Enhancing hydrovoltaic power generation through coupled heat and light-driven surface charge dynamics

Domain: physics
Published: 2026-01-09
Editorial outcome: major_revision

Abstract
Harnessing natural evaporation offers a sustainable pathway for next-generation energy technologies. We present a unified physical and experimental framework for evaporation-driven hydrovoltaic (EDHV) systems that decouples and controls the key interfacial processes underlying electricity generation from heat and sunlight. An intermediate ion-conducting layer separates the evaporative top interface from the silicon–dielectric nanopillar array, enabling independent modulation of evaporation, ion transport, and interfacial chemical equilibrium. This strategy enhances performance and clarifies mechanisms governing thermal and photo-induced charge generation, improving ion migration and electricity output. We develop a predictive equivalent-circuit model that captures process coupling through an analytically derived transfer capacitance. Our results show that capacitive photocharging and thermally modulated surface equilibria—rather than faradaic or photothermal effects—dominate energy conversion. The device achieves 1 V open-circuit voltage and 0.25 W/m² power density, with silicon doping and dielectric choice further boosting performance. These findings inform EDHV optimization across environmental and material conditions.

Introduction
Evaporation, a natural process with an average global energy flux of 80 (W/m²)1, has significant potential for energy harvesting. Hydrovoltaic technology, which generates energy through the direct interaction of materials with water2–4, has recently emerged as a promising avenue for sustainable energy generation5–8. In particular, evaporation-induced hydrovoltaic devices (EDHV) stand out due to their ability to produce a continuous (24h) electricity output, operating without external mechanical energy input across a wide range of environmental conditions. This is achieved through the synergy of spontaneous capillary action and evaporation, enabling autonomous, low-intensity energy supply solutions ideal for portable devices, Internet of Things applications9–11 and harvesting of low-grade waste heat (below 100°C) produced by industrial, agricultural, and domestic processes12,13. When integrated with solar-driven evaporators that utilize photothermal effects14 to significantly enhance evaporation rates, EDHV systems have the capability to also convert solar energy into electrical power. This advancement underscores their potential as a reliable and sustainable energy source. However, as the demonstration of these devices expands to encompass a wider variety of materials and architectures, it is imperative to engage in the ongoing debate surrounding the fundamental mechanisms, optimal micro/nanostructures, and operating conditions of EDHV devices. In particular, beyond enhancing the evaporation rate through photothermal effects, it is crucial to comprehend how external heat and light sources impact the interfacial processes that are essential for effective hydrovoltaic energy conversion.

In recent years, EDHV devices utilizing micro-nanoporous materials have garnered significant attention for their ability to harness energy through the movement of electrolytes within partially wetted regions2,15,16. This phenomenon, which occurs ahead of a liquid meniscus, facilitates the electrokinetic streaming of ions. Previous studies have identified several contributing phenomena, including the streaming potential4,6,17, ionovoltaic effect15,16,18, and evaporating potential2,19. Central to these mechanisms is the critical role of directional electrolyte flow near the liquid-solid interface. Additionally, going beyond the intricate micro- and nanostructures of typical EDHV devices4,17,20,21, we recently utilized a controlled array of silicon nanopillars to demonstrate the significant impact of the geometrical and interfacial chemical properties of the nanostructures, particularly the role of the chemical equilibrium of the surface groups in enabling high salinity operation6, challenging the reliance on deionized water for high performance19. Furthermore, recent work introduced a passive hydrovoltaic device characterized by a limited evaporation rate and fluid permeation, capable of producing electricity through upstream proton diffusion22. This proton diffusion arises from the chemical potential difference between the wet and dry sides of the material, resulting in sustained electricity generation owing to the gradual permeation of water. Despite these advancements, it remains unclear how the various mechanisms identified in different nanomaterials and device geometries can be effectively integrated into hydrovoltaic systems21, or how to design structures that harness them simultaneously. Similarly, previous studies have indicated that combining light and heat can synergistically improve hydrovoltaic performance through enhanced photothermal evaporation7,14,23. On the other hand, in nanofluidic systems with charged interfaces, thermo-osmotic flows can convert thermal gradients into electrical currents24,25. However, one vital area remains largely overlooked: how photocharging and (photo)thermal effects contribute to ion migration, which is a key process for the performance of hydrovoltaic devices6,14. This lack of understanding emphasizes the importance of a fundamental study of light- and heat-driven ion dynamics, potentially revealing new methods to boost hydrovoltaic efficacy.

This work unravels the complex influence of heat and light on EDHV devices, ultimately demonstrating a unified framework for EDHV architectures, instead of mechanisms focused solely on ion streaming at the solid-liquid interface of the evaporating surface. By employing a top evaporating surface and a bottom uniformly structured cm-scale silicon-dielectric (core-shell) nanopillar array (SiNPs, see Fig. 1a), we report major improvements in power output under external heating and solar illumination due to ion thermodiffusion in the electrolyte layer, as well as a combination of the photovoltaic effect and thermally enhanced surface charge at the silicon-electrolyte interface. Through a combination of experiments, numerical calculations, and theoretical modelling, we reveal a mechanism in which thermally and light-assisted ion migration plays a pivotal role in enhancing electricity generation, achieving a state-of-the-art open-circuit voltage of 1 V and an output power density of 0.25 W/m² under optimal conditions with 0.1 M concentrations. Notably, these results are achieved without the need for an additional black absorber14,23.

Overall, our EDHV architecture introduces a device concept and design strategy that leverages thermal and photovoltaic effects to enhance interfacial processes essential for hydrovoltaic energy conversion. By structurally decoupling the top evaporating surface from the bottom nanostructured layer, we establish that the system can operate in a decoupled manner. This architectural innovation represents a significant advancement in hydrovoltaic device design, allowing full exploitation of developments in solar-driven interfacial evaporation14,26 while simultaneously enabling the integration of optimized hydrovoltaic components.

Results
Due to the chemical equilibrium-controlled surface charge, at the oxide-liquid interface, an EDL is formed, and any resulting imbalance in the ion distribution along the SiNP length contributes to the measured electrical potential difference. Interestingly, we previously observed that, due to the closed bottom surface of the nanochannel, the studied geometry presents an intrinsic asymmetry in the surface-charge distribution (SI 8). As a result, even in the absence of an evaporation-induced flow, a chemical potential difference (Φ) exists, and therefore, a Voc can be measured between the top electrode and the bottom SiNPs surface6. Φ is quantified by Eq. (2)), which depends on the temperature (T) and surface charge (σ) of the bottom silicon substrate:

Φ= 2k B T ssinh (cid:2)1 pffiffiffiffiffiffiffiffiffiffiffiffiffiffi σ ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi + σ ð2Þ
8000ϵ 0 ϵ r c 0 k B T s C Stern

where, k , T , e, ϵ , ϵ , c are Boltzmann constant, surface temperature of solid, electronic charge, dielectric permitivity of free space, relative permitivity of the medium, and molar concentration of bulk electrolyte, respectively. σ is the surface charge and C is the Stern capacitance of the Stern layer35. In the following sections, we will demonstrate how the performance metrics of the EDHV devices, specifically open circuit voltage and power density, are influenced by alterations in chemical potential under conditions of external heating and irradiation.

Using a previously validated COMSOL Multiphysics model6, which accounts for the liquid nanoconfinement and incorporates the temperature-dependent equilibrium constants for the oxide/liquid interface (see “Methods”), we calculated the electrostatic potential difference between the bulk electrolyte and bottom SiNPs as a function of temperature. We obtained a linear increase in potential difference with an increase in temperature up to 50 K above room temperature of 298 K (SI 9). Therefore, we first conducted a series of experiments explicitly analyzing the open circuit voltage generated at different temperatures of the bottom SiNPs electrode, denoted as T. To trigger the temperature changes, we utilized an external Peltier heater placed beneath the SiNPs electrode (see “Methods” and SI 10-I). Concurrently, we monitored the temperatures using an infrared camera positioned above the sample.

Fig. 2a provides a time trace of the open circuit voltage of a SiNPs device with N-type low-doping silicon core nanopillars coated with Al2O3. At the beginning of the experiment (dry sample), the voltage was zero. As soon as the electrolyte wets the sample, we observe a gradual increase in voltage until a steady-state value is reached (0.25 V). When we activate the heater (at 125 s), the voltage experiences a noticeable rise, eventually approaching twice the initial value (0.5 V). The corresponding time-trace for T, as recorded by the infrared camera, is depicted in Fig. 2b (empty symbols). As the heater operates, the temperature steadily climbs and ultimately stabilizes around 70°C for the maximum power applied to the heater. Once the heater is turned off, we observe an immediate drop in temperature and Voc. Notably, the cooling rate is slower than the heating phase, which can be attributed to restricted pathways for heat dissipation (Fig. S10-I). It is important to highlight that the temperature of the top electrode, located at the air-water interface, is observed to be slightly lower than the measured T due to the cooling effect of evaporation and the differing thermal environments present at the bottom (heating source) and top (ambient air) of the setup. We quantified this temperature difference as ΔT (see Fig. SI 11). Figure 2b illustrates the time trace of ΔT as T is increased from the ambient temperature of 25°C to 70°C, peaking at around 7 K.

We further examined the slope of the voltage-temperature curve (Fig. S9) across various conditions, including pH, electrolyte concentration, and the initial equilibrium constant (K ), obtaining minimal dependence on these external factors. Indeed, the dV/dT slope is predominantly influenced by the enthalpy of dissociation of the surface groups, Δ , which is the chemical characteristic of the material (Fig. SI2). While this relationship is derived numerically, it underscores a significant physical dependence on the key thermodynamic parameters at play. Thus, we experimentally explored how different surface properties affect the device’s open-circuit performance metrics in relation to T. Figure 2c presents the voltage-temperature profile for two distinct samples that share the same silicon N-type low-doping core but differ in their outer shells, composed of Al2O3 (pink curves) and TiO2 (purple curves), respectively. These experiments were conducted at two concentrations of KCl, specifically 1 mM and 100 mM. Based on the experimental results, Al2O3 displayed a more considerable voltage increase compared to TiO2 for equivalent temperature rises (Fig. 2c), and the slopes remain insensitive to changes in concentration, consistent with the simulation. We observe that the experimental curves present a linear range (approx. up to 20 K), consistent with our COMSOL model, and a super-linear regime at higher temperatures (Fig. SI12 and Table S1). Within the linear regime, we can extract the dV/dT slope and relate it to the enthalpy of dissociation, confirming the expected trend due to the lower enthalpy of TiO2 compared to Al2O3 (Fig. 2d). This behavior clearly stems from the distinct chemical properties of the two materials. Furthermore, the thermal conductivity of the oxide surface—commonly low in TiO2—has minimal impact on the system’s overall behavior (see Fig. SI10-III). As we show later, to model the experimental Voc(T) data beyond the linear regime, it is necessary to account for the complex interplay of the chemical equilibria and the enhancement of the evaporation rates with temperature. This is discussed in the decoupling strategy section, where we develop a comprehensive equivalent electrical circuit and establish an expression for Voc by integrating three distinct phenomena.

As described earlier, the surface charge σ can also be varied at a constant temperature due to dynamic changes in the surface concentration of protons ( H+ ) under irradiation. Thus, we conducted a comprehensive series of measurements to understand the device performance under various illumination conditions and different solid and interfacial properties. We begin by assessing the open circuit voltage of the same samples of the temperature-dependent study, namely N-type low-doping silicon core nanopillars coated with Al2O3 and TiO2. The Voc time trace is shown in Fig. 3a (purple for TiO2 and pink for Al2O3), omitting the transient phase where it rises from 0 V to a steady-state value for improved clarity.

Under ambient conditions, before illumination, the devices show a stable voltage (0.36 V Al2O3, 0.15 V TiO2). Upon exposing the samples to solar illumination (AM1.5, 1 kW/m2), we observed an instantaneous increase in the measured voltage, which stabilizes at a significantly higher steady-state value (0.55 V Al2O3, 0.33 V TiO2). Conversely, when we turned off the light source, the voltage immediately decreased, reverting to its initial value recorded in the dark. To validate the consistency of this response, we performed multiple cycles of switching the light on and off, and each cycle demonstrated a reliable and pronounced rise and fall in voltage. We note here that due to the instantaneous nature of the Voc change upon illumination, photothermal effects are expected to play a minor role. Instead, the photogenerated charges contribute to the observed behavior.

When n-doped silicon is subjected to illumination, upward band bending occurs, accumulating holes at the silicon-oxide interface31 (Fig. 1a panel iii). Simultaneously, on the liquid side, excess charges at the capacitive interface drive the dissociated cations of water, primarily hydronium ions (H3O+), away from the interface. It also creates an attractive force for hydroxide ions (OH-), drawing them toward the interface to neutralize the accumulated holes. Consequently, this process leads to a reduction in the concentration of H+ under illumination, increasing the surface charge (σ) that in turn produces a higher Voc or a positive photovoltage (Vph). Moreover, a differential capacitance of the double layer, C can be defined as the change in surface charge (σ) due to a change in Φ, and mathematically expressed as by C = ∂Φ=∂σ (cid:2)1, which increases with surface charge (see Fig. SI14 for derivation). To quantify the time-dependent changes in total capacitance, which is a combination of the three capacitances as shown in Fig. 1e, we measured the device’s complex impedance in real time at a fixed frequency of 1 kHz (see Fig. SI 15 for details on the measurement and estimating the capacitance). Figure 3a clearly shows that alterations in capacitance triggered by light irradiation, due to changes in the surface charge dynamics, directly correlate with observed increases in Voc.

We then measured the open circuit voltage of the same two low N-doping Si (1–20 Ω.cm) samples for different salinities (from 0.01 mM to 100 mM). Figure 3b presents the photovoltage, defined as Vph = Vlight(cid:2)Vdark, for both materials across varying salinities. Our observations clearly demonstrate that the photovoltage recorded for samples with Al2O3 shells consistently outperformed that of the TiO2 samples across all salinity levels tested. Our observations also reveal a significant decline in photovoltage as salinity levels increase for both sample types. Intriguingly, we further noted that High N-doped silicon samples exhibit photovoltage values that are consistently over 150 mV lower than their low N-doped counterparts (Figs. S15 and S16). Finally, we assessed the photovoltage as a function of combined heating/cooling and irradiation (Figs. 3c and SI17). Interestingly, we observed that, contrary to the open circuit voltage, which increases with temperature, the photovoltage decreases with increasing temperature.

To better understand all of these critical findings and their relationship to the solid-liquid surface charge, we conducted capacitance measurements under all these different conditions. As shown in Fig. 1e, the measured capacitance is linked to three capacitances in series. Firstly, the space charge layer capacitance is directly proportional to silicon doping37. We thus compared the response of two samples with different silicon doping, specifically Low N-doping (1–20 Ω.cm) and high N-doping (<0.005 Ω.cm). As shown in Fig. 3d (blue (T =25°C) and red (T =70°C) shaded areas), the capacitance for the low-doped silicon sample (left two columns) was significantly lower than that of the high-doped silicon samples (right two columns), in agreement with the expected trend. Secondly, the capacitance of the oxide layer is given by C = ε ε =d, where ε is the dielectric constant of the material, and d is the thickness of the oxide. The higher dark capacitance of TiO2 compared to Al2O3 (Fig. 3a, right axis) can thus be related to the dielectric constant of anatase TiO2 being 3-5 times higher than that of Al2O337, explaining the consistently lower photovoltage for TiO2 samples across all the salinity values (Fig. 3b). Thirdly, the EDL capacitance must increase with surface charge (see Fig. SI14 for the analytical expression). By measuring the capacitance at different electrolyte concentrations and temperatures (Fig. SI 18), we confirm that it rises with increased electrolyte concentration and surface charge. This is also in agreement with the observed trend of decreasing photovoltage with an increase in electrolyte concentration due to higher capacitance (Fig. 3b) as well as with the increase in capacitance with temperature for both Low- and High N-doping of Si (Fig. 3d, blue bars, red shaded areas). Overall, these results confirm the key role of light-triggered alterations of the chemical equilibrium at the interface via capacitive photocharging, concurrently underscoring the complex interplay between doping levels, salinity, and capacitance.

To further investigate the interplay between photocharging and interfacial processes, we finally examined how variations in light intensity influence the photovoltage response. As shown in Fig. 4a, due to the capacitive effect, accumulating holes at the silicon-oxide interface drive the dissociated cations of water, primarily hydronium ions (H3O+), away from the interface. This leads to a reduction in the concentration of H+ enabling higher surface charge (σ) that in turn produces a higher Voc or a positive photovoltage (Vph). The number of electron-hole pairs generated is directly proportional to the intensity of the light. However, not all generated carriers will lead to the charging effect as there will be a surface or bulk recombination process, which depends on the interface structure and the energy of generated carriers38. While the detailed analysis of these phenomena is beyond the scope of this manuscript, we notably observe that the number of generated charge carriers is directly proportional to the light intensity, expressed mathematically as n = β λI λ =Eλ, where β λ is the effective number of carriers generated per unit incident photon, Iλ is the incident intensity, and Eλ is the energy of the photon. On the other hand, the concentration of protons on the liquid side is given by the Boltzmann distribution37 as H+ = exp(cid:2)eΦ), which influences the chemical potential according to the relationship30 Φ = (cid:2)log(H+). Assuming the change in H+ is directly proportional to the change in n we can establish the dependence of photovoltage on intensity

V ph = ΔΦ = log(β λI λ =Eλ)

We conducted measurements of photovoltage across various monochromatic light wavelengths, ranging from 450 to 950 nm, as well as the full solar spectrum, across a broad intensity range. The results reveal that the photovoltage exhibits a clear logarithmic dependence on light intensity, with a linear trend observed when plotted on a logarithmic scale (Fig. 4b and Table S2 for fitting parameters). Additionally, we can derive estimates for the parameter β λ at different wavelengths, as illustrated in Fig. 4c, highlighting the selectivity of the wavelengths. Lastly, we have shown in Fig. 4c (blue line) the value of β λ normalized to the absorption of the sample α λ (Fig. S19) to exclude the variation in the amount of light reaching the surface for different wavelengths.

Overall, for a deeper understanding of the underlying mechanisms that contribute to these pronounced light-sensitive behaviors, we need to develop a more comprehensive model of the system, capable of capturing not only the solid-liquid interface but also the light response of the silicon core. In the following section, we introduce an equivalent circuit model and subsequently use it to gain a complete description of the device’s behavior.

Drawing from the mechanistic insights related to the interface, our goal is to enhance the understanding at the device level. We can break down our decoupled device into three distinct regions, each characterized by unique interfacial processes. As illustrated in Fig. 5a, the studied system consists of three key components: the top electrode, the electrolyte layer, and the bottom nanostructured electrode, each defined by its solid/liquid interfaces. At the bottom nanostructured electrode, the coupling of the three surface capacitances (Fig. 1e) leads to a surface charge regulation, whenever either the solid or the liquid side of the interface is perturbed, establishing a non-linear dynamic feedback loop (Fig. SI20). It is essential to recognize that the interaction of surface charges with ion distribution in the electrolyte layer further results in a coupling between the bottom and top electrodes.

As we outline further, the equivalent circuit depicted in Fig. 5b accurately reflects this multi-level coupling, capturing the complex behavior of the hydrovoltaic devices.

Evaporation-induced Ion Streaming at the Three-phase Boundary of the Top Electrode: as depicted within the green rectangle, the top electrode, which serves as the positive terminal for electrical measurements, is only partially immersed in the electrolyte, with the remaining portion exposed to air. This arrangement creates a liquid meniscus and a three-phase contact line around the perimeter of the electrode. The evaporation from this region generates fluid flow along the meniscus. To assess the role of the meniscus at the top electrode, we measured the evaporation rate from our working device with a 1 cm² area SiNP bottom electrode (Low N-doping, coated with Al2O3) under three different conditions: (a) without any top electrode, (b) with a W=0.8 mm (perimeter) top electrode, and (c) with a W=3.2 mm top electrode. We observed that the evaporation rate nearly doubled when introducing the small electrode compared to the scenario without an electrode. Additionally, the evaporation rate increased almost fourfold with the large electrode, which correlates with the perimeter of the three-phase contact line (Fig. S5).

The flow induced by evaporation drives free ions in the liquid’s EDL to stream, which can be represented by a current source, I Evap, with an appropriate resistance in parallel, named R 3ϕ. Equivalently, it can also be represented by a voltage source with R 3ϕ in series (Fig. S21). Physically, the voltage source originates from the three-phase contact boundary that generates an evaporation-rate-dependent contact potential difference between the wet and dry sides of the top electrode39.

We obtained an expression for the current source I Evap in the equivalent circuit (“Methods”, Eq. (7)) that shows that it is indeed proportional to the evaporation velocity (vf). This expression shows that I Evap depends on the charge flux (σ) induced by the direct interaction of polar solvent molecules with the evaporating surface2, as well as ion separation arising due to the chemical potential difference (C Φ) across the electrolyte. To confirm the role of polar solvent molecules in the process, we tested the device using water or ethanol under otherwise identical conditions. The measured Voc values for DI water and ethanol at T equal to 25°C (65°C) are 0.552 V (0.690 V), and 0.195 V (0.336 V), respectively (see Fig. SI22 for more details on the effect of solvent), confirming a clear dependence on the polar solvent molecules’ interaction with the charged surfaces. Overall, these observations indicate the importance of ion streaming at the three-phase boundary created at the top electrode in the system and the need to include it explicitly in the equivalent circuit model.

Chemical Potential Gradient across the Electrolyte Layer: as illustrated in the yellow rectangle, the wetted portion of the top electrode and the bottom SiNPs have different surface charges, resulting in a chemical potential difference (Φ) across the electrolyte layer6. Due to this, the electrolyte region exhibits capacitive effects as the surface charges of either electrode are perturbed by thermal effects or light irradiation. We thus define a transfer capacitance C tr of the electrolyte, which is the capacitance arising from ion transfer across it39. We have obtained an analytical expression for transfer capacitance that depends on the geometrical parameters of the bottom nanostructures as well as the size of the top electrode and the features of the related meniscus regions (see Fig. SI23 for detailed derivation).

Under equilibrium conditions, the chemical potential difference would cease to exist. However, due to the temperature gradient ΔT across the electrolyte layer, the non-zero chemical potential difference persists in the steady-state. Overall, the yellow region can be modeled as a current source driven by the thermodiffusion, IΔT, in parallel with a resistor, which accounts for the ionic resistance of the electrolyte solution R sol, and a capacitor, C tr.

Photovoltage at the Silicon-Oxide-Water Interface: To account for the influence of light, we need to examine the changes in interfacial band bending at the silicon-oxide-water interface as the sample is illuminated. As illustrated in Fig. 4a (right panel), the generation of electron-hole pairs creates a quasi-Fermi level splitting that results in a photovoltage (Vph), as shown in Fig. 3c. As highlighted in Section 3.3, critical factors such as doping, salinity, and the oxide layer non-linearly influence the capacitive photocharging mechanism, which, in turn, has a profound effect on the magnitude of Vph. Therefore, the strength and effectiveness of the photocharging capacitive component are fundamentally encapsulated in the equivalent circuit by the value of Vph, underscoring its crucial role in this phenomenon37,40 (Fig. SI20). This can be represented by a voltage source32,41 or, equivalently, by a current source, I ph, in parallel with a resistance of the photoactive interfacial region (R Si).

Based on the described equivalent electrical circuit, we can derive a few critical equations concerning the device response (full details in “Methods”). These can be used to quantitatively analyze the experimental data and therefore clarify the response of this general model of an EDHV system. Remarkably, the experimental non-linear trend of Voc with temperature (Fig. 2b) can be finally elucidated thank to the obtained expression for Voc (Eq. (4), and “Methods”), which includes the three contributions discussed earlier: (i) evaporation-induced ion streaming, (ii) the chemical potential difference, (iii) photovoltage.

Voc = vf σ r 3Φ + Φ (1 + vf r 3Φ C tr) + V ph

The resistive element R 3Φ = r 3Φ W, where W is the perimeter of the meniscus region (see “Methods”). All quantities in the expression are defined in “Methods”. Notably, both Φ and vf increase with temperature (Figs. SI9 and SI24), thus their product in the second term leads to the observed quadratic dependence of the open circuit voltage on temperature (Fig. S12 and Table S1).

Finally, we investigate the influence of various operational parameters on the power output of our device, emphasizing the effects of temperature, solar illumination, and electrolyte concentration. Figure 6a shows a schematic representation of power curve measurements by sweeping load resistances in the range 100 Ω–70 kΩ. Firstly, the peak value (position) of the power curves increases (shift towards lower resistance) as the environmental conditions change from ambient (T =25°C, no light irradiation) to 1 Sun (T =25°C, 1 kW/m2 light irradiation) and then heat (T =70°C, no light irradiation), as shown in Fig. 6b. Notably, the measured power curves indicate that increasing the concentration of KCl from 1 mM to 100 mM nearly doubles the maximum power output despite a lower open circuit voltage at higher concentrations. Furthermore, as observed in the power curves at varying temperatures (Fig. 6c), the maximum power at 70°C surpasses the ambient temperature output by over five times, demonstrating the profound impact of thermal conditions on device performance. Moreover, the parabolic dependence of power output and voltage (SI 25) across the load resistance underscores the importance of optimizing both aspects to achieve high performance.

The power output is governed by the equivalent electrical circuit, allowing us to derive an expression that captures the relationship between load resistance and output power. The simplification of this expression into a two-parameter family of curves P = A(T,I,c) RL = (B(T,I,c) + RL)2 demonstrates the distinct roles of parameters A and B, which depend on temperature, electrolyte concentration, and solar intensity. By fitting this expression to the experimental data in Fig. 6b, c, we have compiled the values of the A and B parameters for a range of different conditions, as shown in Fig. S26, which can be used to obtain the current and voltage utilized to obtain the power density. The peak power output, represented by P = A=4B, occurs at a specific load resistance RL = B, indicating that careful tuning of these parameters is crucial (see also Fig. SI27 for load line analysis to estimating power). Notably, achieving double the maximum power output at 100 mM compared to 1 mM KCl concentration—despite a lower open circuit voltage—highlights the significant impact of internal resistance on peak power output, as indicated by parameter B in our study model. In fact, the increase in the open circuit voltage with temperature reinforces the need to consider material choices carefully; a transition from TiO2 to Al2O3 yielded remarkable enhancements of 90% and 57% in Voc at 25°C and 70°C, respectively (Fig. 6d). Furthermore, the influence of silicon doping illustrates another pathway for enhancing power output (Fig. S16). High N-doped Al2O3 samples displayed a 28% increase in open circuit voltage over low N-doped counterparts, leading to a 1.6-fold improvement in power output. Lastly, long-term stability tests revealed that the device consistently maintained a steady voltage output for over 50 h. Remarkably, this stable performance persisted even under continuous light exposure, as demonstrated in Fig. 6e, underscoring the robustness and reliability of the EDHV architecture. This finding lays the groundwork for future research focused on material engineering to optimize device performance under various environmental conditions. In summary, the interplay between concentration and material properties presents a rich avenue for improving power output in EDHV devices operating under the influence of external heating and solar illumination.

Methods
Electrical & thermal measurements: As described in Fig. 1a, 5a, and 6a, the SiNPs are used as the active surface, and the Al layer functions as the back electrode, while Ag/AgCl (unless stated otherwise) is employed as the top electrode. We used an Ag/AgCl electrode as it is considered fully reversible, which ensures that the electrodes entirely consume the charges accumulated in its EDL at overpotentials, which are practically zero. There is no unwanted potential difference, which induces a conduction current. The open circuit voltage and complex impedance measurements were done using a CHI bipotentiostat. The impedance measurements were done at zero applied DC voltage with an amplitude of 5 mV at a fixed frequency of 1 kHz (Fig. SI15). The resistance was added to the circuit to measure voltage and power at different load resistances. The bipotentiostat was connected in series or parallel for current or voltage measurements, respectively. For temperature-dependent measurements: by changing the voltage applied to the Peltier element, the device’s temperature varied from an ambient temperature of 25°C to 70°C. Temperature is measured using an Infrared camera (Fortric 600s) with 0.2 frames per second. A type-K thermocouple was used for calibration (Fig. S28). A solar simulator (Newport 66984-300XF-R1 Xe lamp) with an AM1.5G filter was used as the light source for the light-dependent study. For a wavelength and intensity-dependent study, we used the LED solar simulator Ossila lamp (G2009A1). The intensity of the monochromatic light was recorded by a detector (Newport, 818-UV/DB) and a hand-held laser power meter (Newport, 843-R-USB). The electrical measurements were performed similarly to the sample as described above. After, the sample was placed in a DI water bath (maintained at 60°C) for 5–10 min with continuous stirring at 500 RPM. Then, the sample was finally placed in the oven, which was maintained at 80°C. Furthermore, to minimize the effect of salt precipitation on the output, the sweep of concentration was always performed starting from DI water, followed by low concentration and then higher concentrations. Therefore, for the present study, we expect the effect of salt precipitation at high concentrations to be minimal. We have verified the measurement repeatability at 2 M and 4 M KCl concentrations (Fig. S29).

Numerical calculation to obtain the voltage-temperature dependence: We developed a 3D numerical model (COMSOL) to solve the Nernst-Planck-Poisson equation to determine the equilibrium distribution of ions and resulting electrostatic potentials. To perform the simulation, we used the approach described in our previous work6. The simulation details, such as package use and boundary conditions, are given in Fig. SI 30 and Table S3. The following equilibrium reactions govern the amount of surface charge in an oxide-aqueous interface.

MOH + H2O (g) M O (cid:2) + H3O+ . The equilibrium constant, which is temperature-dependent42. The temperature dependence is governed by:

K = K exp (cid:2) Δ H (cid:2) (cid:1) 1 (cid:2) 1 (cid:3) (cid:12)
a a0 R T T0

where the material’s chemical characteristic, Δ H, is the enthalpy of dissociation of the surface groups. We used surface charge density as the boundary condition, which is not a fixed value but is instead governed by the above equilibrium reaction. This results in variable surface charge density that depends on the surface potential at the stern plane35, given by the following equation:

σ = (cid:2)eΓ (cid:1) 1 + 10(cid:2) K pH a (cid:2) e T (cid:3) e k B T Φ 0 (cid:3)

This enabled us to obtain the open circuit voltage as a function temperature for various conditions, such as by varying electrolyte concentration, pH, and K a0. Then, we swept Δ H, and obtained voltage-temperature lines for various conditions. Finally, we constructed the correlation between the slopes of the voltage-temperature lines and the value of Δ H (refer to SI9).

Deriving analytical expression for the performance metrics: The total space charge density per unit area of the meniscus region is the sum of the self-charge density σ = ρ f L 3ϕ (when the electrode was inserted in a bulk electrolyte)2 and the charge density arising due to intermediate electrolyte layer that is equal to transfer capacitance times the chemical potential difference (C tr Φ). Note that σ is not the bound surface charge, but instead free space charge per unit volume ρ f, multiplied by length of the wetted portion of electrode exposed to air, denoted by L 3ϕ (refer Fig. S5). The term I Evap is equal to total charge times vf, which is equal to the evaporative mass flux of the fluid (Figs. SI5 and SI20) divided by density of water.

I Evap = vf ρ f L 3ϕ W + C tr Φ W = W vf σ + C tr Φ

The current driven through the load resistance is obtained by solving the equivalent electrical circuit. The resistive element R 3ϕ = ρ 3ϕ L W 3ϕ = r 3ϕ W 3ϕ, where L 3ϕ and W are the length and perimeter of the meniscus region (see “Methods”). So, we use r 3ϕ instead, as it is independent of top electrode size.

I L = IΔT R Sol (cid:2) 1 + vf r 3ϕ C tr (cid:3) + vf σ r 3ϕ + V ph (cid:2) R Si + R Sol (cid:2) 1 + vf r 3ϕ C tr (cid:3) + r 3ϕ = W + R C + R L

The open-circuit voltage is obtained according to the conditions, I L R L (RL ! 1), and under no current through the external load, we have the relation satisfying IΔT R Sol = Φ. Thus,

Voc = Φ (cid:2) 1 + vf r 3ϕ C tr (cid:3) + vf σ r 3ϕ + V ph

Using Ohm’s law, we obtained the power consumed by the resistive load, and it is given by:

P = (cid:2) IΔT R Sol (cid:2) 1 + vf r 3ϕ C tr (cid:3) + vf σ r 3ϕ + V ph (cid:3) R L (cid:2) R Si + R Sol (cid:2) 1 + vf r 3ϕ C tr (cid:3) + r 3ϕ = W + R C + R L (cid:3) 2 = A (T,I,c) RL (cid:2) B (T,I,c) + RL (cid:3) 2

Therefore, for the present study, we expect the effect of salt precipitation at high concentrations to be minimal. We have verified the measurement repeatability at 2 M and 4 M KCl concentrations (Fig. S29). The maximum power is obtained at the load resistance RL = B, and the maximum power is P max = A=4B, where A and B are functions A and B, as follows:

RL = B (T,I,c) V = A (T,I,c) P max = A (T,I,c) = 4B (T,I,c)

Material and solution preparation: The silicon wafers of different doping (SIEGERT Wafer) were used to fabricate the silicon nanopillar samples as described in Fig. SI 4. The aqueous solutions were prepared using Millipore water (18.2 MΩ cm−1) and KCl (Alfa Aesar, 99% purity). The Ag/AgCl electrode was prepared from silver wire (wire, diam. 1.0 mm, 99.9% trace metals basis) by dipping silver wire into sodium hypochlorite solution for ~1 h.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "For the manuscript titled “A Unified Framework for Harnessing Heat and Light with Hydrovoltaic Devices”, the author\nproposes a promising approach to converting heat and solar energy into electrical power by leveraging both thermodiffusion\nand photovoltaic effects. Specifically, an integrated hydrovoltaic device was constructed, and an equivalent electrical circuit\nmodel was developed to quantify the latter contribution. However, while this work is relatively comprehensive and\ninnovative, it requires significant improvements in comprehensive analysis and in-depth validation, particularly in device\ndesign, material characterization, and theoretical model verification before it can be considered further. The following\ncomments outline key areas that need to be addressed:\n1. A major concern is the efficiency of the proposed system. The author states, “We demonstrate a state-of-the-art open-\ncircuit voltage of 1V and an output power density of 0.25 W/m² at 0.1M concentration.” However, how does this efficiency\ncompare to other similar photoelectric or photothermal-chemical systems? Comparing only with EDHV devices is\ninsufficient. What about the Faraday efficiency and overall energy conversion efficiency of this system? A more detailed\nperformance evaluation with relevant normalized comparison data should be provided against other related systems and\nmethodologies. Refer to Materials Today 42, 178-191(2021).\n2. Related to the above, another issue is the effect of auxiliary heating on system performance. In Figure 2, the output power\nonly increases approximately twofold, from 0.25V to 0.5V, when the temperature is raised via external heating. This increase\nis not particularly significant when accounting for device contact design, error control, and additional energy input. How does\nthis system compare to steam-liquid composite systems, independent photoelectric systems, or standard electrolyte-based\nelectrochemical systems? A more thorough comparative analysis is needed.\n3. The study does not sufficiently address light loss due to steam dissipation. How much light actually reaches the electrode\nsurface? Additionally, what is the wavelength selectivity of light in the presence of vapor dissipation, and how do different\nwavelengths affect the photoelectrode? More discussion and quantitative analysis are needed in this area.\n4. The characterization of electrode materials is insufficient. Only three concentration gradients were analyzed in the doping\ncharacterization, making the results less conclusive due to large experimental uncertainties. Furthermore, in Figure 3C, the\nmeasured photovoltage of TiO₂ is consistently lower than that of Al₂O₃, and its performance decreases with increasing\nconcentration. This suggests that the concentration used was not optimized for maximum activity. The author should\nredesign the experiments to determine the optimal concentration and improve the accuracy of the results.\n5. The study lacks an in-depth analysis of system stability. The author mentions a “partially wetted region”, but what are the\nwettability characteristics of the electrode? Will ions adsorb onto the electrode surface, potentially hindering its\nperformance? Additionally, how do crystal structure and morphology change before and after the reaction? What is the rate\nof steam generation, and how does it affect electrode stability? Long-term stability tests and corresponding results are highly\nrecommended.", "reviewer_2": "The paper focuses on the efficacy of evaporation-driven hydrovoltaic (EDHV) devices, considering a variety of driving forces,\ni.e., involving thermal and ion concentration gradients, as well as illumination. Given an electrolyte as the medium of the\ndevices, it would be expected that potential differences would be generated.\nAt the very outset, the results and the analysis are/have been considered through individual phenomenology while there\nwould be considerable coupling between the forces and inter-dependency. Consequently, the obtained voltages and power\ndensity would be sensitively dependent on the particular system, environment and testing conditions. While the noted\nphenomena have been analyzed in terms of performance metrics, it is unclear as to how they would result in the observed\nenhancements of the voltage, power, etc. For instance, could the observed voltage and power density be predicted from the\nindicated relations?\nA few more specific comments are indicated next.\nThe decoupling of the top evaporating surface from the nanostructures, and related electrodes placed at the bottom, is not\nstraightforward to understand, due to the intervening electrolyte and related electrochemical effects. Is there a Debye length\nrelated correlation, with respect to the various used concentrations? Would not there be a voltage across the EDL rather than\n“along the length of the NP”?\nThe time constants related to the temperature increase and decrease are not easy to understand. Was the Peltier heater\nplaced in the liquid? What accounts for the stabilization of the temperature? How exactly does the convective heat transfer\nplay a role?, say considering the related heat transfer coefficient? What is the role of the respective thermal conductivity\nvalues of the dielectrics used? Typically, TiO2 has a lower thermal conductivity. The interplay of the temperature and the ion\nconcentration is unclear. For instance, can the authors explain clearly what is meant by evaporation-induced ion streaming.\nTo what extent would there be a modification of the liquid diffusion constants of the involved ions? The notion of “ion\ndynamics” needs to be further quantified! How would temperature increase the surface charge linearly? The dV/dT seems to\nbe less sensitive when TiO2 is used. Why would this be?\nHave the authors performed an electrochemical impedance spectroscopy (EIS) analysis? Why was 1 kHz chosen? How\nwas the capacitance monitored and estimated? Light induced charge increase could occur through a variety of factors and\nthe possibilities should be enumerated better. Can the authors consider the possibility of electrolysis? The role of salinity,\nwhich is not clearly defined, should be further elucidated.\nWhen Silicon doping is considered, it would have been worthwhile to use n- and p-doping of the same impurity\nconcentration/resistivity. The magnitudes of the voltage change, say 35 mV, should be explained in terms of the band\nstructure, Else, the values just seem incidental to the performed experiment. When it is stated that “surface charges of either\nelectrode are perturbed by thermal effects or light irradiation”, the meaning is unclear, with respect to whether the charges\ncome off the surface, neutralized, contribute to the EDL, etc.? Are the authors claiming that the P-type Si is inverted, i.e.,\n“through electron accumulation at the interface” – which is highly unlikely in the presented experiments! The instances of\nband bending and their causes should be reviewed again by the authors! Similarly, the “logarithmic” variation of the\nphotovoltage with solar intensity is ambiguous!\nThe definition of transfer capacitance must be clearly quantified. What is the related dielectric permittivity and charge storage\ndistance? A statement such as “thermal motion induces electron transfer between the solid's atoms and the water molecules,\nfacilitated by overlapping of their electron cloud” is imprecise. For the posited “ionization reactions”, what is the standard\nredox potential/s and how does it compare with the overpotentials or observed voltage? The role of solvents must be\nconsidered through the respective polar and/or non-polar attributes. What is the assumed value of the Ka in Eqn. (3)?\nThe authors have come up with an interesting electrical circuit model, in Figure 4(B). However, the coupling of the individual\nphenomena should be clearly indicated as well. The relating of an evaporation velocity to the surface charge is unclear,\ngiven that the surface charge would be bound to the surface. What is the role of electroosmosis? There should be a load-line\nanalysis for the use of the load resistances for the power estimations. evaporation-rate-dependent contact potential\ndifference between the wet and dry sides of\nMany typos should be corrected through the manuscript, e.g., not sure how tunneling is involved, as indicated in the caption\nof Fig. 1(c), as well as several unclear phrases and statements, e.g., “The surface nature is crucial in this relationship”,\n“appears logarithmic-like in nature”, etc.\nIn summary, the paper indicates fascinating interplay of light and heat in an electrolyte, with respect to the generation of\nelectrical voltages and power. However, the interdependence of the various forces is not well explained. Further, the models\nshould indicate or come close to predicting the observed voltage and power values. The authors should then aim, in the next\nrevision, to address these shortcomings.", "reviewer_3": "I have carefully reviewed this manuscript. The authors have conducted innovative research on hydrovoltaic systems.\nBy introducing an intermediate liquid layer, the authors divided the hydrovoltaic system into a surface evaporation layer,\nan intermediate ion-conducting layer, and a bottom silicon nanostructure layer, enabling a relatively independent investigation\nof each component's function. Through a combination of experimental and numerical simulations, the manuscript proposes\nan equivalent circuit model for this system and assigns corresponding circuit components and parameters to each functional\npart. By altering the system's temperature, illumination conditions, and silicon nanostructure surface properties, the study\nreveals mechanisms of ion dynamics, such as light-induced photocharging and thermally-enhanced chemical potential.\nThrough optimization of these conditions, the system achieves an open-circuit voltage of 1V and an output power of\n0.25W/m². Overall, the manuscript presents a rich and innovative study. However, due to concerns regarding clarity and\nother aspects of the manuscript, I recommend major revisions before publication. Below are my specific comments:\n1. Lack of clarity in logic. The study’s innovation lies in introducing an intermediate electrolyte layer to separate the\nhydrovoltaic device into three distinct regions for investigation and in establishing a systematic equivalent circuit for ion\ntransport mechanism analysis. However, the manuscript presents the research in a manner that first describes a large\nvolume of experimental results, then builds the equivalent circuit, conducts numerical calculations, and finally performs\noutput power testing and optimization. This structure fails to highlight the study’s novelty and advantages, making it\nchallenging for readers to follow. I recommend reorganizing the presentation to emphasize the key contributions more\neffectively.\n2. Lack of conciseness in content. In line with the previous point, the manuscript includes a substantial number of\nexperiments to support the proposed model. However, this results in an overly lengthy and complex presentation that\ncompromises clarity. Thus, I suggest moving non-essential content to supplementary materials to enhance the manuscript’s\nconciseness. For example, the fabrication of hydrovoltaic devices using silicon nanostructures has been previously reported,\nso details on device preparation and material characterization could be transferred to the supplementary information (SI).\nSimilarly, in the discussion of temperature and illumination effects on open-circuit voltage, the introduction of electrolyte\nconcentration as a variable appears unnecessary. Please clarify its necessity for explaining the mechanisms, or consider\nplacing it in the SI.\n3. In Section 2.1, the device contains only 250 μL of electrolyte. As the temperature rises, how can it be proven that the\nperformance variations result from temperature changes rather than the rapid evaporation of the solution, which could lead to\nincreased ion concentration?\n4. In Section 3.1, Figure S1 suggests that the introduction of electrodes significantly affects the evaporation rate. However,\nconsidering that the diameters of the introduced electrodes (0.25 mm, 1 mm) are relatively small compared to the original\nevaporation area (~11.3 mm in diameter), how do such small electrodes achieve a twofold or fourfold increase in the\nevaporation rate? Please provide a more detailed explanation.\n5. Ambiguity in the presentation of certain experimental data Figures. Figures 3c and 5e simultaneously use both line and\nbar graphs for the same dataset, making the intended message unclear. In Figure 5b, two separate y-axes represent output\npower, which is confusing and may mislead readers.\n6. Missing or incorrect legends in some experimental data Figures. In Figure 2c, the plot lines and legend color blocks do not\ncorrespond correctly. Figure 2e lacks legends. Figures 3a and 3b also lack sufficient labeling. In Figures 5c and 5d, the\ntemperature indicators are unclear. Please refine these elements for improved clarity.\n7. Lack of explanation for certain schematic elements. In Figure 1, the meaning of the circular dots is not explained.\nAdditionally, the colors of the dots in Figures 1d and 1a are different without explanation. In Figure 4d, the significance of the\nred-white gradient color bar is not clarified.\n8. Missing scale bars and unclear indicators in some Figures. Figure 1b lacks a scale bar. In Figure 1c, the meaning of the\narrows and horizontal lines is unclear.\n9. The reference in Figure 5h is incorrect. Reference 14 describes a device that does not use a silicon nanowire system but\nrather a silica nanosphere system. Please double-check and ensure the citations are accurate.", "reviewer_4": "I co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature\nCommunications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career\nResearchers who co-review manuscripts."}, "author_response": "1 Response to reviewers\n3 have carefully revised the manuscript in accordance with the feedback provided. Below,\n4 we provide point-by-point responses to each comment. Reviewer comments are in\n5 black; our responses are in blue, and changes made to the manuscript are indicated in\n6 red in the revised text.\n10 solar energy into electrical power by leveraging both thermodiffusion and photovoltaic\n11 effects. Specifically, an integrated hydrovoltaic device was constructed, and an equivalent\n12 electrical circuit model was developed to quantify the latter contribution. However, while\n13 this work is relatively comprehensive and innovative, it requires significant\n14 improvements in comprehensive analysis and in-depth validation, particularly in device\n15 design, material characterization, and theoretical model verification before it can be\n16 considered further. The following comments outline key areas that need to be addressed:\n18 “A Unified Framework for Harnessing Heat and Light with Hydrovoltaic Devices.” We\n19 sincerely appreciate the reviewer’s recognition of the novelty and promise of our approach\n20 in integrating thermal and photovoltaic effects for sustainable energy conversion. We are\n21 especially grateful for the time and effort dedicated to providing in-depth feedback on the\n22 device design, material characterization, and theoretical model validation.\n24 further strengthen our work. In response, we have carefully revised the manuscript and\n25 taken concrete steps to address each of the concerns raised. To improve the clarity and\n26 logical flow of the manuscript, we have significantly reorganized the structure to highlight\n27 the central contributions better and guide the reader through our rationale and findings\n28 more effectively. The revised manuscript now follows a clear and logical progression:\n30 phenomena that govern the device’s behavior, which is the central theme of our work.\n32 to affect the voltage generation via thermal or light inputs.\n34 architecture and experimental platform that enable the spatial and functional separation\n35 of evaporation, ion transport, and charge generation processes, a key step to achieve a\n36 comprehensive understanding of the operation of hydrovoltaic devices.\n38 alters interfacial surface charge dynamics, leading to observable changes in voltage.\n40 improve device performance.\n42 influences chemical equilibrium and modulates voltage output. As we discuss later,\n43 contrary to prior works, we do not exploit light to induce photothermal effects and\n44 enhance the evaporation rate. Instead, we focus on how light alters the interfacial\n45 chemical equilibrium.\n47 capacitive photocharging varies with salinity and illumination, providing critical\n48 mechanistic insight into the photovoltaic contribution.\n50 physical and experimental insights, we introduce an equivalent circuit model, explaining\n51 how it maps to each functional component of the device as well as the interplay of these\n52 complex interfacial phenomena.\n54 analyze voltage and power output, showing how the interplay between physical\n55 parameters can be used to predict and optimize device performance.\n57 ensures that the novelty and logic of our approach are communicated clearly and\n58 effectively. Our detailed point-by-point responses are provided below.\n59 1. A major concern is the efficiency of the proposed system. The author states, “We\n60 demonstrate a state-of-the-art open-circuit voltage of 1V and an output power density of\n61 0.25 W/m² at 0.1M concentration.” However, how does this efficiency compare to other\n62 similar photoelectric or photothermal-chemical systems? Comparing only with EDHV\n63 devices is insufficient. What about the Faraday efficiency and overall energy conversion\n64 efficiency of this system? A more detailed performance evaluation with relevant\n65 normalized comparison data should be provided against other related systems and\n66 methodologies. Refer to Materials Today 42, 178-191(2021).\n67\n69 contextualization of performance is important for evaluating a device potential, we would\n70 like to clarify two key points that make direct comparisons with non-hydrovoltaic systems\n71 non-trivial.\n73 electrolyte, making the system fundamentally capacitive—no faradaic reactions occur, as\n74 we've firmly established through our photoelectrochemical tests discussed in the\n75 manuscript. Even in non-passivated conditions and basic electrolyte scenarios, the\n76 possibility of faradaic transformations, such as oxygen or hydrogen evolution, is highly\n77 unlikely under these specific conditions. The overpotential required for these reactions\n78 far surpasses the voltage generated in various scenarios. For example, oxygen evolution\n79 in silicon demands an applied potential of at least 1.2-1.4 V, even under optimal electrode\n80 and electrolyte conditions (Chem. Soc. Rev., 2019, 48, 2158-2181). Thus, our system\n81 distinctly contrasts with typical photoelectrochemical systems, where metrics like\n83 reactions. In our case, enhancement under illumination occurs through charge\n84 accumulation and interfacial capacitive effects, not via redox reactions (Figure R1),\n85 rendering Faraday efficiency an irrelevant metric.\n87 rely on photothermal heating. Instead, we exploit photocharging effects, where light\n88 enhances charge accumulation at the interface by modifying the surface proton\n89 distribution and interfacial potential. This is distinct from systems that rely on enhanced\n90 evaporation via broadband photothermal absorption by resorting to a black light\n91 absorber.\n93 energy recovery across scales, focusing on the fundamental processes that determine their\n94 operation. By using heat and light to selectively modulate interfacial interactions—rather\n95 than driving photothermal evaporation or faradaic reactions—we demonstrate that\n96 interfacial effects in hydrovoltaic systems can be harnessed with better performance than\n97 previously recognized. For this reason, a direct comparison with non-hydrovoltaic\n98 systems would be misleading in this case, as photothermal or additional photochemical\n99 effects could be coupled with the existing system to further enhance its performance.\n101 misinterpretation and to highlight the novelty of our approach.\n103 conversion efficiency relative to Carnot’s efficiency of approximately 3.5% (refer to SI\n104 10), which, although modest, is comparable to other capacitive hydrovoltaic platforms\n105 under similar operating conditions.\nPublished Data Figure Redacted\n106\n108 potassium hydroxide under simulated AM 1.5G illumination (100 mW cm−2) (Reproduced: Chem. Soc. Rev.,\n109 2019,48, 2158-2181). B) Current-Voltage curves under AM 1.5 G illumination of our SiNP electrode in 1 mM KCl.\n112 “…In particular, evaporation-induced hydrovoltaic devices (EDHV) stand out due to\n113 their ability to produce a continuous (24hr) electricity output, operating without\n114 external mechanical energy input across a wide range of environmental conditions. This\n115 is achieved through the synergy of spontaneous capillary action and evaporation,\n116 enabling autonomous, low-intensity energy supply solutions ideal for portable\n117 devices…”\n118 “…In particular, beyond enhancing the evaporation rate through photothermal effects,\n119 it is crucial to comprehend how external heat, and light sources impact the interfacial\n120 processes that are essential for effective hydrovoltaic energy conversion...”\n122 “…Consequently, under illumination, photogenerated charges (electrons or holes)\n123 accumulate at the interface32,33. Due to the capacitive effect of the oxide layer, a\n124 concurrent change in the surface proton concentration will occur, leading to a change in\n125 surface charge. This also highlights the importance of the oxide layer in passivating the\n126 silicon surface34 and preventing any chemical reaction between silicon and water. Our\n127 photoelectrochemical test on the device indeed shows no evidence of faradaic activity,\n128 thereby confirming a capacitive charging, rather than faradaic, process (SI 3)…”\n129\n130 2. Related to the above, another issue is the effect of auxiliary heating on system\n131 performance. In Figure 2, the output power only increases approximately twofold, from\n132 0.25V to 0.5V, when the temperature is raised via external heating. This increase is not\n133 particularly significant when accounting for device contact design, error control, and\n134 additional energy input. How does this system compare to steam-liquid composite\n135 systems, independent photoelectric systems, or standard electrolyte-based\n136 electrochemical systems? A more thorough comparative analysis is needed.\n137\n139 need for comparative performance analysis.\n141 with external heating—may appear modest at first glance. However, we would like to\n142 emphasize that the system's power output increases much more significantly, by more\n143 than fivefold under moderate heating conditions (as shown in Figure 6B of the\n144 manuscript). This is because the power output depends on the square of voltage and\n145 internal resistance of the system. With increase in temperature, there is a synergistic\n146 increase in both factors that leads to a very significant increase in power output.\n148 “The peak power output, represented by , occurs at a specific load\n149 resistance indicating that careful tuning of these parameters is crucial (See also\n𝑃𝑃 = 𝐴𝐴⁄4𝐵𝐵\noa𝐿𝐿d\n= \nli\n𝐵𝐵\nne\n, \nanalysis to estimating power). Notably, achieving double the\n151 maximum power output at 100 mM compared to 1 mM KCl concentration—despite a\n152 lower open circuit voltage—highlights the significant impact of internal resistance on\n153 peak power output, as indicated by parameter B in our study model.”\n155 input, complex system designs, and insulation to achieve boiling and phase transition,\n156 our approach is distinct and advantageous. It operates entirely through surface-driven\n157 thermodiffusion and interfacial effects, using low-grade heat (typically <70 °C)—making\n158 it suitable for integration with ambient heat sources and solar thermal input without the\n159 need for additional infrastructure.\n161 “…In particular, evaporation-induced hydrovoltaic devices (EDHV) stand out due to\n162 their ability to produce a continuous (24hr) electricity output, operating without\n163 external mechanical energy input across a wide range of environmental conditions…”\n165 reactions, our system operates via a non-faradaic mechanism based on capacitive charge\n166 separation and redistribution at solid-liquid interfaces. As we discussed in response to\n167 comment #1, our device differs fundamentally in that it produces voltage through\n168 capacitive ion redistribution. Previous studies have largely enhanced performance\n169 through photothermal evaporation or photoinduced faradaic reactions. In contrast, we\n170 demonstrate that capacitive photocharging and thermally modulated surface equilibria\n171 are dominant mechanisms when interfacial effects are properly engineered.\n172 3. The study does not sufficiently address light loss due to steam dissipation. How much\n173 light reaches the electrode surface? Additionally, what is the wavelength selectivity of\n174 light in the presence of vapor dissipation, and how do different wavelengths affect the\n175 photoelectrode? More discussion and quantitative analysis are needed in this area.\n177 comment #1, we first of all want to emphasize that under light irradiation our\n178 performance change is driven by photocharging effects at the solid/liquid interface and\n179 not by photothermal effects (i.e. evaporation enhancement) or photochemical reactions.\n181 absorption measurement data for the silicon nanopillar sample in SI 19. Additionally,\n182 we have provided the absorption measurement of the original silicon substrate as a\n183 reference (Figure R2).\n184\n187 the manuscript, where we explain in detail the intensity variation, wavelength selectivity\n188 on photovoltage, and the amount of light reaching the electrode surface. Our results\n189 confirm that light has predominantly a photocharging effect on the system, an\n190 observation never reported before for hydrovoltaic devices.\n191\n193 monochromatic incidences as a function of light intensity, plotted in logarithmic scale. I0 is equal to 100 mW/cm2. The points corresponding to solar is the measured photovoltage for the full solar spectrum. The experimental data\n194 points are shown in circle, while the line is the linear fit. C) The black curve is the measured photovoltage for\n195 different at 7 mW/cm2. The red curve is the estimated from the linear fit. The blue curve is the value of\n196 normalized to absorpta 𝛽𝛽 n𝜆𝜆ce of the sample. 𝛽𝛽𝜆𝜆\n𝛼𝛼𝜆𝜆\n199 “To further investigate the interplay between photocharging and interfacial processes, we\n200 finally examined how variations in light intensity influence the photovoltage response. As\n201 shown in Figure 4D, due to capacitive effect, accumulating holes at the silicon-oxide\n202 interface drive the dissociated cations of water, primarily hydronium ions (H O+), away\n3\n203 from the interface. This leads to a reduction in the concentration of enabling higher\n+\n204 surface charge (σ) that in turn produces a higher V\nOC\nor a positive p h\n[𝐻𝐻\noto\n]\nv𝑆𝑆oltage (\nℎ\n). The\n205 number of electron-holes pairs generation is directly proportional to the intensity𝑝𝑝 of the\n𝑉𝑉\n206 light. However, not all generated carriers will lead to the charging effect as there will be\n207 surface or bulk recombination process, which depends on the interface structure and the\n208 energy of generated carriers38. While the detailed analysis of these phenomena is beyond\n209 the scope of this manuscript, we notably observe that the number of generated charge\n210 carriers is directly proportional to the light intensity, expressed mathematically as\n211 , where β is the effective number of carriers generated per unit incident\nλ\n𝑛𝑛ℎ ~ 𝛽𝛽𝜆𝜆𝐼𝐼𝜆𝜆/𝐸𝐸𝜆𝜆\n212 photon, I is the incident intensity, and E is the energy of the photon. On the other hand,\nλ λ\n213 the concentration of protons on the liquid side is given by the Boltzmann distribution36\n214 as , which influences the chemical potential according the\n+ 𝑒𝑒𝑒𝑒\n215 relat [i𝐻𝐻ons]h𝑆𝑆 i~p 3e0x p (−𝑘𝑘𝐵𝐵𝑇𝑇) Assuming the change in is directly proportional to\n+ +\n216 the change in\n𝜙𝜙 ~ −\nw\nlo\ne\ng (\n[𝐻𝐻"}]

Decision letter