Elimination Mechanism Research Articles

Mechanisms of macrozone elimination and grain refinement of near α Ti alloy via the spheroidization of the Widmannstätten structure

Regions with sharp local textures, i.e., macrozones, are common microstructural inhomogeneities in titanium (Ti) alloys that significantly reduce the fatigue resistance of Ti alloy parts. In this study, a two-stage thermomechanical operation was developed to eliminate macrozones and optimize microstructure in a near α Ti alloy. Multiscale microstructure characterization and full-field crystal plasticity (CP) modeling were conducted to uncover the underlying mechanisms. Spheroidizing through dynamic recrystallization (DRX) and superplasticity are indispensable ingredients. The alloy exhibited multiple DRX phenomena, which are strongly associated with grain morphologies. The discontinuous DRX and the main spheroidizing mechanism of the equiaxed primary α phase failed to eliminate macrozones but exacerbated microstructure heterogeneities due to the strong anisotropy of the hexagonal close-packed α phase. The Widmannstätten structure (WS), fabricated through the β heat treatment that generated abundant nano-defects and serrated grain boundaries, significantly promoted the occurrence of geometric dynamic recrystallization (GDRX). A complete GDRX of lamellar α grains can generate a sufficiently fine-grain structure to achieve superplastic deformation in the subsequent hot compression at a moderate deformation. The full-field CP simulations considering slip only versus slip + superplasticity confirmed that the dislocation slip dominated deformation aggravated deformation heterogeneity and the formation of macrozones. In contrast, the superplastic deformation suppressed the heterogeneous deformation and randomized the grain rotation, which in turn homogenized the microstructure and eliminated macrozones. Based on these observations, the β heat treatment followed by α hot compression is an effective method to achieve grain refinement and macrozone elimination of Ti alloys.

An Overview on Neonatal Jaundice

A significant proportion of term and preterm infants develop neonatal jaundice. Jaundice in a healthy term infant is the most common reason for readmission to hospital. Jaundice is caused by a significant increase in serum bilirubin levels, largely due to the breakdown of red blood cells. Bilirubin is transported in the blood as 'unconjugated' bilirubin, largely bound to albumin. The bilirubin is converted into a conjugated form by the liver, which is excreted in the bile. Very high levels of unconjugated bilirubin led to neurotoxicity. In most infants, severe hyperbilirubinemia is caused due to an increase in bilirubin production (e.g., due to haemolysis) and thus reducing bilirubin production is a rational approach for its management. The situation can become critical in infants with an associated impaired bilirubin elimination mechanism as a result of a genetic deficiency and polymorphism. The simplest way to reduce bilirubin levels is by phototherapy. Current management of jaundice in the UK is guided by the NICE guideline.1

Sensitivity analysis and noise reduction optimization design of the insert-pipe double expansion chamber muffler

The insert-pipe double expansion chamber muffler has less passbands and higher sound attenuation in the plane wave range, which is widely used to reduce noise of industrial equipment. But there are many parameters that affect the transmission loss of the insert-pipe double expansion chamber muffler, and the sensitivity of each factor is not clear. Identifying the most influential factor among numerous parameters is an important challenge. It is necessary to investigate the sensitivity of all parameters and study parameter optimization algorithms. Based on the method of transfer matrix analysis, this paper studies the insert-pipe double expansion chamber muffler and its sound elimination mechanism. The global sensitivity analysis of the transmission loss of insert-pipe double expansion chamber muffler was conducted using Sobol's method, and the influence of each parameter sensitivity was examined. According to the noise characteristics of an air conditioner compressor, the external penalty function method (EPFM) algorithm is used to optimize the insert-pipe double expansion chamber muffler, and the maximum transmission loss is obtained in a specific frequency band. According to the optimized parameters, the muffler is designed, manufactured, and installed in a pipeline system to carry out a noise experiment to verify the effectiveness of the optimization scheme.

A many-objective evolutionary algorithm with population preprocessing and projection distance-assisted elimination mechanism

Abstract Pareto dominance-based many-objective evolutionary algorithms (MaOEAs) face a significant challenge from many-objective problems (MaOPs). The selection pressure reduces as the number of objectives rises, while the non-dominated solution grows exponentially. Pareto dominance-based MaOEA increases the selection pressure by designing diversity-related environmental strategies. However, it still struggles to strike a good balance between population diversity and convergence. Moreover, the diversity-selection method increases the likelihood that dominance-resistant solutions (DRSs) will be chosen, which is detrimental to the performance of MaOEAs. To address the aforementioned problems, a many-objective optimization algorithm based on population preprocessing and projection distance-assisted elimination mechanism (PPEA) is proposed. In PPEA, first, the population preprocessing method is designed to lessen the negative impacts of DRSs. Second, to further improve the ability to balance population diversity and convergence of Pareto dominance-based MaOEAs, a projection distance-assisted elimination mechanism is proposed to remove the poorer individuals one by one until the population size satisfies the termination condition. The performance of PPEA was compared with seven excellent MaOEAs on a series of benchmark problems with 3–15 objectives and a real-world application problem. The experimental results indicate that PPEA is competitive and can effectively balance the diversity and convergence of the population when dealing with MaOPs.

Reactions of 2,4‐dinitrophenyl 5‐substituted‐2‐thiophenecarboxylate promoted by 4‐ZC6H4O−/4‐ZC6H4OH in 20 mol% DMSO(aq). Effects of leaving group and nucleophile on the acyl transfer reactions

AbstractThe kinetics of nucleophilic substitution reactions involving 2,4‐dinitrophenyl 5‐substituted‐2‐thiophenecarboxylate were studied kinetically with 4‐Z‐C6H4O−/4‐Z‐C6H4OH, which facilitated the reactions, in 20 mol% DMSO(aq). The reactions followed second‐order kinetics and exhibited βacyl = −2.34 to −2.92, ρ(Y) = 2.71–3.39, βnuc = 0.74–0.83, and |βlg| = 0.40–0.57. Based on the interpretation of the results, we have concluded that the reaction follows an addition–elimination mechanism in which the first step is the rate‐determining step (rds). The transition state structures for the 4‐ZC6H4O−‐promoted reactions remained nearly the same with a change in the leaving group from 4‐nitrophenoxide to 2,4‐dinitrophenoxide. The mechanism of the 4‐ZC6H4O−‐promoted reaction was similar to that of R2NH‐promoted reactions, except that the former proceeded with the 1st step being the rds and the latter proceeded with a change in the rds from the second to the first step with a stronger nucleophile.

Mathematical Modeling of Oncolytic Virus Therapy Reveals Role of the Immune Response.

Oncolytic adenoviruses (OAds) present a promising path for cancer treatment due to their selectivity in infecting and lysing tumor cells and their ability to stimulate the immune response. In this study, we use an ordinary differential equation (ODE) model of tumor growth inhibited by oncolytic virus activity to parameterize previous research on the effect of genetically re-engineered OAds in A549 lung cancer tumors in murine models. We find that the data are best fit by a model that accounts for an immune response, and that the immune response provides a mechanism for elimination of the tumor. We also find that parameter estimates for the most effective OAds share characteristics, most notably a high infection rate and low viral clearance rate, that might be potential reasons for these viruses' efficacy in delaying tumor growth. Further studies observing E1A and P19 recombined viruses in different tumor environments may further illuminate the extent of the effects of these genetic modifications.

Deep reinforcement learning assisted co-evolutionary differential evolution for constrained optimization

Solving constrained optimization problems (COPs) with evolutionary algorithms (EAs) is a popular research direction due to its potential and diverse applications. One of the key issues in solving COPs is the choice of constraint handling techniques (CHTs), as different CHTs can lead to different evolutionary directions. Combining EAs with deep reinforcement learning (DRL) is a promising and emerging approach for solving COPs. Although DRL can help solve the problem of pre-setting operators in EAs, neural networks need to obtain diverse training data within a limited number of evaluations in EAs. Based on the above considerations, this work proposes a DRL assisted co-evolutionary differential evolution, named CEDE-DRL, which can effectively use DRL to help EAs solve COPs. (1) This method incorporates co-evolution into the extraction of training data for the first time, ensuring the diversity of samples and improving the accuracy of the neural network model through information exchange between multiple populations. (2) Multiple CHTs are used for offspring selection to ensure the algorithm’s generality and flexibility. (3) DRL is used to evaluate the population state, taking into account feasibility, convergence, and diversity in the state setting and using the overall degree of improvement as a reward. The neural network selects suitable parent populations and corresponding archives for mutation. Finally, (4) to avoid premature convergence and local optima, an adaptive operator selection and individual archive elimination mechanism is added. Comparisons with state-of-the-art algorithms on benchmark functions CEC2010 and CEC2017 show that the proposed method performs competitively and produced robust solutions. The results of the application test set CEC2020 show that the proposed algorithm is also effective in real-world problems.

Solidification crack elimination in TIG welding of Al7075: Experimental investigation and modified RDG modelling

Although solidification crack susceptibility modelling has been a point of interest for many years in fusion welding of aluminum alloys, the underlying mechanism of solidification crack elimination is not yet fully understood. To contribute in closing this knowledge gap, the present study investigates and proposes a new modified Rappaz-Drezet-Gremaud (RDG) physical model in autogenous and heterogeneous TIG welding of Al7075 sheets. The core novelty of the new model is that it includes the shrinkage strain rate, which allows to better capture the effects of capillary pressure, coherency point, as well as final dendrite or grain size in the fusion zone. In agreement with the experimental results and previous models, the new model shows that the defining mechanism of eliminating solidification cracks in heterogeneous joints is the capacity of nanoparticles to initiate heterogeneous grain nucleation, altering the fusion zone grain morphology from dendritic to fine equiaxed, with only little impact of the resulting grain size. This leads to two main effects causing reduced solidification crack susceptibility: (1) a reduction in coherency point by about 15 % from 902 K to 879 K, which reduces strain accumulation on the coherent solid network; (2) a considerable increase in capillary pressure across the entire mushy zone, allowing to maintain the total pressure at void/liquid interfaces in the positive range, which prevents the growth of potentially formed voids between grains at any temperature during solidification. In contrast, dendrite widths below 68 μm are required to prevent solidification cracks in autogenous joints without TiC nanoparticles, indicating a greater role of grain refinement. Overall, the proposed model highlights the more determinant role of the temperature-dependent solidification shrinkage strain rate in solidification crack susceptibility as it is an order of magnitude greater compared to the temperature-independent thermal contraction strain rate that has been the main or sole focus of previous models.

A Novel Hybrid Firefly Algorithm with Double-Level Learning Strategy

The firefly algorithm (FA) is a swarm intelligence algorithm capable of solving global optimization problems exactly; it has been used to solve many practical problems. However, traditional firefly algorithms solve complex optimization problems with a simple update method, which leads to premature stagnation due to the limitation of firefly diversity. To overcome these drawbacks, a novel hybrid firefly algorithm (HFA-DLL) with a double-level learning strategy is proposed. In HFA-DLL, a double-level learning strategy is proposed to avoid premature convergence and enhance the algorithm’s global search capability. At the same time, a competitive elimination mechanism is introduced to increase the accuracy of solving complex optimization problems and improve the convergence rate of the algorithm. Moreover, a stochastic disturbance strategy is designed to help the best solution jump out of the local optimum and minimize the time cost in the wrong direction. To understand the advantages and disadvantages of HFA-DLL, experiments were conducted on the CEC 2017 benchmark suite. Experimental results show that HFA-DLL outperforms other state-of-art algorithms in terms of convergence rate and exploration efficiency.

Void content of polypropylene/carbon fiber wet‐laid nonwoven composites: Effect of fiber content and molding conditions, and void elimination mechanism

AbstractVarious wet‐laid nonwoven composites have been well‐developed in recent decades. However, studies that systematically investigate the factors affecting the void content of wet‐laid nonwoven composites are still missing. This paper aims to study the factors affecting the void content of wet‐laid nonwoven composites and propose a mechanism for void elimination in wet‐laid nonwoven composites. Polypropylene (PP) and carbon fiber (CF) were chosen to manufacture PP/CF wet‐laid nonwoven composites. An orthogonal experimental design found that the CF content and molding pressure can dominate the void content while molding temperature and time have non‐significant effects. Subsequently, this paper proposed that the void elimination mechanism is the compression of the impregnated CF network and the trapped air (compression mechanism) instead of the matrix's infiltration to the dry CF network (infiltration mechanism). In order to validate the compression mechanism, we developed an analytical model for predicting the void content of the PP/CF wet‐laid nonwoven composites. Good agreement between the predicted and the experimental void content suggests that void elimination follows the compression mechanism.Highlights An orthogonal experimental design reveals that the CF content and molding pressure can dominate the void content of the PP/CF wet‐laid nonwoven composite, while molding temperature and time have non‐significant effects. A mechanism (i.e., compression mechanism) is proposed to explain the effect of CF content and molding conditions on the void content of the PP/CF wet‐laid nonwoven composite. Good agreement between the experimental and the predicted void content validates the compression mechanism.

Synthesis, structure characterization, DFT calculations, and computational anticancer activity investigations of 1-phenyl ethanol derivatives

1-Phenyl ethanol derivatives are well-known classes of drug molecules that play an important role as effective substitute analogs to anticancer and antiviral agents. In this work, phenylacetylene was selected as a simple alkyne in the presence of iron (II) phthalocyanine with NaBH4 as a catalyst. This reaction has been proven that it is a significantly efficient catalyzed conversion of terminal and internal alkynes to 1-phenyl ethanol derivatives as secondary alcohols followed by the addition and elimination mechanism. However, such drug design by compiling the redox reaction and its sequence essentially requires exact stoichiometry of iron phthalocyanine to alkynes. The products were characterized using flash column chromatography with an eluent ratio of PE: EA (5: 1 / V: V), gas chromatography, 1H, and 13C NMR spectroscopy. The potential of the synthesized compounds to bind to protein kinase B was investigated through molecular docking to dig out their probable anticancer activity. Compound 7 (1-(4-bromophenyl) ethan-1-ol) exhibited the highest binding potential. However, the binding potential of all the compounds was less than the standard parent compound. In addition, the density functional theory (DFT) studies of the compounds were also applied which revealed that compound 1 might have the highest chemical stability.

Diazotization-coupling reaction on aluminum-based metal–organic framework for efficient purification of wastewater from carbofuran pesticide

A crucial issue is the development of highly and selectively absorbable pesticides. At room temperature, aluminum-based metal–organic frameworks (MIL-53-NH2, MIL-53-AZA, MIL-53-AZA-La, and MIL-53-AZA-Ce) were successfully formed. Using prepared MOFs as sorbents, carbofuran was adsorbed from wastewater. Experimental and spectroscopic studies were used to investigate the elimination mechanisms. The current process can connect a mixture of pi- pi stacking contact, coordination bonding, and hydrogen bond production. The adsorption of carbofuran from wastewater was best described by pseudo-second-order kinetics and Langmuir isothermal models. MIL-53-NH2, MIL-53-AZA, MIL-53-AZA-La, and MIL-53-AZA-Ce had elimination capacities of 367.87, 433.50, 610.23, and 635.05 mg g-1, respectively. The synthesized MOFs are represented as promising materials for the removal of carbofuran.

Eliminating the oxygen inhibition in the redox free radical polymerization of alicyclic polyurethane acrylate coatings: A study of the beneficial effect of paraffin wax

Elimination of oxygen inhibition is still a challenge in the preparation of copolymers for steel bridge deck coatings industry by redox free radical polymerization (RFRP) technique in air and at room temperature. Herein, solvent-free paraffin wax composite alicyclic polyurethane acrylate (PW/APUA) coatings cured in air and at room temperature were developed by RFRP technique, and the efficacy and mechanism of oxygen inhibition elimination by paraffin wax during curing was investigated. The results of tensile, contact angle (CA) and water absorption (WA) tests showed that compared with pure APUA coating, the PW/APUA coatings exhibited superior mechanical properties and water resistance at room temperature, with tensile strength, elongation at break and CA up to 25.1 MPa, 204.23 % and 112.5°, respectively, and WA down to 0.008 %. Thermogravimetric analysis (TGA) suggested that the thermal initial decomposition of the coating increased from 180 °C to 200 °C after incorporation of paraffin wax. Differential scanning calorimetry (DSC) and dynamic mechanical thermal analysis (DMTA) indicated that two glass transition temperatures of PW/APUA coating with 0.3 % paraffin wax were −88.4 °C and 92.6 °C, respectively. Moreover, microstructural characterization of PW/APUA coatings revealed that paraffin wax eliminated oxygen inhibition by forming a dense barrier layer on the air contact surface of the APUA coating. Furthermore, the paraffin wax molecules co-crystallized with the non-polar groups of acrylates, but did not form new chemical bonds. This study provides a distinct and general strategy for eliminating oxygen inhibition of RFRP technology in air.

Comprehensive hydraulic performance improvement in a pump-turbine: An experimental investigation

Pumped storage power plants, which is known as only large-scale energy management equipment, plays a vital important role in energy field. Hump characteristic and S characteristic are two classical unsteady hydraulic characteristics when pump-turbine operating at turbine mode and pump mode, respectively. It has been found that these two characteristics are both strongly related to the complex vortex evolution process in vaneless region while only few papers focus on the elimination mechanism of them. In present paper, a scaled runner with optimized high-pressure side (HPS) is designed and manufactured based on multi-objective optimization process arming at eliminating unsteady characteristic, i.e. hump characteristic and S characteristic, while maintaining efficiency characteristic unchanged. Thereafter, hydraulic experiments are conducted to investigate the impact of HPS geometry on hydraulic performance (efficiency, hump margin, S margin and pressure fluctuation) of object pump turbine. The experimental results show that compared with the original runner, the weighted average efficiency for pump mode increases by 0.1% while the weighted average efficiency for turbine mode decreases by 0.1%. Moreover, the S margin increases from 76.7 m to 87.2 m and the S2 unsteady region is largely increased. The hump margin decreases a little while it can recover to the original level through increasing 0.6% of the original ratio scale. Moreover, the runner with optimized HPS can effectively reduce the pressure fluctuation amplitude in vaneless region up to 33.3% and 21.4% for turbine mode and pump mode, respectively.

DFT investigations on the mechanisms and kinetics for the DMS + O3 reaction

AbstractThe potential energy surface (PES) for the reaction of ozone with dimethyl sulfide (DMS) was calculated at the CCSD(T)/6‐311++G(3df,2pd)//M06‐2X/6‐311++G(d,p) levels of theory. Result shows that on the singlet PES the addition–elimination mechanism is dominant, and H‐abstraction mechanism is less competitive. The major channel starts from the addition of ozone and DMS leading to a weak intermediate IM1, which decomposes subsequently to DMSO and 1O2 via a barrier around 38.8 kJ/mol. With a barrier of 64.0 kJ/mol, the formation of HO3 + CH3SCH2 via H‐abstraction mechanism is subdominant. Besides, DMSO + 1O2 can take place further reactions to produce several products. The substitution mechanism was located on the triplet PES, however, with a rather high barrier it is negligible. Furthermore, the rate constants for the two channels leading to DMSO + 1O2 and HO3 + CH3SCH2 were calculated from 200 to 1000 K. The total rate constant is 1.13 × 10‐20 cm3·molecule‐1·s‐1 at 298 K and 1 atm, in good agreement with previous experimental data. The overall rate constants are positive temperature dependent in the whole temperature range.

STOCHASTIC DYNAMICS BETWEEN THE IMMUNE SYSTEM AND CANCER CELLS WITH ALLEE EFFECT AND IMMUNOTHERAPY

In this work, we use continuous-time Markov jump processes and the corresponding zero fluctuation ordinary differential equations to analyze the relation between immune response and cancerous cells. We incorporate the Allee effect into our model to show that intrinsic stochasticity and nonlinearity may interact in elimination, equilibrium, and escape mechanisms in the low-count regime. Later, we consider the effect of immunotherapy through a pulse injection term and the Tau-Leaping algorithm. We show using the model state variables and parameters that the cancer cell population at its threshold level gets into the elimination phase for high antigenicity values.

Bacillus thuringiensis EM-A1: A novel bacterium for high concentration of ammonium elimination with low nitrite accumulation

The biological elimination of high concentration of ammonium from wastewater has attracted increasing attention in recent years. However, few studies on the efficient elimination of high concentration of ammonium by a single bacterium have been reported. Here, the efficient elimination of NH4+-N (>99%) and total nitrogen (TN) (>77%) were attained by Bacillus thuringiensis EM-A1 under 150 rpm at pH 7.2 with sodium succinate and a carbon/nitrogen ratio of 15 at 30 °C with an inoculum size (as measured by absorbance at 600 nm) of 0.2. Strain EM-A1 effectively eliminated 100 mg/L of inorganic nitrogen with maximal NH4+-N, NO3−-N, and NO2−-N elimination rates of 4.88, 2.57, and 3.06 mg/L/h, respectively. The elimination efficiencies of NH4+-N were 99.87% and 97.13% at initial concentrations of 500 and 1000 mg/L, respectively. Only 0.91 mg/L of NO2−-N was accumulated with the elimination of 1000 mg/L NH4+-N. A concentration of 5 mg/L exogenous hydroxylamine was toxic and further inhibited heterotrophic nitrification and aerobic denitrification (HN-AD). The NH4+-N and NO2−-N elimination capacities of strain EM-A1 were specifically inhibited by 2-Octyne (OCT) over 4 μmol/L and diethyldithiocarbamate (DDC) over 0.5 mmol/L, respectively. Above 25 mg/L procyanidin (PCY) inhibited the bioconversion of NO3−-N and NO2−-N. The results demonstrated that strain EM-A1 had HN-AD capacity under halophilic conditions, and has great potential for use in the treatment of nitrogen pollution wastewater; this study also provides new insights into this strain's nitrogen elimination mechanism, helping advance environmental biotechnology.

Great Wall Construction Algorithm: A novel meta-heuristic algorithm for engineer problems

In recent years, the optimization community has witnessed a surge in the popularity of population-based optimization methods. However, many of these methods suffer from various shortcomings, including unclear performance characteristics, incomplete validation, excessive reliance on metaphors, inadequate exploration and exploitation components, and compromised trade-offs between exploration and exploitation in real-world scenarios. As a result, users often find themselves needing to extensively modify and fine-tune these methods to achieve faster convergence, stable balance, and high-quality results. To shift the optimization community’s focus towards performance rather than metaphorical changes, we propose a general population-based optimization technique called the Great Wall Construction Algorithm (GWCA). This study presents GWCA as a simple yet robust method with competitive performance for efficiently solving constrained and unconstrained problems. GWCA draws inspiration from the competition and elimination mechanisms observed among workers during the construction of the ancient Great Wall. It introduces a mathematical model of the labor movement to simulate the algorithm’s dynamics. Unlike other methods that employ multiple models to generate new solutions, GWCA randomly assigns a single predefined motion model to each worker in every iteration. This unique approach showcases GWCA’s dynamic nature, simple structure, high convergence performance, and ability to deliver satisfactory solution quality, thus outperforming existing optimization methods in terms of efficiency. To validate GWCA, we conduct extensive comparisons with popular and advanced algorithms on the IEEE CEC 2017 benchmark suite across different dimensions (D = 10, 30, 50, 100). Additionally, GWCA is applied to solve 16 constrained engineering problems and 6 NP-Hard problems, demonstrating its applicability in handling constrained and complex nonlinear problems. Finally, we compare GWCA’s optimized solutions with those obtained from 33 advanced meta-heuristic algorithms, including the winner of CEC 2017. The results confirm the effectiveness of the proposed optimizer in solving a wide range of single-objective problems, surpassing popular base optimizers, advanced variants of existing methods, and several CEC winners. We present GWCA as an open-source population-based method that can serve as a standard optimization tool across various domains of artificial intelligence and machine learning. It exhibits a range of exploratory and exploitative features, offering high performance and optimization capabilities. The method is highly flexible, scalable, and can be further extended in terms of structure and application to accommodate diverse forms of optimization scenarios. https://github.com/guangian/Great-Wall-Construction-Algorithm-a-novel-meta-heuristic-algorithm-for-global-optimization.

Novel anthraquinone photosensitizers: Synthesis, photoactivity, and 3D-QSAR studies

In this study, three-dimensional quantitative conformational relationship (3D-QSAR) analysis was conducted on 38 known anthraquinone derivatives. Additionally, five pH-responsive anthraquinone photosensitizers (A1 to A5) were designed and synthesized through addition, elimination, and substitution mechanisms using the anthraquinone derivative chrysophanol as the raw material. The structures of the products were characterized using 1HNMR, 13CNMR , LCMS, and the UV–Vis absorption spectra and fluorescent spectra at different pH values were obtained. To investigate the photodynamic antibacterial activity of the compounds, their inhibitory activities against Pseudomonas aeruginosa and Staphylococcus aureus were tested in vitro under different light and pH conditions. The results showed that the compounds exhibited good photodynamic antibacterial activity and selectivity in light and weak acid environments. MTT experiments were conducted to evaluate the cytotoxicity of the compounds on the human cancer cell line HeLa. It was found that the phototoxicity and dark toxicity effects of compound A3 at concentrations of 0.625 μM and lower were similar to those of the reference photosensitizer Chlorin e6 (Ce6). However, the amount of singlet oxygen produced by A3 was approximately 7.6 times that produced by Ce6, indicating its potential for application in the photodynamic therapy of tumours and providing a reference for research on anthraquinone photosensitizers.

Effect of hydrazyl radical on the selectivity of γ-alumina with different sizes of pores for dehydration of 2-octanol through radical elimination mechanism

Effect of hydrazyl radical on the selectivity of γ-alumina with different sizes of pores for dehydration of 2-octanol through radical elimination mechanism