All Irradiance-Applicable, Perovskite Solar Cells-Powered Flexible Self-Sustaining Sensor Nodes for Wireless Internet-of-Things

All Irradiance-Applicable, Perovskite Solar Cells-Powered Flexible Self-Sustaining Sensor Nodes for Wireless Internet-of-Things | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article All Irradiance-Applicable, Perovskite Solar Cells-Powered Flexible Self-Sustaining Sensor Nodes for Wireless Internet-of-Things Yantao Shi, Wenqi Han, Ruicheng Nie, Bing Yin, Jie Zhang, Sen Qiu, and 7 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5174154/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Currently, there are 17 billion IoT nodes, mostly powered by cables or batteries, leading to high maintenance costs and increased risk of data loss during power outages. Despite various energy harvesting technologies, the widespread deployment of self-sustaining IoT nodes is limited due to the lack of stable, continuous energy sources and limited power efficiency. We introduce an all-irradiance, 24-hour self-sustaining flexible node (SSN) with a perovskite solar cell module (FPSM) for steady power. The FPSM achieves over 30.54% power conversion efficiency (PCE) indoors, providing power in various lighting. The SSN, equipped with temperature and humidity sensors, uses a low-power Zigbee module for wireless data transfer. The FPSM-SSN reliably conducts 24-hour environmental monitoring indoors and achieves comprehensive three-dimensional data collection across "indoor-outdoor-aerial" environments. Additionally, it can also intelligently control household appliances based on temperature changes. The FPSM-SSN's robust self-sustaining capabilities demonstrate significant potential for IoT applications. Physical sciences/Energy science and technology/Energy harvesting/Devices for energy harvesting Physical sciences/Energy science and technology/Renewable energy/Solar energy/Photovoltaics/Solar cells Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction The Internet of Things (IoT) is rapidly evolving, enabling continuous spatial information detection across diverse environments through intelligent sensing and actuating nodes 1 – 9 . Currently, there are 17 billion IoT nodes powered by cables or batteries, with projections to reach 29 billion by 2030 10 . However, the widespread deployment of these nodes comes with costs related to line damage and battery replacement 6 , 11 , 12 . Additionally, the downtime between power depletion and battery replacement poses a risk of information loss, potentially compromising the reliability of information collection 13 – 15 . Traditional IoT nodes face challenges in meeting the demands for extensive coverage, massive connectivity, and real-time processing in IoT networks 16 , 17 . This limitation impedes the development of IoT nodes towards flexibility, integration, and portability 18 . To address the challenge of relying on batteries or cables as the primary power source for IoT nodes, employing energy harvesters to gather energy from the environment offers a viable solution, enabling the designing of self-powered IoT nodes 19 – 24 . The ideal energy harvesters must prioritize high energy conversion efficiency and ensure that the harvested energy is reliable, easily accessible, and independent of specific environmental conditions. Photovoltaic (PV) cells provide an efficient, stable, and reliable energy solution suitable for any location with light 25 – 28 . The concept of a photovoltaic-powered self-sustaining IoT (PV-SIoT) shows great potential for the future (Fig. 1 a). However, due to the variability of external environmental conditions (e.g. indoor, cloudy and rainy), there is currently a lack of targeted designs for PV-SIoT systems. Considering the diverse irradiance conditions in which PV-SIoT must operate, achieving high photovoltaic conversion efficiency (PCE) under low-irradiance conditions emerges as a pivotal requirement for IoT 27 , 29 – 31 . In various photovoltaic technologies, the silicon solar cell has a meager PCE of only 11.9% due to the bandgap mismatch between silicon (1.12 eV) and indoor PV (1.9-2.0 eV) 32 . The III-V materials demonstrate higher PCE (26.8% under 1000 lux illumination), but their prohibitive production costs hinder their widespread adoption in IoT 6 , 33 (Supplementary Table 2). Perovskite materials stand out due to their tunable bandgap, high absorption coefficient, and flexible fabrication, making them ideal for various irradiance conditions 27 , 34 – 36 . Compared to other PV technologies, perovskite solar cells (PSC) excel in low-light indoor environments, offering superior PCE 37 (Fig. 1 b). This makes PSC suitable for any irradiance environment, from natural to indoor light, serving as power sources for small IoT sensors and wireless transmission devices, enabling wireless-powered autonomous IoT node detection. Figure 1 c compares the energy generation by PSC under different irradiance intensities with the average power consumption of IoT communication protocols. The data shows that PSC can provide sufficient power to operate common IoT protocols under varying irradiance conditions 6 , 38 – 42 . Additionally, the flexibility of PSC enables their integration with flexible electronic systems, making them ideal for deployment in environments with complex structural demands. In this work, we design a self-sustaining node (SSN) powered by a flexible perovskite solar cell module (FPSM). Under indoor lighting (LED 2700K, 1000 lux), the FPSM achieves a PCE of 30.54% (P out : 81.76 µW·cm − 2 ). It can continuously power the SSN module in various irradiance environments ranging from dim indoor settings (100 lux) to outdoor conditions (10000 lux). The SSN module equipped with custom resistive sensors, detects temperatures and humidity. The communication frequency and power consumption of the SSN are adjusted based on light intensity changes using the Zigbee communication module, which enables ultra-low power operation and 24-hour three-dimensional environmental monitoring ("indoor-outdoor-aerial"). Additionally, FPSM-SSN can serve as a self-feedback control hub for smart homes, wirelessly transmitting signals to user interfaces and automatically controlling household appliances based on environment changes. Integrated design of the FPSM-SSN The FPSM-SSN features a compact and foldable design and can be assembled by folding with a total area of 24 cm² (Fig. 2 a and Supplementary Fig. 1). It comprises two main components: (I) FPSM energy supply module: This module includes three series-connected sub-cells, each with an area of 5 cm². The FPSM employs a p-i-n structure, consisting of flexible polyethylene terephthalate (PET) coated with indium tin oxide (ITO), nickel oxide (NiO X ), Cs 0.05 (FA 0.87 MA 0.15 ) 0.95 Pb(I 0.87 Br 0.13 ) 3 perovskite photoactive layer (Supplementary Fig. 2), C 60 , Bathocuproine (BCP), and Cu electrodes. The FPSM is encapsulated with Polyolefin Elastomer (POE) to prevent water intrusion. This module harvests and converts energy to power the entire system (Fig. 2 b and Supplementary Fig. 3). (II) SSN detection system: This system has a total area of 24 cm² and includes power management, information acquisition and processing, and wireless communication modules. The power management module comprises boost and buck converters, a capacitor module, and a maximum power point tracking (MPPT) module. The information acquisition and processing modules include a resistive sensor array, a microcontroller, and high-precision current sensors (Fig. 2 B, Supplementary Fig. 4 and Supplementary Table 3). For the communication module, we select the ZigBee communication module due to its small size, low power consumption, adjustable transmission power, and strong networked capabilities. Under illumination, the FPSM continuously generates electricity and supplies power to the SSN through the power management module. The SSN collects environmental information under various conditions and wirelessly transmits it to the user interface via the ZigBee Zigbee module. Design and characterization of FPSM with high energy harvesting efficiency Given the diverse irradiance conditions in which IoT nodes operate, their performance under low indoor light intensity is pivotal for achieving self-sustaining operation. Perovskite material with its high carrier transport efficiency, tunable bandgap, flexible fabrication, and high defect tolerance, is an optimal choice for various illuminated environments. These characteristics make FPSM ideal for realizing all irradiance-applicable self-sustaining IoT nodes and intelligent communication devices. Figure 2 c presents the Incident Photon-to-Current Efficiency (IPCE) of the Cs 0.05 (FA 0.87 MA 0.15 ) 0.95 Pb(I 0.87 Br 0.13 ) 3 FPSM device, alongside the spectra of the indoor light source used in this study (LED 2700K, 1000 lux) and the AM 1.5 spectrum. The LED has narrower emission spectrum more closely matches the IPCE of the FPSM compared to sunlight. Additionally, the UV-vis spectrum of the perovskite film reveals a distinct absorption peak at 800 nm (Supplementary Fig. 5), enabling the FPSM to effectively absorb and convert LED light within the 400–800 nm range. Consequently, the FPSM achieves an efficiency of 30.54% (Pout: 81.76 µW·cm − 2 ) under 1000 lux LED (267.7 µW·cm − 2 ) indoor lighting. Under dimmer indoor conditions of 500 lux and 100 lux, the FPSM's PCE is 29.53% (Pout: 35.36 µW·cm − 2 ) and 28.29% (Pout: 7.58 µW·cm − 2 ) respectively (Fig. 2 d, Supplementary Fig. 6, and Supplementary Table 4). Additionally, the FPSM achieves a PCE of 15.24% under AM 1.5 illumination (Supplementary Fig. 7), which is a considerable value for flexible large-area perovskite solar cell (Supplementary Table 5). FPSM maintains high PCE across various irradiance intensities, allowing it to effectively adapt to diverse lighting environments, from dim indoor settings (100 lux) to specialized laboratory conditions (2000 lux) and outdoor environments (10000 lux) (Fig. 2 e, Supplementary Figs. 8 and 9). The stable and efficient power output of the FPSM under these conditions ensures that IoT devices can operate reliably across different environmental scenarios. Design of SSN with autonomous power regulation capability Given the need for FPSM to harvest energy under varying irradiance intensities, fluctuations in external light affect its charging state (manifested as voltage changes), which impacts the energy utilization efficiency of the FPSM-SSN system. To address this issue, we have designed the SSN system with targeted features. First, we incorporated an internal MPPT function, which can monitor FPSM's open-circuit voltage every 16 s and set 80% of this voltage as the maximum power point, ensuring optimal energy input (Supplementary Fig. 10). In addition, we also develop a "collect-store-utilize" energy conversion framework. In irradiance environments, such as during the day, the SSN's internal boost converter elevates “surplus output voltage” of FPSM to 3.8 V, storing excess energy in the capacitor module for night-time use. When energy-intensive modules like information processing are active, the SSN's built-in buck converter stabilizes the output voltage of FPSM or the capacitor module at 1.8 V (Supplementary Fig. 11). The boost and buck converters amplify signal voltage with minimal power loss (~ 7%) (Supplementary Fig. 12). For information acquisition and processing, the SSN uses a custom embedded successive approximation analog-to-digital converter to capture measurement information, ensuring each module operates in the lowest power mode (Fig. 2 f). We select the Zigbee communication module as the information transmission unit due to its networked connectivity capabilities, making it suitable for applications such as smart homes and urban monitoring. Combining the Zigbee module with FPSM enables self-sustaining networked information collection in diverse lighting environments. This synergy offers extensive application prospects. To minimize SSN system power consumption, the Zigbee module is programmed to operate in bursts, periodically waking from deep sleep mode for approximately 0.15 s to transmit information to user interfaces. In deep sleep mode, the total current of SSN during operation (at a working voltage of 1.8 V) is approximately 200 µA. When the Zigbee module transmits signals, the total current increases to about 300 µA (Supplementary Fig. 13). Additionally, to further reduce power consumption, we incorporate an adjustable communication frequency feature in the Zigbee module (ranging from once per second to once per 60 seconds). This feature allows the Zigbee module to operate at different communication frequencies under varying light intensities, maximizing energy utilization (Fig. 2 g). Our design allows a 16cm² FPSM to sustain SSN operation for an entire day with just 10 hours of exposure under low indoor light (1000 lux). In outdoor environments with stronger light, the required FPSM size can be further reduced. Temperature/humidity monitoring characterizations of the FPSM-SSN The FPSM-SSN shows significant potential for applications in smart cities and smart homes, especially in environmental monitoring. In this study, we develop two resistive sensors based on PEDOT: PSS (a PEDOT: PSS@ carbon nanotube (CNT) temperature sensor and a PEDOT: PSS@ Ti 3 C 2 T X humidity sensor). The PEDOT: PSS materials can be seamlessly integrated with the SSN module via inkjet printing technology (Fig. 3 a). Given the substantial impact of humidity on the resistance of PEDOT materials, which could interfere with temperature response, we sealed the PEDOT: PSS@ CNT temperature sensor with PET double-sided tape in this study to ensure the accuracy of the test results (Supplementary Fig. 14). The sensing material based on PEDOT: PSS is a resistive sensing material that can change its resistance depending on external environmental changes (Supplementary Fig. 15). Additionally, the FPSM-SSN can achieve multifunctional information monitoring by replacing the sensing materials. We evaluate the information collection capabilities of the FPSM-SSN in an indoor environment with LED illumination at 1000 lux. As shown in Fig. 3 b and 3 c, the PEDOT: PSS@ CNT temperature sensor exhibits stable and sensitive temperature responses within the range of 25℃ to 41℃ (Fig. 3 b). The resistance decreases with increasing temperature, with a sensitivity of -2.543%℃ −1 . Similarly, within the range of 20–60% RH (Fig. 3 c), the PEDOT: PSS@ Ti 3 C 2 T X humidity sensor shows stable and sensitive humidity responses with a sensitivity of 0.616%RH − 1 (Fig. 3 d). We compare the data collected at different transmission frequencies to ensure the accuracy of the SSN system under different information collection conditions. As shown in Fig. 3 e, the SSN measurements are consistent across different transmission frequencies. Considering the operation of FPSM-SSN at night without light, after fully charging the SSN device, we maintain low-power information collection at a transmission frequency of once every 30 s, and monitor the voltage values of the two segments of the capacitor module in real time, as shown in Fig. 3 f. The FPSM-SSN can achieve 13 h long time night self-sustaining detection. This further demonstrates the stable and accurate self-sustaining information collection capability of the FPSM-SSN system. Self-sustaining detection of FPSM-SSN under indoor lighting To validate the self-sustaining detection capability of FPSM-SSN under indoor lighting, we install the integrated temperature and humidity sensor nodes on the wall of the Perovskite Laboratory at Dalian University of Technology (38.87° N latitude). This specific location is chosen because the lab's windows face northwest (346°), resulting in minimal direct sunlight exposure. The natural light received is primarily diffuse radiation and reflections from nearby objects (Fig. 3 g). Under these conditions, the FPSM primarily absorbs energy emitted by LED lights. By adjusting the transmission frequency, the FPSM-SSN achieves 24-hour environmental monitoring under varying irradiance conditions from day to night. Observation shows a slight increase in indoor temperature and a decrease in humidity from 9:00 AM to 7:00 PM, primarily due to daytime sunlight. During the night, from 7:00 PM to 5:00 AM, the temperature slightly decreased, and humidity slightly increased, although overall changes remained stable. From 6:00 AM to 9:00 AM, temperature fluctuation was more pronounced, likely due to the activities of lab personnel, while humidity change was less noticeable (Fig. 3 h). These results are consistent with those from a commercial temperature-humidity detector. These findings demonstrate that the FPSM-SSN can fully meet the long-term environment monitoring need even under low-light conditions. Application of FPSM-SSN in outdoor environments The biggest challenge facing IoT in practical application is power supply. When setting up a large number of sensors, the need for wiring limits the placement of devices 45 , 46 . FPSM, with its ability to adapt to various irradiance environments and provide high energy output under different conditions, can be used in any power supply scenario. The SSN device is equipped with the Zigbee communication module, which offers the advantage of networked connectivity and wireless signal transmission. Combining these two technologies, the FPSM-SSN can fully address the wiring challenge and enable networked wireless detection in any setting. We deploy the FPSM-SSN indoors, outdoors, and on a drone from 12:00–13:00 noon to achieve three-dimensional networked detection of our home environment. Node A is placed on top of a drone and conducted information collection hovering three meters above the ground. Node B is positioned outdoors at Dalian University of Technology (latitude 38.87°N) for information collection. According to reports, the local temperature is approximately 25–30°C, and the humidity is around 50–70% RH. Node C is situated inside the Perovskite Laboratory at Dalian University of Technology, where environmental conditions are controlled by a dehumidifier and air conditioner, maintaining a temperature of 23–25°C and humidity of 30–35% RH (Fig. 4 a). The results indicate that the FPSM-SSN has stable and accurate networked detection capabilities. The outdoor temperature is approximately 5°C higher than the indoor temperature, and the humidity is about 25% RH higher. These findings are consistent with the standard temperature and humidity results reported for the local area. Additionally, we conduct long-term (24h) networked detection of indoor and outdoor environments to further verify its long-term networked detection capabilities (Supplementary Figs. 16 and 17). From the test results, the outdoor environment measurements closely matched the local official weather reports, with a peak temperature of 30°C occurring at 16:00 and humidity fluctuating between 55–70% RH. Compared to the outdoor environment, the indoor environment remained relatively stable due to the operation of dehumidifiers and air conditioners, with temperature fluctuations between 23–25°C. At night, due to the air conditioner being turned off, the temperature slightly increased. Humidity fluctuated between 30–40% RH and showed an upward trend at night due to the dehumidifier being turned off (Fig. 4 b and c). The FPSM-SSN demonstrates strong self-sustaining networked environment monitoring capability, showing significant potential in the development of self-sustaining IoT nodes. Evaluation of FPSM-SSN as smart home control center In recent years, with the advancement of artificial intelligence technology, self-sustaining IoT nodes with intelligent sensing and feedback capabilities have shown tremendous future potential 47 , 48 . To achieve this functionality, we integrate self-feedback design into the FPSM-SSN (Supplementary Fig. 18). The FPSM-SSN can detect changes in environmental temperature and wirelessly transmit the collected information to the control unit of a digital switch, enabling intelligent control of household appliances. In this study, we paired the FPSM-SSN with a digital switch controlling an electric fan (Fig. 4 d and Supplementary Fig. 19). When the detected temperature exceeded 35°C, the FPSM-SSN transmitted the information to the control unit, triggering the fan to turn on. When the temperature dropped below 25°C, the system automatically turned off the fan, achieving smart home control (Fig. 4 e and Supplementary Video 1). The intelligent sensing and feedback capabilities of the FPSM-SSN demonstrate its powerful potential for future applications. Conclusion Here, we present a flexible, fully integrated, all irradiance-applicable, self-sustaining IoT node powered by a FPSM, capable of real-time, continuous information collection under various lighting conditions (from intense outdoor sunlight to dim indoor LED lighting). The FPSM is ideally suited for powering IoT nodes in urban and household environments, achieving an efficiency of 30.54% under indoor lighting condition and maintaining high PCE and power output across diverse lighting conditions. This addresses the issue of insufficient energy harvesting in self-sustaining IoT devices. We pair the FPSM with a low-power SSN module. By adjusting the Zigbee communication frequency of the SSN, we achieve power consumption regulation, enabling 24-hour indoor temperature and humidity detection. The networked capability of the Zigbee module allows the FPSM-SSN to perform networked monitoring in various environments. With its wireless transmission capability, the FPSM-SSN system smartly senses temperature changes and enables intelligent home control. Given its robust self-sustaining detection capabilities under various irradiance conditions, the FPSM-SSN shows great potential in smart cities, smart homes, automation, and human-machine interaction. Method Materials All the materials are used as received from commercial sources, including PbI 2 (> 99%, TCI, Japan), HC(NH 2 ) 2 I (FAI, 99.9%, Advanced Election Technology Co. Ltd, China), polydimethylsiloxane (PDMS, Sylgard 184 Silicone Elastomer, Dow Corning). Cesium iodide (CsI, 99.9%), CH 3 NH 3 I (MAI, ≥ 99.5%), CH 3 NH 3 Cl (MACl, ≥ 99.5%), PEDOT: PSS (Heraeus CLEVIOSTM PH1000), dimethylformamide (DMF, 99.8%), C 60 , dimethylsulfoxide (DMSO, 99.9%) and chlorobenzene (CB, 99.8%), Carbon nanotube (CNT), are all purchased from Sigma Aldrich (USA). Ti 3 C 2 T x is purchased from Weixi technology (China). NiOx is purchased from Furui Technology (China). C 60 is purchased from Tanfeng Technology (China). BCP is purchased from Xi’an Yuri Solar (China). Glass substrates are purchased from Suzhou Shangyang Solar Technology Co. Ltd (China). The PET/ITO substrates (∼12​ µm thickness) are purchased from Shanghai Yiwei Mechanical & Electrical Hardware Co. Ltd (China). Carbon Double-sided tape (50 ohm/sq/inch) is purchased from RiXin (Japan). Electronic components are purchased from electronic technology company (China). FPSM fabrication and characterization Flexible Substrate Etching and Cleaning Process: Cover the PET/ITO with a layer of PTFE tape. Place it in a chamber filled with HCI vapor to etch the uncovered areas, forming 200 µm wide P 1 lines. Sequentially clean with deionized water, absolute ethanol, and isopropanol using ultrasound for 30 min. Follow this with UV ozone treatment for 15 min. PDMS with curing agent in a 10:1 ratio is spin-coat on a clean glass substrate at 2000 rpm for 50 s. Anneal at 100°C for 60 min. Attach PET/ITO to the glass/PDMS substrate, then transfer to a vacuum chamber to remove air between PEN and PDMS. Preparation of NiOx Hole Transport Layer (HTL): Sputter the NiOx hole transport layer at 50W power under vacuum conditions below 9×10 − 4 Pa for 30 min with magnetron sputter. Preparation of Perovskite Absorber Layer: Add the Cs 0.05 (FA 0.87 MA 0.15 ) 0.95 Pb(I 0.87 Br 0.13 ) 3 perovskite precursor solution to a blade coating device. Maintain a gap of approximately 150 µm between the substrate and blade, and coat at a speed of 3.5 mm/s in ambient air with 30%-57% RH. After coating, immediately transfer the wetted substrate to a vacuum chamber, reduce the pressure to less than 1 bar within 10 s, and maintain for 2 min. Transfer to ambient air and anneal the substrate at 150°C for 10 min to complete the conversion to the black phase. Preparation of C 60 Electron Transport Layer (ETL): Place the perovskite film in a vacuum deposition chamber. Under vacuum conditions below 9×10 − 4 Pa, evaporate C 60 at a rate of 0.1 Å/s to a thickness of 30 Å. In the same vacuum (9×10 − 4 Pa) deposition chamber, evaporate BCP at a rate of 0.1 Å/s to a thickness of 10 Å. Preparation of Metal Counter: Use a 355 nm picosecond laser scribing machine (MM2500, OpTeksystem, Inc., USA) with a laser power of 12 W and a pulse repetition rate of 100 kHz. Maintain a distance of 30 µm between P 1 and P 2 lines. Place the multilayer films prepared in the previous steps into a mask, then place them in a vacuum deposition chamber. Under vacuum conditions below 9×10 − 4 Pa, evaporate the Cu electrode at a rate of 0.1 Å/s to a thickness of 600 Å to complete the device fabrication. Use a 355 nm picosecond laser scribing machine (MM2500, OpTeksystem, Inc., USA) with a laser power of 0.78 W and a pulse repetition rate of 80 kHz to remove an 80 µm P3 gap. Encapsulation of flexible perovskite solar modules: Transfer the FPSM to the center of the hot press machine. Place a PET film (3 cm × 4 cm) in the center position on top of the FPSM. Set the hot press machine to a temperature of 120°C and a pressure of -90 Pa. After hot pressing for 2 min, the film encapsulation will be completed. Characterization: The microstructures of the thin films are observed using a field-emission SEM (JSM-7610F Plus, Hitachi, Japan). XRD is performed using a high-resolution diffractometer (SmartLab 9kw, Rigaku, Japan) with CuKa radiation. UV-vis absorption spectra of the perovskite films are obtained using a spectrophotometer (U-4150, Hitachi, Japan). The IPCE spectra were obtained using an EnliTech (Taiwan) QE-R measurement system. The J-V characteristics of FPSM are measured by a source meter (2450, Keithley, USA) at the scan speed of 100 mV s − 1 under AM 1.5G 1-sun illumination (100 mW cm − 2 ) generates by a solar simulator (Sol3A Class AAA, Oriel, Newport, USA). The J-V curves under indoor light are tested using Osram LED lamps (KW CSLPM2.CC, Germany). The LED lamps are calibrated for different light intensities using a DELIXI photometer, and the tests are conducted after calibration. For more detailed test methods, see Supplementary Note 1. FPSM's MPPT detection was performed using a source meter (2450, Keithley, USA). SSN system fabrication and characterization The SSN system is composed of four main modules: information collection, wireless communication, power management, and information processing. The power management module consists of an energy harvesting PMIC (BQ25570, Texas Instruments). The PMIC utilizes maximum power point tracking to effectively boost the solar cell output to 3.8V for charging and stores energy in a 70F capacitor. The PMIC's threshold control unit ensures that the capacitor powers the rest of the system while maintaining the capacitor voltage within a threshold range of 2-3V. The BQ25570's integrates buck converter regulates the capacitor voltage to a stable 1.8V, supplying power to the information processing, wireless communication, and information collection modules. The information collection module uses a high-precision current detector (INA186A5, Texas Instruments) to feed the collects current information back to the MCU for processing. Information processing is performed by a microcontroller (STM32L431, STMicroelectronics), which communicates with the wireless communication module via a serial port. Wireless communication is handled by a compact programmable system-on-chip module and XBee module (XBRR-24Z8UM, DIGI), which integrates an MCU and Zigbee. In this work, the SSN devices are all powered by FPSM. The power consumption of the SSN is characterized using a Keithley 2450 system (Keithley, USA). The Keithley test leads are connected to the reserved interface of the SSN, and a voltage of 1.8V is applied at both ends for testing. Assembly and characterization of the FPSM-SSN The FPSM-SSN is assembled using a combination of conductive adhesive and hot pressing. Initially, the conductive adhesive is applied to the positive and negative electrodes of the FPSM to ensure effective electron and hole extraction. The remaining adhesive is applied to the POE surface at a 90° angle. Next, the upper conductive adhesive on the POE is aligned with the reserved metal electrodes (1 cm × 4 cm) of the SSN. The entire assembly is then hot-pressed at 120°C and 0.4 MPa for 60 seconds using a hot press machine. Finally, the FPSM-SSN is folded along the designated lines, completing the assembly process. The discharging curves of the capacitor are collected using an electrochemical workstation (CHI660E). The discharge of the capacitor module is tested in an environment without light. Resistive sensors fabrication and characterization The resistive temperature sensor is fabricated by spray-coating a mixed solution of PEDOT: PSS and CNT onto the temperature sensing region. Add 30 mg of CNT and 0.5 mL of sodium polystyrene sulfonate to 10 mL of deionized water. Ultrasonic the mixture until it is uniform and free of noticeable precipitates. Combine the CNT-PSS solution with 1.3 wt% PEDOT: PSS at a ratio of 1:7. Load the prepared solution into a spray gun. Spray the solution onto the SSN temperature sensing region for 15 s. Cure the coated sensor on a hot plate at 120°C for 10 min. The resistive humidity sensor is fabricated using PEDOT: PSS and Ti 3 C 2 T X as the sensing materials. The preparation steps are as follows: Disperse 1 g of Ti 3 C 2 T X black powder into 10 mL of deionized water. Stir the mixture mechanically at room temperature for 15 min. Combine the Ti 3 C 2 Tx suspension with 1.3 wt% PEDOT: PSS at a ratio of 1:2. Ultrasonic the mixed solution for 15 min to obtain a liquid-phase PEDOT: PSS and Ti 3 C 2 T X nanocomposite. Load the prepared nanocomposite solution into a spray gun. Spray the solution onto the SSN humidity sensing region for 5 s. Cure the coated sensor on a hot plate at 70°C for 10 min. Characterization: In this work, the response of the sensing material under different temperatures and humidity is tested based on the FPSM-SSN system unless otherwise specified. The temperature response is controlled by the thermostat (LC-HN-25S, Chian), the humidity response is controlled by the humidity control box (Memmert, Germany), and the information collection is completed by receiving resistance signals from the computer. I-V curve tests is performed with the Keithley 2450 system (2450, Keithley, USA) Evaluation of FPSM-SSN Networked Detection The FPSM-SSN networked detection is validated at the Perovskite Solar Cell Laboratory Center of Dalian University of Technology. The FPSM-SSN devices are attached to the test sites using double-sided or transparent tape. During the test, the field temperature is tested in real time and calibrated to ensure accurate test results. To compare the experimental results, we control the indoor environment of the nodes using air conditioners and dehumidifiers, maintaining an indoor temperature of 24–27°C and humidity of 30–40% RH. This contrast sharply with the outdoor conditions of 20–31°C and humidity of 50–70% RH. The drone-carried experiment is conducted at 12:00 AM, with the device attached to the drone for measurements. Evaluating FPSM-SSN as a control hub for smart devices For smart home control, the FPSM-SSN system is connected to digital switches linked with various smart household appliances. The system is programmed to automatically activate the switch when the detects temperature exceeded 35°C (2000KΩ), with the FPSM-SSN wirelessly transmitting the signal to the smart switch, thereby enabling intelligent device control. In this experiment, we manipulate the FPSM-SSN's detection temperature using a hot plate and ice packs. The FPSM-SSN transmits sensor information wirelessly to the user interface, which then controls the home devices. When the temperature is raised above 35°C, the smart switch receives the signal from the FPSM-SSN and activates the connected device. Conversely, when the temperature fell below 35°C, the switch is turned off. This setup effectively demonstrates the FPSM-SSN's capability to enhance smart home automation through responsive environmental monitoring and control. Declarations Competing interests The authors declare no competing interests. Author contributions Y.S., W.H. and B.Y. proposed concepts and designed experiments. W.H. and R.N. designed FPSM and SSN samples, and conducted data analysis. J.Z. and S.Q. contributed to the verification of wireless transmission and networking connectivity features. J.Z., M.P. and Y.Q. regulated the preparation and packaging process of FPSM. Acknowledgements The work was supported by the National Natural Science Foundation of China (52272193), the National Natural Science Foundation of China (No.22304020), and the Fundamental Research Funds for the Central Universities (DUT22LAB602). References Arias R, Lueth KL, Rastogi A (2018) The effect of the Internet of Things on sustainability. 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Joule 3:1415–1426 Pecunia V, Occhipinti LG, Hoye RLZ (2021) Emerging indoor photovoltaic technologies for sustainable Internet of Things. Adv Energy Mater. 11 Pržulj N, Malod-Dognin N (2016) Network analytics in the age of big data. Science 353:123–124 Haight R, Haensch W, Friedman D (2016) Solar-powering the Internet of Things. Science 353:124–125 Vailshery LS (2024) Number of Internet of Things (IoT) connected devices worldwide from 2019 to 2030, by vertical. Statista https://www.statista.com/statistics/1194682/iot-connected-devices-vertically/ Powell DM et al (2015) The capital intensity of photovoltaics manufacturing: Barrier to scale and opportunity for innovation. Energ Environ Sci 8:3395–3408 Ma D et al (2020) Sensing, computing, and communications for energy harvesting IoTs: A survey. IEE Commun Surv Tut 22:1222–1250 Butun I, Osterberg P, Song H (2020) Security of the Internet of Things: Vulnerabilities, attacks, and countermeasures. 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Adv Energy Mater 10:2002782 Yu H, Li N, Zhao N (2020) How far are we from achieving self-powered flexible health monitoring systems: An energy perspective. Adv Energy Mater 11:2002646 Zhao L et al (2024) Triboelectric gait sensing analysis system for self-powered IoT‐based human motion monitoring. InfoMat 6:e12520 Yu Y et al (2020) Biofuel-powered soft electronic skin with multiplexed and wireless sensing for human-machine interfaces. Sci Robot 5:eaaz7946 Li C et al (2019) Flexible perovskite solar cell-driven photo-rechargeable lithium-ion capacitor for self-powered wearable strain sensors. Nano Energy 60:247–256 Zhi C et al (2024) Emerging trends of nanofibrous piezoelectric and triboelectric applications: Mechanisms, electroactive materials, and designed architectures. Adv Mater 36:2401264 Hao D et al (2022) Solar energy harvesting technologies for PV self-powered applications: A comprehensive review. Renewable Energy 188:678–697 Hashemi SA, Ramakrishna S, Aberle AG (2020) Recent progress in flexible–wearable solar cells for self-powered electronic devices. Energ Environ Sci 13:685–743 Polyzoidis C, Rogdakis K, Kymakis E (2021) Indoor perovskite photovoltaics for the Internet of Things—challenges and opportunities toward market uptake. Adv Energy Mater 11:2101854 Olzhabay Y, Ng A, Ukaegbu IA (2021) Perovskite PV energy farvesting system for uninterrupted IoT device applications. Energies 14:7946 Wu Q et al (2022) High-performance organic photovoltaic modules using eco-friendly solvents for various indoor application scenarios. Joule 6:2138–2151 Li M, Igbari F, Wang ZK, Liao LS (2020) Indoor thin-film photovoltaics: Progress and challenges. Adv Energy Mater 10:2000641 Huang J et al (2022) Tandem self-powered flexible electrochromic energy supplier for sustainable all‐day operations. Adv Energy Mater 12:2201042 Agbo SN, Merdzhanova T, Rau U, Astakhov O (2017) Illumination intensity and spectrum-dependent performance of thin-film silicon single and multijunction solar cells. Sol Energ Mat Sol C 159:427–434 Shore A, Roller J, Bergeson J, Hamadani BH (2021) Indoor light energy harvesting for battery-powered sensors using small photovoltaic modules. Energy Sci Eng 9:2036–2043 Hailegnaw B et al (2024) Flexible quasi-2D perovskite solar cells with high specific power and improved stability for energy-autonomous drones. Nat Energy 9:677–690 Wang Z et al (2024) Al 2 O 3 nanoparticles as surface modifier enables deposition of high quality perovskite films for ultra-flexible photovoltaicss. Adv Powder Mater 3:100142 Zhu X et al (2023) Perspectives for the conversion of perovskite indoor photovoltaics into IoT reality. Nanoscale 15:5167–5180 Ma Q et al (2024) One-step dual-additive passivated wide-bandgap perovskites to realize 44.72%-efficient indoor photovoltaics. Energ Environ Sci 17:1637–1644 Silva JC et al (2017) LoRaWAN — A low power WAN protocol for Internet of Things: A review and opportunities. In: 2017 2nd International Multidisciplinary Conference on Computer and Energy Scienc e (SpliTech) Schuß M, Boano CA, Weber M (2017) & Römer K. A competition to push the dependability of low-power wireless protocols to the edge. In: Proceedings of the International Conference on Embedded Wireless Systems and Networks. Junction Publishing (2017) Jeon KE, She J, Soonsawad P, Ng PC (2018) BLE beacons for Internet of Things applications: Survey, challenges, and opportunities. IEEE Internet Things J 5:811–828 Raza U, Kulkarni P, Sooriyabandara M (2017) Low power wide area networks: An overview. lEEE Commun Surv Tutorials 19:855–873 Gungor VC, Hancke GP (2009) Industrial wireless sensor networks: Challenges, design principles, and technical approaches. IEEE T Ind Electron 56:4258–4265 Kim SH, Chong PK, Kim T (2017) Performance study of routing protocols in ZigBee wireless mesh networks. Wirel Pers Commun 95:1829–1853 Uradzinski M, Guo H, Liu X, Yu M (2017) Advanced indoor positioning using Zigbee wireless technology. Wirel Pers Commun 97:6509–6518 Ju Q, Zhang Y (2018) Predictive power management for internet of battery-less things. IEEE T Power Electc 33:299–312 Xia Q et al (2023) All-solid-state thin film lithium/lithium-ion microbatteries for powering the Internet of Things. Adv Mater 35:e2200538 Cao R et al (2018) Screen-printed washable electronic textiles as self-powered touch/gesture tribo-sensors for intelligent human-machine interaction. ACS Nano 12:5190–5196 Chirila R, Dahiya AS, Schyns P, Dahiya R (2024) Self-powered multimodal sensing using energy‐generating solar skin for robotics and smart wearables. Adv Intell Syst 2300824 Additional Declarations There is NO Competing Interest. Supplementary Files FPSMSSN.mp4 Demonstration of FPSM-SSN in smart home control FPSMSSNSI.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5174154","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":369229731,"identity":"18719a87-7ab1-4a19-840d-8ade66db7c4d","order_by":0,"name":"Yantao 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Technology","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Lida","middleName":"","lastName":"Liu","suffix":""}],"badges":[],"createdAt":"2024-09-29 09:30:08","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5174154/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5174154/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":67315602,"identity":"287881bc-cc04-4946-8b46-cedfcb3aa741","added_by":"auto","created_at":"2024-10-23 14:47:26","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":343779,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSelf-Sustaining IoT Framework Powered by Photovoltaics.\u003c/strong\u003e \u003cstrong\u003ea\u003c/strong\u003e, A description of a photovoltaic-powered self-sustaining IoT node: Powered by a large-area flexible perovskite module, this node enables networked information monitoring in both indoor and outdoor lighting conditions. Information is wirelessly transmitting to a mobile user interface via the Zigbee communication module\u003csup\u003e43, 44\u003c/sup\u003e. \u003cstrong\u003eb\u003c/strong\u003e, Indoor PCE of the representative works of crystalline silicon (c-Si), amorphous silicon solar cell (a-Si), dye-sensitized solar cell (DSSC), organic solar cell (OSC), III-V solar cell (GaAs and GaInP) and PSC. \u003cstrong\u003ec\u003c/strong\u003e, Comparison between the average power consumption of wireless protocols and the average power output of PSC.\u003c/p\u003e","description":"","filename":"image1.png","url":"https://assets-eu.researchsquare.com/files/rs-5174154/v1/d0e7ae716376ee60097c9ef7.png"},{"id":67317238,"identity":"ef1df7ab-25a6-4e91-a0e8-70cbc999f37e","added_by":"auto","created_at":"2024-10-23 15:03:25","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":398907,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe energy conversion architecture of the FPSM-SSN.\u003c/strong\u003e \u003cstrong\u003ea\u003c/strong\u003e, The physical diagram of the FPSM-SSN demonstrates efficient energy harvesting from the environment by the FPSM, with wireless information transmission to the user interface via the Zigbee module. \u003cstrong\u003eb\u003c/strong\u003e, The schematic diagram of the FPSM-SSN system includes the FPSM energy supply module, sensor array, boost and buck converters, capacitor module, and programmable system-on-chip module. \u003cstrong\u003ec\u003c/strong\u003e, Calibration of the IPCE spectrum of the FPSM and the emission spectrum of the LED light source (2700K, 1000 lux). \u003cstrong\u003ed\u003c/strong\u003e, The \u003cem\u003eJ-V\u003c/em\u003e curve of the FPSM under LED light source (2700K, 1000 lux). \u003cstrong\u003ee\u003c/strong\u003e, Power output density of PSC as a function of illuminance. \u003cstrong\u003ef\u003c/strong\u003e, Operation flow of the energy control and information-transmission processes. \u003cstrong\u003eg\u003c/strong\u003e, Power output of the FPSM at different light intensities and power consumption of the SSN at different transmission frequencies.\u003c/p\u003e","description":"","filename":"image2.png","url":"https://assets-eu.researchsquare.com/files/rs-5174154/v1/16bbe9fafd61e7bca046602e.png"},{"id":67315598,"identity":"ad8d75c8-31ca-47aa-ae47-703f017efe00","added_by":"auto","created_at":"2024-10-23 14:47:25","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":429402,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eLong-term Environment Monitoring Based on FPSM-SSN.\u003c/strong\u003e \u003cstrong\u003ea\u003c/strong\u003e, Resistive Sensor Arrays for Temperature and Humidity Detection. \u003cstrong\u003eb\u003c/strong\u003e,\u003cstrong\u003e c\u003c/strong\u003e, Response of temperature and humidity sensors. Variation in △R/R\u003csub\u003e0\u003c/sub\u003e for the temperature sensor (\u003cstrong\u003eb\u003c/strong\u003e) and humidity sensor (\u003cstrong\u003ec\u003c/strong\u003e). \u003cstrong\u003ed\u003c/strong\u003e, Calibration plots corresponding to the temperature and humidity sensors. \u003cstrong\u003ee\u003c/strong\u003e, Comparison of signal collection at different transmission frequencies.\u003cstrong\u003e f\u003c/strong\u003e, Real-time voltage of the capacitor module when powers by the capacitor (top) and the collects signal (bottom), with signal collection at 30 s/intervals. \u003cstrong\u003eg\u003c/strong\u003e, FPSM-SSN real-time monitoring photo. \u003cstrong\u003eh\u003c/strong\u003e, The FPSM-SSN conducts round-the-clock information monitoring under various lighting conditions.\u003c/p\u003e","description":"","filename":"image3.png","url":"https://assets-eu.researchsquare.com/files/rs-5174154/v1/a5383963470edadb98bbe752.png"},{"id":67315601,"identity":"a3d7d18a-1217-4ff1-9808-f247a03b39f1","added_by":"auto","created_at":"2024-10-23 14:47:25","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":655743,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eEvaluation of the FPSM-SSN System for Long-Term Networked Monitoring.\u003c/strong\u003e \u003cstrong\u003ea\u003c/strong\u003e, Networked detection analysis of the FPSM-SSN system. The left image shows the networked detection locations, corresponding to the sky, outdoors, and indoors. The middle image displays the information receiving terminal, and the right image compares the networked information collection results. \u003cstrong\u003eb\u003c/strong\u003e, \u003cstrong\u003ec\u003c/strong\u003e, 24-hour cross-environment detection results of the FPSM-SSN system at different locations. (\u003cstrong\u003eb\u003c/strong\u003e) Temperature networked detection information. (\u003cstrong\u003ec\u003c/strong\u003e) Humidity networked detection information. \u003cstrong\u003ed\u003c/strong\u003e, Latency image of the self-feedback intelligent home control function based on FPSM-SSN. \u003cstrong\u003ee\u003c/strong\u003e, Real-time temperature tracking of the intelligent home control based on FPSM-SSN.\u003c/p\u003e","description":"","filename":"image4.png","url":"https://assets-eu.researchsquare.com/files/rs-5174154/v1/2be73b08fb7d736402bc2092.png"},{"id":68664458,"identity":"a9970456-87e6-4b17-a09d-755a9ad06384","added_by":"auto","created_at":"2024-11-10 17:58:47","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2549990,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5174154/v1/0b7ed958-e58c-4eeb-a151-17bc59c5c628.pdf"},{"id":67316862,"identity":"beff40b9-e6e5-49c3-b19f-cf9bc92d23dc","added_by":"auto","created_at":"2024-10-23 14:55:26","extension":"mp4","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":4028176,"visible":true,"origin":"","legend":"Demonstration of FPSM-SSN in smart home control","description":"","filename":"FPSMSSN.mp4","url":"https://assets-eu.researchsquare.com/files/rs-5174154/v1/12baf37be3aa1993338ceb43.mp4"},{"id":67315603,"identity":"a4d15d16-496e-4aa0-9f26-e3fd6a6dc9da","added_by":"auto","created_at":"2024-10-23 14:47:26","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":5639105,"visible":true,"origin":"","legend":"","description":"","filename":"FPSMSSNSI.docx","url":"https://assets-eu.researchsquare.com/files/rs-5174154/v1/23a51daa9c647075c176e8e4.docx"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e Competing Interest.","formattedTitle":"All Irradiance-Applicable, Perovskite Solar Cells-Powered Flexible Self-Sustaining Sensor Nodes for Wireless Internet-of-Things","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe Internet of Things (IoT) is rapidly evolving, enabling continuous spatial information detection across diverse environments through intelligent sensing and actuating nodes\u003csup\u003e\u003cspan additionalcitationids=\"CR2 CR3 CR4 CR5 CR6 CR7 CR8\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. Currently, there are 17\u0026nbsp;billion IoT nodes powered by cables or batteries, with projections to reach 29\u0026nbsp;billion by 2030\u003csup\u003e10\u003c/sup\u003e. However, the widespread deployment of these nodes comes with costs related to line damage and battery replacement\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. Additionally, the downtime between power depletion and battery replacement poses a risk of information loss, potentially compromising the reliability of information collection\u003csup\u003e\u003cspan additionalcitationids=\"CR14\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. Traditional IoT nodes face challenges in meeting the demands for extensive coverage, massive connectivity, and real-time processing in IoT networks\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. This limitation impedes the development of IoT nodes towards flexibility, integration, and portability\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eTo address the challenge of relying on batteries or cables as the primary power source for IoT nodes, employing energy harvesters to gather energy from the environment offers a viable solution, enabling the designing of self-powered IoT nodes\u003csup\u003e\u003cspan additionalcitationids=\"CR20 CR21 CR22 CR23\" citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e. The ideal energy harvesters must prioritize high energy conversion efficiency and ensure that the harvested energy is reliable, easily accessible, and independent of specific environmental conditions. Photovoltaic (PV) cells provide an efficient, stable, and reliable energy solution suitable for any location with light\u003csup\u003e\u003cspan additionalcitationids=\"CR26 CR27\" citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. The concept of a photovoltaic-powered self-sustaining IoT (PV-SIoT) shows great potential for the future (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea). However, due to the variability of external environmental conditions (e.g. indoor, cloudy and rainy), there is currently a lack of targeted designs for PV-SIoT systems.\u003c/p\u003e \u003cp\u003eConsidering the diverse irradiance conditions in which PV-SIoT must operate, achieving high photovoltaic conversion efficiency (PCE) under low-irradiance conditions emerges as a pivotal requirement for IoT\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan additionalcitationids=\"CR30\" citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e. In various photovoltaic technologies, the silicon solar cell has a meager PCE of only 11.9% due to the bandgap mismatch between silicon (1.12 eV) and indoor PV (1.9-2.0 eV)\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e. The III-V materials demonstrate higher PCE (26.8% under 1000 lux illumination), but their prohibitive production costs hinder their widespread adoption in IoT\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e (Supplementary Table\u0026nbsp;2). Perovskite materials stand out due to their tunable bandgap, high absorption coefficient, and flexible fabrication, making them ideal for various irradiance conditions\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan additionalcitationids=\"CR35\" citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e. Compared to other PV technologies, perovskite solar cells (PSC) excel in low-light indoor environments, offering superior PCE\u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb). This makes PSC suitable for any irradiance environment, from natural to indoor light, serving as power sources for small IoT sensors and wireless transmission devices, enabling wireless-powered autonomous IoT node detection. Figure\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ec compares the energy generation by PSC under different irradiance intensities with the average power consumption of IoT communication protocols. The data shows that PSC can provide sufficient power to operate common IoT protocols under varying irradiance conditions\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan additionalcitationids=\"CR39 CR40 CR41\" citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e. Additionally, the flexibility of PSC enables their integration with flexible electronic systems, making them ideal for deployment in environments with complex structural demands.\u003c/p\u003e \u003cp\u003eIn this work, we design a self-sustaining node (SSN) powered by a flexible perovskite solar cell module (FPSM). Under indoor lighting (LED 2700K, 1000 lux), the FPSM achieves a PCE of 30.54% (P\u003csub\u003eout\u003c/sub\u003e: 81.76 \u0026micro;W\u0026middot;cm\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e). It can continuously power the SSN module in various irradiance environments ranging from dim indoor settings (100 lux) to outdoor conditions (10000 lux). The SSN module equipped with custom resistive sensors, detects temperatures and humidity. The communication frequency and power consumption of the SSN are adjusted based on light intensity changes using the Zigbee communication module, which enables ultra-low power operation and 24-hour three-dimensional environmental monitoring (\"indoor-outdoor-aerial\"). Additionally, FPSM-SSN can serve as a self-feedback control hub for smart homes, wirelessly transmitting signals to user interfaces and automatically controlling household appliances based on environment changes.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\n\u003ch3\u003eIntegrated design of the FPSM-SSN\u003c/h3\u003e\n\u003cp\u003eThe FPSM-SSN features a compact and foldable design and can be assembled by folding with a total area of 24 cm\u0026sup2; (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea and Supplementary Fig.\u0026nbsp;1). It comprises two main components: (I) FPSM energy supply module: This module includes three series-connected sub-cells, each with an area of 5 cm\u0026sup2;. The FPSM employs a p-i-n structure, consisting of flexible polyethylene terephthalate (PET) coated with indium tin oxide (ITO), nickel oxide (NiO\u003csub\u003eX\u003c/sub\u003e), Cs\u003csub\u003e0.05\u003c/sub\u003e(FA\u003csub\u003e0.87\u003c/sub\u003eMA\u003csub\u003e0.15\u003c/sub\u003e)\u003csub\u003e0.95\u003c/sub\u003ePb(I\u003csub\u003e0.87\u003c/sub\u003eBr\u003csub\u003e0.13\u003c/sub\u003e)\u003csub\u003e3\u003c/sub\u003e perovskite photoactive layer (Supplementary Fig.\u0026nbsp;2), C\u003csub\u003e60\u003c/sub\u003e, Bathocuproine (BCP), and Cu electrodes. The FPSM is encapsulated with Polyolefin Elastomer (POE) to prevent water intrusion. This module harvests and converts energy to power the entire system (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb and Supplementary Fig.\u0026nbsp;3). (II) SSN detection system: This system has a total area of 24 cm\u0026sup2; and includes power management, information acquisition and processing, and wireless communication modules. The power management module comprises boost and buck converters, a capacitor module, and a maximum power point tracking (MPPT) module. The information acquisition and processing modules include a resistive sensor array, a microcontroller, and high-precision current sensors (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB, Supplementary Fig.\u0026nbsp;4 and Supplementary Table\u0026nbsp;3). For the communication module, we select the ZigBee communication module due to its small size, low power consumption, adjustable transmission power, and strong networked capabilities.\u003c/p\u003e \u003cp\u003eUnder illumination, the FPSM continuously generates electricity and supplies power to the SSN through the power management module. The SSN collects environmental information under various conditions and wirelessly transmits it to the user interface via the ZigBee Zigbee module.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eDesign and characterization of FPSM with high energy harvesting efficiency\u003c/h2\u003e \u003cp\u003eGiven the diverse irradiance conditions in which IoT nodes operate, their performance under low indoor light intensity is pivotal for achieving self-sustaining operation. Perovskite material with its high carrier transport efficiency, tunable bandgap, flexible fabrication, and high defect tolerance, is an optimal choice for various illuminated environments. These characteristics make FPSM ideal for realizing all irradiance-applicable self-sustaining IoT nodes and intelligent communication devices. Figure\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ec presents the Incident Photon-to-Current Efficiency (IPCE) of the Cs\u003csub\u003e0.05\u003c/sub\u003e(FA\u003csub\u003e0.87\u003c/sub\u003eMA\u003csub\u003e0.15\u003c/sub\u003e)\u003csub\u003e0.95\u003c/sub\u003ePb(I\u003csub\u003e0.87\u003c/sub\u003eBr\u003csub\u003e0.13\u003c/sub\u003e)\u003csub\u003e3\u003c/sub\u003e FPSM device, alongside the spectra of the indoor light source used in this study (LED 2700K, 1000 lux) and the AM 1.5 spectrum. The LED has narrower emission spectrum more closely matches the IPCE of the FPSM compared to sunlight. Additionally, the UV-vis spectrum of the perovskite film reveals a distinct absorption peak at 800 nm (Supplementary Fig.\u0026nbsp;5), enabling the FPSM to effectively absorb and convert LED light within the 400\u0026ndash;800 nm range. Consequently, the FPSM achieves an efficiency of 30.54% (Pout: 81.76 \u0026micro;W\u0026middot;cm\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e) under 1000 lux LED (267.7 \u0026micro;W\u0026middot;cm\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e) indoor lighting. Under dimmer indoor conditions of 500 lux and 100 lux, the FPSM's PCE is 29.53% (Pout: 35.36 \u0026micro;W\u0026middot;cm\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e) and 28.29% (Pout: 7.58 \u0026micro;W\u0026middot;cm\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e) respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ed, Supplementary Fig.\u0026nbsp;6, and Supplementary Table\u0026nbsp;4). Additionally, the FPSM achieves a PCE of 15.24% under AM 1.5 illumination (Supplementary Fig.\u0026nbsp;7), which is a considerable value for flexible large-area perovskite solar cell (Supplementary Table\u0026nbsp;5). FPSM maintains high PCE across various irradiance intensities, allowing it to effectively adapt to diverse lighting environments, from dim indoor settings (100 lux) to specialized laboratory conditions (2000 lux) and outdoor environments (10000 lux) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ee, Supplementary Figs.\u0026nbsp;8 and 9). The stable and efficient power output of the FPSM under these conditions ensures that IoT devices can operate reliably across different environmental scenarios.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eDesign of SSN with autonomous power regulation capability\u003c/h3\u003e\n\u003cp\u003eGiven the need for FPSM to harvest energy under varying irradiance intensities, fluctuations in external light affect its charging state (manifested as voltage changes), which impacts the energy utilization efficiency of the FPSM-SSN system. To address this issue, we have designed the SSN system with targeted features. First, we incorporated an internal MPPT function, which can monitor FPSM's open-circuit voltage every 16 s and set 80% of this voltage as the maximum power point, ensuring optimal energy input (Supplementary Fig.\u0026nbsp;10). In addition, we also develop a \"collect-store-utilize\" energy conversion framework. In irradiance environments, such as during the day, the SSN's internal boost converter elevates \u0026ldquo;surplus output voltage\u0026rdquo; of FPSM to 3.8 V, storing excess energy in the capacitor module for night-time use. When energy-intensive modules like information processing are active, the SSN's built-in buck converter stabilizes the output voltage of FPSM or the capacitor module at 1.8 V (Supplementary Fig.\u0026nbsp;11). The boost and buck converters amplify signal voltage with minimal power loss (~\u0026thinsp;7%) (Supplementary Fig.\u0026nbsp;12). For information acquisition and processing, the SSN uses a custom embedded successive approximation analog-to-digital converter to capture measurement information, ensuring each module operates in the lowest power mode (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ef).\u003c/p\u003e \u003cp\u003eWe select the Zigbee communication module as the information transmission unit due to its networked connectivity capabilities, making it suitable for applications such as smart homes and urban monitoring. Combining the Zigbee module with FPSM enables self-sustaining networked information collection in diverse lighting environments. This synergy offers extensive application prospects. To minimize SSN system power consumption, the Zigbee module is programmed to operate in bursts, periodically waking from deep sleep mode for approximately 0.15 s to transmit information to user interfaces. In deep sleep mode, the total current of SSN during operation (at a working voltage of 1.8 V) is approximately 200 \u0026micro;A. When the Zigbee module transmits signals, the total current increases to about 300 \u0026micro;A (Supplementary Fig.\u0026nbsp;13). Additionally, to further reduce power consumption, we incorporate an adjustable communication frequency feature in the Zigbee module (ranging from once per second to once per 60 seconds). This feature allows the Zigbee module to operate at different communication frequencies under varying light intensities, maximizing energy utilization (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eg). Our design allows a 16cm\u0026sup2; FPSM to sustain SSN operation for an entire day with just 10 hours of exposure under low indoor light (1000 lux). In outdoor environments with stronger light, the required FPSM size can be further reduced.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\n\u003ch3\u003eTemperature/humidity monitoring characterizations of the FPSM-SSN\u003c/h3\u003e\n\u003cp\u003eThe FPSM-SSN shows significant potential for applications in smart cities and smart homes, especially in environmental monitoring. In this study, we develop two resistive sensors based on PEDOT: PSS (a PEDOT: PSS@ carbon nanotube (CNT) temperature sensor and a PEDOT: PSS@ Ti\u003csub\u003e3\u003c/sub\u003eC\u003csub\u003e2\u003c/sub\u003eT\u003csub\u003eX\u003c/sub\u003e humidity sensor). The PEDOT: PSS materials can be seamlessly integrated with the SSN module via inkjet printing technology (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ea). Given the substantial impact of humidity on the resistance of PEDOT materials, which could interfere with temperature response, we sealed the PEDOT: PSS@ CNT temperature sensor with PET double-sided tape in this study to ensure the accuracy of the test results (Supplementary Fig.\u0026nbsp;14). The sensing material based on PEDOT: PSS is a resistive sensing material that can change its resistance depending on external environmental changes (Supplementary Fig.\u0026nbsp;15). Additionally, the FPSM-SSN can achieve multifunctional information monitoring by replacing the sensing materials.\u003c/p\u003e \u003cp\u003eWe evaluate the information collection capabilities of the FPSM-SSN in an indoor environment with LED illumination at 1000 lux. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eb and \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ec, the PEDOT: PSS@ CNT temperature sensor exhibits stable and sensitive temperature responses within the range of 25℃ to 41℃ (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eb). The resistance decreases with increasing temperature, with a sensitivity of -2.543%℃\u003csup\u003e\u0026minus;1\u003c/sup\u003e. Similarly, within the range of 20\u0026ndash;60% RH (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ec), the PEDOT: PSS@ Ti\u003csub\u003e3\u003c/sub\u003eC\u003csub\u003e2\u003c/sub\u003eT\u003csub\u003eX\u003c/sub\u003e humidity sensor shows stable and sensitive humidity responses with a sensitivity of 0.616%RH\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ed).\u003c/p\u003e \u003cp\u003eWe compare the data collected at different transmission frequencies to ensure the accuracy of the SSN system under different information collection conditions. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ee, the SSN measurements are consistent across different transmission frequencies. Considering the operation of FPSM-SSN at night without light, after fully charging the SSN device, we maintain low-power information collection at a transmission frequency of once every 30 s, and monitor the voltage values of the two segments of the capacitor module in real time, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ef. The FPSM-SSN can achieve 13 h long time night self-sustaining detection. This further demonstrates the stable and accurate self-sustaining information collection capability of the FPSM-SSN system.\u003c/p\u003e\n\u003ch3\u003eSelf-sustaining detection of FPSM-SSN under indoor lighting\u003c/h3\u003e\n\u003cp\u003eTo validate the self-sustaining detection capability of FPSM-SSN under indoor lighting, we install the integrated temperature and humidity sensor nodes on the wall of the Perovskite Laboratory at Dalian University of Technology (38.87\u0026deg; N latitude). This specific location is chosen because the lab's windows face northwest (346\u0026deg;), resulting in minimal direct sunlight exposure. The natural light received is primarily diffuse radiation and reflections from nearby objects (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eg). Under these conditions, the FPSM primarily absorbs energy emitted by LED lights.\u003c/p\u003e \u003cp\u003eBy adjusting the transmission frequency, the FPSM-SSN achieves 24-hour environmental monitoring under varying irradiance conditions from day to night. Observation shows a slight increase in indoor temperature and a decrease in humidity from 9:00 AM to 7:00 PM, primarily due to daytime sunlight. During the night, from 7:00 PM to 5:00 AM, the temperature slightly decreased, and humidity slightly increased, although overall changes remained stable. From 6:00 AM to 9:00 AM, temperature fluctuation was more pronounced, likely due to the activities of lab personnel, while humidity change was less noticeable (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eh). These results are consistent with those from a commercial temperature-humidity detector. These findings demonstrate that the FPSM-SSN can fully meet the long-term environment monitoring need even under low-light conditions.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\n\u003ch3\u003eApplication of FPSM-SSN in outdoor environments\u003c/h3\u003e\n\u003cp\u003eThe biggest challenge facing IoT in practical application is power supply. When setting up a large number of sensors, the need for wiring limits the placement of devices\u003csup\u003e\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u003c/sup\u003e. FPSM, with its ability to adapt to various irradiance environments and provide high energy output under different conditions, can be used in any power supply scenario. The SSN device is equipped with the Zigbee communication module, which offers the advantage of networked connectivity and wireless signal transmission. Combining these two technologies, the FPSM-SSN can fully address the wiring challenge and enable networked wireless detection in any setting. We deploy the FPSM-SSN indoors, outdoors, and on a drone from 12:00\u0026ndash;13:00 noon to achieve three-dimensional networked detection of our home environment. Node A is placed on top of a drone and conducted information collection hovering three meters above the ground. Node B is positioned outdoors at Dalian University of Technology (latitude 38.87\u0026deg;N) for information collection. According to reports, the local temperature is approximately 25\u0026ndash;30\u0026deg;C, and the humidity is around 50\u0026ndash;70% RH. Node C is situated inside the Perovskite Laboratory at Dalian University of Technology, where environmental conditions are controlled by a dehumidifier and air conditioner, maintaining a temperature of 23\u0026ndash;25\u0026deg;C and humidity of 30\u0026ndash;35% RH (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea). The results indicate that the FPSM-SSN has stable and accurate networked detection capabilities. The outdoor temperature is approximately 5\u0026deg;C higher than the indoor temperature, and the humidity is about 25% RH higher. These findings are consistent with the standard temperature and humidity results reported for the local area.\u003c/p\u003e \u003cp\u003eAdditionally, we conduct long-term (24h) networked detection of indoor and outdoor environments to further verify its long-term networked detection capabilities (Supplementary Figs.\u0026nbsp;16 and 17). From the test results, the outdoor environment measurements closely matched the local official weather reports, with a peak temperature of 30\u0026deg;C occurring at 16:00 and humidity fluctuating between 55\u0026ndash;70% RH. Compared to the outdoor environment, the indoor environment remained relatively stable due to the operation of dehumidifiers and air conditioners, with temperature fluctuations between 23\u0026ndash;25\u0026deg;C. At night, due to the air conditioner being turned off, the temperature slightly increased. Humidity fluctuated between 30\u0026ndash;40% RH and showed an upward trend at night due to the dehumidifier being turned off (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eb and c). The FPSM-SSN demonstrates strong self-sustaining networked environment monitoring capability, showing significant potential in the development of self-sustaining IoT nodes.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eEvaluation of FPSM-SSN as smart home control center\u003c/h2\u003e \u003cp\u003eIn recent years, with the advancement of artificial intelligence technology, self-sustaining IoT nodes with intelligent sensing and feedback capabilities have shown tremendous future potential\u003csup\u003e\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u003c/sup\u003e. To achieve this functionality, we integrate self-feedback design into the FPSM-SSN (Supplementary Fig.\u0026nbsp;18). The FPSM-SSN can detect changes in environmental temperature and wirelessly transmit the collected information to the control unit of a digital switch, enabling intelligent control of household appliances. In this study, we paired the FPSM-SSN with a digital switch controlling an electric fan (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ed and Supplementary Fig.\u0026nbsp;19). When the detected temperature exceeded 35\u0026deg;C, the FPSM-SSN transmitted the information to the control unit, triggering the fan to turn on. When the temperature dropped below 25\u0026deg;C, the system automatically turned off the fan, achieving smart home control (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ee and Supplementary Video 1). The intelligent sensing and feedback capabilities of the FPSM-SSN demonstrate its powerful potential for future applications.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eHere, we present a flexible, fully integrated, all irradiance-applicable, self-sustaining IoT node powered by a FPSM, capable of real-time, continuous information collection under various lighting conditions (from intense outdoor sunlight to dim indoor LED lighting). The FPSM is ideally suited for powering IoT nodes in urban and household environments, achieving an efficiency of 30.54% under indoor lighting condition and maintaining high PCE and power output across diverse lighting conditions. This addresses the issue of insufficient energy harvesting in self-sustaining IoT devices. We pair the FPSM with a low-power SSN module. By adjusting the Zigbee communication frequency of the SSN, we achieve power consumption regulation, enabling 24-hour indoor temperature and humidity detection. The networked capability of the Zigbee module allows the FPSM-SSN to perform networked monitoring in various environments. With its wireless transmission capability, the FPSM-SSN system smartly senses temperature changes and enables intelligent home control. Given its robust self-sustaining detection capabilities under various irradiance conditions, the FPSM-SSN shows great potential in smart cities, smart homes, automation, and human-machine interaction.\u003c/p\u003e"},{"header":"Method","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eMaterials\u003c/h2\u003e \u003cp\u003eAll the materials are used as received from commercial sources, including PbI\u003csub\u003e2\u003c/sub\u003e (\u0026gt;\u0026thinsp;99%, TCI, Japan), HC(NH\u003csub\u003e2\u003c/sub\u003e)\u003csub\u003e2\u003c/sub\u003eI (FAI, 99.9%, Advanced Election Technology Co. Ltd, China), polydimethylsiloxane (PDMS, Sylgard 184 Silicone Elastomer, Dow Corning). Cesium iodide (CsI, 99.9%), CH\u003csub\u003e3\u003c/sub\u003eNH\u003csub\u003e3\u003c/sub\u003eI (MAI, \u0026ge;\u0026thinsp;99.5%), CH\u003csub\u003e3\u003c/sub\u003eNH\u003csub\u003e3\u003c/sub\u003eCl (MACl, \u0026ge;\u0026thinsp;99.5%), PEDOT: PSS (Heraeus CLEVIOSTM PH1000), dimethylformamide (DMF, 99.8%), C\u003csub\u003e60\u003c/sub\u003e, dimethylsulfoxide (DMSO, 99.9%) and chlorobenzene (CB, 99.8%), Carbon nanotube (CNT), are all purchased from Sigma Aldrich (USA). Ti\u003csub\u003e3\u003c/sub\u003eC\u003csub\u003e2\u003c/sub\u003eT\u003csub\u003ex\u003c/sub\u003e is purchased from Weixi technology (China). NiOx is purchased from Furui Technology (China). C\u003csub\u003e60\u003c/sub\u003e is purchased from Tanfeng Technology (China). BCP is purchased from Xi\u0026rsquo;an Yuri Solar (China). Glass substrates are purchased from Suzhou Shangyang Solar Technology Co. Ltd (China). The PET/ITO substrates (\u0026sim;12​ \u0026micro;m thickness) are purchased from Shanghai Yiwei Mechanical \u0026amp; Electrical Hardware Co. Ltd (China). Carbon Double-sided tape (50 ohm/sq/inch) is purchased from RiXin (Japan). Electronic components are purchased from electronic technology company (China).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eFPSM fabrication and characterization\u003c/h2\u003e \u003cp\u003eFlexible Substrate Etching and Cleaning Process: Cover the PET/ITO with a layer of PTFE tape. Place it in a chamber filled with HCI vapor to etch the uncovered areas, forming 200 \u0026micro;m wide P\u003csub\u003e1\u003c/sub\u003e lines. Sequentially clean with deionized water, absolute ethanol, and isopropanol using ultrasound for 30 min. Follow this with UV ozone treatment for 15 min. PDMS with curing agent in a 10:1 ratio is spin-coat on a clean glass substrate at 2000 rpm for 50 s. Anneal at 100\u0026deg;C for 60 min. Attach PET/ITO to the glass/PDMS substrate, then transfer to a vacuum chamber to remove air between PEN and PDMS.\u003c/p\u003e \u003cp\u003ePreparation of NiOx Hole Transport Layer (HTL): Sputter the NiOx hole transport layer at 50W power under vacuum conditions below 9\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;4\u003c/sup\u003e Pa for 30 min with magnetron sputter.\u003c/p\u003e \u003cp\u003ePreparation of Perovskite Absorber Layer: Add the Cs\u003csub\u003e0.05\u003c/sub\u003e(FA\u003csub\u003e0.87\u003c/sub\u003eMA\u003csub\u003e0.15\u003c/sub\u003e)\u003csub\u003e0.95\u003c/sub\u003e Pb(I\u003csub\u003e0.87\u003c/sub\u003eBr\u003csub\u003e0.13\u003c/sub\u003e)\u003csub\u003e3\u003c/sub\u003e perovskite precursor solution to a blade coating device. Maintain a gap of approximately 150 \u0026micro;m between the substrate and blade, and coat at a speed of 3.5 mm/s in ambient air with 30%-57% RH. After coating, immediately transfer the wetted substrate to a vacuum chamber, reduce the pressure to less than 1 bar within 10 s, and maintain for 2 min. Transfer to ambient air and anneal the substrate at 150\u0026deg;C for 10 min to complete the conversion to the black phase.\u003c/p\u003e \u003cp\u003ePreparation of C\u003csub\u003e60\u003c/sub\u003e Electron Transport Layer (ETL): Place the perovskite film in a vacuum deposition chamber. Under vacuum conditions below 9\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;4\u003c/sup\u003e Pa, evaporate C\u003csub\u003e60\u003c/sub\u003e at a rate of 0.1 \u0026Aring;/s to a thickness of 30 \u0026Aring;. In the same vacuum (9\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;4\u003c/sup\u003e Pa) deposition chamber, evaporate BCP at a rate of 0.1 \u0026Aring;/s to a thickness of 10 \u0026Aring;.\u003c/p\u003e \u003cp\u003ePreparation of Metal Counter: Use a 355 nm picosecond laser scribing machine (MM2500, OpTeksystem, Inc., USA) with a laser power of 12 W and a pulse repetition rate of 100 kHz. Maintain a distance of 30 \u0026micro;m between P\u003csub\u003e1\u003c/sub\u003e and P\u003csub\u003e2\u003c/sub\u003e lines. Place the multilayer films prepared in the previous steps into a mask, then place them in a vacuum deposition chamber. Under vacuum conditions below 9\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;4\u003c/sup\u003e Pa, evaporate the Cu electrode at a rate of 0.1 \u0026Aring;/s to a thickness of 600 \u0026Aring; to complete the device fabrication. Use a 355 nm picosecond laser scribing machine (MM2500, OpTeksystem, Inc., USA) with a laser power of 0.78 W and a pulse repetition rate of 80 kHz to remove an 80 \u0026micro;m P3 gap.\u003c/p\u003e \u003cp\u003eEncapsulation of flexible perovskite solar modules: Transfer the FPSM to the center of the hot press machine. Place a PET film (3 cm \u0026times; 4 cm) in the center position on top of the FPSM. Set the hot press machine to a temperature of 120\u0026deg;C and a pressure of -90 Pa. After hot pressing for 2 min, the film encapsulation will be completed.\u003c/p\u003e \u003cp\u003eCharacterization: The microstructures of the thin films are observed using a field-emission SEM (JSM-7610F Plus, Hitachi, Japan). XRD is performed using a high-resolution diffractometer (SmartLab 9kw, Rigaku, Japan) with CuKa radiation. UV-vis absorption spectra of the perovskite films are obtained using a spectrophotometer (U-4150, Hitachi, Japan). The IPCE spectra were obtained using an EnliTech (Taiwan) QE-R measurement system. The \u003cem\u003eJ-V\u003c/em\u003e characteristics of FPSM are measured by a source meter (2450, Keithley, USA) at the scan speed of 100 mV s\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e under AM 1.5G 1-sun illumination (100 mW cm\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e) generates by a solar simulator (Sol3A Class AAA, Oriel, Newport, USA). The \u003cem\u003eJ-V\u003c/em\u003e curves under indoor light are tested using Osram LED lamps (KW CSLPM2.CC, Germany). The LED lamps are calibrated for different light intensities using a DELIXI photometer, and the tests are conducted after calibration. For more detailed test methods, see Supplementary Note 1. FPSM's MPPT detection was performed using a source meter (2450, Keithley, USA).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eSSN system fabrication and characterization\u003c/h2\u003e \u003cp\u003eThe SSN system is composed of four main modules: information collection, wireless communication, power management, and information processing. The power management module consists of an energy harvesting PMIC (BQ25570, Texas Instruments). The PMIC utilizes maximum power point tracking to effectively boost the solar cell output to 3.8V for charging and stores energy in a 70F capacitor. The PMIC's threshold control unit ensures that the capacitor powers the rest of the system while maintaining the capacitor voltage within a threshold range of 2-3V. The BQ25570's integrates buck converter regulates the capacitor voltage to a stable 1.8V, supplying power to the information processing, wireless communication, and information collection modules.\u003c/p\u003e \u003cp\u003eThe information collection module uses a high-precision current detector (INA186A5, Texas Instruments) to feed the collects current information back to the MCU for processing. Information processing is performed by a microcontroller (STM32L431, STMicroelectronics), which communicates with the wireless communication module via a serial port. Wireless communication is handled by a compact programmable system-on-chip module and XBee module (XBRR-24Z8UM, DIGI), which integrates an MCU and Zigbee.\u003c/p\u003e \u003cp\u003eIn this work, the SSN devices are all powered by FPSM. The power consumption of the SSN is characterized using a Keithley 2450 system (Keithley, USA). The Keithley test leads are connected to the reserved interface of the SSN, and a voltage of 1.8V is applied at both ends for testing.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eAssembly and characterization of the FPSM-SSN\u003c/h2\u003e \u003cp\u003eThe FPSM-SSN is assembled using a combination of conductive adhesive and hot pressing. Initially, the conductive adhesive is applied to the positive and negative electrodes of the FPSM to ensure effective electron and hole extraction. The remaining adhesive is applied to the POE surface at a 90\u0026deg; angle. Next, the upper conductive adhesive on the POE is aligned with the reserved metal electrodes (1 cm \u0026times; 4 cm) of the SSN. The entire assembly is then hot-pressed at 120\u0026deg;C and 0.4 MPa for 60 seconds using a hot press machine. Finally, the FPSM-SSN is folded along the designated lines, completing the assembly process.\u003c/p\u003e \u003cp\u003eThe discharging curves of the capacitor are collected using an electrochemical workstation (CHI660E). The discharge of the capacitor module is tested in an environment without light.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e\u003cb\u003eResistive sensors fabrication and characterization\u003c/b\u003e\u003c/h2\u003e \u003cp\u003eThe resistive temperature sensor is fabricated by spray-coating a mixed solution of PEDOT: PSS and CNT onto the temperature sensing region. Add 30 mg of CNT and 0.5 mL of sodium polystyrene sulfonate to 10 mL of deionized water. Ultrasonic the mixture until it is uniform and free of noticeable precipitates. Combine the CNT-PSS solution with 1.3 wt% PEDOT: PSS at a ratio of 1:7. Load the prepared solution into a spray gun. Spray the solution onto the SSN temperature sensing region for 15 s. Cure the coated sensor on a hot plate at 120\u0026deg;C for 10 min.\u003c/p\u003e \u003cp\u003eThe resistive humidity sensor is fabricated using PEDOT: PSS and Ti\u003csub\u003e3\u003c/sub\u003eC\u003csub\u003e2\u003c/sub\u003eT\u003csub\u003eX\u003c/sub\u003e as the sensing materials. The preparation steps are as follows: Disperse 1 g of Ti\u003csub\u003e3\u003c/sub\u003eC\u003csub\u003e2\u003c/sub\u003eT\u003csub\u003eX\u003c/sub\u003e black powder into 10 mL of deionized water. Stir the mixture mechanically at room temperature for 15 min. Combine the Ti\u003csub\u003e3\u003c/sub\u003eC\u003csub\u003e2\u003c/sub\u003eTx suspension with 1.3 wt% PEDOT: PSS at a ratio of 1:2. Ultrasonic the mixed solution for 15 min to obtain a liquid-phase PEDOT: PSS and Ti\u003csub\u003e3\u003c/sub\u003eC\u003csub\u003e2\u003c/sub\u003eT\u003csub\u003eX\u003c/sub\u003e nanocomposite. Load the prepared nanocomposite solution into a spray gun. Spray the solution onto the SSN humidity sensing region for 5 s. Cure the coated sensor on a hot plate at 70\u0026deg;C for 10 min.\u003c/p\u003e \u003cp\u003eCharacterization: In this work, the response of the sensing material under different temperatures and humidity is tested based on the FPSM-SSN system unless otherwise specified. The temperature response is controlled by the thermostat (LC-HN-25S, Chian), the humidity response is controlled by the humidity control box (Memmert, Germany), and the information collection is completed by receiving resistance signals from the computer. \u003cem\u003eI-V\u003c/em\u003e curve tests is performed with the Keithley 2450 system (2450, Keithley, USA)\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eEvaluation of FPSM-SSN Networked Detection\u003c/h2\u003e \u003cp\u003eThe FPSM-SSN networked detection is validated at the Perovskite Solar Cell Laboratory Center of Dalian University of Technology. The FPSM-SSN devices are attached to the test sites using double-sided or transparent tape. During the test, the field temperature is tested in real time and calibrated to ensure accurate test results.\u003c/p\u003e \u003cp\u003eTo compare the experimental results, we control the indoor environment of the nodes using air conditioners and dehumidifiers, maintaining an indoor temperature of 24\u0026ndash;27\u0026deg;C and humidity of 30\u0026ndash;40% RH. This contrast sharply with the outdoor conditions of 20\u0026ndash;31\u0026deg;C and humidity of 50\u0026ndash;70% RH. The drone-carried experiment is conducted at 12:00 AM, with the device attached to the drone for measurements.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eEvaluating FPSM-SSN as a control hub for smart devices\u003c/h2\u003e \u003cp\u003eFor smart home control, the FPSM-SSN system is connected to digital switches linked with various smart household appliances. The system is programmed to automatically activate the switch when the detects temperature exceeded 35\u0026deg;C (2000KΩ), with the FPSM-SSN wirelessly transmitting the signal to the smart switch, thereby enabling intelligent device control.\u003c/p\u003e \u003cp\u003eIn this experiment, we manipulate the FPSM-SSN's detection temperature using a hot plate and ice packs. The FPSM-SSN transmits sensor information wirelessly to the user interface, which then controls the home devices. When the temperature is raised above 35\u0026deg;C, the smart switch receives the signal from the FPSM-SSN and activates the connected device. Conversely, when the temperature fell below 35\u0026deg;C, the switch is turned off. This setup effectively demonstrates the FPSM-SSN's capability to enhance smart home automation through responsive environmental monitoring and control.\u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003ch2\u003eCompeting interests\u003c/h2\u003e \u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e \u003ch2\u003eAuthor contributions\u003c/h2\u003e \u003cp\u003eY.S., W.H. and B.Y. proposed concepts and designed experiments. W.H. and R.N. designed FPSM and SSN samples, and conducted data analysis. J.Z. and S.Q. contributed to the verification of wireless transmission and networking connectivity features. J.Z., M.P. and Y.Q. regulated the preparation and packaging process of FPSM.\u003c/p\u003e\u003ch2\u003eAcknowledgements\u003c/h2\u003e \u003cp\u003eThe work was supported by the National Natural Science Foundation of China (52272193), the National Natural Science Foundation of China (No.22304020), and the Fundamental Research Funds for the Central Universities (DUT22LAB602).\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eArias R, Lueth KL, Rastogi A (2018) The effect of the Internet of Things on sustainability. \u003cem\u003eWorld Economic Forum\u003c/em\u003e. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.weforum.org/agenda/2018/2001/effect-technology-sustainability-sdgs-internet-things-iot/\u003c/span\u003e\u003cspan address=\"https://www.weforum.org/agenda/2018/2001/effect-technology-sustainability-sdgs-internet-things-iot/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSparks P (2017) The economics of a trillion connected devices. 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Adv Intell Syst 2300824\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-5174154/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5174154/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eCurrently, there are 17\u0026nbsp;billion IoT nodes, mostly powered by cables or batteries, leading to high maintenance costs and increased risk of data loss during power outages. Despite various energy harvesting technologies, the widespread deployment of self-sustaining IoT nodes is limited due to the lack of stable, continuous energy sources and limited power efficiency. We introduce an all-irradiance, 24-hour self-sustaining flexible node (SSN) with a perovskite solar cell module (FPSM) for steady power. The FPSM achieves over 30.54% power conversion efficiency (PCE) indoors, providing power in various lighting. The SSN, equipped with temperature and humidity sensors, uses a low-power Zigbee module for wireless data transfer. The FPSM-SSN reliably conducts 24-hour environmental monitoring indoors and achieves comprehensive three-dimensional data collection across \"indoor-outdoor-aerial\" environments. Additionally, it can also intelligently control household appliances based on temperature changes. The FPSM-SSN's robust self-sustaining capabilities demonstrate significant potential for IoT applications.\u003c/p\u003e","manuscriptTitle":"All Irradiance-Applicable, Perovskite Solar Cells-Powered Flexible Self-Sustaining Sensor Nodes for Wireless Internet-of-Things","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-10-23 14:47:21","doi":"10.21203/rs.3.rs-5174154/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"12ffa025-c194-414d-9ca7-9a4a117acc9b","owner":[],"postedDate":"October 23rd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":39292298,"name":"Physical sciences/Energy science and technology/Energy harvesting/Devices for energy harvesting"},{"id":39292299,"name":"Physical sciences/Energy science and technology/Renewable energy/Solar energy/Photovoltaics/Solar cells"}],"tags":[],"updatedAt":"2024-11-10T17:50:39+00:00","versionOfRecord":[],"versionCreatedAt":"2024-10-23 14:47:21","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5174154","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5174154","identity":"rs-5174154","version":["v1"]},"buildId":"FbvkV6FR0MCFSLy54lSbu","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}