Release Cycles Research Articles

Continuous Integration and Continuous Deployment (CI/CD) Optimization

The advent of Continuous Integration and Continuous Deployment (CI/CD) has fundamentally altered the landscape of software development, enabling teams to deliver updates with unprecedented speed and reliability. By automating the integration of code changes from multiple developers into a central repository, CI/CD practices ensure that software is continuously tested and deployed. This ongoing cycle not only facilitates quicker release cycles but also enhances collaboration among team members and fosters a culture of shared responsibility for code quality. Despite these advancements, organizations face significant challenges in optimizing their CI/CD pipelines. As software systems grow in complexity, the demand for swift and dependable deployments intensifies. This paper explores various techniques and strategies for optimizing CI/CD processes to minimize deployment times while maintaining system reliability. Key optimization methods discussed include: Parallelization of Build Processes: This technique involves breaking down the build process into smaller, independent tasks that can be executed concurrently. By leveraging distributed computing resources, organizations can significantly reduce build times, allowing for faster iterations and deployments. Dependency Caching: Caching dependencies can drastically decrease build times by reusing previously downloaded components. This approach not only speeds up the build process but also minimizes network load and enhances the overall efficiency of the CI/CD pipeline. Incremental Builds: Unlike full builds that compile the entire codebase, incremental builds focus on compiling only the changes made since the last build. This strategy reduces the amount of work needed for each build, accelerating the overall development process. The paper also delves into advanced rollback mechanisms such as blue-green deployments and canary releases. Blue-green deployments allow teams to maintain two identical production environments, enabling smooth transitions and quick rollbacks in case of issues. Canary deployments, on the other hand, introduce new features to a small subset of users before a full rollout, allowing teams to monitor the impact and catch potential failures early. Additionally, automated rollback mechanisms play a vital role in maintaining system reliability, ensuring that any failed deployments can be reverted swiftly to avoid downtime and user disruption. The impact of automation tools on deployment speed and error reduction is another critical aspect examined in this research. Automation frameworks can streamline various stages of the CI/CD process, from code integration to testing and deployment, minimizing human error and ensuring consistent, repeatable processes. By implementing robust automation strategies, organizations can not only accelerate their deployment cycles but also improve overall software quality.

Early steps of protein disaggregation by Hsp70 chaperone and class B J-domain proteins are shaped by Hsp110

Hsp70 is a key cellular system counteracting protein misfolding and aggregation, associated with stress, ageing, and disease. Hsp70 solubilises aggregates and aids protein refolding through substrate binding and release cycles regulated by co-chaperones: J-domain proteins (JDPs) and nucleotide exchange factors (NEFs). Here, we elucidate the collaborative impact of Hsp110 NEFs and different JDP classes throughout Hsp70-dependent aggregate processing. We show that Hsp110 plays a major role at initial stages of disaggregation, determining its final efficacy. The NEF catalyses the recruitment of thick Hsp70 assemblies onto aggregate surface, which modifies aggregates into smaller species more readily processed by chaperones. Hsp70 stimulation by Hsp110 is much stronger with class B than class A JDPs and requires the auxiliary interaction between class B JDP and the Hsp70 EEVD motif. Furthermore, we demonstrate for the first time that Hsp110 disrupts the JDP-Hsp70 interaction. Such destabilisation of chaperone complexes at the aggregate surface might improve disaggregation, but also lead to the inhibition above the sub-stoichiometric Hsp110 optimum. Thus, balanced interplay between the co-chaperones and Hsp70 is critical to unlock its disaggregating potential.

Early steps of protein disaggregation by Hsp70 chaperone and class B J-domain proteins are shaped by Hsp110.

Hsp70 is a key cellular system counteracting protein misfolding and aggregation, associated with stress, ageing, and disease. Hsp70 solubilises aggregates and aids protein refolding through substrate binding and release cycles regulated by co-chaperones: J-domain proteins (JDPs) and nucleotide exchange factors (NEFs). Here, we elucidate the collaborative impact of Hsp110 NEFs and different JDP classes throughout Hsp70-dependent aggregate processing. We show that Hsp110 plays a major role at initial stages of disaggregation, determining its final efficacy. The NEF catalyses the recruitment of thick Hsp70 assemblies onto aggregate surface, which modifies aggregates into smaller species more readily processed by chaperones. Hsp70 stimulation by Hsp110 is much stronger with class B than class A JDPs and requires the auxiliary interaction between class B JDP and the Hsp70 EEVD motif. Furthermore, we demonstrate for the first time that Hsp110 disrupts the JDP-Hsp70 interaction. Such destabilisation of chaperone complexes at the aggregate surface might improve disaggregation, but also lead to the inhibition above the sub-stoichiometric Hsp110 optimum. Thus, balanced interplay between the co-chaperones and Hsp70 is critical to unlock its disaggregating potential.

A model-driven, metrics-based approach to assessing support for quality aspects in MLOps system architectures

In machine learning (ML) and machine learning operations (MLOps), automation serves as a fundamental pillar, streamlining the deployment of ML models and representing an architectural quality aspect. Support for automation is especially relevant when dealing with ML deployments characterised by the continuous delivery of ML models. Taking automation in MLOps systems as an example, we present novel metrics that offer reliable insights into support for this vital quality attribute, validated by ordinal regression analysis. Our method introduces novel, technology-agnostic metrics aligned with typical Architectural Design Decisions (ADDs) for automation in MLOps. Through systematic processes, we demonstrate the feasibility of our approach in evaluating automation-related ADDs and decision options. Our approach can itself be automated within continuous integration/continuous delivery pipelines. It can also be modified and extended to evaluate any relevant architectural quality aspects, thereby assisting in enhancing compliance with non-functional requirements and streamlining development, quality assurance and release cycles.

ПОСТРОЕНИЕ МОДЕЛИ РАСЧЕТА ВРЕМЕНИ ВЫПУСКА ДОРАБОТОК ПРОГРАММНОГО ОБЕСПЕЧЕНИЯ ПОСЛЕ ВНЕДРЕНИЯ СИСТЕМЫ УПРАВЛЕНИЯ РЕЛИЗНЫМ ЦИКЛОМ

The paper proposes a mathematical model for calculating the release time of a new software release. This model allows you to evaluate the difference between the operation of a production system during the release cycle and after it. The relevance of the proposed methodology determines the need for its application to the problem of assessing the effectiveness of an information complex and an automated release process cycle. The object of the study is the information department of the bank, ensuring automation – the process of estimating the release time of software improvements. The goal of the work is to build a model for calculating the release time of software improvements after the implementation of a release cycle management system, ensuring regular, fast and stable implementation of new software versions. To achieve this goal, within the framework of the work, an architectural solution for a system that automates the release cycle process was designed; a new process of personnel interaction was modeled after the implementation of the release cycle system; a pipeline for automatic delivery of software to an industrial environment and a process for automatic packaging of software into containers have been developed; a mathematical model was built to calculate the release time of software improvements after the release cycle management system. To solve these problems, we used the Gitlab CI/CD class system, which provides the ability to automatically assemble containers and deploy them into environments, and the Deckhouse system for container orchestration.

Analysis on the effect of novel topological optimization fin structures considering eccentricity on the heat storage and release characteristics of shell and tube phase change heat accumulator

Shell and tube phase change accumulator (STPCA), as a common type of heat accumulator, can effectively solve the mismatching of time and space in solar thermal power generation by using phase change storage technology. However, the low thermal conductivity of phase change materials (PCMs) reduces its heat storage and release rate. To achieve a rapid latent heat energy storage and release, it needs to carefully modify the structure of STPCA. In the existing literature, insufficient attention has been given to simultaneously addressing the heat storage and release processes, while there is a scarcity of topological optimization methods employed in fin design. On one hand, it is difficult to find the optimal structure. On the other hand, the optimized structure is suitable for melting process but may not be suitable for solidification process. In this contribution, we initially integrated topological optimization and eccentricity to derive fin structures suitable for respective melting and solidification processes. Then, we compared and analyzed the effects of eccentricity and objective function on melting and solidification processes. Finally, we summarized the topology optimization process, objective function and eccentricity suitable for fast heat storage and release. The findings indicated that as the eccentricity increases, the rate of heat storage and release initially rises before subsequently declining. In this work, it is found that an eccentricity of 5 mm is the best. From the whole heat storage and release cycle, when the eccentricity is 5 mm, the objective function is the minimum temperature difference and the topological optimization fin structure calculated during solidification process shows the best heat storage and release performance. Compared with the topology optimization structure without eccentricity, the heat storage speed is increased by 36.43 %, and the heat release speed is increased by 15.53 %. The design law of the STPCA based on combined with the eccentricity influence and topology optimization method is summarized to help improve its heat storage and release performance.

Chemotherapeutic Efficacy of Rutin in Triple Negative Breast Cancer

Cancer is a complex group of diseases characterized by the uncontrolled growth and spread of abnormal cells in the body. It causes millions of deaths each year and remaining a significant global health concern for both men and women. Effective treatment strategies are crucial for improving patient outcomes in breast cancer, particularly in the case of triple-negative breast cancer (TNBC), characterized by the absence of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2). Chemotherapy, like paclitaxel and docetaxel, is the standard treatment for TNBC due to the lack of targeted therapies for this subtype. Paclitaxel (PTX) is a widely used chemotherapeutic medication that is particularly effective against lung, ovarian, and other cancers; nevertheless, its clinical use is limited due to its multi-organ toxicity. As a result, the current study aims to improve treatment efficacy and reduce PTX-induced toxicity through the concurrent use of the natural polyphenolic substance Rutin. Rutin hydrate (purity > 94%) and paclitaxel were utilized in in vitro studies with 4T1 and MDA MB-231 cell lines. In the proliferation assay, cells were treated with rutin and paclitaxel at varying concentrations. Cytochrome-c release and cell cycle analysis were conducted, and flow cytometry assessed apoptosis. According to the findings of this investigation, rutin in combination with PTX considerably (P<0.05) lowers the growth and proliferation of breast cancer cell lines in vitro. Furthermore, flow cytometry research revealed that combining rutin with PTX triggered GO/Gl cell cycle arrest and apoptosis in a breast cancer cell line. Furthermore, after co-administration of rutin and PTX, mitochondrial depolarization increased significantly (P<0.05). Thus, the current study convincingly established rutin’s sensitizing activity and suggests it could be a potential adjuvant in cancer chemotherapy.

Automated Security Testing in DevOps Environments Using AI and ML

The rapid adoption of DevOps practices has transformed the software development landscape by emphasizing continuous integration, continuous delivery (CI/CD), and agile methodologies. However, this rapid pace of development often introduces significant security challenges, as traditional security testing methods struggle to keep up with the accelerated release cycles. To address these challenges, the integration of Artificial Intelligence (AI) and Machine Learning (ML) into automated security testing has emerged as a promising solution. This paper explores the use of AI and ML to enhance automated security testing within DevOps environments, offering a comprehensive approach to identifying, predicting, and mitigating security vulnerabilities in real time. Automated security testing leverages AI and ML algorithms to analyze code, detect anomalies, and predict potential security threats. These technologies enable the continuous monitoring of codebases, allowing for the early identification of vulnerabilities before they are exploited. By incorporating AI-driven security testing into the CI/CD pipeline, organizations can ensure that security is not an afterthought but a continuous process integrated into every stage of the software development lifecycle. AI and ML models can be trained to recognize patterns associated with security risks, such as code injection, unauthorized access, and data leakage. These models continuously learn from new data, improving their accuracy over time and adapting to evolving threats. The dynamic nature of AI-driven security testing makes it particularly suited for DevOps environments, where frequent code changes and updates can introduce new vulnerabilities. Moreover, AI and ML can assist in automating complex tasks, such as threat modeling, risk assessment, and the prioritization of security issues, enabling security teams to focus on higher-order tasks that require human expertise.

Numerical prediction model for long- and short-term concentration of indoor volatile organic compounds from building materials

ABSTRACT Emission models of volatile organic compounds (VOCs) from individual indoor building materials have been developed and validated. However, multiple indoor building materials release VOCs simultaneously, and neither single building material nor multiple building material emission models can predict the entire release cycle of VOCs accurately. This study established a long- and short-term numerical prediction model for indoor VOC concentration. The model includes an attenuation coefficient θ. To describe the decay rate of the total VOC content, which is mainly influenced by time, and by designing experiments and testing in environmental warehouses under different seasonal conditions, the value of θ was first obtained. Then, after successfully plotting the emission curve of indoor pollutant concentration over time through numerical solution and using θ, the VOC content was corrected for various seasonal conditions. On the basis of this model, an exposure dose integration algorithm was proposed to evaluate the environmental health risks, as an application of this model. In comparison with previous research results and experimental data, this model has better predictive performance.

High stability of dark current enables stretchable near-infrared self-powered organic photodetectors

Ultra-flexible and stretchable organic photodetectors (s-OPDs) sensitive in the near-infrared (NIR) region hold great potential for wearable health monitoring with excellent physiological signal and skin conformability. However, the development of OPDs that combines NIR sensitivity, low power consumption, low cost, simple fabrication structure, and good mechanical properties is still challenging and has not been well explored. In this work, we report a self-powered s-OPD with a simple fabrication structure used for organic solar cells and a detectivity of more than 1 × 1012 Jones (corrected by noise current) in the NIR region at 10% tensile strain and short response time (2.46 μs), representing state-of-the-art performances. Reducing energetic disorders other than discrete traps in photoactive layers is more crucial to further reduce the dark current at zero bias. The dark current of the OPDs exhibits higher mechanical stability than photocurrent due to the slower degradation of the parallel resistance than the series resistance under tensile strain. The higher stability of dark current enables the s-OPDs as a stretchable organic photoplethysmogram heart rate sensor, showing excellent detectivity under 30% strain or 800 stretching–release cycles at 10% strain, indicating the great potential for application in wearable optoelectronics.

Intrinsically Stretchable Polymer Semiconductor with Regional Conjugation for Stretchable Electronics

AbstractThe development of intrinsically stretchable polymer semiconductor holds substantial promise in the field of wearable electronics. However, charge transport mobility is typically compromised in existing stretchable semiconductors to achieve the desired stretchability. Herein, a novel “regional conjugation” strategy is proposed to design an intrinsically stretchable polymer semiconductor oligo‐diketopyrrolopyrrole‐thieno[3,2‐b]thiophene (DPPTT)–urethane, in which oligo‐DPPTT conjugated units and alkyl urethane nonconjugated units are introduced. The regional conjugation of oligo‐DPPTT in the polymer backbone endows DPPTT–urethane with good molecular packing, leading to a high mobility of up to 1.7 cm2 V−1 s−1. Additionally, incorporating alkyl urethane nonconjugated units in the backbone can reduce film crystallinity and chain aggregation, which contribute to the stretchability of the polymer thin film. Consequently, fully stretchable transistors retain carrier mobility even at 100% biaxial tensile strain. Furthermore, the fully stretchable organic field‐effect transistor arrays show remarkable charge transport reversibility and durability after 1000 stretch–release cycles at 25% strain. Additionally, the device exhibits extraordinary electrical stability in air atmosphere. Overall, these results indicate that the “regional conjugation” strategy provides an effective and promising methodology to design intrinsically stretchable and high‐performance polymer semiconductor that can advance the development of soft and wearable electronics.

Hierarchical antibiotic delivery system based on calcium phosphate cement/montmorillonite-gentamicin sulfate with drug release pathways

Antibiotic-loaded calcium phosphate cement (CPC) has emerged as a promising biomaterial for drug delivery in orthopedics. However, there are problems such as the burst release of antibiotics, low cumulative release ratio, inappropriate release cycle, inferior mechanical strength, and poor anti-collapse properties. In this research, montmorillonite-gentamicin (MMT-GS) was fabricated by solution intercalation method and served as the drug release pathways in CPC to avoid burst release of GS, achieving promoted cumulative release ratios and a release cycle matched the time of inflammatory response. The results indicated that the highest cumulative release ratio and release concentration of GS in CPC/MMT-GS was 94.1 ± 2.8 % and 1183.05 μg/mL, and the release cycle was up to 504 h. In addition, the hierarchical GS delivery system was divided into three stages, and the kinetics followed the Korsmeyer-Peppas model, the zero-order model, and the diffusion-dissolution model, respectively. Meanwhile, the compressive strength of CPC/MMT-GS was up to 51.33 ± 3.62 MPa. Antibacterial results demonstrated that CPC/MMT-GS exhibited excellent in vitro long-lasting antibacterial properties to E. coli and S. aureus. Furthermore, CPC/MMT-GS promoted osteoblast proliferation and exhibited excellent in vivo histocompatibility. Therefore, CPC/MMT-GS has favorable application prospects in the treatment of bone defects with bacterial infections and inflammatory reactions.

Screen-Printed Stretchable Supercapacitors Based on Tin Sulfide-Decorated Face-Mask-Derived Activated Carbon Electrodes with High Areal Energy Density

Screen-Printed Stretchable Supercapacitors Based on Tin Sulfide-Decorated Face-Mask-Derived Activated Carbon Electrodes with High Areal Energy Density

Pararorine A, isoindolinone alkaloid from the endophytic fungus Paramyrothecium roridum and its anti-tumor activity

Pararorine A, a new isoindolinone alkaloid was isolated from Paramyrothecium roridum, an endophytic fungus from the medicinal plant Gynochthodes officinalis (F.C. How) Razafim. & B. Bremer. The structure of this compound was elucidated by extensive spectroscopic (UV, IR, MS, and NMR) analyses. In addition, the antitumor activity of pararorine A was evaluated against SF-268, MCF-7, HepG2, and A549 tumor cell lines. The results revealed that pararorine A exhibited potent antitumor activities with the IC50 values ranging from 1.69 to 8.95 μM. Moreover, the tumor cell inhibitory activity of pararorine A was evidenced by promoting cytochrome C release and cell cycle arrest as well as the induction of apoptosis by the up-regulation of the protein expressions of JNK and Bax through PARP-cleavage and caspase 3-cleavage.

The Norbornadiene/Quadricyclane Pair as Molecular Solar Thermal Energy Storage System: Surface Science Investigations.

For the transition to renewable energy sources, novel energy storage materials are more important than ever. This review addresses so-called molecular solar thermal (MOST) systems, which appear very promising since they combine light harvesting and energy storing in one-photon one-molecule processes. The focus is on norbornadiene (NBD), a particularly interesting candidate, which is converted to the strained valence isomer quadricyclane (QC) upon irradiation. The stored energy can be released on demand. The energy-releasing cycloreversion from QC to NBD can be initiated by a thermal, catalytic, or electrochemical trigger. The reversibility of the energy storage and release cycles determines the general practicality of a MOST system. In the search for derivatives, which enable large-scale applications, fundamental surface science studies help to assess the feasibility of potential substituted NBD/QC couples. We include investigations under well-defined ultra-high vacuum (UHV) conditions as well as experiments in liquid phase. Next to the influence of the catalytically active surfaces on the isomerization between the two valence isomers, information on adsorption geometries, thermal stability limits, and reaction pathways of the respective molecules are discussed. Moreover, laboratory-scaled test devices demonstrate the proof of concept in various areas of application.

In-situ monitoring of charge and discharge process in supercapacitor with a micro-cavity Mach-Zehnder interferometer and a fiber Bragg grating

Supercapacitors are promising energy storage devices. However, efficient monitoring of charge and discharge process remains challenging. Current methods are limited by large size, high cost and complex manufacturing processes, restricting their practical application. To address this issue, a low-cost and easily fabricated micro-cavity Mach-Zehnder interferometer (MZI) combined with a Fiber Bragg grating (FBG) is proposed for real-time, in-situ monitoring of charge and discharge process in supercapacitor. The MZI sensor has a ultrahigh refractive index sensitivity of −21833 nm/RIU. In cyclic voltammetry(CV) test, a charge sensitivity of 11.49 nm/C is obtained. Furthermore, the temperature sensitivities of MZI and FBG are 1.64 nm/℃ and 0.011 nm/℃ respectively, measured in an electrolyte environment. This innovative approach enables precise and instantaneous measurement of critical parameters like capacitance and temperature throughout energy storage and release cycles. The proposed compact, flexible and low-cost fiber MZI sensor offers a highly promising solution for in-situ supercapacitor monitoring.

The Entrainment of Task Allocation and Release Cycles in Open Source Software Development

In this study we identify a process of “entrainment” around open source software (OSS) development release cycles to capture patterns of self-organized task allocation among developers. We conducted an abductive, computationally intensive study of eight OSS projects, using relational event modeling to analyze 1,169,489 actions covering 93 major software releases. The process of entrainment that we identify involves three task allocation mechanisms: (1) developer-issue inertia, (2) developer contribution frequency, and (3) issue popularity. Our analysis demonstrates that these mechanisms and the phases of the release cycle entrain each other. Before a major release, developers engage in a concentrated mobilization phase, whereby they democratize development activity and increasingly allocate community contributions to the set of issues related to the release. After a major release, the extended cleanup phase garners a greater share of development work from recently highly active developers and dilutes the activity of these developers across a wider range of issues. Our theorizing suggests that major releases constitute important events around which OSS communities self-organize and we characterize how this occurs. Our research contributes to theorizing on organizing in OSS communities by explaining how self-organizing task allocation interacts with release cycles through the mechanism of entrainment. We also contribute to the literature on entrainment by showing how it may unfold in the context of online peer production communities such as OSS.

Fluorinated Nonporous Adaptive Cages for the Efficient Removal of Perfluorooctanoic Acid from Aqueous Source Phases.

Per- and polyfluoroalkyl substances (PFAS) accumulate in water resources and pose serious environmental and health threats due to their nonbiodegradable nature and long environmental persistence times. Strategies for the efficient removal of PFAS from contaminated water are needed to address this concern. Here, we report a fluorinated nonporous adaptive crystalline cage (F-Cage 2) that exploits electrostatic interaction, hydrogen bonding, and F-F interactions to achieve the efficient removal of perfluorooctanoic acid (PFOA) from aqueous source phases. F-Cage 2 exhibits a high second-order kobs value of approximately 441,000 g mg-1 h-1 for PFOA and a maximum PFOA adsorption capacity of 45 mg g-1. F-Cage 2 can decrease PFOA concentrations from 1500 to 6 ng L-1 through three rounds of flow-through purification, conducted at a flow rate of 40 mL h-1. Elimination of PFOA from PFOA-loaded F-Cage 2 is readily achieved by rinsing with a mixture of MeOH and saturated NaCl. Heating at 80 °C under vacuum then makes F-Cage 2 ready for reuse, as demonstrated across five successive uptake and release cycles. This work thus highlights the potential utility of suitably designed nonporous adaptive crystals as platforms for PFAS remediation.

Highly stretchable conductor with elastomeric passivation sheath enabling applications in harsh conditions

The rapid development of robotics requires stretchable electrical conductors capable of large deformations and having high operational stability in terms of electrical and mechanical characteristics. Carbon nanotubes (CNT) have been considered as the primary component of stretchable conductors, and mechanically drawn CNT sheets have shown their functionality when combined with various elastomeric materials in the shape of yarns. Herein, an electrically passivated stretchable conductor with an elastomer sheath and a spandex–CNT coiled-yarn core structure is reported. Based on the proven performance of spandex–CNT coiled-yarn, the electrical insulation by the Ecoflex elastomer enhances its applicability in an actual situation without degrading the stretchable conductor functionality. The experimental results show a substantial working deformation range (up to 350%), high durability, and low resistance variation during repetitive stretch and release cycles. Additionally, its stability is confirmed over a wide temperature range (up to 150 °C) and even inside an acidic liquid environment where the elastomeric sheath protects the conducting core. The perfect cooperation between the Ecoflex sheath and spandex–CNT core opens the possibility of deploying this stretchable conductor technology under harsh conditions.

Parafilm Enabled Rapid and Scalable Delamination/Integration of Graphene for High‐Performance Capacitive Touch Sensor

The high electrical conductivity and bendability of graphene makes it versatile for flexible electronic sensor applications. The fabrication of such flexible sensors necessitates two important prerequisites: defect‐free transfer of graphene to a flexible substrate and creating appropriate patterns without altering graphene's inherent properties. Here, a potentially rapid and scalable method to delaminate graphene non‐destructively from a metal substrate by using flexible parafilm is reported. This method allows not only the scalable transfer of continuous graphene, but also the realization of graphene patterns on the parafilm substrate. Graphene on parafilm showed negligible doping effect with high room temperature carrier mobility exceeding 6 × 103 cm2 V−1 s−1 for a centimeter‐scale sample. Using parafilm as a substrate‐cum‐dielectric medium, a proof‐of‐concept capacitive touch sensor (CTS) arrays is demonstrated without the use of lithography, by simple cross‐assembling and mild heating. The graphene sensor thus realized in its simplistic device configuration had an enhanced sensitivity of 43% when touch and release cycles are performed on the device. The nearly non‐destructive and user‐friendly route for directly integrating graphene with a flexible substrate is expected to play a potential role in the design of graphene‐based flexible electronics.