C) of soft layers, such as rockfill and silt, is a key factor, the internal friction angle (φ) is an important influencing factor, and the elastic modulus (E) is a general influencing factor. Theoretical analysis was employed to establish the relationship curve between each parameter and the maximum pile deformation, as well as the sensitivity factors, further verifying the impact of these weak soil parameters. The research findings presented in this paper can provide valuable guidance for geotechnical engineers when selecting geological parameters for similar deep excavation projects.In order to investigate the sensitivity of weak soil parameters on the deformation of balanced double-row piles, a case study was conducted in a deep foundation pit project in Shenzhen City. A variety of analysis methods, including numerical simulation, field measurements, orthogonal experiments, and theoretical analysis, were employed to analyze the impact of three weak soil parameters on the deformation of balanced double-row piles. The research results showed that the deformation of the front and back rows of piles exhibited overturning deformation, gradually decreasing with depth and reaching the maximum at the pile top due to the constraint effect of the balance platform. The numerical simulation results of horizontal displacements for the front and rear piles were in good agreement with the field measurements, confirming the accuracy and reasonableness of the numerical analysis model and parameter selection. Through a series of orthogonal numerical simulation experiments, it was determined that the cohesive strength ( Therefore, it is necessary to conduct research on the impact of weak soil parameters on the deformation of supporting structures in reclaimed areas.With the rapid development of coastal urbanization, the utilization of land reclamation and underground space has effectively addressed various urban land constraints. However, it has also presented numerous challenges in underground engineering, mainly characterized by complex geological conditions and high demands for controlling surrounding environmental deformations7 based on a case study in a specific soft soil area, employed parameter sensitivity analysis to identify critical geological parameters. They proposed a dynamic construction inverse analysis method using parameter sensitivity analysis and BP (Backpropagation) neural networks. Qi et al.8 took the Shenzhen International Convention and Exhibition Center Project (Phase I) super-large deep foundation pit engineering design as the research object. In order to solve the challenges of tight construction schedule and high deformation control requirements in the reclamation area, a combined method of counterweight double-row piles and large-span supports was employed. A calculation model for the support stiffness of this structure was established, and numerical simulations were conducted to investigate the influence of large-span support spacing on the deformation and internal forces of the supporting structure. Lan et al.9 investigated the effects of dimensional parameters such as pile diameter and length, as well as engineering parameters such as pile spacing and row spacing, on the stress and deformation of double-row pile support structures. They also studied the influence of soil arching effect on the stress and deformation of these structures based on a calculation model considering pile-soil interaction. Li et al.10 effectively combined the treatment of soft soil foundation with the excavation and support of deep foundation pits, proposing a new method for excavating deep foundation pits in soft soil—the Vacuum Curtain Waterproofing and Atmospheric Pressure Support Deep Foundation Pit Excavation method. This method has provided new design concepts and directions for the development of deep foundation pit engineering technology. Based on the enclosed area of the foundation pit project for the Guangxi Nanning Rail Transit Line 4, Ou et al.11 used the finite element software ABAQUS to establish a numerical model of the deep foundation pit double-row pile support structure. They combined it with on-site measurement data to analyze the displacement and deformation characteristics of the double-row pile support structure. By changing the spacing between the double-row piles, the pile diameter, the pile stiffness, and the beam height, they analyzed the impact of design parameter changes on the support effect. Yan et al.12 conducted a three-dimensional elastoplastic numerical simulation of the excavation process for the maximum excavation depth of the double-row pile support in the underground water treatment plant foundation pit project in Wuhan City. By comparing the field measurement results, design software calculation results, and numerical calculation results, they validated the rationality of the numerical model. They analyzed the effects of pile-soil reinforcement depth, elastic modulus, cohesion, and internal friction angle on the bearing deformation characteristics of the double-row pile support system. Dong et al.13 derived and studied the theoretical calculations of the counterweight double-row pile support structure. They applied the derived calculation method to Midas GTS NX simulation calculations. Taking a deep foundation pit project in Shenzhen City as an example, they verified and analyzed the simulation results and field monitoring results. Based on this, they further explored the influence of deformation parameters such as row spacing, diameter of back row piles, and top load on the pile body. Meng et al.14, based on a certain deep foundation pit project in a soft soil area, established a three-dimensional foundation pit numerical model. They analyzed the influence of the dimensions, specifically the width and depth of the foundation pit model, on the deformation during excavation. Their findings suggest that when the width of the foundation pit model is greater than 7 times the excavation depth and the depth exceeds 6 times the excavation depth, the influence of the size effect on the model can be essentially disregarded. Ren et al.15 conducted on-site monitoring of the foundation pit's groundwater level, pore water pressure, and dewatering well flow rates to analyze the temporal and spatial variations in dewatering. They further investigated the deformation and seepage characteristics induced by excavation-induced dewatering by analyzing the measured results of soil settlement and horizontal deformation of the retaining structure. Zhang et al.16 based on the Euler–Bernoulli double-layer subgrade beam theory, considered the interaction between piles and pile-soil, and obtained the flexural differential equations of the double-row pile support structure in layered subgrade. They solved the equations using the power series method and obtained the calculation formulas for the horizontal displacement, rotation angle, shear force, and bending moment of the pile body at any depth based on the continuity conditions of internal forces and displacements at the interface and the boundary conditions at the pile top and pile bottom. Finally, through an engineering case analysis, they compared and analyzed the calculation results of their method with the results of the case study, validating the correctness of their method. Yi et al.17 studied the influence of retained soil in the pit on the double-row pile support structure. They used the finite element numerical analysis method to parametrically analyze the dimensions of the retained soil, reinforcement effects, and elastic modulus, and conducted an in-depth study on the displacement, bending moment, and passive zone soil pressure changes of the double-row piles. Fan et al.18 employed finite element analysis considering the small strain stiffness characteristics of soil in multiple case statistics to investigate the influence of internal support pit excavation on the deformation characteristics of the underlying subway tunnels. They defined influence area parameters based on deformation contour analysis, combined with deformation control standards of 20 mm, 10 mm, and 5 mm for the subway tunnels, and established the corresponding impact zone ranges. They also simplified the description of the impact zone range based on its characteristics. Niu et al.19 conducted a study to investigate the influence characteristics of reverse faults on the deformation of pile foundations in deep excavation projects. They used various research methods such as numerical simulation, field monitoring, and orthogonal experiments, taking a deep excavation project in Shenzhen as an example. They analyzed the effects of reverse faults on the deformation of retaining piles, finding a positive correlation between pile deformation and fault slip distance as well as fault dip angle. Furthermore, they analyzed the sensitivity of fault slip distance, fault dip angle, and fault position to the maximum deformation of the piles. They determined that fault dip angle had the highest sensitivity, followed by fault slip distance, while fault position had the lowest sensitivity.In recent years, as the number of deep excavation projects in weak soil areas has increased, significant progress has been made in this field of study. Xiao et al.Through an analysis of the literature mentioned above, it becomes evident that there is relatively limited research regarding the influence of weak soil parameters on the deformation of supporting structures in reclaimed areas. Therefore, in this study, based on a deep pit engineering project in Shenzhen, orthogonal numerical simulation experiments were conducted using MIDAS GTS NX finite element software to analyze the sensitivity of three parameters of weak soil to the deformation of cantilevered double-row pile piles. The research findings have certain theoretical value and practical significance for engineering applications.ϕ1.2 m@1.8 m interlocking piles arranged in an alternating pattern, while the back row piles are ϕ1.2 m@3.6 m single piles. The plan view schematic diagram of double-row piles is shown in Fig. L-shaped counterweight platform consists of a horizontal plate approximately 4.8 m wide and 0.5 m thick, along with retaining plates that are 2.3 m high and 0.3 m thick on the upper part of the horizontal plate. The L-shaped counterweight platform is used for backfilling soil and unloading pressure. The section dimensions and physical and mechanical performance parameters of the supporting structure are shown in Table This project is located in the Shenzhen Bay reclamation area of Nanshan District, Shenzhen City. The subsurface strata at the site consist of fill stone, silt, silty clay, gravelly clay, and completely weathered granite, arranged from top to bottom. The pit design employs a cantilevered double-row pile support structure. The front row piles are 21, monitoring points for pile deformation in the cantilevered double-row pile configuration were set up at the site. Since this study focuses on the eastern profile 1–1 with the worst geological conditions, the layout diagram for on-site monitoring points only displays the monitoring points for this specific profile. The layout of on-site monitoring points is shown in Fig. This paper selected the profile with the worst geological conditions for analysis, which is the eastern profile 1–1 of the foundation pit, as shown in Fig. 4 MPa, a Poisson's ratio of 0.20, and a density of 25kN/m3. The boundary conditions of the calculation model were set as: vertical displacement constraints at the bottom and horizontal constraints around the model, limiting horizontal and vertical displacement. The entire model was divided into a regular hexahedral mesh with a total of 26,366 mesh units and 27,616 node elements. The three-dimensional finite element analysis model and support structure model are shown in Figs. A three-dimensional numerical simulation analysis model was established using the finite element software MIDAS GTS NX to analyze the excavation stages of the foundation pit. The dimensions of the soil model were 72 m horizontally along the 1–1 profile, 36 m vertically perpendicular to the 1–1 direction, and 54 m vertically, resulting in a model size of 72 m × 36 m × 54 m.The support piles were represented using one-dimensional implanted beam elements, while the crown beam and connecting beam were modeled using one-dimensional elastic beam elements. The counterweight plate and retaining plate were simulated using plane plate elements. The soil was modeled using a modified Mohr–Coulomb constitutive model, and the parameter values for each soil layer are shown in Table After excavation of the foundation pit to the bottom, the deep horizontal displacement variation curves of the pile bodies at X3 and X4 of the front and rear rows of piles were extracted, as shown in Figs. The deep horizontal displacement of the front row pile at the on-site measurement point X3, and the deep horizontal displacement of the back row pile at the on-site measurement point X4 are shown in Fig. C), internal friction angle (φ), and elastic modulus (E) on numerical simulations involving two weak layers: filling stones and silt. A three-factor, five-level orthogonal numerical simulation experiment is conducted, comprising a total of 25 experiment groups. Aside from the previously mentioned parameters associated with weak soil conditions, the models and calculation parameters remain consistent for each test group. Specific parameter values for each factor are detailed in Tables In this paper, the authors employ an orthogonal experimental design to examine the impacts of cohesion , internal friction angle (φ), elastic modulus (E), and others. Specifically, it refers to the difference between the maximum and minimum values of the sum of the maximum horizontal displacements of the front and rear piles resulting from different orders, including A1 to A5, B1 to B5, and C1 to C5, as shown in Table Based on the data provided above, the orthogonal experimental factors and levels are shown in Table C) factor of the soil exhibits the largest relative range value at 10.88%, making it the key factor. The internal friction angle (φ) factor of the soil has an important influence with a relative range value of 9.68%, while the elastic modulus (E) factor of the soil plays a general influencing role with a relative range value of 7.29%. Similarly, the analysis of influencing factors for the back row piles yields consistent results with those of the front row piles.This paper employs the relative range of maximum horizontal pile body displacement from orthogonal experimental results to investigate the sensitivity of balanced double-row pile deformation to weak stratum parameters. The results demonstrate that the larger the relative range, the greater the impact of the corresponding factors on the target parameters, and vice versa. Analyzing the calculation results and the relative range value curve of influencing factors for the front and back row piles in Fig. Q, which is determined by m main factor parameters β1, β2, β3, … , βm. The relationship between the variable Q and the parameters can be expressed as Q = f . Assuming that the parameters under certain conditions are set as the reference parameters, the system reference variable Q* can be obtained as Q* = f . When multiple factor parameters are adjusted, the trend and degree of deviation of the system variable Q from the reference variable Q* indicate the sensitivity of parameter influence24.Assuming a system, the system variable is Q and the relative error of parameter βk are defined as the sensitivity function Sk(βk). When △βk/△Q is small, Sk(βk) can be approximately expressed as:In order to compare the sensitivity of multiple parameters, sensitivity functions and sensitivity factors in dimensionless form are defined. The relative error of the system variable C), internal friction angle (φ), and elastic modulus (E) for the silty clay strata. The initial reference values for parameters C, φ, and E are based on the geotechnical test report. The specific numerical values can be found in Tables C.Sensitivity analysis of cohesive The baseline model and parameters established in this section are consistent with those in Sect. 3. The experimental design involved changing one parameter while keeping the other two constant, based on the values from Tables μ) and the cohesion is:(2) φ.Sensitivity analysis of internal friction angle Keeping the internal friction angle and elastic modulus constant, the maximum deformation of the pile body under different cohesion values is shown in Table (3) E.Sensitivity Analysis of Elastic Modulus Keeping the cohesion and elastic modulus constant, the maximum deformation of the pile body under different internal friction angles is shown in Table Keeping the cohesion and internal friction angle constant, the maximum deformation of the pile body under different elastic modulus values is shown in Table C) value has a sensitivity factor of 0.393, designating it as the key factor. The internal friction angle (φ) value has a sensitivity factor of 0.369, making it an important factor. Additionally, the elastic modulus (E) value has a sensitivity factor of 0.312, categorizing it as a general factor. All three parameters exert certain effects on the deformation of the double-row pile body. Therefore, when designing the support structure values, it is essential to comprehensively consider the influence of each parameter.In summary, Table Both the top and bottom of the front and back row piles exhibit certain horizontal displacements, with the overall deformation being characterized as cantilever-type deformation. Due to the restraining effect of the counterweight platform, the deep-seated horizontal displacement of the front and back row piles follows a similar pattern, gradually decreasing with depth. The maximum deep-seated horizontal displacement of both the front and back row piles occurs at the pile top, with the horizontal displacement values at the pile bottom and pile top being roughly equal.A three-dimensional numerical simulation analysis model for pit excavation was established using the finite element analysis software MIDAS GTS NX. A comparison between numerical simulation results and on-site measurements indicates that the numerical analysis results are in good agreement with the actual field measurements, validating the rationality and accuracy of the model and parameter selection in this study.C) in weak soil layers such as fill stone and silt is a critical factor, internal friction angle (φ) is an important influencing factor, and elastic modulus (E) is a generally significant factor.Sensitivity analysis was conducted using the orthogonal experimental method, and through a three-factor, five-level orthogonal numerical simulation experiment, a total of 25 groups of maximum pile deformation values for the front row piles were obtained. By calculating and utilizing the relative range, the sensitivity of various weak soil parameters on the horizontal deformation of the front row piles during pit excavation was studied. The results show that cohesion (Sensitivity analysis was performed using the theoretical analysis method. By controlling variables, relationship curves between various weak soil parameters and maximum pile deformation were obtained. These curves were then fitted, and sensitivity factors were calculated, further validating the impact of these weak soil parameters.Taking a deep foundation pit engineering project in Shenzhen Bay reclamation area, Nanshan District, Shenzhen City as the research subject, a comprehensive analysis was conducted using methods such as numerical simulation, field measurements, orthogonal experiments, and theoretical analysis to perform sensitivity analysis on three weak soil parameters affecting the deformation of the cantilevered double-row piles. The main conclusions are as follows:L-shaped counterweight platforms, as well as the spatiotemporal effects of soil parameters.This paper only considers the influence of soft soil parameters on the deformation of cantilevered double-row piles, while there are many other factors affecting the deformation of deep foundation pit engineering in weak soil conditions that require further investigation. These factors include pile spacing, the depth and width of


For HHUS, both unnecessary biopsy rate and IC yields were significantly reduced when changing biopsy thresholds by adding MAM for US 4a in the total population  compared with the current scenario . Notably, scenario #1 reduced false-positive biopsies without affecting IC yields when compared to the current scenario for ABUS . The higher unnecessary biopsy rate of category 4a by ABUS was similar to HHUS. However, the second-look MAM adjunct to ABUS has the potential to safely reduce false-positive biopsies compared with HHUS.The appropriate management strategies for BI-RADS category 4a lesions among handheld ultrasound (HHUS) remain a matter of debate. We aimed to explore the role of automated breast ultrasound (ABUS) or the second-look mammography (MAM) adjunct to ultrasound (US) of 4a masses to reduce unnecessary biopsies. Women aged 30 to 69 underwent HHUS and ABUS from 2016 to 2017 at five high-level hospitals in China, with those aged 40 or older also accepting MAM. Logistic regression analysis assessed image variables correlated with false-positive lesions in US category 4a. Unnecessary biopsies, invasive cancer (IC) yields, and diagnostic performance among different biopsy thresholds were compared. A total of 1946 women (44.9 ± 9.8 years) were eligible for analysis. The false-positive rate of category 4a in ABUS was almost 65.81% (77/117), which was similar to HHUS . Orientation, architectural distortion, and duct change were independent factors associated with the false-positive lesions in 4a of HHUS, whereas postmenopausal, calcification, and architectural distortion were significant features of ABUS (all  Mammography (MAM) is widely used as the standard modality for detecting and screening early breast cancer. However, the diagnostic accuracy of MAM is limited in women with dense breasts ,2,3. AnoConventional handheld ultrasound (HHUS) offers a low-cost and portable way of breast cancer detection without the limitations of breast density , therebyTo provide standardized ultrasound (US) findings reporting systems and aid quality assurance and risk assessment, the Breast Imaging Reporting and Data System (BI-RADS) is generalized worldwide . The latThe benign biopsy rate on breast US of 4a patients is a considerable percentage (more than 50%) ,10. UnneThe diagnostic performance between ABUS and HHUS has been proven comparable based on the fifth BI-RADS edition . HoweverTherefore, we aimed to exploratorily assess the diagnostic performance of ABUS or the second-look MAM adjunct to US to help reduce false-positive diagnoses of 4a patients without impacting the breast cancer detection rate.The research design has been published in detail elsewhere . BrieflyAll participants were invited to attend both HHUS and ABUS, while those aged 40 years and above also underwent MAM. Patients with the most severe category on three modalities, including BI-RADS 4 and 5, were considered positive findings and required a biopsy, whereas those with BI-RADS 1, 2, or 3 were categorized as negative findings. The study was registered in the Chinese Clinical Trial Registry (ChiCTR1800017908) and approved by the Institutional Review Board of Cancer Institute, Chinese Academy of Medical Sciences , and the Institutional Review Board of all participating hospitals. According to the study aims, we included the participants with HHUS or ABUS categories 3 and 4a as the analysis set. The study design was shown in The participants underwent ABUS using Invenia ABUS  performed by technicians who received training for 3 days and interpreted by radiologists with 3–6 months of experience with ABUS. Three planes  are collected on each breast. The image in three views could be transmitted to the workstation and reconstructed in the breast and displayed in 3D volumes. The HHUS images were acquired by one of the following devices, including GE LOGIQ9 , iU22 Ultrasound System , S2000 , and the Aixplorer system , which was performed by qualified radiologists with 5–25 years of experience in five hospitals. All MAM examinations were performed by one of three techniques including GE Sengraphe DS , Hologic Selenia , and Fujifilm FDR MS-2500  and interpreted by doctors with 5–25 years of experience. All screening physicians involved in the study were trained in the protocol and related technical specifications and diagnostics before starting the study.During the study, different experienced radiologists reviewed and interpreted images from three modalities and were blinded to each other. However, they were provided with information on participants’ clinical examinations. We analyzed and compared the detection rate of normal/benign and malignant lesions classified as US categories 3, 4a, 4b, and 4c using the Chi-squared test for trend. In clinical practice, observers always have difficulty in better characterizing category 3 and 4a lesions even for highly qualified experts. Therefore, to evaluate the clinical and image features influencing the false-positive lesions in category 4a, we selected those who were categorized as 3 and 4a and underwent biopsy and evaluated them as benign breast lesions as an analysis set. With category 3 as the reference group, multivariable logistic regression analysis was used to estimate odds ratios (ORs) and confidence intervals (CIs). As for HHUS, the following characteristics of the lump were included in the analysis: maximum diameters, shape, orientation, margin, posterior feature, calcification, distorted structure, duct change, and vascularity. As for ABUS, we also analyzed retraction phenomenon in the coronal view. Furthermore, age, menopausal status, breast density, and palpability of the mass were also included in logistic regression analysis to control for potential confounding variables. Variables that were statistically significant in the univariate analysis would be prioritized for inclusion in the multivariate analysis, and for that were non-significant in the univariate but clinically valuable also be considered for analysis.p-value <0.05 was considered statistical significance.Unnecessary biopsy rate, invasive cancer (IC) detection rate, malignant rate of biopsy, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and area under curve (AUC) were calculated to evaluate the diagnostic performance among different biopsy thresholds, which were compared using the McNemar’s tests or the Chi-squared test. The statistical analysis was performed with SAS, version 9.4 . A p for trend <0.001). ABUS showed the same trend as HHUS among 4a, 4b, and 4c . Meanwhile, 72.84% of unnecessary biopsies occurred in 81 participants who have assessed the BI-RADS 4a category with both ABUS and HHUS , architectural distortion , and duct change  were independent factors linked with the false-positive lesions in the BI-RADS-US 4A in HHUS, while postmenopausal , calcification , and architectural distortion  were the significant features of ABUS.Among 371 benign lesions assessed as categories 3 and 4a on HHUS, 127 were assessed as false-positive cases in 4a. Meanwhile, the false-positive cases were 77 in ABUS 4a among 357 benign lesions in 3 and 4a. We evaluated the effect of changing biopsy thresholds for women with US category 4a lesions who underwent MAM among women aged 40 and above . Three scenarios about different biopsy thresholds are shown in p = 0.238; p = 0.095). Meanwhile, only scenario #1, which adds MAM to ABUS, obtained a similar AUC compared with the current scenario (p = 0.277). Although sensitivity was significantly lower in both new scenario groups than in the current scenario group, specificity and PPV improved for HHUS and ABUS .The diagnostic performance of different scenarios was compared among women with BI-RADS-US category 3 and 4a lesions . The AUCp < 0.001), and the malignancy rate of biopsy increased to 45.54% (46/101) and 51.25% (41/80), respectively . However, both new scenarios had significantly lower IC detection rates than the current scenario . Similar patterns were recorded for ABUS, apart from scenario #1, which significantly reduced the false positive biopsies (p < 0.001) without decreasing IC yield (p = 0.125).p < 0.001). The IC yields of the two new biopsy thresholds were not inferior to the current scenario for HHUS in women with less dense breasts (p = 1.000) and those with palpable masses (p = 0.063). For ABUS, we did not observe a significant difference in diagnostic performance in all subgroups between the two new scenarios and the current scenario, except for the IC yields of scenario #2 of women with dense breasts (p = 0.016).We also compared the unnecessary biopsy rates, IC yields, and malignant rate of biopsy between the two new scenarios and the current scenario by age, breast density, and palpability of the mass . In all The potentially large number of unnecessary biopsies resulting from the current recommendation for BI-RADS-US category 4a creates an additional burden for women and impacts clinical resources. Our findings showed that the false-positive rate of category 4a in ABUS was almost 65.81%, which was similar to HHUS (67.55%). Meanwhile, clinical and sonographic factors influencing the 4a false-positive lesions were observed differently between HHUS and ABUS, which might be associated with radiologists’ experiences and equipment difference. To note, the potential added value of the second-look MAM adjunct to HHUS 4a was identified to reduce unnecessary biopsy procedures among women with dense breasts or palpability masses without influencing the invasive cancer detection. In addition, the new strategy combining ABUS category 4a and MAM 3, 4, and 5 as a new biopsy threshold would have the potential to safely reduce false-positive biopsies.Current criticisms of HHUS include concern about the false positive results and associated unnecessary biopsies . The ranThe potential of ABUS in the diagnostic setting of breast cancer has currently become the research focus because of its benefits . Some unIn routine clinical practice, the interpretation criterion of category 4a is a mass with benign ultrasound appearance but exhibiting any suspicious sign . Of all Previous works have explored the management strategies of US category 4a. Several studies mainly focused on the new US imaging technique, elastography, and have confirmed the potential of combined shear wave and strain elastography to US to reduce unnecessary biopsies in breast cancer diagnostics ,14,15. HUS (HHUS or ABUS) category 4a combined with MAM positive results (category 4 and above) as the biopsy threshold can significantly improve diagnostic performance and reduce false-positive biopsies when compared to the current scenario, but probably with the risk of missing invasive cancer. The most likely explanation is that more than 70% of participants were aged 40 and older and almost 50% of them were premenopausal who underwent MAM and were found to have dense breasts in our study, which may be associated with the lower sensitivity of MAM . Of noteNotably, we found that the added value of the second-look MAM adjunct to HHUS 4a could acquire higher cancer yields when breast masses were palpable, which might be related to the probability of malignancy being fairly high in palpable lesions. Palpability is likely to be viewed with more suspicion by these masses, providing information to aid diagnosis for radiologists . A previMost importantly, this study provides a more practical perspective that when the biopsy threshold identified BI-RADS 3 and above for MAM combined with BI-RADS 4a for ABUS has benefited over the current biopsy strategy for reducing false-positive biopsies without affecting the detection performance. Findings from a prospective study indicated that ABUS has a higher ability to detect architectural distortions, one of the risk factors of subsequent breast cancer in mammographic findings , on the The reasons for false-positive findings need to be identified through external quality assessment in clinical practice. Some cases without abnormal pathological findings might have image changes that mimic the appearance of precancerous lesions, resulting in misclassification as positive results. This group then needs to be given priority attention, because the image feature abnormalities are more likely to be risk markers of breast cancer . A previThe main strength of this study is that it is the first to evaluate the added value of the second-look MAM adjunct to US (HHUS or ABUS) category 4a. It possibly contributes to the understanding that MAM might be a useful additional tool for US in breast cancer diagnostics to better distinguish which patients require a histopathologic confirmation of suspicious lesions on imaging. This also provides potentially helpful strategies for improving diagnostic performance in areas where US is applied as the first-line breast diagnostic method.This study had several limitations. First, the experience of the radiologists among five research centers could affect the ability of image acquisition and interpretation. However, the variability among radiologists might be avoided to some extent by the standardized training before the research. Another limitation is that the absence of follow-up information may affect the accurate evaluation of long-term effectiveness results in patients with false-positive biopsies of US 4a among different biopsy thresholds. In addition, the study participants were recruited from hospital outpatients with a higher risk of breast cancer, which does not reflect the new biopsy thresholds applications for the general population. To address this issue, we now have conducted ongoing real-world research to explore the screening effectiveness for HHUS, ABUS, and MAM in average-risk populations.The higher unnecessary biopsy rate of category 4a by ABUS was very similar to HHUS, reflecting the image factors influencing the false positive 4a lesions should be the focus of integrated training. The second-look MAM adjunct to HHUS had the potential to reduce overdiagnosis for women with less dense breasts or palpable breast masses. Notably, BI-RADS 3 and above for MAM combined with BI-RADS 4a for ABUS benefited from the current biopsy strategy and safely reduced false-positive biopsies. Future work is still needed to explore the appropriate follow-up interval for false-positive patients in specific populations.


To improve the accuracy of deformation perception and shape reconstruction of flexible thin-walled structures, this paper proposes a method based on the combination of FOSS (fiber optic sensor system) and machine learning. In this method, the sample collection of strain measurement and deformation change at each measuring point of the flexible thin-walled structure was completed by ANSYS finite element analysis. The outliers were removed by the OCSVM (one-class support vector machine) model, and the unique mapping relationship between the strain value and the deformation variables  at each point was completed by a neural-network model. The test results show that the maximum error of the measuring point in the direction of the three coordinate axes: the x-axis is 2.01%, the y-axis is 29.49%, and the z-axis is 15.52%. The error of the coordinates in the y and z directions was large, and the deformation variables were small, the reconstructed shape had good consistency with the deformation state of the specimen under the existing test environment. This method provides a new idea with high accuracy for real-time monitoring and shape reconstruction of flexible thin-walled structures such as wings, helicopter blades, and solar panels. Due to technical or economic factors, some special flexible thin-walled structures, such as helicopter blades, aircraft wings, wind-turbine blades, solar panels, etc., are difficult to achieve real-time structural deformation perception. However, due to the continuous development of technology and the attention of scholars, the methods and means of monitoring the deformation of these flexible thin-walled structures have been diversified and matured in recent years. The method is based on the image As ,2,3,4,5,Machine learning has become one of the most efficient tools for complex problems through the promotion of big data ,27,28,29Micromachines [(1)For the problem of sensor arrangement in thin-walled structures, the idea of using double FBGs for each measuring point is proposed to improve the accuracy of deformation perception of thin-walled structures, and the influence of sensor placement on the accuracy of deformation prediction is quantitatively analyzed by using the Ansys finite-element model;(2)For the problem of outliers in the measurement process, the OCSVM (one-class support vector machine) model is used, which not only effectively eliminates the outliers and ensures the accuracy of shape reconstruction, but also provides a basis for judging abnormal conditions such as structural damage;(3)Aiming at the shape-reconstruction error of thin-walled structures, analyze the prediction error of the neural network model, and the calculation error of the interpolation method for the shape-reconstruction error of thin-walled structures in this paper, and provide a reliable basis for improving the accuracy of the shape-reconstruction method.To the existing problems of flexible thin-walled structure deformation perception, such as strong dependence on experience, mathematical models, and structure-specific curvature (shape) sensors, this paper proposes a method based on the combination of FOSS (fiber optic sensor system) and data drive, using the strain information measured by FOSS laid on the flexible thin-walled structure to complete the deformation perception and shape reconstruction. Based on the team’s previous research  × 200 mm (width) × 2 mm (height) is selected as the test piece for the flexible thin-walled structure in this system, as shown in The layout of the FBG sensor can follow the optimization algorithm, such as the particle-swarm algorithm (PSO), considering the small area of the test piece and the force distribution in Combining the characteristics of the loads  applied to the structure, inspired by the dual FBG shape sensor designed in the literature , one meaFor the structure of the test piece shown in The torque is 50 Nm, the coordinate of the action point is (1.0), the force is 300 N, the coordinate of the action point is (0.100), and the cloud diagram of the test piece deformation is shown in When the force is positive, it means the direction of force is vertical upward, otherwise the opposite, torque is negative clockwise, positive counterclockwise.For flexible thin-walled structures, differences in the value and the loading point of the load can lead to differences in the degree of structural deformation. The load is loaded on the test piece in six cases, as shown in The angular variations of the two gratings are shown in There are four rows of 16 measuring points on the test piece, and one measuring point in each row is randomly selected, compared with the strains measured by the FBG for different angles between the FBG and the x-axis, under the loading of the six other loads listed in As can be seen from Considering the combination, combination nine (the angle between the two FBGs and the x-axis is ±45°) is selected as the angle between the FBGs of the measuring points.In the simulation system shown in Using Ansys finite element method to collect sample data, when setting simulation boundary conditions, the system defaults that all data are within the range of elastic deformation, however, there are still samples of inelastic deformation, which is called a negative sample. Before the model training, these negative samples need to be eliminated, which may be inelastic deformation. The method of kicking out these negative samples is one class of SVM (support vector machine) in machine learning. OCSVM (one-class support vector machine) algorithm, strictly speaking, is not an outlier detection algorithm, but a novelty detection algorithm, that is, OCSVM starts from normal data and regards all the data different from normal data as novel data, and then sets the boundary according to the actual needs, and the data beyond the boundary can be judged as abnormal data. The characteristics of the deformation variables in the three axes of the measuring point are obvious, and the deformation variable in the z-axis is the largest, which is 104 times that of the x-axis and y-axis. To reduce the amount of calculation, instead of choosing the dimensionality reduction, the authors choose the simplest way—two feature quantities as one classification input feature. In the first row of measuring points with relatively large deformation variables, the authors randomly selected two deformation variables in the z-axis as input features since there was no sample with the same deformation variable in the z-axis in all 6000 samples. In the Matlab software version 2021, after installing the LIBSVM library, select reasonable performance parameters to build the OCSVM model by SVM toolbox in Matlab 1.0 of LU Zhen-bo.Select reasonable performance parameters to build the OCSVM model, ocsvm = OneClassSVM , the kernel function of the model is the linear kernel. The test output is shown in As can be seen from the final results, 605 samples are kicked out of 6000 samples, with a missing report rate of 0.39% and a false report rate of 5.75%. When creating the model, there were about 10% abnormal data in the default data of setting parameters nu = 0.1, and the performance of the established OCSVM model on clean data achieved the desired results.The neural network is one of the common mathematical models in machine learning. In theory, the neural network can fit any function. In the training of sample data, the weights and thresholds of the network are constantly adjusted by backpropagation, and the gradient descent method is used to reduce the network error function. Finally, the predicted value approaches the expected output value.4 orders of magnitude, in this system, a BP neural network is used to establish two sets of mapping relations, between the strain value and the deformation variables in the z-axis of the measuring point, and between the strain value and the deformation variables in the x-and y-axis of measuring point, respectively. The mapping relationship between the x- and the y-axis is used as an example to illustrate. Due to the deformation variables in the z-axis differing from those in the x- and y-axes by 10After repeated experiments and continuous adjustment, the structure of the neural network is shown in 4, the target error to be achieved by the training network is 10−6, and the activation function is chosen as the sigmoid function, as shown in Equation (1).The learning rate of the network is 0.01 (the x- and y-axis), The learning rate of the network is 0.0001 (the z-axis), the maximum number of training is 10The distribution of the sample data is random, for convenience of calculation, out of the 5395 samples left after eliminating outliers, 5000 of them are arbitrarily selected, of which 75% of the samples are used for training, 15% for validation, and 15% for testing.To evaluate the predictive performance of the model, the residual of the predicted value, determination coefficient (R2), MSE (the mean squared error), and so on, are considered comprehensively.MSE and R2 are important indicators for evaluating the prediction performance of neural network models. The closer the MSE is to zero, the better the model selection and fitting effect, and the more successful the data prediction. The closer R2 is to one, the better the model fit is. From −8 m, which is within the acceptable range; in The model residual is the difference between the predicted value and the actual value. From To test the accuracy of the predicted values of the neural network model, the simulation model, as shown in The predicted values of the neural network model and the theoretical values of the system simulation for any 4 of the 16 measuring points on the test piece are shown in The flexible thin-walled structure will deform by loading, and the degree of deformation is directly related to the size and type of the load. By observing the characteristics of the theoretical and predicted data in In comprehensive comparison, there are errors in the prediction of the model in each direction, the influence of the error in the x-axis and y-axis on deformation reconstruction can be ignored, and the error in the z-axis has an impact on the shape reconstruction, though within an acceptable range, so the structure deformation perception method based on neural network is feasible.The authors have verified the proposed method is feasible in theory, that of deformation sensing and shape reconstruction, and copy set up a simulation system of an experimental platform for test validation, as shown in The system shown in The test piece has two types of loading, as shown in In two test cases, the reconstructed shape of the test piece is shown in Measuring point one and measuring point five on the test piece are selected as reference points, to compare the difference between the predicted value and the measured value of the coordinate axis. The deformation in the y-axis direction of each measuring point on the test piece is small, and the change in the coordinate value of this direction can be ignored.The experimental environment and equipment conditions are relatively simple, all the measured values are measured by laser rangefinder (the measurement accuracy is 1 mm). As can be seen from The authors find that the reconstruction error is related to the selection of the coordinate origin and redefining the axis origin, as shown in (1) The reconstructed error of the coordinates of the measuring points in the direction of the z-axis does not change.The reconstruction error of the z-axis will never change if the XY coordinate axis is chosen on the thin-walled plane since the coordinate of the z-axis is perpendicular to the XY plane. The reconfiguration error of the measuring points in the z-axis direction is the measurement error of the deformation of the measuring points.The thin walled has a larger deformation in the z-axis direction, which has a relatively large impact on shape reconstruction;(2) The reconstruction error of the measuring points in the x y-axis direction is very much related to the selection of the coordinate origin, which is a relative error, and is not consistent with the measurement error of the form variable of the measuring points in the XY direction. Further, the deformation of the measurement points in the x- and y-axis direction is small and has limited impact on the shape reconstruction of the thin plate, so the relative error in the x- and y-axis direction can be used to verify whether the accuracy of the upgraded reconstruction method is improved.The reconstruction error of the coordinate values of each measuring point is significantly improved compared with the previous article, and the error contrast values, as shown in the following As shown in The proposed method for deformation perception and shape reconstruction of thin-walled structures is based on the data-driven mode, and similar literature is not common for shape-reconstruction applications of structures.−8 m. The influences on the subsequent shape reconstruction are all within the controllable range. In The error of the structure shape reconstruction proposed comes from two aspects, namely the prediction error of the model and the computational error by the interpolation method. The model prediction residuals shown in In summary, the advantages of the reconstruction method proposed in this paper are as follows: (one) a new idea is put forward for the real-time monitoring method of thin-walled structure deformation; that is, the layout method of the sensor. The orthogonal sensor network proposed in the literature  is used All the experiments are conducted based on the test piece—thin-walled stainless steel. All the data in the theoretical simulation and the experimental verification have verified the feasibility and reliability of the proposed method, though the reconstruction accuracy of the method still needs to be improved. In the follow-up, further improvement to the reconstruction algorithm is needed to improve the accuracy of the whole structure shape reconstruction.In this paper, Leveraging FBG in combination with data-driven models were used to establish a prediction model for structure measuring-points deformation, obtaining each point-deformation variable in the x, y, and z axes, getting the coordinate values of each measuring point on the structure after deformation, and then to complete the structure shape reconstruction by an interpolation method. The authors chose flexible thin-walled stainless steel as the test piece to establish the prediction model between the strain value and the deformation variables of the structure measuring points. The results showed that the reconstructed errors of the coordinates of the measuring points were within the acceptable range, and the reconstructed results were reliable. It provides a new method for real-time monitoring and shape reconstruction of flexible thin-walled structures such as wings, helicopter blades, wind-turbine blades, and solar panels with a high-accuracy reconstruction.


Connecting organic building blocks by covalent bonds to design porous crystalline networks has led to covalent organic frameworks (COFs), consequently transferring the flexibility of dynamic linkages from discrete architectures to extended structures. By virtue of the library of organic building blocks and the diversity of dynamic linkages and topologies, COFs have emerged as a novel field of organic materials that propose a platform for tailor-made complex structural design. Progress over the past two decades in the design, synthesis, and functional exploration of COFs in diverse applications successively established these frameworks in materials chemistry. The large-scale synthesis of COFs with uniform structures and properties is of profound importance for commercialization and industrial applications; however, this is in its infancy at present. An innovative designing and synthetic approaches have paved novel ways to address future hurdles. This review article highlights the fundamental of COFs, including designing principles, coupling reactions, topologies, structural diversity, synthetic strategies, characterization, growth mechanism, and activation aspects of COFs. Finally, the major challenges and future trends for large-scale COF fabrication are outlined. The covalent chemistry of organic molecules has matured throughout the 20th century and at the core of many important advances in science. The synthesis of chemicals, polymers, and pharmaceuticals via the modification of organic molecules through stable covalent bonds have fundamentally changed our way of life ,2. The fA crystalline framework with exclusive conformation and morphology generates a confined molecular space (pores) with the accessibility of atoms facilitating host–guest interactions. Furthermore, the porosity and structure stability are of profound importance to expand functional development via post-synthetic modification ,17,18. P−1). At lower temperatures, kinetically controlled disordered polymeric products are seen to dominate; thus, it is difficult to construct the ordered covalent network solids under ambient reaction conditions. Moreover, the desired thermodynamic reaction pathways demand a very-high activation energy. Coupling chemistry refers to a variety of organic reactions where two fragments are stitched together. COFs are built from organic building blocks via reversible condensation reactions. This micro-reversibility prevents the formation of disordered amorphous kinetic products and bolsters thermodynamically stable crystalline covalent networks. Furthermore, the reversibility in bond formation imparts self-healing and error-correction during crystallization. Throughout the reversible covalent bond formation and extension, if any bond formation happens in an undesired direction, the system can repair it through a back reaction and bond reformation, thereby supporting crystalline thermodynamic products with the lowest free energy. However, the condition for reversible covalent bond formation can be achieved only at a very-high temperature and pressure owing to the higher covalent bond energies  between ortho-difluoro benzene and catechol building blocks generate 1,4-dioxine-linked COF-316 and COF-318 with good thermal and chemical stability  two-component approach, a multiple-component reaction strategy offers multiformity and structurally diverse skeletons. The orthogonal reaction usually involves reversible formations of covalent bonds, which is an imperative prerequisite for the construction of crystalline frameworks. Zhao and co-workers reported orthogonal reaction strategy to construct binary NTU-COF-1 and ternary NTU-COF-2 by reversible formation of two types of covalent bonds . Two-dim12 [C2 + C2 + C2], [C3 + C2], and [C3 + C3] symmetric organic building blocks form hexagonal COFs with different pore sizes and stacking patterns [C4 + C4] and [C4 + C2] linkers afford a tetragonal framework of varying pore size (C2 + C2 + C2] or [C4 + C4] combinations result in COFs with micropores (<2 nm), whereas [C3 + C2], [C3 + C3], and [C4 + C2] yield mesoporous COFs (2–50 nm). The symmetricity, point group, and structural features of organic building blocks bolster interlayer (π–π) interactions and facilitates COF topology. Linking organic building blocks toward topology-directed framework growth occurs in concurrence with the geometry of building blocks. A high-order crystalline structure with unique conformation and morphology relies on the directional nature of covalent bonds. A covalent bond is a chemical bond made by sharing electrons between atoms. Organic molecule synthesis exhibits the full benefits of the directionality of covalent bonds, as exemplified by the synthesis of vitamin B12 ,122. Org12 ,124. Thepatterns ,126. Howore size . NotablyTd) or orthogonal geometry of building blocks to enable the extension of the backbone into a 3D network. For instance, the stitching of tetrahedral or orthogonal nodes with C1, C2, C3, C4, and tetragonal organic building blocks produce 3D COFs  oTd or orthogonal nodes and inadequate dynamic linkages. Nonetheless, the expansion of 3D COFs with conventional coupling reactions is still a major challenge.Numerous building blocks with unique geometrical and structural features enable the design of COFs with varying pore shapes and sizes. This permits the frameworks’ topological diversity via the bottom-up approach. Furthermore, building blocks of varying sizes and functionalities have been extensively explored to tune the electronic and steric environment of 2D frameworks . On the C3- and C2-symmetric building blocks in either a [C2 + C2] or [C3 + C3] manner. The chemically and thermally stable imine-linked, azine-linked, and olefin-linked COFs, such as Py-Azine, Py-2,3-DHPh, Py-3,3′-BPyPh, Py-2PE, sp2c-COF-2, sp2c-COF-3, and HAT-NTBA-COF, possess rhombic lattices with pore sizes larger than 1.5 nm and smaller than 3.0 nm -5,5′-dicarbaldehyde, and -6,6′-dicarbaldehyde, respectively, at 120 °C for 3 days  and [C4 + C4] topologies. For instance, Jiang and co-workers synthesized tetragonal metallophthalocyanine 2D MPc-COFs  via the boronate esterification reaction of 1,4-benzenediboronic acid and [OH]8PcM  under solvothermal conditions. CoPc-COF, CuPc-COF, NiPc-COF, and ZnPc-COF displayed disk-like morphologies and showed type-I reversible sorption isotherms, resulting in BET surface areas of 517 m2/g, 1360 m2/g, 624 m2/g, and 985 m2/g, respectively  and [C2 + C2] topologies were imitated in tetragonal COF-366-M , COF-367-M , and ILCOF-1, respectively [C4 + C4] enabled the synthesis of tetragonal microporous porphyrin-co-phthalocyanine COF with a high density of π-columns. The polycondensation reaction of phthalocyanine with eight hydroxyl groups, M2Pc[OH]8  and tetraphenyl porphyrin with four boronic acids, and M1TPBAP  generated M1TTP-M2Pc COFs under solvothermal conditions [C4 + C4] topology experienced a substantial decrease in the pore size as compared to the [C2 + C2] topology. In addition to a single-stage strategy, the double-stage strategy allowed the combination of boronate-ester- and imine-linked microporous CuPc-FPBA-ETTA COFs (1.8 nm) and mesoporous CuPc-FPBA-PyTTA (2.1 nm) frameworks and boronate-ester- and hydrazone-linked mesoporous CuPc-FPBA-DETHz COFs (3.7 nm) benzene, respectively, at 200 °C or 250 °C for 5–7 days. PI-COFs showed high thermal stability over 500 °C and BET surface areas of 1027 m2/g and 1297 m2/g for PI-COF-1 and PI-COF-2, respectively, and 2346 m2/g for PI-COF-3  and DBA[18], with C2-symmetric 1,4-benzenediboronic acid in dioxane/mesitylene (2:1) at 105 °C for 3 days led to the creation of DBA COF-1 and DBA COF-2, respectively. The crystalline DBA COF-1 and DBA COF-2 displayed permanent porosity with BET surface areas and pore sizes of 1952 m2/g and 3.2 nm and 984 m2/g and 3.6 nm, respectively. Notably, the BET surface area of DBA COF-1 was larger than that of the well-known COF-5 (1590 m2/g), NTU-COF-2 (1619 m2/g), COF-10 (1760 m2/g), and TT-COF (1810 m2/g) -3,5-dicabaldehyde and C2-symmetric 1,4-diaminobenzene or benzidine. The crystalline COF-BABD-DB and COF-BABD-BZ displayed BET surface areas and pore sizes of 569 m2/g and 0.98 nm, 1.72 nm and 750 m2/g, and 1.8 nm and 2.5 nm, respectively. More importantly, the dual-pore COF-BABD-DB and COF-BABD-BZ exhibited high selectivity and sensitivity for the detection of 2,4,6-trinitrophenol over other nitro compounds with Stern–Volmer quenching constant (Ksv) values of 5.7 × 105 M−1 and 4.5 × 105 M−1, respectively , [Td + C3], [Td + C4], [Td + C2], and [C2 + C3] building blocks. Yaghi and co-workers reported the first-ever boroxine- and boronic-ester-linked 3D COFs (Td) tetra(4-dihydroxyborylphenyl)methane or tetra(4-dihydroxyborylphenyl) silane and by the condensation of C3-symmetric 2,3,6,7,10,11-hexahydroxytriphenylene favored the formation of 3D COF-102, COF-103, COF-105, and COF-108 by targeting two framework types (ctn and bor) based on triangular and tetrahedral nodes  condensation reaction between triangular 4′,4′″,4′″″-Nitrilotris) with rectangular 4,4′,4″,4′″-tetraaniline and triangular tris(4-aminophenyl)amine with rectangular 4,4′″,4′″″-tetrakis), respectively. Both COFs displayed excellent thermal stability (350 °C) and chemical stability in DMF, MeOH, HCl (aq), and NaOH (aq). Notably, COFs serve as efficient photocatalysts for the cross-dehydrogenative coupling reaction and the asymmetric α-alkylation of aldehydes integrated with a MacMillan imidazolidinone as the chiral catalyst under visible light . Recentlnd 1 bar . In addipologies .p-phenylenediamine and dimethyl-p-phenylenediamine at elevated temperatures. Both COFs showed a uniform rod-like morphology with excellent thermal stability (400 °C). Furthermore, NUST-5 and NUST-6 serve as an effective photocatalyst for CO2 reduction with CO and CH4 production values of 54.7, 76.2 µmolg−1 and 17.2, 12.8 µmolg−1, respectively -3,3″,5,5″-tetracarbaldehyde with 1,4-phenylenediamine, benzidine, and 4,4′-diaminoterphenyl afforded NKCOF-21, NKCOF-22, and NKCOF-23, respectively. The NKCOF 21-23 displayed uniformly distributed block crystal and square pores with extremely high thermal stability. The BET surface areas and pore volumes were 1397 m2/g and 0.23 m3g−1, 1580 m2/g and 0.34 m3g−1, and 1900 m2/g and 1.05 m3g−1 for NKCOF-21, NKCOF-22, and NKCOF-23, respectively. Due to hydrogen-bond interactions (C—H∙∙∙∙N), NKCOFs displayed high ethane and ethylene adsorption at 273K, 298K, and 308K. For instance, NKCOF-21, -22, and -23 for ethene at 298K and 1 bar were 74.3 cm3/g, 40.7 cm3/g, and 51.0 cm3/g, respectively, while the adsorption capacity for ethane reached 97.9 cm3/g, 65.9 cm3/g, and 60.5 cm3/g, respectively. More importantly, bcu-network COFs displayed ethylene/ethane separation for 10 cycles with a complete retention of their structural robustness and crystallinity [2/g [The photocatalytic efficacy of 3D COFs for oxidative amine coupling and cycloaddition reactions were examined by a novel H or Ni) . The [8 allinity . One of allinity . This boity [2/g .The judicious choice of building blocks and the directional nature of dynamic linkages are essential to construct crystalline and porous frameworks. A de novo approach creates the formation of robust, reversible covalent linkage, thereby bolstering the thermodynamic control of condensation reactions. However, a kinetically controlled reaction enables the irreversible bond. This self-healing procedure encompasses the error checking and proof reading of structures to afford stable networks without defects. In addition to the fundamental role of reversibility, irreversible coupling reactions, such as dioxin, olefin, and nucleophilic aromatic substitution, have been reported in the design of porous networks and expansion of the library of COFs via different synthetic routes ,102,103.2 bath), sealed using a burner, and set aside for the required amount of time at a suitable temperature. Then, the precipitate is collected, washed, and dried to produce fluffy, solid-powdered COFs  of COF-5 followed by purification and activation yielded a surface area over 2000 mynthesis . The genynthesis ,205,206.p-toluenesulfonic acid frameworks, the crystallinity and porosity can be considerably improved. In the mechanochemical synthesis of β-ketoenamine TpPa-1, TpPa-2, TpPa-NO2, TpPa-F4, TpBD-(NO2)2, TpBD-(OMe)2, TpBpy, and other COFs, the building blocks were mechanically grinded using a mortar and pestle followed by heating at 170 °C for 1 min [To take COF chemistry to an interdisciplinary level, it is essential to explore simple synthetic methods, thus avoiding any complicated conditions, such as a reaction in a sealed Pyrex tube, inert atmosphere, and elevated temperatures. A mechanochemical synthesis prompted the construction of COFs via stable covalent bonds through a simple, economical, and environment friendly route . Despiteor 1 min ,208,209.or 1 min . 2/g) [The sonochemical method provides an alternative approach to the fabrication of frameworks with uncomplicated reaction conditions. The sonochemical method uses the process of cavitation, in which the reaction conditions, temperature, and pressure can be raised to initiate and accelerate the extent of polymerization. Yang and co-workers reported the use of the sonochemical method for COF-1 and COF-5 syntheses in a short reaction time (30 min–2 h) with high crystallinity and porosity (BET surface area = 2122 m2/g) . Althougp-phenylenediamine, 4,4′-diaminobuiphenyl, and 4,4″-diamino-p-phenylenediamine, respectively [Covalent triazine frameworks (CTFs) synthesized using the ionothermal route are crystalline in nature; however, most CTFs are amorphous materials with the absence of a long-range order. In a usual method, organic building blocks of zinc chloride are placed in an ampule, which is sealed and heated to an elevated temperature (350–450 °C) for a long time (2–3 days). The solid product is washed with water and stirred in diluted hydrochloric acid to remove the unreacted monomers and zinc chloride . Using tectively . 2/g) [−1 at an extremely high space–time yield of 703 Kgm−3day−1. In another work, Bein and co-workers reported the synthesis of boroxine-based COF films from diboronic acid and hexahydroxy triphenylene through the vapor-assisted conversion method. This method is based on the conversion of precursors in a cast solution layer into a continuous crystalline and porous film by exposure to a vapor of specific composition at moderate temperatures [Most widely used COF synthetic methods require elevated temperatures and prolonged reaction times. The innumerable building blocks are unstable at high temperatures, and synthetic approaches can be hazardous and dangerous. In comparison to the solvothermal route, the room-temperature method offers simplicity and ease of operation. It is of profound importance to explore novel synthetic conditions, catalysts, and linkages to enable the large-scale synthesis of COFs. Within this context, the solution–suspension approach is employed to prepare COFs at room temperature. In this approach, 1,4-phenylenediamine and 1,3,5-triformylbenzene were dissolved in dioxane at room temperature, followed by the addition of acetic acid as the catalyst. The mixture was kept for 3 days at ambient temperature conditions to construct COFs with good crystallinity and porosity (410–1537 m2/g) . This meeratures . The rol2)/water solvent. Compressed CO2 is cheap and nonflammable and can affect the properties of solvents to influence the structure and morphology of COFs. The first-ever report used the gram-scale method for preparing COF nanosheets with n-butyl lithium as the intercalation agent. Guan et al. reported imine-linked 3D interpenetrated dia structures, 3D-IL-COF-1, 3D-IL-COF-2, and 3D-COF-3, by suspending tetrakis(4-formylphenyl)methane with p-phenylenediamine, 4,4′-diaminobuiphenyl, and 4,4″-diamino-p-phenylenediamine, respectively, at ambient temperature in a 1-butyl-3-methylimidazolium bis((trifluoromethyl)sulfonyl)imide solvent [2/g for 3D-IL-COF-1, 653 m2/g for 3D-IL-COF-2, and 870 m2/g for 3D-IL-COF-3. This highlights the potential pathways of using ionic liquid as a green solvent for the large-scale synthesis of COFs. In addition to green solvent, Lewis acids, such as metal triflates, are effective in escalating the construction of imine-linked frameworks in ambient temperature conditions. Matsumoto et al. reported the room-temperature synthesis of imine-linked TAPB-PDA COF using Sc(OTf)3  in 20 min. In addition to Sc(OTf)3, other triflates, such as Eu(OTf)3, In(OTf)3, Yb(OTf)3, Y(OTf)3, and Zn(OTf)3, in different ratios were tested and found ineffective to catalyzed crystalline TAPB-PDA frameworks [3, a conventional catalyst, such as acetic-acid-assisted solvothermal synthesis, requires elevated temperatures (70 °C) and long time (72 h), exhibiting a moderate degree of crystallinity and porosity (692 m2/g). In another work, Verduzco and co-workers reported the fabrication of imine-linked framework using transition-metal nitrate as the catalyst at room temperature. Six different catalysts, Fe(NO3)3⸱9H2O, Ni(NO3)2⸱6H2O, Zn(NO3)2⸱6H2O, Mn(NO3)2⸱6H2O, Cu(NO3)2⸱6H2O, and Co(NO3)2⸱6H2O, in varying stoichiometric ratios  tried to synthesize TAPB-OMePDA COF through the condensation reaction of 1,3,5-tris(4-aminophenyl)benzene and 2,5-dimethoxyterephthalaldehyde at room temperature. Notably, 10 mol% of Fe(NO3)3⸱9H2O was found effective to synthesize the framework with the highest degree of crystallinity and porosity (1345 m2/g). In addition to Fe(NO3)3⸱9H2O, other nitrate salts were found either moderately or poorly effective to prepare crystalline framework. In addition to TAPB-OMePDA COF, TAPB-PDA, TAPB-BPDA, COF-V, TAPB-C8PDA, TAPT-PDA, and TAPT-OMePDA COFs successfully synthesized at ambient temperature with a high porosity after activation using supercritical CO2 [m-cresol or dimethyl sulfoxide (DMSO) [In another work, COF nanobars were synthesized in a carbondioxide  . 2/g, 647 m2/g, 626 m2/g, and 333 m2/g, respectively. Notably, porous and crystalline Tp-Bpy thin films exhibited an unprecedented acetonitrile permeance of 339 Lm−2h−1bar−1. The interfacial polymerization of a COF membrane is usually conducted in ambient conditions. In general, high temperature can increase the solubility of monomer units, but interrupts the interface morphology, which can lead to defects in the framework membrane. In addition to interfacial polymerizations at the liquid/liquid interface, interfacial polymerization at the liquid/air interface was established for the fabrication of COF membranes. Lai and co-workers reported the fabrication of a TFP-DHF 2D COF membrane from 1,3,5-triformylphloroglucinol and 9,9-dihexylfluorene-2,7-diamine through the Langmuir–Blodgett method [COF membrane synthesis was viable a decade after the first ever COF fabrication performed under a solvothermal condition. To date, the development of COF membranes is still in its early stages. The prominent drawbacks come from three aspects, including low crystallinity, inferior processability, and irregular pore channel size. As such, the interfacial polymerization of β-ketoenamine-linked COF membranes at room temperature has advanced as a prominent method to prepare COF membranes. Banerjee and co-workers fabricated Tp-Bpy, Tp-Azo, Tp-Ttba, and Tp-Tta COF membranes by the liquid–liquid interfacial polymerization of 1,3,5-triformylphloroglucinol with 2,2′-bipyridine-5,5′-diamine, 4,4′-azodianiline, 4,4′,4″-tristrianiline, and 4,4′,4″-trianiline, respectively, at ambient temperature . In thist method . A monom−2h−1MPa−1 with desirable dye rejection. Furthermore, a heterostructure COF bilayer membrane was fabricated by a mixed-assembly strategy under an ambient condition. The Jiang research group illustrated the assembly of a TpDHBD nanosheet on a polydopamine-modified PAN substrate by vacuum filtration. Subsequently, the TpHZ COF layer displayed an in situ growth on the framework nanosheet layer via the vapor–liquid interfacial synthesis method. This exclusive promotion of heterogeneous nucleation assisted the creation of a second TpHZ COF layer. Remarkably, the crystallinity of the bilayer membrane was greater as compared to the membrane fabricated by liquid–liquid interfacial polymerization due to the epitaxial growth of a COF nanosheet and slow diffusion of monomers. Furthermore, the heterostructural membrane displayed a separation factor of 4464 for water/butanol separation [2O) was mixed with water to form salt. The resultant organic salt and 1,3,5-triformylphloroglucinol were shaken to produce a dough followed by a knife-cast on a plate to fabricate film. Lastly, baking the film at elevated temperatures (60–120 °C) for 12–72 h led to the in situ growth of the COF membrane. This strategy extended to synthesize TpBD(Me)2-, TpAzo-, TpBpy-, TpOMe-Pa1-, TpOMe-BD(NO2)2-, TpOMe-Azo-, and TpOMe-Bpy-based COF membranes [−2h−1bar−1. In addition to the liquid–liquid interface, solid–vapor or liquid–vapor interfaces for COF membrane fabrications required high temperatures [−2h−1bar−1) and acetonitrile (583 Lm−2h−1bar−1). These varying synthetic strategies were used to compare the advantages and disadvantages of constructing frameworks  substrate . The polparation . COF memparation . The aroembranes ,224. Noteratures ,225,226.ameworks . NotablyCOFs synthesized by stitching organic building blocks using a range of coupling reactions are typically characterized by various physiochemical techniques to establish structural and physical properties. In this section, we describe the analytical techniques to comprehend the structural, physical, and chemical features of porous frameworks. wp and Rp. In addition to PXRD, small-angle and wide-angle scattering values (SAXS/WAWS) reflect the extent of the polymerization and crystallinity of COF suspensions [Powder X-ray diffraction (PXRD) patterns with distinct and clear diffraction signals helped us to evaluate the structure and crystallinity of the framework. Structural simulations together with calculated PXRD comparisons with experimental PXRD patterns aided the correct prediction of COF structures. To further evaluate the stacking layer patterns (AA or AB stackings) of 2D COFs, density functional tight binding (DFTB) calculations along with optimization of conformation was pivotal ,228. In pensions ,230.The influence of temperature and pressure on COF structural changes are usually investigated via in situ XRD. To reveal the thermal and pressure stability values, the diffraction intensity against pressure or heat underlined the structural information. High temperature favored a change in the crystalline structure of the framework, whereas high pressure was unfavorable to crystalline COFs. Three-dimensional imine-based COF-300, COF-303, LZU-79, and LZU-111 were synthesized as single crystals. These COF crystals were resolved using single-crystal X-ray diffraction (SXRD) to generate detailed crystal parameters, including atomic positions, bond lengths, bond angles, and unit cell parameters . This co2 adsorption isotherm at 77 K to obtain pore volume, pore size, and surface area. The physisorption isotherms of the framework are divided into six types of micropores, mesopores, and macropores. More importantly, the number of COFs is of significant importance; in general, the weight of the tested COF multiplied by specific surface area (m2/g) should be equal to 100 m2 or greater. Both 2D and 3D COFs should be appropriately activated before understanding the textural parameters. In general, COFs are usually activated by solvent exchange (low-surface-tension solvents), super critical drying, Soxhlet extraction, and vacuum drying, followed by N2)2, TpOMe-Azo, and TpOMe-Bpy with a 2,4,6-trimethoxy-1,3,5-benzenetricarbaldehyde group displayed high chemical stability outcomes in H2SO4 (18M), HCl (12M), NaOH (9M), boiling water, and common organic solvents [Thermogravimetric analysis (TGA) measures the mass loss versus temperature in a controlled atmosphere. This helps us to understand the thermal stability of frameworks. Moreover, the frameworks first undergo a loss of solvent molecules within a temperature range of 60–120 °C, followed by the structural modification or collapse of frameworks (350–450 °C). Furthermore, TGA measurements as mass loss are not inevitably associated with structural change; therefore, the measurement should be complementary to variable temperature powder X-ray diffraction (VT-PXRD) and in situ PXRD. Notably, TGA measurements can be used to roughly estimate the pore volume. The mass loss ascribed to the release of the trapped solvent in the pores near the boiling point can reflect the pore volume of the COFs. In addition to thermal stability, the chemical stability of COFs is fundamentally important to tune the pore environment via established principles of organic and organometallic chemistry. To evaluate the frameworks’ chemical stability, COFs were immersed in acid (diluted and concentrated hydrochloric acid), base (sodium hydroxide), protic , and aprotic solvents  for multiple days to weeks. The physiochemical analysis comparison of pristine and immersed frameworks underlined structural integrity, porosity, crystallinity, and morphology, which is fundamental to develop scaffolds such as novel sensors and catalytic systems. For instance, Py-Azine COFs exhibit excellent chemical stability in 1M HCl and 1M NaOH . In addisolvents . 13C CP-MAS NMR and FT-IR spectroscopy bolstered the successful synthesis, purity, and local chemical environment of the framework. This reinforced the chemical state of multiple functionalities and identities, for instance, dynamic imine-linked COFs showed the appearance of -C=N functionalities at 159 ppm in 13C CP-MAS NMR and at 1620 cm−1 in FT-IR spectroscopy with a disappearance of -C=O and -NH2 moieties. In addition, FT-IR spectra showed absorption values at 1774 cm−1 and 1720 cm−1 corresponding to the asymmetric and symmetric vibrations, respectively, of the -C=O groups of five-membered imide rings. Moreover, 13C CP-MAS NMR exhibited the carbonyl carbon of an imide ring at 163.0–165.0 ppm. Scanning electron microscopy (SEM) and transmission electron microscopy (TEM) are useful to investigate the morphology, elemental composition, and particle size of frameworks. To obtain high-quality SEM images, sputter coating can be performed by applying an ultra-thin coating of electrically conductive metal, such as gold. These microscopies can be combined with energy dispersive spectroscopy (EDS) or energy dispersive X-ray analysis (EDX) to assist elemental quantitative and qualitative composition determinations in COFs. This technique is particularly important to study the presence of immobilized transition metals in COFs via pore surface engineering, which is fundamental to characterize heterogeneous catalysts. In addition, high-resolution TEM allows the visualization of structural features using the low-dose TEM technique based on the use of a direct-detection electron-counting camera. For instance, Peng et al. reported the honeycomb-like porous structure of a TPA-COF nanosheet using high-resolution TEM. The high-resolution TEM image displayed hexagonally arranged white contrasts surrounded by six black dots, which corresponded to a 1D pore channel and building blocks . Further2/g and experience exponential increase in the crystalline TAPB-PDA framework (287 m2/g) after being subjected to two days of optimized reaction conditions [Considerable progress has been achieved in understanding the growth mechanisms of COFs from organic building blocks. The amorphous-to-crystalline transformation mechanism was highlighted by Dichtel and co-workers. The robust and rigid monomer units in solution after the addition of acid catalyst rapidly produced a solid product, which, in most cases, was an amorphous polymer. The solid amorphous product at elevated temperatures under a sealed condition converted kinetically generated amorphous product into thermodynamically stable crystalline networks. For instance, the growth mechanism process of the TAPD-PDA COF was studied under two isolated conditions. First, the initial polymer was characterized by PXRD, underlining the amorphous nature. Thereafter, the amorphous product was re-subjected to the optimized COF synthetic condition (70 °C) without any addition of solvent, and monomers exhibited intense diffraction peaks, underlining the crystalline nature of frameworks. Second, the solid amorphous product without any addition of catalysts of specific concentrations displayed an absence of intense diffraction peaks, thereby confirming an amorphous-to-COF transformation. Notably, the transformation process did not show any major change in morphology. Furthermore, the initial TAPB-PDA amorphous product exhibited a surface area of 18 mnditions . The resnditions ,236. In nditions .2/g and 20 Å, respectively [The reaction-induced mechanism was entirely different from amorphous-to-crystalline and dissolution–recrystallization mechanisms due to no amorphous polymer formation in the early stage of the reaction. Dichtel and co-workers first investigated this mechanism using boron-containing COF-5  Figure . In the ectively .The limited scalability and fragility components are critical challenges in the advancement of COFs towards commercialization and industrial applications. The stable dynamic linkage is essential to connect building blocks in a network structure, which usually require closed conditions to maintain the reversibility of condensation reactions. This is usually achieved by sealed Pyrex tubes with low internal pressures or a hydrothermal reactor. The low internal pressure inside the Pyrex tube permits the slow diffusion of water to enable nucleation and crystallization. In contrast, heated building blocks at elevated temperatures in an open atmosphere can disturb reversibility via a loss of water molecules, thereby exhibiting a poor structural order. Consequently, it is difficult to maintain an ideal reaction condition to synthesize COFs on a larger scale, thereby the percentage yield of most COFs is in the order of milligrams. In addition, a prolonged reaction time, high-temperature boiling solvents, and activation prohibit COFs’ development in the interdisciplinary research.COFs’ high degree of crystallinity differentiates the porous organic material from conventional amorphous polymers. The entire organic character of COFs presents their fundamental role and the utilization of robust dynamic coupling reactions to impart chemical/thermal stability. For example, β-ketoenamine and benzoxazole COFs showed tolerance towards acidic and basic conditions . The hig3PO4, HCl, and CF3SO3H, displayed poor crystallinity and porosity properties due to the strong binding with aromatic diamine, which in turn negatively influenced the nucleophilicity and acid–amine proton transfer reaction required for COF synthesis. Moving beyond the acid catalyst, Lewis acid catalysis for a transamination reaction drastically reduced the reaction time and temperature, however, it introduced activation challenges. In addition, the nucleophilic catalyst and ionic liquids positively influenced the reaction rate. The generalization and widespread usage of ionic liquid in COF synthesis is a significant challenge to expand the library of frameworks in ambient conditions. The sustainability of the catalysts has yet to be considered to a large extent. Nonetheless, under the principle of green chemistry, it is conceivable that toxicity, efficacy, aquatic damage, and safe handling will emerge as relevant factors during synthetic expansion. Apart from the mechanisms and green chemistry, stable linkages are indispensable to avert the initiation of the hydrolytic decomposition of COFs. This primarily depends on the choice of building blocks and dynamic linkage. In general, an electron-withdrawing group directly attached to imine nitrogen exponentially decreases the nucleophilicity of imine nitrogen makes proton attack unfavorable. Consequently, β-ketoenamine, hydrazone, and azine linkages exhibited extra-chemical and thermal stability; however, limited building blocks do not help in the design of stable COFs. It is important to discover novel stable linkages to synthesize COFs at ambient temperature conditions. Furthermore, the robust interlayer stacking interactions bolster addition stability. The electrostatic repulsion among polarized bonds and π–π stacking interactions between an individual layers improves stability. Notably, the presence of intramolecular hydrogen bonding interaction via the uniform distribution of hydroxy group, methoxy groups significantly improve crystallinity, porosity, and chemical stability of COFs [The addition of catalysts is highly relevant to hasten COFs reaction rates. However, an aspect of green chemistry is equally relevant. The stitching of building blocks via ultra-stable dynamic linkages is scarcely practicable without a catalytic mediation. Acetic acid is one of the most widely used catalysts for COF synthesis. Brønsted acids, such as H of COFs ,140. Theo-dichlorobenzene/n-butanol, mesitylene/1,4-dioxane) further facilitates water partition between a reaction mixture, which is effective in reversibly controlled reaction rates. COFs constructed through an irreversible coupling reaction are pivotal to address crystallization. The solvent trapped in the pores adds activation issues and differentiates frameworks as ultra-stable and fragile COFs.Apart from synthetic challenges, the crystallization of extended structures is relatively difficult as compared to discrete structures. The crystallization process requires reversible bond formation to allow the self-correction of defects and avoid the design of an amorphous network. This involves the judicious design of building blocks and the specific positioning of functionalities to add covalent linkages between organic molecules. In addition to the building blocks’ symmetricity, the appropriate stoichiometric quantities of building blocks are important to control the equilibrium in a closed system. The combination of hydrophilic and hydrophobic solvents , acetone (91 m2/g), tetrahydrofuran (28 m2/g), dioxane (113 m2/g), and dimethylformamide (172 m2/g) [In most instances, the as-synthesized COFs, heated (60 °C–80 °C) under vacuum, may be sufficient to remove the trapped solvent. This is observed in an ultra-robust imine-linked, β-ketoenamine-linked, hydrazone-linked, azine-linked, imide-linked, and other COFs. On the contrary, fragile COFs collapse under vacuum due to high surface tension and capillary forces imposed on the structure by the liquid-to-gas phase transformation of trapped solvent molecules . One of 72 m2/g) . To appr2/g and 3312 m2/g, respectively), whereas activation with tetrahydrofuran disrupted crystallinity and porosity (91 m2/g). Notably, hydroxyl-functionalized rhombic Py-OH1P COF displayed structural robustness, crystallinity, and porosity after activation with methanol, tetrahydrofuran, and perfluorohexane. This underlined the profound role of hydrogen bonding in maintaining the structural integrity of frameworks. A similar activation effect was unambiguously observed for imine-linked COFs of varying pore sizes, TAPB-BTCA (0.9 nm), TAPB-TFPA (1.7 nm), TAPB-TFPB (2.0 nm), and TAPB-PDA (3.3 nm), and pore functionalities, TAPB-FPDA, TAPB-OH PDA, and TAPB-Br PDA. In addition, Soxhlet extraction is another important means for solvent exchange, particularly in the case of linkers, which are difficult to separate due to poor solubility and the solvent being difficult to remove from the pores. For instance, COF-ETTA-EDDA, COF-ETTA-DMDA, TPAPC-COF, and others activated by Soxhlet extraction using anhydrous tetrahydrofuran and acetone displayed significant improvement in crystallinity and porosity [In another work, Verduzco and co-workers elaborate an insight into the relationship between structural integrity and pore size, pore functionality, and pore architecture . Rhombicporosity . 2, surface tension = 0.6 dynes/cm) is a milder activation technique especially used for fragile framework in which conventional solvent exchange is unsuccessful and causes structure collapse. Using scCO2, the activation process avoids the liquid-to-gas phase transformation of the guest solvent and instead experiences a supercritical phase, thereby eliminating capillary forces and the surface tension effect. From an experimental perspective, the solvated COFs can be placed in a scCO2 dryer and cooled to 2–10 °C, followed by exchange with CO2. The sample chamber temperature should not drop below 0 °C and fresh CO2 can be purged every hour. After multiple exchanges (4–5 times), the sample can be heated to 31 °C and 73 atm, the supercritical temperature and pressure of CO2 to release gaseous CO2, respectively, often called as bleeding. The activation challenge associated with a fragile framework can be resolute to access porosity. For instance, Medina and co-workers underlined scCO2 activation to access the porosity of TA TAPB-COF, TT TAPB-COF, and BDT TAPB-COF fragile COFs with BET surface areas of over 1000 m2/g [2 activated hydrazone-linked TFPB-DHz COF, TFPT-DHz COF, and Py-DHz COF exhibited excellent crystallinity and porosity [2/g, 790 m2/g, and 932 m2/g respectively, while the conventional solvent-activated COFs appeared to be amorphous. Recently, Feriante et al. highlighted the minimization of capillary strain to avoid pore collapse using scCO2 and to bolster the rapid synthesis of ultra-robust imine-linked TAPB-PDA, TAPB-OHPDA, TAPB-OMePDA, TAPPy-PDA, and TAPPy-NDI-DA COFs in four hours [2 activation is approximately ten times higher as compared to vacuum activation. In contrast to TAPB-PDA COF, the influence of vacuum or scCO2 activation on TAPB-OMePDA and TAPPy-PDA COFs is less noticeable, thereby approving the stabilizing effect due to docking behavior.Supercritical carbon dioxide (scCO000 m2/g . On the porosity . The BETur hours . The surp-aminophenyl)corrole and terephthaldehyde in mesitylene/n-butanol at 120 °C exhibited good crystallinity and a BET surface of 745 m2/g. However, the similar stoichiometric ratio of building blocks in either ethanol/mesitylene or butanol/o-dichlorobenzene displayed lower BET surface areas [The synthetic development of COFs can benefit greatly by establishing manufacturing equipment. A mobile robot is widely used in the industry to exponentially increase the productivity. The robot has human-like dimensions and can operate to dispense insoluble and soluble solutions with high accuracy and repeatability. Furthermore, the robot arm and the mobile base comply with safety standards. To date, no approaches have integrated COFs with mobile robotics to shorten the timeline for either the synthesis or optimization of reaction conditions. Cooper’s research group recently reported a mobile robot for improved photocatalysts for hydrogen production from water . Notablyce areas . This lace areas . The ide3OH, THF, DMAc, DMF, 1,4-dioxane, and dimethylsulfoxide) or a mixture of solvents  at varying temperatures (60 °C and 120 °C) and times (72 h and 96 h) showed poor crystallinity or no solid product [Recently, Beuerle, Würthner and co-workers reported the influence of varying reaction conditions to fabricate crystalline COFs from amorphous polymers. The solvothermal reaction of rutheniumdialdehyde and tetra-(4-anilyl)methane at 60 °C in N,N- dimethylacetamide/mesitylene (1:1) displayed high crystallinity; however, nine solvothermal reactions in one solvent (CH product . This suCovalent organic frameworks, a novel porous organic material, has been broadly examined in various fields and displays an imperative role in nanotechnology. COFs’ porosity and crystallinity confirms the unambiguous validation of their structures constructed by dynamic covalent linkages using the principle of reticular chemistry. Dynamic covalent chemistry proposes distinct properties, such as thermal stability, chemical stability, and high porosity, of the designed frameworks, which is important in industrial applications. Furthermore, the library of symmetrical building blocks bearing multiple binding sites at a specific position shows the structural and topological diversity of COFs. This expansion of organic chemistry to an extended network was comprehensively discussed in this review. The design principle can be useful in building either reported or hypothesized structures with varying pore shapes and sizes. This variable pore geometry offers ample opportunities to create an ideal electronic and steric environment either via pore surface engineering or de novo approaches. With these accomplishments, COFs have a unique position in the fields of material sciences and chemistry. However, despite their many favorable characteristics and great advances, the fields require considerable research to urgently address the level of synthetic control, from molecular geometry to network geometry. This requires manipulation at the fundamental level, including synthetic, crystallization, activation, controlled morphology, and coupling chemistry, which hinder the large-scale synthesis of COFs. The review underlined these issues, which deserve attention in future research.1. The building blocks for constructing COFs are either unavailable commercially or expensive. The most common starting materials involve multistep tedious reaction under severe conditions, and the complicated purification step hampers gram-scale synthesis. In addition, the role of the catalyst in COF synthesis remains a nascent field from a mechanistic perspective, which requires in-depth investigation, especially when moving from protic acid to metal salt. The stitching of building blocks in the presence of a novel catalyst may provide a plausible solution to poor-crystalline COFs and extends the reaction time, but limits safety and presents sustainability concerns. 2. The uniformity and reproducibility in the large-scale synthesis of crystalline and porous COFs are central to commercialization. However, the complexity in structural, activation, and crystallization aspects at the milligram scale demands sustainable tactics for scalable production and batch-to-batch reproducibility. The solvent-free mechanosynthesis might be a plausible method, but suffer from a limited scope. It is imperative to focus on irreversible coupling reactions to develop a simple and effective method for well-defined, uniform, and reproducible COFs, which is still in its infancy. 3. The scalable and sustainable preparation of COFs will significantly be assisted by using manufacturing equipment. The use of automation and robotics can not only bolster the optimization of reaction conditions to fabricate established or novel linkages in a short time, but also positively influence large-scale synthesis at the industrial level for wider applications. Thus, this is only the beginning of this exciting field.