The binding of ticagrelor, its two major metabolites, adenosine diphosphate (ADP) and 2-Methylthioadenosine diphosphate (2MeS-ADP) as agonist, and ethyl 6-[4-(benzylsulfonylcarbamoyl)piperidin-1-yl]-5-cyano-2-methylpyridine-3-carboxylate (AZD1283)as antagonist were assessed systematically by means of ensemble docking. It is shown that the binding of all ligands becomes systematically stronger with the increase of the membrane rigidity. Binding of all ligands to the agonist-bound-like conformations is systematically stronger in comparison to antagonist-bound-likes ones. This is dramatically opposite to the results obtained for static crystal structures. Our results show that accounting for internal protein dynamics, strongly modulated by its lipid environment, is crucial for correct assessment of the ligand binding to P2Y12.The binding of natural ligands and synthetic drugs to the P2Y12 receptor is of great interest because of its crucial role in platelets activation and the therapy of arterial thrombosis. Up to now, all computational studies of P2Y12 concentrated on the available crystal structures, while the role of intrinsic protein dynamics and the membrane environment in the functioning of P2Y12 was not clear. In this work, we performed all-atom molecular dynamics simulations of the full-length P2Y Platelets are major drug targets in case of thromboembolic disorders. Pharmacological inhibition of platelet aggregation is necessary for preventing complications after an acute coronary syndrome (ACS) and the formation and progression of thrombotic processes. Adenosine diphosphate (ADP) is an important signal molecule for platelet function, which is involved in their physiological and pathological responses . The inhCurrently, two classes of P2Y12 antagonists have been developed and approved by the FDA as antiplatelet agents, namely the irreversible thienopyridines and the reversible ATP analogues. Thienopyridine compounds such as ticlopidine, clopidogrel, and prasugrel irreversibly inhibit P2Y12 receptor . They arLimitations of existing drugs, such as a very long half-life of clopidogrel and adverse effects of ticagrelor ,15, indiExperimental studies of the influence of lipid environment on membrane proteins are complex, tedious, and time consuming, which recently boosted the development of computational approaches to this problem. In the case of P2Y12, early numerical studies ,24 were Recently, an extensive molecular docking study of the major classes of substances, previously reported as P2Y12 ligands, was performed . The autIn the present study, we propose the most realistic computational model of P2Y12 available to date. First, we consider the receptor in its native lipid bilayer environment. The dynamics of the receptor is investigated as a function of bilayer composition. Phosphatidylcholine (PC), sphingomyelin (SM), and SM/cholesterol mixture (referred as “raft” hereafter) environments are studied. Second, both agonist and antagonist-bound crystal structures are used as initial conformations in each lipid environment. Third, an extensive ensemble docking analysis is made on a representative set of simulation snapshots extracted from equilibrated molecular dynamics (MD) trajectories, which takes into account both the local flexibility of the binding site and the large-scale protein motions. This methodology was already used with great success for the proteins with complex internal dynamics, such as STAT1/STAT3 ,29 and hWe demonstrate that the lipid environment imposes significant constraints into the dynamics and internal flexibility of P2Y12, which in turn influences its binding to a variety of ligands. In general, the more ordered the lipid environment, the higher the binding propensity of P2Y12 to all studied ligands. The bulky nucleotide ligands, such as ticagrelor, can access the binding pockets of both agonist and antagonist-bound P2Y12 conformations with the help of internal protein dynamics.In this work, we considered two crystal structures of P2Y12: 4PXZ:A in complex with 2MeS-ADP agonist  (referreThe closed structure of P2Y12 (PDB code 4PXZ:A) was chosen as the starting point for homology modeling. It covers only the residues 15–305, which constitute the major part of transmembrane core of this membrane protein. The crystallized structure is an engineered chimeric protein with soluble cytochrome B562 inserted between the residues 223 and 224 of P2Y12. According to UniProt annotation (UniProtKB: Q9H244), the secondary structure of the missing regions 1–14 and 306–342 is not known and presumed to be unstructured.The homology modeling approach was used to reconstruct the full-length structure of P2Y12. The cytochrome insertion was removed, and the GalaxyTBM server  was usedIn order to construct the open structure of the protein, we first aligned the obtained homology model of the closed form with the crystal structure 4NTJ:A and then transferred all atomic coordinates from the crystal structure to our model. This resulted in the models of closed and open conformations which share the same reconstructed peripheral regions missed in the crystal structures.According to the closed crystal structure, the residues reported to bind with 2MES-ADP are ARG19, ARG93, CYS97, SER101, VAL102, TYR105, PHE106, TYR109, MET152, LEU155, SER156, ASN159, THR163, CYS175, LYS179, HIS187, VAL190, ASN191, CYS194, ARG256, TYR259, GLN263, and LYS280 [We studied ticagrelor (TIC) and its two major metabolites : an acti+ and Cl– ions were added corresponding to ionic strength of ≈0.15 mol/L and adjusted to counterbalance the net charge of the protein. All systems were hydrated to approximately 50 water molecules per lipid. The content of the resulting systems is shown in In this work, the open and closed forms of P2Y12 were inserted into three different lipid environments, namely PC  were reported to be the most abundant ones in platelets membranes . The memThe membrane ordering and fluidity was assessed by computing lateral diffusion coefficients of the lipids in all studied systems. The results are shown in The open form of the protein was built by substituting the transmembrane core of the closed form with the coordinates from 4NTJ:A crystal structure as described above. The open forms were built separately for three lipid environments from the corresponding pre-equilibrated closed forms.For all systems, the following equilibration protocol was applied. First, all protein atoms were restrained, and the lipids and solvent were equilibrated for 100 ns. Then, the protein backbone was restrained, and the side chains were equilibrated with the rest of the system for another 100 ns. Finally, all restraints were removed, and the production run of at least 200 ns was performed. The equilibration was monitored by the Root Mean Square Deviation (RMSD) of the transmembrane part of the protein (residues 20–300) excluding the termini, which were fluctuating significantly during the simulations. Simulations that did not converge in 200 ns were prolonged until the RMSD stabilizes.All MD simulations were performed in Gromacs  version In order to account for protein conformational flexibility, multiple conformations from MD trajectories were extracted and used in docking simulations. The last 50 ns of MD trajectories were used to extract 834 equally spaced frames. For each frame, the docking of all ligands was performed. The docking volume was centered in the center of mass of the binding site and had dimensions 2 × 2 × 2 nm. Quick Vina 2  docking Both open and closed forms of the protein were found to be stable in all membrane environments . HoweverFirst, the equilibration of the protein was significantly longer for the open form than for the closed one. It took up to 400 ns for the open structure in a raft environment. In contrast, the closed form equilibrated in only 200 ns in all three membrane environments. This suggests that the closed crystal structure is closer to equilibrium conformation in a native membrane environment than the open one. Second, the final RMSD for the transmembrane region is less than ≈0.3 nm in the closed form and less than ≈0.5 nm in the open form. These are rather small values for a protein of this size. This means that the structure of the transmembrane part of the protein is in general quite rigid and is not prone to dramatic conformational changes in the course of simulations. The same trend is observed for the active site of the protein, which suggests that the dynamic of the active site is not significantly different from the rest of the protein. The protein termini (residues 1–19 and 301–342), which are exposed to aqueous solution, fluctuate randomly and interact with the membrane transiently. The interaction energies of N and C-terminal regions of the protein with the membranes are shown in The pattern of root mean square fluctuations (RMSFs) in the closed form of the receptor is very similar in all lipid environments A. HoweveThe fluctuations of the open form are more interesting. This structure appears as rigid as the closed one except for two distinct regions (residues 252–269 and 220–235), which are much more flexible than the rest of the protein C. IntereWe performed an in-depth analysis of the conformational mobility of TM6 by computing the RMSD of the region 252–269 with both closed and open crystal structures of P2Y12 after alignment on the rest of the membrane core of the protein (residues 20–300). Only equilibrated parts of the trajectories were used for analysis. The results are shown in The conformation of TM6 helix was stable in all simulations experiencing only slight fluctuations, which is obvious from well-localized clouds of points corresponding to each trajectory. In the simulations that started from the closed structure, the orientation of the TM6 helix evolved significantly in the cases of PC and raft environments and stabilized in very similar intermediate conformations between closed and open crystal structure , which is responsible for the key structural differences between open and closed states, decreases up to 40% in an SM environment and up to 25% in a raft environment. The flexibility of the intracellular loop region 220–235 decreases up to 70% in the SM environment and up to 60% in the raft environment. This points out the importance of the lipid environment on the flexibility of this protein. It also proves that the models of P2Y12, which do not take into account of their lipid environment, could lead to artifacts.The ensemble docking utilized in this study allowed us to sample multiple conformations of the protein for each ligand. It takes into account changes of the protein flexibility in each of the studied lipid environments. The distributions of obtained docking scores are shown in The first remarkable feature is the binding scores of TIC and its metabolites. It is clearly seen that the active metabolite M8 shows stronger binding than pristine TIC (the distribution is shifted to the left) in all membranes and in both protein conformations. The other metabolite M5 shows dramatically worse binding than TIC . The difference between the peaks of TIC and M8 distributions is ≈0.3–0.5 kcal/mol, while the difference between TIC and M5 is ≈2–2.5 kcal/mol in all membranes. This feature corroborates well with the experimental data, which show that the primary metabolite of ticagrelor (M8) is also active with potency equal to the parent compound .The specific agonist 2MeS-ADP binds a bit worse than pristine ADP in most cases; the difference between them varies from zero to ≈0.5 kcal/mol. This difference is systematic and thus unlikely to be an artifact of our docking methodology, but its relevance for the real receptor is not clear. The binding energy of the AZD1283 antagonist varies from one system to the other but remains comparable to or slightly better than that of TIC and much better than that of ADP. One notable exception is the raft membrane in closed form, where AZD1283 binds ≈0.5 kcal/mol weaker than TIC.In general, the binding scores of TIC, its active metabolite M8, and AZD1283 are better than those of ADP, which means that these compounds could serve as concurrent antagonists. This correlates well with the experimentally observed action of these compounds. There is a strong and systematic influence of the lipid environment on the ligand binding—the binding of all ligands becomes stronger as the membrane rigidity increases. Another systematic trend concerns the comparison of binding with respect to the two forms of the receptor. In general, the binding of all ligands to the closed form of protein  and open (4NTJ:A) forms of P2Y12 using the same setup as for the ensemble docking. The results are shown in The best docking scores for the crystal structures differ dramatically from the results obtained in ensemble docking. In the case of crystal structures, the binding to open form is stronger for all ligands, while for ensemble docking, the trend is strictly opposite, and the binding to closed form is stronger. The pattern of binding scores for different ligands is strikingly different as well for the closed form. Particularly M8 and AZD12831 bind substantially weaker than TIC in the crystal structures. In ensemble docking, the situation is again the opposite: M8 and AZD12831 bind stronger than TIC.In the case of the open form of protein, the differences between ensemble docking and the docking to crystal structure are less pronounced, and the trends for different ligands are much more consistent.In the closed form of the protein, the volume of the binding pocket is restricted by the TM6 helix, which is kinked inwards and may impose steric restraints on the ligands. The static crystal structure is especially unfortunate in terms of such restraints. The ligands do not fit well into the pocket and exhibit weak binding. MD simulations allow equilibrating positions of TM6 side chains and to sample different orientations of this helix see , includiThese observations emphasize the fact that collecting statistics over many protein conformations in ensemble docking allows comparing docking score distributions as a whole, which leads to reliable and unambiguous results. The dynamics of the protein, particularly its flexibility and fluctuations, are affected dramatically by the lipid environment. Such dynamical effect could never be correctly rendered by the docking to single protein conformation. Docking to the single crystal structures of P2Y12 should be avoided because it produces incorrect and misleading results, as it is evident from Due to the large number of docking simulations, we can estimate the probability of each ligand to be in contact with particular protein residues. The results of this analysis are shown in The pattern of binding probabilities changes with lipid environment and the protein form, but these changes are surprisingly similar for different ligands despite their different chemical nature. Detailed analysis of observed fine differences between the ligands is beyond the scope of this work.The number of residues with high binding propensity is significantly larger in a PC environment in comparison to SM and raft environments. Particularly, in the closed form of protein in the PC environment, there are two additional groups of residues with high binding probability: 111–115 and 197,201,240,248 respectively. In the open form of protein in the PC environment, there is another additional group: 154,155,157. The raft environment exhibits two residues with high binding propensity, which are absent in other environments: 88 for closed and 18 for open form, respectively.However, these results should be interpreted with caution because they could be biased by the limited sampling in the particular MD trajectory. Ideally, multiple independent MD and ensemble docking simulations should be performed in each lipid environment, but this requires a prohibitively large amount of time and computational resources.Comparison with crystallographic structures show that there is a partial match between the residues with highest binding probability in our simulations and the binding pockets in closed and open crystal structures, which correspond to the complexes of P2Y12 with the agonist 2MeS-ADP and the antagonist AZD1283, respectively. In the closed structure, the residues reported to bind with 2MeS-ADP are 19, 93, 97*, 101*, 102, 105,106, 109, 152, 155*, 156, 159, 163, 175*, 179, 187*, 190*, 191, 194*, 256, 259*, 263, and 280* (the matching residues in our docking simulations are marked by asteriscs). In the open structure, the residues reported to bind with AZD1283 are 101*, 102, 105, 106, 109, 152, 155*, 156, 159, 187*, 190*, 191, 194*, 195, 252, 255*, 256, 259*, 260, 276*, 279*, 280*, and 283.Spatial locations of the binding pockets for 2MeS-ADP and AZD1283 in our simulations are similar to ones present in the crystal structures, but there is no exact correspondence, as it is evident from The major limitation of the current work is limited sampling caused by rather short MD trajectories. These trajectories are sufficient to generate useful ensemble of conformations for docking, which is confirmed by the fact that we managed to dock all ligands successfully to both forms of protein. However, much longer trajectories are needed for comprehensive study of the protein dynamics in the membrane environment. A typical timescale of the physiological conformational changes in the family of GPCR proteins is likely to be in the milliseconds range, which is not accessible in all-atom MD simulations. We presume that in the present study, we mostly see the influence of the hindrance, caused by the lipid environment, on the relaxations of two initial states, which are represented by the closed and open crystal structures. Indeed, the lateral diffusion of the lipids is an order of magnitude slower in SM and raft membranes in comparison to the PC one , which iThus, our work provides proof of the principle for the influence of the membrane environment on the ligand-binding propensity of the P2Y12 receptor. Further simulations with larger time scales, multiple replications, and realistic membrane compositions are needed to determine the concrete mechanism of this phenomenon.The MD and ensemble docking simulations of the full-length P2Y12 receptor in different membrane environments show that the active ticagrelor metabolite M8 (AR-C124910XX) binds to the receptor stronger than ticagrelor itself, while the metabolite M5 (AR-C133913XX) shows much weaker binding. With the increase of membrane stiffness and ordering, the binding of ticagrelor and both its metabolites becomes stronger with the best binding scores observed in the raft-like sphingomyelin–cholesterol membrane. Our results suggest that this effect is caused by the decrease of the overall protein flexibility and relaxations in the rigid membrane environment rather than due to distinct conformational changes or the rearrangement of its active site. Our data provide first direct evidence of the strong influence of the membrane environment on the ligand binding in P2Y12 receptors and suggest an optimal functioning of this protein in the lipid rafts.


Moreover, a random forest (RF) model was developed to optimize the model based on a metaheuristic method to improve the model performance. Based on the experimental results the RF model achieve better results than response surface methodology (RSM). The functional quadratic regression is curvature and the tested variable shows stable close data of the mean 0 and α2. Based on the Pareto analysis, the PHT and VF were key variables that significantly affected the UTS, microhardness, and density of the product. The maximum properties were achieved at an optimum PHT, PHti, and VF of 541 °C, 2.25 h, 1 vol% SiO2 and 2.13 vol% CuO, respectively. Furthermore, the morphological results of the tensile fractured surface revealed the homogenous distribution of nano-reinforced CuO and SiO2 particles in the specimens’ structure.To date, various studies have analysed the effects of reinforced ceramic on the properties of AA6061 recycled aluminum alloy chips, such as the tensile strength and fractography. However, a comprehensive analysis of the properties of hybrid composite with the addition of nano-silica oxide and nano-copper oxide reinforcements is still very limited. Therefore, this study aimed to optimise the factors comprising the preheating temperature (PHT), preheating time (PHti), and volume fraction (VF) of reinforcements then determine their impacts on the physical and mechanical properties of the recycled solid-state extruded composite aluminum chips. A total of 45 specimens were fabricated through the hot extrusion technique. The response surface methodology (RSM) was employed to study the optimisation at a PHT range of 450–550 °C with PHti of 1–3 h and VF of 1–3 vol% for both reinforcements (SiO Composite materials have useful properties due to their constituent matrix and reinforced materials ,2. One oThe conventional approach for aluminum production from ores requires approximately 113 GJ per tonne of aluminum, while the secondary fabrication and production from conventional aluminum recycling methods from scrap requires around 13.6 GJ per tonne of energy . In contSolid-state recycling is used to convert the metallic scraps into bulk material, consequently eliminating the remelting process that is commonly found in the conventional recycling approach ,6,7. MorThe quality and properties of hot extruded aluminum alloy chips are determined by several extrusion factors, such as process temperature, extrusion ratio, die geometry, chip morphology, and extrusion speed. These factors play a vital role in determining the final properties and microstructure of the extruded products . The for2) nanocomposites prepared by powder metallurgy and subsequent hot extrusion resulted in an enhanced tensile strength and compressive mechanical properties , and k represents the iteration numbers. The above processes were used until convergence or termination constraints was achieved.Particle Swarm Optimisation (PSO) is an important set of evolutionary algorithms commonly employed in optimisation issues and problems. PSO algorithms have been frequently used in biological population studies to analyse individual and social behaviours . PSO hasa vector :S = {S1,MSE), Mean Absolute Error (MAE), and correlation coefficient (R2) were primarily used during the regression analysis to determine the rate of prediction error and efficiency. The MSE describes the difference between both original and predicted values that were calculated and derived from the square average difference in the data set. In addition, the MAE provides the discrepancy and difference within the original and predicted values due to the average absolute difference in the data set. The value of R2 explains the accuracy of the matched values with the original values. The higher value of R2 from a scale between 0 and 1 indicates a good RF model. The fitting error during the prediction and training analysis in the developed model was validated and tested through MSE, MAE, and R2, which were calculated through Equations (6)–(8).An important part of the process for the development of the RF model was measuring the model accuracy in order to analyse the performance and predictions. The Mean Squared Error  below:2 and CuO volume fraction to analyse the UTS for the extruded composite samples. Moreover, the RSM indicated various processing parameters (PHT (A), PHT*, PHti (AB), VF (SiO2)*, VF (CuO) (CD), VF (CuO) (C), VF (CuO)*, VF (CuO) (CC), VF (SiO2), and PHti (BB)) were important. The overall quality of the model was analysed and evaluated through the results of R2, adjusted R2 (adj. R2), predicted R2 (pred. R2), and proper, precise values. The quadratic model was obtained along with mathematical modelling with a strong and accurate determination of R2 = 92.24%, which was a better regression model fit to the research studies. The adj. R2 and pred. R2 values were 88.23% and 80.84%, respectively. A great agreement between the adj. R2 and pred. R2 prevented the over-fitting of the mathematical model . Data normalising boosts the evaluation and prediction while in use. The microhardness, UTS, and density of the data samples were used in the training data, and k-fold cross-validation was set to 10. The confirmation tests were used as the test data for the verification of the accuracy of the RF model. For this model, a complete data set of 48 data samples were used. A total of 45 samples were obtained from the full factorial, while the output  was obtained from the experimental results. In addition, 45 data samples were chosen and selected at random for the training and samples validation, while the remaining 3 data samples were employed as the testing samples for output prediction assessment and the confirmation test to validate the results.MSE and MAE values demonstrated better results in the RF model, as shown in MSE and MAE values of the RF model were low, indicating that the model performed well in predicting the microhardness, UTS, and density. The highest R2 value for the RF model was 0.9647. Moreover, the MSE and MAE values of the RF model were lower, indicating the highly accurate results with no significant over-estimation or under-estimation of the targeted values. This study concluded the significance and efficiency of the RF model in predicting the microhardness, UTS, and density of the nano-reinforced AA6061 aluminum chips based on the MAE and MSE values with low error rate between the experimental and predicted results.Low 2 to the alloy in PHT to 550 °C, 3 h and SiO2 2 vol% with few effects on UTS of 217 MPa as shown in The Scanning Electron Microscope (SEM) was used in analysing the morphology of fractured surface for tensile profiles of hot extruded composite samples. It was noticed that the fractured surface among tensile samples differed in contours. As shown in 2.The fractographic analysis also revealed that the weakest point served as the crack initiation site for the failure. This was an indication of the sudden change in the force equilibrium in the samples, as seen in The effect of reduction in preheating temperatures from 550 °C to 450 °C was clear effected on the extruded sample microvoids and other defects and impurities served as the stress concentration sites and were responsible for the decrement in strength and other mechanical properties. The fracture surface exhibited ridges and large crack ridge instead of equiaxed dimples, as seen in The Field Emission Scanning Electron Microscope (FESEM) was used in analysing the morphology of fractured surface for AA6061 chips extruded sample at PHT, PHti, and VF of 450 °C and 3 h the presence of cleavage fractures, microvoids, and unequal dimples could easily be seen in some regions, as shown in 2 1 vol%, as shown in In addition, the uniformly distributed dimples and small cracks could easily be observed with the increase in PHT to 541 °C and VF of CuO 2.13 vol%, SiOThe crystallinity analysis was conducted on the three most important samples utilising their highest, optimum, and lowest parameters, as presented in 2, respectively) recorded the lowest intensity of almost 37,892 a.u. compared to other samples. In contrast, for the extruded sample using the optimum parameters  and , the intensity at the plane (111) was 130,112 and 182,419 a.u., respectively.The crystalline structure was identified by matching the data and peaks with the standard JCPDS data. Based on the results, the extruded sample using the optimum parameters  and more accurate Such models could assist in predicting the outcome of the processing materials, which will be helpful to minimise and limit the number of experiments, therefore, minimising the time and energy consumption due to the high prediction rate. Moreover, this study demonstrated that the use of machine learning was significant to obtain high efficiency in research studies and manufacturing processes.A thorough investigation on the effects of PHT, PHti, and VF of CuO and SiO


Among reducing agents, hydrogen has shown a great potential to be replaced with fossil fuels and to decarbonize the steelmaking processes. Although hydrogen is in great supply on earth, extracting pure H2 from its compound is costly. Therefore, it is crucial to calculate the partial pressure of H2 with the aid of reduction reaction kinetics to limit the costs. This review summarizes the studies of critical parameters to determine the kinetics of reduction. The variables considered were temperature, iron ore type , H2/CO ratio, porosity, flow rate, the concentration of diluent , gas utility, annealing before reduction, and pressure. In fact, increasing temperature, H2/CO ratio, hydrogen flow rate and hematite percentage in feed leads to a higher reduction rate. In addition, the controlling kinetics models and the impact of the mentioned parameters on them investigated and compared, concluding chemical reaction at the interfaces and diffusion of hydrogen through the iron oxide particle are the most common kinetics controlling models.A clean energy revolution is occurring across the world. As iron and steelmaking have a tremendous impact on the amount of CO Nowadays, carbon dioxide emissions have become one of the most important environmental concerns, the consequences of which include global warming. Approximately 7% of the total carbon dioxide produced in the world belongs to the iron and steel industries . On averHydrogen such as carbon monoxide can reduce iron oxides and produces water vapor instead of carbon dioxide. At the moment, a mixture of hydrogen and carbon monoxide is used for iron ore reduction in the direct reduction plants by reforming the natural gas. Hence, it seems by performing some modifications and considering the technical and economical essentials, direct reduction plants can use hydrogen as the only reducing agent in the future. Furthermore, hydrogen can be produced from renewable sources such as biomass that makes the process more environmentally friendly. Therefore, the reduction of iron ore with hydrogen has attracted much attention in recent years ,17.In order to minimize the consumption of energy and other elements, it is crucial to study the kinetics of reduction reactions. As there are several reactions that are occurring simultaneously, the kinetics of reduction is very complex .Due to the working temperature, there are different ways to obtain metallic iron from hematite. Reactions can be a chain of single reaction, single and double reaction or a triple reaction as the following :  to the surface of the unreacted iron ore.Chemical reaction of hydrogen with iron ore at this reaction surface.2O) through the ash back to the exterior surface of the particle.Diffusion of the gaseous product (H2O) through the gas film back to the main body of fluid ..28].Zhang et al. found that by increasing the pellet size from 5.5 to 8.5 mm, the reduction rate decreases steadily due to the shorter diffusion distance  46]. Si. Si46]. Wagner et al. investigated the hydrogen reduction of three samples of coarse powder (P1), sintered piece (S1), and nanopowder (N1). Although the specific area for N1 and S1 is higher than P1 due to their smaller particle size, the reduction of the P1 sample was faster than the two other samples. By investigation of the reduced samples’ morphology, it became clear that S1 and N1 samples became compact and lost most of their porosities after reduction while the P1 sample retains its porosity after the reduction  26]..26].2O4 and FexSiyO4 become faster, which increases the resistance of interfacial chemical reaction during the reduction. Higher contents of CaO, SiO2, and MgO can be found in larger particles which leads to the formation of cracks and accelerate the reduction of wüstite ..(18)ln(ϕThe amounts of apparent activation energy determined in various studies related to the reduction of iron oxides to hydrogen are listed in The summary of some research on the iron oxides reduction by hydrogen and the used kinetics models are provided in 2 pollution in the iron and steel industry, it is crucial to investigate new methods of iron oxide reduction. Among all these techniques, using hydrogen as a reducing agent is receiving much attention. In addition, it is necessary to study the exact material and energy consumption by investigating the kinetics of the reduction reactions. These solid–gas reactions are complex and can vary due to the working temperature, gas atmosphere, chemical composition, etc. The mechanisms that control the kinetics of reduction are the diffusion of H2/H2O through the gas film layer, diffusion of H2/H2O through the ash layer, and chemical reaction. For the high gas velocity, film resistance can be ignored. It was approved by some researchers that nucleation also can be considered as a controlling mechanism at the early stages of the reduction and at low temperatures.In order to reduce the amount of CO2O3 to Fe3O4 and reduction of FeO to Fe is negligible, but for the reduction of Fe3O4 to FeO it is considerable.Effect of Temperature: Due to the Arrhenius equation, by increasing the temperature, the rate of reduction will increase exponentially. At temperatures above 590 °C, the effect of temperature on the reduction of Fe2/CO ratio: The reaction rate would increase with the higher hydrogen content at temperatures above 1000 °C. Additionally, H2/CO proportion has the most beneficial effect on the reduction rate when being 1.6, and the higher ratios effect is negligible.Effect of HEffect of hydrogen flow rate: Higher inlet flow rate causes higher steam generation at the early stages of the reaction and at the later stages, the effect is minor. Additionally, there is a critical gas velocity below which gas flow rate controls the rate of the reaction.Effect of iron ore mineralogy: Because of the hard and dense shell of magnetite in comparison with hematite, magnetite has lower diffusion. Thus, the reduction of hematite by hydrogen is faster than the reduction of magnetite, especially at higher temperatures.Effect of particle size: As the size of the particle decreases the specific area increases, therefore the reduction rate enlarges because the reaction starts from the surface. Furthermore, the smaller particle size leads to a shorter distance that gas has to pass to reach inner layers. However, as the particle size shrinks, the chance of agglomeration will increase and as a result, the specific area decreases.2 and CO. Impurities such as CaO, SiO2, and MgO and alumina forms can lead to the formation of micro-cracks that promote the reduction of wüstite. Contrarily, some impurities such as Al2O3 and MgO decrease the rate of magnetite reduction.Effect of impurities: The effect of impurities can be assumed as reduction by HMoreover, the parameters such as temperature, porosity, mineralogy, etc. can play a vital role in order to determine the kinetics of hydrogen reduction precisely. The following conclusions can be made for each parameter according to this literature review:Activation energy definition is the minimum energy that is required to perform a chemical reaction. Lower activation energy shows easier reduction of iron oxides. For instance, the activation energy decreases by increasing the percentage of hydrogen in the reducing gas. In fact, activation energy is dependent on chemical composition, physical properties of materials, temperature range, and process conditions. As a result, there is a wide range of values for the activation energy of reactions. The activation energy of natural magnetite to iron is higher than the reduction of the other forms of iron oxide.Kinetics models depend on different parameters of reduction such as temperature, iron oxide type, particle size, etc. commonly, chemical reactions at the interfaces and the diffusion of hydrogen through the iron oxide particle are used as kinetics models. Through the reduction of wüstite to iron an iron shell covers the surface of the sample and makes the diffusion hard. Thus, wüstite reduction is the rate-controlling and slowest step.


Background and purpose — Information on the epidemiological trends of pelvic fractures and fracture surgery in the general population is limited. We therefore determined the incidence of pelvic fractures in the Finnish adult population between 1997 and 2014 and assessed the incidence and trends of fracture surgery.Patients and methods — We used data from the Finnish National Discharge Register (NHDR) to calculate the incidence of pelvic fractures and fracture surgery. All patients 18 years of age or older were included in the study. The NHDR covers the whole Finnish population and gives information on health care services and the surgical procedures performed.Results and interpretation — We found that in Finnish adults the overall incidence of hospitalization for a pelvic fracture increased from 34 to 56/100,000 person-years between 1997 and 2014. This increase was most apparent for the low-energy fragility fractures of the elderly female population. The ageing of the population is likely therefore to partly explain this increase. The annual number and incidence of pelvic fracture surgery also rose between 1997 and 2014, from 118 (number) and 3.0 (incidence) in 1997 to 187 and 4.3 in 2014, respectively. The increasing number and incidence of pelvic fractures in the elderly population will increase the need for social and healthcare services. The main focus should be on fracture prevention. Pelvic fractures range from minor to major trauma and constitute about 3% to 8% of all fractures treated in hospitals  (THL 2015) is maintained by the National Institute for Health and Welfare, which, in turn, is a research and development institute under the Finnish Ministry of Social Affairs and Health, Helsinki, Finland. The main purpose of the NHDR is to collect data on patients and hospitalization events in Finland. The NHDR covers the entire well-defined Finnish population of 5.5 million (in 2014) people  . The surgical procedures are coded according to the Finnish Classification of Procedures (FCP), which is based on the Nordic Classification of Surgical Procedures (NCSP)  in Finland between 1997 and 2014. All patients aged 18 years or older were included.A secondary outcome variable was the number of surgical operations performed due to a pelvic fracture in Finland between 1997 and 2014 .All persons aged 18 years and older who were admitted to a hospital in Finland due to a pelvic fracture between 1997 and 2014 were included . The stuAll incidences were calculated and expressed annually. To compute the incidence ratios of pelvic fractures leading to hospitalization, the annual mid-populations were obtained from Official Statistics of Finland   to 56 (CI 54–58) between 1997 and 2014 , Table. The frequency and incidence of pelvic fractures was different between the sexes, and this difference was more evident in the elderly population. Of all pelvic fractures, 66% occurred in women, and 52% of fractures occurred in women aged 65 years or older. 68% of all pelvic fractures were in the elderly population.The age-specific incidence increased from 121 (CI 113–129) to 169 (CI 161–177) between 1997 and 2014 in persons aged 65 years and older. The incidence in the elderly female population was twice as high as that in the elderly male population. From 1997 to 2014, the incidence increased from 159 (CI 148–171) to 220 (CI 209–232) in the elderly female population and from 57 (CI 49–67) to 100 (CI 92–110) in the elderly male population. In the younger population, including both sexes, there was only a slight increase in the incidence of pelvic fractures from 14 (CI 12–15) to 19 (CI 17–20). The sex-specific increase in incidence in the younger population was from 17 (CI 15–19) to 20 (CI 18–22) in males and from 10 (CI 8–11) to 17 (CI 15–19) in females during the same period.2,755 operations for pelvic fractures  were performed between the years 1997 and 2014. During the study period, the annual number and incidence of pelvic fracture operations  in both age groups and sexes increased from 30 to 82 operations/year and from 0.8 to 1.9 between 1997 and 2014. The annual number and incidence of internal pelvic fracture fixations was most common in young male patients (from 26 to 32 operations/year and from 1.6 to 1.9). In the younger female population, the number and incidence of internal pelvic fracture fixations was also increasing (from 2 to 16 operations/year and from 0.1 to 1.0). Between 1997 and 2014, the number and incidence of internal pelvic fracture fixations also increased in the elderly population from 2 to 34 operations/year and from 0.3 to 3.1. In the elderly male population, the number and incidence rose from 1 to 10 and from 0.4 to 2.1. In the elderly female population, the number and incidence rose from 1 to 24 operations/year and from 0.2 to 3.9.The annual number and incidence of acetabular fracture operations (NEJ60) increased from 56 to 100 operation and from 1.4 to 2.3 from 1997 to 2014. In the elderly population, the increase was more evident; the annual number of surgeries increased from 15 to 55 operations/year and the incidence of operations from 2 to 5, respectively. In the younger population, the number and incidence of acetabular fracture surgery remained at the same level (from 41 to 45/year and from 1.3 to 1.4) from 1997 to 2014.The rate and incidence of external fixation (NEJ70) operations was highest between the years 2000 and 2002 . However, since then, the number of external fixation decreased dramatically. The annual number of external fixations decreased from 32 to 5 operations/year and the incidence of the operations decreased from 0.8 to 0.1 between 1997 and 2014. External fixation was more common in the treatment of pelvic fractures in the younger population. In the elderly population, the number of external fixations has always been low, and no significant changes occurred during the study period. The use of external fixation became sporadic at the end of the study period. The main finding in this nationwide study was that the overall incidence of pelvic fractures in adult Finns increased by 67% between 1997 and 2014. Pelvic fractures are common in high-energy-induced polytrauma patients. However, they are seen more frequently in elderly populations after a simple fall at ground level  was used both as temporary and definitive fixation of pelvic fractures during the beginning of the study period. Since then, the role of external fixation in the treatment of pelvic fractures has diminished. One reason for this might be the increased use of pelvic binders in emergency situations. The definitive operative treatment of pelvic fractures in Finland has been centralized mainly to our 5 level I trauma centers, whereas primary stabilization and emergency surgery were previously also performed in smaller hospitals. Surgical treatment protocols of pelvic fractures have changed towards performing the definitive fixation of a pelvic fracture as a primary fracture operation after pelvic binder as the primary treatment. Therefore, the role of external fixation as a temporary fixator for the stabilization period and transport to a level I trauma center has diminished.A limitation of this study is related to the ICD-10 coding system, which is not entirely accurate with all pelvic fractures. Codes S32.7 (multiple fractures of lumbar spine and pelvis) and S32.8 (fracture of other and unspecified parts of lumbar spine and pelvis) include both pelvic and lumbar spinal fractures, which may cause some inaccuracy in the register, and therefore the ICD-10 system is not entirely unambiguous in classifying pelvic fractures. The change in the practice of coding of the fractures might also affect the study results. The ICD-10 coding system has been used in the Finnish NHDR since 1996 while our study started in 1997. Thus, introduction of the ICD-10 coding system may have had some effect on the practice of coding at the beginning of our study period. Another limitation of this study is related to the FCP coding system, which is not entirely accurate with the codes relating to open reduction of pelvic fracture (NEJ50) and reoperation or late fracture surgery of pelvis (NEJ86). However, as the same ICD-10 and FCP coding was used during the whole study period from 1997 to 2014, this possible problem with the accuracy of the classification did not affect the reported time trends in fracture incidence. Finally, as such, the NHDR cannot separate the hospitalization events of two different pelvic fractures in a single patient. We solved this by counting one patient only once. Also, it was possible that some patients in the early study population might have had a pelvic fracture prior to the study period but been sampled into the study population merely due to re-hospitalization of the fracture. We note that this type of case must have been rare.In summary, we observed that in Finnish adults the overall incidence of hospitalization for a pelvic fracture increased from 34 to 56/100,000 person-years between 1997 and 2014. The increase was especially apparent in low-energy fragility fractures among the elderly female population. The increasing number and incidence of pelvic fractures in the elderly population will increase the need for social and healthcare services. The main focus should be on fracture prevention.Conception and design: VMM. Collection and assembly of data: PR. Analysis: PR. Interpretation of the data: PR, VMM, ML. Drafting of the manuscript: PR. Critical revision and final approval of the article: PR, VMM, ML, PK. Acta thanks Marianne Hansen Gillam and Alma B Pedersen for help with peer review of this study.


The experiment lasted for 42 days and consisted of three periods  of 14 days each. These stages entail feeding of the laying hens with basal diets, addition of drugs and selenium synchronously into the diets, drug withdrawal from diet, and supply of selenium uninterruptedly in the diet. Egg production and feed intake were recorded on daily and weekly bases, respectively. The selenium content in egg yolk, egg white, and whole eggs and the drug residues in eggs, plasma, liver, kidney, and breast muscle were determined on days 2, 3, 5, 6, 7, 9, 11, and 14 of the depositional and eliminating stages. There was no significant difference (p > 0.05) in egg production among the dietary treatments, but feed intake decreased significantly (p < 0.05) in the drug treatment group compared to other groups. Dietary organic selenium decreased the residue of drugs in tissues and eggs, while the metabolism and deposition of selenium in laying hens were suppressed due to drug effects. The results of the present study are of significance to enrich the knowledge of the pharmacokinetics of florfenicol and enrofloxacin in laying hens and ensure the quality of poultry products.In the context of increasing awareness on the dietary supplementation of organic selenium in commercial poultry production and ensuring safe egg production, the present study investigated the effects of selenium on the pharmacokinetics of the therapeutic use of florfenicol and enrofloxacin from perspectives of laying performance, selenium deposition in eggs, and drug residue in plasma, organs, and eggs. A 2 × 3 factorial arrangement with two kinds of drugs  and three levels of dietary organic selenium SCIP (selenium conjugated to insect protein)  was designed together with a blank control group. Healthy Hy-Line Brown laying hens ( In the poultry industry, veterinary drugs such as antibiotics and antiparasitics are extensively used for disease prevention and treatment. Antibiotic growth promoters have been banned on livestock and poultry feed in China in 2020 adhering to the European Union in 2006, and a series of additives were explored to replace antibiotics for the healthy and sustainable development of the poultry industry –3. NonetFlorfenicol and enrofloxacin are wide-spectrum, synthetic antibacterial drugs widely used in the livestock industry, but an adequate drug withdrawal period must be ensured before marketing the animal or its products. In this context, concerns over drug residues in eggs and consumers' health have led several countries including China, UK, and USA to ban the use of florfenicol and enrofloxacin in diets of laying hens –10. HoweNowadays, dietary supplementation of selenium is a common practice in commercial poultry production in order to improve the immunity and overall health of animals , 16. IncA 2 × 3 factorial design with two kinds of drugs  and three levels of dietary selenium supplementation  was adopted in the present study. The experimental treatments are shown in A total of 252 Hy-Line Brown laying hens aged 40 weeks and 90.0 ± 1.7% of egg production rate were randomly allocated into one of seven treatments with six replicates and six hens per replicate. Birds were fed a commercial laying hen diet until the experiment started. Birds had free access to water and diets throughout the experiment and were managed according to the Hy-Line International Online Management Guide . The experiment lasted for 42 days and consisted of three periods  of 14 days, respectively. All the laying hens were fed basal diet at the adjusted stage; the drugs and selenium were synchronously added into diets according to the experimental design at the depositional stage while the drugs were removed from diets to start the eliminating stage with selenium to be supplied uninterruptedly. During the trial, birds were raised in three-tier cages  with 16 h of light/day, 20 lx of light intensity, and 14~20°C of room temperature. Egg number, egg weight, abnormal egg, and mortality per replicate were recorded every day. Feed intake per replicate was recorded every week and timely adjusted according to the death of birds. Egg mass was calculated as egg weight × laying rate. The feed conversion ratio (FCR) was calculated as feed intake/egg mass . On daysAccording to the China National Standard, GB 5009.93-2017, the selenium content in experimental diets, whole egg, albumen, and yolk was analyzed using hydride-atomic fluorescence spectrometry  coupled with a standard reference of selenium . The florfenicol residues in eggs and tissues were determined by the high-performance liquid chromatography (HPLC) method in accordance with the recommendations (DB34/T 1376-2011) of the China National Library of Standards. The enzyme-linked immunosorbent assay (ELISA) method was used to analyze the enrofloxacin residue in eggs and tissues in terms of notice no. 1025, 25-2008, published by the Ministry of Agriculture and Rural Affairs of the People's Republic of China.p ≤ 0.05 was set as the threshold for significance.Experimental data were analyzed by the one-way ANOVA procedure of SAS 9.2  for a completely randomized design. The data were also analyzed by 2 × 2 or 2 × 3 factorial using the GLM procedure of SAS for a randomized complete block design. The model included the fixed effect of selenium levels, drugs, and their associated two-way interaction. p ≤ 0.05) affected by experimental treatments. Laying hens fed florfenicol and enrofloxacin (Se-0) showed lower (p ≤ 0.05) ADFI than those of the control group, while laying hens fed drugs and selenium were similar with the control group. No interaction effects existed between drugs and selenium levels for egg production, ADFI, FCR, and egg weight of laying hens.The performance of laying hens is shown in p ≤ 0.05) than those of florfenicol during almost all depositional and eliminating stages except for day 7 of the former and day 11 of the latter. At days 5 and 11 of the depositional stage and day 11 of the eliminating stage, residues of both florfenicol and enrofloxacin in plasma were dose-dependently decreased (p ≤ 0.05) along with the increase of dietary selenium level. There were no significant interactions between drugs and selenium for the residues of drugs in plasma.The drug residues in the plasma, liver, kidney, and breast muscle in the treatment groups are presented as the ratio of their concentration of drugs to those in the control group. As shown in p ≤ 0.05) those of enrofloxacin at day 2 of the depositional stage and days 2, 3, 9, 11, and 14 of the eliminating stage, but less (p ≤ 0.05) at days 3, 5, 7, 9, and 11 of the depositional stage and day 5 of the eliminating stage. The residues of drugs in the liver at day 3 of the depositional stage and day 7 of the eliminating stage were significantly (p ≤ 0.05) affected by dietary selenium levels. There were significant (p ≤ 0.05) interactions between drugs and selenium levels at days 3 and 9 of the depositional stage and day 9 of the eliminating stage. At day 3 of the depositional stage, along with the increase of dietary selenium, the residues of florfenicol showed decrease first and then increase (p ≤ 0.05), but those of enrofloxacin was not affected. At day 9 of both depositional stage and eliminating stage, the residues of florfenicol were decreased (p ≤ 0.05), while those of enrofloxacin were increased (p ≤ 0.05), as the dietary selenium levels increased.The effects of dietary selenium on residues of drugs in the liver of laying hens are presented in p ≤ 0.05) than those of enrofloxacin, but were more (p ≤ 0.05) at day 14 of the eliminating stage. The dietary selenium levels did not affect the residues of drugs, and no interactions were observed between drugs and selenium levels. As shown in p ≤ 0.05) than those of enrofloxacin, but less (p ≤ 0.05) at day 11 of the depositional stage and days 3 and 11 of the eliminating stage. Along with the increase of dietary selenium, the residues of drugs were significantly decreased (p ≤ 0.05) at day 3 of the depositional stage and days 2 and 11 of the eliminating stage. There were no significant interactions between drugs and dietary selenium levels during the depositional and eliminating stages.Residues of drugs in the kidney of laying hens are shown in p ≤ 0.05) than that of florfenicol at the whole depositional stage and days 2, 3, 5, and 11 of the eliminating stage. For laying hens fed florfenicol, diets supplemented with 2 mg/kg selenium significantly (p ≤ 0.05) decreased the drug residue rate in eggs at day 2 of the depositional stage relative to the control group, while those with 5 mg/kg selenium showed significant (p ≤ 0.05) opposite effects. The residue rate of florfenicol in eggs for laying hens fed 2 mg/kg selenium was significantly (p ≤ 0.05) decreased as compared with the control group at days 3 and 14 of the eliminating stage, that of 5 mg/kg selenium was significantly (p ≤ 0.05) decreased at day 2, and that of 2 mg/kg selenium was less (p ≤ 0.05) than that of 5 mg/kg at day 7. At days 2 and 11 of the eliminating stage, the residue rate of enrofloxacin in eggs showed significantly (p ≤ 0.05) gradient reduction along with increased level of dietary selenium. During the whole depositional stage, no interaction effects existed between drugs and selenium levels for drug residue of eggs. At day 2 of the eliminating stage, significant (p ≤ 0.05) interaction effects on drug residue were observed between drugs and selenium and disappeared during the rest of the eliminating stage.The drug residues of eggs in the treatment groups are presented as the ratio of their concentration of drugs in eggs to those in the control group . The resp ≤ 0.05) concentration of selenium in the yolk of eggs than those in the control group from day 5 of the depositional stage to the end of the eliminating stage. Increasing dietary selenium from 2 to 5 mg/kg significantly (p ≤ 0.05) increased the content of selenium in yolk of laying hens fed enrofloxacin at days 7 and 9 of the depositional stage, while no effects were observed at other time points of the depositional and eliminating stages. Dietary selenium levels showed no effects on the selenium enriched in yolk of laying hens fed florfenicol during the depositional and eliminating stages, except for day 5 of the latter where the dietary selenium content exhibited a positive relationship (p ≤ 0.05) with the concentration of selenium in yolk. For laying hens fed 5 mg/kg selenium, enrofloxacin increased (p ≤ 0.05) the enrichment of selenium in yolk relative to florfenicol. During the two stages, significant (p ≤ 0.05) interaction effects were observed only at day 9 of the depositional stage.The concentration of selenium in the yolk of eggs is shown in p ≤ 0.05) increased the concentration of selenium in albumen relative to the control group from day 5 of the depositional stage to the end of the eliminating stage. At day 2 of the eliminating stage, the dietary selenium level showed positive effects (p ≤ 0.05) on the enrichment of selenium in albumen. For laying hens fed florfenicol, at day 7 of the depositional stage, the diet containing 5 mg/kg selenium significantly (p ≤ 0.05) increased the content of selenium in albumen as compared with that of 2 mg/kg selenium. Increasing dietary selenium from 2 to 5 mg/kg obviously (p ≤ 0.05) increased the enriched selenium in albumen of eggs for laying hens fed enrofloxacin. Drugs and dietary selenium levels exhibited significant (p ≤ 0.05) interaction effects on the content of selenium in albumen on day 2 of the depositional stage.The content of selenium enriched in albumen of eggs is presented in The yolk and albumen of the egg were mixed together evenly, and then the selenium content of the mixture was determined . It is tThe organic selenium SCIP as a new kind of selenium source conjugated to insect protein has been demonstrated to be beneficial for the health of laying hens and improve the safety of selenium enriched eggs . In the Recently, various studies have investigated and confirmed the positive effects of different selenium sources on the laying performance and antioxidant capacity of laying birds including sodium selenite, nanoselenium, selenomethionine, and selenium yeast –32. In tEggs from laying hens have been reported to contain drug residues from different classes of drugs used in the poultry for therapeutic purposes, and such residues can persist for a long time in the posttreatment period . In the Increased intake of dietary selenium culminated in a corresponding increase of selenium content in eggs and meat . It is cDietary organic selenium decreases the residue of drugs in tissues and eggs probably through enhancing the metabolism of laying hens. The treatment of drugs showed inhibition effects on the metabolism and deposition of selenium in laying hens. In the context of the wide application of selenium in poultry feed, these findings contribute to the knowledge of the pharmacokinetics of florfenicol and enrofloxacin in laying hens and ensuring the safety of poultry products.The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.The animal study was reviewed and approved by Animal Care and Use Committee of the Feed Research Institute of the Chinese Academy of Agricultural Sciences.Conceptualization, methodology, and project administration were performed by S-gW and G-hQ. Animal experiment, chemical analysis, and data collection were conducted by KQ and H-jZ. Original draft was written by KQ. Writing-review was finished by H-jZ, JW, and UO. All authors have agreed to the final manuscript.This study was supported by the earmarked fund for Modern Agro-industry Technology Research System (CARS-40-K12), Beijing Innovation Consortium of Agriculture Research System (BAIC04-2021), Shandong Key Science and Technology Innovation Program (2019JZZY010704), National Natural Science Foundation of China (32072774), and Agricultural Science and Technology Innovation Program (ASTIP) of the Chinese Academy of Agricultural Sciences.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


The results show that with the increase in Co content, the saturation magnetization of Fe80−xCoxB20  amorphous alloys initially increases and then decreases upon reaching the maximum at x = 10 at.%, while for Fe80−xNixB20 , the saturation magnetization decreases monotonously with the increase in Ni content. Accordingly, for the two kinds of amorphous alloys, the obtained simulation results on the variation trends of the saturation magnetization with the change in alloy composition are in good agreement with the experimental observation. Furthermore, the relative maximum magnetic moment was recorded for Fe70Co10B20 amorphous alloy, due to the induced increased magnetic moments of the Fe atoms surrounding the Co atom in the case of low Co dopant, as well as the increase in the exchange splitting energy caused by the enhancement of local atomic symmetry.The effects of the substitution of Fe by Co or Ni on both the structure and the magnetic properties of FeB amorphous alloy were investigated using first-principle molecular dynamics. The pair distribution function, Voronoi polyhedra, and density of states of Fe Since the successful preparation of the Auc orders ,5,6. Amoc orders ,11. The The magnetic theory of amorphous alloys has been developed with the study of amorphous magnetism. Similar to the investigation of the magnetic properties of crystalline alloys, there are two main competing theories in the study of the magnetic properties of amorphous alloys, namely, the local electron theory and the itinerant electron theory. Based on the local electron theory, Corb et al. developed a coordination bond model  to explad transition elements and the average number of 3d + 4s electrons present in an atom of the alloy. When Ni or Co forms an alloy with Fe, the resulting alloy exhibits a different set of magnetic properties. The incremental addition of Ni results in the continuous decrease in the magnetic moment of the alloy. However, when Co is added to Fe, the magnetic moment increases initially and, eventually, decreases after reaching a maximum magnetic moment [Ms) of Fe-based amorphous alloys is still unclear. To date, in order to better understand the structure and properties of amorphous materials, computer simulations have been used as an effective auxiliary means of experimental observation. The computational approach provides an effective way to explore the geometric structure, electronic structure, and internal correlation of crystal state and amorphous materials at an atomic scale [80-xTMxB20  amorphous alloys are systematically studied by employing a series of first principles molecular dynamics simulation. The effects of replacing Fe with either Ni or Co on the SM of the alloy are discussed. The intrinsic relationship between local atomic structure and magnetism of Fe-based amorphous alloys is also analyzed. The most significant foundation of many studies on alloy magnetism is the discovery of the Slater–Pauling curve , which dc moment ,18. Simic moment ,20. As aic scale ,25,26,2780−xTMxB20  amorphous alloys were studied by means of the Vienna ab initio simulation package (VASP) software  based on the density functional theory [14 K/s starting from the melting state at 1600 K and the amorphous structure was thus obtained. Total pair distribution functions (TPDFs), partial pair distribution functions (PPDFs), and Voronoi polyhedra (VPs) [Fel theory . The Perl theory ,30. A cal theory . Due to ra (VPs)  were calra (VPs) , which w80−xCoxB20 and Fe80−xNixB20  amorphous alloys obtained from the experiments [80−xCoxB20  amorphous alloys is shown in Ms is achieved for a composition of Co of 10 at.%. For x > 10 at.%, the saturated magnetic moment decreases gradually. As can be seen from 80−xNixB20  amorphous alloys gradually decreases with the increase in Ni content. The calculated results of the magnetic moment of the two amorphous alloys are in good agreement with the experimental results, which indicates the validity of the simulations. As the magnetic moments of Co and Ni are significantly smaller than those of Fe atoms, when the content of Co or Ni is high, the moment decreases quickly due to the dilution effect. Therefore, the doping concentration of Co and Ni was chosen to be only 40%. However, a small amount of Co is added, the magnetic moment increases. By contrast, the magnetic moment decreases monotonically upon adding Ni. The reasons for these phenomena are described in detail in the following sections.eriments  and theo70Co10B20 alloys were chosen for analysis. The PPDFs 70Co10B20 alloys at 1600 K and 300 K are shown in Although amorphous alloy is a long-range disordered system, there still exists a short-range ordered structure. Local atomic structure of each amorphous alloy was analyzed by using PPDFs. Here, Fe80−xCoxB20  amorphous alloys after adding a small amount of Co atoms, the atomic packing characteristics were investigated via the VP analysis. The VPs of the five amorphous alloys were studied at 300 K. The VP index is expressed as 70Co10B20 amorphous alloy.In order to understand the increase in the magnetic moment of Fe80−xCoxB20  amorphous alloys was calculated based on the equilibrium structure. As the DOSs of the five amorphous alloy states are similar, the Fe70Co10B20 amorphous alloy was selected for the analysis. F) and the top of the energy band (E0). Similarly, the other four alloys are also weakly ferromagnetic. The PDOS of Fe and Co are shown in 70Co10B20 amorphous alloy are dominated by 3d states of Fe and Co. Moreover, the contribution of the p states of B to the magnetic properties of the alloy is very small, as illustrated in p states of B overlap with the 3d states of Fe and Co, i.e., there is hybridization between them. The exchange splitting energies of Fe80−xCoxB20  amorphous alloys were estimated to be 1.117, 1.127, 1.005, 0.921, and 0.851 eV, respectively. The splitting energy of the Fe70Co10B20 amorphous alloy is the highest, which may be due to the high local symmetry of this alloy. The number of perfect icosahedra in the Fe70Co10B20 alloy is higher than that in other alloys, and the icosahedron structure has a higher symmetry. This higher degree of symmetry results in an increase in the local magnetic moment [In addition, the spin-polarized DOS of Fec moment ,35, whicc moment .As the crystalline FeCo alloy has translational symmetry, however, for amorphous alloys, the fivefold symmetry is an important feature of the amorphous structure . The per80−xCoxB20 and Fe80−xNixB20  alloys. Regarding the average gain and loss of electrons, the Fe atoms in Fe80−xCoxB20 or Fe80−xNixB20  amorphous alloys tend to loose electrons and have a positive charge, while Co or Ni atoms tend to gain electrons on average. Moreover, B atoms prefer to gain electrons, which is consistent with the electronegativity of the B element. However, with the increase in Co or Ni atoms, the average electron loss of Fe atoms in both types of amorphous alloy increases gradually. The number of lost electrons is essentially related to the increase in the magnetic moment of the iron atom. As shown in d electrons of the two amorphous alloys gradually increases, and the magnetic moment correspondingly increases. For Co or Ni atoms, the difference between the number of spin-up and spin-down d electrons hardly changes, indicating that the magnetic moment of Co or Ni atoms exhibits minor changes.The magnetic behavior is mainly determined by the density and spin polarization of the electrons. To be short-range order and a long-range disorder, the structure of the amorphous alloy certainly affects the behavior of the electrons. This disordered potential field renders the electron wavefunction partially localized, so that the electrons are not uniformly distributed between the atoms. d electrons of Fe and Co (Ni) atoms was calculated, and the obtained trend is consistent with the change in the magnetic moment  alloys, in the case of a small Co content, the magnetic moment of the alloy increases at first; however, as the Co content increases, the total magnetic moment of the alloy is gradually diluted, and thus decreases. Due to the dilution effect, the magnetic moment of Fe80−xNixB20  alloys decreases gradually with the increase in the Ni content, as the magnetic moment of Ni is much smaller than that of Fe.The sum of the difference between the number of spin-up and spin-down c moment . TherefoBased on the above analysis, it was found that, with the increase in the Co or Ni content, the magnetic moment of Co or Ni atoms change little, while the magnetic moment of Fe atoms gradually increases. The reasons behind this behavior can be further analyzed from the perspective of the interaction between the neighboring atoms. Amorphous alloys do not exhibit the periodicity as crystalline solids, which are characterized by different local environments for each atom due to structure fluctuations and chemical short-order arrangement. As for the amorphous alloys investigated above, the distribution of the magnetic moment of the Fe atom is bound to be affected by the increase in the Co or Ni atom concentration. The relationship between the number of Co or Ni atoms near Fe and the average magnetic moment of the Fe atoms were determined. The four lines shown in 80−xCoxB20  amorphous alloys, the number of Co atoms near each Fe atom gradually increases upon the increase in the Co concentration, and the magnetic moment of the Fe atom increases slowly and finally reaches saturation. For Fe80−xNixB20  amorphous alloys, the number of Ni neighboring atoms increases with the Ni concentration, finally reaching saturation. The reasons for this phenomenon can be analyzed from the interaction point of view. The magnetic properties of amorphous alloys are mainly determined by magnetic atoms. The interaction is modified by increasing the number of Co or Ni atoms. It has been reported that, for the FeNiB amorphous alloy, the exchange parameter follows the order of JFe–Ni > JFe–Fe > JNi–Ni [Fe–Co > JCo–Co > JFe–Fe [For Fe> JNi–Ni . On the > JFe–Fe . This sh80-xTMxB20  amorphous alloys were studied by means of ab initio molecular dynamics simulations. The influence of the increase in the Co or Ni content on the structure and magnetic properties of Fe-based amorphous alloys was discussed. For Fe80−xCoxB20  amorphous alloys, the probability of obtaining a complete icosahedron is the highest at x = 10 at.%, which leads to a much more local structural symmetry enhancement, thus increasing the exchange splitting energy of the alloy and finally leading to the maximum magnetic moment. The magnetic moment of Fe80−xCoxB20 amorphous alloys gradually decreases due to the dilution effect for x > 10 at.%. For Fe80−xNixB20  amorphous alloys, the magnetic moment decreases continuously with the increase in the Ni content due to the dilution effect. For the two types of alloys, the trends of the calculated magnetic moments as a function of the Co or Ni composition are all in good agreement with the experimental observations.In summary, the local atomic structure and electronic properties of FeThe exchange interaction between the adjacent magnetic atoms in Fe-based amorphous alloys is closely related to the doping elements. With the addition of Co or Ni, the magnetic interaction in the amorphous alloy changes. The Co (Ni) atoms can induce a larger magnetic moment in the surrounding Fe atoms; however, the magnetic moment of the Co or Ni atoms remains almost unchanged. This is also one of the reasons why the magnetic moment of the FeCoB amorphous alloy increases with the increase in the Co content in the case of a small amount of Co doping.


The methods of fire risk assessment in its early phase employed so far used to take into account only the temperature of the heating of coal. The research works reported so far in this field have been conducted at ambient temperatures, without considering the rock mass primary temperature occurring in a particular coal seam and neglecting the depth of coal seams. The method for the determination of the composition of gases emitted from coal samples, employed in the study presented here, takes into account the effect of rock mass pressure, and therefore the depth of the coal seam, as well as the temperature typical for the rock mass in a particular coal mine. In the paper the results of the experimental research on the effects of the primary temperature of a coal seam on the content of gases emitted from coal, performed with the use of a specially designed experimental stand are presented. The method may be useful in developing fire hazard predictions for longwalls with residual coal in goafs. The relations between the self-ignition characteristics as well as selected physical properties of coal samples and carbon monoxide emission were also given. The research results proved that the accurate fire hazard assessment requires considering other than just self-heating of coal causes of carbon monoxide emission, including the rock mass primary temperature, which is expected to improve the existing methods of fire risk assessment in coal mines and post-mining areas. The fire hazard assessment in bituminous coal mining industry nowadays employs the measurements of concentration of gases released in the process of coal oxidation, including carbon monoxide, ethylene, propylene, acetylene and hydrogen6. Such methodological approach has been in use for decades and is based on the observation that the contents of the above mentioned gaseous indicators in a mine atmosphere increases with the temperature of coal self-heating. In particular, rapid increases in the contents of carbon monoxide and hydrogen are observed above the temperature of coal ignition.Exogenous fires pose a severe challenge in bituminous coal extraction practice. In recent years, research studies concerning the process of coal self-heating and the development of new methods dedicated to the assessment of this phenomena have been carried out in many countries8. The main gas emitted during the process of low temperature self-heating of coal is methane, while carbon monoxide was proven and implemented as the main indicator of the development of low temperature self-ignition of coal9. The variations in particular gaseous components concentrations in a mine air may be also independent from coal self-heating, which was demonstrated by Singh et al.10.The phenomena of coal self-heating are accompanied by numerous processes hindering the appropriate assessment of fire hazard, including the natural desorption of gases from coal13.Nevertheless, with the temperature increase, the proportions between the concentrations of particular gaseous components change, creating a specific atmosphere background for a given coal seam. Coal oxidation, under the low temperature conditions, is considered to be the predominant source of heat provided to the process of self-heating of coal in underground mines and the main gas emission driver14. The effect of an air inflow to coal beds is also studied as one of the factors facilitating the development of fires in underground mines16.In the attempts of the description of the oxidation process mechanism reported in the literature various parameters are applied in the development of kinetic models, covering coal sample weight loss, heat release, oxygen demand, as well as kinds and amounts of gaseous and solid products17. It has also been proven in studies on the impact of moisture, primary temperature, as well as the content of seam gas and reactive pyrite on coal self-heating rates at low temperatures using adiabatic tests, that gases characteristic for a mine atmosphere may be also emitted as a result of natural desorption18.When it comes to analyzing in details the sources of carbon monoxide emission it has already been reported that the two main are: coal crushing and oxidation at ambient temperature19. Carbon monoxide is also naturally present within the seams of coal  and is detected during the course of mining activities at the levels of up to several hundred ppm21. Fracturing of coal in the process of coal extraction may also itself release gases from coal structure with the values of carbon monoxide concentrations depending on the coal rank, the mode and depths of the exploitation as well as the type of the overlying rocks. Pressure and temperature also have an influence on coal sorption properties25.In the study on gas release in the process of coal production higher initial amounts and rates of gas desorption were observed for fragmented coal than for the body of coal26.Therefore, it should be taken into account that the simply mechanical factors may also affect (increase) the values of gas concentrations in a coal mine atmosphere and consequently the correctness of the assessment of coal self-heating status, performed on the basis of carbon monoxide concentrations detected in a mine atmosphere and determining the specified, legally required fire-fighting activities27 gave the principles of the calculation of the vertical roof failure with respect to rock relaxation coefficient. The increasing amount of rocks fills the post-extraction space, which finally meets the roof strata with no transformation into the roof failure state. The rock debris is bent and squeezed and in consequence cracked and delaminated by the roof strata over the full failure zone, creating the high roof failure zone of the height of 1–1.5 times of the seam thickness. The full and the high roof failure zones form the roof strata of the thickness of 3–3.5 times of the seam thickness, which enables estimation of the force effect of the roof strata on the residual coal. Thus, intensified extraction of coal creates conditions facilitating desorption of carbon monoxide from longer walls, by affecting the range of the stress relief in the surrounding bed, and therefore also the volume of the degassed bed. This makes the applicability of carbon dioxide as a coal self-heating indicator arguable28, while the enhanced release of carbon monoxide from the body of coal is considered to be useful in these terms29.In underground mining, the zone of full roof failure includes roof strata of the thickness equal to 1–2 times the thicknesses of the seam. PengCrushing of coal, taking place in the goafs of longwall increases the surface area of coal bed exposed and thus intensifies gas desorption. The depth of coal extraction affects the primary temperature of the rock mass , and therefore the rise in carbon monoxide content in a mine atmosphere cannot be considered solely as a certain prove of coal self-heating.In the light of the above, a new, more precise method of fire hazards assessment, based on the analysis of carbon monoxide concentrations related both to the primary temperature of the rock mass and the depth of a seam is needed, which was also proven experimentally in the study presented in this paper on the basis of the research results acquired with the use of the unique experimental set-up. This test stand was designed to enable simulation of the coal crushing process behind the roof support and under the conditions of the primary temperatures in the workings. Thus, the innovativeness of the approach adopted in the study presented covers two main methodological aspects: taking into account the effect of rock mass pressure  and the temperature, typical for the rock mass in a particular coal mine, and the research installation specially designed and constructed, and applicable in simulation of the process of coal crushing behind the roof support, and under the conditions of the primary temperatures in the workings. The research results presented in the paper are therefore considered to be contributing to the improvement of the fire hazard assessment in coal mines.In order to determine the amount of carbon monoxide emitted at primary temperature of the rock mass, coal was sampled from a freshly uncovered longwalls, at the largest possible mass, and transported to the laboratory in metal, airtight vessels. The physical and chemical characteristics of coal samples are given in Table The research method consists in degassing the samples of crushed coal at four temperatures. For the purpose of the study presented in this paper, the following temperatures were predetermined: 20, 30, 40 and 50 °C, reflecting the primary temperature ranges occurring in Polish mines.The crushing of coal takes place inside a research vessel without external air access. In the course of the experiment, the concentration of carbon monoxide in gaseous samples is determined. The test stand is presented in Fig. 2, N2, CH4, CO and CO2 is employed.Shimadzu GC 2014 gas chromatograph (GC) with a TCD detector, a molecular sieve column and a Porapak column for determination of concentrations of Ozcsw, is calculated as31:Wc—total moisture content, % w/w, Aa—ash content, % w/w.The content of dry and ash free coal in a sample, mcsw, is:mw—coal sample mass, g.Then the mass of dry ash free coal, Vw, and free space in the vessel are 1533 cm3 and 10,350 cm3, respectively.The volumes of coal sample, VCO, is calculated as:V0—degassed mixture volume, cm3, Sco—carbon monoxide content in degassed mixture, % v/v.The volume of CO in tested gaseous mixture, Carbon monoxide content in a sample is:32 is also determined.The self-ignition indexThe analyses of selected gaseous components release were conducted for 15 bituminous coal samples exposed to 20 MPa, simulating the rock mass pressure at the depth of 800 m and at the temperature of 20, 30, 40 and 50 °C, simulating the rock mass primary temperature in the studied coal seams. The obtained results demonstrated that carbon monoxide desorption increases rapidly with the rise in the rock mass primary temperature and the amount of carbon dioxide released varies for various samples  were low and increased above 41 °C. The exception was reported for samples 4, 5, 9 and 15, which showed high concentrations of carbon monoxide despite the fact that the rock mass temperature occurring in these seams was low and ranged from 21 to 23 °C.The correlation between the content of carbon monoxide desorbed from a coal sample and the respective moisture content and the self-ignition index value was also observed Fig. .Figure 4As it can be seen from Fig. 33. In the study presented in this paper, however, the ash content was low, in the range from 1.6%w/w (sample 3) to 10.1%w/w (sample 5) and therefore no direct impact of this parameter on carbon monoxide desorption was observed.The values of the total moisture content in coal samples tested Table  varied fcsw, was from 72.6%w/w for sample 4 to 96.4%w/w for sample 3  release in coal extraction, (ii) release from rock strata cracks caused by coal extraction, and (iii) oxidation of residual coal43.Natural desorption of gases from bituminous coal results in methane release to the atmosphere with smaller amounts of ethane, propane and carbon dioxide44 measured the carbon monoxide emission under non-isothermal conditions using an apparatus of their own design and construction, and coal type, grain size and oxygen content in coal as variables adopted in the experimental procedure. They found that the application of coal of larger particle diameters resulted in decreasing the emission of carbon monoxide, particularly at higher temperatures.Zhang et al.45 also studied the process of coal self-heating at low temperatures. In their experiment, the concentrations of gaseous products as well as the temperature inside the research vessel were measured when the coal samples were subjected to heating. Based on data analysis, four stages of the oxidation process were identified: (i) preliminary heating without oxidation reaction or volatilization, (ii) volatilization without oxidation, (iii) unevenly accelerated oxidation with parallel vaporization, and (iv) late heating stage, when the entire volume of oxygen is consumed in the oxidation reaction. Tang17 also confirmed the correlation between the grain size of coal and carbon monoxide release intensity: the finer the coal sample was ground (1–3 mm) with a ball grinder, the higher the amount of carbon monoxide was produced. The concentration of carbon monoxide released was also lower for coal samples of higher moisture content.Xu et al.46 found that the presence of certain oxidation products may facilitate identification of particular phases and the intensity of the coal self-heating process. The sequence in which the products occur varied depending on coal types. However, the mechanism of these phenomena, and in particularly the effects of various factors on the initiation and the development of the self-heating process, has been reported to be still unrecognized.Xie et al.In the research works presented in this paper the share of grains above 0.7 mm constituted above 70% of the coal sample; therefore, the analyses performed with porosimeters would not reflect the coal mine conditions. The experimental stand employed in the study allowed desorbed gas sampling at ambient pressure and with no air–derived diluting effect.On the basis of the research results presented in this paper, it may be concluded that coal samples of the highest moisture content : samples 4, 5, 9 and 15, acquired respectively from seams 212, 215, 206 and 207, at shallow depths, where the rock mass primary temperature only slightly exceeded 20 °C.Another strong correlation was observed for the primary temperature: samples 12, 13 and 14, although of I and II self-ignition groups, also showed high amounts of carbon monoxide desorbed, which resulted from relatively high rock mass primary temperature values, of 41, 43 and 48 °C, respectively. Under such primary temperatures, coals theoretically not very prone to self–ignition, when taking into account their self-ignition groups, release under the mine conditions the amounts of carbon monoxide comparable to coals particularly prone to the self-ignition process.3CO/Mgcsw; with the rock mass primary temperature below 40 °C and of the self-ignition groups of II and III .Coals emitting less than 0.001 m3CO/Mgcsw; with the rock mass primary temperature above 40 °C and of the self-ignition groups of I and II .Coals emitting over 0.001 m3CO/Mgcsw; with the rock mass primary temperature below 25 °C and of the self-ignition groups of IV and V .Coals emitting over 0.003 mTo sum up, on the basis of the experimental results presented in this paper, the coal samples studied may be divided into the following groups:The primary temperature of the rock mass surrounding the longwall affects significantly the amounts of carbon monoxide released and therefore testing of coal at laboratory temperature leads to erroneous conclusions. The same coal at the laboratory temperature will emit much lower concentrations of carbon monoxide than at the primary temperature of the rock mass. The higher is the temperature of the rock mass, the greater the error in the correct assessment of fire risk is. Since the concentrations of carbon monoxide and other gases are commonly employed as the indicators of coal self-heating progress, the desorption of gases and the factors affecting its intensity need to be taken into account, especially when coal extraction takes place at increasingly deeper depths.Coal samples 4, 5, 9 and 15, of the highest self-ignition groups (IV and V), were characterized by the highest rate of carbon monoxide desorption, despite the fact that they were acquired from shallow coal seams of relatively low rock mass temperature, of 21–23 °C.Coal samples 12, 13 and 14, of the lowest self-ignition groups (I and II), but acquired from deeper coal seams, of the rock mass temperature above 40 °C, also desorbed significant amounts of carbon monoxide.The remaining coal samples, of self-ignition groups II and III, and taken from coal seams of the moderate rock mass temperatures (below 40 °C), emitted considerably smaller amounts of carbon monoxide.The following correlations between the amount of carbon monoxide released and the physical and chemical characteristics of coal as well as the rock mass primary temperature was observed:When the depth of the coal bed (and the rock mass primary temperature) is taken into account in the method of fire hazard assessment, then the previously employed scheme of coal classification changes: coals of low self-ignition groups, under the conditions of high rock mass primary temperature, emit carbon monoxide in the amounts similar to these characteristic for coals of high self-ignition groups.The rise in the rock mass primary temperature results in intensified natural desorption of gases commonly applied as indicators of the coal self-heating process development. This, in particularly, may result in detection of carbon monoxide concentrations similar to the ones characteristic for coal self-heating.The accurate fire hazard assessment requires considering other than self-heating of coal causes of carbon monoxide emission, including the rock mass primary temperature.The methodological approach proposed in this paper is expected to improve the existing methods of fire risk assessment in coal mines and post-mining areas.On the basis of the research results presented in this paper the following conclusions may be drawn: