Operando X-ray imaging reveals size-dependent evolution of cobalt oxide thermochemical material during thermal redox cycles

Domain: physics
Published: 2025-12-17
Editorial outcome: minor_revision

Abstract
Multivalent metal oxides are promising thermochemical materials (TCMs) for energy storage and conversion owing to their high energy density, air compatibility, and high-temperature stability. Co3O4 serves as a model system for examining particle-size-and structure-dependent redox behavior. While particle size and porosity are known to affect performance, their interplay and the kinetics of pore formation during cycling remain unclear. Here we show the chemical and 3D morphological evolution of Co3O4 micro-and nanoparticles during redox cycles at 800–900 °C using thermal analysis, in-situ synchrotron transmission X-ray microscopy (TXM), and scanning electron microscopy. Thermal analysis shows that nanoparticles re-oxidize more rapidly than microparticles at 800 °C. In-situ nanotomography and chemical imaging reveals that nanoparticles undergo redox conversion without forming internal pores, whereas microparticles develop isolated porosity during reduction. These pores persist through re-oxidation, correlating to a lower conversion rate in subsequent cycles. Our results demonstrate distinct degradation kinetics in Co3O4 micro-and nanoparticles, underscoring the critical role of particle size and porosity in redox performance and informing strategies to enhance the long-term efficiency of metal oxide TCMs.

Introduction
As the global energy landscape shifts towards sustainable sources, the need for efficient and durable thermal energy storage (TES) materials is becoming increasingly critical in many applications, such as concentrated solar power systems1,2. Among TES materials, thermochemical materials (TCMs) have gained significant attention in recent years due to their competitive energy density and capability to operate at higher temperatures3,4. Multivalent metal oxides undergoing redox reactions, typically in an open system at temperatures above 700 °C, are promising TCMs because they can operate with air as the working fluid5,6.

Multivalent metal oxides have emerged as promising TCMs for TES systems because of their high energy storage capacity, favorable reaction reversibility, suitable redox temperatures, and cost-effective working atmosphere7–10. However, challenges such as limited material reversibility and performance degradation over multiple cycles remain11–13. Among these oxides, Co3O4 is an ideal candidate for mechanistic studies, despite its relatively high material cost. Its well-characterized redox behavior14 enables clear evaluation of reaction kinetics and pathways at the nano-and meso-scales, providing insights that can guide the development of more cost-effective TCMs. One of the degradation issues is structural deformation, such as cracking and fragmentation, induced by thermal cycling, likely resulting from repeated thermal expansion and contraction15,16. Another common degradation mechanism in Co3O4 is the sintering of particles at elevated temperatures, which impedes diffusion of gaseous species and leads to reduced storage capacity11,12. Common mitigation strategies, such as reducing the initial particle size7,17,18 or introducing a porous structure7,16,19, have been applied to Co3O4 and doped Co3O4 TCMs to enhance their performance. While a porous structure is generally believed to improve redox rate by increasing surface area and facilitating gas transport, recent studies suggest that its benefits may not always be straightforward. For instance, a Co3O4–based porous, foam-like structure with a pore size of 1–1.5 mm exhibited a lower conversion rate during thermal cycling compared to a dense structure; furthermore, the porosity of both dense and porous Co3O4 changed after 10 thermal redox cycles15. These findings highlight that, beyond simply introducing porosity, it is critical to ensure the stability of the porous structure throughout the thermal cycling. Recent studies suggest that micro-and nano-structuring strategies and the addition of stabilizers can help maintain effective thermal cycling performance20,21. Similarly, nanoparticles are generally believed to improve Co3O4 conversion rate by increasing reactive surface area and reducing diffusion distances7,11. Therefore, it is important to track the evolution of the porous structure within particles with different sizes during thermal cycling to better understand their conversion efficiency. However, the kinetics of the pore evolution, both within and between individual particles, especially the isolated pores, remain poorly understood. Traditional technique, like the Brunauer-Emmett-Teller (BET) method based on adsorption isotherms of nonreactive nitrogen or argon22, commonly used for porosity measurements, has limitations in analyzing internal and isolated pores at the sub-particle level. As a result, the influence of particle size and isolated pores on the chemical and morphological evolution of Co3O4 during thermal cycling has not been thoroughly explored, partly due to the challenges in characterizing intermediate morphological and oxidation state changes at the micron and nanometer scales in situ during the thermal cycling.

Synchrotron transmission X-ray microscopy (TXM) has been employed in various studies to characterize the morphological evolution of materials. For instance, in battery research23,24, it allows for direct 3D imaging of a range of materials under real-time cycling conditions. Additionally, changes in material interfaces, such as coarsening25 and alterations in the pore/ligament network26 over time, can be captured and quantified. Moreover, the spatial distribution of chemical information and oxidation states in materials can be directly visualized and quantified using X-ray absorption near-edge structure (XANES) imaging, a spectroscopic imaging technique27,28. These time-resolved synchrotron-based techniques can capture the morphological evolution and spatially resolved chemical changes of Co3O4 during thermal cycles at sub-30 nm resolution, providing insights into how morphological changes under high-temperature thermal cycling affect the thermal redox reaction.

In this work, Co3O4 micro-and nano-particles were selected to study their chemical and morphological evolution, as well as their reversibility during thermal redox cycles. Since the transition temperature of Co3O4 to CoO was reported to be 885 °C13, the temperature range for the thermal redox cycle in this study was set between 800 and 900 °C. At the macro-scale, thermal analysis was performed on these two materials using thermogravimetric analysis (TGA). At the micron to tens of nm length scale, the morphological and chemical evolution of the materials in an air atmosphere during thermal redox cycles was studied using in-situ TXM and 2D XANES imaging techniques. For further analysis, the in-situ samples after thermal redox cycles were analyzed using scanning electron microscopy (SEM). Through the investigation and analysis of the morphological evolution and chemical changes of Co3O4 in different particle sizes at various scales, the fundamental phase transition and degradation mechanisms of Co3O4 TCM during thermal redox cycles in air are discussed.

Results
TGA results
To investigate the reversibility and kinetics of the conversion between Co3O4 and CoO, the redox behaviors of Co3O4 micro and nanoparticles were analyzed by TGA in one and five thermal redox cycles between 800 °C and 900 °C. The results are shown in Fig. 1.

As shown in Fig. 1A, B, both the micro and nanoparticles of Co3O4 rapidly converted to CoO at 900 °C during the first cycle, as indicated by the significant weight loss accompanied by O2 evolution. The theoretical calculation shows that the expected weight loss in the full conversion of Co3O4 to CoO is 6.6 wt%, following the reaction shown in Eqs. (1, 2).

Reduction: 2Co3O4 + ΔH T > Tc 6CoO + O2(g) (1)

Oxidation: 6CoO + O2(g) T < Tc 2Co3O4 + ΔH (2)

Where T is temperature and Tc is transition temperature. The normalized weight was calculated as the ratio between the difference of the theoretical and actual weight losses to theoretical weight loss, and the experimental results are presented in Fig. S1. During the cooling process, the reversed direction of the reaction (2) took place. Initially, there was no significant weight change for the particles at 850 °C. To further investigate the temperature of the re-oxidation reaction, additional TGA scans were conducted under a controlled cooling rate of 2 °C/min, and the result is shown in Fig. S2. But at 800 °C, the nanoparticles increased in weight rapidly and fully converted to Co3O4 in approximately 5 min. In contrast, the microparticles increased in weight at a slower rate, and did not fully convert even after 30 min. To further examine the conversion fraction of CoO during the re-oxidation process, we performed additional simultaneous TGA–DSC experiments, with the results presented in Fig. S3. As shown in Fig. 1C, D, there was no significant difference in the weight change for the Co3O4 particles over five cycles. Additionally, the derivative of mass change remained consistent across the five cycles for both the micro-and nanoparticles, indicating that the conversion rate of Co3O4 did not change and that both particle types retained their reversibility throughout the cycles. Therefore, there was no obvious degradation in the micro and nanoparticles of Co3O4 during the short-term thermal redox cycles under the current cycling conditions, which is consistent with the literature data19.

Chemical evolution analyzed by in-situ 2D XANES imaging
To study the chemical evolution and kinetic differences between Co3O4 microparticles and nanoparticles during thermal redox cycles, 2D XANES images were collected at various time points in the temperature range of 800 to 900 °C at the FXI beamline. Fig. 2, Supplementary Movie 1 and Supplementary Movie 2 show the fitted 2D XANES images of Co3O4 microparticles and nanoparticles, with each pixel corresponding to the atomic fraction of Co in the CoO phase, based on the white line positions. This was determined by the linear combination fitting of normalized XANES spectra of CoO and Co3O4, and the fraction of CoO spectrum used in the fitting corresponds to the atomic fraction of Co in the CoO phase; for simplicity, the term “fraction of CoO” will be used for the remainder of the manuscript.

In Fig. 2A, an early full conversion of Co3O4 to CoO was observed in the microparticles during the first cycle at 900 °C within a short time (~3 min), which is consistent with the TGA results (Fig. 1). When the temperature cooled down to 850 °C, CoO gradually converted back to Co3O4 through reoxidation. Detailed XANES spectra at different locations, from the center region to the surface, are shown in Fig. S4. However, CoO did not fully convert back to Co3O4 after 55 min, indicating a kinetically limited reoxidation process. The incomplete reoxidation process and the resulting chemical heterogeneity can be visualized in Fig. 2B: the region of interests (ROIs) in the enlarged view of Fig. 2A–h, along with the corresponding spectra, identifies a mixture of the Co3O4 (purple) and residual CoO (yellow). Fig. 2C shows the temperature profile of the imaging data collection from Fig. 2Aa–p. In the in-situ 2D XANES analysis, the conversion from CoO to Co3O4 occurred at ~850 °C, as shown in Fig. 2Ae–h, but this re-oxidation process did not initiate in the TGA analysis at this temperature. A separate DSC thermal analysis determined that the re-oxidation process of the microparticles initiate at ~850 °C, as shown in Fig. S5. Literature reports the onset re-oxidation temperature as 850 °C12, 870 °C13, and 879.7 °C5. These variations can reasonably be attributed to kinetic factors such as sample geometry, mass, and heat transfer behavior. Therefore, 850 °C is likely the equilibrium temperature during the re-oxidation process in the TXM experiment. If the experimental temperature is slightly below this equilibrium temperature, it may promote the conversion to Co3O4, whereas if it is slightly above, the conversion may be inhibited.

Since the reoxidation process was incomplete, the temperature was further decreased to 800 °C, with results shown in Fig. 2Ai–l. At 800 °C, most CoO converted back to Co3O4 within a short period of time (~3 min), but a small amount of the CoO did not convert back to Co3O4 after 21 min. In the subsequent cycle, when the temperature was increased back to 900 °C, the conversion rate of Co3O4 to CoO was significantly decreased compared to the first cycle at 900 °C. It can be seen in Fig. 2Am–p that the reduction process took longer in the second cycle, with a small amount of Co3O4 not converting to CoO after 30 min.

To study the CoO nanoparticles, 2D XANES imaging with a similar temperature profile (Fig. 2F) as microparticles was conducted at the FXI beamline, with the results shown in Fig. 2D, E. As shown in Fig. 2D, the CoO nanoparticles rapidly converted to CoO within the first 3 min during the first cycle at 900 °C. However, upon cooling, the CoO phase did not fully convert back to Co3O4 within 30 min at 850 °C, leaving a small amount of the nanoparticles unreacted. The normalized XANES spectra extracted from the selected ROIs from images, as shown in Fig. 2E, indicate that some CoO phase remained in the particles, particularly in ROI-2. When the temperature was further lowered to 800 °C, most of the CoO converted to Co3O4 within ~3 min. Notably, in the second cycle at 900 °C, the conversion rate of CoO nanoparticles was faster than that of the microparticles, with most of Co3O4 converting to CoO within ~3 min, which was in the same conversion rate as the first cycle. Since the specific surface area (surface area per volume) of nanoparticles is larger than microparticles, there is a larger amount of the interfaces between air and nanoparticles where the oxidation process can take place. Consequently, the rate of the re-oxidation process was faster in the nanoparticles, leading to a faster conversion rate between Co3O4 and CoO during the thermal redox cycles.

To quantify the conversion rate of the Co3O4 micro-and nanoparticles, the amount of Co (arbitrary unit, proportional to the mol. of Co) in each pixel of the 2D XANES images was calculated. The fraction of CoO in the total sample and the conversion depending on the amount of Co, during the thermal redox cycles, are shown in Fig. 3, for both the micro-and nano-particles.

Figure 3A shows that the conversion rate of Co3O4 microparticles to CoO at 900 °C is faster in the first cycle (reaching >95.0% in ~25 min after the temperature reaching 900 °C) than in the second cycle (reaching only ~60.0% in ~25 min). In contrast, ~95.0% of Co3O4 nanoparticles converted to CoO within 2 min at 900 °C in both the first and second cycles, as shown in Fig. 3B. The conversion rate significantly decreased for microparticles during the second cycle but remained unchanged for nanoparticles, possibly due to morphological changes in the microparticles during the first thermal cycle.

In Fig. 3C, microparticles in regions with higher Co amount (thicker regions) converted to Co3O4 to a greater extent (in fraction) than those with less Co amount (thinner regions) at 850 °C and 800 °C. This might be because the specific surface area and surface curvature increase significantly in the thicker regions at 900 °C, promoting conversion to Co3O4 when the temperature is lowered. The larger specific surface area may be due to the thicker region being composed of a large number of small particles. As shown in Fig. 3D, the thicker and thinner regions of the nanoparticle sample exhibited similar conversion rates when the temperature was lowered to 850 °C and 800 °C, suggesting that this morphological evolution did not occur in nanoparticles at 900 °C. To better understand the differences in redox behavior between micro-and nanoparticles, the morphological changes during thermal redox cycles will be discussed in the following section. Interestingly, both micro-and nanoparticles converted to Co3O4 back and forth at 850 °C (green-color dash rectangles in Fig. 3C, D), indicating that 850 °C is the equilibrium temperature for the re-oxidation process.

Morphological evolution analyzed by in-situ X-ray nano-tomography
To understand the morphological evolution with time of Co3O4 micro and nanoparticles, the in-situ X-ray nano-tomography data were collected at the endpoint of each temperature segment. The 3D volume rendering, as well as the corresponding 2D XY and XZ pseudo-cross-sectional views of Co3O4 micro and nanoparticles during the thermal redox cycles at different temperatures, are shown in Fig. 4.

In microparticles, as shown in Fig. 4A–C, several large particles were observed in the first cycle at 800 °C before any chemical evolution, and no porosities were present inside the particles. However, after ramping the temperature to 900 °C, cooling to 850 °C, and then down to 800 °C, porous structures appeared within the particles, as shown in the detailed 2D XY and XZ views shown in Fig. 4A, B. Figure 4C shows the 3D volume rendering of the particles, with the internal and isolated pores displayed in the sub-figures. Internal pores formed within a particle because of O2 evolution, whereas isolated pores originated from sintering. At 850 °C, the volume of internal and isolated pores (shown in magenta) increased significantly within the particles during the back-and-forth conversion between Co3O4 and CoO. This conversion process likely promoted sintering, causing the particles to connect and form large isolated pores. The volume fraction of internal and isolated pores (calculated as the volume of internal pores divided by the volume of particles and internal and isolated pores) was 8.2% at 850 °C, decreasing to 7.2% at 800 °C due to more CoO being converted. These internal and isolated pores likely inhibited the reduction of Co3O4 to CoO during the second cycle at 900 °C. However, this back-and-forth conversion was not observed in the TGA results, suggesting that fewer internal and isolated pores were generated within the particles. Thus, the subsequent reduction process remained as fast as in the first cycle. A detailed discussion of internal and open pores is provided in section 2.4. These porous structures persisted in the particles even after completing the thermal redox cycles and returning to room temperature. In contrast, these porous structures were not observed in the nanoparticles during the thermal cycles, as shown in Fig. 4D–F. The nanoparticles retained their original morphology without agglomeration or merging after the thermal redox cycles. To further understand the morphological evolution of the microparticles and nanoparticles during the thermal cycles, the surface area and volume changes for these two samples as a function of the thermal cycling are shown in Fig. S6.

Based on the chemical evolution kinetics shown in Figs. 2, 3, the formation of a porous structure in the microparticles may have hindered the conversion from Co3O4 to CoO during the second cycle at 900 °C, as the slower conversion rate was not observed in nanoparticles. While porosity can increase the surface area and potentially enhance the interaction between cobalt oxide and oxygen, the internal and isolated pores likely contribute, affecting the overall conversion process. The porosity evolution will be further explored in the following sections.

Porosity evolution and impact on Co3O4/CoO conversion during thermal redox cycles
To fully understand the mechanism behind the formation of the porous structure inside the Co3O4 microparticles, another in-situ X-ray nano-tomography experiment of Co3O4 microparticles during thermal redox cycles between 800 °C and 900 °C was conducted at the FXI beamline. A single Co3O4 microparticle was continuously measured with X-ray nano-tomography throughout the thermal redox cycles, and the morphological evolution of the particle and porous structure visualized in 3D are shown in Fig. 5, Supplementary Movie 3 at different temperatures and time points.

A smooth surface was observed on the particle at room temperature, as shown in Fig. 5Aa, but it became rougher when the temperature was raised to 900 °C, shown in Fig. 5Ac, d. This surface character did not change significantly during the following thermal redox cycle (Fig. 5Ae–h). Since both the surface area and volume of the single particle changed due to the O2 evolution, here, the specific surface area (SSA) was calculated by dividing the surface area (including from both internal and open pores) by volume to characterize the surface and porosity properties of the particle. The plot of SSA versus time is shown in Fig. 5B, overlaid with the temperature profile during the thermal cycling. The specific surface area increased significantly at the beginning of the first cycle at 900 °C, indicating that smaller pores were generated inside the particle with O2 evolution. O2 evolution could lead to a sudden generation of a large amount of vacancies, which then diffuse through the lattice, forming the initial small pores when there is excess concentration of vacancies29.

Following the initial rapid generation of pores, there was then a sudden decrease in specific surface area at 900 °C observed at ~6 min (as indicated by the green arrow in Fig. 5B), which might be due to the coarsening process of the surface with high curvatures, corresponding to the small features such as pores generated from the O2 evolution30. The continued evolving oxygen gas caused the pores to grow further, eventually slowing down and stopping after 12 min of heating the sample at 900 °C, as evidenced by the steady decrease in specific surface area. Coarsening became the dominant process after 12 min at 900 °C, with smaller pores merging into larger ones and larger pores interconnecting to form pore networks, which will be further discussed in Fig. 5E. The driving force for coarsening here is to reduce the total surface energy of the system by reducing the amount of the surface31.

To further understand the kinetics of coarsening in the Co3O4 particle, the power-law relationship between the characteristic length (lc), which is reciprocal of specific surface area and coarsening time (tc) was determined to provide insights into the coarsening mechanism. The lc for materials with complex morphology has been used to analyze the morphological evolution of materials26,32. The coarsening time is determined relatively from the time when the temperature reached 900 °C. The power (n) was determined by fitting the experimental data to the following Eq. (3)26:

lc^n = kt (3)

where different values of n correspond to different mechanisms: n=3 for bulk diffusion, and n=4 for surface diffusion26,33,34. Other coarsening mechanisms, such as viscous flow and evaporation/recondensation, were not considered in this study. The fitting line was set to intercept at the origin, as coarsening likely began when the temperature was raised to 900 °C. As shown in Fig. 5C, D; the fit of lc4 versus t exhibited a higher goodness-of-fit (R2=0.96) than lc3 versus time (R2=0.70). This result indicates that surface diffusion is the rate-determining mechanism controlling coarsening in the microparticles under this condition33.

Figure 5E shows the morphology of pore formation inside the particle in a sub-region, as marked by a red dashed cube in Fig. 5Ac. In the region highlighted by a red circle, a small internal pore formed and continued to grow due to the evolution of O2 gas, which could potentially increase the O2 partial pressure within the pore. This early stage of morphological evolution was dominated by the kinetics of gas evolution and vacancy diffusion through the lattice (bulk diffusion) rather than surface diffusion coarsening. Following this initial small pore formation, to minimize surface energy, ions on the particle surface migrated from regions of high curvature, where there are sharp features and a higher chemical potential, to regions of lower curvature, where there are smoother features with a lower chemical potential. The curvature evolution will be further discussed in Fig. 6. As a result, the pore merged with another nearby pore through surface diffusion. Over time, the connected pores grew and the surface became smoother, ultimately forming a more stable microstructure.

Figure 5F, Supplementary Movie 4 show the evolution and changes of open and internal pores within the particle during the thermal cycles, and Fig. 5G illustrates the change in the volume of open pores and internal pores over time. During the O2 evolution process in the first cycle at 900 °C, both internal and open pores formed simultaneously. Open pores that opened to the air facilitated the evolution of O2 during the conversion to CoO with an enlarged active surface area. Conversely, internal pores trapped O2, increasing its local concentration and thermodynamically inhibiting the conversion. In the subsequent stage, the morphological evolution was dominated by the material coarsening process. The volume of open pores decreased during this stage, possibly due to the densification process accompanied by the coarsening. Additionally, the volume fraction of the internal pores increased slightly, indicating that a small amount of the open pores may be enclosed by the surrounding material, transforming into internal pores. After 83 min of isothermal heating at 900 °C in the first cycle, both internal and open pores were still observed in the particles.

At 800 °C, the volume fraction of the open pores decreased, while that of the internal pores increased slightly. CoO near the open pores readily reacted with O2, promoting its re-oxidation to Co3O4. As the density at room temperature of CoO (6.44 g cm−335) is larger than that of Co3O4 (6.11 g cm−336), the oxidation process caused the particle volume to increase, reducing the volume of open pores, consistent with our findings here. Literature has described this CoO reoxidation process involves displacement reaction and ambipolar diffusion of Co ions and electrons37,38. For the internal pores, it has been confirmed with TEM that there is no pore formation from reoxidation of CoO back to Co3O439, and thus the increased volume of internal pores at 800 °C was likely due to the enclosure of open pores from the coarsening process.

Figure 7 shows 3D XANES analysis of Co3O4 microparticles quenched after the second reduction cycle at 900 °C for 30 min, preserving the high-temperature phases. (A) 3D volume rendering based on peak position fitting, showing lower peak position values (corresponding to the CoO phase) predominantly at the particle surface, while higher values (Co3O4 phase) remain in the interior; (B) Representative image slices in XY view from the 3D XANES data, illustrating the spatial distribution of CoO and Co3O4 phases, as well as the presence of internal/isolated and open pores, Z=0 is defined as the bottom of the sample in z direction in (A); (C) The enlarged view in the white dash rectangle in the X-Y views in (B) at Z=6.63 and 6.89 μm.

In Fig. 7A, the color in the 3D volume rendering represents the peak position of the XANES spectra at the Co K-edge. A peak position of ~7.726 keV corresponds to a region fully converted to the CoO phase, while a position of ~7.730 keV corresponds to unconverted Co3O4. Since the high-temperature phases were preserved during quenching, the surface regions indicate full conversion to CoO due to the easy release of O2. In contrast, the interior regions, containing internal and isolated pores that trap O2 and increase the local O2 partial pressure, remain largely unconverted as Co3O4. The subfigure highlights regions with approximately 40% CoO (mole fraction). In the innermost region, the material remains entirely as unconverted Co3O4. To further illustrate the spatial distribution of CoO and Co3O4 phases, as well as the presence of isolated and open pores, representative slices in XY view are shown in Fig. 7B. The enlarged view in the white dashed rectangle in the subfigures (Z=6.63 and 6.89 μm) is shown in Fig. 7C. Regions near open pores appear purple, indicating the presence of CoO, while areas adjacent to isolated pores appear red or yellow, indicating the retained Co3O4. Therefore, the open and internal/isolated pore structures play a critical role in the conversion process: while open pores facilitate gas exchange and promote the reduction reaction, isolated and internal pores likely inhibit the conversion of Co3O4 to CoO by trapping evolved O2, increasing the local oxygen concentration and thereby suppressing further reduction of Co3O4.

To summarize the mechanism of porous structure formation in the Co3O4 microparticle sample and the influence of internal and isolated pores on the subsequent reduction process, a schematic illustration is shown in Fig. 8.

In summary, when Co3O4 microparticles are heated to high temperatures, multiple types of pores are generated. Open and internal pores form because of O2 evolution, followed by vacancy diffusion and subsequent coarsening. Isolated pores develop between particles due to sintering. Upon cooling to lower temperatures, some open pores may transform into closed pores due to the volume expansion associated with the re-oxidation of CoO to Co3O4. During subsequent heating, these closed and internal pores inhibit the reduction of Co3O4 to CoO by trapping the evolved O2, which increases the local oxygen concentration and thereby suppresses further reduction. In contrast, this porous structure is not observed in the Co3O4 nanoparticle samples.

The commonly accepted benefit of a porous structure lies in the formation of open pores, which facilitate oxygen release to the surrounding atmosphere. In our study, the volume of open pores is significantly higher than that of internal pores. However, the impact of internal and isolated pores should not be overlooked, as their ability to trap evolved O2 gases can undermine redox performance. In addition to their role in trapping oxygen, internal and isolated pores can also negatively decrease the thermal conductivity of the material. This reduction in thermal conductivity can hinder efficient heat transfer within the particle, potentially slowing the temperature rise required to drive the endothermic reduction of Co3O4. A number of studies have demonstrated this inverse relationship between porosity and thermal conductivity41–43. However, in the present study, the sample consists of a thin particle layer attached to the inner wall of a quartz capillary and is heated via radiative transfer from an external furnace. Due to the small sample volume and the predominance of radiative over conductive heating in this configuration, we believe the impact of isolated pores on thermal conduction is negligible in our case.

Post-TXM experiment analysis with SEM for particle sintering
To validate the morphological changes observed via X-ray nano-tomography, Co3O4 microparticles were subsequently characterized using SEM. For SEM imaging, the microparticles were examined at room temperature directly on the quartz capillaries used for the X-ray experiments, as shown in Fig. 9A, B. Initially, the microparticles were imaged before thermal cycling. As shown in Fig. 9C, the uncycled microparticles exhibited flat, sharply faceted surfaces. In contrast, after one thermal redox cycle (heating to 900 °C, cooling to 800 °C, and then returning to ambient temperature), the particle surfaces became considerably smoother and less faceted, as shown in Fig. 9D. This change in surface morphology resulted from a surface smoothing and coarsening effect during the high-temperature thermal redox cycle, driven by the minimization of total surface energy, as also discussed in the X-ray imaging analysis (Fig. 5)44. Notable particle sintering11,12 was also observed after one cycle, with the apparent merging of small, discrete particle units into larger, continuous microstructures. Both surface coarsening and sintering are likely to contribute to the decrease in specific surface area during thermal redox cycling of Co3O4 as a thermochemical material.

Methods
Experimental procedure of thermal analysis
The Co3O4 microparticles (<10 μm, 99.0%, Sigma-Aldrich) and nanoparticles (<50 nm, 99.5% trace metal basis, Sigma-Aldrich) were used in the experiments. The thermal redox cycles of Co3O4 micro and nanoparticles were evaluated using a thermogravimetric and differential scanning calorimetry analyzer (TGA, Mettler Toledo TGA/DSC 3+) at atmospheric pressure. The schematic TGA experimental setup is shown in Fig. 10A. Approximately 3.0 mg of sample was loaded into a 70 μL alumina crucible and thermally cycled between the temperatures of 800 °C, 850 °C and 900 °C. The temperature was initially kept at 800 °C19 to remove impurities from the particle surface. A ramping rate of 50 °C/min was applied during both the heating and cooling cycles. Throughout the tests, sample mass and temperature were monitored at a sampling rate of 1 data point per second.

In-situ synchrotron X-ray nano-tomography and XANES imaging
The schematic of the in-situ synchrotron TXM setup with the capillary sample preparation is shown in Fig. 10B.

The TXM sample preparation of the micro and nanoparticles follows the procedure described below. First, the Co3O4 particles were loaded into an open-ended quartz capillary (Charles Supper, 05-QZ) with a 500 μm outer diameter and 10 μm wall thickness. After filling, the particles were poured out, leaving only a thin layer adhered to the inner wall to ensure the collection of a high-quality transmission signal. The funnel end was then removed, resulting in a 20 mm long capillary containing the remaining particles. Afterward, the capillary was attached to an alumina tube (2 mm OD, 1 mm ID, 28 mm length) using an alumina-based ceramic adhesive (Resbond™ 989). In-situ 2D XANES imaging and nano-tomography were conducted on the particle samples enclosed in the capillary, during thermal redox cycles in a temperature range of 800 °C to 900 °C with a versatile, compact heater after proper calibration45 at the Full Field X-ray Imaging beamline (FXI, 18-ID)46 at the National Synchrotron Light Source-II (NSLS-II) at Brookhaven National Laboratory (BNL).

The images from the TXM at the FXI beamline were captured using a lens-coupled CCD detector with 2560 × 2160 pixels, providing a field of view of 46.8 μm × 55.48 μm. A camera binning of 2 × 2 was used, resulting in an effective pixel size of 43.34 nm. For nano-tomography, the X-ray incident energy was set to 8.0 keV, which is the designed energy for the objective zone plate. It is also slightly higher than the Co K-edge (7.709 keV), which provides a good contrast between particle and air regions. The nano-tomography was conducted at a fly scan mode, with a rotation speed of 8°/s to capture the morphological evolution at a higher temporal and spatial resolution to minimize the impact of particle movements on the imaging quality due to the elevated temperature. The exposure time for each projection image was 0.05 s. The full tomography was collected with a 180° rotation capturing about 450 projections, with a total acquisition time of 0.5 to 1.0 min per tomographic scan. For the 2D and 3D XANES imaging, scans were conducted at X-ray energy across the Co K-edge, from 7500–7709 eV in 100 eV steps, 7710–7715 eV in 5 eV steps, 7715–7735 eV in 1 eV steps, and 7740–8000 eV in 100 eV steps. With fewer energy points, each 2D XANES imaging scan took about 4.5 min to ensure that the chemical evolution was well captured. The 3D XANES scan was carried out on microparticle samples quenched to room temperature after the second reduction cycle at 900 °C for 30 min, in order to preserve the high-temperature phases. 3D XANES was measured by collecting tomography as a function of energy, following the same energy points mentioned above. The tomography at different energies was reconstructed and subsequently registered to ensure proper alignment, enabling accurate XANES fitting.

3D volumes were reconstructed from tomography projection images using gridrec algorithm implemented in Tomopy47 package. Post image processing of the 3D tomographic reconstruction stack images, including data at different energies and different time points, was conducted using the Crop3D and Median (3D) plugin in the FIJI package of ImageJ48, as well as Python packages including Skimage49, Numpy50 and Scipy51 to perform cropping, filtering, segmentation and volume registration. Volume registration from fast Fourier transforms of the 3D volumes was used to align the whole tomography. Thresholding segmentation was performed to differentiate the solid phase (Co3O4 and CoO mixture) and air. Watershed image segmentation and flood fill method was used to identify a single particle and the internal pores. The open pores of the particle were identified with further image processing, and the details are shown in Fig. S7. The image profiles of mean curvature and Gaussian curvature were calculated using Tomviz (version 1.10), an open-source software package52. The principal curvatures were then derived from the mean curvature and the Gaussian curvature. The interfacial shape distribution (ISD) plot was then generated based on the curvature values using customized code developed in our previous study40. The processed image stacks were then visualized in 2D using ImageJ and in 3D using Dragonfly software (version 2020.1, Comet Technologies Canada Inc.)53. The volume and surface area of the particles were calculated using Dragonfly software after proper segmentation. The XANES data were processed using PyXAS27,54 and Athena software55.

Standard X-ray absorption spectra of CoO and Co3O4 were collected at the Inner Shell Spectroscopy beamline (ISS, 8-ID) at NSLS-II at BNL (Fig. S8). The white line position of CoO is 7726.4 eV, while that of Co3O4 is 7729.8 eV. Therefore, in the 2D XANES imaging and the 3D XANES image stacks data, the fitted white line position at each pixel can be representative of the reduction (CoO) and oxidation (Co3O4) phases in the particles. Here, the spectrum at each pixel is a linear combination of CoO and Co3O4 spectra proportional to the amount of Co in each phase, from the projected views. The fitted white line positions between 7726.4 and 7729.8 eV do not indicate an intermediate oxidation state, but rather the ratio of these two phases. The corresponding fitted white line positions of the combined spectra of Co3O4 and CoO are shown in Fig. S9. Thus, the fraction of Co in the CoO phase in each pixel can be calculated based on the white line position. Using the amount of Co estimated from the X-ray absorption, the conversion depending on the amount of Co can also be calculated. The detailed calculation method is shown in Fig. S10.

SEM sample preparation and characterization
The post-TXM Co3O4 microparticles were characterized with SEM using two methods. With the first method, microparticles were imaged directly through the open end of the microcapillary using a low-energy backscattered electron detector on a TESCAN Solaris Ga-FIB-SEM operated at 2 kV accelerating voltage with a 300 pA beam current in UH-Resolution mode. Second, the microcapillary was broken, and a piece was mounted on a standard SEM stub using Ag paint and subsequently sputter-coated with 5 nm Au. The broken microcapillary piece is shown in Fig. 10C. Secondary electron images were then acquired on a FEI Nova NanoSEM 630 operated at 5 kV accelerating voltage with a 3.6 nA beam current.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "This work reports the morphological and chemical evolution of Co₃O₄ micro- and nanoparticles over thermal cycles. Novel testing techniques offer valuable info in the TCES field, yet many statements are controversial. Pore structure formation is mostly explained by literature citation, lacking in-depth analysis. The author should improve on mechanism aspects to offer new ideas for high-performance redox TCES media design. If the following questions are thoroughly addressed, the work may be considered for publication in Nature Communications.\n1. Keywords like TGA are unsuitable.\n2. On page 2, lines 49-51, the expression is unreasonable. Co₃O₄'s high-cost limits it widespread application, which is often used for mechanism investigation in TCES.\n3. On page 2, lines 52-55 and 56-58, I do not agree with these viewpoints. The particle breakage caused by the rapid gas releasing during cycling process, which is called the \"self-activation\" phenomenon, may improve the materials’ cycling performance. [Energy Storage Materials 73 (2024) 103825] and [ACS Appl. Energy Mater. 2022, 5, 4903−4915]. Although reducing the initial particle size or introducing a porous structure is beneficial for improving cycling performance, in current research, it is more important to maintain the stability of the pore structure.\n4. What's 2D XANES' sample penetration depth? Gas-solid reactions are surface to interior; can it detect particle-interior reactions?\n5. “the conversion from CoO to Co3O4 occurred at ~850°C as shown in Figure 2(A)(e-h), but this re-oxidation process did not initiate in the TGA analysis at this temperature”.\nThe measurement of the instrument may have errors. Especially when using two different instruments. Or is it caused by uneven temperature distribution of the sample?\n6. What are microparticle and nanoparticle specific surface areas and pore structures and their differences?\n7. What causes internal pore formation and why does it inhibit Co₃O₄ reduction, contrary to common knowledge? Oxidation depends on oxygen diffusion and reduction is controlled by heat conduction. Does it have an impact on heat conduction? What is the specific impact?\n8. For “Following this initial small pore formation… where there are smoother features with a lower chemical potential.”\nTheoretical calculations could better quantify surface-energy changes.\n9. Mechanism analysis content is scarce.\n10. As per the title, the author should link particle structure and chemical reactions.\n11. Overall, the article offers valuable structural-evolution info, but doesn't provide desired knowledge on structure-evolution driving forces and future compositional-regulation ways to suppress negative changes.", "reviewer_2": "The authors present an analysis of the chemical and morphological changes of cobalt oxide during thermal reduction and reoxidation. Thermal analysis of this is done through thermogravimetric analysis (TGA) to investigate cyclability and particle size dependence. Synchrotron transmission x-ray microscopy (TXM) is used to measure 2D chemical and 3D morphological changes in-situ. SEM is lastly used to analyze changes in the surface structure through cycling. By combining these, the authors present a well corroborated mechanism through which the thermal cycling affects the reaction kinetics for micro- and nanoscale particles.\nWe found this an interesting and compelling read, with implications for the development of cobalt oxide, and perhaps more broadly metal oxides, as a heat storage material. Given the change in reaction rate when going from micro to macro, which is well documented in literature, the observed differences between the nano- and microparticles outlined in this work were expected to follow this trend and are thus generally not surprising. The strength of this manuscript however lies in the combination of various used methodologies (e.g., using TXM to track changes occurring on the nanoscale, in-situ), which provides new insights.\nHowever, we have some concerns about the presentation and wider relevancy of the work.\n• Reduction in reaction kinetics in microparticles is attributed to a reduction in specific surface area through a combination of sintering, coarsening, and the development of internal porosity. In nanoparticles, on the other hand, no reduction in reaction kinetics is observed. We would like to consider the application where a large energy storage capacity and density are desired. How can the results from this study be applied to the development of a stable material? Is the deposition of a single layer of micro- or nanoparticles on a (macroporous) substrate sufficient to obtain competitive performance characteristics? If not, would a tight packing of the given particles not result in more sintering and thus a departure from micro or nano particles?\n• Co3O4 is used as a ‘representative’ TCM, citing various positive performance indicators with its biggest challenge to widespread adoption being material reversibility\no To what extent is Co3O4 representative of metal oxides? and can the insights gained in this work thus be applied to other TCMs?\no If not, is the methodology applicable to other materials as well, or are there restrictions on what materials can be tested this way, such as the working atmosphere, corrosivity or toxicity?\no Cobalt oxide as a material is costly and has ethical concerns regarding its procurement. Considering this, is widespread adoption, in the authors’ views, still reasonable?\n• On line 155, a slowdown of the reduction process was noted for the microparticles in TXM, a result that was not observed in the TGA results (figure 1). This is stated by the authors in line 221, who attribute this to the generation of fewer internal pores in the TGA. What could be the cause of this, a difference in test conditions between TXM and TGA, randomness of the sample, or is there something else? It would be generally helpful to outline if/how the testing conditions and samples might differ between the TXM and TGA.\n• Figure 1 could be improved for clarity. Currently the mass percentages are not normalized between graphs, thus making it not straightforward to compare them directly. It would be helpful to indicate the theoretical mass change to compare directly. Furthermore, the inclusion of DTG lines would help interpret the rate of reaction, as the authors state there is no obvious degradation (line 115), but this is difficult to confirm just from the steep curves.\n• Multiple times the authors use the ‘reaction efficiency’ when appearing to refer to the reaction kinetics. This is ambiguous and non-standard terminology which we recommend changing.\n• The timepoints taken for Figure 2-C and F, as well as those in Figure 3-A and B, are not distributed uniformly. We would like to know the reasoning for this, as it obfuscates the interpretation of the results.\n• In Figure 3-C and D, the horizontal axis indicates the amount of Co. Although explained on line 171, it is not clear from the image or the caption that this is on a per pixel basis. We suggest adding this for clarity.\n• Through power-law fitting of the characteristic length, seen in Figure 5-C and D, the authors reason that surface diffusion dominates the coarsening in the microparticles. However it was not clear from the text how these results support this conclusion, so we would like the authors to elaborate on this.", "reviewer_3": "I co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature Communications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career Researchers who co-review manuscripts.", "reviewer_4": "The manuscript presents a multi-mode operando X-ray characterization of thermochemical energy storage in cobalt oxide particles. Both XANES and nano-scale X-ray CT are applied to analysis the spatial distributions of oxidation and the changes in the 3D morphology. The results show interesting evolutions of the particle structure with temperature cycling and a clever length scale analysis is used to evaluate whether process is bulk or surface transport driven. The quality of the characterization and image analysis is high and the results are intriguing from both the materials point of view and the analytical method development an demonstration for operando high temperature cycling of thermochemical materials. I recommend publication with minor revisions.\n• It seems a significant missing component of the main manuscript is the quantification of the heat absorbed and desorbed during the reduction and oxidation cycles. It would likely not be viable during TXM or XANES, but it could be done separately on similar samples. Given the application, it seems that evaluating the correlation between the processes with micro and nano particles should include evaluation of the heat capacity. However, a discussion of the heat capacity is mostly absent beyond the basic introduction. Some discussion of the heat flow results of Figure S1 for the micro-particles could be added to the main manuscript. Are there corresponding results for the nano-particles? Is the heat consistent with other measurements of the thermal capacity?\n1) Some correlation analysis of the heat flow to the fraction of CO would be worth investigating, even if just using the microparticle DSC data in Figure S1.\n2) Line 217 – is sintering a process that would form porosity within a solid?\n3) It seems like in the XANSES has a lower threshold of Co fraction that is saturated (purple). Is there variation below the roughly zero threshold that is missing in the images of Figure 2?\n4)The terminology of external and internal pores is a bit confusing. All pores are internal, but the external pores seem to be described as those with a connection to the external void volume. Perhaps is just “connected pores” and “isolated pores”"}, "author_response": "We sincerely thank the reviewer for the thoughtful and constructive feedback. We appreciate your recognition of the value provided by our use of operando synchrotron-based imaging techniques in advancing the understanding of thermochemical energy storage materials.\nWe acknowledge the concern regarding the limited mechanistic discussion in the original manuscript. In the revised version, we have expanded our analysis to provide a more in-depth discussion of the mechanisms behind pore structure formation and morphological evolution during redox cycling.\n1. Keywords like TGA are unsuitable.\n[Response] We have deleted this “TGA” keyword in the manuscript\n[Changes] Deleted “TGA” in “keyword” section.\n2. On page 2, lines 49-51, the expression is unreasonable. Co₃O₄'s high-cost limits it widespread application, which is often used for mechanism investigation in TCES.\n[Response] We agree with the reviewer that Co O is relatively high-cost, which limits its widespread\n3 4\napplication. Thank you for pointing this out. We have revised the text in lines 49–51 accordingly to clarify\nthis point.\n[Changes] Changed in the “Introduction” section:\nCo O , one of the multivalent metal oxides used as TCMs, has Multivalent metal oxides have emerged as a\n3 4\npromising candidate due to TCMs for TES systems because of its their high energy storage capacity,\nfavorable reaction reversibility, suitable redox temperatures, and cost-effective working atmosphere 7-\n10.However, the widespread use of Co O in TES systems faces, challenges particularly in terms of such as\n3 4\nlimited material reversibility and performance degradation over multiple cycles remain 11-13. Among these\noxides, Co O is an ideal candidate for mechanistic studies, despite its relatively high material cost. Its well-\n3 4\ncharacterized redox behavior 14enables clear evaluation of reaction kinetics and pathways at the nano- and\nmeso-scales, providing insights that can guide the development of more cost-effective TCMs.\n3 4\ncouple with a cubic micro-nanostructure. Journal of Energy Storage 43, 103167 (2021).\n3. On page 2, lines 52-55 and 56-58, I do not agree with these viewpoints. The particle breakage caused\nby the rapid gas releasing during cycling process, which is called the \"self-activation\" phenomenon,\nmay improve the materials’ cycling performance. [Energy Storage Materials 73 (2024) 103825] and\n[ACS Appl. Energy Mater. 2022, 5, 4903−4915]. Although reducing the initial particle size or\nintroducing a porous structure is beneficial for improving cycling performance, in current research,\nit is more important to maintain the stability of the pore structure.\n[Response] Thank you for your insightful comment, and we apologize for the confusion in our original\nwording. We agree that gas release or oxygen evolution during cycling can, in some cases, enhance\nperformance through the so-called \"self-activation\" phenomenon, which increases surface area and may\npartially inhibit sintering.\nIn the original statement (lines 52–55), our intent was to highlight that mechanical degradation such as\ncracking can occur during cycling. However, we incorrectly attributed this cracking to oxygen evolution.\nSuch cracking is more likely caused by thermal expansion and stress accumulation during repeated redox\ncycling, rather than by gas release. We have therefore revised this section and removed the words “oxygen\nevolution” as the primary cause of cracking.\nWe also appreciate the references you provided and agree that preserving the porous structure is crucial for\nimproving cycling performance. As you rightly point out, while reducing the initial particle size or\nintroducing porosity can help, the stability of the pore structure during cycling is even more important. In\nresponse, we have incorporated a discussion of the research work of preserved porosity in suppressing\nsintering and maintaining performance. This also serves to better motivate our study, which focuses on\ntracking the evolution of pore structures under operando conditions.\n[Changes] Changed in the “Introduction” section:\nOne of the degradation issues is structural deformation, such as cracking and fragmentation, induced by\nthermal cycling, likely resulting from repeated thermal expansion and contraction the deformation of the\nmaterial such as cracks and fragmentation upon thermal cycling 15,16, which may be due to gas evolution\nand thermal expansion. Another common degradation mechanism in Co O is the sintering of particles at\n3 4\nelevated temperatures, which impedes diffusion of gaseous species and leads to reduced storage capacity\n11,12. Common mitigation strategies, such as reducing the initial particle size 7,17,18 or introducing a porous\nstructure 7,16,19 have been applied to Co O and doped Co O TCMs to enhance their performance. While a\n3 4 3 4\nporous structure is generally believed to improve redox efficiency rate by increasing surface area and\nfacilitating gas transport, some studies suggest otherwise recent studies suggest that its benefits may not\nalways be straightforward. For instance, a Co O -based porous, foam-like structure with a pore size of 1–\n3 4\n1.5 mm exhibited lower conversion efficiency rate during thermal cycling compared to a dense structure;\nfurthermore, the porosity of both dense and porous Co O changed after 10 thermal redox cycles 15. These\n3 4\nfindings highlight that, beyond simply introducing porosity, it is critical to ensure the stability of the porous\nstructure throughout thermal cycling. Recent studies suggest that preserving the porous structure in TCMs\nthrough lattice-matching strategies and the addition of stabilizers can help maintain effective thermal\ncycling performance 20,21. Similarly, nanoparticles are generally believed to improve Co O conversion rate\n3 4\nby increasing reactive surface area and reducing diffusion distances 7,11. Therefore, it is important to track\nthe evolution of the porous structure within particles with different sizes during thermal cycling to better\nunderstand their conversion efficiency. However, it remains unclear whether the pores form within the\nparticle as well as their potential impact on the redox thermal cycling behaviors of the materials. the kinetics\nof the pore evolution, both within and between individual particles, especially the isolated pores, remain\npoorly understood. Additionally, the Traditional technique like the Brunauer-Emmett-Teller (BET) method\nbased on adsorption isotherms of nonreactive nitrogen or argon 19, commonly used for porosity\nmeasurements, has limitations in analyzing internal and isolated pores at the sub-particle level within\nindividual particles. As a result, the influence of particle size and internal porosity isolated pores on the\nchemical and morphological evolution of Co O during thermal cycling has not been thoroughly explored,\n3 4\npartly due to the challenges in characterizing intermediate morphological and oxidation state changes at the\nmicron and nanometer scales in situ during the thermal cycling.\nthermochemical energy storage. Energy Storage Materials 73, 103825 (2024).\nstabilized, CaO-based composites under different thermal energy storage modes. ACS Applied\nEnergy Materials 5, 4903-4915 (2022).\n4. What's 2D XANES' sample penetration depth? Gas-solid reactions are surface to interior; can it\ndetect particle-interior reactions?\n[Response] We appreciate the reviewer’s insightful question regarding the penetration depth and spatial\nsensitivity of 2D XANES. In our study, 2D XANES imaging was conducted using transmission X-ray\nmicroscopy, which enables full penetration of the sample along the X-ray beam path. Therefore, each pixel\nin the 2D image represents an integrated X-ray absorption signal through the entire sample thickness at that\nlocation. This allows for detection of chemical changes occurring not only on the surface but also within\nthe interior of particles.\nTo spatially resolve interior transformations and localize chemical changes within specific regions inside\nthe particle, 3D XANES tomography would be required. The technique combines XANES imaging with\ntomographic measurement and can resolve the 3D distribution of chemical states. Further analysis using\n3D XANES has been included in our response to Comment 10 and the corresponding manuscript section.\nDue to the long scan time required for 3D XANES, it is limited to equilibrium-state measurements rather\nthan time-resolved in situ experiments.\nIn our current in situ 2D XANES analysis, as shown in Figure 3, we captured pixel-resolved chemical\nconversion that reflects the amount-dependent conversion. To clearly illustrate this, we further included the\nXANES spectra along the center region to the surface for the first 5 minutes at 850°C for the Co O\n3 4\nmicroparticle.\n[Changes] In section 2.2\nIn Figure 2(A), a nearly full conversion of Co O to CoO was observed in the microparticles during the first\n3 4\ncycle at 900°C within a short time (~3 min), which is consistent with the TGA results (Figure 1). When the\ntemperature cooled down to 850°C, CoO gradually converted back to Co O through reoxidation. Detailed\n3 4\nXANES spectra at different locations, from the center region to the surface, are shown in Figure S4.\nHowever, CoO did not fully convert back to Co O after 55 min, indicating a kinetically limited reoxidation\n3 4\nprocess.\nIn Supporting Information\nFigure S4. XANES spectra of Co O microparticle during the first 5 minutes at 850oC at different locations.\n3 4\nThe difference between the post-edge and pre-edge baselines in the XANES spectra reflects the relative\namount of cobalt present in the material. As shown from the Region of Interest (ROI)-1 (center) to ROI-6\n(surface), the cobalt content decreases toward the surface. Additionally, in this localized region, the surface\nmaterial has re-oxidized to Co O , as evidenced by the rightward shift of the absorption peak, while the\n3 4\ncenter region remains predominantly as CoO.\n5. “the conversion from CoO to Co3O4 occurred at ~850°C as shown in Figure 2(A)(e-h), but this re-\noxidation process did not initiate in the TGA analysis at this temperature”. The measurement of the\ninstrument may have errors. Especially when using two different instruments. Or is it caused by\nuneven temperature distribution of the sample?\n[Response] Thank you for raising this important point. We agree that variations in temperature\nmeasurements can arise due to differences in instrumentation and experimental setups. In our study, several\nfactors may contribute to the observed discrepancy in the onset temperature of the CoO to Co O re-\n3 4\noxidation reaction between the TGA and TXM experiments:\nThe TGA sample (~3 mg) is composed of densely packed micro-particles, while the TXM sample consists\nof a thin layer of micro-particles (~ few µg) attached to the inner wall of a capillary. Differences in sample\nmass and geometry can lead to uneven or delayed heat transfer, particularly in bulkier TGA samples,\npossibly resulting in a slight shift in the apparent onset temperature.\nTo further investigate this discrepancy, we conducted additional TGA scans under a controlled cooling rate\nof 2 °C/min. These measurements showed the re-oxidation onset temperature to be approximately 811°C\nfor the microparticles and 816°C for the nanoparticles.\nOverall, the difference in onset temperatures can be reasonably attributed to instrumental temperature\ncalibration tolerances, sample geometry, mass, and heat transfer behavior.\n[Changes] In section 2.1:\nInitially there was no significant weight change for the particles at 850°C, To further investigate the\ntemperature of the re-oxidation reaction, additional TGA scans were conducted under a controlled cooling\nrate of 2 °C/min, and the result is shown in Figure S2. But at 800°C, the nanoparticles increased in weight\nrapidly and fully converted to Co O in approximately 5 min. In contrast, the microparticles increased in\n3 4\nweight at a slower rate, and did not fully convert even after 30 min.\nIn Supporting Information\nFigure S2. Characterized onset temperature of the re-oxidation process for microparticles (A) and\nnanoparticles (B), based on mass change measured by TGA. The onset temperature is approximately 811°C\nfor microparticles and 816°C for nanoparticles.\nIn section 2.2\nIn the in-situ 2D XANES analysis, the conversion from CoO to Co O occurred at ~850°C as shown in\n3 4\nFigure 2(A)(e-h), but this re-oxidation process did not initiate in the TGA analysis at this temperature. A\nseparate DSC thermal analysis determined that the re-oxidation process of the microparticles initiate at\n~850°C, as shown in Figure S5. Literature reports the onset re-oxidation temperature as 850°C 12, 870°C\n13, and 879.7°C 5. These variations can reasonably be attributed to kinetic factors such as sample geometry,\nmass, and heat transfer behavior. Therefore, 850°C is likely the equilibrium temperature during the re-\noxidation process in the TXM experiment.\nIn section 3.2\nIn-situ 2D XANES imaging and nano-tomography were conducted on the particle samples enclosed in the\ncapillary, during thermal redox cycles in a temperature range of 800°C to 900°C with a versatile, compact\nheater after proper calibration 45 at the Full Field X-ray Imaging beamline (FXI, 18-ID) 46 at the National\nSynchrotron Light Source-II (NSLS-II) at Brookhaven National Laboratory (BNL).\nX-ray microscopy. Synchrotron Radiation 27, 746-752 (2020).\n6. What are microparticle and nanoparticle specific surface areas and pore structures and their\ndifferences?\n[Response] Thank you for your thoughtful question. We have added an analysis of the specific surface\nareas of the microparticles and nanoparticles in Figure S6. The pore structures are presented in Figure 4 of\nthe main manuscript. During thermal cycling, both open and isolated pores were observed in microparticles.\nIn contrast, no apparent porous structures were detected in the nanoparticles.\n[Changes] In the discussion of Figure 4:\nThe nanoparticles retained their original morphology without agglomeration or merging after the thermal\nredox cycles. To further understand the morphological evolution of the microparticles and nanoparticles\nduring the thermal cycles, the surface area and volume changes for these two samples as a function of the\nthermal cycling are shown in Figure S6.\nBased on the chemical evolution kinetics shown in Figure 2 and Figure 3, the formation of a porous structure\nin the microparticles may have hindered the conversion from Co O to CoO during the second cycle at\n3 4\n900°C, as the slower conversion rate was not observed in nanoparticles.\nIn section 3.2:\nThe processed image stacks were then visualized in 2D using ImageJ and in 3D using Dragonfly software\n(version 2020.1, Comet Technologies Canada Inc.) 52. The volume and surface area of the particles were\ncalculated using Dragonfly software after proper segmentation. The XANES data were processed using\nPyXAS 27,53 and Athena software 49.\nIn Support Information\nFigure S6. Comparison of (A) surface area, (B) volume, and (C) specific surface area of microparticle and\nnanoparticle samples at the end of each temperature segment during thermal cycling. Note: The first 800°C\nmeasurement corresponds to the pristine state. The particles were then heated to 900°C and subsequently\ncooled to 850°C. The sampling regions are different between the pristine state and the heated states due to\nthe large sample motion in the microscope during the heating process, but comparing the specific surface\narea remains valid.\n7. What causes internal pore formation and why does it inhibit Co₃O₄ reduction, contrary to common\nknowledge? Oxidation depends on oxygen diffusion and reduction is controlled by heat conduction.\nDoes it have an impact on heat conduction? What is the specific impact?\n[Response] We appreciate the reviewer’s insightful question regarding the causes of internal pore formation\nand its unexpected inhibitory effect on Co O reduction.\n3 4\nWe have discussed the formation of internal pores in the manuscript. The formation of internal pores is\nprimarily attributed to a coarsening process following oxygen evolution at elevated temperatures during the\nreduction process. Secondly, in Figure 5, since a slight increase in internal pore volume is observed at 800°C,\nit suggests that some external pores may become enclosed by surrounding material, transforming into\ninternal pores.\nIn subsequent cycles, as Co O undergoes reduction, oxygen is released and may become trapped within\n3 4\nthese internal pores. The localized accumulation of oxygen raises the internal partial pressure of O , which\n2\nthermodynamically inhibits the further reduction of Co O to CoO. This process may be extended to include\n3 4\nisolated pores formed by sintering between adjacent particles. These isolated pores may similarly trap O\n2\nand elevate the local oxygen partial pressure, further hindering reduction.\nWe have now added a description to clarify the competing effects of the pores.\nWe agree with the reviewer that the pores also influence heat conduction. Poor heat conduction may delay\nor suppress Co O reduction in affected regions. This interpretation is supported by several studies\n3 4\ndemonstrating the inverse relationship between porosity and thermal conductivity:\n[1] Resl, Ondřej, et al. \"Influence of Porous Oxide Layer on Water Spray Cooling.\" Proceedings of the 9th\nInternational Conference of Fluid Flow, Heat and Mass Transfer (FFHMT’22), Niagara Falls, ON, Canada.\n2022.\n[2] Sumirat, Iwan, Y. Ando, and S. Shimamura. \"Theoretical consideration of the effect of porosity on\nthermal conductivity of porous materials.\" Journal of Porous Materials 13 (2006): 439-443.\n[3] Chen, L. L., et al. \"Giant reduction in thermal conductivity of Co O with ordered mesopore\n3 4\nstructures.\" Microporous and Mesoporous Materials 296 (2020): 109969.\nHowever, in our TXM experiments, the sample volume is relatively small and there is only a thin layer\nattached to the inner wall of a quartz capillary. Heating is provided by radiative heat transfer from the\nexternal heater. Given this setup, we believe that thermal conduction within the sample has a negligible\nimpact on the overall redox reactions. Nonetheless, we have included citations to these studies to provide a\nmore complete discussion.\n[Change] Changes before section 2.5\nAlthough the internal and isolated pore volume decreased to 7.2% at 800°C, the trapped O created a\n2\nlocalized high-concentration environment within these pores, which could inhibit the reduction reaction\n(Co O to CoO) during the second cycle, as discussed previously for Figure 2 and Figure 3.\n3 4\n…\nThe commonly accepted benefit of a porous structure lies in the formation of external, open pores, which\nfacilitate oxygen release to the surrounding atmosphere. In our study, the volume of open pores is\nsignificantly higher than that of internal pores. However, the impact of internal and isolated pores should\nnot be overlooked, as their ability to trap evolved O gases can undermine redox performance. In addition\n2\nto their role in trapping oxygen, internal and isolated pores can also negatively decrease the thermal\nconductivity of the material. This reduction in thermal conductivity can hinder efficient heat transfer within\nthe particle, potentially slowing the temperature rise required to drive the endothermic reduction of Co O .\n3 4\nA number of studies have demonstrated this inverse relationship between porosity and thermal conductivity\n40-42. However, in present study, the sample consists of a thin particle layer attached to the inner wall of a\nquartz capillary and is heated via radiative transfer from an external furnace. Due to the small sample\nvolume and the predominance of radiative over conductive heating in this configuration, we believe the\nimpact of isolated pores on thermal conduction is negligible in our case.\n8. For “Following this initial small pore formation… where there are smoother features with a lower\nchemical potential.” Theoretical calculations could better quantify surface-energy changes.\n[Response] We appreciate the reviewer’s insightful comment highlighting the value of theoretical\ncalculations in supporting our interpretation of surface-energy-driven morphological evolution. In response,\nwe have expanded our discussion to more explicitly connect the observed mass transport from high-\ncurvature regions (sharp features with higher chemical potential) to low-curvature regions (smoother\nfeatures with lower chemical potential) with surface energy minimization principles, consistent with the\nGibbs-Thomson effect. To strengthen this point, we have also incorporated quantitative analysis of the mean\ncurvature, Gaussian curvature, and interfacial shape distribution in Figure 6, which provides direct evidence\nof the morphological transition toward smoother, energetically favorable features. These results not only\nsupport our qualitative interpretation but also offer a more rigorous basis for understanding curvature-driven\nmass transport in the system.\n[Changes] In section 3.2\nThe open pores of the particle were identified with further image processing, and the details are shown in\nFigure S7. The image profiles of mean curvature and Gaussian curvature were calculated using Tomviz\n(version 1.10), an open-source software package 52. The principal curvatures were then derived from the\nmean curvature and Gaussian curvature. The interfacial shape distribution (ISD) plot were then generated\nbased on the curvature values using customized code developed in our previous study 40. The processed\nimage stacks were then visualized in 2D using ImageJ and in 3D using Dragonfly software (version 2020.1,\nComet Technologies Canada Inc.) 52.\nAdvanced Electronics Manufacturing by Ptychographic X‐ray Nanotomography. Advanced\nEngineering Materials 22, 1901250 (2020).\nNature Communications 13, 4458 (2022).\nIn section 2.4\nFollowing this initial small pore formation, to minimize surface energy, ions on the particle surface migrated\nfrom regions of high curvature, where there are sharp features and a higher chemical potential, to regions\nof lower curvature, where there are smoother features with a lower chemical potential. The curvature\nevolution will be further discussed below.\nAlthough the internal and isolated pore volume decreased to 7.2% at 800°C, the trapped O created a\n2\nlocalized high-concentration environment within these pores, which could inhibit the reduction reaction\n(Co O to CoO) during the second cycle, as discussed previously for Figure 2 and Figure 3. To understand\n3 4\nthe mass transport from high-curvature regions (sharp features with higher chemical potential) to low-\ncurvature regions (smoother features with lower chemical potential) driven by surface energy minimization,\nthe curvature distribution on the particle surface was analyzed. Figure 6 shows the 3D visualization of mean\ncurvature of the particle during the thermal cycles, along with the corresponding interfacial shape\ndistribution and Gaussian curvature analysis.\n[Redacted]\nFigure 6. Quantitative curvature analysis of the Co O particle during the thermal cycles: (A) Temperature\n3 4\nprofile during the in-situ X-ray nano-tomography experiment, with labeled data points (a-h) corresponding\nto the particle views in (B). (B) Surface rendering of the particle at different temperature points, as indicated\nin the temperature profile in (A). The surface is color-mapped by the local mean curvature at each point.\n(C) Scaled interfacial shape distributions (K vs. K ) at different temperature points. (D) Schematic of the\n1 2\ninterfacial shapes for the interfacial shape distribution contour plots. (E) Histograms of the mean curvature\n(H = (K + K )/2) and Gaussian curvature (H = K ·K ) at 900°C during cycle 1, corresponding to points (c)\n1 2 1 2\nand (d), and during cycle 2, corresponding to points (g) and (h).\nAs shown in Figure 6(B), regions of the Co O particle with mean curvature near zero (blue areas) generally\n3 4\ncorrespond to relatively smooth surfaces, although they can still include points with either positive or\nnegative Gaussian curvature, reflecting different local geometries. As the temperature increased to 900°C,\nhigh-curvature features developed, leading to noticeable morphological changes. During the isothermal\nhold at 900°C, surface coarsening led to a reduction in these sharp features, resulting in smoother\nmorphologies. The scaled interfacial shape distribution in Figure 6(C) clearly shows that point (d) has a\ngreater proportion of low curvature features compared to point (c), indicating a smoother interface. A similar\nsmoothing trend was observed during the second cycle at 900°C, comparing (g) and (h), the distributions\nof the principal curvatures (K , K ) shift toward lower values, indicating a smoother surface. Figure 6(D)\n1 2\npresents a map of the different regions along with their corresponding interfacial shapes 32.Features within\nthe particle characterized by K < 0 and K > 0 exhibit saddle-like curvature 32.\n1 2\nTo further quantify these changes, histograms of the mean curvature (H = (K + K )/2) and Gaussian\n1 2\ncurvature (H = K ·K ) for points (c), (d), (g), and (h) are shown in Figure 6(E). In both cycles, the coarsening\n1 2\nprocess promoted the mass transport from high-curvature regions, associated with sharp features and higher\nchemical potential, toward lower-curvature regions with smoother geometries and lower chemical potential.\nAs a result, both the mean curvature and Gaussian curvature values for points (d) and (h) shifted closer to\nzero, indicating the development of more planar surface features 40.\n9. Mechanism analysis content is scarce.\n[Response]\nWe appreciate the reviewer’s feedback regarding the limited discussion of the mechanisms. In our revised\nmanuscript, we have elaborated on:\n1. The formation of porous structures in microparticles, which is not observed in nanoparticles.\n2. The dependence of chemical evolution on morphology, considering not only thickness but also the\nthree-dimensional porous structure.\n3. The distinct driving forces behind porosity formation and the subsequent coarsening process.\n4. The mechanisms by which internal and isolated pores influence the redox conversion.\nWe have added Figure 8 to summarize our mechanisms discussion\n[Changes]\nWe added Figure 8 to summarize the mechanisms in section 2.4:\nAlthough the internal and isolated pore volume decreased to 7.2% at 800°C, the trapped O created a\n2\nlocalized high-concentration environment within these pores, which could inhibit the reduction reaction\n(Co O to CoO) during the second cycle, as discussed previously for Figure 2 and Figure 3.\n3 4\n…\nTo summarize the mechanism of porous structure formation in the Co O microparticle sample and the\n3 4\ninfluence of internal and isolated pores on the subsequent reduction process, a schematic illustration is\nshown in Figure 8.\nFigure 8. Schematic illustration of the mechanism of porous structure formation in Co O microparticles\n3 4\nand the role of internal and isolated pores in the subsequent reduction process, in contrast to the absence of\nan apparent porous structure in Co O nanoparticles.\n3 4\nIn summary, when Co O microparticles are heated to high temperatures, multiple types of pores are\n3 4\ngenerated. Open and internal pores form because of O evolution, followed by vacancy diffusion and\n2\nsubsequent coarsening. Isolated pores develop between particles due to sintering. Upon cooling to lower\ntemperatures, some open pores may transform into closed pores due to the volume expansion associated\nwith the re-oxidation of CoO to Co O . During subsequent heating, these closed and internal pores inhibit\n3 4\nthe reduction of Co O to CoO by trapping the evolved O , which increases the local oxygen concentration\n3 4 2\nand thereby suppresses further reduction. In contrast, this porous structure is not observed in the Co O\n3 4\nnanoparticle samples.\n10. As per the title, the author should link particle structure and chemical reactions.\n[Response]\nThank you for the suggestion. In the current manuscript, we have discussed the 2D XANES chemical\ndistribution in relation to particle thickness and size (microparticles vs. nanoparticles), and we analyzed the\ncorresponding conversion behavior. While this discussion qualitatively suggests that structural features,\nsuch as size and specific surface area, affect the chemical conversion, we acknowledge that we did not\nexplicitly quantify the relationship between internal particle structure and the chemical reaction\nTo directly examine the effect of structure on conversion, a 3D XANES scan is required, in which XANES\nimaging is combined with tomography to resolve 3D chemical distribution alongside the internal\nmicrostructure. Such scans require longer data acquisition, as a series of tomographic datasets must be\ncollected at multiple incident X-ray energies. During this time, slow, continuous phase transitions may\noccur; additionally, at high temperatures, maintaining mechanical stability over the extended scanning\nperiod can be challenging. To overcome this, we performed a quenching experiment: Co O particles were\n3 4\nthermally cycled and then rapidly quenched after the second reduction cycle at 900°C for 30 minutes. The\nphases at 900°C after 30 minutes were preserved through quenching, allowing us to conduct a 3D XANES\nscan at room temperature.\nThe resulting 3D XANES analysis (Figure 7) clearly shows that the surface region undergoes faster\nconversion to CoO (a reduction process at high temperature), as reflected by a shift XANES peak position\nto lower energy. Furthermore, we observed that isolated pores hinder the reduction process, while open,\ninterconnected pores facilitate conversion by enhancing gas accessibility. This new result directly links the\ninternal structure of the material to its chemical conversion.\n[Changes] In section 3.2\nFor the 2D and 3D XANES imaging, scans were conducted at X-ray energy across the Co K-edge, from\n7500 – 7709 eV in 100 eV steps, 7710 – 7715 eV in 5 eV steps, 7715 – 7735 eV in 1 eV steps, and 7740 –\n8000 eV in 100 eV steps. With fewer energy points, each 2D XANES imaging scan took about 4.5 min to\nensure that the chemical evolution was well captured. The 3D XANES scan was carried out on microparticle\nsamples quenched to room temperature after the second reduction cycle at 900°C for 30 minutes, in order\nto preserve the high-temperature phases. 3D XANES was measured by collecting tomography as a function\nof energy following the same energy points mentioned above. The tomography at different energies were\nreconstructed and subsequently registered to ensure proper alignment, enabling accurate XANES fitting.\nPost image processing of the 3D tomographic reconstruction stack images including data at different\nenergies and different time points, was conducted using the Crop3D and Median (3D) plugin in the FIJI\npackage of ImageJ 48, as well as Python packages including Skimage 49, Numpy 50 and Scipy 51 to perform\ncropping, filtering, segmentation and volume registration.\nThe white line position of CoO is 7726.4 eV, while that of Co O is 7729.8 eV. Therefore, in the 2D XANES\n3 4\nimaging and the 3D XANES image stacks data, the fitted white line position at each pixel can be\nrepresentative of the reduction (CoO) and oxidation (Co O ) phases in the particles.\n3 4\nAdded Figure 7 in section 2.4.\nAlthough the internal and isolated pore volume decreased to 7.2% at 800°C, the trapped O created a\n2\nlocalized high-concentration environment within these pores, which could inhibit the reduction reaction\n(Co O to CoO) during the second cycle, as discussed previously for Figure 2 and Figure 3.\n3 4\n…\nTo investigate the spatial distribution of CoO and Co O phases, as well as the presence of internal/isolated\n3 4\nand open pores at 900°C, Co O microparticles were quenched after the second reduction cycle at 900°C\n3 4\nfor 30 minutes to preserve the high-temperature phases. A 3D XANES analysis was then conducted at room\ntemperature, with the results shown in Figure 7.\nFigure 7. 3D XANES analysis of Co O microparticles quenched after the second reduction cycle at 900°C\n3 4\nfor 30 minutes, preserving the high-temperature phases: (A) 3D volume rendering based on peak position\nfitting, showing lower peak position values (corresponding to the CoO phase) predominantly at the particle\nsurface, while higher values (Co O phase) remain in the interior; (B) Representative image slices in XY\n3 4\nview from the 3D XANES data, illustrating the spatial distribution of CoO and Co O phases, as well as the\n3 4\npresence of internal/isolated and open pores; Z = 0 is defined as the bottom of the sample in z direction in\n(A) (C) The enlarged view in the white dash rectangle in (B) at Z=6.63 and 6.89 μm\nIn Figure 7(A), the color in the 3D volume rendering represents the peak position of the XANES spectra at\nthe Co K-edge. A peak position of ~7.726 keV corresponds to a region fully converted to the CoO phase,\nwhile a position of ~7.730 keV corresponds to unconverted Co O . Since the high-temperature phases were\n3 4\npreserved during quenching, the surface regions indicate fully conversion to CoO due to the easy release of\nO . In contrast, the interior regions, containing internal and isolated pores that trap O and increase the local\n2 2\nO partial pressure, remain largely unconverted as Co O . The subfigure highlights regions with\n2 3 4\napproximately 40% CoO (mole fraction). In the innermost region, the material remains entirely as\nunconverted Co O .\n3 4\nTo further illustrate the spatial distribution of CoO and Co O phases, as well as the presence of isolated and\n3 4\nopen pores, representative slices in XY view are shown in Figure 7(B). The enlarged view in the white dash\nrectangle in the subfigures (Z=6.63 and 6.89 μm) is shown in Figure 7(C). Regions near open pores appear\npurple, indicating the presence of CoO, while areas adjacent to isolated pores appear red or yellow,\nindicating the retained Co O . Therefore, the open and internal/isolated pore structures play a critical role\n3 4\nin the conversion process: while open pores facilitate gas exchange and promote the reduction reaction,\nisolated and internal pores likely inhibit the conversion of Co O to CoO by trapping evolved O , increasing\n3 4 2\nthe local oxygen concentration and thereby suppressing further reduction of Co O .\n3 4\n11. Overall, the article offers valuable structural-evolution info, but doesn't provide desired\nknowledge on structure-evolution driving forces and future compositional-regulation ways to\nsuppress negative changes.\n[Response]\nWe appreciate the reviewer’s constructive feedback. In the revised manuscript, we have expanded our\ndiscussion to more clearly explain the driving forces behind the observed structural evolution, as also\naddressed in our response to reviewer’s Comment 8.\nTo address the structure-evolution driving forces, we now emphasize the role of oxygen gas evolution\nduring the reduction of Co O to CoO as a primary contributor to vacancy formation and initial porosity\n3 4\ndevelopment. As these vacancies accumulate and diffuse, they lead to the formation of nanopores, which\nsubsequently grow into larger pores through coarsening. This coarsening process is further driven by\nsurface curvature: regions with higher curvature exhibit elevated chemical potential, promoting mass\ntransport and morphological transformation. To better illustrate this mechanism, we have added a new\nfigure (Figure 6) that demonstrates how surface curvature evolves during thermal cycling.\nRegarding future compositional-regulation strategies, we propose that compositional tuning (e.g., doping)\ncan be employed to balance thermal transport and phase transition kinetics, thereby mitigating undesirable\nstructural changes. For example:\n Improving thermal conductivity (e.g., by reducing porosity) can enhance heat transfer and\naccelerate reaction kinetics within the material core.\n Increasing surface area and maintaining open porosity (e.g., through nanoparticle design, activated\nmicroparticles, or lattice-matching techniques) may facilitate oxygen accessibility, though this must\nbe optimized to avoid excessive coarsening or pore collapse.\nWe further suggest that doping can be used to (1) promote the formation of stable, open porous networks\nand (2) suppress sintering during redox cycling. These strategies can be guided by compositional\nadjustments.\n[Changes] We modified the last paragraph in the “Conclusion” section.\nOverall, nanoparticles showed a faster conversion rate without forming porous structures, while\nmicroparticles tended to form internal pores, which may lower the conversion rate over cycles, presenting\na challenge for long-term stability and efficiency. Therefore, understanding the degradation mechanisms\nwith different particle sizes and the effect of porous structures is crucial for optimizing the performance of\nCo O as a thermochemical material in practical applications.\n3 4\nOverall, nanoparticles exhibited a faster and more stable conversion without developing significant porous\nstructures, whereas microparticles were prone to forming internal and isolated pores, which can slow down\nthe reduction process and reduce long-term cycling performance. This highlights the importance of\nunderstanding how particle size and pore structure affect degradation during cycling. Future material design\nshould focus on approaches that prevent sintering and coarsening, such as adding dopants to help maintain\na stable structure with high surface area. In addition, promoting and preserving open porous networks can\nimprove gas exchange while reducing the formation of isolated pores that limit performance. Applying\nthese particles onto a chemically stable, macroporous support may further enhance structural stability and\nheat transfer by improving gas flow and reducing densification. Finally, adjusting thermal conductivity and\noxygen transport properties through material selection or structure changes may offer additional ways to\nimprove redox performance. Together, these insights provide a practical direction for developing\nthermochemical materials with better durability and efficiency under thermal cycling conditions.\nReviewer #2 (Remarks to the Author):\nThe authors present an analysis of the chemical and morphological changes of cobalt oxide during\nthermal reduction and reoxidation. Thermal analysis of this is done through thermogravimetric\nanalysis (TGA) to investigate cyclability and particle size dependence. Synchrotron transmission x-\nray microscopy (TXM) is used to measure 2D chemical and 3D morphological changes in-situ. SEM\nis lastly used to analyze changes in the surface structure through cycling. By combining these, the\nauthors present a well corroborated mechanism through which the thermal cycling affects the\nreaction kinetics for micro- and nanoscale particles.\nWe found this an interesting and compelling read, with implications for the development of cobalt\noxide, and perhaps more broadly metal oxides, as a heat storage material. Given the change in\nreaction rate when going from micro to macro, which is well documented in literature, the observed\ndifferences between the nano- and microparticles outlined in this work were expected to follow this\ntrend and are thus generally not surprising. The strength of this manuscript however lies in the\ncombination of various used methodologies (e.g., using TXM to track changes occurring on the\nnanoscale, in-situ), which provides new insights.\nHowever, we have some concerns about the presentation and wider relevancy of the work.\n[Response]\nWe sincerely thank the reviewer for the thoughtful and encouraging feedback. We appreciate the recognition\nof the strength of our work in leveraging in situ techniques to provide new insights into\nnanoscale/microscale kinetics.\nWe have carefully considered the reviewer’s comments regarding the broader relevance, and we have\nrevised the manuscript accordingly to clarify the novelty and general significance of our findings. Specific\nresponses and revisions are detailed in the point-by-point responses below.\n1. Reduction in reaction kinetics in microparticles is attributed to a reduction in specific surface area\nthrough a combination of sintering, coarsening, and the development of internal porosity. In\nnanoparticles, on the other hand, no reduction in reaction kinetics is observed. We would like to\nconsider the application where a large energy storage capacity and density are desired. How can the\nresults from this study be applied to the development of a stable material? Is the deposition of a single\nlayer of micro- or nanoparticles on a (macroporous) substrate sufficient to obtain competitive\nperformance characteristics? If not, would a tight packing of the given particles not result in more\nsintering and thus a departure from micro or nano particles?\n[Response]\nWe agree that a macroporous substrate can be beneficial in practical applications, provided it remains\nchemically and structurally stable and prevents interdiffusion with the deposited layer. While a single layer\nis not necessary, applying a thin layer of micro- or nanoparticles onto such a substrate may help preserve a\nporous structure, facilitate gas transport, and limit sintering.\nPacking particles more densely may also be advantageous for achieving high energy density. However, as\nhighlighted in current study, sintering remains a major challenge. Strategies to mitigate or inhibit sintering,\nsuch as doping to suppress ion diffusion, can help preserve the porous structure generated during thermal\ncycles. This in turn maintains a higher surface area and improves overall performance.\nImportantly, our findings indicate that not all pores contribute positively to cycling performance.\nSpecifically, internal pores, especially those that trap oxygen, can locally increase the oxygen partial\npressure, impeding the reduction of Co O to CoO. These internal pores are likely formed not only due to\n3 4\ngas evolution but also through the closure of external pores during coarsening and sintering.\nIn contrast, the nanoparticle sample exhibited minimal porous structure formation and maintained stable\nperformance, at least over the first two cycles. This underscores the importance of a high specific surface\narea in enhancing conversion efficiency during thermal cycling. In fact, preserving an effective porous\nstructure, specifically open pores, contributes to a larger specific surface area. Therefore, minimizing\ninternal pore and isolated pore formation and preventing open pore closure, which help preserve a high\nspecific surface area are critical to sustaining performance over repeated cycles.\n[Changes] We modified the last paragraph in the “Conclusion” section\nOverall, nanoparticles showed a faster conversion rate without forming porous structures, while\nmicroparticles tended to form internal pores, which may lower the conversion rate over cycles, presenting\na challenge for long-term stability and efficiency. Therefore, understanding the degradation mechanisms\nwith different particle sizes and the effect of porous structures is crucial for optimizing the performance of\nCo O as a thermochemical material in practical applications.\n3 4\nOverall, nanoparticles exhibited a faster and more stable conversion without developing significant porous\nstructures, whereas microparticles were prone to forming internal and isolated pores, which can slow down\nthe reduction process and reduce long-term cycling performance. This highlights the importance of\nunderstanding how particle size and pore structure affect degradation during cycling. Future material design\nshould focus on approaches that prevent sintering and coarsening, such as adding dopants to help maintain\na stable structure with high surface area. In addition, promoting and preserving open porous networks can\nimprove gas exchange while reducing the formation of isolated pores that limit performance. Applying\nthese particles onto a chemically stable, macroporous support may further enhance structural stability and\nheat transfer by improving gas flow and reducing densification. Finally, adjusting thermal conductivity and\noxygen transport properties through material selection or structure changes may offer additional ways to\nimprove redox performance. Together, these insights provide a practical direction for developing\nthermochemical materials with better durability and efficiency under thermal cycling conditions.\n2. Co3O4 is used as a ‘representative’ TCM, citing various positive performance indicators with its\nbiggest challenge to widespread adoption being material reversibility\n2.1. To what extent is Co3O4 representative of metal oxides? and can the insights gained in this work\nthus be applied to other TCMs?\n[Response]\nWe appreciate the reviewer’s thoughtful question regarding the representativeness of Co O as a\n3 4\nthermochemical material and the broader applicability of our findings.\nCo O serves as a model system among transition metal oxides due to its well-defined redox properties,\n3 4\nrelatively low reduction temperature, and demonstrated reversibility under certain conditions. While each\nmetal oxide system has its own specific redox chemistry and structural behavior, many transition metal\noxides used in TCM applications, such as Mn O , Fe O , and CuO, undergo similar types of transformations\n2 3 2 3\nduring thermal cycling, including changes in oxidation state, structural rearrangements, and gas-evolving\nmorphological changes. These shared features suggest that the mechanistic insights gained from Co O ,\n3 4\nparticularly regarding pore evolution, sintering, and the impact of particle size on redox kinetics, can\nprovide valuable guidance for understanding and designing other TCM systems.\nWe acknowledge, however, that the specific kinetics, extent of structural degradation, and the interplay\nbetween chemical and morphological changes will vary across different oxides. Thus, while the trends\nobserved in this study may not translate directly to all systems, the principles, such as the importance of\nmaintaining open porous structures and minimizing sintering, are broadly applicable and offer a foundation\nfor understanding and then further optimizing the performance of other metal oxides TCM.\n[Changes] In section 4\nPost-TXM experiment analysis with SEM revealed that the initial microparticles had flat, sharply faceted\nsurfaces and became smoother and less faceted after the thermal redox cycle due to the coarsening process.\nAdditionally, larger, more continuous microparticles structures were observed due to sintering. These\nfindings demonstrate that Co O serves as a representative model for understanding redox-induced\n3 4\nstructural evolution in metal oxides, and the mechanistic insights gained here, particularly on pore evolution,\nsintering, and particle size effects, can be extended to guide the future studies, as well as design and\noptimization of other thermochemical materials.\n2.2. If not, is the methodology applicable to other materials as well, or are there restrictions on what\nmaterials can be tested this way, such as the working atmosphere, corrosivity or toxicity?\n[Response]\nWe thank the reviewer for raising this important point regarding the broader applicability of our\nmethodology. The main approach used in this study, the in situ synchrotron-based transmission X-ray\nmicroscopy is generally applicable to a wide range of thermochemical materials, including other metal\noxides beyond Co O . This technique is particularly valuable for studying systems that undergo chemical,\n3 4\nespecially the oxidation state changes and morphological changes during thermal cycling.\nWhile our current study was conducted in open air, the experimental setup can be adapted for more\ncontrolled environments in future work. Gas-controlled atmospheres can be implemented to study materials\nwith different oxygen partial pressure requirements, including other TCMs such as carbonates. For\nmaterials involving corrosive or toxic species, appropriate sealing and engineering controls, such as the use\nof flowing gas systems to safely collect and handle byproducts, can be employed to contain the material\nsecurely.\nIn summary, the methodology presented here is highly adaptable and has the potential to be extended to a\nwide range of TCMs beyond Co O .\n3 4\n[Changes] In section 4\nPost-TXM experiment analysis with SEM revealed that the initial microparticles had flat, sharply faceted\nsurfaces and became smoother and less faceted after the thermal redox cycle due to the coarsening process.\nAdditionally, larger, more continuous microparticles structures were observed due to sintering. … Moreover,\nthe in situ synchrotron-based imaging methodology used in this work is highly adaptable. It can be applied\nto a broad range of TCMs under controlled atmospheres or reactive conditions, and with proper containment,\neven to materials that are corrosive or toxic, thereby providing a versatile platform for investigating\nchemical and morphological evolution across diverse material systems.\n2.3. Cobalt oxide as a material is costly and has ethical concerns regarding its procurement.\nConsidering this, is widespread adoption, in the authors’ views, still reasonable?\n[Response]\nIn this study, Co O was chosen primarily as a model material due to its well-characterized redox behavior\n3 4\nand suitability for investigating fundamental thermal cycling mechanisms in thermochemical materials. We\nacknowledge that cobalt is relatively costly and has associated ethical concerns regarding its sourcing,\nwhich may limit its widespread commercial adoption for large-scale energy storage.\nThe mechanistic insights gained here can inform the development of alternative materials with reduced\ncobalt content or entirely different compositions that address cost and ethical constraints. Future work may\nexplore such alternatives, including Co O mixed with other metal oxides or entirely different transition\n3 4\nmetal oxides. By understanding the key factors governing performance and degradation in Co O , we aim\n3 4\nto provide a foundation for rational design across a broader range of thermochemical materials. Therefore,\nwe have changed the description in the Introduction section.\n[Changes] Changed this description in the Introduction section.\nCo O , one of the multivalent metal oxides used as TCMs, has Multivalent metal oxides have emerged as a\n3 4\npromising candidate due to TCMs for TES systems because of its their high energy storage capacity,\nfavorable reaction reversibility, suitable redox temperatures, and cost-effective working atmosphere 7-\n10.However, the widespread use of Co O in TES systems faces, challenges particularly in terms of such as\n3 4\nlimited material reversibility and performance degradation over multiple cycles remain 11-13. Among these\noxides, Co O is an ideal candidate for mechanistic studies, despite its relatively high material cost. Its well-\n3 4\ncharacterized redox behavior 14enables clear evaluation of reaction kinetics and pathways at the nano- and\nmeso-scales, providing insights that can guide the development of more cost-effective TCMs.\n3 4\ncouple with a cubic micro-nanostructure. Journal of Energy Storage 43, 103167 (2021).\n3. On line 155, a slowdown of the reduction process was noted for the microparticles in TXM, a result\nthat was not observed in the TGA results (figure 1). This is stated by the authors in line 221, who\nattribute this to the generation of fewer internal pores in the TGA. What could be the cause of this, a\ndifference in test conditions between TXM and TGA, randomness of the sample, or is there something\nelse? It would be generally helpful to outline if/how the testing conditions and samples might differ\nbetween the TXM and TGA.\n[Response] Thank you for this insightful comment. We agree that the difference in reduction behavior of\nCo O microparticles between the TXM and TGA experiments needs further clarification, particularly at\n3 4\n850°C. In the TXM experiment, we observed a back-and-forth redox reaction at 850°C (Figure 3), which\nwe believe results in the formation of a large number of isolated internal pores, as supported by the\nmorphological evidence shown in Figure 4. These isolated pores likely impede gas exchange and thus slow\nthe reduction process at 900°C. In contrast, no measurable mass change was observed at 850°C in the TGA\nexperiment, suggesting that the back-and-forth redox reaction did not occur.\nThe discrepancy likely arises from differences in experimental conditions and sample configurations\nbetween the two techniques. The TGA sample (~3 mg) is composed of densely packed micro-particles,\nwhile the TXM sample consists of a thin layer of micro-particles (~ few µg) attached to the inner wall of a\ncapillary. Differences in sample mass and geometry can lead to uneven and/or delayed heat transfer,\nparticularly in bulkier TGA samples, possibly resulting in a slight shift in the apparent onset temperature.\nIn our TGA measurements, the onset re-oxidation temperature was 811°C for microparticles and 816°C for\nnanoparticles. Therefore, at 850°C, the back-and-forth redox reaction did not occur in the TGA experiments.\nAs a result, pore evolution was likely minimal, and fewer internal pores were present in the TGA samples.\n[Changes] In section 2.1:\nInitially there was no significant weight change for the particles at 850°C. To further investigate the\ntemperature of the re-oxidation reaction, additional TGA scans were conducted under a controlled cooling\nrate of 2 °C/min, and the result is shown in Figure S2. But at 800°C, the nanoparticles increased in weight\nrapidly and fully converted to Co O in approximately 5 min. In contrast, the microparticles increased in\n3 4\nweight at a slower rate, and did not fully convert even after 30 min.\nIn Support Information\nFigure S2. Characterized onset temperature of the re-oxidation process for microparticles (A) and\nnanoparticles (B), based on mass change measured by TGA. The onset temperature is approximately 811°C\nfor microparticles and 816°C for nanoparticles.\nIn section 2.2\nIn the in-situ 2D XANES analysis, the conversion from CoO to Co O occurred at ~850°C as shown in\n3 4\nFigure 2(A)(e-h), but this re-oxidation process did not initiate in the TGA analysis at this temperature. A\nseparate DSC thermal analysis determined that the re-oxidation process of the microparticles initiate at\n~850°C, as shown in Figure S5. Literature reports the onset re-oxidation temperature as 850°C 12, 870°C\n13, and 879.7°C 5. These variations can reasonably be attributed to kinetic factors such as sample geometry,\nmass, and heat transfer behavior. Therefore, 850°C is likely the equilibrium temperature during the re-\noxidation process in the TXM experiment.\nIn section 3.2\nIn-situ 2D XANES imaging and nano-tomography were conducted on the particle samples enclosed in the\ncapillary, during thermal redox cycles in a temperature range of 800°C to 900°C with a versatile, compact\nheater after proper calibration 45 at the Full Field X-ray Imaging beamline (FXI, 18-ID) 46 at the National\nSynchrotron Light Source-II (NSLS-II) at Brookhaven National Laboratory (BNL).\nX-ray microscopy. Synchrotron Radiation 27, 746-752 (2020).\n4. Figure 1 could be improved for clarity. Currently the mass percentages are not normalized between\ngraphs, thus making it not straightforward to compare them directly. It would be helpful to indicate\nthe theoretical mass change to compare directly. Furthermore, the inclusion of DTG lines would help\ninterpret the rate of reaction, as the authors state there is no obvious degradation (line 115), but this\nis difficult to confirm just from the steep curves.\n[Response] Thank you for the helpful suggestion. In the revised Figure 1, we have normalized the weight\nchange based on the theoretical mass loss expected for the Co O to CoO conversion, allowing for clearer\n3 4\ncomparison between samples. Additionally, we have included the corresponding derivative\nthermogravimetry (DTG) curves to better illustrate the reaction rates.\n[Changes] Revised Figure 1 and the corresponding description in section 2.1.\nFigure 1. Thermogravimetric analysis curves of Co O microparticles and nanoparticles during one and five\n3 4\nthermal redox cycles; blue lines represent normalized weight change (actual weight loss divided by\ntheoretical weight loss for a complete Co O -to-CoO conversion), black lines indicate the temperature\n3 4\nprofile, and red lines show the derivative of mass change (DTG): (A-B) normalized weight change of\nmicroparticles (A) and nanoparticles (B) during one redox cycle (900–850–800–900°C); (C-D) normalized\nweight change and DTG curves of microparticles (C) and nanoparticles (D) over five redox cycles (900–\n800°C) with 30 min holding time at each temperature.\nIn section 2.1\nWhere T is temperature and T is transition temperature. The normalized weight loss was calculated as the\nc\nratio of the actual weight loss to theoretical weight loss, and the experimental results are presented in Figure\nS1. During the cooling process, the reverse direction of the reaction (2) took place.\nIn section 2.1\nAs shown in Figure 1 (C) and (D), there was no significant difference in the weight change for the Co O\n3 4\nparticles over five cycles. Additionally, the derivative of mass change remained consistent across the five\ncycles for both the micro- and nanoparticles, indicating that the conversion rate of Co O did not change\n3 4\nand that both particle types retained their reversibility throughout the cycles. indicating that both the micro\nand nano particles of Co O retained their reversibility. Therefore, there was no obvious degradation in the\n3 4\nmicro and nano particles of Co O during the short-term thermal redox cycles under the current cycling\n3 4\nconditions, which is consistent with the literature data 18.\n5. Multiple times the authors use the ‘reaction efficiency’ when appearing to refer to the reaction\nkinetics. This is ambiguous and non-standard terminology which we recommend changing.\n[Response]\nThank you for the valuable suggestion regarding the terminology. To improve clarity and align with\nstandard usage of the terms, we will replace instances of “redox efficiency” and “conversion efficiency”\nwith “redox rate” and “conversion rate,” respectively, when referring to the speed of the chemical reaction.\nWe recognize that “reaction kinetics” is a broader term including both reaction rates and pathways, and we\nwill use it accordingly where appropriate.\n[Changes] Changed “redox efficiency” and “conversion efficiency” with “redox rate” and “conversion rate”\nwhen referring to the speed.\n6. The timepoints taken for Figure 2-C and F, as well as those in Figure 3-A and B, are not distributed\nuniformly. We would like to know the reasoning for this, as it obfuscates the interpretation of the\nresults.\n[Response]\nWe thank the reviewer for pointing this out. The timepoints shown in Figures 2-C, 2-F, 3-A, and 3-B are\nindeed not uniformly spaced due to several practical considerations during in situ measurements.\nRepresentative data are presented in Figure 2 for clarity, while the complete datasets are provided in the\nSupporting Information videos and fully plotted in Figure 3.\nSpecifically, gaps in data collection, particularly toward the later stages, occurred because of the need to\nperform tomographic scans to capture the morphology at each stage of the thermal cycle, during which no\nsignificant chemical or structural changes were observed. Ideally, the first scan would be acquired\nimmediately after reaching the target temperature; however, additional time is required to realign the sample\nprecisely at the center of the field of view. This occasionally creates a delay between temperature\nstabilization and the initial scan, especially for the microparticle samples. This may be because significant\nmorphological changes cause the microparticles to shift with temperature fluctuations, requiring additional\ntime to realign the samples after temperature changes.\nWe hope this explanation clarifies the observed timepoint distribution and its impact on data interpretation.\n7. In Figure 3-C and D, the horizontal axis indicates the amount of Co. Although explained on line\n171, it is not clear from the image or the caption that this is on a per pixel basis. We suggest adding\nthis for clarity.\n[Response]\nWe have changed the caption of Figure 3.\n[Changes] Caption of Figure 3.\nFigure 3. The fraction of CoO in the microparticle (A) and nanoparticle (B), during thermal redox cycles.\n(C) and (D) show the conversion as a function of the amount of Co per pixel, given in relative units\nproportional to the molar amount of Co, in the microparticle and nanoparticle, respectively, as well as the\nconversion depending on the amount of Co in the microparticle (C) and nanoparticle (D) during thermal\nredox cycles, which are calculated based on the 2D XANES images.\n8. Through power-law fitting of the characteristic length, seen in Figure 5-C and D, the authors reason\nthat surface diffusion dominates the coarsening in the microparticles. However it was not clear from\nthe text how these results support this conclusion, so we would like the authors to elaborate on this.\n[Response]\nWe thank the reviewer for this important comment. To clarify, the power-law exponent n obtained from\nfitting the characteristic length l versus time reflects the rate-determining mechanism controlling\nc\ncoarsening. According to established theory, an exponent n=3 corresponds to bulk diffusion control, while\nn=4 indicates surface diffusion control. Our fitting results show that plotting l 4 versus time yields a higher\nc\ngoodness-of-fit (R2 = 0.96) compared to l 3 versus time (R2 = 0.70), strongly suggesting that surface\nc\ndiffusion is the dominant coarsening mechanism in the microparticles under our experimental conditions.\nThis approach, commonly used in coarsening studies, allows us to infer the controlling diffusion pathway\nbased on the kinetic exponent.\n[Changes] In the discussion of power law in section 2.4.\nwhere different values of n correspond to different mechanisms: n = 3 for bulk diffusion, and n = 4 for\nsurface diffusion 26,33,34. Other coarsening mechanisms such as viscous flow and evaporation/re-\ncondensation were not considered in this study. The fitting line was set to intercept at the origin, as\ncoarsening likely began when the temperature was raised to 900°C. As shown in Figures 5(C)-(D), the fit\nof l c 4 versus time exhibited a higher goodness-of-fit (R2 = 0.96) than l c 3 versus time (R2 = 0.70). This result\nindicates that surface diffusion is the rate-determining mechanism controlling coarsening in the\nmicroparticles under this condition. The fitting results are shown in Error! Reference source not\nfound.(C)-(D); l 4 versus t showed a better fit with a higher goodness of fit, R² value of 0.96, compared to\nc\n0.70 for l 3 versus t, indicating that coarsening in the particle was dominated by surface diffusion 30.\nc\nReviewer #3 (Remarks to the Author):\nI co-reviewed this manuscript with one of the reviewers who provided the listed reports. This\nis part of the Nature Communications initiative to facilitate training in peer review and to\nprovide appropriate recognition for Early Career Researchers who co-review manuscripts.\n[Response] Thank you for letting us know. We appreciate Nature Communications’ initiative to support the\ntraining and recognition of Early Career Researchers through co-reviewing. We are grateful for the\nthoughtful feedback provided and hope that our revisions address the comments raised by you and your co-\nreviewer.\nReviewer #4 (Remarks to the Author):\nThe manuscript presents a multi-mode operando X-ray characterization of thermochemical energy\nstorage in cobalt oxide particles. Both XANES and nano-scale X-ray CT are applied to analysis the\nspatial distributions of oxidation and the changes in the 3D morphology. The results show interesting\nevolutions of the particle structure with temperature cycling and a clever length scale analysis is used\nto evaluate whether process is bulk or surface transport driven. The quality of the characterization\nand image analysis is high and the results are intriguing from both the materials point of view and\nthe analytical method development an demonstration for operando high temperature cycling of\nthermochemical materials. I recommend publication with minor revisions.\n[Response] We sincerely thank the reviewer for the positive and encouraging feedback. We are glad that\nthe reviewer finds our operando X-ray characterization and the associated image analysis to be of high\nquality. We appreciate the work is recognized as valuable from both a materials science and analytical\nmethods perspective. We have addressed the minor revisions as suggested.\n• It seems a significant missing component of the main manuscript is the quantification of the heat\nabsorbed and desorbed during the reduction and oxidation cycles. It would likely not be viable during\nTXM or XANES, but it could be done separately on similar samples. Given the application, it seems\nthat evaluating the correlation between the processes with micro and nano particles should include\nevaluation of the heat capacity. However, a discussion of the heat capacity is mostly absent beyond\nthe basic introduction. Some discussion of the heat flow results of Figure S1 for the micro-particles\ncould be added to the main manuscript. Are there corresponding results for the nano-particles? Is\nthe heat consistent with other measurements of the thermal capacity?\n[Response] Thank you for this insightful comment. The heat capacity and enthalpy of the Co O to CoO\n3 4\nredox reaction have been previously reported in the literature. In this study, Co O is primarily used as a\n3 4\nmodel material to demonstrate our multimodal characterization approach, and a detailed evaluation of its\nheat capacity was not the main focus. However, in response to the reviewer’s suggestion, we have now\nperformed simultaneous DSC and TGA measurements on both the microparticle and nanoparticle samples,\nand we have included the results in the revised Supporting Information. The changes are made in the\nfollowing comment concerning similar issues.\nWe note that the measured enthalpy for the oxidation reaction is approximately 380 J/g, which differs from\nthe commonly reported value of 562 J/g [1]. To avoid confusion, we have chosen to present and discuss\nthese results in the Supporting Information rather than in the main text, while acknowledging the variation\nand its potential implications. This change is also made in the following comment.\n[1] Block, Tina, and Martin Schmücker. \"Metal oxides for thermochemical energy storage: A comparison\nof several metal oxide systems.\" Solar Energy 126 (2016): 195-207.\n1) Some correlation analysis of the heat flow to the fraction of C[o]O would be worth investigating,\neven if just using the microparticle DSC data in Figure S1.\n[Response] We appreciate the reviewer’s suggestion. To address this, we conducted additional\nsimultaneous TGA and DSC measurements for the reoxidation process of both micro- and nanoparticles\nfrom CoO to Co O at a heating rate of 2 °C/min. This analysis enables us to correlate the CoO conversion\n3 4\nfraction using these two techniques. The corresponding plots have been included in the revised Supporting\nInformation.\n[Changes] In section 3.1\nThe thermal redox cycles of Co O micro and nano particles were evaluated using a thermogravimetric and\n3 4\ndifferential scanning calorimetry analyzer (TGA, Mettler Toledo TGA/DSC 3+) at atmospheric pressure.\nIn section 2.1\nIn contrast, the microparticles increased in weight at a slower rate, and did not fully convert even after 30\nmin. To further examine the conversion fraction of CoO during the reoxidation process, we performed\nadditional simultaneous TGA–DSC experiments, with the results presented in Figure S3.\nIn Supporting Information\nFigure S3. Simultaneous differential scanning calorimetry and thermogravimetric analysis curves of Co O\n3 4\nmicroparticles and nanoparticles during reoxidation process (900–750°C); red lines represent heat flow\nchange, black lines indicate the temperature profile, blue lines show the weight change: (A-B) heat flow\ncurves of microparticles (A) and nanoparticles (B). (C-D) weight change of microparticles (C) and\nnanoparticles (D).\nIn Figure S3, the measured enthalpy of the reoxidation reaction from CoO to Co O is 380.89 J/g for the\n3 4\nmicroparticle sample and 383.71 J/g for the nanoparticle sample. Furthermore, an independent\nmeasurement conducted using the DSC404 F3 Pegasus (Netzsch) yielded an enthalpy of 386.3 J/g for the\nmicroparticle sample (Figure S5). These results demonstrate consistency across different instruments and\ndifferent sample sets, providing confidence in the measured values.\nSome studies have noted that the reported enthalpy values for the CoO/Co O redox reaction can vary\n3 4\ndepending on the source and preparation of the Co O sample. For example, one study reported values of\n3 4\n3 4\ncontrast, the theoretical enthalpy for the complete reoxidation of CoO to Co O is reported to be 844 J/g [2].\n3 4\nWhen compared with this theoretical value, our measured enthalpies correspond to an apparent conversion\nfraction of only ~45%.\nHowever, the simultaneous TGA analysis suggests a much higher conversion. Based on the mass change\nduring reoxidation and applying equation (1), the calculated conversion ratios are 95.1% for microparticles\nand 99.8% for nanoparticles:\n∆𝑚 6𝑀\n𝐶𝑜𝑂\n× (1)\n𝑚 𝑀\n0 𝑂2\nWhere ∆𝑚 is the weight gain after reoxidation, 𝑚 is the initial weight, 𝑀 is atomic weight of CoO, and\n0 𝐶𝑜𝑂\n𝑀 is atomic weight of O .\n𝑂2 2\nIdeally, the conversion fractions determined from DSC and TGA should be comparable, yet our results\nhighlight a clear discrepancy. This suggests that the enthalpy value corresponding to 100% conversion may\ndiffer for our samples. The theoretical enthalpy value of 844 J/g may not be an appropriate reference point\nfor our samples, and conversion fractions based solely on enthalpy cannot be reliably calculated in this case.\n[1] Agrafiotis, Christos, et al. \"Exploitation of thermochemical cycles based on solid oxide redox systems\nfor thermochemical storage of solar heat. Part 1: Testing of cobalt oxide-based powders.\" Solar Energy 102\n(2014): 189-211.\n[2] Wong, B. \"Thermochemical heat storage for concentrated solar power.\" Final Report for the US\nDepartment of Energy (2011).\n2) Line 217 – is sintering a process that would form porosity within a solid?\n[Response] In our original manuscript, we used the term \"internal pores,\" but a more accurate description\nin the context of sintering is \"isolated pores\" that form between particles as they merge together through\nthe sintering process. These are not pores formed within a single solid but rather in the spaces between\npartially coalesced particles during sintering. When discussing the evolution within a single particle,\nparticularly the formation of isolated pores due to oxygen evolution or structural rearrangement, the term\n\"internal pores\" remains appropriate. We have revised the text to clarify this distinction.\n[Changes] In section 2.3.\n“internal pores” changed to “internal and isolated pores” and “external pores\" changed to \"open pores”.\nFigure 4(C) shows the 3D volume rendering of the particles, with the internal and isolated pores displayed\nin the sub-figures. Internal pores formed within a particle because of O evolution, whereas isolated pores\n2\noriginated from sintering.\n3) It seems like in the XANSES has a lower threshold of Co fraction that is saturated (purple). Is\nthere variation below the roughly zero threshold that is missing in the images of Figure 2?\n[Response] Thank you for the thoughtful observation. We would like to clarify that the purple color in the\nXANES images corresponds to a CoO fraction of zero, indicating regions that are fully re-oxidized to Co O .\n3 4\nThere is no issue with saturation in these images. In the original manuscript, a mask was applied during\ndata processing to filter out pixels where the sample amount is too low and does not show sufficient edge\njump in the Co XANES. This processing step is described in the Supporting Information (Figure S10). In\nthis process, we used a -0.1 value to indicate the masked region. This -0.1 value was also included in the\ncolor scale, which may have caused confusion. In response to the reviewer’s suggestion, we have adjusted\nthe color scale bar in Figure 2 in the revised manuscript to more clearly reflect the valid range of CoO\nfractions and to avoid potential misinterpretation.\n[Changes] Figure 2: color scale bar.\nFigure 2. The evolution of chemical states of Co O for different particle sizes as a function of thermal\n3 4\nredox cycles: (A)-(C) microparticles and (D)-(F) nanoparticles: (A, D) Fitted 2D XANES images reflecting\nthe atomic ratio of Co in CoO phase at different temperatures and time points. (B, E) Enlarged view of (A-\nh) for microparticles and (D-g) for nanoparticles, highlighting particle heterogeneity and corresponding\nXANES spectra, where μ indicates the X-ray attenuation. (C, F) Temperature profile during the in-situ\nexperiment, indicating time points (a-p) for imaging data collection. Note that black color in the XANES\nimages indicates a masked region where the sample amount is negligible.\n4) The terminology of external and internal pores is a bit confusing. All pores are internal, but the\nexternal pores seem to be described as those with a connection to the external void volume. Perhaps\nis just “connected pores” and “isolated pores”.\n[Response] Thank you for the helpful suggestion regarding pore terminology. We agree that the terms\n\"external\" and \"internal\" pores may cause confusion. In our revised manuscript, we have adopted the more\nprecise terms \"open pores\" (those open to the external void space) and \"isolated pores\" (those enclosed\nbetween particles and not connected to the surface). However, the “internal pores” are still used to describe\nthe isolated pores in one particle.\nSpecifically, in Figure 4, the isolated pores result from the sintering process, where particles merge together\nand enclose voids between them. In Figure 5, the internal pores are formed within individual particles,\nlikely due to structural changes during redox cycling. We have revised the manuscript text accordingly to\nreflect this clarification and improve consistency.\n[Changes] in section 2.4\n“external pores\" changed to \"open pores”.\nIn Figure 5 (G). label “External” changed to \"Open\"."}, {"round": 2, "reviewer_comments": {"reviewer_1": "The questions and suggestions I raised have been thoroughly revised. This manuscript can be published.\nBut please check the units of the vertical axis in Figure 1, it seems to be missing;", "reviewer_2": "The authors addressed all the raised questions with convincing answers, as such we recommend the paper for the publication.", "reviewer_3": "I co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature Communications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career Researchers who co-review manuscripts.", "reviewer_4": "The response to the reviewer comments is thorough and satisfactorily addresses the concerns of this reviewer. I recommend accepting for publication."}, "author_response": "[Response] We appreciate the reviewer’s careful observation. The units for the y-axis in Figure 1\nhave now been added in the revised manuscript.\n[Change] Added unit in y-axis in Figure 1\n[Response] We sincerely thank the reviewer for the positive evaluation and recommendation for\npublication. We greatly appreciate the reviewer’s time and constructive feedback, which helped us\nimprove the quality and clarity of the manuscript.\n[Response] We thank both the reviewer and the co-reviewer for their valuable time and insightful\nfeedback, which have greatly helped us improve the manuscript.\n[Response] We sincerely thank the reviewer for the positive feedback and recommendation for\npublication. We truly appreciate the reviewer’s thoughtful comments and valuable time throughout\nthe review process."}]

Decision letter