On-site detection of chemical warfare agents (CWAs) can be performed by various analytical techniques. Devices using well-established techniques such as ion mobility spectrometry, flame photometry, infrared and Raman spectroscopy or mass spectrometry  are quite complex and expensive to purchase and operate. For this reason, other solutions based on analytical techniques well suited to portable devices are still being sought. Analyzers based on simple semiconductor sensors may be a potential alternative to the currently used CWA field detectors. In sensors of this type, the conductivity of the semiconductor layer changes upon interaction with the analyte. Metal oxides , organic semiconductors, carbon nanostructures, silicon and various composites that are a combination of these materials are used as a semiconductor material. The selectivity of a single oxide sensor can be adjusted to specific analytes within certain limits by using the appropriate semiconductor material and sensitizers. This review presents the current state of knowledge and achievements in the field of semiconductor sensors for CWA detection. The article describes the principles of operation of semiconductor sensors, discusses individual solutions used for CWA detection present in the scientific literature and makes a critical comparison of them. The prospects for the development and practical application of this analytical technique in CWA field analysis are also discussed. Despite the signing and ratifying of the CWC  by almosSo far, the dominant analytical techniques in this field include ion mobility spectrometry-IMS ,5, flameIn addition to the above-mentioned analytical techniques, devices using simple and undemanding chemical sensors, such as electrochemical sensors , acousti2, ZnO or WO3. Despite many years since their first application, these sensors are still intensively developed and used to detect various gases [The group of semiconductor sensors includes a number of devices using various transducers , the common feature of which is the semiconductor material used as a receptor. To put it simply, the semiconductor materials used can be divided into two groups: oxide semiconductors and non-oxide semiconductors . Oxide sus gases ,17,18. OThe review of scientific works in the field of the use of semiconductor sensors for the detection of chemical warfare agents allows us to see both the material/basic research  and construction/application works . In these works, instead of actual chemical warfare agents, their simulants are predominantly used, i.e., substances with similar physicochemical properties, but with much lower toxicity.In the available literature, you can also find several review articles published in recent years on semiconductor sensors for detecting CWAs ,20,21,22In this review, we present the current state of knowledge and achievements in the field of various semiconductor sensors used to detect chemical warfare agents and their simulants. The work divides the sensors according to the criterion of the semiconductor material used, additionally distinguishing the type of transducer used. The review was mainly based on reports published in the scientific literature, but commercially available solutions are also included. The article also discusses the advantages and limitations of individual types of sensors and the prospects for their development.According to the IUPAC definition , a chemiThe construction of a semiconductor sensor is determined by the type of transducer used. Based on this criterion, sensors can generally be divided into resistive and field effect sensors. In the case of resistive sensors, a semiconductor resistor serves as a transducer, while in the case of field effect sensors, the transducer is a Schottky diode, FET or MIS capacitor.2 and O3, while reducing gases include, e.g., all CWAs and their simulants. From the point of view of the subject of this work, the principle of operation of MOS sensors during the detection of reducing gases, which is presented below, is particularly important.Due to the fact that the dominant group of semiconductor resistive sensors is MOS sensors, the principle of operation of resistive sensors will be discussed briefly on their example , oxygen ionosorption is accompanied by the depletion of electrons near the surface of the grain  and the formation of the so-called electron depletion layer-EDL. As a result, the resistance of the semiconductor will increase. In a p-type semiconductor , a hole accumulation layer-HAL will be created by removing electrons, and the electrical resistance of the semiconductor will decrease. If the grains have a sufficiently small diameter, the EDL or HAL areas may extend to their entire volume . The regional and volume depletion situations in an n-type semiconductor are shown in In the case of an n-type semiconductor  and (2) proceed at the same rate and the resistance of the sensor reaches the value Rg.The surface concentration of electrons (or holes) determines the contact resistance of the grains, i.e., the sensor signal. As a result, in clean air, a certain resistance of the sensor is established, called the base resistance Ra ≫ Rg), the change in resistance can be described by the relation [2 and k−1 are, respectively, the rate constants of reaction (2) and the inverse reaction (1); r is the grain radius; ND, donor density of the semiconductor; and PM, the partial pressure of the gas. Thus, the sensitivity  increases with decreasing grain size and carrier density. However, a decrease in grain size is accompanied by an increase in the response time of the sensor resulting from slower diffusion of gas into the porous layer and a slower rate of removal of oxidation reaction products. Relationship (3) is a particular case of the following power law:2 and CO2, as well as O2 and O3, the constant c ≈ 1/2, while for NO2 c ≈ 1 [In the case of volume depletion, when a change in resistance under the influence of the reducing gas is significant (Rrelation :(3)RgRa=O2 c ≈ 1 . In the In the literature, the relative response of the sensor for a specific concentration of vapors is usually given :The sensitivity of oxide gas sensors to reducing gases strongly depends on temperature, which results from the overlapping of several processes. As the temperature increases, the reaction rate between the analyte and the adsorbed oxygen (2) increases exponentially, and the gas diffusion coefficient into the porous semiconductor layer increases sublinearly. At lower temperatures, the limiting factor for the signal is the reaction rate of the gas with oxygen. However, at high temperatures, a sharp decrease in the sensitivity of the device is observed, resulting from a decrease in gas concentration in the reaction area. This occurs as a result of gas diffusion into the porous layer and local reduction of gas concentration under the surface of this layer. The effect of this is a non-linear dependence of the sensor response in the temperature domain with a clearly present maximum ,30. An eA special feature of MOS sensors is that the detection of gases in the air usually takes place at high temperatures (200–500 °C). Therefore, sensors of this type are equipped with a heater that ensures the appropriate operating temperature. A typical sensor consists of a substrate, a heater, a semiconductor resistor and electrodes attached to it for measuring resistance . 2O, Co3O4, Fe2O3, Cr2O3) as well as semiconductor metal oxides . If the role of the sensitizer is limited to the catalysis of the analyte reaction without changing the redox state of the sensitizer, we are talking about chemical sensitization . In this case, the sensitization is due to an increase in the reaction rate of the analyte. The sensitizer can also react with the analyte by changing its redox state. In this case, a change in the form of the sensitizer may cause a change in the resistance of the semiconductor layer by electronic interaction with the semiconductor . In such a situation, we are talking about electronic sensitization [In resistive semiconductor sensors, oxide and non-oxide semiconductor materials are used. Sensitizers , i.e., small amounts of foreign materials, are often added to the base semiconductors, which improve the sensitivity, selectivity, dynamic properties and change the optimal operating temperature of the sensors. For this purpose, metal nanoparticles are commonly used, e.g., Pt, Au or metal oxides  is baseNo redox reactions (either I or II) of the analyte occur in resistive sensors with non-oxide semiconductors. In this case, only the amount of charge carriers in the conduction band changes due to the sorption  of the detected molecules on the surface of the semiconductor material. Examples include semiconducting polymers and some types of carbon nanotube sensors.Field effect sensors use three different configurations, as shown in B value is equal to the difference between the metal–vacuum ΦM work function and semiconductor–electron affinity χ  controls the drain-source current (IDS). The current starts to flow when the threshold voltage (Vth) is exceeded and is proportional to (VGS−Vth)2, as shown in DS (VGS) characteristics, and especially the threshold voltage Vth ((1)Solid electrolyte–gate FET, where electrochemical half-cells are formed at the point of contact between metal, solid electrolyte and gas.(2)Oxide semiconductor–gate FET, in which the contact potential between the gate metal and the oxide crystals plays a decisive role.(3)th.Dielectric material–gate FET. When a porous dielectric capable of adsorbing vapors and gases is placed under the gate metal, a capacitor is formed whose capacity depends on the gaseous environment. Highly polar vapors change the dielectric constant of the capacitor, which results in a change in the electric field and a shift in the threshold voltage VIn the FET, the voltage applied between the gate and source , which is a commonly used sarin simulant. The mechanism of the DMMP reaction on the surface of a semiconductor sensor has been studied many times and is well described in the literature ,37,38,392  is permanently adsorbed on the surface of the semiconductor  and with the simulant of nitrogen mustard-di(propylene glycol)monomethyl ether (DPGME). There is also work describing research with actual sulfur mustard . In addi2, H2O, NO2, Cl2 or SO2, which do not cause contamination of the sensor surface . An exaensor [3 :(6)2-CEEAt 300 °C, the 2-CEES molecule breaks down into radicals on the surface of the semiconductor. These radicals then react with adsorbed oxygen ions to release electrons. In this case, the sensor poisoning effect was not observed ,45,46. I2, ZnO) were used to detect vapors of organophosphorus compounds was published in 1993 [2, ZnO and other semiconductor oxides.Historically, the first paper in which MOS sensors  applied to the sensor surface by screen printing or in the form of pressed disks [The first generation of semiconductor materials used in the detection of chemical warfare agents and their simulants were polycrystalline  powders, mainly SnOed disks ,53,54,55ed disks ,57.2 thick film sensors used for DMMP, DPGME, ACN and DCM detection. In this study, SnO2 sensors differing in grain size (40 and 15 nm) and applied dopants  were used. The sensors were operated at 350 °C and exposed to a gas stream with concentrations of simulants ranging from 0.02 to 0.8 ppm. The presented results showed the influence of the grain size, porosity of the semiconductor layer and the type of dopant used on the sensitivity, selectivity and dynamic parameters of the sensors. It was found that dopants significantly affect the sensitivity of the sensor. An example may be a sensor with SnO2 doped with NiO, for which the response to DPGME, DMMP, DCM vapors increased by 24, 38 and 1300%, respectively, compared to the undoped sensor. Significant observations also concerned the recovery time of the sensors. In the case of DMMP and DCM detection using undoped SnO2 sensors, prolonged recovery times and a decrease in sensor sensitivity were observed. These phenomena were attributed to the poisoning of the sensor surface with the products of analyte oxidation. The magnitude of the poisoning effect was significantly reduced in the case of the MoO3-doped sensor.Paper  describe2 layer doped simultaneously with NiO, MoO3 and Sb2O3 was developed, which reportedly showed no poisoning effect during DMMP detection. The influence of individual dopants on the properties of the sensor was empirically identified: the addition of NiO improved the signal amplitude, while MoO3 and Sb2O3 shortened the sensor recovery time. Similarly, work [2 sensor for detecting DCM. In this case, the participation of NiO in the improvement of the response to DCM and MoO3 and in the reduction of recovery time was also found.The issue of optimizing the content and composition of dopants towards eliminating the poisoning effect was developed by the same research team in subsequent works ,51. In wly, work  describe2 sensors during DMMP detection are described in [2 nanoparticles. SnO2 nanoparticles were obtained by the hydrothermal method and had a diameter of approximately 10 nm. Ni, Sb and Nb were used as dopants. As a reference, the sensor with a commercially available SnO2 nanopowder  was used. The results revealed that the sensors with synthesized, undoped SnO2 had a much higher sensitivity to DMMP than the sensor with commercial powder . The increase in sensitivity was attributed to the larger specific surface area of the nanoparticles. At the same time, the sensors with synthesized SnO2 returned to equilibrium much slower after switching off the DMMP. Doping with metals significantly shortened the response and recovery times. Particularly good results were achieved for sensors doped with 5% wt. Ni. As reported by the authors, this sensor was characterized by a complete signal recovery in less than 10 min after the DMMP was turned off. At the same time, doping SnO2 with Ni significantly reduced the sensitivity of the sensor.Further studies, aimed at improving the dynamic parameters of SnOribed in . The aut2 sensors were also studied. In the cited publication, they were used to detect CWAs simulants such as DPGME, DMMP, DCM and ACN. The research was aimed at investigating the influence of the porosity of the semiconductor layer on the sensitivity toward individual analytes. For this purpose, sensors with four different SnO2 materials, characterized by different specific surface areas and pore size distribution, were prepared. The results showed that the sensitivity of the sensor is influenced not only by the total specific surface area of the semiconductor layer, but also by the pore size distribution of the layer. For this reason, the sensitivity towards individual analytes differing in mass and molar volume does not increase monotonically with the increase in specific surface area. Research showed that sensors with larger pore sizes were more sensitive to larger molecules (DMMP and DCP). At the same time, materials with a higher specific surface area, but available mainly in micropores, showed lower sensitivity towards these substances.In , thick-f2 film were also investigated in [2 was presented, which was used to detect real sarin gas (GB). The use of controlled ethanol aging (exposure to 100 ppm ethanol vapor in air at 300 °C for 12 h) significantly changed the performance of the sensor during GB detection. The sensor at a temperature of 300 °C showed unusual behavior for a sensor with an n-type semiconductor in the presence of reducing GB. As a result of the sorption of this gas, the resistance increased as in the case of oxidizing gases. At the same time, the effect was not observed with DMMP. Additionally, at 400 °C, the anomalous behavior towards GB was no longer observed. The authors explain this phenomenon by the adsorption of -CHx groups on the SnO2 surface as a result of previous exposure to ethanol. During the detection of GB, the fluorine atom present in GB captures electrons from the -CHx groups and, thus, also from the semiconductor layer, causing an oxidative response of the sensor (increase in resistance). Parallel to this process, GB is oxidized by interaction with Oˉ, and electrons are released into the semiconductor. However, the result of these processes is an increase in the resistance of the sensor. As research has shown, the sensor can detect GB at a very low concentration of 6 ppb and distinguish GB from DMMP.Sensors with a porous SnOgated in . In this2/Si3N4 in the form of a square-shaped membrane with a side of 150 μm and a thickness of 1 μm. The membrane, which was integrated with the heater and platinum IDEs, was suspended over the bulk silicon slice via four slender cantilever beams. A film with SnO2 was then applied to the membrane surface by the sacrificial template method. In the case of this method, the semiconductor layer is produced using a template , thanks to which it was possible to deposit a highly ordered monolayer of SnO2 nanospheres from a liquid solution . The produced sensor was characterized by a significantly reduced power consumption . A deta0–300 mW .2 as the basic semiconductor material, the following dopants were most often used: Pt, Pd [2, Al2O3, In2O3 [2O3 [3O4, Nb2O5, MoO3, NiO, Sb2O3 [2 doped with different contents of metals  or metal oxides . Semiconductor materials were prepared by methods such as impregnation , physical milling  or co-precipitation . Sensors prepared by screen printing were tested in the presence of DMMP, DPGME, DCM and ACN. As the research showed, the addition of sensitizers significantly influenced the sensitivity of the sensors to individual substances. From among the prepared sensors, four characterized by good sensitivity and stability were selected and used in a sensor array. The analysis of the four-dimensional signal was based on the principal components analysis. As the results showed, the array successfully distinguished vapors of individual simulants.A very problematic issue in the case of MOS sensors is the relatively low selectivity resulting from the fact that their principle of operation is based on rather non-specific oxidation and reduction reactions taking place on the grain surface. One of the ways to improve selectivity is the use of appropriately selected dopants. In the case of sensors with SnO: Pt, Pd ,53, ZnO,2O3 [2O3 , Co3O4, O, Sb2O3 . In most2 thick films. In the manufacturer’s catalog, individual sensors are described as intended for detecting various organic solvents and gases, but not as targeting CWAs. The intention of the authors was, therefore, to create an array of sensors for CWA detection that meets the definition of a dual-use device. The ability to selectively detect CWAs was to be ensured by using a relatively large number of different MOS sensors and using statistical analysis to interpret the multidimensional signal of the array. In the work, measurements were carried out with nerve CWA simulants such as diethyl diethyl cyanophosphate (DCNP), diisopropyl fluoride, chlorophosphonate and their derivatives, as well as some interferents. As the results showed, the array distinguished individual organophosphorus analytes. In addition, on the basis of the signal, a quantitative analysis was possible  of 5 ppm was obtained). Despite the fact that the authors of the study found that the array may be suitable for detecting actual CWA in the field, the LOD values obtained for DCNP significantly exceed the immediate dangers to life or health (IDLH) values of nerve agents [Another work aimed at improving the selectivity of MOS sensors is . The pape agents . NoteworThe use of polycrystalline sensor layers, especially those made of coarse grains, is associated with certain limitations. Larger grains are characterized by a lower surface to volume ratio, which limits the active surface on which redox reactions with analyte molecules can take place. Moreover, in the case of such grains, the depletion in charge carriers usually concerns only the surface layer of the grain , and not its entire volume. This results in less change in the conductivity of the layer due to depletion . For thi2 and In2O3 nanowires and sensors equipped with traditional polycrystalline oxide layers. Semiconductor nanowires were fabricated using the vapor–liquid–solid (VLS) method. In this method, semiconductor powders are thermally evaporated and then absorbed to a supersaturated concentration in droplets of a catalytic liquid platinum alloy deposited on a sensor substrate. By maintaining appropriate thermodynamic conditions, the growth of single-crystalline nanowires is obtained in accordance with a specific crystallographic direction at the substrate–liquid alloy interface. In the cited paper, sensor responses to vapors of DMMP, DPGME, ACN and other substances  were tested. Research has revealed a higher sensitivity of sensors with nanowires than with traditional films to DMMP and DPGME vapors . At the same time, lower sensitivity to other gases, such as NH3 and CO, was observed. For all sensors, a strong signal drift was observed, indicating the occurrence of the poisoning effect. The sensor responses were also statistically analyzed to determine their suitability to the sensor array. The authors found that due to significant differences in sensitivity to individual substances, it is advisable to use both sensors equipped with nanowires and traditional polycrystalline films in the array.The work  presents2 films were also compared. The research focused on the qualitative and quantitative description of the sensor poisoning effect by phosphorus compounds during DMMP detection. Research includes testing sensor response to ethanol (25 ppm) and DMMP (0.2 ppm) vapors. The sensors were exposed alternately to these two gases to examine the degree of signal reduction from ethanol under the influence of DMMP poisoning. Studies have shown that the poisoning effect occurs on a similar scale for both types of semiconductor layers. The authors found that the drift of the sensor response in the short term is mainly caused by the contamination of the surface with phosphorus compounds. After a longer period of time without exposure to DMMP , however, these compounds desorb, and full recovery of the sensor response was possible.A continuation of the above research was presented in . In this2 nanowires for the detection of DMMP and ACN has also been described in [The use of sensors with SnOribed in . The stu2 nanobelt. The aim of the authors was to create a sensor free of grain boundaries. Tests conducted at 500 °C showed that the sensor relative signal reached 5 and 3% at 78 and 53 ppb of DMMP, respectively. Additionally, the authors did not observe the poisoning effect commonly seen with polycrystalline sensors. Noteworthy is the interesting design solution of the sensor setup. To ensure good thermal insulation, a system consisting of a single SnO2 nanobelt and a heater  was suspended in gas on silicon nitride fibers. Thanks to this, it was possible to significantly reduce the energy consumption of the sensor.Interesting research results are also presented in , which d2 decorated with Au nanoparticles was presented. Modification of commercial SnO2 consisted of reaction with (CH3)2SnCl2 and then calcination in air atmosphere. As a result, a significant increase in the concentration of oxygen vacancies on the semiconductor surface was obtained . The sensor prepared in this way was used to detect DMMP. The sensor obtained a relative signal of about 19% at a DMMP concentration of 240 ppb at 320 °C. The detection limit was estimated at 4.8 ppb. The sensor was also characterized by above-average dynamic parameters with response and complete recovery times of 26 and 32 s, respectively. Such good sensor properties were attributed by the authors of the cited paper to the total effect of three mechanisms: increasing the number of oxygen vacancies by modifying the surface with (CH3)SnCl2, creating metal-semiconductor junctions and thus better modulating the conductivity of the layer and the catalytic effect of Au nanoparticles. The sensor testing results presented in the cited paper are among the best obtained so far for SnO2 sensors. It is noteworthy that, in this case, at the optimum operating temperature (320 °C), no poisoning was found, and the sensor was completely reversible.In the recently published work , a sensoetail in ). Au nan2, ZnO is an n-type semiconductor.ZnO is also often used in MOS sensors to detect CWA simulants ,68,69,70In , a sensoThe work  presents3, CO and NO were 0.73, 0.14 and 0.11, respectively). As stated by the authors, Al doping increases the concentration of oxygen vacancies on the ZnO surface. As a reason for observing a strong amplification only in the case of Al, the authors indicate a different electron configuration of this element with three valence electrons . Nevertheless, the work does not provide a detailed explanation and deeper analysis of this issue.In subsequent work published by the same scientific group , it was 3, which thus did not interfere with the detection of 2-CEES. The intention of the authors was to significantly improve the selectivity of MOS sensors through the use of a combined technique. As the results of the analyses showed, the device was indeed characterized by above-average selectivity, at the cost of a significant complexity of construction. It is also worth paying attention to the parameters of the sensor produced as a detector in the GC system. The sensor was characterized by much higher sensitivity than the previously described solutions. In the case of 20 ppm 2-CEES at 450 °C, a relative signal of 5395 was obtained. The outstanding sensitivity was attributed to the effect of the size of the synthesized nanoparticles .The issue of Al-doped ZnO was continued in . This pa3+ ions replace Zn2+ ions in the crystal lattice of the semiconductor. Due to the smaller ionic size, Al dopants can generate more oxygen vacancies and act as preferential adsorption sites for DMMP. A significant achievement in the field of semiconductor sensors for DMMP detection is described in . The autB—Boltzmann constant, ΔΦB—change in height of Schottky barrier, T—temperature.One of the ways to improve the sensitivity of MOS sensors is the use of dopants that form semiconductor junctions or metal–semiconductor junctions with the base semiconductor. When two different semiconductors come into intimate contact, due to the differences in the Fermi levels of both materials, energy bands will bend at the contact surface and a potential barrier (Schottky barrier) will be created. Changes in the concentration of charge carriers caused by the redox reaction, taking place on the surface of the semiconductor, affect the height of the created barrier and, thus, also the conductivity of the material. Changes in the conductivity of the layer in the case of an n-p heterojunction are proportional to the height of the potential barrier as follows :(9)ΔR~ex3, CO, NO and NO2 values of relative signals did not exceed 50). In addition, the response time of the CuO/ZnO sensor to DMMP was almost 13 times shorter than that of the ZnO sensor . The studies have shown that the addition of CuO causes a significant increase in sensor resistance in clean air, which may be caused by the expansion of the EDL by the formation of p-n junctions. At the same time, during exposure to DMMP, the width of the depletion area is reduced, and the resistance decreases to a value close to the value achieved by a sensor with pristine ZnO under the same conditions. As a result, the modulation of the sensor signal is four times wider than in the case of a sensor with pristine ZnO. A detailed analysis of the results contained in the cited publication also allows us to draw conclusions about the short-term repeatability of the sensors. It is clear that the sensors show a decrease in the sensitivity to DMMP during subsequent, repeated exposure cycles. This phenomenon has already been mentioned for SnO2 sensors and results from the poisoning of the sensor surface with phosphorus compounds.Particularly interesting results for a system of this type have been described in . In this2 and ZnO-based materials, other oxides were also used in MOS sensors for the detection of CWAs and their simulants. These include materials such as: WO3, In2O3, CuO [2, Mn3O4 [3 [In addition to SnO2O3, CuO ,56,72, M2, Mn3O4 ,73,74,75Mn3O4 [3 ,46.3 and In2O3 used for the detection of actual CWAs and their simulants. The list of analytes included sarin, soman (GD), sulfur mustard (HD) and simulants . Both tested sensors showed high sensitivity to CWAs and estimated GB and HD detection limits of 10 ppb at 400 °C. In addition, the sensors were found to be much more sensitive to live agents than to their simulants. An interesting observation was the trend of increasing the sensitivity of the WO3 sensor in the group of organophosphorus compounds: DMMP-GB-GD. This phenomenon was attributed to the increase in the number of methyl groups in the analyte molecule. During adsorption of the analyte, these groups are oxidized and constitute a source of additional electrons. As in the case of DMMP for GB and GD, the sensors showed poisoning.The work  presents3 and Pt-doped CdSnO3 are described. Several sensors with different thicknesses of semiconductor films were manufactured and tested. As determined by X-ray diffraction, CdSnO3 grains were characterized by an average diameter of less than 5 nm. The films were deposited using the ultrasonic spray pyrolysis technique. The manufactured sensors were used to detect sulfur mustard simulants: 2-CEES and CEPS, as well as a sarin simulant-DMMP. The study revealed that both undoped and platinum-doped sensors were highly sensitive and selective towards 2-CEES. In the case of the undoped sensor (with a film thickness of 1.87 μm) at 350 °C, the signals for 4 ppm 2-CEES, CEPS and DMMP were: 12.05, 2.04 and 2.14, respectively. Under the same conditions at 250 °C, the signals for the Pt-doped sensor  reached 58.63, 6 and 3.85. As the results showed, Pt doping significantly increased the sensitivity to 2-CEES and lowered the optimal operating temperature of the sensor from 300 to 250 °C. In addition, as the authors indicate, the dynamic parameters of the sensor have improved.In , sensors3 sensors focused on Ru doping [3 and platinum-doped CdSnO3 [3 sensor, a much shorter response and recovery time was obtained . In the case of the Pt-CdSnO3 sensor, it was 30 and 300 s, respectively. It is worth noting, however, that these values were obtained at the optimal operating temperatures of the sensors, for Ru-CdSnO3: 350 °C and for Pt-CdSnO3: 250 °C. Due to the much lower operating temperature, which is reflected in the electrical power consumption and long-term stability, the Pt-CdSnO3 sensor is also worthy of attention.Further work on CdSnOu doping . In thisd CdSnO3 , it can 3O4 and MnO2 sensors have also attracted a lot of interest [3O4 layers manufactured by the chemical vapor deposition (CVD) method. Deposition of the layers was carried out in an oxygen atmosphere in the presence of water vapor and in dry oxygen, which resulted in obtaining films with different surface morphology and grain sizes . The sensors were tested in the presence of CH3CN (hydrogen cyanide simulant) and DMMP. The results showed that the sensor manufactured in a humid oxygen atmosphere was more sensitive to CH3CN than the second sensor. At the same time, both sensors have similar sensitivity to DMMP. Unfortunately, in both cases, significant sensor poisoning was observed during the detection of DMMP. Mn3O4, as a p-type semiconductor, decreased its conductivity under the influence of the detected reducing gases . The response time for CH3CN at 300 °C at a concentration of 2 ppm was 1 min, and the recovery time was 8 min. DMMP at 200 °C at a concentration of 0.5 ppm was detected with a response time of 0.83 min; however, severe sensor poisoning occurred. The LOD for CH3CN was estimated at 0.6 ppm and for DMMP at 0.04 ppm.Recently, Mninterest ,73,75. Tinterest  describe3O4 sensor is described in [3O4 sensors doped with Au and Ag. The sensor layers were manufactured by depositing Mn3O4 with the CVD method on the substrate (40 nm grains were obtained) and then introducing metal nanoparticles onto it by radio frequency sputtering. The tests of the sensor’s response to DPGME and other substances  revealed that among the prepared sensors , the Au-Mn3O4 sensor has the highest sensitivity and selectivity towards DPGME. The estimated DPGME detection limit for this sensor was 0.6 ppb (in contrast to 50 ppb for the sensor with undoped Mn3O4). This effect was attributed to the formation of Schottky junctions in the Au/Mn3O4 system  to Ag(I) during deposition on Mn3O4). The formation of metal–semiconductor junctions enabled higher modulation of HAL during interaction with the analyte. The optimum operating temperature of the Au-Mn3O4 sensor was only 200 °C, while for the other sensors, it was 300 °C. Nevertheless, it was found that during the detection of DPGME, there is a slight poisoning resulting in a prolonged time of complete recovery . This effect was attributed to the low operating temperature of the sensor, which reduced the rate of desorption of products formed during DPGME oxidation. Taking into account the high sensitivity, reversibility and selectivity of the Au-Mn3O4 sensor, it can be concluded that the results presented in this paper are a significant achievement in the field of nitrogen mustard simulant detection. It is also worth noting that the DPGME LOD of 0.6 ppb is many times lower than the IDLH of nitrogen mustard. For this reason, a sensor of this type can potentially be used in devices for the selective detection of DPGME.Another application of the Mnribed in . In this2), which is an n-type semiconductor. Sensor layers were produced using the plasma enhanced-CVD method, which allowed obtaining elongated MnO2 nanoparticles with dimensions of 600 × 90 nm. Then, using radio frequency sputtering, CuO and SnO2 dopants were applied. Doping MnO2 with other semiconductor oxides was aimed at producing p-n (CuO/MnO2) and n-n (SnO2/MnO2) semiconductor nanojunctions . The SnO2/MnO2 sensor allowed the detection of DPGME and DMMP with LODs of 0.1 ppm and 2.3 ppb, respectively, at 250 °C. However, the analysis of the results presented in the paper did not allow deeper conclusions about the selectivity of the CuO/MnO2 and SnO2/MnO2 sensors. In work , another8–109 A/cm2) and excellent temperature stability [2/g) and their electrical properties strongly depend on the environment. These features have made them widely used in gas sensors. CNTs come in the form of single-walled tubes , which can be metallic or semiconductor, and multi-walled , mainly metallic. The planar equivalent of carbon nanotubes is graphene, which has also found wide application in gas sensors.Carbon nanotubes (CNTs) exhibit extraordinary electrical properties, such as ballistic transport over a few hundred nanometers, high current-carrying capacities , the conductivity of the semiconducting SWCNTs can be modulated by applying a gate voltage (VGS). The device exhibits the characteristics of a p-type transistor in air, as the atmospheric oxygen atoms adsorbed on the semiconductor SWCNTs pull out electrons and create holes. The gate voltage modifies the height of the Schottky barrier built at the junction of the semiconducting SWCNTs electrodes/metal interfaces, and thus the probability of holes passing from the electrodes to the valence band of the semiconducting SWCNTs. The presence of the analyte changes the voltage–current characteristic of the transistor, in particular, the threshold voltage (Vth). The direction of these changes depends on whether the analyte is an electron donor or acceptor , the typical LOD is at the level of a single ppb. The response times of these sensors depend on the structure of the SWCNT layer and are several seconds for single nanotubes. The response time of sensors with thick layers of CNTs is limited by the diffusion rate of the analyte into the bulk of layer, as in the case of oxide sensors. A certain problem is the recovery of SWCNT sensors, as it usually requires many hours of air flushing or a significant increase in temperature, usually to about 200 °C. In FET sensors, this process can be accelerated by changing the polarity of the VDS. In this way, a complete recovery was obtained in 200 s [SWCNT field-effect transistors are much more sensitive than MOS sensors and, unlike them, can operate at room temperature. For simple gases -functionalized aniline (HFiPA) . SWCNTs In the work cited above, the selectivity and sensitivity of the sensors were ensured by the HFiP group, which forms hydrogen bonds with organophosphorus compounds. The hexafluorobisphenol moiety works in a similar way. Both groups have been widely used in SWCNTs sensors for DMMP detection ,87.In , hexafluWang  studied 3Cl, hexane, acetone, CH3OH, water).The work  presentsIn paper , polyaniThe use of polyaniline as a coating for multi-walled carbon nanotubes (MWCNTs) was presented in . In addiIn addition to polymer coatings, metal oxides have also been used. An example is a sensor with an SWCNT layer covered with ZnO . Using sAn unprecedented type of coating was used in . In thisMWCNT functionalized with thiourea groups was used to detect DMMP in . The senGraphene is a planar equivalent of CNTs and, as such, is used in resistive and field effect gas sensors ,99,100. In , reducedThe type of chemical compound used for the reduction of graphene oxide has a large impact on the properties of graphene as a sensor material . In the In , the proIn a paper published in 2021, graphene in the form of quantum dots (GQD) combined by a strong π-π bond with cobalt phthalocyanine (PC) derivatives was used . Graphen2.Graphene analogs are two-dimensional nanomaterials obtained from elements of group IVA and VA. One of them is ε-arsenene, which is a nanosheet of the allotrope of arsene. It was used in a sensor for detecting sulfur mustard simulant-2-chloroethyl dichloromethyl sulfide (CECMS) . Using tOne type of sensor layer is materials in which semi-conductive organic polymers are mixed with carbon black . The mix2. The sensor obtained in this way was characterized by high mechanical durability. It was used to detect DMMP. Both MnO2 and CNS participated in the detection process according to the charge-transfer mechanism, causing an increase in the resistance of the sensor layer. The detectability of the MnO2/CNS sensor was clearly better than the CNS sensor used here as a reference. In the first case, DMMP could be detected at 0.1 ppb, and in the second at 0.1 ppm. The sensor showed good stability and reversibility. At the same time, the MnO2/CNS sensor showed high selectivity to DMMP in the presence of acetone, benzene, chloroform, dimethylformamide, ethanol, hexane and toluene.In , a flexiSignificant progress in the technology and availability of carbon nanostructures and 2D materials has enabled dynamic development in the field of non-oxide semiconductor sensors. In contrast to MOS-type sensors, these materials offer much wider possibilities of tailoring selectivity. Especially the use of functionalizing carbon materials with specific polymers gives good results and it seems that thanks to these materials, it will be possible to build ready-to-use sensors in the near future.In the case of non-oxide sensors, it is also very important that they usually work at lower temperatures than MOS sensors, which translates into lower electricity consumption. For a single sensor, power consumption of 100–300 mW  is acceptable even for portable devices. However, in the case of a sensor array composed of several or a dozen or so sensors, the total energy consumption can be a big problem. This issue is all the more important because, so far, a very effective way to improve the selectivity of devices based on semiconductor sensors has been the fabrication of arrays.Despite the apparent advantages, many issues related to non-oxide sensors remain to be resolved. Of particular importance is the improvement of recovery time. In this case, methods involving the use of IR lamps, a laser or reverse polarity in the case of FET transistors seem very promising and may result in implementations in ready-to-use devices in the future.Organic semiconductors, e.g., in the form of polymers, have also been used as active materials in semiconductor sensors ,108. Sem2-Pc), were obtained. The layers were prepared by depositing 100 nm phthalocyanine and 10 nm palladium on the substrate. DMMP and several other organic compounds have been detected using such sensors. Under the influence of DMMP, the primary resistance of the sensor decreased. As the research showed, the sensor with H2-Pc was characterized by better DMMP detection than the sensor with Co-Pc. Methanol, ethanol, iso-propanol and water vapor did not interfere with DMMP detection at 10 to 60 ppb in the H2-Pc sensor and 10 to 300 ppb in the Co-Pc sensor.In the literature, one can find sensors with active layers made of phthalocyanines ,110. In 2. The following phthalocyanines were used as semiconductor sensor layers: metal-free, cobalt, nickel, copper and zinc. Using the produced sensors, DMMP and eleven other chemical compounds from the group of Lewis bases and forming hydrogen bonds with phthalocyanines were detected. The detection of individual substances was related to the enthalpy of the analyte–phthalocyanine interaction. The enthalpy value also affected the recovery time. In the case of metal phthalocyanines, the mechanism of interaction of the analytes with them was related to the Lewis basicity. The interaction of the analytes with metal-free phthalocyanine was associated with the formation of hydrogen bonds.Several different phthalocyanines were also studied in . Thin laSemiconductor sensors are a diverse group of devices whose common feature is the semiconductor material used as a receptor. It has been 61 years since the construction of the first semiconductor gas sensor , and theAs shown in this review, many papers have been published over the years on the use of semiconductor sensors in the detection of CWAs and their simulants. In some of them, systems characterized by very good sensor properties, such as the detection of toxic substance simulants at the level of single ppb , high sThe analysis of the studies presented in this review indicates that the selectivity of the sensors is still a big problem. The methods used to improve selectivity, especially in the case of MOS sensors, are insufficient, and in most studies, they are based on an empirical approach and not on the principles resulting from the analysis of the sensor operation mechanism. Significantly more advances in improving selectivity have been made with sensors using non-oxide semiconductors, which often rely on more selective interactions with the analyte  than with MOS sensors. The approach involving the construction of sensor arrays also seems promising.In conclusion, despite significant achievements in this field, the CWA detection technique based solely on semiconductor sensors is rather far from being implemented in commercial devices. A number of unsolved problems, the biggest of which is poor selectivity, have meant that, despite many years of research, it has not been possible to build ready-made devices so far. On the other hand, sensors using oxide-free semiconductors have great potential. In this case, the possibilities of obtaining highly selective sensors are much greater than for MOS sensors. In addition, these sensors typically operate at room temperature, unlike MOS sensors, which typically operate at temperatures of 300–500 °C.In our opinion, further development of semiconductor sensor technology will focus on sensors with non-oxide semiconductors . This development will be possible thanks to the increasingly better mastered technology and the improving availability of carbon nanomaterials used for their construction.


Autism spectrum disorder is a heterogeneous group of disorders that affects virtually every population, regardless of their ethnic or socioeconomic origin. The pathogenesis of ASD is probably multifactorial, based on interactions between genetic and environmental factors. Their key elements are disorders in the field of social communication, establishing and maintaining relationships and the so-called stereotypical and repetitive patterns of interests and activities. However, of the above- mentioned symptoms, the most important are communication disorders, which are the basis for many of the functional difficulties observed in these patients.The aim of the presented study was to analyze the clinical picture of social cognition deficits in males with autism spectrum disorders, and to link its elements with the frequency of alleles of selected polymorphisms within the OXTR and AVPR1A genes.The study included 132 people, 77.5% of whom were male (n = 100). 113 participants (85.6%) were diagnosed with autism spectrum disorders confirmed by the ADOS-2 test conducted by a certified diagnostician. In this group, men constituted 76.1% of the population (n = 77). The remaining 28 people did not have a diagnosis of autism spectrum disorders, and in the ADOS-2 study they obtained the result below the cut-off level. The mean age in the whole group was 14.4 years (95% CI: 13.92-14.93).A higher frequency of the rs53576 A allele and the rs10877969 C allele could be observed than expected on the basis of the European / world population. In the case of the rs7294536 and rs2254298 polymorphisms, no differences in the distribution of alleles in relation to the expected values were observed. In the network analysis reference allele (T) of SNPs rs10877969 was linked to the higher outcome of the “social affect” domain of ADOS-2 and through it influenced ADOS-2 outcome. All other SNPs did not significantly affect neither domain of ADOS-2. Reference allele (A) of rs53576 was linked with higher odds ratio of clinical diagnosis of ASD in logistic regression. Similarly the rs10877969 polymorphism within the AVPR1a gene significantly shaped the risk of autism spectrum disorders, while in the combined analysis with rs7294536 within the haplotype, the observed effect was significantly stronger.The studied polymorphisms may constitute an element of larger haplotypes which, depending on the number of mutated alleles, may determine the severity of autism spectrum traits, from the neurotypical population, through people with a broad autism phenotype, to people diagnosed with ASD. Further research is required on the potential clinical application of genotype analysis of the studied polymorphisms and on the exact mechanism of their impact on the risk of ASD and the development of social cognition disorders.None Declared


In the present study, we investigated the antiviral activities of 17 flavonoids as natural products. These derivatives were evaluated for their in vitro antiviral activities against HIV and SARS-CoV-2. Their antiviral activity was evaluated for the first time based on POM (Petra/Osiris/Molispiration) theory and docking analysis. POM calculation was used to analyze the atomic charge and geometric characteristics. The side effects, drug similarities, and drug scores were also assumed for the stable structure of each compound. These results correlated with the experimental values. The bioinformatics POM analyses of the relative antiviral activities of these derivatives are reported for the first time. The renin-angiotensin-aldosterone system (RAAS) is one of the human body’s main systems and is of crucial importance in the regulation of most physiological and pathophysiological conditions, including vascular tone and blood pressure (BP), remodeling of the vascular wall and heart muscle, mechanisms of development and progression of atherosclerosis, glomerulosclerosis, and other pathologies ,2,3,4,5.The use of inhibitors that affect the renin–angiotensin system may be a promising therapeutic strategy for combating coronavirus infection. Preliminary data on the use of ACE2 inhibitors, drugs containing this receptor in circulatory form, and angiotensin receptor II blockers indicate their effectiveness and the possibility of improving the condition and prognosis of patients with coronavirus infection taking ACE2 inhibitors ,11.Thus, when developing drugs to combat coronavirus infection, inhibitors of the ACE2 protein can be considered a promising group of compounds for the creation of new antiviral agents. The search for effective ACE2 blockers among various natural compounds can be conducted empirically using traditional viral models. However, this approach requires a large amount of work and considerable material costs. Therefore, in the first stage of assessing the potential capabilities of compounds, it seems appropriate to simulate their activity by molecular docking using computer programs. The promising structures selected based on the results of such a study can then be studied in more detail using appropriate experimental models, which will reduce both material costs and development time ,17,18. δ−, O′ δ−, O″ δ−) that are regenerated from parent flavonoids and their metabolites.In the present work, computer docking and POM analyses of several polyphenolic and triterpenoid compounds were carried out and their possible effect on angiotensin converting enzyme 2 (ACE2), which contributes to the transport of the COVID-19 virus into the host cell, was evaluated. The POM theory was of great help in the identification of two antiviral pharmacophore sites -1R42 model was chosen to analyze possible inhibition  19]..19].A computer simulation of the interaction of 50 plant compounds of various chemical natures with the ACE2 protein was carried out, and the binding activity of the studied structures with the protein was evaluated. The analysis considered the position at which the binding energy of the protein to the ligand was the best .The interaction activity of the analyzed drugs was compared with that of standard drugs used to inhibit ACE2. Computer analysis of the selected compounds revealed that the energy used for the ligand binding to the protein ranged from −7 to −10 kcal/mol .Based on the fact that the selected standard comparison drugs used to inhibit ACE2 in order to reduce pressure had binding energy ranging from −6 to −8 kcal/mol , we determined the cut-off value of the binding energy of the protein to the ligand as −7.4 kcal/mol. The use of this threshold value allowed us to identify 17 compounds with potentially high inhibitory properties in relation to the ACE2 protein .Compounds with a binding energy of the protein to the ligand below the selected cut-off value were divided into two equal groups, the first of which mainly interacted with the second allosteric activity center of the ACE2 protein and the second of which mainly interacted with the third allosteric activity center .The RAAS is of paramount importance in the regulation of most physiological and pathophysiological conditions, from the level of blood pressure (BP) to the mechanisms of development and progression of atherosclerosis ,2,3,4. THighly conserved amino acid residues Lys 31, Glu35, Asp38, Met82, and Lys353 were identified in the ACE 2 structure, four of which were located in the N-terminal part of the ectodomain of the enzyme responsible for interaction with the COVID-19 S protein . TherefoThe search for compounds affecting the orthosteric site of ACE2 showed that these are mainly short peptides or drugs, based on the use of monoclonal or polyclonal antibodies ,21. SimuThus, it was shown that computer modeling makes it possible not only to detect whether a ligand is able to interact with a particular protein but also to evaluate the mechanism of action of such compounds. The results obtained can be used for the preliminary assessment of the activity of compounds in the development of new effective drugs.POM Theory (Petra/Osiris/Molinspiration), which was proposed by a group led by Taibi Ben Hadda in collaboration with the American NCI and TAACF, has led to great success in the pharmacology and drug-design fields of antibacterial, antifungal, antiviral, and antiparasitic agents ,90,91,92Here, we treated a series of natural products 1–17 with the goal of identifying their antiviral pharmacophore sites according to the POM organigram. The identification of pharmacophore sites for these compounds was derived from the physical and chemical properties of the tested compounds using a bioinformatics POM platform . The results of the pharmacokinetic properties and bioactivity score analysis are shown in the The result of the Molinspiration analysis is presented in the δ−, O′ δ−, O″ δ−) antiviral pharmacophore site. Because of this, most hits are related to antiviral agents rather than antifungal or antibacterial agents. As a result, it was identified as a pharmacophore site with antiviral properties for compounds 1–17  [http://vina.scripps.edu/, accessed 2 February 2022), as well as external tools such as AutoDock Tools  [For the practical application of molecular docking, a data bank is required to search for a target with the appropriate PDB format and a methodology for preparing the ligand in the form of a PDB file. Various programs are available in which the ligand can be converted to the PDB format. In our case, ligand preparation was carried out in the PyMol program 2.5.2 (ry 2022) ,97,98,99https://www.ebi.ac.uk/thornton-srv/software/LigPlus/download2.html, accessed 2 February 2022) [In this program, the protein combines with one of the ligands to form a protein–ligand complex. After entering the data, the program automatically generates a grid of the active center of the protein after which an algorithm is prescribed in the command line to determine the active sites of the ligand. As a result, the AutoDock Vina program 1,1,2 identified nine active ligand positions, with the best position being in the region with the lowest binding energy (BE) in kcal/mol. Visualization of the protein–ligand complex itself can be performed using various programs. We performed 2D visualization of the ACE2 protein with a ligand in the LigPlot+ program 2.2.5. This program allows for better visualization of the connection between the protein and ligand. This determines the amino acids that are directly linked to the ligand (ry 2022) ,99.For a comparative study, 54 compounds were used, including four compounds used as blockers of the ACE2 protein at elevated pressure. The choice of compounds was determined based on previous studies (data are not presented) showing high efficacy of glycoside derivatives of flavonoids, methoxtflavonoids, and triterpene compounds.We conducted a computational docking and POM study to identify the pharmacophore sites of 17 flavonoids, known as anti-viral agents. All flavonoids were successfully analyzed in silico for antiviral activity prediction, POM calculation, molecular docking, and pharmacokinetic properties. The insertion of various aliphatic and aromatic groups into the basic flavonoid structure can considerably improve its biological and antiviral activities. Antiviral prediction indicated that aliphatic/aromatic (1–17) derivatives exhibit potential antiviral effects. These findings were rationalized through molecular docking, which revealed the excellent antiviral efficacy of flavonoid derivatives. Many derivatives have shown outstanding binding energy and binding interactions with biotargets. Most flavonoid derivatives exhibited good potential in silico to inhibit HIV. The derivatives were unraveled in a stable binding conformation in the docked pocket, engaged by both hydrophobic and hydrophilic interactions. Future in vitro and in vivo studies are needed to determine whether these derivatives can be used to treat SARS-CoV-2 and HIV. The POM study confirmed the predominant antiviral profile of most compounds in series 1–17. This is highly encouraging to screen the antiviral hits as potential antiviral candidates.


A recent meta-analysis on the incidence of iatrogenic injury to the VA has revealed that patients with variant anatomy are more prone to iatrogenic injury. Therefore, this review is designed to investigate the incidence of variations in the suboccipital component of the vertebral artery in different population groups according to the available literature.This systematic review was conducted according to PRISMA guidelines . The review is based on a comprehensive and extensive search of PubMed, Google Scholar, and ResearchGate. The following search terms were used: “vertebral artery” AND “suboccipital segment” AND “anomalies/anatomical variations of the V3 segment.” Reference lists of all extracted articles were also extensively searched for references to any further relevant publications.A total of 17 papers met the inclusion criteria. The 17 studies corresponded to a total of 10,820 patients. A persistent first intersegmental artery was registered in 1.8%  of the patients. Extradural PICA origin was observed in 1.6%  of the patients. Fenestration was detected in 0.7%  of the patients.The authors summarize the incidence of vascular variation at the suboccipital segment of the VA in different population groups across the Asian, European, American, and African continents. Awareness of the extent of possible anatomical variation will help interpret radiographs, which will enhance the identification of vascular pathologies and reduce the risk of iatrogenic injury. Vertebral artery (VA) injuries during surgical interventions around the atlantoaxial region constitute a potentially catastrophic complication that may result in permanent neurological deficit or even death , 2. The Apart from the aforementioned standard anatomical description, reports of variant vascular anatomy such as fenestration (FEN), persistent first intersegmental artery (FIA), hypoplasia, and incidence of the posterior inferior cerebellar artery (PICA) arising from the V3 segment also contribute to the complexity of this segment , 10. A rThis systematic review was conducted according to PRISMA guidelines   Fig. 1)1). This This review includes English language angiographic studies . In every single article, the reported variation in morphology at the suboccipital segment of the VA was recorded in the study population without bone anomalies at the craniovertebral junction (CVJ).The following are the inclusion criteria: all research articles on anatomical variations, morphology, and morphometry of the suboccipital segment of the VA and studies in English language, angiographic studies, or studies combining cadaveric with angiographic.The following are the exclusion criteria: research articles with no evidence of knowledge of anatomical variations and morphology of the suboccipital segment of the VA.The initial title screening was done by the principal investigator. Included studies at the title screening stage were exported to a library on EndNote reference manager (EndNote X9) for abstract and full article screening, both of which were guided by the eligibility criteria. The EndNote library was shared with a second screener (LL) for abstract and full article screening. Any discrepancies in the screeners’ results of abstract screening were resolved through discussion until an agreement was reached. Discrepancies in full article screening results were resolved by a third screener (RH). Records that were duplicated and did not meet the eligibility criteria were excluded.Details on characteristics of the included studies  were extracted Table .Table 1SThe AQUA  Tool was used to appraise the methodological quality (risk of bias) of the studies . AQUA isMost of the included studies are from the Asian continent 12/17) (Table 2/17 (TabAll included studies (17) were of good quality as the risk of bias was judged “low” following assessment with AQUA Tool. In the case where any of the signaling questions on the AQUA Tool answered “NO,” indicating potential for bias, all authors reached a consensus regarding the eligibility of the study.Adequate information about anatomical variation can influence the choice of procedure for the treatment of deformities and injuries at the CVJ. The V3 segment is susceptible to injury at the point of transition from V2 to V3, particularly within the C-2 groove when inserting a C1-2 transarticular screw or when placing C-2 pars screws , 29. AutEmbryologically, the VA develops from the fusion of six primitive cervical intersegmental arteries (CIAs). The seventh CIA persists to form the subclavian artery and the point of origin of the VA, while the first CIA is also referred to as the proatlantal artery . As repoAnatomical variations have been identified as a clinically significant risk factor for VA injury, especially during the posterior approach to the V3 segment , 39, 40.th segment). However, due to numerous embryonic vessels involved in forming the VA and its branches, PICA sometimes emerges from the V3 part   Table . This isIn some instances, the morphology of the variant VA and osseous relationship at the CVJ is incompatible with screw placement. In the presence of FIA, insertion of a C1-2 transarticular screw may not be appropriate; C1 superior lateral mass may be the best alternative . On the Because only a few of the included manuscripts presented data on morphometry, there was no sufficient data to perform a meta-analysis of pooled data. Regarding morphology, most of the studies were conducted in Asia. This may skew the result, and it may not be easy to generalize results beyond Asia. Hence, we grouped the included studies into Asian, European, American, and African and commented on the differences.The authors summarize the incidence of vascular variation at the suboccipital segment of the VA in different population groups across the Asian, European, American, and African continents Table . Althoug


This study presents a comparison of the protective properties of three concretes of similar composition on the effect of chloride ions. To determine these properties, the values of the diffusion and migration coefficients of chloride ions in concrete were determined using both standard methods and the thermodynamic ion migration model. We tested a comprehensive method for checking the protective properties of concrete against chlorides. This method can not only be used in various concretes, even those with only small differences in composition, but also in concretes with various types of admixtures and additives, such as PVA fibers. The research was carried out to address the needs of a manufacturer of prefabricated concrete foundations. The aim was to find a cheap and effective method of sealing the concrete produced by the manufacturer in order to carry out projects in coastal areas. Earlier diffusion studies showed good performance when replacing ordinary CEM I cement with metallurgical cement. The corrosion rates of the reinforcing steel in these concretes were also compared using the following electrochemical methods: linear polarization and impedance spectroscopy. The porosities of these concretes, determined using X-ray computed tomography for pore-related characterization, were also compared. Changes in the phase composition of corrosion products occurring in the steel–concrete contact zone were compared using scanning electron microscopy with a micro-area chemical analysis capability, in addition to X-ray microdiffraction, to study the microstructure changes. Concrete with CEM III cement was the most resistant to chloride ingress and therefore provided the longest period of protection against chloride-initiated corrosion. The least resistant was concrete with CEM I, for which, after two 7-day cycles of chloride migration in the electric field, steel corrosion started. The additional use of a sealing admixture can cause a local increase in the volume of pores in the concrete, and at the same time, a local weakening of the concrete structure. Concrete with CEM I was characterized as having the highest porosity at 140.537 pores, whereas concrete with CEM III (characterized by lower porosity) had 123.015 pores. Concrete with sealing admixture, with the same open porosity, had the highest number of pores, at 174.880. According to the findings of this study, and using a computed tomography method, concrete with CEM III showed the most uniform distribution of pores of different volumes, and had the lowest total number of pores. Depending on their location and function, building structures are exposed to many harmful factors. The most common causes of reinforcement corrosion and concrete damage are carbonation and chloride penetration . The fasA factor affecting the rate of chloride ion penetration into concrete is undoubtedly its porosity. However, the relationship between pore diameter and chloride diffusivity is reported to be linear by some researchers, such as Moon et al.  and SchuIn recent years, the X-ray computed microtomography method (XRD) has been used to determine the porosity of concrete. This method, although promising, is not without some disadvantages. The main problem is the relationship between sample size and spatial resolution. In order to obtain a sufficiently high spatial resolution, it is important to use a sufficiently small sample. However, such a small section of the tested material may not represent the properties of the whole object ,18. DespIn addition to evaluating the diffusion and porosity properties, it is necessary to assess the rate of development in corrosion processes against the reinforcement in concrete. To evaluate the rate of corrosion development, nondestructive polarization methods are used: the Linear Polarization Resistance (LPR) method , and ele3O4), and siderite (FeCO3) are common. However, under simulated coastal environments, ferrihydrite (Fe(OH)3) is also found [3 ⸱3H2O. In contrast, Fe(OH)2 and Fe(OH)3 hydroxides increase in volume by 2.17 and 1.76 times more than noncorroded steel, respectively. Determining the type of corrosion products is important in the process of modeling the cracking of concrete lagging [The type of corrosion products of reinforcement  depends on the environment in which the corroding elements are located. The initial stages of atmospheric corrosion of carbon steel in both rural and urban atmospheres leads to the formation of lepidocrocite (γ-FeOOH) and goethite (α-FeOOH), which are the main phases present in corrosion products, regardless of the environment. In chloride-containing coastal environments, akaganeite ), magnetite  were also compared. Using scanning electron microscopy (SEM) with microarea chemical analysis capabilities, as well as X-ray microdiffraction (XRD) to study microstructural changes, changes in the phase composition of corrosion products occurring in the steel–concrete contact zone were compared. It turns out that a slight modification of the composition of the concrete used can result in a huge improvement in its protective properties, ensuring the safety and durability of the reinforced concrete structures made from it.3); gravel, 2 ÷ 8 mm (512 kg/m3); and gravel, 8÷16 mm (681 kg/m3). The first tested concrete (B1) contained CEM I 42.5 R cement in its composition. The next concrete (B2) differed from the first only in the use of CEM III/A 42.5 N-LH/HSR/NA cement. The last concrete (B3) was further modified using a refining admixture in the amount recommended by the manufacturer (0.5% of the weight of the cement). The detailed compositions and properties of mixes are presented in The tests were performed on three types of concrete mix. All of the concretes tested were designed to be ordinary concretes (used for precast foundation elements). Three types of natural rounded aggregate  were utThe compressive strength of the concrete was determined using cubic samples possessing 150 mm sides, which were stored and made in accordance with PN-EN12350-3:2011 .Next, a series of tests was conducted to determine the protective properties of the tested concretes against the effects of corrosion on the concrete’s reinforcements by chloride ions. In order to perform these tests, 12 samples of each type of concrete were prepared.To determine the depth of penetration by the pressurized water, cubic samples with 150 mm sides were used. In order to perform these tests, 3 samples of each type of concrete were prepared.3) was used.To determine the open porosity of hardened concrete, 1 sample for every type of concrete  were carried out each time on 2 test pieces in the shape of cylinders that were 100 mm in diameter and 60 mm high, made of each of the three types of concrete. A reinforcing bar was placed in each cylinder. A reinforcement cover 20 mm in thickness was used .The research for phase identification and quantitative analysis (using the Rietveld method) of corrosion products was conducted on three rebar specimens in concrete lagging made of 3 types of concrete, following simulations of the deterioration process under the formation of corrosion hazards caused by the presence of chloride ions. The test was conducted after 1, 2, 7, and 28 days of concrete curing, which had been performed with the use of machine for testing the compressive strength of concrete. The results are shown in Testing the depth of water penetration under pressure was performed according to EN 12390-8, Testing of concrete: Part 8: Depth of water penetration under pressure . A waterOpen porosity was defined as the ratio of the differences between A Nikon Corporation Industrial Metrology Business Unit, Tokyo, Japan XT H 225 ST industrial microtomograph equipped with a reflection lamp was used for the tomographic study; at the maximum approximation of small specimens, it proposed a resolution of 3 µ. The optimal resolution used in this case was 10 µ, which made it possible to obtain reliable images of the scanned sample. The resulting images were then reconstructed using Nikon’s CTPro 3D 6th generation software. After reconstruction, data preparation and all analyses were carried out using the appropriate tools available in VGStudio MAX 3.1 software. Prior to defectoscopy, an area 13 mm in diameter and 15 mm in height, slightly smaller than the scanned area, was taken from each scanned core. Clipping was necessary due to artifacts and imperfections in the tomographic image created during scanning. The data prepared in this way was analyzed for porosity.The test was conducted in accordance with the standards NT BUILD 443  and ASTMD coefficient is determined by adjusting the chloride concentration graph. This graph is obtained by calculating the distribution of chloride ion concentration expressed to the cement mass according to the solution of the diffusion equation, with the concentrations of these ions determined in the test:The value of the c is the chloride ion concentration that was measured during the test at a distance x (mm) from the edge of the element (%), t is time (s), and n is the number of concrete layers in which the chloride concentration was determined. The determined values of the diffusion coefficient are presented in To determine the best fit calculation of the diffusion coefficient complying with the results of the experiment, the mean squared error was calculated based on the following formula:The study was conducted in accordance with the procedure described in standards AASHTO T 277  and ASTM2/s), 3), −1), L is sample thickness (m), V is electrical potential (V), A is the cross-sectional area of a sample (m2), and t is time (s).Based on the determined charge, the value of the diffusion coefficient was also calculated using the Nernst–Einstein equationThe tests were carried out in accordance with the procedure described in NT BUILD492 , being p3 solution, according to the formula:In accordance with the standard NT BUILD492 , the migThe depth of chloride penetration was determined in one of the three test samples made from each concrete.In turn, the other two samples were used to determine the distribution of chloride ion concentration in concrete using the method described in the papers ,9,37. In1 = 24 and t2 = 48 h. At the end of migration, the level of chloride ion concentration in the water extracts obtained from stratified stripped concrete was determined using a Profile Grinding Kid device with both a diamond drill and an attachment that allowed the extraction of 2 mm thick concrete layers, to a depth of 20 mm.Migration tests were conducted using the method described in the papers ,9, and . Six cylBased on measurements of the mass density distribution tionship ,9,37(6)− at the midpoints of consecutive intervals B = 0). Furthermore, z1 is the ion valence, R = 8.317 J/mol·K is the universal gas constant, F = 96 487 C/mol is the Faraday constant, U is the voltage between the electrodes, and h is the specimen height. The determined values of the diffusion coefficient are presented in In this expression, 3 = 30 and t4 = 60 days. After diffusion, the value of chloride ion concentration in the water extracts was determined in the same way as after migration tests.Diffusion tests were carried out using the method described in the papers ,9,37. SiPolarization studies of the corrosion rate in the reinforcements using a polarization resistance measurement method (LPR) were carried out using a potentiostat , coupled with a computer set. The measurement was recorded in a three-electrode system in which the working electrode was the sample reinforcement, the reference electrode was a silver chloride electrode, and the counterelectrode was a stainless-steel circle with a diameter close to that of the concrete samples. In order to accelerate the very long timescale for adequate chloride diffusion in the concrete, accelerated electromigration of chloride ions was used, similar to the works ,25, whil2))k is electrochemical equivalent, and t is time. The above relationship shows the correlation of the corrosion current density, with the linear corrosion rate , concrete resistance (Rc), and constant phase element describing concrete cover (CPEc). The impedance spectra at medium and high frequencies characterizes steel, and corresponds to the right-hand part of the electrical equivalent circuit, which contains the ohmic resistance in pits or defects of the passive layer (Rpit), the constant phase element for passive surface (CPEpas), the charge transfer resistance (Rct), constant phase element describing double layer on the steel (CPEdl), and the Warburg  impedance (W).The impedance spectra obtained were analyzed using the electrical equivalent circuit shown in Phase Identification”, in addition to the International Centre for Diffraction Data’s PDF-4+ database. Quantitative analysis was performed using the Rietveld method, in accordance with the accredited procedure M2-RTG, entitled “Quantitative Phase Analysis.” Observations were carried out using a JSM 7200F scanning electron microscope from JOEL, with a BSE backscattered electron detector and an EDS detector, to perform microarea chemical analysis.Measurements were performed with an Empyrean X-ray diffractometer acquired from PANalytical, using filtered iron radiation in a pixel detector configuration. Identification of phase composition was carried out in accordance with the M1-RTG accredited procedure, entitled “Changing the cement from Portland cement (for B1 concrete) to metallurgical cement (for B2 and B3 concretes) caused a reduction in compressive strength in the first 7 days of maturation. This reduction in compressive strength could also have been caused by the sealer admixture (B3 concrete). After the 28th day of maturation, the strength of concrete with metallurgical cement was the highest, and a clear upward trend was also visible. The properties of blast furnace slag, which is a component of metallurgical cement, allow us to hypothesize that the strength of B2 and B3 concretes will be higher than that of B1 concrete after a longer maturation time.The use of metallurgical cement significantly reduced the depth of pressurized water penetration. However, the addition of a sealing admixture did not significantly improve the achieved effect in B3 concrete. It should be noted that the penetration of water deep into each sample was of a local nature. The magnitude of penetration forming about 20 mm was small and appropriate for concretes with a good quality of cement matrix.As can be seen from the results, the tested concretes did not differ substantially in terms of open porosity as determined using the gravimetric method. Concrete B3  had slightly better properties than the other concretes.These were based on tomographic studies of a smaller cylindrical sample, measuring 18 mm in diameter and 21 mm in height.1 = 14%, p2 = 6%, and p3 = 6% for concretes B1, B2, and B3, respectively. According to these tomograph tests, it can be said that the replacement of the ordinary cement (CEM I) with metallurgical cement (CEM III) resulted in a reduction in the porosity of the concrete by almost half. On the other hand, the use of a sealing agent had practically no effect on the porosity.On the basis of the analysis performed, the porosity of the concretes was calculated, expressed as the percentage of the sum of all air voids (imaged using the tomograph) against the volume of the fragment of the cylindrical sample with a diameter of 18 mm and a height of 21 mm, amounting to pAll three concretes were tested using both standard methods and the thermodynamic method. A detailed discussion of the methods, including a comparison with the results obtained in different concrete mixtures, are presented in the paper . Table 41202-997  after apUILD 492 , based oUILD 492 . On the UILD 443 ; this waAccording to an analysis of various methods of determining the diffusion coefficient in different types of concrete, each of which having been carried out in the paper , the valt of chloride concentration at the reinforcement–concrete interface of the lagging  are shown in It was assumed that the threat of corrosion of the reinforcing bars causes, according to the standard PN-EN 1992-1-1 Eurokod 2 , chloridThe corrosion hazard of the reinforcement in B1 concrete will occur after just 2 years of using the structure with the applied lagging thickness of 15 mm, while with the application of a lagging thickness of 25 mm the corrosion hazard will occur after 5 years. Application of the minimum thickness of lagging around the reinforcement required by the standard EN-PN 1992-1-1  in constThe specimens, for which a number of measurements were taken during the whole research process, were analyzed. They were the B1_P1, B1_P2 and B2_P1, B2_P2 and B3_P1, and B3_P2 specimens. The first measurement was a reference, prior to the chloride migration in the concrete. The second measurement was taken after 7 days of chloride migration onto concrete. After waiting a further 7 days, the third measurement was taken after 14 days of chloride migration into concrete. After waiting 7 days again, the fourth measurement was taken, 21 days after chloride migration into the concrete. Likewise, the fifth measurement, taken after 28 days of chloride migration into the concrete and after waiting 7 days. Three seven-day cycles of chloride ion recharge with an electric field were performed for B1 concrete. For B2 concrete, five seven-day cycles of chloride ion recharge were carried out using an electric field. For B3 concrete, four seven-day cycles of recharging chloride ions with an electric field were carried out. Each time the seven-day migration process was completed, post measurements of the corrosion current density were made after waiting seven days from the electric system being turned off. Charging cycles were applied until the corrosion current density value that would indicate advanced corrosion was obtained. Exemplary shapes for the six selected measuring elements are illustrated in corrE = 236 mV corrE = 90 mV corrE = 15 mV. After the second charge, the values of the corrosion potential in both samples reached a value above the 200 mV A similar change in the distribution of polarization curves over time was observed for the specimens B1_P1 and B1_P2 a,b afterIn B3 concrete, a decrease in corrosion potential was also observed during all test cycles, but the initial values in one of the samples currence .corri) of the steel reinforcement in concrete from two chosen test elements made of tested concretes. corrE) of the steel reinforcement in concrete from two chosen test elements made of tested concretes.The analysis was made on the basis of assumptions made in the work . The firBefore the injection of chloride ions into the concrete, fragments of large arcs were visible on the Nyquist spectra for steel . This ise + Rc) associated with an increase in the conductivity of the concrete due to an increase in the ion concentration in the concrete pore liquid. The sum of Re + Rc determined from the analysis of the spectra for concretes B2 and B3 was greater than it was for concrete B1  decreased with the duration of the tests  started to corrode after the shortest time following chloride introduction into the concrete. The Rp values determined from the analysis of the impedance spectra of steel in concrete confirmed the results obtained from the analysis of the steel polarization curves.The determined polarization resistance Rhe tests . The valdl) were also observed , equipped with microarea chemical analysis capabilities and X-ray microdiffraction (μXRD), were used to study microstructural changes, in addition to changes in the phase composition of corrosion products occurring in the steel–concrete contact zone. These changes were observed during the development of corrosion processes caused by an increase in the concentration of chloride ions in the concrete. Examples of tests performed using X-ray microdiffraction (XRD) and surface micrography are shown in The use of phase identification showed that there are differences in the iron compounds formed depending on the type of sample. Lepidocrocite and akaganeite are present in all areas tested, while the presence of δ-type iron oxide was only confirmed in the sample from B2 concrete; likewise, goethite was identified only in the sample from B3 concrete. The only iron compound containing chlorine is akaganeite, though chlorine–calcium compounds also appeared in the sample from concrete B3. In addition, the presence of hydrated iron–potassium oxide was possible. No reflections of chlorine, potassium, or sodium compounds were registered in any of the samples.2O) to gypsum (CaSO4 2H2O) controls the setting process of gypsum plaster [Only a small amount of bassanite was identified in the B1 concrete sample. Aqueous conversion of bassanite , while akaganeite was 24% of the mass. In the B3 concrete sample, goethite was the most abundant at 48.7% of the mass; lepidocrocite was at the same level as it was in the B1 concrete sample, i.e., 35.9% of the mass. In this sample, the share of akaganeite was the lowest, at about 10% of the mass. This was also the lowest share of this mineral in all the samples tested.It can be concluded that a common feature of the tested samples was the presence of lepidocrocite and akaganeite, although their proportions varied from sample to sample. In each of the samples, a different phase was dominant; in the B1 concrete sample, all three iron compounds were found in similar amounts, while in the B2 concrete sample, half of the tested material was formed of iron oxide type δ, and in sample No. 3, the main phase was goethite. Since lepidocrocite was the result of hydration of goethite (and there was the least amount of it in the B2 concrete sample), it can be assumed that corrosion processes in the B2 concrete sample occurred more slowly than in the other samples.The type of cement influences the rate of chloride diffusion in the concrete, and thus the duration of corrosion initiation of the reinforcement by chlorides penetrating into the concrete from the environment.Of the concretes tested, concrete B2 with CEM III cement was the most resistant to chloride ingress, and therefore provided the longest period of protection for the reinforcement against chloride-initiated corrosion. The fastest, occurring after only two 7-day cycles of chloride migration in the electric field, was the steel corrosion that started in concrete with CEM I cement (concrete B1).The results of the concrete diffusion and porosity tests correlated with the time of the onset of steel corrosion in the tested concretes due to chloride penetration into the concrete.Similarly, studies of both the microstructure and changes in the phase composition of corrosion products occurring in the steel –concrete contact zone confirmed these observations as having the smallest amount of lepidocrocite, which was the result of goethite hydration in the smallest amount, occurring in the sample made of B2 concrete.The additional use of a sealing admixture did not seem to be the most effective strategy, as it can cause a local increase in the volume of pores in the concrete, and, at the same time, a local weakening of the concrete structure, as can be seen from the distribution of the number of pores in a given volume found using computed tomography. According to the study conducted with this method, B2 concrete shows the most uniform distribution of pores of different volumes, with the lowest total number of pores.The test results obtained were consistent with the results obtained in the work , where t


We have studied high light out-coupling efficiency top-emitting organic light-emitting diodes (TOLEDs) under the guidance of the finite-difference time-domain (FDTD) simulation. TOLED achieves an extraordinarily high light extraction efficiency at 468 nm, in deep-blue regions, of 49.70%, which is approximately 3.5 times that of the bottom light-emitting diode (BOLED) by changing the thickness of the organic layer and the position of the light-emitting layer in the FDTD simulation. Based on the simulation results, the TOLED with ultrahigh efficiency and narrow full width at half maximum is successfully fabricated, and the maximum external quantum efficiency of TOLED is almost 3.3 times that of the BOLED, which is perfectly consistent with the FDTD simulation results. Meanwhile, the shift of the electroluminescence spectrum of the TOLED is restricted within 10° in the angular-dependence test (0° to 80°). The optimized performance of the OLED indicates a new method to develop a high-performance device under the guidance of simulation. Organic light-emitting diodes (OLEDs) have attracted much attention in recent years owing to their unique advantages of being lightweight, flexible, and environmentally friendly, and they have been utilized in the field of full-color displays and indoor lighting ,2,3,4. IOn the other hand, because of the unique advantages of fast response, high contrast, and ultra-thinness, active-matrix organic light-emitting diodes (AMOLEDs) have become the first candidate in the field of high-quality image screens and flexible displays. In the application of AMOLED, the open ratio of top-emitting organic light-emitting diodes (TOLEDs) is significantly greater than that of bottom-emitting organic light-emitting diodes (BOLEDs) ,19,20. Fmax) of 23.28 cd·A−1 and a maximum power efficiency (PEmax) of 21.55 lm·W−1, approximately doubling the properties of the BOLED device [max). Benefiting from excellent optical simulations, they achieved maximum EQEs of 29%, 17%, and 12%, respectively. However, the peak wavelength of the EL spectrum shifted obviously at different viewing angles, resulting in a significant deviation from commercial requirements [max of 28.27 cd·A−1, which was in great agreement with the light output intensity simulated by the FDTD method [In 2009, Qiang Wang et al. set the organic layer thickness of a green TOLED to 116 nm so that the device was located at the first-order microcavity length and obtained a maximum current efficiency -pyrene-1,6-diamine (DITBDAP) reported by our group previously in this structure . The optThe software Lumerical FDTD Solutions 2018a is able to simulate micro- and nano-optical structures and non-linear optics in OLEDs accurately. The schematic diagrams of BOLED and TOLED are depicted in x nm)/EML (20 nm)/4,6-bisphenyl)-2-methylpyrimidine /Yb (1 nm)/Mg:Ag /CPL (90 nm). TAPC is the hole transport layer (HTL) and B3PyMPM is the ETL. We varied the thicknesses of HTL and ETL, and the position of the EML to regulate the length of the microcavity. To compare and verify the high light out-coupling efficiency of TOLED, we designed BOLEDs with different thicknesses of organic layers as follows ) of a TOLED with a microcavity effect is shown below [I0(λ) is the intensity of the luminescence of the EML; L is the total optical thickness of the cavity (the sum of the thicknesses of organic layers); λ is the resonant wavelength; Z is the optical distance between the EML and anode; and Rf and Rr are the reflectivity of the cathode and the anode. For our TOLED, the light transmits through the front mirror (the cathode). In the case of metal as a reflector, the total optical thickness L of the cavity, taking into account the effective depth of penetration in the metal, is given by [nm and dm are the refractive index and thickness of organic material of the mth layer in the microcavity. It is related to the reflected phase shift of the metal (Φ), and the phase shift of a metal mirror is expressed by the following equation [am and bm are real and imaginary parts of the metal mirror refractive index and ns is the refractive index of the material adjacent to the mirror. In order to maximize the I(λ), the L of the microcavity device is also subject to the following equation:q is the mode index and λq is the resonant wavelength of the series q. Since the total optical length is less than one optical wavelength, the order of the resonant cavity should be set to the lowest order. In the calculation, the refractive indices of organic materials were set as 1.75 and the complex refractive indices of the metal mirror were taken from [I(λ) could be maximized at the classical deep-blue light wavelength (about 464 nm) when the sum of the thicknesses of the organic layer is approximately 90 nm.We first calculated the optimized thickness of the organic layers. From an optical perspective, a TOLED could be simplified as a Fabry–Pérot optical resonance cavity with an electrically pumped emitting layer. The beam of light produced by the EML will be reflected back and forth indefinitely between the front mirror (cathode) and the rear mirror (anode), during which most of the light will be emitted and some will be dissipated. The microcavity effect will occur when the distance between the two electrodes is of the same order of magnitude as that of the wavelength of the light emitted by the EML. Only the light of a specific wavelength will be reinforced and transmitted through the semitransparent mirror (cathode). The intensity of the external luminescence spectrum (wn below :(1)I(λ)=given by :(2)L=∑nmequation :(3)Φ=arcken from . TheoretIn order to verify this result, we used FDTD to simulate the emission intensity and light out-coupling efficiency of the TOLED at visible wavelengths. Meanwhile, it was assumed that the combined exciton in the EML could be represented as an oscillating dipole uniformly distributed in any direction, and that small variations in the decay rate of the excited state radiation were neglected. We varied the thickness of the HTL, so that the sums of the thicknesses of organic layers were 70 (device S1), 90 (device S2), and 110 nm (device S3), respectively, and the specific device structures are shown in λq, as follows [ξ represents the enhancement factor related to the position of the EML, with a maximum value of 2 when the EML is just in the wave ventral region of the first-order microcavity. τcav/τ is the ratio of the exciton lifetime in free space and in the microcavity device, it could be considered as a constant in the simulation. Therefore, we design devices S4 and S5 by adjusting the thickness of both ETL and HTL on the basis of the total thickness of organic layers fixed at 90 nm, the specific structures are shown in Given that the sum of the thicknesses of organic layers is determined, the position of EML will affect the efficiency of the device. The efficiency improvement of a TOLED could be expressed in terms of the radiation enhancement factor of the device at the resonant wavelength  follows :(5)Gcav=The spectral radiance energy of devices S4 and S5 are depicted in In addition, to verify the effect of the CPL layer, we adjust the thickness of the CPL to 0 nm on the basis of device S4 and name it as device S6. The spectral radiance energy of device S6 shown in In order to clarify whether the light out-coupling efficiency of TOLED device is improved compared to a BOLED, a BOLED named device B1 b possessJ-V characteristics of BOLEDs and TOLEDs and Under the guidance of FDTD, BOLEDs and TOLEDs based on the new TTA material DITBDAP have been fabricated in the structure of devices S4 and B2, and the key parameters have been reported . Both thmax of 20.6%, about 3.3 times as high as the 6.1% obtained by BOLED, which further validates the FDTD simulation on the light out-coupling efficiency. The theoretical EQE calculation formula is as follows:γ is the equilibrium constant of the carrier in the device, ΦPL is the photoluminescence quantum yield (PLQY) of the molecules in the thin film state, ηγ is the radial exciton yield, ideally 100%, and ηop represents the light out-coupling efficiency of the device. Therefore, under the same structure of the organic layer, the high EQEmax of TOLED devices is mainly attributed to the excellent light out-coupling efficiency, consistent with the FDTD simulation results. As shown in the insert of L. Within a certain range, as L increases, the FWHM will be significantly narrowed.It is obvious in In order to test the angular dependence of the EL spectrum of TOLEDs, we have also measured the orientation pattern of the EL. It is clearly observed in max of 20.6% are successfully fabricated, indicating a new method to develop high-performance devices under the guidance of proper simulation.In summary, we have studied a light out-coupling efficiency deep-blue TOLED under the guidance of FDTD simulation. We optimized the performance of the TOLED by adjusting the thickness of the organic layer and the location of the EML and using the capping layer. In this design process, the organic layer thickness is one of the most crucial parameters. A thinner thickness of the organic layer leads to the blueshift of the spectral radiance energy and best light out-coupling efficiency, whereas a thicker one results in redshift. After determining the sum of the thicknesses of the organic layers to be 90 nm, we obtained a maximum light out-coupling efficiency of 49.70% by changing the position of the EML through FDTD, almost 3.5 times that of the BOLED. According to the simulation results of the FDTD, high-performance TOLEDs with EQE