Sichuan Normal University

Abstract Although single-atomically dispersed metal-N x on carbon support (M-NC) has great potential in heterogeneous catalysis, the scalable synthesis of such single-atom catalysts (SACs) with high-loading metal-N x is greatly challenging since the loading and single-atomic dispersion have to be balanced at high temperature for forming metal-N x . Herein, we develop a general cascade anchoring strategy for the mass production of a series of M-NC SACs with a metal loading up to 12.1 wt%. Systematic investigation reveals that the chelation of metal ions, physical isolation of chelate complex upon high loading, and the binding with N-species at elevated temperature are essential to achieving high-loading M-NC SACs. As a demonstration, high-loading Fe-NC SAC shows superior electrocatalytic performance for O 2 reduction and Ni-NC SAC exhibits high electrocatalytic activity for CO 2 reduction. The strategy paves a universal way to produce stable M-NC SAC with high-density metal-N x sites for diverse high-performance applications.

Abstract A binder‐free efficient MoNi 4 /MoO 3‐ x nanorod array electrode with 3D open structure is developed by using Ni foam as both scaffold and Ni source to form NiMoO 4 precursor, followed by subsequent annealing in a reduction atmosphere. It is discovered that the self‐templated conversion of NiMoO 4 into MoNi 4 nanocrystals and MoO 3‐ x as dual active components dramatically boosts the hydrogen evolution reaction (HER) performance. Benefiting from high intrinsic activity, high electrochemical surface area, 3D open network, and improved electron transport, the resulting MoNi 4 /MoO 3‐ x electrode exhibits a remarkable HER activity with extremely low overpotentials of 17 mV at 10 mA cm −2 and 114 mV at 500 mA cm −2 , as well as a superior durability in alkaline medium. The water–alkali electrolyzer using MoNi 4 /MoO 3‐ x as cathode achieves stable overall water splitting with a small cell voltage of 1.6 V at 30 mA cm − 2 . These findings may inspire the exploration of cost‐effective and efficient electrodes by in situ integrating multiple highly active components on 3D platform with open conductive network for practical hydrogen production.

Magnetic skyrmions are promising for building next-generation magnetic memories and spintronic devices due to their stability, small size and the extremely low currents needed to move them. In particular, skyrmion-based racetrack memory is attractive for information technology, where skyrmions are used to store information as data bits instead of traditional domain walls. Here we numerically demonstrate the impacts of skyrmion-skyrmion and skyrmion-edge repulsions on the feasibility of skyrmion-based racetrack memory. The reliable and practicable spacing between consecutive skyrmionic bits on the racetrack as well as the ability to adjust it are investigated. Clogging of skyrmionic bits is found at the end of the racetrack, leading to the reduction of skyrmion size. Further, we demonstrate an effective and simple method to avoid the clogging of skyrmionic bits, which ensures the elimination of skyrmionic bits beyond the reading element. Our results give guidance for the design and development of future skyrmion-based racetrack memory.

The generalized Heronian mean and geometric Heronian mean operators provide two aggregation operators that consider the interdependent phenomena among the aggregated arguments. In this paper, the generalized Heronian mean operator and geometric Heronian mean operator under the q-rung orthopair fuzzy sets is studied. First, the q-rung orthopair fuzzy generalized Heronian mean (q-ROFGHM) operator, q-rung orthopair fuzzy geometric Heronian mean (q-ROFGHM) operator, q-rung orthopair fuzzy generalized weighted Heronian mean (q-ROFGWHM) operator, and q-rung orthopair fuzzy weighted geometric Heronian mean (q-ROFWGHM) operator are proposed, and some of their desirable properties are investigated in detail. Furthermore, we extend these operators to q-rung orthopair 2-tuple linguistic sets (q-RO2TLSs). Then, an approach to multiple attribute decision making based on q-ROFGWHM (q-ROFWGHM) operator is proposed. Finally, a practical example for enterprise resource planning system selection is given to verify the developed approach and to demonstrate its practicality and effectiveness.

This article has been retracted. A retraction notice can be found at https://doi.org/10.3233/JIFS-219434 .

Abstract A novel noncentrosymmetric (NCS) polar fluoride sulfate, CsSbF 2 SO 4 , was obtained by ionothermal synthesis. A meticulously designed co‐substitution approach was used to successfully replace the [TiO 6 ] 8− and [PO 4 ] 3− functional groups in KTiOPO 4 (KTP) with [SbO 4 F 2 ] 7− and [SO 4 ] 2− units, respectively. The structure of CsSbF 2 SO 4 features a pseudo‐3D framework consisting of interconnected 1D [SbF 2 O 2 SO 4 ] 5− chains of corner‐sharing [SbO 4 F 2 ] 7− octahedra and [SO 4 ] 2− tetrahedra. The title compound exhibits a sharply enlarged band gap compared to its parent compound, KTP, benefitting from the introduction of F − ions and the displacement of Sb 3+ cations. Second harmonic generation (SHG) measurements manifested that CsSbF 2 SO 4 is phase‐matchable and revealed a strong SHG response of about 3.0 KH 2 PO 4 (KDP), which is the highest value reported for any metal sulfate reported to date. The reported fluoride sulfate is a promising near ultraviolet (UV) nonlinear optical (NLO) material.

Graphite carbon nitride (g-C3N4) has a stable structure but poor catalytic capability for activating peroxymonosulfate (PMS). In this study, the codoping of g-C3N4 with bimetallic oxides (iron and cobalt) and oxygen was investigated to enhance its catalytic capability. The results showed that iron, cobalt, and oxygen codoped g-C3N4 (Fe–Co–O–g-C3N4) was successfully prepared, which was capable of completely degrading sulfamethoxazole (SMX) (0.04 mM) within 30 min, with a reaction rate of 0.085 min–1, indicating the superior catalytic activity of Fe–Co–O–g-C3N4. The mineralization efficiency of SMX was 22.1%. Sulfate radicals and singlet oxygen were detected during the process of PMS activation. However, the role that singlet oxygen played in degrading SMX was not obvious. Surface-bound reactive species and sulfate radicals were responsible for SMX degradation, in which sulfate radicals contributed to 46.6% of SMX degradation. The superior catalytic activity was due to the synergistic effect of metal oxides and O–g-C3N4, in which O–g-C3N4 could act as a carrier and an activator as well as an electron mediator to promote the conversion of Fe(III) to Fe(II) and Co(III) to Co(II). Four main steps of SMX degradation were proposed, including direct oxidation of SMX, bond fission of N–C, bond fission of N–S, and bond fission of S–C. The effect of the pH, temperature, PMS concentration, chloridion, bicarbonate, and humic acids on SMX degradation was investigated. Cycling experiments demonstrated the good stability of Fe–Co–O–g-C3N4. This study first reported the preparation of bimetallic oxide and oxygen codoped g-C3N4, which was an effective PMS activator for degradation of toxic organic pollutants.

Abstract Recently, monolayer molybdenum disulphide (MoS 2 ) has emerged as a promising and non–precious electrocatalyst for hydrogen evolution reaction. However, its performance is largely limited by the low density and poor reactivity of active sites within its basal plane. Here, we report that domain boundaries in the basal plane of monolayer MoS 2 can greatly enhance its hydrogen evolution reaction performance by serving as active sites. Two types of effective domain boundaries, the 2H-2H domain boundaries and the 2H-1T phase boundaries, were investigated. Superior hydrogen evolution reaction catalytic activity, long-term stability and universality in both acidic and alkaline conditions were achieved based on a multi-hierarchy design of these two types of domain boundaries. We further demonstrate that such superior catalysts are feasible at a large scale by applying this multi-hierarchy design of domain boundaries to wafer-scale monolayer MoS 2 films.

The field of magnetic skyrmions has been actively investigated across a wide range of topics during the last decades. In this topical review, we mainly review and discuss key results and findings in skyrmion research since the first experimental observation of magnetic skyrmions in 2009. We particularly focus on the theoretical, computational and experimental findings and advances that are directly relevant to the spintronic applications based on magnetic skyrmions, i.e. their writing, deleting, reading and processing driven by magnetic field, electric current and thermal energy. We then review several potential applications including information storage, logic computing gates and non-conventional devices such as neuromorphic computing devices. Finally, we discuss possible future research directions on magnetic skyrmions, which also cover rich topics on other topological textures such as antiskyrmions and bimerons in antiferromagnets and frustrated magnets.

In this paper, we utilize power aggregation operators to develop some Pythagorean fuzzy power aggregation operators: Pythagorean fuzzy power average operator, Pythagorean fuzzy power geometric operator, Pythagorean fuzzy power weighted average operator, Pythagorean fuzzy power weighted geometric operator, Pythagorean fuzzy power ordered weighted average operator, Pythagorean fuzzy power ordered weighted geometric operator, Pythagorean fuzzy power hybrid average operator, and Pythagorean fuzzy power hybrid geometric operator. The prominent characteristic of these proposed operators are studied. Then, we have utilized these operators to develop some approaches to solve the Pythagorean fuzzy multiple attribute decision-making problems. Finally, a practical example is given to verify the developed approach and to demonstrate its practicality and effectiveness.

The industrial Internet of Things (IIoT) supports recent developments in data management and information services, as well as services for smart factories. Nowadays, many mature IIoT cloud platforms are available to serve smart factories. However, due to the semicredibility nature of the IIoT cloud platforms, how to achieve secure storage, access control, information update and deletion for smart factory data, as well as the tracking and revocation of malicious users has become an urgent problem. To solve these problems, in this article, a blockchain-enhanced security access control scheme that supports traceability and revocability has been proposed in IIoT for smart factories. The blockchain first performs unified identity authentication, and stores all public keys, user attribute sets, and revocation list. The system administrator then generates system parameters and issues private keys to users. The domain administrator is responsible for formulating domain security and privacy-protection policies, and performing encryption operations. If the attributes meet the access policies and the user's ID is not in the revocation list, they can obtain the intermediate decryption parameters from the edge/cloud servers. Malicious users can be tracked and revoked during all stages if needed, which ensures the system security under the Decisional Bilinear Diffie-Hellman (DBDH) assumption and can resist multiple attacks. The evaluation has shown that the size of the public/private keys is smaller compared to other schemes, and the overhead time is less for public key generation, data encryption, and data decryption stages.

In this paper, we investigate the multiple attribute decision making problems with picture fuzzy information. The advantage of picture fuzzy set is easily reflecting the ambiguous nature of subjective judgments because the picture fuzzy sets are suitable for capturing imprecise, uncertain, and inconsistent information in the multiple attribute decision making analysis. Thus, the cross entropy of picture fuzzy sets, called picture fuzzy cross entropy, is proposed as an extension of the cross entropy of fuzzy sets. Then, a multiple attribute decision making method based on the proposed picture fuzzy cross entropy is established in which attribute values for alternatives are picture fuzzy numbers. In decision making process, we utilize the picture fuzzy weighted cross entropy between the ideal alternative and an alternative to rank the alternatives corresponding to the cross entropy values and to select the most desirable one(s). Finally, a practical example for enterprise resource planning system selection is given to verify the developed approach and to demonstrate its practicality and effectiveness.

Abstract Electrocatalytic two‐electron oxygen reduction has emerged as a promising alternative to the energy‐ and waste‐intensive anthraquinone process for distributed H 2 O 2 production. This process, however, suffers from strong competition from the four‐electron pathway leading to low H 2 O 2 selectivity. Herein, we report using a superhydrophilic O 2 ‐entrapping electrocatalyst to enable superb two‐electron oxygen reduction electrocatalysis. The honeycomb carbon nanofibers (HCNFs) are robust and capable of achieving a high H 2 O 2 selectivity of 97.3 %, much higher than that of its solid carbon nanofiber counterpart. Impressively, this catalyst achieves an ultrahigh mass activity of up to 220 A g −1 , surpassing all other catalysts for two‐electron oxygen reduction reaction. The superhydrophilic porous carbon skeleton with rich oxygenated functional groups facilitates efficient electron transfer and better wetting of the catalyst by the electrolyte, and the interconnected cavities allow for more effective entrapping of the gas bubbles. The catalytic mechanism is further revealed by in situ Raman analysis and density functional theory calculations.

The cleavage of C-C bonds has been a great challenge owing to their thermodynamic and kinetic stability. To date, the progress made in this area has mainly relied on the reaction of small rings, which is driven by releasing ring strain. Encouragingly, more and more examples of the cleavage of non-strained C-C bonds have been reported. This review provides a comprehensive overview of the transition-metal-catalyzed C-C bond activation of relatively stable and unstrained molecules that involves the formation of organometallic intermediates. In the first section we focus on the C-C bond activation achieved through β-carbon elimination, and in the second section the oxidative addition of the C-C bond to low-valent metal is summarized in detail.

It is highly desired to enhance the catalytic activity of oxygen evolution reaction (OER) electrocatalysts made of earth-abundant elements. In this Letter, we report that the OER activity of a CuO nanoarray can be largely enhanced by Co doping. In 1.0 M KOH, the Co-CuO nanoarray on copper foam requires a current densities of 50 and 100 mA cm–2 at overpotentials of only 299 and 330 mV, respectively. It also shows superior long-term durability over 15 h with a turnover frequency of 0.056 mol O2 s–1 at an overpotential of 300 mV.

A highly attractive, but still a key challenge, is the development of earth-abundant electrocatalysts for efficient NH3 electrosynthesis via the N2 reduction reaction (NRR). In this communication, we report the development of a Mo2N nanorod as a highly efficient and selective NRR electrocatalyst for artificial N2 fixation in acidic electrolytes under ambient conditions. In 0.1 M HCl, this catalyst achieved a high Faradaic efficiency of 4.5% with a NH3 yield of 78.4 μg h-1 mgcat.-1 at -0.3 V vs. a reversible hydrogen electrode, thus outperforming most reported NRR electrocatalysts under ambient conditions and some under harsh conditions. Density functional theory calculations revealed that the free energy barrier of the potential determining step of NRR on MoO2 decreases dramatically after nitrogenization.

MoO₃ nanosheets act as an efficient electrocatalyst for N₂ fixation to NH₃ with excellent selectivity at ambient conditions. In 0.1 M HCl, they show high activity with an NH₃ yield of 4.80 × 10⁻¹⁰ mol s⁻¹ cm⁻² (29.43 μg h⁻¹ mg_cat.⁻¹) and a faradaic efficiency of 1.9%.

Recent research suggests that biochar amendment is a promising approach to mitigate soil contamination via immobilizing heavy metals and organic pollutants. Through intensive literature review, this paper was aimed to better understand the processes, mechanisms, and effectiveness of biochar in immobilizing chemical contaminants in soil. The quality characteristics of biochar as a soil amendment varied greatly with the feedstock materials and the pyrolysis conditions. Biochar products from different sources demonstrated remarkably diversified capacities and efficiencies for stabilizing soil contaminants. Soil-incorporated biochar was able to stabilize Cd, Cu, Ni, Pb, and Zn and reduce their bioavailability through enhanced sorption (based on electrostatic attraction, ion exchange, and surface complexation) and chemical precipitation (incurred from soil pH elevation and ash addition of carbonates and phosphates). The stabilization efficacy was largely determined by cation exchange capacity, pH, and ash content of the biochar. Biochar amendment increased the mobility of anionic toxic elements [e.g., CrO 2- 4 , AsO - 3 , and Sb(OH) - 6 ] in soil. Soil-incorporated biochar was also able to adsorb non-polar organic compounds (through pore filling, partition, and hydrophobic effect) and polar organic compounds (via H-bonding, electrostatic attraction, specific interaction, and surface precipitation). The adsorption efficiency was controlled by the biochar surface properties specific surface area, microporosity, and hydrophobicity. Biochar may facilitate the mineralization of organic pollutants by enhancing soil microbial activities. The effectiveness of biochar-facilitated soil remediation was case specific, changing with the biochar source, amendment rate, placement, soil type, and pollutant species. More field studies are needed to evaluate the long-term effectiveness of biochar-facilitated soil remediation under practical circumstances.

Alkaline hydrogen evolution reaction (HER), consisting of Volmer and Heyrovsky/Tafel steps, requires extra energy for water dissociation, leading to more sluggish kinetics than acidic HER. Despite the advances in electrocatalysts, how to combine active sites to synergistically promote both steps and understand the underlying mechanism remain largely unexplored. Here, Density Functional Theory (DFT) calculations predict that NiO accelerates the Volmer step while metallic Ni facilitates the Heyrovsky/Tafel step. A facile strategy is thus developed to control Ni/NiO heterosurfaces in uniform and well-dispersed Ni-based nanocrystals, targeting both reaction steps synergistically. By systematically modulating the surface composition, we find that steering the elementary steps through tuning the Ni/NiO ratio can significantly enhance alkaline HER activity, and Ni/NiO nanocrystals with a Ni/NiO ratio of 23.7% deliver the best activity, outperforming other state-of-the-art analogues. The results suggest that integrating bicomponent active sites for elementary steps is effective for promoting alkaline HER, but they have to be balanced.

In this paper, we presented 10 similarity measures between Pythagorean fuzzy sets (PFSs) based on the cosine function by considering the degree of membership, degree of nonmembership and degree of hesitation in PFSs. Then, we applied these similarity measures and weighted similarity measures between PFSs to pattern recognition and medical diagnosis. Finally, two illustrative examples are given to demonstrate the efficiency of the similarity measures for pattern recognition and medical diagnosis.