Experimental Parameters Research Articles

MOF-derived porous carbon microspheres Ni@C-acid as solid-phase microextraction coating for extraction of polycyclic aromatic hydrocarbons from tea infusions

The improvement of the stability and adsorption properties of materials on targets in sample pre-treatment has long been an objective. Extensive efforts have been made to achieve this goal. In this work, metal-organic framework Ni-MOF precursors were first synthesized by solvothermal method using polyvinylpyrrolidone (PVP) as an ideal templating agent, stabiliser and nanoparticle dispersant. After carbonization and acid washing, the nanoporous carbon microspheres material (Ni@C-acid) was obtained. Compared with the material without acid treatment (Ni@C), the specific surface area, pore volume, adsorption performance of Ni@C-acid were increased. Thanks to its excellent characteristics (high stability, abundant benzene rings), Ni@C-acid was used as fiber coatings in headspace solid-phase microextraction (HS-SPME) technology for extraction and preconcentration of polycyclic aromatic hydrocarbons (PAHs) prior to gas chromatography-flame ionization detector (GC-FID) analysis. The experimental parameters of extraction temperature, extraction time, agitation speed, desorption temperature, desorption time and sodium chloride (NaCl) concentration were studied. Under optimal experimental conditions, the wide linear range (0.01-30 ng mL−1), the good correlation coefficient (0.9916-0.9984), the low detection limit (0.003-0.011 ng mL−1), and the high enrichment factor (5273-13793) were obtained. The established method was successfully used for the detection of trace PAHs in actual tea infusions samples and satisfied recoveries ranging from 80.94-118.62 % were achieved. The present work provides a simple method for the preparation of highly stable and adsorbable porous carbon microsphere materials with potential applications in the extraction of environmental pollutants.

Photocatalytic degradation of linezolid antibiotic from aqueous solution by magnetically separable nanoheterostructure Fe3O4/ MgAl2O4/BiOBr0.5Cl0.5 synthesized Composite catalyst

The photocatalytic system has been emerging as a practical method for antibiotic removal in an aqueous medium. In this study, novel MgAl2O4/BiOBr0.5Cl0.5 heterojunction was synthesized by the decoration of different mass percentages of MgAl2O4 nanoparticles (10, 20, and 30 %) on the BiOBr0.5Cl0.5 solid solution and used for the photocatalytic degradation of linezolid antibiotic. Also, to facilitate easy separation of 10 % MgAl2O4/BiOBr0.5Cl0.5 from the solution after use, it was magnetized by Fe3O4 as 2 % Fe3O4/10 % MgAl2O4/BiOBr0.5Cl0.5. Synthesized photocatalysts were characterized by XRD, XPS, Raman, FESEM, TEM, EDX, BET-BJH, DRS, PL, Mott–Schottky, VSM, and pHpzc analyses to specify the synthesized photocatalysts and determine their chemical and physical properties. In addition, the influence of experimental parameters, including pH of the initial solution, the dosage of photocatalyst, and linezolid concentration on the performance of photocatalyst in linezolid removal, were elucidated in this study. The results showed that 10 % MgAl2O4/BiOBr0.5Cl0.5 photocatalyst was the optimal sample with a maximum removal efficiency of 95.59 % within 90 min under optimal experimental parameters (1 g/L catalyst, 10 mg/L linezolid, pH = 6.5). The kinetic studies revealed that the degradation rate of 10 % MgAl2O4/BiOBr0.5Cl0.5 photocatalyst was approximately 1.8, 2.7, 2.0, and 6.3 times faster than 20 % MgAl2O4/BiOBr0.5Cl0.5, 30 % MgAl2O4/BiOBr0.5Cl0.5, BiOBr0.5Cl0.5 photocatalyst and photolysis, respectively. Scavenger tests conducted in the same process operation revealed that h+ and •O2− play the predominant roles in linezolid photocatalytic degradation. The 2 % Fe3O4/10 % MgAl2O4/BiOBr0.5Cl0.5 photocatalyst was easily collected by magnet after each use for the next run, and its activity after five runs has reached 90 %.

Self-healing properties of mortar with crystalline admixture: experimental investigation and parameter optimization

The inclusion of crystalline admixture (CA) is a highly effective method for enhancing the self-healing properties of mortar. This study examined the complexing abilities of different complexing agents under varying temperatures, pH levels, and ion species in order to select effective complexing agents for diverse environments, as complexing agents play a crucial role in CAs. After determining the type of complexing agent, an orthogonal array design was used to optimize the components of CA, and the strengthening mechanism of CA for mortar was discussed through microstructure analysis. The results showed that the complexation behavior of triethanolamine (TEA) and glycine performed better than sodium citrate for different pH levels, temperatures, and ion species. Meanwhile, TEA and glycine showed complementarity at different stages, so TEA and glycine were used as complexing agents in this study. Based on the orthogonal experiment, the optimal contents of Na2SiO3, Na2CO3, TEA, glycine, Ca(COOH)2, and nano-SiO2 in CA were determined to be 1.0%, 1.0%, 0.04%, 1.0%, 0.5%, and 1.0%, respectively. Under the synergistic effect of TEA and glycine, the hydration of aluminate and ferrialuminate was accelerated, and the hydration degree of cement paste was increased. At 28 d, the contents of CaCO3, calcium-silicate-hydrate (C-S-H) gel, and ettringite of cement paste with CA were higher than these of plain paste, but its Ca(OH)2 content was lower. Although the Ca(OH)2 content in the cement paste with CA was lower, the Ca(OH)2 crystal structure filled in the pores was larger. Therefore, the mortar mixed with CA exhibited higher compressive strength, water impermeability, and self-healing ability.

Iron as recyclable metal fuel: Unraveling oxidation behavior and cyclization effects through thermogravimetric analysis, wide-angle X-ray scattering and Mössbauer spectroscopy.

The carbon-free chemical storage and release of renewable energy is an important task to drastically reduce CO2 emissions. The high specific energy density of iron and its recyclability makes it a promising storage material. Energy release by oxidation with air can be realized by the combustion of micron-sized iron powders in retro-fitted coal fired power plants and in fixed-bed reactors under milder conditions. An experimental parameter study of iron powder oxidation with air was conducted based on thermogravimetric analysis in combination with wide-angle X-ray scattering and Mössbauer spectroscopy. In agreement with literature the oxidation was found to consist of a very fast initial oxidation of the outer particle layer followed by much slower oxidation due to diffusion of iron ions through the Fe2O3/Fe3O4 layer being the ratelimiting step. Scanning electron microscopy analysis of the iron particle before and after oxidation reveal a strong particle morphology transformation. This impact on the reaction was studied by cyclization experiments. Up to 10 oxidation-reduction cycles show that both, oxidation and reduction rates, increase strongly with cycling due to increased porosity.

Development of an Experimentally Validated Computational Fluid Dynamics Model for a PBI Membrane-Based Anhydrous HCl Electrolyzer

Abstract We report the development of an experimentally-validated computational fluid dynamics (CFD) model for simulation of an anhydrous HCl electrolyzer. The experimental data from 3 membrane variants was used to provide kinetic and membrane parameters for the model. The model not only accurately simulates overall electrolyzer performance, but it also provides key insights into the transport phenomena within the electrolyzer. The model allows simulation of experimental parameters like high HCl flowrates and increased cell pressure that pose a high safety risk to researchers. The model shows hotspots in the temperature distribution that will need to be addressed by flow field modification when scaling up the electrolysis process. The increasing of cell pressure reduces the gradient of current distribution throughout the electrolyzer and lowers the cell voltage required for a given current density. Increasing electrolyzer temperature reduces cell voltage by decreasing losses due to kinetic overpotential and ohmic overpotential. The implications of the simulated results are discussed, including potential limitations in our experiments and how the model can be used effectively when considering important steps like industry scale-up.

Selective Initiation of Corrosion Pits in Stainless Steel Using Scanning Electrochemical Cell Microscopy.

Scanning electrochemical cell microscopy is a useful technique for determining variations in corrosion behavior across a surface. However, the numerous options for experimental parameters and little understanding of their effect on the corroding system render comparisons of results between studies difficult. Herein, we explore changes in corrosion behavior of two martensitic stainless steels, a cast CA6NM and a wrought S41500, as a result of the chosen experimental parameters, including scan rate, approach potential, surface oil immersion, and tip aperture diameter. The study demonstrates that these experimental parameters can be controlled to probe oxide passivation kinetics and single pitting events by changing the surface state and cathodic currents. We measured the pitting and repassivation kinetics of a single pit and determined the compositional change of the Al2O3 inclusion site initiation point. Hundreds of data points were measured within 17 h of experimental time on the stainless steel samples, allowing statistical averages of corrosion and pitting values. This work will open new avenues for fine-tuning various corrosion aspects at the microscale, thereby contributing to a deeper understanding of the corrosion processes and mechanisms of diverse materials.

Comparative Assessment of ESI‐MS Softness for Inorganic Complexes: How Soft is Your ESI‐MS?

Electrospray ionization mass spectrometry (ESI‐MS) is a powerful tool for identifying and characterizing organometallic and coordination compounds. However, detection of fragile structures bound by weaker intermolecular forces can be significantly limited in ESI‐MS owing to the use of relatively harsh instrument conditions and configurations. In this study, a set of tests was developed to assess the softness of ESI‐MS systems. Two variants are presented: positive ion mode, utilizing a mixture of sodium ions and triphenylphosphine oxide producing [Na(OPPh3)n]+ ions (n = 1–4), and negative ion mode, utilizing Pd(PPh3)4 and sulfonated triphenylphosphine producing [Pd(L)(PPh3)n]– ions (n = 0–2), where softer instrument conditions preserve a higher proportion of the high‐coordinate ions and harsher conditions will result in increased detection of products of ion fragmentation. The results revealed notable variations in instrument softness, which were influenced by a combination of instrument design and experimental parameters. Meticulously optimizing experimental conditions and ESI‐MS parameters is essential to achieving the softest ionization possible, ensuring reliable analysis where applicable. This study offers valuable insight through straightforward tests that can be employed to assess the suitability of an instrument for specific research needs.

Tsunami Debris Damming Drag Forces And Associated Coefficients On Elevated Coastal Structure Columns

Tsunami overland flow induces hydrodynamic loads on coastal structures and may transport various objects located within the inundation zone, which could become debris and exacerbate hydrodynamic loading. In the process of adopting “the first national, consensus-based standard for tsunami resilience” (Chock, 2016) in the form of ASCE 7-16 Chapter 6: Tsunami Loads and Effects, emphasis was placed on evaluating debris transport and impact forces. This is evidenced by the robust body of literature regarding physical model experiments of these processes and thorough design procedures for both load considerations in current structural engineering standards (ASCE, 2022). Debris damming forces, resultant of debris being transported and accumulating against structures, are less thoroughly studied, having only recently begun to transition from steady flow experiments to transient flow conditions representative of coastal inundation events. A recent pair of experiments bridges this gap, comparing debris damming via steady-state, subcritical flow conditions to that caused by a dam-break style hydraulic bore (Stolle et al., 2018). That paper aimed to study debris dam formation, stability, and loading as well as runup of the flow onto idealized structural columns. Another study varied debris quantity, orientation, and arrangement to determine the effect had on damming and impact loads (Shekhar et al., 2020), however neither compared findings to current standards. The experimental work presented herein represents initial findings of a multi-year experimental campaign to better understand the mechanisms that lead to debris damming and increased structural loading. This work builds upon previous studies by using larger scale debris elements, more numerous debris fields, and more trials to better model such a stochastic process as debris damming. Three different incident wave conditions also led to varied hydrodynamics at the column specimen. In later phases, this campaign will also investigate the debris damming consequences of heterogeneous debris, which more accurately represent highly variable debris fields observed in post-event site surveys (Nistor et al., 2017). This paper aims to compare experimental debris dam loading parameters to those in the current ASCE 7-22 standard (ASCE, 2022). Namely, evaluating conservatism of ASCE 7-22 design values for: overall drag force on buildings, minimum closure ratios used in load determination, and empirical rectilinear structure drag coefficients during both debris accumulation and quasi-steady debris damming phases.

Optimization of biomass durian peel as a heterogeneous catalyst in biodiesel production using microwave irradiation

Abstract The present study investigated biodiesel production from the transesterification of palm oil with methanol using calcined biomass durian peel (BDP) as a heterogeneous catalyst assisted by microwave irradiation. Characterization of the calcined BDP showed that K2O is the main compound with a concentration of 86.15 wt%. The effect of three independent variables of catalyst weight (3–12 wt%), reaction time (1–10 min), and power of microwave (180–900 W) was used to determine the optimum condition on biodiesel production using the response surface method-based on the Box–Behnken design experiment. The optimum biodiesel conversion of 97.3% was achieved under experimental parameters of catalyst concentration of 12 wt%, reaction time of 9 min, and microwave power of 180 W. The catalyst concentration and reaction time have significant effects on biodiesel conversion.

Dimensional Analysis based Prediction Model for Fuel Consumption in the Deutz Agrotrac Tractor

Background: Fuel consumption is a critical factor in the performance of an agricultural tractor. And it can be affected by numerous parameters. Farming practices is an essential aspect that affects the cost of operation and the overall efficiency of the tractor. Predictions of fuel consumption rates in tractors and the energy consumption parameters of primary tillage equipment under local conditions are therefore essential selection criteria in purchasing decisions. Methods: A prediction model for fuel usage during tillage operations was created using dimensional analysis. The model was established by incorporating experimental findings into an equation. The experiment was conducted in the El Ouracia region of Setif, Algeria in 2022/2023 crop season, with fuel usage per time unit determined through topping-up the tank method. The fuel experiment parameters were measured according to their respective standard procedures. Result: By simulating fuel usage with tillage depth, tillage width, travel speed, soil bulk density and cone index. The constant in the prediction model was obtained. This developed model has the potential to forecast the tractor fuel consumption during tillage operation.

Extraction and recovery of zinc from spent pickling solution: Experimental design and mechanism analysis

Solvent extraction of zinc with N, N-di(1-methylheptyl) acetamide (N503) from hot-dip galvanizing spent pickling solution is studied. The interaction between N503 concentration, extraction time, and phase ratio (O/A) is investigated using response surface methodology (RSM), and the experimental parameters are optimized as follows: the concentration of N503 is 50 % (v/v), the extraction time is 12 min, and the O/A is 16:5. The extraction efficiency of zinc is 82.12 %, and the separation coefficient (βZn/Fe) is 278.92 under the condition of single stage extraction. After four stages of countercurrent extraction, zinc is almost completely extracted from the aqueous phase. Additionally, it is found that zinc can be stripped effectively under the conditions of 0.4 mol/L HCl, stripping time of 10 min and O/A of 4:1. Also, the extraction mechanism of N503 is determined by electrostatic potential, FT-IR, and 1H NMR spectroscopy, and the extraction complex is [CH3CONR2H]ZnCl3. In summary, a method for separating zinc from spent pickling solution has been developed, and it has a certain industrial application prospect.

Low frequency signal detection via correlated Ramsey measurements

The low frequency region of the spectrum is a challenging regime for quantum probes. We support the idea that, in this regime, performing Ramsey measurements carefully controlling the time at which each measurement is initiated is an excellent signal detection strategy. We use the Fisher information to demonstrate a high quality performance in the low frequency regime, compared to more elaborated measurement sequences, and to optimise the correlated Ramsey sequence according to any given experimental parameters, showing that correlated Ramsey rivals with state-of-the-art protocols, and can even outperform commonly employed sequences such as dynamical decoupling in the detection of low frequency signals. Contrary to typical quantum detection protocols for oscillating signals, which require adjusting the time separation between pulses to match the half period of the target signal, and consequently see their scope limited to signals whose period is shorter than the characteristic decoherence time of the probe, or to those protocols whose target is primarily static signals, the time-tagged correlated Ramsey sequence simultaneously tracks the amplitude and the phase information of the target signal, regardless of its frequency, which crucially permits correlating measurements in post-processing, leading to efficient spectral reconstruction.

Enhanced Photodegradation of Methylene Blue Using Reusable Cobalt Ferrite Nanocomposites

Growing industrialization is contributing to the worsening shortage of potable water in society. Consequently, wastewater treatment and dye degradation become the foremost aim to overcome this problem. Magnetic nanoparticles (MNPs) emerged as an efficient tool to overcome the problem of wastewater treatment. Easy recovery of the MNPs reduces the operational cost of the reaction. Therefore, in the current study simple, cheap, green, and highly proficient synthesis methodology for the magnetically recoverable cobalt ferrite is reported. The X-ray diffraction spectroscopy (XRD) and Fourier transform infrared spectroscopy (FTIR) confirm the crystalline structure and functional group on the synthesized nanoparticles. The elemental composition, surface morphology, and surface area were investigated by Energy-dispersive X-ray spectroscopy (EDS), Field emission scanning electron microscopy (FESEM), and Brunauer-Emmett-Teller (BET) analysis. The Photo-Fenton process was used to check the catalytic activity of the prepared CoFe2O4 nanoparticles (NPs). The effect of the various experimental parameters like pH (3–9), catalyst dosage (50–200 mg/L), H2O2 dosage (5–20 mM), and varied dye (methylene blue) concentration (0.05–0.2 mM) on catalytic performance were studied. According to this investigation, 90% degradation of the methylene blue was achieved in just 90 minutes using the assynthesized catalyst. The catalyst showed 76.91% of the dye degradation even after 4 consecutive cycles; it suggests the admirable stability of the catalyst during the reaction. The robustness of the CoFe2O4 NPs makes it potential candidate for the waste water treatment.

Phosphorus-Nitrogen compounds part 74. Syntheses of (p-dimethylamino)benzyl-spiro-(N/N)-cyclotriphosphazenes: Structural characterizations, bioactivity studies, DFT calculations and reactivity parameters

Reactions of hexachlorocyclotriphosphazene (HCCP, N3P3Cl6), with equimolar amounts of N-methyl-N'-(p-dimethylaminobenzyl)-1,2-diaminoethane (1), N-ethyl-N'-(p-dimethyl-aminobenzyl)-1,2-diaminoethane (2), and N-methyl-N'-(p-dimethylaminobenzyl)-1,3-diami-nopropane (3) produced the corresponding tetrachloro-(p-dimethylaminobenzyl)spiro-(N/N)-cyclotriphosphazenes (4, 5, and 6), regioselectively. Tetrapyrrolidino (4a-6a), tetrapiperidino (4b-6b), tetramorpholinophosphazenes (4c and 6c), dichlorodimorpholinophosphazene (5c) and tetra-1,4-dioxa-8-azaspiro[4,5]decanophosphazenes (DASD) (4d-6d) were synthesized from Cl-substitution reactions of 4, 5 and 6 with excess pyrrolidine, piperidine, morpholine, and DASD, respectively. Their structures were elucidated by MS, FTIR, NMR and single crystal X-ray diffraction (for 4, 4b and 6a) techniques. Hirshfeld surface (HS) analyzes of 4, 4b, and 6a were performed to visualize intermolecular interactions in the crystals. In addition, according to the antimicrobial activity test results, compound 6b shows a better inhibitory effect on S. aureus ATCC 25923 G(+) (MİC: 78.1 µM) and C. tropicalis Y-12968 (MİC: 19.54 µM) microorganisms. The interactions of cyclotriphosphazenes with 5′-G/GATCC-3′ and 5′-A/AGCTT-3′ sequences of DNA were evaluated by examining BamHI and HindIII restriction enzyme digestion. The quantum chemical calculations of 4, 4b, and 6a were performed using DFT, and their experimental parameters were compared with the theoretical ones. Natural bond orbitals (NBOs) were determined and HOMO-LUMO energy gaps (Eg) were calculated as 3.55, 5.23, and 5.24 eV for 4, 4b, and 6a, respectively.

Study on temperature and hardness behaviors of Al-6060 alloy during magnetic abrasive finishing process using artificial neural networks

Magnetic Abrasive Finishing (MAF) revolutionizes surface finishing by utilizing magnetic fields to apply pressure, ensuring exceptionally high-quality surfaces. Its potential for ultra-precise finishing with fine magnetic abrasives is particularly noteworthy. This study analyzes subsurface temperature dynamics during the MAF process on Al-6060, recognizing temperature's pivotal role in shaping surface texture and mechanical-chemical properties. Unbonded magnetic abrasives containing SiC were used without lubrication or coolants in experimentation. Experimental parameters, including machining gap, abrasive weight, voltage, and rotational speed, were systematically varied using a Box-Behnken Design of Experiments. An artificial neural network facilitated comprehensive data modeling, enabling a detailed parametric study. Post-processing surface characterization provided crucial insights into the impact of surface temperature rise on surface finish and hardness. This holistic approach enhances understanding of temperature's influence on MAF efficacy and its outcomes on Al-6060 surfaces. Experimental findings demonstrate MAF's effectiveness in achieving low-temperature finishing of Al-6060, with a maximum surface temperature of 36ºC. ANOVA analysis quantitatively determined that voltage has greatest influence (55.56%), followed by abrasive weight (20.00%) and machining gap (13.89%), with rotational speed having the least impact (2.22%). Qualitatively, the developed ANN model accurately predicted changes in surface roughness (ΔRa), temperature (ΔT), and hardness (ΔH), with maximum errors of 4.107%, 5.588%, and 6.680%, respectively. XRD analysis provided quantitative evidence of SiC diffusion into the surface, resulting in a hardness increase from 2.7 HV to 5.6 HV. Additionally, chemical substrates deposition, such as silicon carbide, kaolinite, iron silicide, and cristobalite, elucidated chemical-mechanical interactions during the process at such low temperatures.

Rapid synergistic cloud point extraction based on hydrophobic deep eutectic solvent combined with hydride generation atomic absorption spectrometry for determination of selenium in tea samples

Herein, hydrophobic deep eutectic solvents (HDESs) were created for the fast preconcentration of Se(IV) from tea samples at room temperature. A facile and rapid synergistic cloud point extraction (HDES-RS-CPE) procedure was used, followed by hydride generation atomic absorption spectrometry (HG-AAS). The selected synergistic DES included glycine and lauric acid (molar ratio 3:1). 2-hydroxy-5-p-tolylazobenzaldehyde (HTAB) and Triton X-114 were utilized as chelating reagent and non-ionic surfactant, respectively. The experimental parameters that impact extraction recovery were examined and optimized. The detection limit, quantification limit, preconcentration factor, and enhancement factor for Se(IV) under optimum circumstances were 0.02 μg L−1, 0.06 μg L−1, 125, and 149, respectively. The method exhibited analytical linearity in the range up to 700.0 μg L−1. The procedure was used effectively for the quantification of Se(IV) in tea and certified samples. Moreover, the National Environmental Method Index (NEMI), the analytical greenness scale for sample preparation (AGREEprep), and the Green Analytical Procedure Index (GAPI) criteria have been used to measure the greenness score of the extraction procedure. To further highlight the environmental friendliness of this method, a detailed evaluation has been performed.

Viscosity Measurements at High Pressures: A Critical Appraisal of Corrections to Stokes' Law

AbstractFluids and melts in planetary interiors significantly influence geodynamic processes from volcanism to global‐scale differentiation. The roles of these geofluids depend on their viscosities (η). Constraining geofluid η at relevant pressures and temperatures relies on laboratory‐based measurements and is most widely done using Stokes' Law viscometry with falling spheres. Yet small sample chambers required by high‐pressure experiments introduce significant drag on the spheres. Several correction schemes are available for Stokes' Law but there is no consensus on the best scheme(s) for high‐pressure experiments. We completed high‐pressure experiments to test the effects of (a) the relative size of the sphere diameter to the chamber diameter and (b) the top and bottom of the chamber, that is, the ends, on the sphere velocities. We examined the influence of current correction schemes on the estimated viscosity using Monte Carlo simulations. We also compared previous viscometry work on various geofluids in different experimental setups/geometries. We find the common schemes for Stokes' Law produce statistically distinct values of η. When inertia of the sphere is negligible, the most appropriate scheme may be the Faxén correction for the chamber walls. Correction for drag due to the chamber ends depends on the precision in the sinking distance and may be ineffective with decreasing sphere size. Combining the wall and end corrections may overcorrect η. We also suggest the uncertainty in η is best captured by the correction rather than propagated errors from experimental parameters. We develop an overlying view of Stokes' Law viscometry at high pressures.

Remediation of 3,4,3′,4′-tetrachlorobiphenyl (PCB77) contaminated soil via a fluidized bed dielectric barrier discharge

In this study, 3,4,3′,4′-tetrachlorobiphenyl (PCB77) contaminated soil was remediated by a fluidization bed dielectric barrier discharge (DBD) reactor and a fixed bed DBD reactor. The fluidized bed reactor could attain superior removal efficiency of PCB77 under same experimental parameters. In-situ discharge mode was more conducive to the degradation of PCB77 than ex-situ discharge mode due to short-lived active species existing in in-situ discharge. The influence of experimental parameters in the fluidized bed DBD reactor on the degradation of PCB77 were discussed such as electric features, gas features, soil features and initial PCB77 concentration. PCB77 removal efficiency in air discharge could reach 88.5 % after 8 min under the alkaline condition. Optical emission spectroscopy (OES) and quench tests showed that reactive oxygen species (ROS) and reactive nitrogen species (RNS) were generated in the discharge system and they both played a vital role in the degradation of PCB77. Scanning electron microscopy (SEM) results demonstrated that discharge had little effect on the morphology of soil particles. Energy dispersive spectrometer (EDS), ion chromatography (IC), and total organic carbon (TOC) results showed that the DBD could effectively mineralize and dechlorinate PCB77. The possible degradation pathway of PCB77 was inferred at the end based on the degradation products determined by gas chromatography–mass spectrometry (GC–MS).

Progress of electrical stimulation to promote peripheral nerve regeneration

This study reviews the latest progress on the research of electrical stimulation（ES） in peripheral nerve regeneration, summarizes the parameters in preclinical experiments and discusses the effect on nerve regeneration. A detailed description is given in the study of conditioning electrical stimulation and nerve conduit scaffolding technology combined with ES, which have been hotly researched in recent years.

Determination of impact parameter for CEE with digi-input neural networks

The impact parameter characterizes the centrality in nucleus-nucleus collision geometry. The determination of impact parameters in real experiments is usually based on the reconstructed particle attributes or the derived event-level observables. For the scheduled Cooler-storage-ring External-target Experiment (CEE), the low beam energy reduces correlation between the impact parameter and charged particle multiplicity, which decreases the validity of the explicit determination methods. This work investigates a few neural network-based models that directly take the digitized signals from the external Time-of-flight detectors as input. The model with the best performance shows a mean absolute error of 0.479 fm with simulated U-U collisions at 0.5 AGeV. The performances of the models implemented with digi inputs are compared with reference models with phase space inputs, showing the capability of neural networks to handle the original but potentially interrelated digitized signal information.