A Solar Water‐Heating Smart Window by Integration of the Water Flow System and the Electrochromic Window Based on Reversible Metal Electrodeposition

Abstract Various smart windows with dynamic modulation of the light transmittance have been developed rapidly in recent years. However, current design of the smart windows can only modulate the indoor solar irradiation instead of effectively utilize them. Here, a solar water‐heating (SWH) smart window is proposed by the integration of the traditional electrochromic window and the water flow system, which can not only provide dynamic daylight modulation but also harvest the solar energy and store them by heating water. In the SWH window, the reversible metal electrodeposition (RME) not only provides daylight modulation but also provides metal layer working as a flat‐plate solar collector for energy harvesting. Compared with traditional electrochromic windows, the SWH window with a water flow system can more effectively modulate the indoor temperature, owing to the significantly enhanced tunability of the thermal irradiation from the window. Compared with water‐flow windows, the RME provide a metallic layer for efficient light harvesting, up to 42% solar energy can be effectively harvested and stored as hot water. Such an SWH smart window is promising to reduce the heating, lighting, and air conditioning energy consumption, which may bring new insights in the design of the next‐generation green buildings.

50 mmol/L KCl, 10 mmol/L FeCl 3 and 10 mmol/L K 3 [Fe (CN) 6 ] in deionized water under stirring for 5 min at room temperature. Then the electrodeposition procedure was carried out in a three-electrode cell system with the ITO glass as the working electrode, Ag/AgCl electrode as the reference electrode and Pt as the counter electrode. Typically, a constant current density of 20 μA cm -2 was applied to the electrodeposited system and the optimal deposition time was 600 s. After the deposition process, the PB electrodes were washed by deionized water and dried at 60 °C for 1 h in the oven.

Calculation of the ion diffusion coefficients for the PB film and explanation for the performance fluctuation of the PB film
To further investigate the performance fluctuation of the PB film, we have calculated the diffusion coefficients D (cm 2 /s) of Zn 2+ and Cu + in the PB using CV results in Figure S4 by the Randles-Sevcik equation: I p =kn 3/2 AD 1/2 cv 1/2 (Equation S1) where I p (A) is the peak current, k is the Randles-Sevcik constant, k= 2.69 10 5 , n is the transferred electron number involved in the redox process, A (cm 2 ) is the area of the electrode, C (mol/cm 3 ) is the concentration of ion in the bulk solution, and v (V s -1 ) is the scan rate.
Ion diffusion coefficients: As shown in the above calculations, the initial ion diffusion coefficient D dropped from cm 2 /s to cm 2 /s after 200 cycles, which is about 10 times dropped and induces the rapid performance decay within 200 cycles. After 1000 cycles, the diffusion coefficient only slightly decays from cm 2 /s to cm 2 /s. Such a small change of the ion diffusion coefficient cannot greatly influence the performance of the film. Then, why the PB performance increased from 200 cycles to 1000 cycles? We further obtained the SEM images of the PB film in the initial state before cycling, after 200 cycles and 1000 cycles. As shown in Figure S5, with continuous cycling, the PB film experiences gradual etching, and the relatively clean film etched to rough surface within 200 cycles, and after 1000 cycles, the film becomes highly porous. We propose the increased performance of the film may be owing to the highly porous surface of the film, which increase the active surface area and promotes the color switching process.

Solar water-heating smart window assembly
Solar water-heating smart window was assembled using two pieces of ITO glass, one was bare ITO glass and another was with PB deposited on it. We prepared two sizes of devices, one size is 5*5*0.5cm 3 , which used for the electrochromic measurements and solar energy harvesting system tests. Another is 10*10*0.5 cm 3 , used for the test of indoor temperature control. The Cu metal frame was used as the anode, and aqueous electrolyte containing ZnSO 4 (1 M)/CuCl 2 (0.01 M) were used as the electrolyte. As shown in Figure S2, first, the two ITO electrodes and the Cu metal frame (in the middle of the two ITO electrodes) were inserted into a custom resin (photosensitive resin 9400) box, assembled as a cell. Epoxy glue was used to seal three sides of the cell. The electrolyte was injected into the cell by a syringe through the unsealed side of the cell. Before injection, the empty cell and the electrolyte in a vial were purged with dry N 2 for 15 min to drive away ambient air. Finally, the cover matching with the resin frame was encapsulated on the cell, and the solar waterheating smart window was finally prepared.

Temperature control and solar energy harvesting test
Temperature control: The temperature control test was carried out in a 22*26*26 cm 3 model house, which was made of wood. In order to avoid the influence of ambient temperature as much as possible, we attached a layer of insulation cotton to the interior of the house. The photo of the model house is shown in Figure 4a. The size of the window is 10*10 cm 2 , which corresponds to the size of the device. In the temperature control test, we tested the air temperature near the window (position A) and the air temperature in the middle of the model house (position B), respectively.
The model of the thermometer is GJD-200LED, which was purchased from Hengshui Zhengxu Electronic Technology Co. Ltd.. The Xenon lamp with filter was used as the light source to simulate the sunlight and it was placed 15 cm away from the window outside the model house and adjusted the optical power density to that the average optical power density of the device was 84 mW/cm 2 (the center of the window was 100 mW/cm 2 and the edge of the window was 68 mW/cm 2 ). The temperature of position A and B were measured continuously and the temperature changes were recorded every 1 minute. To maintain the metal deposition of the SWH window, a bias of 1 V between the ITO and Cu-frame was applied to the SWH window in the temperature control measurements.
The details of the model house: The geometry of the model house is provided in Figure S0 in  mW/cm 2 , and the edge position is 78.8 mW/cm 2 ), and the device was continuously tested and the temperature changes in the vacuum cup were recorded for 4 hours. In the test, the flow rate of the peristaltic pump was set at 25 mL/min and the cycle was performed every 12 minutes. The thermometer was placed in the vacuum cup to test the temperature change and the temperature was recorded every 12 minutes. To maintain the metal deposition of the SWH window, a bias of 1 V between the ITO and Cu-frame was applied to the SWH window in the solar energy harvesting measurements.
The details of the STP-F01A peristaltic pump: the motor voltage is 24 V, the rated voltage is 12 W, and the output DC is 24 V, 1.9 A. According to the calculation of power consumption formula W= P×t, the power consumption of two peristaltic pumps is W= 2 ×12 W×(5/60) h = 2 Wh. The heat generated in the circulation process is very small, which has no effect on the temperature recorded in the experiment and can be ignored.

Specific heat capacity of the electrolyte
For the calculation of specific heat capacity of multicomponent system, the following formula shall be followed: Here, is the specific heat capacity of solvent (J kg -1 K -1 ), is the mass fraction of solvent, is the specific heat capacity of solute (J kg -1 K -1 ), is the mass fraction of solute.
The specific heat capacity of the electrolyte:     Since the 10 cm×10 cm device is too large to fit into the UV-vis spectrometer for continuous measurement, the switching time of the 10 cm×10 cm device was tested by continuously monitoring the RGB (red, green, blue) changes of the images. It is well known that due to the potential drop of ITO itself, the color change between the middle and the edge will be out of sync and there will be a delay in the middle in the color change process of large-area devices. Therefore, we recorded the continuous RGB change between the edge and the central part in the color change process (Table  S1 and Table S2), and selected the R value for drawing, so as to calculate the color response time of large-area devices, as shown in Figure S6.