Recent progress in multifunctional, reconfigurable, integrated liquid metal-based stretchable sensors and standalone systems.

Possessing a unique combination of properties that are traditionally contradictory in other natural or synthetical materials, Ga-based liquid metals (LMs) exhibit low mechanical stiffness and flowability like a liquid, with good electrical and thermal conductivity like metal, as well as good biocompatibility and room-temperature phase transformation. These remarkable properties have paved the way for the development of novel reconfigurable or stretchable electronics and devices. Despite these outstanding properties, the easy oxidation, high surface tension, and low rheological viscosity of LMs have presented formidable challenges in high-resolution patterning. To address this challenge, various surface modifications or additives have been employed to tailor the oxidation state, viscosity, and patterning capability of LMs. One effective approach for LM patterning is breaking down LMs into microparticles known as liquid metal particles (LMPs). This facilitates LM patterning using conventional techniques such as stencil, screening, or inkjet printing. Judiciously formulated photo-curable LMP inks or the introduction of an adhesive seed layer combined with a modified lift-off process further provide the micrometer-level LM patterns. Incorporating porous and adhesive substrates in LM-based electronics allows direct interfacing with the skin for robust and long-term monitoring of physiological signals. Combined with self-healing polymers in the form of substrates or composites, LM-based electronics can provide mechanical-robust devices to heal after damage for working in harsh environments. This review provides the latest advances in LM-based composites, fabrication methods, and their novel and unique applications in stretchable or reconfigurable sensors and resulting integrated systems. It is believed that the advancements in LM-based material preparation and high-resolution techniques have opened up opportunities for customized designs of LM-based stretchable sensors, as well as multifunctional, reconfigurable, highly integrated, and even standalone systems.

Direct Laser Processing and Functionalizing PI/PDMS Composites for an On-Demand, Programmable, Recyclable Device Platform.

Skin-interfaced high-sensitive biosensing systems to detect electrophysiological and biochemical signals have shown great potential in personal health monitoring and disease management. However, the integration of 3D porous nanostructures for improved sensitivity and various functional composites for signal transduction/processing/transmission often relies on different materials and complex fabrication processes, leading to weak interfaces prone to failure upon fatigue or mechanical deformations. The integrated system also needs additional adhesive to strongly conform to the human skin, which can also cause irritation, alignment issues, and motion artifacts. This work introduces a skin-attachable, reprogrammable, multifunctional, adhesive device patch fabricated by simple and low-cost laser scribing of an adhesive composite with polyimide powders and amine-based ethoxylated polyethylenimine dispersed in the silicone elastomer. The obtained laser-induced graphene in the adhesive composite can be further selectively functionalized with conductive nanomaterials or enzymes for enhanced electrical conductivity or selective sensing of various sweat biomarkers. The possible combination of the sensors for real-time biofluid analysis and electrophysiological signal monitoring with RF energy harvesting and communication promises a standalone stretchable adhesive device platform based on the same material system and fabrication process.

Flexible Antibacterial Respiratory Monitoring Sensor Based on Controllable Au-Modified Surface of Highly {001} Preferred Anatase Titanium Dioxide Thin Film.

Respiratory signals are critical clinical diagnostic criteria for respiratory diseases and health conditions, and respiratory sensors play a crucial role in achieving the desired respiratory monitoring effect. High sensitivity to a single factor can improve the reliability of respiratory monitoring, and maintaining the hygiene of the sensors is also important for daily health monitoring. Herein, we propose a flexible Au-modified anatase titanium dioxide resistive respiratory sensor, which can be mechanically compliantly attached to curved surfaces for respiratory monitoring in different modalities (i.e., respiratory intensity, frequency, and rate). The uniform and preferentially oriented anatase titanium dioxide films gained by the polymer-assisted deposition technique can be fabricated on flexible substrates through a liquid-assisted transferring process. The Au modification can enhance surface plasmon resonance to facilitate the photocatalytic activity of titanium dioxide, and the optimized distribution of Au on the surface of titanium dioxide film made the sensor have an excellent antibacterial effect. The uniquely designed encapsulation can effectively control the contact between the surface of titanium dioxide films and electrodes, allowing the flexible sensor to exhibit fast response time (0.71 s) and recovery time (1.06 s) to respiratory as well as insensitivity or low sensitivity to other factors (i.e., gas composition, humidity, temperature, stress, and strain). This work provided an effective strategy for flexible wearable respiratory sensors and has great potential in daily respiratory monitoring for health management and pandemic control.

Highly Sensitive Wearable Sensor Based on (001)-Orientated TiO2 for Real-Time Electrochemical Detection of Dopamine, Tyrosine, and Paracetamol.

The concentration of dopamine (DA) and tyrosine (Tyr) reflects the condition of patients with Parkinson's disease, whereas moderate paracetamol (PA) can help relieve their pain. Therefore, real-time measurements of these bioanalytes have important clinical implications for patients with Parkinson's disease. However, previous sensors suffer from either limited sensitivity or complex fabrication and integration processes. This work introduces a simple and cost-effective method to prepare high-quality, flexible titanium dioxide (TiO2) thin films with highly reactive (001)-facets. The as-fabricated TiO2 film supported by a carbon cloth electrode (i.e., TiO2-CC) allows excellent electrochemical specificity and sensitivity to DA (1.390 µA µM-1 cm-2), Tyr (0.126 µA µM-1 cm-2), and PA (0.0841 µA µM-1 cm-2). More importantly, accurate DA concentration in varied pH conditions can be obtained by decoupling them within a single differential pulse voltammetry measurement without additional sensing units. The TiO2-CC electrochemical sensor can be integrated into a smart diaper to detect the trace amount of DA or an integrated skin-interfaced patch with microfluidic sampling and wireless transmission units for real-time detection of the sweat Try and PA concentration. The wearable sensor based on TiO2-CC prepared by facile manufacturing methods holds great potential in the daily health monitoring and care of patients with neurological disorders.

Trehalose in Trace Quantities as a Multifunctional Electrolyte Additive for Highly Reversible Zinc Metal Anodes.

The unsatisfactory performance of Zn metal anodes significantly impedes the commercial application of aqueous zinc-ion batteries (AZIBs). Herein, we introduce a trace amount of a multifunctional trehalose additive to enhance the stability and reversibility of Zn metal anodes. The trehalose additive exhibits a stronger Zn2+ ion affinity due to abundant lone-pair electrons, disrupting hydrogen bonds in H2O, regulating solvation structures, and tuning the Zn-electrolyte interface. Consequently, the Zn metal anode demonstrates a remarkable Coulombic efficiency of 99.80% and a cycle stability exceeding 4500 h at 1 mA cm-2. Even under stringent conditions of 10 mA cm-2, the Zn metal anode maintains a cumulative capacity of 2500 mA h cm-2 without a short circuit. Furthermore, Zn//Zn symmetric batteries exhibit excellent low-temperature cycle performance (over 400 h at -10 °C). As a proof of concept, assembled Zn//NH4V4O10 and Zn//MnO2 pouch cells demonstrate an improved electrochemical performance. This work presents an electrolyte additive strategy for achieving stable zinc anode operation in AZIBs.

Omnidirectional Configuration of Stretchable Strain Sensor Enabled by the Strain Engineering with Chiral Auxetic Metamaterial.

An electromechanical interface plays a pivotal role in determining the performance of a stretchable strain sensor. The intrinsic mechanical property of the elastomer substrate prevents the efficient modulation of the electromechanical interface, which limits the further evolution of a stretchable strain sensor. In this study, a chiral auxetic metamaterial (CAM) is incorporated into the elastomer substrate of a stretchable strain sensor to override the deformation behavior of the pristine device and regulate the device performance. The tunable isotropic Poisson's ratio (from 0.37 to -0.25) achieved by the combination of CAM and elastomer substrate endows the stretchable strain sensor with significantly enhanced sensitivity (53-fold improvement) and excellent omnidirectional sensing ability. The regulation mechanism associated with crack propagation on the deformed substrate is also revealed with finite element simulations and experiments. The demonstration of on-body monitoring of human physiological signals and a smart training assistant for trampoline gymnastics with the CAM-incorporated strain sensor further illustrates the benefits of omnidirectionally enhanced performance.

Effective Orthodontic Tooth Movement via an Occlusion-Activated Electromechanical Synergistic Dental Aligner.

Malocclusion is a prevalent dental health problem plaguing over 56% worldwide. Mechanical orthodontic aligners render directional teeth movement extensively used for malocclusion treatment in the clinic, while mechanical regulation inefficiency prolongs the treatment course and induces adverse complications. As a noninvasive physiotherapy, an appropriate electric field plays a vital role in tissue metabolism engineering. Here, we propose an occlusion-activated electromechanical synergistic dental aligner that converts occlusal energy into a piezo-excited alternating electric field for accelerating orthodontic tooth movement. Within an 18-day intervention, significantly facilitated orthodontic results were obtained from young and aged Sprague-Dawley rats, increasing by 34% and 164% in orthodontic efficiency, respectively. The different efficiencies were attributed to age-distributed periodontal tissue status. Mechanistically, the electromechanical synergistic intervention modulated the microenvironment, enhanced osteoblast and osteoclast activity, promoted alveolar bone metabolism, and ultimately accelerated tooth movement. This work holds excellent potential for personalized and effective treatment for malocclusions, which would vastly reduce the suffering of the long orthodontic course.

Snowflake-inspired and blink-driven flexible piezoelectric contact lenses for effective corneal injury repair.

The cornea is a tissue susceptible to various injuries and traumas with a complicated cascade repair process, in which conserving its integrity and clarity is critical to restoring visual function. Enhancing the endogenous electric field is recognized as an effective method of accelerating corneal injury repair. However, current equipment limitations and implementation complexities hinder its widespread adoption. Here, we propose a snowflake-inspired, blink-driven flexible piezoelectric contact lens that can convert mechanical blink motions into a unidirectional pulsed electric field for direct application to moderate corneal injury repair. The device is validated on mouse and rabbit models with different relative corneal alkali burn ratios to modulate the microenvironment, alleviate stromal fibrosis, promote orderly epithelial arrangement and differentiation, and restore corneal clarity. Within an 8-day intervention, the corneal clarity of mice and rabbits improves by more than 50%, and the repair rate of mouse and rabbit corneas increases by over 52%. Mechanistically, the device intervention is advantageous in blocking growth factors' signaling pathways specifically involved in stromal fibrosis whilst preserving and harnessing the signaling pathways required for indispensable epithelial metabolism. This work put forward an efficient and orderly corneal therapeutic technology utilizing artificial endogenous-strengthened signals generated by spontaneous body activities.

Skin-Attachable and Stretchable Patch Antenna with Fractal Design for Remote On-Body Motion Sensing.

This article describes the implementation of a wireless human motion detection with interference resistance to untargeted deformations based on a stretchable patch antenna with fractal design. By rationally incorporating the Hilbert fractal pattern in the conductive patch and ground plane, the patch antenna shows a mechanical stretchability of ∼40% and a maximum gain of 2.95 dB at 2.5 GHz. Furthermore, the influence of the fractal order on the mechanical stretchability and radiation properties of the stretchable patch antenna is discussed. The resonant frequency of the stretchable fractal antenna demonstrates highly selective sensitivity to different deformations; i.e., it remains almost unchanged with bending deformations and is linearly dependent on the tensile strain. Remote detection of joint motions is experimentally verified by a wireless on-body strain sensor based on the fractal design-based stretchable microstrip antenna.

Hierarchical Serpentine-Helix Combination for 3D Stretchable Electronics.

3D stretchable electronics attract growing interest due to their new and more complex functionalities compared to 1D or 2D counterparts. Among all 3D configuration designs, a 3D helical structure is commonly used as it can be designed to achieve outstanding stretching ratios as well as highly robust mechanical performance. However, the stretching ratio that mainly focuses on the axis direction hinders its applications. Inspired by hierarchies in a tendon, a novel structural design of hierarchical 3D serpentine-helix combination is proposed. The structural design constructed by a sequence with repeating small units winding in a helical manner around the axis can enable large mechanical forces transferred down to a smaller scale with the dissipation of potentially damaging stresses by microscale buckling, thereby endowing the electronic components made from high-performance but hard-to-stretch materials with large stretchability (≥200%) in x-, y-, or z-axis direction, high structural stability, and extraordinary electromechanical performance. Two applications including a wireless charging patch and an epidermal electronic system are demonstrated. The epidermal electronic system made of several hierarchical 3D serpentine-helix combinations allows for high-fidelity monitoring of electrophysiological signals, galvanic skin response, and finger-movement-induced electrical signals, which can achieve good tactile pattern recognition when combined with an artificial neural network.

Smart bioadhesives for wound healing and closure.

The high demand for rapid wound healing has spurred the development of multifunctional and smart bioadhesives with strong bioadhesion, antibacterial effect, real-time sensing, wireless communication, and on-demand treatment capabilities. Bioadhesives with bio-inspired structures and chemicals have shown unprecedented adhesion strengths, as well as tunable optical, electrical, and bio-dissolvable properties. Accelerated wound healing has been achieved via directly released antibacterial and growth factors, material or drug-induced host immune responses, and delivery of curative cells. Most recently, the integration of biosensing and treatment modules with wireless units in a closed-loop system yielded smart bioadhesives, allowing real-time sensing of the physiological conditions (e.g., pH, temperature, uric acid, glucose, and cytokine) with iterative feedback for drastically enhanced, stage-specific wound healing by triggering drug delivery and treatment to avoid infection or prolonged inflammation. Despite rapid advances in the burgeoning field, challenges still exist in the design and fabrication of integrated systems, particularly for chronic wounds, presenting significant opportunities for the future development of next-generation smart materials and systems.

An End-to-End Cardiac Arrhythmia Recognition Method with an Effective DenseNet Model on Imbalanced Datasets Using ECG Signal.

Electrocardiography (ECG) is a well-known noninvasive technique in medical science that provides information about the heart's rhythm and current conditions. Automatic ECG arrhythmia diagnosis relieves doctors' workload and improves diagnosis effectiveness and efficiency. This study proposes an automatic end-to-end 2D CNN (two-dimensional convolution neural networks) deep learning method with an effective DenseNet model for addressing arrhythmias recognition. To begin, the proposed model is trained and evaluated on the 97720 and 141404 beat images extracted from the Massachusetts Institute of Technology-Beth Israel Hospital (MIT-BIH) arrhythmia and St. Petersburg Institute of Cardiological Technics (INCART) datasets (both are imbalanced class datasets) using a stratified 5-fold evaluation strategy. The data is classified into four groups: N (normal), V (ventricular ectopic), S (supraventricular ectopic), and F (fusion), based on the Association for the Advancement of Medical Instrumentation® (AAMI). The experimental results show that the proposed model outperforms state-of-the-art models for recognizing arrhythmias, with the accuracy of 99.80% and 99.63%, precision of 98.34% and 98.94%, and F 1-score of 98.91% and 98.91% on the MIT-BIH arrhythmia and INCART datasets, respectively. Using a transfer learning mechanism, the proposed model is also evaluated with only five individuals of supraventricular MIT-BIH arrhythmia and five individuals of European ST-T datasets (both of which are also class imbalanced) and achieved satisfactory results. So, the proposed model is more generalized and could be a prosperous solution for arrhythmias recognition from class imbalance datasets in real-life applications.

Recent Advances in Stretchable and Wearable Capacitive Electrophysiological Sensors for Long-Term Health Monitoring.

Over the past several years, wearable electrophysiological sensors with stretchability have received significant research attention because of their capability to continuously monitor electrophysiological signals from the human body with minimal body motion artifacts, long-term tracking, and comfort for real-time health monitoring. Among the four different sensors, i.e., piezoresistive, piezoelectric, iontronic, and capacitive, capacitive sensors are the most advantageous owing to their reusability, high durability, device sterilization ability, and minimum leakage currents between the electrode and the body to reduce the health risk arising from any short circuit. This review focuses on the development of wearable, flexible capacitive sensors for monitoring electrophysiological conditions, including the electrode materials and configuration, the sensing mechanisms, and the fabrication strategies. In addition, several design strategies of flexible/stretchable electrodes, body-to-electrode signal transduction, and measurements have been critically evaluated. We have also highlighted the gaps and opportunities needed for enhancing the suitability and practical applicability of wearable capacitive sensors. Finally, the potential applications, research challenges, and future research directions on stretchable and wearable capacitive sensors are outlined in this review.

Multifunctional flexible contact lens for eye health monitoring using inorganic magnetic oxide nanosheets.

As a non-invasive innovative diagnosis platform, advanced flexible contact lenses can dynamically monitor vital ocular indicators, spot abnormalities and provide biofeedback guidance for real-time diagnosis and rehabilitation tracking of chronic eye diseases. However, most of the state-of-the-art reported contact lenses either can only monitor a single indicator at a time or realize multifunctional integration based on multiple materials. Herein, we developed a flexible multifunctional contact lens based on inorganic γ-Fe2O3@NiO magnetic oxide nanosheets, which can be attached conformally and seamlessly to the eyeball to simultaneously monitor glucose level in tears, eyeball movement, and intraocular pressure. The optimized contact lens has a reliable glucose detection limit (0.43 µmol), superior eye movement measurement accuracy (95.27%) and high intraocular pressure sensitivity (0.17 MHz mmHg- 1). This work presents a concept in the biochemical and biophysical integrated sensing of ocular signals using contact lens via an innovative material, and provides a personalized and efficient way for health management.

An Effective and Lightweight Deep Electrocardiography Arrhythmia Recognition Model Using Novel Special and Native Structural Regularization Techniques on Cardiac Signal.

Recently, cardiac arrhythmia recognition from electrocardiography (ECG) with deep learning approaches is becoming popular in clinical diagnosis systems due to its good prognosis findings, where expert data preprocessing and feature engineering are not usually required. But a lightweight and effective deep model is highly demanded to face the challenges of deploying the model in real-life applications and diagnosis accurately. In this work, two effective and lightweight deep learning models named Deep-SR and Deep-NSR are proposed to recognize ECG beats, which are based on two-dimensional convolution neural networks (2D CNNs) while using different structural regularizations. First, 97720 ECG beats extracted from all records of a benchmark MIT-BIH arrhythmia dataset have been transformed into 2D RGB (red, green, and blue) images that act as the inputs to the proposed 2D CNN models. Then, the optimization of the proposed models is performed through the proper initialization of model layers, on-the-fly augmentation, regularization techniques, Adam optimizer, and weighted random sampler. Finally, the performance of the proposed models is evaluated by a stratified 5-fold cross-validation strategy along with callback features. The obtained overall accuracy of recognizing normal beat and three arrhythmias (V-ventricular ectopic, S-supraventricular ectopic, and F-fusion) based on the Association for the Advancement of Medical Instrumentation (AAMI) is 99.93%, and 99.96% for the proposed Deep-SR model and Deep-NSR model, which demonstrate that the effectiveness of the proposed models has surpassed the state-of-the-art models and also expresses the higher model generalization. The received results with model size suggest that the proposed CNN models especially Deep-NSR could be more useful in wearable devices such as medical vests, bracelets for long-term monitoring of cardiac conditions, and in telemedicine to accurate diagnose the arrhythmia from ECG automatically. As a result, medical costs of patients and work pressure on physicians in medicals and clinics would be reduced effectively.

Reconfigurable, Stretchable Strain Sensor with the Localized Controlling of Substrate Modulus by Two-Phase Liquid Metal Cells.

Strain modulation based on the heterogeneous design of soft substrates is an effective method to improve the sensitivity of stretchable resistive strain sensors. In this study, a novel design for reconfigurable strain modulation in the soft substrate with two-phase liquid cells is proposed. The modulatory strain distribution induced by the reversible phase transition of the liquid metal provides reconfigurable strain sensing capabilities with multiple combinations of operating range and sensitivity. The effectiveness of our strategy is validated by theoretical simulations and experiments on a hybrid carbonous film-based resistive strain sensor. The strain sensor can be gradually switched between a highly sensitive one and a wide-range one by selectively controlling the phases of liquid metal in the cell array with a external heating source. The relative change of sensitivity and operating range reaches a maximum of 59% and 44%, respectively. This reversible heterogeneous design shows great potential to facilitate the fabrication of strain sensors and might play a promising role in the future applications of stretchable strain sensors.

Configurable direction sensitivity of skin-mounted microfluidic strain sensor with auxetic metamaterial.

Electromechanical coupling plays a key role in determining the performance of stretchable strain sensor. Current regulation of the electromechanical coupling in stretchable strain sensor is largely restricted by the intrinsic mechanical properties of the device. In this study, a microfluidic strain sensor based on the core-shell package design with the auxetic metamaterial (AM) is presented. By overriding the mechanical properties of the device, the AM in the package effectively tunes the deformation of the microfluidic channel with the applied strain and configures the directional strain sensitivity with a large modulation range. The gauge factor (GF) of the strain sensor in the radial direction of the channel can be gradually shifted from the intrinsically negative value to a positive one by adopting the AMs with different designs. By simply replacing the AM in the package, the microfluidic strain sensor with the core-shell package can be configurated as an omnidirectional or directional stretchable strain sensor. With the directional sensitivity brought by the rational AM design, the application of the AM-integrated strain sensor in the skin-mounted tactile detection is demonstrated with high tolerance to unintended wrist movements.

A programmable and skin temperature-activated electromechanical synergistic dressing for effective wound healing.

Mechanical regulation and electric stimulation hold great promise in skin tissue engineering for manipulating wound healing. However, the complexity of equipment operation and stimulation implementation remains an ongoing challenge in clinical applications. Here, we propose a programmable and skin temperature-activated electromechanical synergistic wound dressing composed of a shape memory alloy-based mechanical metamaterial for wound contraction and an antibacterial electret thin film for electric field generation. This strategy is successfully demonstrated on rats to achieve effective wound healing in as short as 4 and 8 days for linear and circular wounds, respectively, with a statistically significant over 50% improvement in wound closure rate versus the blank control group. The optimally designed electromechanical synergistic stimulation could regulate the wound microenvironment to accelerate healing metabolism, promote wound closure, and inhibit infection. This work provided an effective wound healing strategy in the context of a programmable temperature-responsive, battery-free electromechanical synergistic biomedical device.

An Automatic Premature Ventricular Contraction Recognition System Based on Imbalanced Dataset and Pre-Trained Residual Network Using Transfer Learning on ECG Signal.

The development of automatic monitoring and diagnosis systems for cardiac patients over the internet has been facilitated by recent advancements in wearable sensor devices from electrocardiographs (ECGs), which need the use of patient-specific approaches. Premature ventricular contraction (PVC) is a common chronic cardiovascular disease that can cause conditions that are potentially fatal. Therefore, for the diagnosis of likely heart failure, precise PVC detection from ECGs is crucial. In the clinical settings, cardiologists typically employ long-term ECGs as a tool to identify PVCs, where a cardiologist must put in a lot of time and effort to appropriately assess the long-term ECGs which is time consuming and cumbersome. By addressing these issues, we have investigated a deep learning method with a pre-trained deep residual network, ResNet-18, to identify PVCs automatically using transfer learning mechanism. Herein, features are extracted by the inner layers of the network automatically compared to hand-crafted feature extraction methods. Transfer learning mechanism handles the difficulties of required large volume of training data for a deep model. The pre-trained model is evaluated on the Massachusetts Institute of Technology-Beth Israel Hospital (MIT-BIH) Arrhythmia and Institute of Cardiological Technics (INCART) datasets. First, we used the Pan-Tompkins algorithm to segment 44,103 normal and 6423 PVC beats, as well as 106,239 normal and 9987 PVC beats from the MIT-BIH Arrhythmia and IN-CART datasets, respectively. The pre-trained model employed the segmented beats as input after being converted into 2D (two-dimensional) images. The method is optimized with the using of weighted random samples, on-the-fly augmentation, Adam optimizer, and call back feature. The results from the proposed method demonstrate the satisfactory findings without the using of any complex pre-processing and feature extraction technique as well as design complexity of model. Using LOSOCV (leave one subject out cross-validation), the received accuracies on MIT-BIH and INCART are 99.93% and 99.77%, respectively, suppressing the state-of-the-art methods for PVC recognition on unseen data. This demonstrates the efficacy and generalizability of the proposed method on the imbalanced datasets. Due to the absence of device-specific (patient-specific) information at the evaluating stage on the target datasets in this study, the method might be used as a general approach to handle the situations in which ECG signals are obtained from different patients utilizing a variety of smart sensor devices.

Lattice Strain Relaxation and Grain Homogenization for Efficient Inverted MAPbI3 Perovskite Solar Cells.

The lattice strain of a perovskite film is vital to the controllable growth and charge transport in perovskite solar cells (PSCs). In this work, a lead chloride (PbCl2) assisted crystallization (LCAC) protocol is introduced for releasing the strain across the interface of a NiOx/perovskite, which induces a preferred (h00) crystal plane growth and grain homogenization. PSCs with LCAC show a facilitated charge extraction and suppressed nonradiative recombination. Thanks to the controlled film growth and strain-released interface, the inverted MAPbI3 (MA = methylammonium) PSC devices with LCAC deliver a power conversion efficiency (PCE) over 20% with a short-circuit current density (Jsc) of 23.60 mA cm-2, which is obviously higher than that of the control device with a PCE of 18.36% and a Jsc of 21.74 mA cm-2. Meanwhile, the LCAC devices maintain 80% of their initial efficiency after being exposed to an ambient atmosphere with a relative humidity of 40% over 1000 h in the dark.