Atomic surface structure for unraveling the trade-off between the propane dehydrogenation activity and anti-deactivation of PtSn catalysts

Abstract

In commercial Pt-based propane dehydrogenation catalysts, Sn doping is a fascinating strategy to suppress side reactions and optimize selectivity. Nevertheless, excessive Sn incorporation results in a decline in surface Pt sites, leading to a significant reduction in catalytic activity. It challenges the precision of surface chemical design and the atomic unraveling of surface coordination is critical to resolving the inherent trade-off between catalytic activity and anti-deactivation. In this work, we modulated PtSn catalyst surface structures by controlling the Sn content, achieving optimal activity, anti-deactivation, and selectivity. Building upon the average structural characterization, we further resolved three-dimensional atomic configurations and extracted surface structures of catalysts by integrating the Reverse Monte Carlo method with pair distribution function analysis. It was found that the increasing Sn content enhances anti-deactivation by reducing surface Pt–Pt coordination numbers; this effect reaches saturation when the coordination number on the surface approaches approximately 3. Beyond this critical threshold, additional Sn incorporation compromises activity through Pt site blockage while offering a negligible effect on anti-deactivation. These findings provide clear guidelines for the rational surface design of nanocatalysts and synthesis of high-performance platinum-based catalysts with superior catalytic properties.

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Introduction

The remarkable alkane adsorption capacity and C–H bond activation capabilities of platinum underscore its widespread use as a commercial catalyst for the dehydrogenation of light alkanes in industrial applications.^1,2 Nonetheless, the pronounced activity of platinum catalysts impedes the desorption of olefins,³ thereby promoting unintended reactions such as cracking and deep dehydrogenation.⁴ These adverse reactions severely degrade catalyst selectivity and accelerate carbon-induced deactivation.⁵ The introduction of heterogeneous metals to modulate the coordination environment and regulate the olefin adsorption capacity of Pt atoms represents a predominant strategy for enhancing catalytic performance.⁶ However, the incorporation of heterogeneous metals generally induces elemental segregation like Fe,⁷ Zn,⁸ and Co,⁹ with the specific segregation patterns being highly dependent on the nature of the doping elements. This phenomenon leads to the formation of diverse coordination environments for Pt atoms on the catalyst surface, consequently resulting in varied impacts on the catalytic performance.¹⁰

In the catalytic dehydrogenation of light alkanes, industrial-grade catalysts commonly employ Sn as a promoter element to form bimetallic PtSn nanocatalysts, which have shown remarkable effectiveness in optimizing catalytic performance metrics.¹¹ The strategic incorporation of Sn not only effectively stabilizes the catalyst particle size below the critical threshold of 5 nm under demanding propane dehydrogenation conditions (typically 550–700 °C), but also induces significant modifications in the coordination geometry of surface Pt atoms, thereby optimizing their electronic structure and catalytic properties.^12,13 In PtSn bimetallic catalysts, platinum atoms are widely acknowledged as the active centers for alkane dehydrogenation,³ but tin atoms do not participate directly in catalytic activity.¹⁴ Notably, the transformation of alkanes into olefins is structurally insensitive,¹⁵ whereas the deep dehydrogenation and cracking of olefins are structurally sensitive,^16,17 emphasizing the importance of the catalyst's structural properties in governing these secondary reactions. Meanwhile, the changes in the coordination environment of Pt atoms on the catalyst surface resulting from Sn doping play a critical role in improving propylene selectivity and enhancing resistance to deactivation.^18,19 The introduction of Sn not only modifies the catalyst's surface structure but also decreases the population of surface Pt atoms, which subsequently results in a reduction in catalytic activity.¹⁷

The fundamental challenge in designing catalysts with superior overall performance lies in reconciling the trade-offs among selectivity, anti-deactivation, and catalytic activity. This requires a comprehensive understanding of the intricate modifications in the coordination environment of surface platinum (Pt) atoms induced by the incorporation of tin (Sn), as well as the determination of the optimal structural configuration.²⁰ However, the segregation of Pt and Sn elements in nanocatalysts represents a prevalent phenomenon, which is significantly influenced by variations in support materials and pretreatment conditions.^21,22 This heterogeneity results in a pronounced discrepancy between the surface structure and the overall average structure of the catalyst. Relying solely on average structural characterization fails to accurately capture the true state of the catalyst surface.²³ Therefore, in addition to analyzing the average structure, it is imperative to investigate the local structural features and resolve the three-dimensional architecture of the catalyst. Such comprehensive structural analysis is crucial for the rational optimization of catalytic performance.^24,25

In this study, a series of PtSn catalysts with distinct structural configurations were synthesized by systematically varying the Sn content. Among these, a PtSn catalyst exhibiting exceptional comprehensive performance in the propane dehydrogenation process was identified. Beyond the average structural information, we employed X-ray atomic Pair Distribution Function (PDF) analysis coupled with the Reverse Monte Carlo (RMC) method to resolve the three-dimensional atomic arrangements and extract the surface structure of the catalyst. It revealed a significant threshold of surface Pt–Pt coordination to balance selectivity and anti-deactivation properties. These findings establish a fundamental framework for designing commercially viable PtSn catalysts with enhanced performance, highlighting the critical role of the surface coordination structure in governing catalytic behavior.

Results and discussion

Synthesizing PtSn catalysts with varied Sn contents

Controlling the Sn content represents an effective approach to tailoring the local structure of Pt atoms. In this study, a series of PtSn/SiO₂ catalysts, samples 1–4, were synthesized by varying the Sn precursor amount while keeping the Pt precursor constant. As shown in Fig. 1a, PtSn catalysts were prepared by a step-by-step impregnation method where Sn was first loaded onto the SiO₂ support followed by Pt deposition, and the precursor was then reduced by hydrogen at 580 °C after one week of aging at room temperature. Table S1† shows the chemical composition of the four catalysts, which was determined by inductively coupled plasma optical emission spectroscopy (ICP-OES) to be Pt₈₀Sn₂₀, Pt₅₃Sn₄₇, Pt₄₂Sn₅₈, and Pt₃₃Sn₆₇.

Fig. 1 (a) Schematic flow of PtSn catalyst synthesis and (b) X-ray powder diffraction patterns of Pt₈₀Sn₂₀, Pt₅₃Sn₄₇, Pt₄₂Sn₅₈, and Pt₃₃Sn₆₇. (c) The schematic illustrating the variation of PtSn nanocatalysts with changing Sn loading. HRTEM and FTT image of (d) Pt₈₀Sn₂₀, (e) Pt₅₃Sn₄₇, (f) Pt₄₂Sn₅₈, and (g) Pt₃₃Sn₆₇.

The long-range average structure of these catalysts is shown in the X-ray powder diffraction pattern (Fig. 1b). As the Sn content rises, the phase of the catalysts transitions from a single Pt₃Sn phase (Pt₈₀Sn₂₀) to mixed Pt₃Sn and PtSn phases (Pt₅₃Sn₄₇ and Pt₄₂Sn₅₈) and eventually converts to a single PtSn (Pt₃₃Sn₆₇) phase. As illustrated in Fig. 1c, the structural evolution of the catalyst system is clearly demonstrated, with increasing Sn content driving a distinct phase transformation from a Pt-rich cubic structure to a Sn-dominated hexagonal configuration. This structural transition exhibits a direct correlation with a progressive decrease in the Pt–Pt coordination number in the catalyst's average structure. The phase transition process was also observed using high-resolution transmission electron microscopy in specific nanoparticles; in the Pt₈₀Sn₂₀ sample, the (111) and (200) planes of the Pt₃Sn phase with d = 2.01 and 2.33 Å, respectively, were visible (Fig. 1d) and in Pt₃₃Sn₆₇ only the (102) plane of the PtSn phase with d = 2.17 Å was observed (Fig. 1g), but in Pt₅₃Sn₄₇ and Pt₄₂Sn₅₈ samples, we could observe both the (111) plane of the Pt₃Sn phase and the (102) plane of the PtSn phase in one nanoparticle (Fig. 1e and f), indicating that this mixed-phase plane exposure situation is common.^26,27 The particle size of the PtSn nanocatalysts was determined by HAADF-STEM. As shown in Fig. S1† the particle size in the PtSn nanocatalysts is mainly distributed between 2–4 nm, and it increases slightly as the content of Sn increases. This is consistent with the results obtained from CO-pulse chemisorption (Table S2†), which further indicates that Pt dispersion on the catalyst surface decreases from 57.23% to 29.04% with increasing Sn content.

Evaluation of catalytic performance

To quantitatively assess the catalytic performance variations, the propane dehydrogenation activity of the PtSn catalysts was systematically evaluated using a fixed-bed reactor system operated at 580 °C under atmospheric pressure, with a weight hourly space velocity (WHSV) of 5.9 h⁻¹ (C₃H₈ : N₂ = 1 : 9). As shown in Fig. 2a, Pt₈₀Sn₂₀ shows an initial conversion rate of 54.3%, which is the highest among Pt₈₀Sn₂₀, Pt₅₃Sn₄₇, Pt₄₂Sn₅₈, and Pt₃₃Sn₆₇ catalysts, but it has the lowest initial propylene selectivity (Fig. 2b) and poor resistance to deactivation. Although the initial activity of the catalysts decreased with increasing Sn content, propylene selectivity and resistance to deactivation improved significantly (Fig. 2c). The Pt₄₂Sn₅₈ catalyst exhibits exceptional catalytic performance, achieving 99.5% propylene selectivity with a deactivation rate an order of magnitude lower than that of the Pt₈₀Sn₂₀ catalyst, despite only a marginal 3% reduction in initial activity. Notably, this catalyst demonstrates outstanding resistance to carbon deposition among Pt-based catalytic systems reported to date (Fig. S2†). Meanwhile, when the content of Sn continued increase on the basis of Pt₄₂Sn₅₈ elemental composition, the catalyst's performance of propylene selectivity and anti-deactivation improved only little, but the activity was significantly decreased. These experimental findings reveal that the Pt₄₂Sn₅₈ catalyst achieves an optimal balance between catalytic activity and resistance to deactivation in direct propane dehydrogenation, attributable to its appropriate surface architecture that facilitates both reactant activation and coke resistance. Meanwhile, the catalyst demonstrates exceptional operational stability, maintaining its performance over an 100-hour testing period (Fig. 2g). The FT-IR spectrum and TG curves of Pt₈₀Sn₂₀, Pt₅₃Sn₄₇, Pt₄₂Sn₅₈, and Pt₃₃Sn₆₇ catalysts after six hours of reaction were measured to study the behavior of deposited carbon during the deactivation process. As illustrated in Fig. 2d, the FT-IR spectrum exhibits characteristic absorption bands in the ranges of 1550–1700 cm⁻¹ and 2850–2960 cm⁻¹, corresponding to the stretching vibrations of C–C and C–H bonds, respectively.²⁸ These spectral features indicate the presence of carbonaceous deposits on the spent catalyst, which are known to deactivate the catalyst through the physical blockage of active sites. The TG curves of the used catalyst show the loss of coke material during the heating process (Fig. 2e),²⁹ and the used Pt₄₂Sn₅₈ and Pt₃₃Sn₆₇ samples exhibit a minimal loss of carbon, about 1.4%, while the Pt₈₀Sn₂₀ sample shows a higher carbon loss of about 2.2%. This corresponds to their deactivation rates and indicates that the excellent resistance to deactivation performance arises from a favorable resistance to carbon material generation.³⁰

Fig. 2 Time on-stream for (a) propone conversion and (b) propylene selectivity for PtSn catalysts. (c) Deactivation rates of Pt₈₀Sn₂₀ (purple), Pt₅₃Sn₄₇ (blue), Pt₄₂Sn₅₈ (red), and Pt₃₃Sn₆₇ (yellow) catalysts. (d) FT-IR spectra of the spent PtSn catalysts collected at 6 h on stream. (e) TG curves of the spent PtSn catalysts collected at 6 h on stream. (f) CO adsorbed FT-IR spectra of PtSn catalysts. (g) Stability test of the Pt₄₂Sn₅₈ catalyst.

Catalyst surface coordination structure analysis

Based on a comprehensive analysis of the experimental results, it is evident that the variation in Sn content exerts a substantial influence on both the structural characteristics and catalytic properties of the materials. Through systematic optimization of the Sn composition, a catalyst demonstrating superior overall performance has been successfully developed. This appears to be related to the transition in the long-range structure of the catalysts; when the catalysts transition from the pure Pt₃Sn phase to the pure PtSn phase, both the deactivation and propane conversion rate decrease significantly. This seems to prove that the Pt₃Sn phase is the reason for high catalytic activity and rapid deactivation of PtSn catalysts. However, the Pt₄₂Sn₅₈ sample contained nearly half of the Pt₃Sn phase; its resistance to carbon deactivation is still similar to that of the pure PtSn phase catalysts, while its initial conversion is 5% higher than that of the pure PtSn phase catalysts. It is difficult to explain this phenomenon using the average structure; the key to solving the challenge is analyzing the surface structural changes of Pt₈₀Sn₂₀, Pt₅₃Sn₄₇, Pt₄₂Sn₅₈, and Pt₃₃Sn₆₇ samples. Within the PtSn catalytic system, comprehensive characterization and mechanistic studies have revealed that platinum atoms serve as the exclusive active sites for both propane adsorption and propylene desorption processes. In contrast, spectroscopic analysis and kinetic studies demonstrate that tin atoms remain catalytically inert throughout the reaction pathway.³¹ Therefore, the primary research focus should be directed toward elucidating the structural evolution of Pt active sites. CO-FTIR is a favorable tool for characterizing differences in the catalyst surface structure;³² as illustrated in Fig. 2f, the PtSn catalyst system exhibits a characteristic absorption band centered at approximately 2080 cm⁻¹, which can be assigned to the linearly adsorbed CO species on Pt sites. And the intensity of the CO adsorption peak decreases with increasing Sn content, indicating that the incorporation of Sn reduces the surface exposure of Pt sites.³³ Meanwhile, when observing the CO adsorption peaks in the Pt₈₀Sn₂₀, Pt₅₃Sn₄₇, Pt₄₂Sn₅₈, and Pt₃₃Sn₆₇ samples, the absorption band centers of Pt₈₀Sn₂₀ and Pt₅₃Sn₄₇ samples are lower than those of Pt₄₂Sn₅₈ and Pt₃₃Sn₆₇, which suggests a change in the coordination environment of surface Pt; however, further identification of the surface structures is difficult.³⁴

Furthermore, the average changes in the electronic structure and coordination environment of the Pt₈₀Sn₂₀, Pt₅₃Sn₄₇, Pt₄₂Sn₅₈, and Pt₃₃Sn₆₇ samples are investigated by XAFS. As shown in Fig. S3,† increasing Sn content induces a positive Pt L₃-edge energy shift, which is corroborated by the corresponding XPS data (Fig. S4†). Concurrently, the attenuated white-line intensity is indicative of an enhanced Pt 5d electron density. This electronic modification, induced by Sn-mediated modulation of the Pt coordination environment, results in a reduction in the energy of the antibonding orbitals. It facilitates the desorption of propylene, which consequently suppresses further side reactions of propylene and optimizes catalytic anti-deactivation through controlled reaction pathways.³⁵ The wavelet transform EXAFS analysis of the Pt L₃-edge elucidates Sn-dependent coordination evolution (Fig. 3a), where increasing Sn content attenuates Pt–Pt coordination signals above 10 Å⁻¹ (Fig. S5†) while simultaneously enhancing Pt–Sn spectral features below 10 Å⁻¹. These findings indicate strengthened Pt–Sn synergy and weakened Pt–Pt correlations at elevated Sn concentrations.¹⁸ EXAFS fitting results (Fig. S6–9 and Table S3†) show that the Pt–Pt coordination numbers decrease from 6.6 to 2.3 with increasing Sn content, correlating with enhanced carbon resistance. However, these ensemble averages mask structural nonuniformity,^20,21 as evidenced by a 2.2 Å scattering feature indicating elemental segregation.³⁶ Precise atomic-scale characterization of Pt coordination environments, crucial for understanding the superior catalytic performance of Pt₄₂Sn₅₈, remains challenging due to inherent disorder, necessitating complementary techniques beyond EXAFS.

Fig. 3 (a) Wavelet transform of Pt L₃-edge EXAFS for Pt₈₀Sn₂₀, Pt₅₃Sn₄₇, Pt₄₂Sn₅₈, and Pt₃₃Sn₆₇ nanocatalysts in the R-space range of 1.7 to 4.3 Å. (b) RMC fitting of the PDF data for Pt₈₀Sn₂₀, Pt₅₃Sn₄₇, Pt₄₂Sn₅₈, and Pt₃₃Sn₆₇ nanocatalysts and 3D elemental distribution of bimetal PtSn nanocatalysts from the RMC simulation of atomic pair distribution functions; blue balls represent Pt atoms, and the red balls represent Sn atoms; the illustration is a magnification of the PDF in the range of 10–15 Å. (c) Surface Pt–Pt coordination number of Pt₈₀Sn₂₀, Pt₅₃Sn₄₇, Pt₄₂Sn₅₈, and Pt₃₃Sn₆₇ nanocatalysts.

Through the Fourier transform of X-ray total scattering data, the atomic pair distribution function of the sample in real space can be obtained; the peak positions and peak shapes correspond to different atomic pair distances and coordination numbers,^37,38 and the varying X-ray scattering capabilities of different elements can help to distinguish the occupancy and segregation of Pt and Sn elements.^39,40 In the illustration of Fig. 3b, the different features observed in the high-r region of the PDF indicate significant variations in atomic pair correlations at longer interatomic distances, which clearly reflect the structural differences among the samples. The PDF data of Pt₈₀Sn₂₀, Pt₅₃Sn₄₇, Pt₄₂Sn₅₈, Pt₃₃Sn₆₇ was fitted in a small box by using PDFgui (Fig. S10†); the fitting results demonstrate that Pt₈₀Sn₂₀ and Pt₃₃Sn₆₇ can be adequately modeled using a single-phase structure, while Pt₅₃Sn₄₇ and Pt₄₂Sn₅₈ require a dual-phase model incorporating both Pt₃Sn and PtSn phases for optimal fitting. Meanwhile, the percentage of the two phases in the Pt₅₃Sn₄₇ and Pt₄₂Sn₅₈ samples can be obtained; the PtSn phase in Pt₅₃Sn₄₇ is 29% and 51% in Pt₄₂Sn₅₈. These values are close to the phase ratios of 37% and 52%, obtained from XRD data analysis by using the RIR method (Fig. S14 and Table S5†); the discrepancy between the two methods was within 10%. The three-dimensional atomic distribution profiles of the Pt₈₀Sn₂₀, Pt₅₃Sn₄₇, Pt₄₂Sn₅₈, and Pt₃₃Sn₆₇ catalysts were determined through Reverse Monte Carlo (RMC) analysis of the Pair Distribution Function (PDF) data within a large-box model framework (Fig. 3b). The resulting three-dimensional atomic configurations are graphically represented in the corresponding illustrations of Fig. 3b. Quantitative surface analysis demonstrates an inverse correlation between Sn content and Pt surface exposure, and it is supported by the attenuated CO-FTIR adsorption intensity.²⁵ While the surface Pt concentration exhibits a progressive decrease with increasing Sn content (Fig. S11†), the Pt species maintain preferential surface segregation. This surface distribution behavior is further corroborated by EDS elemental mapping of the Pt₃₃Sn₆₇ sample (Fig. S12†), which shows excellent consistency with the three-dimensional atomic distribution profiles.

To establish a more precise correlation between the catalyst's structural properties and its catalytic performance, the coordination environment of Pt species throughout the nanoparticle ensemble was extracted, as summarized in Table S2.† Furthermore, the local coordination environment of surface Pt sites was quantitatively determined based on the three-dimensional atomic distribution profiles of the PtSn catalysts. Fig. 3c depicts the evolution of nearest-neighbor Pt–Pt coordination numbers on the surfaces of Pt₈₀Sn₂₀, Pt₅₃Sn₄₇, Pt₄₂Sn₅₈, and Pt₃₃Sn₆₇ catalysts, where the color gradient from red to blue represents a systematic decrease in the coordination number. This reveals a clear inverse correlation between Sn content and surface Pt–Pt coordination, demonstrating that increasing Sn incorporation progressively reduces the Pt–Pt coordination number. The statistical distribution of surface coordination numbers is systematically illustrated in Fig. 4a. Quantitative analysis of the coordination geometry reveals a substantial reduction in Pt–Pt coordination numbers across the Pt₈₀Sn₂₀, Pt₅₃Sn₄₇, Pt₄₂Sn₅₈, and Pt₃₃Sn₆₇ catalyst series, demonstrating a distinct transition from an initial distribution predominantly centered around 6 to a final distribution with a characteristic peak near 2. Notably, the coordination numbers of Pt₄₂Sn₅₈ catalysts predominantly cluster around 3. This progressive decrease in coordination numbers exhibits a strong positive correlation with enhanced catalytic performance metrics, particularly reflected in improved propylene selectivity and enhanced resistance to deactivation. Furthermore, complementary projected density of states (PDOS) analysis for surface Pt atoms with varying coordination environments (Fig. 4b) provides fundamental insights into the geometric effects on electronic structure. The computational results demonstrate that the reduction in the coordination number induces a systematic shift of the Pt conduction band to lower energy states relative to the Fermi level. Specifically, the d-band center undergoes a significant downshift from −1.83 eV to −2.07 eV, representing a substantial electronic structure modification. This electronic reorganization preferentially promotes elevated occupancy of antibonding states, which effectively reduces the adsorption strength of propylene, thereby facilitating more efficient product desorption. The electronic structure, influenced by coordination structure effects, synergistically contribute, to the enhanced propylene selectivity and superior anti-deactivation characteristics observed in the PtSn catalyst system.^11,41

Fig. 4 (a) Surface Pt–Pt coordination number of Pt₈₀Sn₂₀, Pt₅₃Sn₄₇, Pt₄₂Sn₅₈, and Pt₃₃Sn₆₇ samples. (b) PDOS projected onto the d-bands of surface Pt atoms with different coordination environments. (c) Schematic illustration of the effect of surface coordination structure changes on the anti-deactivation properties of PtSn catalysts.

However, the reduction in the Pt–Pt coordination number, indicative of increased Sn incorporation, leads to surface coverage of Pt atoms and consequent activity attenuation. Consequently, an optimal surface configuration exists that achieves a balanced optimization of catalytic activity, selectivity, and deactivation resistance. Based on systematic performance characterization of the catalyst series, we have established the following structure–performance relationships, as illustrated in Fig. 4c. While increasing Sn content effectively suppresses the deactivation rate when the surface Pt–Pt coordination number is high, this stabilization effect reaches saturation as the coordination number approaches a critical threshold of approximately 3. Beyond this optimal value, additional Sn incorporation not only fails to provide substantial improvements in anti-deactivation characteristics but also induces excessive Pt surface coverage, resulting in significant activity loss. These findings underscore the critical importance of precisely controlling the Sn/Pt ratio and optimizing synthesis parameters to maintain the surface Pt–Pt coordination number within the optimal range of 3 which is essential for developing high-performance PtSn catalysts with well-balanced activity–stability characteristics.

Conclusion

In conclusion, we have successfully synthesized a series of PtSn catalysts with distinct surface structures through precise modulation of Sn content. Building upon average structural characterization, the surface structures of these catalysts were effectively extracted by combining Pair Distribution Function (PDF) analysis and Reverse Monte Carlo (RMC) simulations. Through comprehensive correlation with catalytic performance evaluation, we have established that while increasing Sn content effectively suppresses the deactivation rate in catalysts with high Pt–Pt coordination numbers, this stabilization effect reaches saturation when the coordination number approaches a critical threshold of approximately 3. Beyond this optimal value, additional Sn incorporation not only fails to provide substantial improvements in anti-deactivation characteristics but also induces excessive Pt surface coverage, resulting in significant activity deterioration. These findings have enabled us to identify the optimal surface configuration, which is crucial for the development of high-performance PtSn catalysts with well-balanced activity–stability characteristics.

Data availability

The authors declare that the data supporting the findings of this study are available within the paper and its ESI files.† Should any raw data files be needed in another format they are available from the corresponding author upon reasonable request.

Author contributions

X. X. and Q. L. guided the experimental design and lead the study process. M. L. performed the majority of the experiments as well as data analysis. F. X. help with the catalytic testing. L. F. provided the necessary discussion and analysis for PDF data and J. Z. provided the discussion and analysis for XAFS data. X. C. contributed to the DFT calculations. J. D., Z. L., P. Z., Y. Z., Q. L. and K. L. participated in the carful discussion of local structure of nanocatalysts. The corresponding authors of this manuscript are X. X. and Q. L. All authors discussed the results and commented on the manuscript.

Conflicts of interest

There are no conflicts to declare.

Acknowledgements

This research was supported by the National Key R&D Program of China (2020YFA0406202) and the National Natural Science Foundation of China (22090042 and 22175018). We thank the team at the 3W1 Beamline of the Beijing Synchrotron Radiation Facility (https://cstr.cn/31109.02.BSRF.3W1) for providing technical support and assistance in total scattering data collection. And we thank the team at the Shanghai Synchrotron Radiation Facility of BL13SSW (https://cstr.cn/31124.02.SSRF.BL13SSW) for assistance with XAFS measurements.

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Footnote

† Electronic supplementary information (ESI) available. See DOI: https://doi.org/10.1039/d5sc01513h

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