While deep learning has found widespread utility in gearbox fault diagnosis, its direct application to wind turbine gearboxes encounters significant hurdles. Disparities in data distribution across a spectrum of operating conditions for wind turbines result in a marked decrease in diagnostic accuracy. In response, this study introduces a tailored dynamic conditional adversarial domain adaptation model for fault diagnosis in wind turbine gearboxes amidst cross-condition scenarios. The model adeptly adjusts the importance of aligning marginal and conditional distributions using distance metric factors. Information entropy parameters are also incorporated to assess individual sample transferability, prioritizing highly transferable samples during domain alignment. The amalgamation of these dynamic factors empowers the approach to maintain stability across varied data distributions. Comprehensive experiments on both gear and bearing data validate the method’s efficacy in cross-condition fault diagnosis. Comparative outcomes demonstrate that, when contrasted with four advanced transfer learning techniques, the dynamic conditional adversarial domain adaptation model attains superior accuracy and stability in multi-transfer tasks, making it notably suitable for diagnosing wind turbine gearbox faults. As an essential component in the wind turbine’s transmission system, the gearbox often operates under variable loads and is prone to failures . AbsolutIn order to tackle the aforementioned challenges, domain adaptation methods are applied in cross-domain fault diagnosis . Domain By utilizing the improved Wasserstein distance, the algorithm effectively measures the dissimilarity between the source and target domains. This distance metric allows the model to align the distributions of data from different working conditions, mitigating the domain shift problem. Consequently, the model can identify and extract features that are relevant across various conditions, enhancing its ability to accurately diagnose faults in bearings even under different operational scenarios. The use of domain-invariant features ensures that the model remains robust and consistent across different working conditions, ultimately leading to improved fault diagnosis performance . Han et The above domain adaptation algorithms only focus on reducing the distance between the marginal distributions of the source and target domains. However, in complex classification tasks, even if the marginal distributions are successfully aligned, it does not guarantee good classification performance . TherefoThe DCAA method jointly adjusts the marginal and conditional distributions between two different domains. By introducing dynamic weighting factors, it dynamically measures the relative importance of marginal and conditional alignment, enhancing the accuracy of feature distribution alignment.The method employs information entropy as a metric to assess the reliability of classifier predictions. It prioritizes using data with high confidence for domain adaptation training, thereby improving the fault diagnosis accuracy under complex working conditions.Through a series of experiments, the effectiveness of DCAA is demonstrated in both WT gearbox and bearing fault diagnosis scenarios. Furthermore, the method’s superiority is validated by comparing it with other domain adaptation approaches.Based on this, this paper proposes a semi-supervised fault diagnosis method for WT gearbox systems based on Dynamic Conditional Adversarial Adaptation (DCAA). The main contributions of this paper are summarized as follows:The remaining sections are as follows. The high accuracy of intelligent fault diagnosis is contingent upon a critical premise: the training and test data must come from the same distribution. Hence, in the fault diagnosis of WT gearboxes, we are often limited to labeled data from a single working condition due to challenges in data acquisition. However, the data distribution in actual working conditions (target domain data) often differs from that of the existing conditions (source domain data) due to changes in working conditions, such as speed and load, as illustrated in m labeled data points, following the joint distribution n unlabeled data points, following the joint distribution disc  is quantified using a domain discriminator and a conditional domain discriminator.This paper investigates fault diagnosis in wind turbine gearbox systems under diverse working conditions. The problem is described as follows: This research involves collecting vibration signals from different working conditions, which serve as the source domainF, the classifier G, and the domain discriminator D. During forward propagation, the feature extractor F is responsible for extracting information from the data and encoding it into feature vectors. The classifier G uses these feature vectors to classify the data and generates pseudo-labels. The domain discriminator D, on the other hand, utilizes the information from the feature vectors and pseudo-labels to determine whether the data come from the source domain or the target domain.i-th sample from the source (or target) domain, i.e., i-th sample from the source (or target) domain, i.e., D takes values between 0 and 1, indicating whether the input data come from the source domain or the target domain.Conditional adversarial domain adaptation (CADA) is an advanced transfer learning method. The CADA network consists of three components: the feature extractor During the training process, the objective is to minimize the classification loss while simultaneously maximizing the domain discriminator’s loss. Adversarial training is employed to reduce the distribution discrepancy between the source and target domain features. The optimization objective can be represented as follows:F is encouraged to extract features that are invariant to domain shifts, making it difficult for the domain discriminator D to distinguish the source and target domains. At the same time, the classifier G is fine-tuned to improve its accuracy in classifying the source domain data. This dual optimization strategy allows the model to effectively classify unlabeled data in the target domain, achieving domain adaptation and enhancing the model’s generalization to target domain samples.Through the optimization process described above, the feature extractor F is responsible for extracting domain-invariant features from the source domain and target domain data, encoding them into feature vectors C is able to perform fault classification utilizing feature vectors. The domain discriminator D1 and conditional domain discriminator D2 are used to align the marginal distribution and conditional distribution, respectively. Additionally, dynamic weighting factors ω1 and ω2 are introduced to adjust the model training process, enhancing the model’s generalization capability and robustness.As shown in The optimization objectives for the classifier, domain discriminator, and conditional domain discriminator are expounded in In the subsequent case studies of this article, the architecture of the feature extractor is composed of three convolutional layers, three pooling layers, and two dropout layers, all employing the ReLU activation function. For specific model parameters, please refer to G. The classifier, employing the feature vector D1 is a binary classification model, and its loss is calculated using a binary cross-entropy function. Therefore, the output of F is capable of extracting domain-invariant features, thereby effectively confusing the domain discriminator.Due to domain shift, a classifier that is solely trained on source domain data might not exhibit satisfactory performance when applied to target domain data. We introduce a domain discriminator to differentiate the data sources. The domain discriminator’s discrimination loss can be expressed asD1 for domain alignment is insufficient. This often leads to a situation where the extracted features can successfully confuse the discriminator, but the classification performance on the target domain remains unsatisfactory. This is because the domain discriminator narrows the distance between features of different classes in the source and target domains. Therefore, it is necessary to add a conditional domain discriminator to align the classes. The conditional domain discriminator D2 is trained by conditioning the feature vector D2. The domain discriminator loss function can be expressed asf and predicted label In multi-class tasks, relying solely on the domain discriminator (a)ω1: The information entropy weight factor ω1 is used in the model to dynamically adjust the training weights of the classifier and discriminator. It is introduced to handle cases where certain training data may have high classification error due to noise or other factors. These data can negatively impact the alignment of classes in the domain discriminator and result in suboptimal transfer performance. The information entropy Information entropy weight C represents the number of classes, and ω1 is determined based on this entropy measure and is used to adjust the importance of the classifier’s training during the domain adaptation process. By incorporating this dynamic weight factor, the model can achieve better adaptation performance and handle uncertain or noisy data more effectively. The class-domain weight factor can be expressed asThe value of ω1. The magnitude of ω1 dynamically adjusts in response to changes in the input data.Equations (8) and (9) demonstrate that the more complex the input sample, the greater the value of (b)ω2: In this part, the cross-entropy weight ω2 is introduced to dynamically balance the relative importance of domain alignment and class alignment. When the feature marginal distributions between domains are far apart, domain alignment is prioritized to reduce the marginal distribution distance. On the other hand, when the feature marginal distributions are close, class alignment is prioritized to reduce the conditional distribution distance. By dynamically adjusting the weight, the convergence speed and class alignment performance of the model can be improved. The specific method is as follows.Cross-entropy weight First, the A-distance between the inter-domain marginal distribution and the conditional distribution is computed separately asω2 is defined asDd1 and Dd2 are, respectively delineated in Equations (10) and (11). Equation (12) elucidates that, during the model optimization process, the parameter ω2 is capable of autonomously adjusting in response to the variations in the loss of D1 and D2.Then, the cross-entropy weight Based on the above derivation, the final optimization objective of DCAA can be summarized as follows:During the adversarial training process, the following occurs.D1 and D2 are frozen, followed by the optimization of the parameters of F and C as per Equation (13). As indicated by Equation (13), this procedure aims to decrease classification loss while increasing domain discrimination loss, thereby extracting discriminable domain-invariant features. Additionally, according to Equation (9), the more complex the input data, the smaller the value of ω1 becomes, thus minimizing the interference of complex data in domain adaptation. Furthermore, as per Equation (12), ω1 adaptively shifts focus to the domain discriminator with greater loss by computing the losses of the D1 and D2. Firstly, the parameters of F and C are frozen, and the parameters of D1 and D2 are optimized in accordance with Equation (14). This stage of the process is designed to enhance the discriminative abilities of D1 and D2.Subsequently, the parameters of F is continuously enhanced.Through the iterative minimax game between them, the feature extraction capability of fθ, gθ, dθ1 and dθ2 be the parameters of the feature extractor, classifier, domain discriminator, and class discriminator, respectively. α denotes the learning rate.The proposed DCAA algorithm adopts the stochastic gradient descent with backpropagation for training. Let During the training of the model using backpropagation, the parameters of each part are updated as follows:λ. In summary, the training process of CDAA can be delineated as Algorithm 1.Algorithm 1: Training process of CDAAF and classifier G#pre-train feature extractor F, GInput: source domain data and labels, for i in  do: The classification loss is computed using Equation (4). Model parameters are updated utilizing Equation (16). endF, G.Return: pre-trained D1 and Conditional Domain Discriminator D2.#pre-train Domain Discriminator D1, D2.Input: source domain data, target domain data, for i in  do:D1 and D2 are computed using Equations (5) and (6), respectively. The domain losses for D1 and D2 are updated using Equations (16) and (17), respectively. Parameters of endD1, D2.Return: pre-trained # Adversarial trainingD1 and D2.Input: source domain data and labels, target domain data, pre-trained F, G, for i in  do: Parameters are optimized using Equation (15) to achieve the optimization objective outlined in Equation (13). Parameters are optimized using Equations (17) and (18) to achieve the optimization objective outlined in Equation (14).endOutput: fault diagnosis model.where ‘epoch1′ and ‘epoch2′, respectively, denote the epochs for pre-training and training.The optimization objective of maximizing the domain discriminator loss is achieved by introducing gradient reversal layers between the feature extractor and the domain discriminator, as well as the conditional domain discriminator. The gradient reversal layer multiplies the gradients received from the two domain classifiers by −We used the Case Western Reserve University bearing dataset and the Southeast University gearbox dataset to validate the performance of the method proposed in this paper. The performance is compared with four advanced transfer learning models: DANN , CDAN 3, CORAL , DATN 3.The comparison is based on classification accuracy and the model’s stability in various transfer tasks. By conducting these experiments, the effectiveness and applicability of the proposed method in wind turbine systems are validated.Experiment 1: The data were collected by Southeast University from a transmission system dynamic simulator . The expExperiment 2: The data for this experiment were obtained from Case Western Reserve University and the experimental setup is shown in (1)Experiment 1: The feature extractor is a 2D convolutional neural network with a kernel size of 5 × 5 and a pooling layer size of 2 × 2. A total of 150 epochs were set for training, with an initial learning rate of 0.001. The mini-batch size was set to 128, with 64 samples from the source domain and 64 samples from the target domain. In the training process, only the classifier was trained for the first five epochs. To eliminate the impact of randomness, the results were averaged over 20 experiments. To ensure fairness in the experiments, the same hyperparameters were set for the comparison models, and they were trained for the same number of epochs. The baseline in this study is a convolutional neural network with the same feature extractor, trained only on the source domain data. We evaluate and compare the performance of various models using the accuracy. Accuracy is defined as the ratio of the number of correctly classified samples to the total number of samples in the test set.The experimental results are shown in (2)Experiment 2: The model parameters remain unchanged, and each batch size is set to 64, containing 32 samples from both the source and target domains. During the training process, the classifier is exclusively trained for the first 15 epochs, and the total number of epochs is set to 150. The baseline remains consistent with the previous experiments. There are a total of 12 transfer tasks based on the four operating conditions, and the results are shown in In the baseline convolutional neural network without transfer learning, the average accuracy on the target domain is 67.50%. In the comparative experiments, the proposed CDAA model achieved the highest average accuracy, which is 95.81%. Additionally, the CADA model demonstrated more stable performance across the 12 transfer tasks.(3)Results Analysis: Indeed, the experimental results clearly demonstrate that while convolutional neural networks (CNNs) have the ability to learn deep features, they struggle with domain shift in transfer tasks, resulting in the lowest accuracy among the tested models.ω1 and ω2 in CDAA effectively suppress negative transfer and adaptively adjust the training emphasis on the marginal and conditional distributions based on different data distributions. This capability allows CDAA to adapt to complex and variable operating conditions effectively.Among the methods that consider marginal distribution alignment, DANN performs slightly better than CORAL, but their accuracies are both lower than those of the conditional distribution alignment methods. This is because they do not take into account the relationships between sub-domains, leading to suboptimal performance. In the methods that consider conditional distribution alignment, CDAN, DATN, and CDAA perform equally well in some individual tasks, but CDAN and DATN have lower average accuracies across all tasks compared to CDAA. Exactly, CDAA synergizes the alignment of both marginal distributions and conditional distributions, allowing it to perform well in tasks with significant differences between source and target domain data. This adaptability to different data distributions makes CDAA effective in various transfer learning tasks. Taking the two transfer tasks in Experiment 1 as examples, due to the simultaneous variation of rotation speed and load, there is a significant difference in data distribution between the two operating conditions. It is evident that CDAA performs better, achieving a 5.97% improvement compared to DATN. Additionally, the dynamic weighting factors To demonstrate the impact of dynamic weighting factors on the model, we conducted ablation experiments using Experiment 2 as an example. The experimental results are shown in To visually demonstrate the effect of DCAA feature distribution alignment, T-SNE is employed for the visualization of feature vectors. We selected the more complex tasks from the two sets of experiments as examples. The results are shown in From To gain a better understanding of DCAA’s classification performance on each class, we have plotted the confusion matrices for CDAA and other comparative models on the two datasets. Taking the more complex tasks from the two experiments as examples, the confusion matrix results are shown in From the confusion matrices, it can be observed that in Experiment 1, the miss, root, and surface fault categories have significant differences in feature distributions. DANN and CORAL, which only perform marginal distribution alignment, struggle to accurately discriminate these three fault categories. The conditional distribution alignment methods can effectively improve this situation, but the accuracy is still influenced by the fault types. CDAA, proposed in this study, adjusts the alignment of both distributions using dynamic weight factors, aiming to minimize the feature distribution distance among the same fault categories. As a result, CDAA performs well in complex fault classification tasks. The same conclusion can be drawn from Experiment 2, demonstrating the robustness of CDAA in different conditions.ω2 is set to balance domain alignment and class alignment training. Moreover, using information entropy as an indicator to measure the data’s classification ability, another dynamic weight factor ω1 is introduced to balance adversarial training and classification training. Comparative experiments on different datasets demonstrate that the proposed model achieves superior fault diagnosis accuracy compared to other models, achieving accuracies of 92.45% and 95.68%, respectively. The experiments also show that this method is more adaptable to various operating conditions and exhibits stronger applicability in the fault diagnosis of wind turbine gearboxes.This paper proposes a novel fault diagnosis model for wind turbine gearbox, called CDAA, which can improve fault diagnosis accuracy in the absence of labeled target domain data and reduce the impact of data feature domain distribution under different operating conditions. The model utilizes a convolutional neural network as a feature extractor, taking time-frequency spectrograms generated through wavelet transformation as the input to extract domain-invariant features from vibration signals. Domain discriminator and conditional domain discriminator are employed to measure the marginal distribution distance and class distribution distance between the source and target domain features, respectively. Through adversarial training, the model reduces the feature distribution distance between the two domains. The A-distance is used to evaluate the relative importance of domain alignment and class alignment, and a dynamic weight factor


Staphylococcus aureus and environmental pathogens such as Escherichia coli and Klebsiella spp. can affect cows and milk for human consumption, generating a public health risk. This study aimed to estimate the prevalence of herds with somatic cell count (SCC) ≥200,000 cells/mL, S. aureus, E. coli, and Klebsiella spp., in bulk tank milk (BTM) and its associated risk factors in Colombian dairy cow herds.Bovine mastitis is one of the most costly and prevalent diseases in dairy herds, which can be prevented and controlled through proper milking practices, diagnosis, and elimination of chronic animals, among others. Contagious pathogens such as A cross-sectional probabilistic study was carried out in 150 dairy herds located in the north of the Antioquia province. A single visit per herd was conducted, during which three BTM samples were aseptically collected. General data and milking practices were collected through an epidemiological survey applied in each herd.S. aureus, E. coli, and Klebsiella spp. were 14% (21/150), 2% (3/150), and 8% (12/150), respectively. Moreover, 95% of the herds presented an SCC of ≥200,000 cells/mL. Practices such as in-paddock milking, change of milker during the last month, use of disposable gloves, and hand disinfection were associated with increased prevalence of S. aureus, whereas proper dipping was a protective factor. Proper washing and disinfection of the milking machine, use of chlorinated disinfectants for hand hygiene, and use of disposable gloves decreased the prevalence of E. coli and Klebsiella spp. Bulk tank SCC increased in herds with 30–60 milking cows, herds with >60 milking cows, and herds with a change of milker during the last month. Hand disinfection and dipping decreased the SCC.The prevalence of Staphylococcus aureus, E. coli, and Klebsiella spp. were prevalent in BTM from dairy cow herds. The risk of S. aureus isolation was higher in herds with an in-paddock milking system. The risk of E. coli and Klebsiella spp. isolation were higher in herds with >60 milking cows, with a change of milker during the last month. Processes such as avoiding changing the milker and greater control in medium and large herds could improve the SCC in BTM. Bovine mastitis is one of the most important diseases of the udder tissue, affects specialized dairy farming, and is the most common and costly disease in dairy herds worldwide –3. EconoStaphylococcusaureus, which is the prime etiological agent of contagious bovine mastitis and is closely linked to milking hygiene, as well as udder and leg hygiene [S. aureus are difficult to treat and particularly challenging because of their tendency to become chronic and recur [S. aureus strains have the potential to express several enterotoxins in the case of foodborne intoxication in humans [Staphylococcus aureus food contamination by food handlers is considered the most common source of staphylococcal food poisoning; however, outbreaks have also been associated with the consumption of raw milk or raw milk cheese derived from dairy animals with mastitis [Escherichia coli and Klebsiella spp., are known as the main bovine mastitis pathogens associated with environmental mastitis [The etiopathology of bovine mastitis is complex and information on the prevalence and distribution of mastitis-causing bacteria , 8, as w hygiene , 12. Intnd recur  and theind recur . In addin humans . Staphylmastitis . In addimastitis . These mS. aureus in small dairy cattle herds [et al. [In Colombia, several non-probabilistic studies have reported the presence of contagious and environmental pathogens as a cause of intramammary infections in dairy cattle –21. Somele herds . In addile herds , 24. Rey [et al.  reportedS. aureus, E. coli, and Klebsiella spp., in BTM and associated risk factors in Colombian dairy cow herds.Considering the above, this study aimed to estimate the prevalence of herds with SCC ≥200,000 cells/mL, This study was approved by the Ethics Committee for Experimentation with Animals of the Universidad de Antioquia, Colombia . Farmers provided informed consent before data collection.The study was conducted from August 2019 to January 2020 in the municipalities of Santa Rosa de Osos, Entrerríos, and San Pedro de los Milagros, which are recognized as having the highest milk production in the north of Antioquia, Colombia. The sampling frame was the database of the anti-foot and mouth disease vaccination program, corresponding to the first period of 2018, which covered approximately 95% of the dairy cattle population in the area. According to this database, the dairy cattle population in the three municipalities in that year included 107,395 animals distributed in 8200 herds .S. aureus without the hypothesized risk factor (washing hands before milking each cow) (P1 = 0.1), and expected prevalence of S. aureus with the risk factor (not washing hands before milking each cow) (P2 = 0.45) [In this cross-sectional probabilistic study, the sample size was calculated using the PROMESA™ Software version 2.3.0.2  by applying the “comparison of proportions” command. For this calculation, a confidence level of 95%, power of 90%, expected prevalence of  = 0.45)  were conConsidering the aforementioned sampling framework, stratified random sampling was carried out, where the number of herds sampled was proportional to the total number of cows in milk production per municipality. Herd selection was carried out in the three districts of each municipality with a higher number of cows in milk production. The number of herds selected for each district was proportional to their percentage share in the number of herds in the municipality.In all cases, herds had to fulfill the following inclusion criteria: (1) Having a BTM – not shared or a community one; (2) willingness of the owner to participate  voluntarily; and (3) having an easily accessible herd.For the random herd selection, a consecutive number was assigned to each herd in each selected district, and random numbers were then chosen using the “random number” tool of Microsoft Excel . Using the contact list, one of the authors contacted the herd owner or manager by phone, to validate compliance with the inclusion criteria and schedule the visit. When one of the herds must be replaced, the researchers selected another herd from the list of eligible ones.S. aureus, E. coli, and Klebsiella spp. All samples were transported under refrigeration at 4°C in Styrofoam coolers with sealed ice blocks until they arrived at the Diagnostic Unit of the Faculty of Agrarian Sciences. Once at the laboratory, samples were kept under refrigeration for a maximum of 24 h until analysis.A single visit was made to each of the 150 herds, between August 7, 2019, and January 18, 2020. An epidemiological survey was conducted in each herd to identify herd-level and milking management practices. Bulk tank milk sampling was conducted in each herd once. Before the collection of the milk sample, the raw milk inside the bulk tank was shaken, and from each tank , three milk samples were collected aseptically in 33 mL sterile screw-top plastic containers, following the protocols established by the National Mastitis Council of the United States [® Group Ltd., Shandong, China), 0.01 mL of milk samples was streaked on Columbia agar plates supplemented with 5% sheep blood . This procedure was repeated on MacConkey agar plates . Each plate was incubated at 37°C for 48 h. Colonies on Columbia agar plates were selected by morphology, Gram stain, and catalase test result. Gram-positive and catalase-positive colonies were subjected to BD BBL® tube coagulase  and plate mannitol (Merck) biochemical tests. Isolates positive for all biochemical tests were selected as S. aureus. Colonies grown on MacConkey agar plates were subjected to the oxidase strip test (Merck). The oxidase-negative colonies were subjected to biochemical tube tests to screen for identification on the genus and species levels, triple sugar iron agar, indole, citrate, urea, and lysine.Each of the 150 BTM samples was left at room temperature (22°C) for 30 min and homogenized 30 times by inversion. Microbiological procedures were performed in a Type II Biosafety cabinet. Briefly, using a sterile calibrated loop .Each of the 150 BTM samples was analyzed by automated procedures using flow cytometry with the FossomaticS. aureus, E. coli, Klebsiella spp.) if at least one isolate of the pathogen was found per milk sample. A herd was positive for Gram-negative bacteria when E. coli and/or Klebsiella spp. was isolated. For the SCC analysis, the cutoff SCC was 200,000 cells/mL, in which herds with SCC ≥200,000 cells/mL were considered affected by SM [A herd was defined as positive for any of the pathogens of interest  for statistical analysis. Data were examined for biologically implausible entries, and erroneous entries were removed or corrected. Descriptive statistics were calculated for all variables of interest. Variables with >30% missing values were eliminated. All study variables were described as frequency and percentage. For all study outcomes , prevalence and a 95% confidence interval  were estimated and adjusted by sample design using Stata’s svy linearized command.All the information collected using the epidemiological survey and laboratory results were entered into Excel worksheets (Microsoft Corp.) and then exported to Stata 16.0The crude prevalence ratio and its 95% CI municipality-adjusted cluster were estimated to determine the factors associated with each outcome, considering p < 0.05 as significant. In addition, Chi-square test, Fisher’s exact test, or the likelihood test was used to assess statistical significance, according to each case. For the SCC variable, the geometric mean and its 95% CI and statistical significance were estimated using the Mann–Whitney U test because the variables did not follow a normal distribution according to the Kolmogorov–Smirnov test. For the selection of the variables to be included in the multivariate models, those with p < 0.25 by the bivariate analysis and those previously reported in the literature were used. For dichotomous outcomes, binomial regression or Poisson regression was used when the former failed to converge. For continuous outcomes, a generalized linear regression model with γ-family and identity bond was used. All main exposures of interest were adjusted for potential confounding variables by readjusting the final models and omitting the variables to see if the coefficients of other predictors changed substantially. The interaction of variables was also evaluated by including the term in the model whenever it was significant. For the selection of the final model, Akaike’s information criterion was used. All analyzes were performed using Stata 16.0® software (StataCorp).In this study, 44.7% of the herds have <30 milking cows, half of the herds only have one milker, and a little more than 50% of the milkers own the herd (55.3%). In addition, according to herd type , 79.3% of the herds are closed. In the geographical area where the municipalities and herds are located, two milking times per day are common (98.7%), using milking mechanical devices (92%), and in-parlor milking facilities (45.3%). Therefore, most of the herds do not have automatic separators (82.7%); however, they conduct maintenance activities of the milking equipment (90%) at least every 6 months (57.4%) or every year (17.6%) .The disinfection of the milking system is conducted manually (64%) using a milking protocol (91.3%) on a formal basis (60%). For the milk tank, a little more than half of the herds (55.7%) use the formal disinfection protocol . In relaS. aureus, E. coli, and Klebsiella spp., respectively. Moreover, 22.7% of the herds were positive for at least one of the pathogens analyzed, and 10.7% were positive for one of the coliform bacteria (E. coli and/or Klebsiella spp.).The microbiological culture of the 150 BTM samples showed an apparent prevalence for the three municipalities of 14% (21/150), 2% (3/150), and 8% (12/150) for The analysis of the SCC of the BTM samples showed that in the 150 herds visited, a geometric mean of 445,200  cells/mL and an arithmetic mean of 507,966  cells/mL were found. Moreover, 94.9% (95% CI: 89.3–97.6) of the herds presented an SCC of ≥200,000 cells/mL.S. aureus isolation in BTM by 33%, compared with in-parlor milking. The change of milker during the last month tended to be associated with a 50% increase in the prevalence of S. aureus compared with those who did not report such change (p = 0.08). Hand disinfection between cows, even when gloves are used, decreased the prevalence of S. aureus by 92% compared with not doing so. The use of chlorinated or other disinfectants  as hand disinfection products was associated with a 40% and 43% lower prevalence of S. aureus, compared with not disinfecting hands. Herds that used disposable gloves tended to have increased S. aureus incidence by 2.2 times compared with herds that did not use them (p = 0.07). Appropriate teat post-dipping decreases the prevalence of S. aureus by 49% compared with not doing so. An interaction effect was observed between the number of milking cows and hand disinfection between cows, which increased the prevalence of S. aureus in BTM samples by 3.5 times  were associated with a 3.48-fold increase in the prevalence of bacteria .According to the generalized linear regression analysis, the SCC increases as the number of milking cows also does; thus, the SCC increased by an average of 117,000 cells/mL in the BTM of herds with 30–60 milking cows compared with those with <30 milking cows, whereas herds with >60 milking cows had an average increase of 155,000 cells/mL. The SCC decreased by 35,000 cells/mL on average in herds that had a change of milker during the last month compared with those that did not change. Compared with herds that did not use hand disinfection, those that used other disinfectants  as hand disinfection products showed a trend of increasing SCC by 176,000 cells/mL on average. Hand disinfection between cows was associated with a decrease of 150,000 cells/mL on average compared with not doing this procedure within the milking routine. Appropriate fore-stripping was associated with a decrease of 116,000 cells/mL on average in the BTM compared with those that did not undergo this procedure .This study was conducted in specialized dairy herds located in one of the main dairy basins in Colombia, and since the country’s specialized dairy areas share similar characteristics, such as average temperature, specialized dairy breeds , development feeding systems, and infrastructure, focused on milk production , two milCrencus clandestinum) and are only supplemented at the milking time with commercial concentrate. Conversely, Colombia is not a seasonal country, and its climate varies between dry and rainy periods; therefore, pastures are present throughout the year. For all of the above and because this study did not evaluate individual animal conditions, the authors did not consider the effect of feeding on the results of this study; thus, it could be taken into account for future research.In specialized dairy systems in Colombia, the cows are not stable, and the cows are fed directly on pasture grass , which, according to some authors, indicates technification or intensification of the production system; therefore, these systems have allowed improving parameters related to milk production and proportion of milking cows . In relaalactiae , which hS. aureus in this study is lower than that reported by the previous studies conducted in BTMs in Colombia [The prevalence of Colombia , 35 and Colombia , United Colombia , Canada Colombia , and DenColombia , but higColombia . The difColombia  and theiStaphylococcus aureus isolation in BTM indicated that milking cows were infected with this pathogen inside the herds [S. aureus successfully remains in the cow population and it can be spread by the milker’s hands or milking machine from the infected animals to healthy ones during milking. In addition, its virulence factors allow it to establish itself subclinically and chronically in the mammary gland, turning infected animals into primary reservoirs and increasing the risk of intra-herd spread [he herds . This isd spread , 41. Thed spread , combined spread , was proS. aureus in the study herds could be due to their herd type (according to purchasing practices) — where 21% of the herds are open—and lack of effective prevention, control, and eradication plans in the area, coupled with the little or scarce implementation of diagnostic tools to identify the organism with the highest incidence in animals. In this way, the presence of infected animals in the herd without a clear diagnosis of the same, and therefore without actions aimed at its control, increases the risk of dissemination to healthy animals, people who consume raw milk, or those who are in direct contact with the animals. Consequently, implementing udder health programs complemented with direct educational campaigns to milkers and workers is necessary to correct the problems [The presence of problems .E. coli found in this study is lower than that reported by the previous studies conducted in BTM in the country  [The prevalence of pp., 5%) , 35. Howpp., 5%) , Korea  , and Brapp., 5%) . The difKlebsiella spp. was found when compared with E. coli in the study BTMs. Klebsiella spp. is found in the environments, especially in used bedding material, fecal shedding, soil, water troughs, rumen content, alleyways, holding pens, and water [Klebsiella spp. may be due to washing utensils with running water (contaminated with the pathogen) in the study herds; therefore, the recommendation is to improve the hygienic quality of water for washing utensils and milking practices to avoid contamination of pathogens that can affect people who consume raw milk or its derivatives [A higher prevalence of nd water , 46. Becivatives .E. coli could contaminate the milk during or between milkings, thus reaching the BTM [Although this study cannot guarantee that the isolated Gram-negative bacteria come from the animals themselves, bacteria such as  the BTM . In addiE. coli and Klebsiella spp. is a matter of concern in recent times because Enterobacteriaceae have been reported to have virulence factors that can cause hemorrhagic syndromes or antimicrobial resistance factors in strains isolated from raw milk or its derivatives, representing a risk to public health. In this sense, establishing control and prevention measures is necessary, especially in the milking routine and procedures, to prevent their presentation in the cooling tank [The contamination of the BTM by coliform bacteria such as ing tank , preventBos indicus and Bos taurus crossbreeds predominate, the cows are milked once a day, and the calf remains next to the mother during milking and grazing [The average SCC in the study herds was lower than that found in BTM in the province of Valle del Cauca (Colombia) and the same region of the present study , 34, but grazing . The forS. aureus.The findings of this study show that most of the herds analyzed had an SCC of >200,000 cells/mL, a cutoff point that has been used in other countries for monitoring milk quality in udder health programs, both in animals and BTM . AccordiS. aureus, which therefore, can increase the SCC in the quarter and finally in the BTM. Thus, the findings at this level reinforce the concept that BTM SCC assessment is an inexpensive diagnostic tool that assists veterinarians and producers in monitoring mastitis-specific pathogens in a cow population [In the multivariate analysis, inadequate practices during milking increased the risk of intramammary infections by pulation  since a pulation . Thus, iS. aureus (47%) and a higher SCC were found in large herds [Given that the SCC increases as the size of the herd does, this could be due to a greater control applied over the processes, such as the milking protocol, for the prevention of contagious pathogens in small herds. This finding is consistent with those of other studies in which a higher prevalence of ge herds , 22, 38.ge herds , puttingS. aureus isolation in the herd. In this study, 88% of the in-paddock milking systems were mechanical, which probably means that this special characteristic of this system  in the region is a risk factor for the infection of cows with S. aureus. However, more studies are needed to understand this possible link. Although the milking system characteristics are not the same, these findings are consistent with a study that found a higher probability of isolating the pathogen in herds that used mobile milking machines in Portugal [Interestingly, in this study, the in-paddock milking system was a risk factor for Portugal . At leasPortugal . In addiS. aureus positivity in BTM. Among them, surprisingly, the use of disposable gloves showed a trend to increase the prevalence of pathogens. Although disposable gloves did not show statistical significance, the trend is noteworthy given that this finding differs from what was evaluated in other studies, in which the use of disposable gloves decreases the incidence of S. aureus and other contagious pathogens. In addition, not wearing gloves was related to herds with BTM SCC ≥200,000 cells/mL [The milking protocol is part of the internationally established control and prevention measures such as the 10-step program to prevent and control bovine mastitis , 3. Thiscells/mL , 52. SinS. aureus isolation, which agrees with the findings of other studies that not executing it was a risk factor for the presentation of the agent and SM in cows [Adequate post-dipping of teats was a protective factor for  in cows , 31, 53.Most of the producers in the evaluated area follow the classic milking protocol . However, practices such as drying teats with newspaper, which is frequently used in dairies in the country, despite not being supported by any study, are recommended by technicians and professionals in the sector.S. aureus [Although most herds followed the routine milking steps, it is necessary to harmonize their execution protocol in the herds, because, according to the study finding, details in the implementation of this protocol can interfere with the effective prevention and control of milking pathogens. A study identified that the implementation of standardized, systematic, and constant programs for the prevention of mastitis have reduced the SCC in BTM samples and the prevalence of pathogens such as . aureus .E. coli and Klebsiella spp.) in raw milk. These findings are consistent with those of other studies in which increased bacteria counts in milk were associated with poor milking hygiene, dirty equipment, inadequate disinfection practices, and milk stone deposits in pipes, suggesting that an inadequate cleaning system can be an important risk factor for BTM contamination [We confirmed that some processes  decrease the prevalence of Gram-negative pathogens  influence the efficacy of pre-dipping [To our surprise, the use of the manufacturer’s recommended pre-dipping concentration was associated with an increased prevalence of -dipping .S. aureus, E. coli, and Klebsiella spp. and the increase in SCC in the BTM. This finding agrees with the results of other studies in that SCC, and consequently mastitis, increased significantly with herd size [In this study, the increase in the number of milking cows was associated with an increase in the probability of isolating erd size , 57.A lower SCC was found in herds that performed forestripping. This has been previously identified by other authors who reported that forestripping is one of the best methods to reduce SCC in the BTM, being also a method that allows the identification of changes in milk appearance and animals affected by clinical mastitis and avoids adding low/poor quality milk to the bulk tank .S. aureus and consequently increase the SCC in the BTM [Inadequate hygiene practices can increase the probability of isolating  the BTM , 51, whiImportantly, Colombia does not have a national SCC control and evaluation program; therefore, the implementation of regional or national mastitis monitoring programs is recommended, where SCC is evaluated at least once a month to give special attention to chronic cases, determine the order of entry to milking, and make decisions to dispose of infected animals .Conducting a single visit per herd and obtaining data directly from the milkers, not from other sources, are limitations of this study because data provided could bias the reality of what is implemented in milking. Despite this, producers provided all the requested information without difficulty.S. aureus, E. coli, and Klebsiella spp. were prevalent in BTM from dairy cow herds. The risk of S. aureus isolation was higher in herds with an in-paddock milking system, probably in-paddock mechanical milking; however, more studies are needed to understand this possible link. The risk of E. coli and Klebsiella spp. isolation was higher in herds with >60 milking cows, with a change of milker during the past month, and when hand disinfection between cows is carried out, even if gloves are on. Processes such as avoiding changing the milker and greater control in medium and large herds could improve the SCC in BTM. Finally, implementing a national udder health monitoring program, considering the conditions of the regions, is necessary to influence the practices that can alter the quality of raw milk and the health of cows.This study highlights the importance of identifying the risk factors present in developing tropical countries such as Colombia, whose milking systems are diverse and constantly changing . According to the results, JAF and NFR: Designed the study. ASA: Collected samples, performed experiments and drafted the manuscript. JAF, NFR, and ASA: Analyzed and interpreted the data. All authors have read, reviewed, and approved the final manuscript.


Introduction: The Objective Structured Clinical Examination (OSCE) is the mainstay of clinical assessment in the final-year undergraduate Family Medicine clerkship at King Faisal Specialist Hospital and Research Centre (KFSHRC). The gold standard for OSCE assessment is the checklist rating, completed by physician examiners. Numerous studies have suggested that global or domain-based OSCE ratings may be a better indicator of competence than checklist ratings. The aim of this study was to examine the utility of domain-based OSCE ratings in the context of final-year, undergraduate, Family Medicine OSCE examinations in Riyadh, Saudi Arabia. This is akin to an exercise in quality improvement, as we continuously look for ways to improve our OSCE assessment processes.Methods: This study utilised a quantitative methodology. Three final year OSCE exams were chosen. Physicians rated each student using a checklist score and using a more holistic domain-based score. Physician checklist scores and physician domain-based scores were then compared, and correlation was assessed. We also looked at the internal consistency of the scoring methods.Results: A significant correlation was found between checklist and domain-based scores by physicians for all exams , with a good internal consistency for these methodologies for all exams.Conclusion: The results demonstrate that both checklist and domain-based scores offer some benefit to the assessment, with a similar internal consistency and strong correlation. Domain-based ratings should be utilised for softer skills that are not easily assessed by checklists. There is clearly a need to rethink our OSCE assessment. The assessment should combine checklist and domain-based physician scores. As trainees become more experienced, checklist OSCE may penalise directness and efficiency, while domain-based ratings would offer a better appraisal of competence, and have been shown to be more sensitive to the level of training and expertise. Changing the assessment methods will lead to necessary changes in the student approach to the OSCE and improve authenticity and validity. The need for fair, reliable, and accurate assessment of medical trainees is a challenge that has been studied extensively. Everyone recognises, for example, that a good family physician is someone whom patients would happily be treated by, and be comfortable following up with regularly. The challenge is to design assessments that can measure these qualities that are difficult to define, and even harder to assess. Summative assessment, or assessment of learning, allows us to grade performance to ensure that the trainee has reached the required standard to practice in a safe and competent manner, as well as to provide a way of discriminating among levels of competence as trainees compete for higher training posts ,2.The Objective Structured Clinical Examination (OSCE) is a standardised simulation intended to be carefully designed in alignment with learning outcomes that are mapped to curriculum objectives . HoweverThe OSCE has long been championed as the benchmark for clinical assessment, with detailed binary checklists containing clear, pre-determined criteria for recording the presence or absence of specified behaviours. These might produce more reliable, valid, objective and therefore unbiased results than the global assessment of long case or overall clerkship performance . The purHowever, Norman and Feightner opined that the essence of the effective physician was not merely knowing how best to perform what they are asked to perform, but actually determining what it is that needs to be done and focusing on the most essential issues . As suchDreyfus and Dreyfus have described five stages of development in trainees, starting at the novice level, where large amounts of data are collected in the consultation, in a non-structured approach, in an attempt to formulate a diagnosis . The traDomain-based ratings are more holistic judgements of performance, not confined to specific behaviours or actions that must be performed. As a result, they are much less likely to encourage rote memorisation of knowledge or behaviours. Domain-based ratings therefore allow for the fact that the same problem can be approached in different ways, allowing for the recognition of superior levels of competence and efficiency, geared more towards quality than quantity and breadth of coverage . In esseVan der Vleuten found that as a predictor of future performance levels, domain-based ratings demonstrated significantly enhanced predictive power when compared to checklist ratings, while by contrast, checklists did not appear to provide a true measure of overall professional competence .Several metrics are now commonly used for analysing the reliability of an OSCE assessment. Cronbach’s alpha is a measure of the internal consistency of a test, with a minimum alpha value of 0.7 or 0.8, suggesting a reliable test . HoweverWard et al. showed that the addition of the checklist scores to the domain-based ratings did not appear to significantly affect the overall OSCE reliability in a positive or negative way . This woClearly, it is important that the OSCE reflects the reality of clinical consultations as much as possible, and that the assessment process is valid, i.e., it truly measures the important knowledge, skills and attitudes that are required for the competent practice of medicine. OSCE has become the gold standard of undergraduate medical assessment, and it has been assumed that OSCE performance can be readily extrapolated to performance in real clinical practice . Any disAlthough there has been considerable debate in the literature about the validity of checklists versus domain-based scoring, few studies have compared these two methods directly . In an aSampling strategyUndergraduates each complete three 10-minute OSCE stations with simulated patients (SPs) and three different physician examiners at the end of their fifth year Family Medicine clerkship. The study population comprised final year students undergoing this OSCE between October and December 2020. Three groups of students were included, with approximately 20-25 students per exam, for a total study population of 71 students, passing through a total of 213 OSCE stations. Sampling strategy was purposive non-random sampling, as every student who passed through the Family Medicine clerkship at King Faisal Hospital during the named period was included.ScoringIn each of the OSCE stations, one physician examiner scored the OSCE using a standard checklist rating method, as well as domain-based ratings organised into four domains: clinical competence, communication skills, knowledge and empathy. An example of a checklist rating scoresheet (out of 30) and a domain rating scoresheet (out of 20) is provided in Appendix 1 and Appendix 2, respectively. Examiners were purely silent observers and evaluators of the consultation during the OSCE, neither asking questions nor giving prompts. The examiners were instructed to add up the total checklist scores only after they had entered the domain-based scores, to reduce the likelihood that the checklist scores might affect the domain-based scores. A rubric was prepared for examiners to standardise the marking process (Appendix 3). The rubric was used during the training sessions to practice some scenarios with the participants and to resolve any inconsistencies or confusion in rating trainees. Students were aware that the official documentation of their summative performance would be from checklists, as has been the practice at this institution since the clerkship began nine years ago. From the student’s perspective, nothing about the assessment environment was different from normal.Data analysisThe analysis of the quantitative data started with descriptive statistics including range, mean, standard deviation, skew and kurtosis for each of the scoring methods. Next, correlation was checked between the two data sets, examiner checklist ratings and examiner domain-based ratings. Physician domain ratings for trainees were correlated with physician checklist ratings for those same trainees in the same OSCE stations. Correlation was performed using the Spearman's rank correlation, a non-parametric test, because the data was not normally distributed. Interstation reliability was also checked using Cronbach’s alpha, for each scoring method. Statistical analysis was performed with SPSS, version 27 .The study was approved by the University of Dundee School of Medicine Research Ethics Committee (SMED REC number 20/105) as well as the Research Advisory Committee at King Faisal Specialist Hospital (RAC#2201125).Quantitative dataAll 71 eligible Al-Faisal University final-year medical students agreed to participate after informed verbal consent was obtained. In OSCE round 1, 20 students were recruited, in round 2, 25 students were recruited, and in round 3, 26 students were recruited. No students declined or withdrew from the study. Figure Figure This observation was confirmed by the Shapiro-Wilk test: p values were <0.05 for every station in all three rounds. The distribution of checklist scores had a skew of -0.73 and a kurtosis of 0.86, while the distribution of domain-based scores had a skew of -0.28, and a kurtosis of -0.77. This indicates that the checklist scores were moderately negatively skewed, while the domain-based scores were only slightly negatively skewed. Regarding kurtosis, checklist scores demonstrated a positive kurtosis suggesting a more peaked distribution, whereas domain-based scores demonstrated a negative kurtosis, suggesting a flatter distribution with thinner tails.Table Both checklist and domain-based scoring produced some scores of 100%, i.e. maximum scores were given to some students with either method. Minimum scores were similar with the two methods: 10/30 (33%) with checklists and 6/20 (30%) with domains.Table Table There was a strong correlation between domain-based total and checklist total scores for the entire group, with a correlation coefficient of 0.858 (p<0.01).The results suggest that the correlation between physician checklists and domain-based scores is strong and positive. Cronbach’s alpha comparisons for these two grading methods also show similar levels of internal consistency for both physician checklist and domain-based scores for each of the three separate OSCE examinations. This is in agreement with previous studies, which found similar reliability and a good correlation between the two scoring methods ,24. One Assessment drives learning. Clearly, students would be aware of the system of assessment and would adapt their behaviours and consultation manner to suit the perceived system of evaluation. A checklist evaluation will prompt a more thorough approach to the consultation, whereas a domain-based scoring system might prompt a more focused and patient-centred consultation. McIlroy et al. found that when students were expecting a checklist evaluation, they performed better on the checklist scoring system and worse on the domain-based evaluation . HoweverExperienced, knowledgeable physicians do not solve real-life problems in a purely ‘checklist’ manner. At the very least, it appears that a mix of assessment indicators is required to enrich the process and lead to the construction of more holistic, personalized assessment information that could be used in both a formative and a summative capacity to improve patient care.In a recent study, Giemsa et al. found that domain-based ratings were more sensitive discriminators than checklist scores in differentiating between clinical and pre-clinical undergraduate medical students in a family medicine OSCE . This waThe most important aspect of the evaluation is the OSCE station design itself. Station designers should ask themselves whether the stations are testing what they need to test, with the correct methods and suitably trained evaluators? Pell et al. found that ‘chunking’ or grouping together related checklist items into ratings scales, for example, overall introduction or pharmacological management, significantly improved OSCE reliability, and would encourage trainees to gain a deeper understanding of the topic, rather than learning checklists . At the Checklists might measure information-gathering and completeness more effectively, while domain-based ratings may be more suited to the appraisal of communication skills, empathy, consultation structure and general competence. Adding checklist items that pertain to these latter skills seems inappropriate, as the skills themselves transcend any individual consultation and are instead indicators of a holistic and efficient approach to patient care in general. The triangulation of all available assessment data allows us to paint a comprehensive picture of the trainee’s performance, which can be utilised in a formative or summative manner.A possible limitation of this study includes its reliance on data from a single institution. This may mean that there is limited generalisability of findings. Additionally, examiners and stations were different for each examination. This was a logistical necessity. Another limitation is that the trainees were all final-year undergraduates. Trainees with different levels of experience, such as interns or residents, were not included in this study. Turner et al. found that the correlation in OSCE between domain-based scores and checklist scores increased for more advanced students in a physiotherapy department . This maKane proposed a framework that provides an approach to evaluating the validity of an assessment . This frThe theme that seems to be emerging is that there is no ‘best’ way to undertake the OSCE examination. There are many variables that might affect one’s choice of assessment rating, including the level of the trainees, the domains being assessed and the resources available. Physician checklist and domain-based scores were reliably positively correlated, and both showed a reasonable internal consistency, with both rating methods having their place in undergraduate assessment.Locally, there is certainly a need to improve the validity and reliability of our own OSCE assessments by increasing the number of stations, basing all the stations on real clinical scenarios to increase authenticity, and blueprinting the exam such that all aspects of medical expertise are tested, including knowledge, examination skills, communication skills, ethics, counselling, professionalism, advocacy and even teaching skills. Specific stations could be designed to test specific skills rather than trying to incorporate as many skills as possible into each station, which might lead to inadequate assessment of all skills.A growing body of evidence supports the idea that domain-based ratings are more reliable than checklists, producing consistent, reproducible ratings, and providing a more accurate means of discriminating between different competence levels of trainees. Checklist items should be relevant, evidence-based, clinically discriminating items. Areas of competence that are not readily accessible to checklist scoring should be scored by domain-based ratings. Well-designed checklists, in association with domain-based ratings, have a vital role to play in the assessment of undergraduates, especially, as there is a process that novices need to go through to gather all the necessary information. Only by regularly going through this process will they eventually attain expert status, at which point a more focused consultation methodology would certainly have developed naturally in the physician. The transition from novice to expert involves a shift from analytic, piecemeal thinking to a more efficient holistic approach. As the trainees become more experienced, a shift to a more domain-based rating method would certainly seem to be warranted, to avoid punishing the efficiency that stems from experience and, indeed, expertise.


Flexible covalent organic frameworks (COFs) have been studied for applications containing sorption, selective separation, and catalysis. How to correlate the microscopic structure with flexibility in COFs is a great challenge. Herein, we visually track the flexible deformation behaviors of single COF-300 and COF-300-AR particles in response to solvent vapour guests with dark-field microscopy (DFM) in an in operando manner. COF-300-AR with freely-rotating C-N single bonds are synthesized by the reduction of imine-based COF-300 consisting of rigid C=N double bonds without changing topological structure and crystallinity. Unexpectedly, we observe that the flexible deformation of COF-300 is extremely higher than that of COF-300-AR despite it bears many C-N single bonds, clearly illustrating the apparent flexibility decrease of COF-300 after reduction. The high spatiotemporal resolution of DFM enables the finding of inter-particle variations of the flexibility among COF-300 crystals. Experimental characterizations by variable-temperature X-ray diffraction and infrared spectroscopy as well as theoretical calculations demonstrate that the flexible deformation of COF-300 is ascribed to the pedal motion around rigid C=N double bonds. These observations provide new insights into COF flexibility. To correlate the microstructure of flexible covalent organic frameworks with their flexibility is challenging. Here, the authors visually track the deformation behaviors of single covalent organic framework particles with dark-field microscopy discovering that their flexibility is dictated by the pedal motion around rigid imine bonds. In particular, the flexibility of some COFs is considered as a key feature differing from traditional porous materials, including zeolites and activated carbons9. For instance, flexible COFs can dynamically change the pore diameters/shapes during the host-guest recognition process, displaying attractive elasticity, good affinity, and self-adaptive ability for superior adsorption, highly selective separation, and catalytic activity improvement12. To obtain the flexible COFs, flexible building blocks such as C–O and C–N single bonds have been incorporated into the backbone16. Indeed, sp3 carbon-involved single bonds rotate freely, and the rotation of double bonds is strictly restricted. However, it is questionable whether the local flexible single bonds must result in the whole flexibility of COF crystals. Accordingly, fundamentally understanding the microscopic structure-flexibility relationship is extremely important for guiding the design and development of advanced flexible COFs.Covalent organic frameworks (COFs) have shown great application potential in separation, gas storage, catalysis, and sensing because of their tunable active sites, large surface area, good stability, high crystallinity, and regular microporous structures17. Although adaptive structural transformations such as contraction, expansion, and distortion have been documented8, these bulk-ensemble measurements simply average the flexible behavior of many COF crystals due to the lack of spatial resolution, masking the flexibility differences among individual COF particles. Actually, the preparation of high-quality crystals is a still huge challenge in the chemistry of COFs18. The synthesized flexible COFs always display a wide distribution in regard to shape, size, crystallinity, and surface defect19. Significant heterogeneity among different flexible COF crystals is inevitable. Investigating the structural transformation of flexible single COF particles therefore represents a powerful avenue to gain the intrinsic flexibility via eliminating the heterogeneity.Currently, the flexibility of COFs is usually revealed by X-ray diffractions (XRD) and adsorption isotherms20. DFM which collects the elastic scattering light has been widely applied to image individual plasmonic nanomaterials and dielectric nanoparticles23. Recently, we have confirmed the feasibility of DFM for spatiotemporally investigating a series of physical and chemical processes of single COFs and metal-organic frameworks (MOFs) based on their inherent Mie scattering features, including adsorption, thermal decomposition, and expansion26. Nevertheless, how the structures of local chemical bonds influence the whole flexibility of COFs remains unknown.Dark-field microscopy (DFM) has emerged as an economical and effective optical imaging technique for in situ monitoring of physical properties and chemical processes with nanoscale spatial resolution in the past decades27, directly observed by DFM with single-particle resolution  frameworks (COF-300-AR)ion Fig. . The genion Fig. . Single-27, the COF-300-AR is prepared by chemical reduction of COF-300  groups emerge  . At t = 0 s, both COF-300 and COF-300-AR are ellipsoidal , both COF-300 and COF-300-AR are not deformed, and the ΔR values are zero all the time, as shown in Fig. In addition, to prove the generality of the flexibility difference between COF-300 and COF-300-AR for different guest molecules, we image the corresponding structural evolution processes in the presence of various solvent vapours, including isopropanol (IPA), n-hexane, water, tetrahydrofuran (THF), and ethyl acetate (EA). As displayed in Fig. The high spatial resolution and wide-field imaging feature of DFM enable in situ examining single-particle-level deformation processes on highly heterogeneous COF-300 crystals in terms of size and shape, which are inaccessible to conventional bulk-ensemble tools. Figure 29. Previous reports have demonstrated that the pedal motion can regulate the expansion behavior of organic co-crystals30. In consequence, we infer that the flexible deformation of COF-300 crystals is dependent on the pedal motion around rigid C = N bonds in the framework. To determine the dynamic conformations of C=N bonds in COF-300, variable-temperature infrared spectra are measured under a nitrogen atmosphere at different temperatures. As depicted in Fig. −1 is shifted to 1618.9 cm−1 when increasing the temperature from 300 K to 500 K, illustrating the different conformations of C=N bonds (planar/nonplanar) due to the pedal motion29. Oppositely, the N–H bending vibration at 1252 cm−1 in the COF-300-AR is almost invariable at different temperatures  as the crank arm Fig. 28,29. Pr31. Other parameters such as bond lengths and bond angles are not changed at different temperature -C(9)-C(8)-N(7) at the torsion angle of 180° in Fig. In order to acquire further insight into the pedal motion within COF-300, we conduct quantum-mechanical calculations on N, 1-diphenylmethanimine as a model molecule Fig. . The torIn summary, we have applied in situ DFM to visually study the flexible deformations of single imine-based COF-300 before and after reduction to COF-300-AR, uncovering an unforeseen and significantly diminished flexibility in COF-300-AR with freely-rotating single bonds. The present imaging results demonstrate that the observed flexible deformations of COF-300 crystals are influenced by guest concentrations and properties, displaying particle-to-particle heterogeneity. By combining DFM observations, variable-temperature XRD/IR measurements, and theoretical calculations, we have revealed that the pedal motion of C=N double bonds dictates the flexible deformations of COF-300. Given the widespread C=N linkages within COFs, the discovered pedal motion-dependent deformation not only enriches our fundamental understanding of the flexibility, but also paves the way for rational design and development of more flexible COFs. From the point of view of accurate measurement, these findings highlight the requirement to employ in situ high-resolution tools for evaluating the flexibility of COFs at the single-particle level.p-phthalaldehyde (BDA), tetrakis(4-aminophenyl)methane (TAM), and aniline were obtained from Leyan Chemical Company. 1, 4-dioxane, acetonitrile, and p-phthalic acid were purchased from Aladdin Reagent Co. Ltd. Sodium borohydride, trichloromethane, dichloromethane, ethyl acetate, tetrahydrofuran, methanol, ethanol, and isopropanol were purchased from Chengdu Kelong Chemical Co., Ltd. All the chemical reagents are of analytical pure grade and directly used without any purification.18. Briefly, the mixture of 12.0 mg BDA, 50 μL aniline, 0.5 mL 1,4-dioxane, and 0.2 mL acetic acid (6 M) was added to a glass vial, followed by the injection of 0.5 mL TAM 1,4-dioxane solution (40.0 mg.mL−1). The reaction mixture is kept at 25 °C for 3.5 days. The final product is collected by centrifugation, washed with ethanol and dried at 70 °C.COF-300 crystals were synthesized by an imine-exchange protocol4 as the reductant27. Briefly, a mixture consisting of COF-300 crystals (50 mg), p-phthalic acid (57.6 mg), and 25 mL of methanol was prepared at room temperature under stirring for 5 min until COF-300 was fully dispersed. Subsequently, 263.2 mg of NaBH4 is slowly added into the above mixture within 10 min, which was further stirred for 10 h. The light-yellow COF-300-AR crystals were obtained by centrifugation and washing with deionized water (18.2 MΩ cm) and ethanol several times, followed by drying at 70 °C.COF-300-AR crystals are further prepared by the reduction of COF-300 using NaBHTM, Olympus) were joined. Before single-particle imaging, COF-300 or COF-300-AR particles were dispersed into deionized water under ultra-sonication. After that, 5 μL of COF-300 or COF-300-AR dispersion was added onto a clean glass slide and dried at 25 °C. A coverslip and two cannulas as the inlet and outlet of solvents were then placed onto the glass slide and sealed with glue, which served as the micro-reaction chamber. Eventually, variable solvent vapours or liquids were introduced to the micro-reaction chamber for single-particle DFM imaging.The dark-field microscopy setup was fabricated on the BX53 microscope (Olympus), on which a halogen lamp incident light source (100 W), an oil-immersion dark-field condenser  = 1.2–1.4), a ×20 objective (N.A. = 0.5), and a color charge-coupled-device camera . Fourier transform infrared spectroscopy measurements were carried out on a SPECTRUM ONE AUTOIMA spectrometer. Variable-temperature X-ray diffraction  in the temperature range of 300–500 K was used to characterize the crystal configurations of COF-300 and COF-300-AR under a nitrogen atmosphere. Variable-temperature Fourier-transform infrared spectroscopy measurements were measured using a Nicolet iS50 spectrometer equipped with an automated temperature controller (Harrick Scientific) under a nitrogen environment. NSupplementary InformationPeer Review FileDescription of Additional Supplementary FilesSupplementary Movie 1Supplementary Movie 2


Codirectional charge transfer and large energetic differences between linkages and linkers are verified in the double donor-acceptor structures of periodic frameworks. The active sites are mainly concentrated on the electron-acceptor fragments near the imine bond, which regulate the electron distribution of adjacent carbon atoms to optimally reduce the Gibbs free energy of O2* and OOH* intermediates during the formation of H2O2.Constructing photocatalytically active and stable covalent organic frameworks containing both oxidative and reductive reaction centers remain a challenge. In this study, benzotrithiophene-based covalent organic frameworks with spatially separated redox centers are rationally designed for the photocatalytic production of hydrogen peroxide from water and oxygen without sacrificial agents. The triazine-containing framework demonstrates high selectivity for H 2O2 from water and oxygen without sacrificial agents.In this study, benzotrithiophene-based covalent organic frameworks with spatially separated oxidative and reductive reaction centers are rationally designed for photocatalytic production of H Currently, H2O2 is manufactured by an energy-intensive and indirect anthraquinone technique4, which involves safety issues caused by mixed H2/O2 and produce toxic byproducts6. Although artificial synthesis of H2O2 using semiconductor-based photocatalysis is an alternative method, the low activity of photocatalysts in pure water and heavy dependence on various sacrificial agents need to be urgently solved8. In terms of sacrificial agents, the introduction of alcohol leads to additional consumption of valuable chemicals, and the resulting aldehydes disfavor the separation of H2O2. Continuous charging with oxygen in photocatalytic systems under dark reaction adds an additional source of energy to the consumption. Much effort has been devoted to developing sacrificial agent-free, energy-saving, and direct processes H2O2 production.A promising path towards a sustainable future is utilizing solar energy to create chemical fuels, such as hydrogen peroxide  and H2O/H2O2 (two holes)9. Most oxidation centers  can only undergo four-electron oxidation of water to oxygen (4e− WOR) due to thermodynamically favorable reactions rather than direct two-electron oxidation of water to H2O2 (2e− WOR). The former has an atomic utilization efficiency of only 68%, while the latter reaches 100%7. If both halves occur at the same/adjacent sites, the efficiency of the reaction is extremely limited by charge recombination. Therefore, direct evolution of H2O2 through a two-electron reaction involving separate oxygen reduction and water oxidation by respective photoinduced electrons and holes provides an ideal routine. Functional motifs with accessible channels and spatially separated redox species in the photocatalytic system that can facilitate the mass transfer and selective formation of H2O2 intermediates in the two-electron pathway are highly desirable.In principle, the H12. The structural tunability and regularity of COFs, which is easily realized by practical building blocks with abundant topologies and dimensionalities, endow broad optical absorption, favorable mass transfer and fast charge carrier mobility15. However, COFs are rarely used as photocatalysts for H2O2 production. Voort et al. reported two COFs based on a (diarylamino)benzene linker for H2O2 production, and subsequently vinyl, fluorinated and Ti-based COFs were used to catalyze H2O2 production20. Most of these reports require sacrificial agents or oxygen bubbling during the reactions. Thiophene is a stable π-aromatic five-membered ring compound, and due to the aromatic rings, electroactive and solubilizing groups can be introduced at each alpha or beta site, with excellent conductivity and adjustable electron density22. The combination of COFs and thiophene motifs is a popular trend in various fields, including ion batteries, hydrogen production, carbon dioxide reduction and organic synthesis25. It was reported that the pentacyclic thiophene-S functional motif in JUC-527 and JUC-528 acted as the active center for the electronic oxygen reduction reaction (ORR), and more thiophene-S (one thiophene-S and bi-thiophene-S) structures enabled higher ORR efficiency26. However, utilizing thiophene-based COFs to produce H2O2 through molecular engineering and mechanistic investigation remain challenge. Functional thiophene motifs can not only be preassembled to easily construct donor-acceptor COFs, but also differ in the transport direction and dissipation of excited charge carriers in the presence of polarized imine linkage. It also provides a paradigm and indicate how the push-pull effects between intramolecular motifs and linkage chemistry in polymers affords high catalytic efficiency. Considering the n-π* transition of the long pairs on sulfur and suitable molecular orbital occupancy, precisely placing independent oxidation and reduction centers in an ordered manner based on thiophene-COFs may be more accessible for photocatalytic H2O2 production.Covalent organic frameworks (COFs), a type of crystalline and nonmetallic polymers, have become feasible and promising platforms in the field of artificial photosynthesis due to their porous structure, photoelectric properties, and photochemical stability2O2 synthesis in water and natural dissolved oxygen under visible light irradiation. Sulfur-rich Btt has a planar conjugated system of C3h symmetry, in which three thiophene rings are blended on the benzene central ring, tending to achieve favorable optical absorption, π-electron delocalization and high hole mobility27. Combining benzotrithiophene-2,5,8-tricarbaldehyde (Btt) and different monomers with various electron-acceptor capabilities, including 4,4,4-triaminotriphenylamine (Tpa), 1,3,5-tris(4-aminophenyl)benzene (Tapb), and 2,4,6-tris(4-aminophenyl)-1,3,5-triazine (Tapt), successfully afforded three kinds of imine-linked COFs, termed as TpaBtt, TapbBtt and TaptBtt , far higher than that of TpaBtt (252 μmol g−1 h−1) and TapbBtt (557 μmol g−1 h−1), and also exceeded all of the previously reported COFs. The efficiency of solar-to-chemical conversion was 0.297 % for H2O2 production, surpassing that of the natural synthetic plants 28. Collected H2O2 can be directly used to degrade sulfamethoxazole  via the Fenton reaction. Mechanistic study and theoretical calculation revealed that the active sites of the three COFs (2e− ORR) were concentrated on the electron-acceptor fragments near the imine bond. The unique electronic structure of TaptBtt provides a sufficient driving force for the synchronous 2e− WOR and 2e− ORR, significantly lowering the Gibbs free energy of OH* and OOH* intermediates for H2O2 generation.In this work, we presented benzotrithiophene (Btt)-based COFs with an intrinsically adjustable charge distribution for nonsacrificial photocatalytic HBtt Fig. . We unveA mixture containing Btt and Tpa  with a molar ratio of 1:1 was adopted via Schiff-base polycondensation under solvothermal conditions, producing TpaBtt, TapbBtt, and TaptBtt. The highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbitals (LUMO) for the three COFs are predicted and displayed in Supplementary Fig. 30. In this work, we referred to the imine bonds as the “atomic spot” and the functional building blocks as the “molecular area”. As shown in Fig. Since the linkage of COFs serves as the connection and transport bridge, the D-A structure within linkage from the perspective of atomic scale should be considered, i.e., carbon of imine bonds as the D unit and nitrogen as the A unit−-h+ recombination  reflection of TpaBtt, TapbBtt and TaptBtt at 2θ = 5.43°, 4.84°, and 4.76°, respectively  plane of the three COFs at the peak position of ~26°, contributes to weak long-range order with an interlayer stacking of ~3.1 Å along the c direction. Fourier transform infrared spectroscopy (FTIR) showed stretching vibrations at 1579, 1617, and 1618 cm−1 for TpaBtt, TapbBtt, and TaptBtt, respectively, which correspond to C=N bond that appeared , as shown in Fig. ayed the 00 reflec13C cross-polarization magic angle spinning nuclear magnetic resonance spectroscopy at the molecular level. As shown in Supplementary Fig. 38. The characteristic carbon signal of imine group for TaptBtt was observed at ~151 ppm, and the relatively high peak intensity is due to its coincidence with the position of benzene ring carbon bonded with nitrogen39. X-ray photoelectron spectroscopy (XPS) of the three COFs displayed C, N, O and S elements  and C=N bonds (represented imine linkage)40. These results provide solid evidence that three kinds of COFs with favorable crystallinity and porosity were successfully prepared. From scanning electron microscopy images and transmission electron microscopy images , compared with TpaBtt and TaptBtt (850.9 and 994.9 m2 g−1) in Supplementary Table 2 in the photocatalytic reactions.The chemical structures of the three COFs were further verified by solid-state 2O2 synthesis, both pure water and air were utilized as the hydrogen and oxygen sources. Figure 2O2 generation and irradiation time for TaptBtt was found compared with the other two COFs. After 90 min of light irradiation, the H2O2 concentration in the presence of TaptBtt reached 3167 μM (31.67 μmol), which was ~5.5 and 2.5 times higher than that of TpaBtt (568 μM and 5.68 μmol) and TapbBtt (1254 μM and 12.54 μmol), respectively. The observed trend was consistent with the intrinsic electronics of three COFs based on theoretically calculated results. The photosynthetic rate of H2O2 under different catalyst dosages was evaluated in Fig. −1 was obtained, corresponding to 378 μM h−1 (3.78 μmol h−1 and 252 μmol g−1 h−1) for TpaBtt, 836 μM h−1 (8.36 μmol h−1 and 557 μmol g−1 h−1) for TapbBtt and 2111 μM h−1 (21.11 μmol h−1 and 1407 μmol g−1 h−1) for TaptBtt. Excessive COFs inhibiting the ability to absorb light could cause the decrease in H2O2 concentration. The optimal performance of TaptBtt is much higher than that of TpaBtt and TapbBtt, and surpasses that of previously reported non-metal COFs and other nonmetal-heteroatom-doped C3N4-based photocatalysts , correspond to 645 nm, 578 nm, and 590 nm, respectively  of TpaBtt, TapbBtt, and TaptBtt, from the plots of (ahv)2 vs. photon energy (hv), were counted as 1.95, 2.32, and 2.29 eV, severally. The valence band positions of TpaBtt, TapbBtt, and TaptBtt, calculated from the valence-XPS spectra, were 1.13, 1.54, and 1.83 eV, respectively  revealed that TaptBtt showed a lower charge transference resistance, which resulted in the faster transfer of electrons in the interface  spectra exhibited obvious PL quenching of TaptBtt, as shown in Fig. 30. Inspired by this result, we think that the charge reversal caused by protonation is directly related to the energy difference of the line-region combination between linkages and linkers , assigned to the C=NH+ bond62. Subsequently, the photocatalytic H2O2 evolution performance of all COFs was examined , which was nearly three times higher than that of pristine TpaBtt, followed by that of TapbBtt-AC (7.2 μmol h−1), and nearly 1.8 times higher than that of pristine TapbBtt. However, H2O2 production in TaptBtt was essentially unchanged, and even slightly decreased. We further probed the difference in the separation and recombination of carriers for these COFs by i-T and EIS. Obviously, TpaBtt-AC and TapbBtt-AC showed a higher current density than that of their pristine COFs  was added in the presence of Ar. However, the H2O2 concentration was almost undetectable for TpaBtt and TapbBtt under the same conditions. This result implies that a four-electron water oxidation process may have occurred in TpaBtt and TapbBtt, while TaptBtt could directly utilizes holes and electrons synchronously during the production of H2O2.To verify that photoinduced holes and electrons participate in photocatalysis, the yields of Hair Fig. , only th− WOR and 2e− WOR routes of COFs. As shown in Fig. 2O2 selectivity is higher under the same conditions. The results also reveal the advantage of the line-region combination between imine linkage and Tapt/Btt linker in TaptBtt for 2e− ORR pathway. During the RRDE test, the incremental disk currents . TaptBtt might have the ability to directly exploit holes  measurements were used to examine the 4eles Fig. . When th218O was used in photocatalytic tests to further identify the two/four-electron water oxidization. As shown in Supplementary Fig. 18O2 production in the first stage , while all did in the second stage-decomposition of photogenerated H2O2 by MnO2  is significantly different after H2O2 decomposition in the second step. The ratio of 18O2 and 16O2 is 1:4.8   significantly inhibited the yield of H2O2 for TpaBtt, TapbBtt, and TaptBtt. When tert-butanol (·OH scavenger) was added to the system, H2O2 production tended to increase. The carbon-centered radical (R·) produced by tert-butanol reacts with dissolved oxygen to form RO2·, which spontaneously binds to form tetroxide intermediates, and finally splits to form H2O265.There are two pathways by which WOR and ORR generate H to Eqs. –3 and Eq to Eqs. –6. Wheth to Eqs. , 2 and E to Eqs. , 5 occur M) Fig. , suggest−1 appears under photocatalytic reaction, verifying the occurrence of two-step single-electron route67. The O-O bond serves as the key intermediate for H2O2 production in 2e− ORR. The intensity of the O-O peak follows the order of TaptBtt > TapbBtt > TpaBtt, matching well with the EPR and NBT results. The intensity of the peaks at 1012 cm−1 and 1086 cm−1, corresponding to the bending modes of C-H and C-C of the center ring on the three COFs, gradually increases. Besides, the C-S-C (951 cm−1), belonging to the thiophene unit68, is also gradually enhanced. The vibration of the C-C and C-S-C peaks indicates that occurrence of photoinduced electron transfer occurs between the thiophene of the Btt motif and the benzene ring fragments of Tapt motif. More importantly, vibrations were observed for C=N (1623−1627 cm−1) and C=NH+ (1567 cm−1) for three COFs after photoexcitation, indicating that protonation occurs on imines  spectroscopy measurements were taken to monitor the interactions between the active sites and the intermediates. As shown in Fig. O2− Fig. . OOH*, a2O2 formation on the three COFs. The key to selectivity of 2e− ORR to H2O2 relied on the generation of OOH* and consequent hydrogenation71. The adsorption of O2 and H+ is a precondition for the formation of OOH* on the surface of photocatalysts. Therefore, the photocatalytic reduction of O2 to H2O2 can be divided into four steps (Eqs. (S1–S4)). The optimized structures of three COFs with adsorbed intermediates are carefully given in Fig. 2 adsorption falls into the electron-acceptor motif of COFs so that it facilitates access to electrons and protons for selectively forming the OOH* intermediate. This is consistent with the stretching of O-O characteristic peaks in the in-situ DRIFT spectra. Hirshfeld analysis reveals that the average charge of these carbon (C) atoms close to imine linkage is ~−0.122 eV for TpaBtt (the thiophene ring in Btt) and increases to −0.119 eV for TaptBtt (the benzene ring of Tapt nears imine bond)  of O2 on TaptBtt decreases in relative to that of TpaBtt (−0.143 eV) and TapbBtt (−0.109 eV)  calculations were conducted to investigate the elementary step of HG) for each step involved in 2e− ORR was calculated, as shown in Fig. 2* intermediate with a ΔG1 value of −2.33 eV, terrifically restricting the desorption of the OOH* intermediate. The rate-limiting step (OOH* → H2O2) has an extremely high energy barrier with a value of 1.14 eV. The OOH* formed on the active sites cannot be released in a timely manner from the surface of the catalyst, which affects the continuous utilization of the site. Although TapbBtt weakened the adsorption of O2* intermediate with a ΔG1 value of 0.28 eV, it exhibited a relatively high free energy (0.67 eV) during protonation to form the O2*/H* intermediate. Optimally, TaptBtt simultaneously modulates the binding strength of O2* and OOH* intermediates, thus promoting the 2e− ORR with a lower energy barrier of 0.57 eV. The real active sites of forming OOH* are located on the C atom of electron-acceptor fragments nearest the imine linkage  COFs differentially adsorb dissolved oxygen under dark reaction and then undergo photoinduced in-plane electron transfer; ii) the formed O2* on electron-acceptor fragment utilizes the transferred electrons and the protons from the adjacent imine bond to generate the OOH* intermediate; iii) protons in water are hydrogenated with OOH* to selectively produce H2O2. For the 2e− WOR process of TaptBtt, two H2O molecules are adsorbed onto the Tapt unit to form an intermolecular hydrogen bond75, which is subsequently attacked by photoinduced holes to directly produce H2O2. The remaining two protons are finally utilized by ORR process, forming a complete cycle of H2O2 synthesis in Fig. Based on the above analysis, the overall process of H2O2 production with a yield rate of 2111 μM h−1 (21.11 μmol h−1 and 1407 μmol g−1 h−1) and a solar-to-chemical conversion efficiency of 0.296 %. The codirectional charge transfer and larger energy difference of the line-region combination between linkages and linkers in terms of dual-donor-acceptor structures in the periodic framework promote a satisfying energy band, favorable intermediate interaction, optimal reactive pathways and finally high-yield synthesis of H2O2. The collected H2O2 solution can be utilized for pollutant removal. DFT calculations revealed that Btt binding to different functional motifs  could regulate electron distribution on C atoms near imine bonds, which can facilitate the in-plane charge transfer and mediate the binding strength of O2* and OOH* intermediates during 2e− two-step redox reaction. In addition, partial water oxidation promoted the protonation of TaptBtt, reducing the barrier for the formation of intermediates O2*/H* and OOH*. This study provides insight into the push-pull effects between intramolecular motifs and linkage chemistry in polymers based on COF-based platforms towards highly efficient energy conversion and artificial photosynthesis.In summary, we rationally engineered benzotrithiophene-based covalent organic frameworks by regulating the electron distribution and transfer directionality for hydrogen peroxide photosynthesis. TaptBtt displayed attractive activity for Ho-dichlorobenzene  and n-butanol (3 mL) mixed solution (v/v = 1:1). After the above mixture was sonicated for 10 min, acetic acid aqueous solution  was added, and then the system sonicated again for 2 min. The tube was degassed by three freeze-pump-thaw cycles and then was sealed off and heated at 120 °C for 3 days. The powder collected was washed with N,N-dimethylformamide, methanol and ethanol several times, and dried at 120 °C under vacuum for 2 h to obtain TpaBtt sample in 87% isolated yield.4,4,4-Triaminotriphenylamine  and benzotrithiophene-2,5,8-tricarbaldehyde  were placed into a 10 mL Pyrex tube, and dissolved into o-DCB, 3 mL) and n-butanol (3 mL) mixed solution (v/v = 1:1). After the above mixture was sonicated for 10 min, acetic acid aqueous solution  was added, and then the system was sonicated again for 2 min. The tube was degassed by three freeze-pump-thaw cycles and then sealed off and heated at 120 °C for 3 days. The powder collected was washed with tetrahydrofuran and acetone several times, and dried at 80 °C under vacuum for 24 h to obtain TapbBtt sample in 82% isolated yield.1,3,5-Tris(4-aminophenyl)benzene  and benzotrithiophene-2,5,8-tricarbaldehyde  were placed into a 10 mL Pyrex tube, and dissolved into 1,2-dichlorobenzene (v/v = 1:1). After the above mixture was sonicated for 10 min, acetic acid aqueous solution  was added, and then the system was sonicated again for 2 min. The tube was degassed by three freeze-pump-thaw cycles and was sealed off and heated at 120 °C for 3 days. The powder collected was washed with tetrahydrofuran and acetone several times, and dried at 80 °C under vacuum for 24 h to obtain TaptBtt sample in 85% isolated yield.2,4,6-Tris(4-aminophenyl)−1,3,5-triazine  and benzotrithiophene-2,5,8-tricarbaldehyde  were placed into a 10 mL Pyrex tube, and dissolved into mesitylene (3 mL) and 1,4-dioxane (3 mL) mixed solution (Supplementary InformationPeer Review FileSource Data