption and solvated structure, and its physical structure, chemical composition and growth thickness on Li+ diffusion. (d) The effect of the diffusion coefficient of the host material on Li atom migration. After dendrite formation, the attention is focused on two detrimental factors together with dendrite growth: (e) low coulombic efficiency; (f) large volume expansion. Correspondingly, the emphasis is placed on reducing the side reactions and minimizing the volume expansion. Conclusions and perspectives on the current limitations and future research directions are recommended. It is anticipated that the dynamic dendrite evolution can provide fresh insight into similar electrochemical reaction processes of other anode chemistries in nonaqueous electrolytes, ranging from a conversion-reaction metal anode (Li, Na, Al) and an alloying anode (LiAlx, NaAlx) to an intercalation-based anode (graphite, TiS2), as well as aqueous, ionic liquid and flow redox battery systems.

Functional compound micromachines are fabricated by a design methodology using 3D direct laser writing and selective physical vapor deposition of magnetic materials. Microtransporters with a wirelessly controlled Archimedes screw pumping mechanism are engineered. Spatiotemporally controlled collection, transport, and delivery of micro particles, as well as magnetic nanohelices inside microfluidic channels are demonstrated.

Higher-efficiency, lower-cost refrigeration is needed for both large- and small-scale cooling. Refrigerators using entropy changes during cycles of stretching or hydrostatic compression of a solid are possible alternatives to the vapor-compression fridges found in homes. We show that high cooling results from twist changes for twisted, coiled, or supercoiled fibers, including those of natural rubber, nickel titanium, and polyethylene fishing line. Using opposite chiralities of twist and coiling produces supercoiled natural rubber fibers and coiled fishing line fibers that cool when stretched. A demonstrated twist-based device for cooling flowing water provides high cooling energy and device efficiency. Mechanical calculations describe the axial and spring-index dependencies of twist-enhanced cooling and its origin in a phase transformation for polyethylene fibers.

Spider silk is a natural polymeric fiber with high tensile strength, toughness, and has distinct thermal, optical, and biocompatible properties. The mechanical properties of spider silk are ascribed to its hierarchical structure, including primary and secondary structures of the spidroins (spider silk proteins), the nanofibril, the "core-shell", and the "nano-fishnet" structures. In addition, spider silk also exhibits remarkable properties regarding humidity/water response, water collection, light transmission, thermal conductance, and shape-memory effect. This motivates researchers to prepare artificial functional fibers mimicking spider silk. In this review, the authors summarize the study of the structure and properties of natural spider silk, and the biomimetic preparation of artificial fibers from different types of molecules and polymers by taking some examples of artificial fibers exhibiting these interesting properties. In conclusion, biomimetic studies have yielded several noteworthy findings in artificial fibers with different functions, and this review aims to provide indications for biomimetic studies of functional fibers that approach and exceed the properties of natural spider silk.

The grey wolf optimizer (GWO) is a novel type of swarm intelligence optimization algorithm. An improved grey wolf optimizer (IGWO) with evolution and elimination mechanism was proposed so as to achieve the proper compromise between exploration and exploitation, further accelerate the convergence and increase the optimization accuracy of GWO. The biological evolution and the "survival of the fittest" (SOF) principle of biological updating of nature are added to the basic wolf algorithm. The differential evolution (DE) is adopted as the evolutionary pattern of wolves. The wolf pack is updated according to the SOF principle so as to make the algorithm not fall into the local optimum. That is, after each iteration of the algorithm sort the fitness value that corresponds to each wolf by ascending order, and then eliminate R wolves with worst fitness value, meanwhile randomly generate wolves equal to the number of eliminated wolves. Finally, 12 typical benchmark functions are used to carry out simulation experiments with GWO with differential evolution (DGWO), GWO algorithm with SOF mechanism (SGWO), IGWO, DE algorithm, particle swarm algorithm (PSO), artificial bee colony (ABC) algorithm and cuckoo search (CS) algorithm. Experimental results show that IGWO obtains the better convergence velocity and optimization accuracy.

The iron-chromium redox flow battery (ICRFB) is considered the first true RFB and utilizes low-cost, abundant iron and chromium chlorides as redox-active materials, making it one of the most cost-effective energy storage systems. ICRFBs were pioneered and studied extensively by NASA and Mitsui in Japan in the 1970-1980s, and extensive studies on ICRFBs have been carried out over the past few decades. In addition, ICRFB is considered to be one of the most promising directions for cost-effective and large-scale energy storage applications, as its cost can theoretically be lower than that of zinc-bromine and all-vanadium RFBs, giving it the potential for large-scale promotion. With the resolution of problems such as hydrogen evolution and electrolyte intermixing, the ICRFB technology is moving out of the laboratory and striving for greater power and more stable industrialization requirements. This Review summarizes the history, development, and research status of key components (carbon-based electrode, electrolyte, and membranes) in the ICRFB system, aiming to give a brief guide to researchers who are involved in the related subject.