In situ synchrotron X-ray scattering reveals organic-mediated scaling mechanisms on desalination membranes

Domain: biology
Published: 2026-03-10
Editorial outcome: major_revision

Abstract
Inorganic scaling, governed by complex organic–inorganic interactions, presents a pervasive challenge in aqueous environments with broad implications for engineering systems. Using reverse-osmosis (RO) desalination as a model platform, we investigate how mixed organic foulants influence inorganic gypsum scaling at membrane–water interfaces. Representative proteins, humic substances, and polysaccharides are employed as model foulants to reveal their roles in modulating gypsum crystallization behavior. By integrating advanced in situ, time-resolved synchrotron X-ray scattering within the concentration polarization layer—a region typically inaccessible to conventional characterization techniques—with modelling, spectroscopic, and imaging analyses, we track the evolution of gypsum scaling from nanoscale precursors to mature crystals. Our findings reveal that different classes of organic foulants regulate gypsum crystallization through distinct mechanisms, ranging from inhibiting precursor aggregation in the bulk solution to altering interfacial physicochemical properties that govern the kinetics of heterogeneous nucleation and growth. These findings provide molecular-level insights into the coupled dynamics of organic fouling and inorganic scaling, advancing mechanistic understanding of crystallization at functional interfaces. Such insights offer guidance for the rational design of anti-scaling strategies in engineering systems.

Introduction
Inorganic scaling, i.e., the crystallization of sparingly soluble salts, is a widespread phenomenon observed across both natural and engineered systems1. During crystallization, a disordered phase in a supersaturated solution transforms into a highly ordered, periodic lattice. This process proceeds through two fundamental stages: nucleation and subsequent crystal growth. Nucleation constitutes the critical, rate-determining step of this first-order phase transition, wherein the smallest thermodynamically stable nuclei of the new crystalline phase emerge. In the natural systems, scaling regulates long-term carbon and sulfur cycles through geochemical processes such as marine carbonate precipitation2 and the formation of travertine terraces at geothermal springs3, thereby shaping mineral landscape of the Earth. In the engineered systems, such as membrane-based desalination4-6, electrochemical reactors7, and energy storage devices8,9, scaling poses significant challenges to operating efficiency as the presence of scaling layers substantially inhibit mass or heat transfers10,11. Even a minimal scale accumulation—on the order of few millimeters—can elevate energy demands for operation, leading to considerable economic and environmental costs12,13. For instance, in reverse osmosis (RO) seawater desalination processes, managing inorganic scaling through antiscalant dosing, periodic cleaning, and module replacements can account for over 25% of operating costs12. Such fact thus necessitates effective scaling control strategies for the engineering systems.

Precise design of scaling control strategies relies on the mechanistic insights into interfacial scaling pathways13. Despite the pervasive occurrence of scaling, the fundamental physicochemical mechanisms governing scale nucleation, phase selection, and crystal growth at solid-liquid interfaces remain inadequately understood—particularly realistic water chemistries containing complex organic substances16,17. As a consequence, conventional scaling control strategies in engineering systems are largely based on trial-and-error approaches14-17, highlighting the urgent need for mechanistic understanding to enable rational design of effective anti-scaling strategies.

Scaling typically proceeds via two distinct mechanisms: homogeneous nucleation and crystal growth in bulk solution, and heterogeneous nucleation and crystal adhesion to surfaces17,22. These pathways are dynamically coupled at the nano- to microscale regimes for the formed nucleates and crystals. Both experimental and theoretical studies suggest that crystallization can proceed through different dominant nucleation pathways, including classical descriptions based on direct ion-by-ion assembly into a crystalline nucleus18 and non-classical, precursor-mediated scenarios, characterized by the formation of pre-nucleation clusters19, amorphous precursor assembly20, and subsequent structural rearrangement21. Distinguishing the dominant nucleation pathway under specific conditions is critical for revealing scaling behaviors and developing control strategies. For example, in systems where ion-by-ion attachment plays a primary role, inhibitors function primarily by reducing supersaturation or chelating free ions to suppress nucleation22, while in systems governed by precursor-mediated nucleation, inhibitors could elevate interfacial energy barriers to prevent lattice matching and subsequent crystal growth on surfaces23. The challenge is further compounded by the complex water matrices, which do not contain inorganic salts alone24. The inevitable presence of natural organic matter25, extracellular polymers26, and biomineralization agents27 creates mixed fouling environments, where organic–inorganic interactions modulate interfacial energy barriers, shield nucleation sites, or promote alternative crystallization pathways28. These interactions can lead to distinct morphologies and deposition dynamics compared to pure inorganic scaling. Therefore, developing cross-scale, in situ characterization methods29, together with advancing in multiphysics simulations30, is essential to delineate the dominant scaling pathways, as well as their synergistic or antagonistic effects under mixed fouling conditions.

Traditional analytical methods for studying scaling—such as flux decay measurements, ex situ imaging or spectroscopic techniques—are inherently limited in their ability in capturing dynamic processes. These approaches typically provide only static snapshots or time-averaged data. Such limited spatiotemporal resolution prevents in situ characterization of nucleation pathways and aggregation dynamics during the early stages of scaling. Moreover, most of these approaches involve destructive procedures in sample preparation, such as vacuum drying or metal coating, which likely disrupt the native structure of scaling layers and complicate the direct observation of interactions among organic foulants and inorganic phases.

In contrast, synchrotron radiation-based techniques offer distinct advantages for investigating scaling dynamics in complex aqueous systems31,32. Specifically, small-angle and wide-angle X-ray scattering (SAXS/WAXS) utilize high brightness and precise monochromaticity to enable real-time observations of homogeneous crystallization processes in supersaturated solutions33,34. By simultaneously acquiring SAXS and WAXS data from the same sample, these scattering techniques provide reciprocal-space coverage from nanometer to sub-micrometer scales35,36, allowing for quantitative analysis of structural transitions—from amorphous pre-nucleation states detected by SAXS to crystalline phases characterized by distinct Bragg peaks in WASX37,38. This approach yields continuous, multiscale analysis of complex fouling processes, bridging molecular to mesoscopic scales and offering insights into interfacial crystallization dynamics under realistic conditions. Besides these scattering techniques, synchrotron radiation could also be coupled with Fourier-transform infrared (FTIR) mapping to resolve spatial distribution of foulant molecules (i.e., characteristic functional groups) on material surfaces with micrometer-scale resolution39-42. The combination of these synchrotron radiation-based techniques (SAXS, WAXS, and FITR mapping) can provide a comprehensive, chemically specific view of scaling formation and transformation at material interfaces, enabling a closer look of both structural and compositional dynamics during the scaling processes.

In this study, we integrated advanced synchrotron radiation techniques with interfacial energy analysis to unravel the complex dynamics of hybrid organic–inorganic scaling. Using gypsum as a model inorganic scalant and three representative organic foulants—bovine serum albumin (BSA), humic acid (HA), and sodium alginate (SA)—we explored both homogeneous crystallization within the concentration polarization (CP) layer and heterogeneous nucleation on the membrane surface. Our characterization approach combines time-resolved small- and wide-angle X-ray scattering to capture, in real time, the transformation from precursor species to crystalline phases. In addition to X-ray scattering, our approach was further complemented by quartz crystal microbalance with dissipation monitoring (QCM-D) and extended DLVO (XDLVO) theory to quantify interfacial interactions. By synchronizing multiscale structural characterization with interfacial energy landscape analysis, we identified how organic–inorganic interactions regulate scaling behavior—ranging from delayed nucleation to altered crystal growth directions and morphologies. Notably, we revealed that gypsum crystallization under RO conditions proceed via a non-classical precursor-mediated nucleation pathway, characterized by metastable precursor clusters prior to the emergence of long-range crystalline order. This observation contrasts with the direct ion-by-ion assembly typically described within classical nucleation frameworks. We further demonstrate that organic co-foulants modulate the early-stage nucleation behavior by acting as molecular “switches” that redirect the dominant crystallization pathway under RO conditions. Our findings offer a mechanistic foundation for predicting and controlling mixed fouling in membrane systems, representing a significant step toward the rational design of antifouling strategies in water treatment, energy conversion, and other interface-dependent technologies.

Results
Impact of organic foulants on gypsum scaling.
To investigate the influence of organic foulants on gypsum scaling, we conducted membrane scaling experiments using a lab-scale reverse osmosis (RO) system. The feed solutions consisted of 30 mM calcium chloride (CaCl ) and 30 mM sodium sulfate (Na SO ), resulting in a supersaturation ratio (SR) of 1.71, corresponding to a supersaturation index (SI) of 0.234. Under these bulk conditions, the theoretical induction time for gypsum scaling, when estimated using an idealized classical nucleation model neglecting wall effects and impurities, suggests a relatively long duration. Despite the potential for bulk nucleation under specific conditions43-45, no visible crystals or turbidity were observed in the feed tank during the 24-hour experiment. This observation confirms that spontaneous crystallization did not occur in the bulk phase under the experimental conditions employed in this study. However, due to the presence of concentration polarization at the membrane surface, the gypsum SR rose to 10.05 (SI =1.002) (Supplementary Note 2), significantly reducing the induction time to ~4 minutes46,47. This finding indicates that gypsum scaling occurs exclusively within the concentration polarization layer, rather than from spontaneous crystallization in the bulk solution. For comparison, we also examined flux decline in the presence of organic foulant alone, allowing for a direct evaluation of individual foulants to membrane fouling.

Figure 1 illustrates the membrane flux decline caused by gypsum scaling alone and gypsum-organic mixed fouling in the presence of different organic foulants. Pure gypsum fouling (grey triangles) led to complete flux loss within 4.04 ± 0.06 hours. In contrast, mixed fouling with gypsum and bovine serum albumin (BSA, dark blue squares in Figure 1a) exhibited a significantly slower flux decline, with a reduction of 46.18% ± 0.54% after 6 hours, indicating that BSA effectively inhibits gypsum scaling. Mixed fouling with gypsum and humic acid (HA, dark orange squares in Figure 1b) caused a flux decline of 92.27% ± 0.25% after 6 hours, suggesting that HA moderates the severity of flux loss compared to pure gypsum scaling. For sodium alginate (SA) and gypsum mixed fouling (dark red squares in Figure 1c), the initial flux decline mirrored the trend observed for pure gypsum; however, the rate slowed as flux decreased, ultimately leading to in complete flux loss after 9.00 ± 0.12 hours. These findings indicate that SA also mitigates gypsum scaling during operation. Overall, the flux declines in the mixed fouling systems were less severe than the cumulative effect of pure gypsum (grey triangles) and individual organic foulants (light circles), demonstrating that organic foulants reduce gypsum scaling and alleviate the severity of mixed fouling.

Corresponding SEM images of the fouled membranes (Figure 1d and Supplementary Figure 1) revealed distinct gypsum crystal morphologies influenced by the type of organic foulants. Pure gypsum fouling produced elongated, needle-shaped crystals that were loosely deposited on the membrane surface. In the BSA mixed fouling system, the crystals appeared as short, thick blocks with smooth sides and stepped tops, with minor amounts of protein observed on the crystal surfaces. In the HA mixed fouling system, the crystals formed rosette-like structures with incomplete growth on individual petals and exhibited stepped growth on the side surfaces, resulting in a stacked-flake structure. Additionally, some HA clusters were observed between the crystals. In the SA group, the crystals were encased in alginate gel, forming rosette shapes with longer, thicker prisms, alongside small needle-like and shield-shaped twinned crystals. These observations suggest that while gypsum crystallization remains the primary mechanism of membrane blockage, the presence of organic foulants significantly alters the morphology of gypsum crystals, thereby affecting their nucleation, formation, and growth.

Notably, higher-magnification SEM images (Figure 1e) revealed distinct growth behaviors of gypsum crystals under different conditions. In the case of pure gypsum, the crystals formed well-defined, needle-like crystals with the largest surface area on the (020) side face, while the top face (011) and the other side face (120) were relatively smaller due to the crystal’s elongated shape. With the presence of BSA, the crystals became shorter and thicker, exhibiting more balanced proportions of side faces (020) and (120), with steps emerging along the (–102) plane on the top face. In the HA group, the crystals showed incomplete growth on the side faces, alternating (120) and (111) planes, which significantly reduced the area of the (020) face. In the SA group, shield-shaped twinned crystals, commonly referred to as “Montmartre twins,” were observed, with twinning planes aligned along the (–101) plane 48,49. 

In situ monitoring of inorganic foulant crystallization processes within the concentration polarization layer.
Rejection of ions in membrane desalination results in the formation of concentration polarization (CP) (Figure 2a). Under the operating conditions used in this study, CP caused calcium sulfate to accumulate on the membrane surface at concentrations 3.9 times higher than those in the bulk solution, corresponding to a gypsum SR of 10.05 (SI =1.002) (Figure 2b). Detailed calculation parameters, including diffusion coefficients and calculated surface concentrations, are provided in Supplementary Table 1. According to the empirical relationship between induction time and supersaturation, such elevated supersaturation levels promotes homogeneous nucleation, initiating gypsum crystallization47,50,51. The process of inorganic scaling is time-dependent and involves a series of complex, overlapping microscopic events that occur after the onset of supersaturation, including nucleation, crystal growth, and aggregation. The induction time is defined as the macroscopic time interval between the achievement of supersaturation and the first detectable appearance of the solid phase, thus encompassing these initial, often inseparable, microscopic processes52,53. Consequently, real-time monitoring of the CP layer is crucial to understanding the progression of inorganic scaling, especially under the mixed fouling conditions. While conventional techniques such as conductivity and turbidity measurements demonstrate that organic foulants delayed the onset of gypsum crystallization and reduced crystal volume (Supplementary Note 3, Supplementary Figure 5), the low sensitivity of these methods limited further elucidation of crystallization mechanisms.

To gain a deeper understanding of the nucleation and growth dynamics, we employed a time-resolved, synchrotron-based in situ X-ray scattering technique to investigate the transformation of nanoscale precursors into macroscopic gypsum crystals (Figure 2c). Notably, these in situ SAXS/WAXS measurements were designed to probe the crystallization kinetics within the fluid phase of the CP layer and were performed in a membrane-free configuration. Solutions were prepared to replicate the ion concentration in the CP layer adjacent to the membrane surface, and a peristaltic pump circulated the reaction mixture through a quartz capillary rather than a membrane module. The crystallization was initiated by injecting calcium chloride (CaCl ) using a remotely controlled syringe pump (Figure 2c ), ensuring uniform mixing with sodium sulfate (NaSO ). During the measurement, X-ray was propagated through the sample in the quartz tube, and scattering signals were collected by WAXS and SAXS detectors positioned at designated distances (Figure 2c ). Time-resolved scattering data were collected at intervals of five seconds, capturing the entire sequence of homogeneous crystallization. SAXS images revealed a gradual expansion of the central scattering patterns, while WAXS images displayed emerging diffraction patterns, reflecting the progression from nucleation to crystal growth (Figure 2c ). This high spatiotemporal resolution approach enables a closer-look of the crystallization dynamics, enabling the tracking of nanoscale precursor development into gypsum crystals until no further changes were observed in the scattering signals.

Supplementary Figure 8 illustrates the raw 2D isotropic SAXS patterns acquired by the detector, which were subsequently integrated into 1D profiles and processed to present the data as time-resolved in situ SAXS patterns. The time-resolved SAXS waterfall plots and heatmaps for the four sample groups are displayed in Supplementary Figure 9 and Figure 3a, respectively. The concentration of 85 AmM CaSO used in Figure 3 represents a characteristic mid-region concentration within the CP layer, lying between the bulk concentration (~30 mM) and the membrane-surface concentration shown in Fig 2b. Data collection began with the injection of calcium chloride and continued until the scattering intensity stabilized over 40 minutes. The stages of scatterer evolution are delineated by dashed lines.

As shown in Figure 3a, throughout the entire crystallization induction period, the scattering intensity in the presence of organic foulants remained consistently lower than that of the pure CaSO group. This finding indicates that the organic foulants reduced the effective supersaturation, thereby decreasing both the nucleation density and the number of primary clusters. For the three organic foulants, the signal changes exhibited four distinct SAXS phases, reflecting the continuous evolution of nanoscale scatterers prior to and during crystallization: an initial increase in intensity, a slight decrease followed by stabilization, a significant intensity increase, and final stabilization at a maximum intensity with a slight decline. In the CaSO -BSA group (Figure 3a ), Phase 1 (below the blue dashed line) showed an intensity increase within the first 160 seconds. In the HA (Figure 3a ) and SA (Figure 3a ) groups, the initial intensity increase lasted for 40 and 95 seconds, respectively (as indicated by the blue dashed line). The durations of Phase 2—defined as the region between the blue and yellow dashed lines—for BSA, HA, and SA were 590, 340, and 90 seconds, respectively. In contrast, no clear distinction between the first two stages was observed in the pure CaSO group (Figure 3a ). This group exhibited an extremely short induction period, followed by a rapid intensity increase across all q values from the beginning of the experiment, making it challenging to differentiate the initial stages. The durations of Phase 3, defined as the region between the yellow and red dashed lines, for the pure CaSO , BSA, HA, and SA groups were 300, 1615, 345, and 800 seconds, respectively.

Nanoscale particles or regions exhibiting electron density with the surrounding solution (i.e., scatterers) were identified through their contribution to SAXS signal intensity. The dynamic evolution of scatterers during the crystallization process can be illustrated by taking pure CaSO as an example. As illustrated in Figure 3b, in Phase 1, the increase in scattering intensity indicates the formation of scatterers with electron densities distinct from the background solution. In Phase 2, interactions among primary species led to the formation of small clusters and the development of the system’s structure factor, resulting in a slight decrease in scattering intensity. Despite these interactions, the local concentration remained relatively low, and the scatterers were still sparsely distributed. In Phase 3, scattering intensity increased significantly by several orders of magnitude, reflecting a transition from an initially dispersed arrangement to a denser and more compact structure, implying the growth of clusters. Following this stage, the stacking and merging of clusters reduced the overall surface area, leading to a slight decline in scattering intensity, as depicted in Figure 3c. Taken together, these stages represent the dynamic evolution of scatterers, from initial formation and sparse interactions to cluster densification and eventual structural consolidation.

Figure 3d illustrates the evolution of the power-law dependence between scattering intensity (I) and vector (q). In Phase 1, the scattering intensity shows an overall increase, indicating the formation of initial scatterers. In Phase 2, the intensity follows the relationship I(q) ∝ q–1, suggesting that the primary scatterers formed in the solution were larger than typical ion pairs54,55. During this stage, a slight decrease in intensity at q > 0.78 nm–1 suggests the aggregation of primary scatterers into larger structures56. In Phase 3, I(q) follows a power-law dependence on q, with an exponent ranging from –3 to –4, reflecting the surface fractal dimension (Dₛ) of the scatterers, where I(q) ∝ q(–6+Dₛ). A Dₛ value of 2 indicates smooth surfaces, while a value approaching 3 indicates rough, fractal-like surfaces53,54. As such, the increase in Dₛ suggests that the scatterers develop more irregular and complex surfaces, implying ongoing rearrangement and structural evolution within the system. These observations highlight the dynamic transitions in scatterer structure and surface properties throughout the crystallization process.

All organic foulants significantly prolonged the formation and evolution of primary scatterers during the initial SAXS Phases 1 and 2, corresponding to the crystallization induction period observed by WAXS. In Phase 3, BSA strongly delayed the formation of larger nuclei, thus effectively inhibiting the aggregation and growth of clusters (Figure 3a ). Although HA and SA displayed similar overall trends, their effects differed across specific stages. In the HA group, Phases 1 and 3 were relatively short, with the prolongation primarily occurring in Phase 2 (Figure 3a ). This behavior is likely due to the weaker ionic binding capacities of HA molecules, which prevented significant suppression of supersaturation. However, as well-dispersed, charged small molecules, HA effectively blocked interactions between primary CaSO scatterers, maintaining them in a dispersed state. In contrast, SA formed an irregular gel structure that acted as nucleation sites. While SA failed to suppress scatterer formation in Phase 2, it delayed cluster growth in Phase 3, effectively extending this phase (Figure 3a ). At the end of the reaction, the gyration radius of nuclei in the pure CaSO , HA, and SA groups was ~4 nm, whereas in the BSA group, it was about 2 nm (Figure 3e). Such size difference indicates that BSA most significantly inhibited the growth and aggregation of clusters in the CP-layer solution, while HA and SA exert weaker control over bulk cluster growth.

Supplementary Figure 11 illustrates the integration and processing of the WAXS patterns, showing the procedures in transforming the patterns into time-resolved waterfall plots and heatmaps. The 3D waterfall plots for the four groups are presented in Supplementary Figure 12, providing a clear visualization of the temporal evolution of diffraction signals during the scaling process. As shown in Figure 4a, characteristic peaks of gypsum appeared sequentially across all simulated concentration polarization layer solutions and intensified over time. By correlating the X-ray wavelength (λ), and diffraction angle (2θ), with q using the Bragg’s law (q = 4πλ/sinθ), the WAXS data largely aligned with the powder XRD spectrum of gypsum (Supplementary Figure 13), verifying the formation the crystalline gypsum in our system.

During the initial formation and aggregation of primary scatterers, pronounced changes were observed in the SAXS signals across all samples, whereas no WAXS diffraction peaks were detected, indicating the formation of non-crystalline nanoscale precursors. This discrepancy indicates that the system initially contained non-crystalline, nanoscale CaSO₄ precursors detectable by SAXS but invisible to WAXS. The aggregation and evolution of these amorphous precursors correspond to the WAXS induction period for gypsum crystallization. The induction time varied among the different organic foulants (Figure 4b). In pure gypsum (without organic foulants), it was less than 100 seconds. In comparison, HA and SA extended the induction time to 550 and 400 seconds, respectively, while BSA caused the longest delay, up to 1,000 seconds. Taking the (020) peak area as an indicator of gypsum crystallinity (Figure 4c), the result showed that all three foulants significantly reduced the crystallization rate of gypsum, leading to different degrees of gypsum crystallinity, in the order of: pure gypsum > SA > HA > BSA. To further explore the time evolution of crystal structure, three distinct stages were identified in the WAXS spectrum (Figure 4d). Stage I exhibited no detectable diffraction peaks, corresponding to the induction period during which amorphous precursors formed and evolved, as captured by SAXS Phases 1–2. Stage II was characterized by a rapid emergence and growth of characteristic gypsum diffraction peaks, coinciding with SAXS Phase 3, indicating the structural transformation of amorphous clusters into crystalline gypsum. Stage III represented the crystal growth phase, where the solution’s supersaturation decreased, no new nuclei formed, and the signal intensity increased at a slower rate. Towards the end of the process, a slight decline in diffraction intensity was observed across all groups, likely due to the settling of millimeter-sized crystals at the bottom of the beaker. This settling reduced the number of crystals passing through the quartz tube, thereby lowering the detected signal intensity.

A notable observation was made in the SA group: the first crystallization stage was prolonged (Figure 4b), yet its crystallinity was the highest among the mixed fouling groups (Figure 4c). These results suggest that while SA delays nucleation, it does not suppress subsequent crystal growth. Instead, the strong complexation of SA with Ca2+ led to the formation of a gel layer, thereby resisting their interaction with SO 2– ions. This process lowers the local supersaturation and effectively increases crystal solubility. As a result, nucleation occurs more slowly in the SA group compared to pure gypsum, without significantly altering the subsequent crystal growth dynamics. Such delay, combined with a gel-mediated growth environment, enables continued crystal development, ultimately leading to a higher degree of crystallinity during the later stages of crystallization despite the initial delay. In comparison, BSA and HA both led to delays across all crystallization stages and resulted in a reduction in the degree of crystallinity, likely due to their adsorption onto active sites on crystal surfaces. This adsorption interferes with crystal face growth by blocking key sites for ion attachment, altering the surface energy and leading to irregular crystal morphologies. Additionally, the steric hindrance provided by BSA disrupts crystal stacking and restructuring, further limiting crystallinity.

At the end of the reaction, the crystallite size and the (020)/(021) face ratio are shown in Figure 4e. The crystallite size, i.e., the spatial length perpendicular to the (020) plane (Figure 4e ), remained relatively consistent across both the pure gypsum group and the organic fouling mixed groups (Figure 4f), ranging from 73.44 to 76.73 nm. The (020) plane corresponds to the side facet of gypsum crystals, while the (021) plane corresponds to the top facet (Figure 4e ). The ratio of diffraction intensity between these planes serves as an indicator of the growth direction and overall morphology of the gypsum crystals57. In the WAXS signals obtained from the four supersaturated solutions, the (020)/(021) facet ratio remained largely unchanged and eventually stabilized at approximately 0.75 (Figure 4f). This consistent ratio suggests that the differences in crystal morphology observed on the membrane surface arose primarily during the subsequent crystal growth stages, rather than during the initial formation of crystallites in the nucleation phase.

Effects of organic foulants on the surface-mediated gypsum crystallization.
Organic fouling precedes gypsum scaling, altering membrane surface properties (Supplementary Figures 16 and 17), modifying nucleation energy barriers, and influencing crystal growth morphology. It should be noted that the gypsum scaling process under the conditions of Figure 5 involves a superposition of homogeneous nucleation within the concentration polarization (CP) layer and surface-mediated heterogeneous nucleation and adhesion on the membrane. To isolate and highlight the role of surface-mediated interactions, surface conditioning experiments were conducted under otherwise identical feed composition and hydrodynamic conditions. In brief, the membranes were first pre-treated with solutions containing specific organic foulant, rinsed to form a thin and tightly bound organic layer, and then subjected to pure CaSO fouling. The conditioned membrane exhibited a less severe flux decline compared to the fresh membrane when exposed to gypsum scaling (Figure 5a), with HA exhibiting the strongest inhibition (flux decline after 6 h: 15.50% for HA, 55.03% for BSA, and 91.16% for SA). Although homogeneous nucleation in the CP layer is expected to occur simultaneously due to the high supersaturation, the identical feed solution composition and hydrodynamic conditions across all conditioning groups render its contribution a constant baseline. Therefore, the observed differences in flux decline primarily reflect variations in surface-mediated processes, including crystal adhesion and heterogeneous nucleation barriers induced by the different organic conditioning layers. The apparent reversal in inhibition efficiency between Fig. 1a and Fig. 5a reflects a shift in the rate-limiting step from bulk precursor formation to surface attachment, rather than a contradiction in inhibitor functionality. QCM-D analysis revealed distinct adsorption behaviors and nucleation suppression effects (Figure 5b). Both BSA and HA formed rigid interfacial layers (ΔD/Δf ≤ 0.18 × 10–6 Hz–1, Figure 5c). BSA primarily suppressed nucleation through steric hindrance, experiencing minimal structural disturbance upon CaSO exposure. HA demonstrated the strongest nucleation inhibition (Δf = –14.20 Hz, compared to –68.90 Hz for pure gypsum), with weakened interfacial rigidity, likely due to calcium ion chelation causing the HA layer to loosen around calcium, thereby disrupting nucleation and reducing gypsum adhesion. In contrast, SA formed a gel-like layer that underwent a pronounced structural reorganization upon Ca2+ exposure. This transition was evidenced by a shift in ΔD/Δf from 2.35 × 10–6 to 0.89 × 10–6 Hz–1, indicating a transformation from a highly hydrated, soft polymer layer to a more compact and mechanically rigid network. Such behavior is characteristic of calcium-induced ionic cross-linking within alginate chains, consistent with the formation of a hydrogel-type structure rather than a rigid steric barrier.

The adhesion propensity of gypsum was quantified through a comprehensive interfacial energy analysis, integrating surface energy measurements (contact angle, zeta potential; Supplementary Figure 18) with XDLVO theory calculations. As shown in Figure 5d, the distance-dependent interaction energy profiles highlight three key governing factors: electrostatic (EL) contributions remain negligible due to gypsum’s inherently low surface charge, long-range (LW) interactions are consistently attractive across all membrane types, and polar Lewis acid-base (AB) interactions play a dominant role in determining adhesion behavior. BSA conditioning induces a dual effect—while it enhances polar adsorption by shifting AB interactions negatively (∆𝐺AB = –10.24 mJ m–2), it simultaneously reduces LW attraction by 21.5% compared to pristine membranes. In contrast, HA and SA treatments preserve LW interactions but reverse AB polarity through selective modulation of electron donor/acceptor properties, establishing repulsive AB forces (∆𝐺AB: +52.20 mJ m–2 for HA and +34.53 mJ m–2 for SA). These contrasting interfacial interactions result in distinct adhesion thresholds: on BSA-conditioned and pristine membranes, the total energy profile remains negative, facilitating spontaneous gypsum attachment, whereas HA- and SA-conditioned surfaces impose substantial energy barriers of 85.80 and 47.69 kT, respectively, requiring nascent crystals to overcome repulsive forces for surface adhesion. This hierarchical interfacial resistance (HA > SA > BSA) correlates with macroscopic antifouling performance of the conditioned membranes.

A comparison of surface XRD and powder XRD (Supplementary Figure 19) of the fouled membranes confirmed that organic foulants influenced the growth direction of gypsum crystals. BSA inhibited the development of the (020) plane, while HA suppressed growth along the (021) and (041) planes. AFM characterization of crystal faces further revealed distinct differences in step distances and surface textures (Supplementary Note 7). In the presence of BSA, dislocations primarily formed on the crystal surface perpendicular to the a-axis, leading to the development of characteristic stepped structures and the formation of short, thick, blocky crystals. In contrast, HA-induced dislocations along the (020) plane resulted in prismatic crystals with scale-like surface patterns.

Spatial dynamics of organic-inorganic mixed fouling.
Synchrotron-based infrared microscopy offers a highly accurate and quantitative approach for in situ mapping the spatial distribution of foulants across the membrane surface and within the fouling layer. As schematically illustrated in Figure 6a, the fouled membranes were embedded in paraffin wax, sectioned into thin slices, and fixed onto calcium fluoride (CaF ) windows. The measurements were conducted on fouled membranes in transmission mode, enabling spatially resolved two-dimensional scans. After collecting FTIR spectrum on different location (Figure 6b), characteristic peaks of the polyamide membrane (1587 cm–1 for N–H bending and C–N stretching), gypsum (3395 cm–1 for O–H stretching), and organic foulants (1687 cm–1 for BSA amide (I) α-helix, 1012 cm–1 for HA O–H deformation, and 1048 cm–1 for SA C–O elongation) were extracted and visualized as heatmaps, revealing their spatial distribution and chemical abundance across the membrane surface and fouling layer. Detailed experimental procedures are provided in the Supplementary Information (Supplementary Note 8, Figures 21 and 22).

The spatial distribution and chemical abundance of each foulant on the same membrane sample are presented as a heat map in Figure 6c, and the absorbances of gypsum and organic foulants were plotted against distance from the membrane surface (Figure 6d and Supplementary Figure 23). In the pure gypsum scaling group (Figure 6c ), gypsum was concentrated near the membrane surface, with its intensity starting to decrease beyond 10 microns from the surface (grey squares in Figure 6d). This decrease corresponds to the effects of concentration polarization, which increases local gypsum supersaturation and promotes crystallization near the membrane. In the BSA group (Figure 6c ), BSA was detected within 3-4 microns from the membrane surface (blue circles in Figure 6d), without the presence of gypsum, suggesting that BSA adhered to the membrane first. This BSA-rich layer was overlaid by a seven-micron-thick gypsum layer with relatively low intensity. Beyond this, the gypsum layer, another 10-micron-thick BSA layer appeared, indicating that BSA inhibited further gypsum growth. In the HA group (Figure 6c ), HA was also found on the membrane surface before gypsum. But unlike in the BSA group, HA and gypsum regions overlapped. The highest gypsum abundance was observed about 10 microns away from the membrane surface (orange triangles in Figure 6d), indicating that HA strongly inhibited early-stage gypsum fouling but had a reduced impact on crystal growth in solution. For the SA group (Figure 6c ), both SA and gypsum signals were low near the membrane surface, which can be attributed to the shrinkage of a highly hydrated alginate gel caused by dehydration during sample preparation. The calcium-cross-linked alginate network (“egg-box” structure) acted as a porous hydrogel layer that temporarily retained calcium ions while altering ion transport pathways near the membrane surface, leading to low gypsum abundance in this region. At greater distances from the membrane, the spatial distributions of the gypsum and SA overlapped almost completely, indicating that crystal growth occurred within the alginate matrix rather than being excluded by it. Although the maximum gypsum intensity was the lowest in the SA group, the gypsum layer was the thickest, surpassing even the thickness in the pure gypsum group (red diamonds in Figure 6d). This result suggests that SA did not effectively suppress overall gypsum growth; instead, the extended gel network provided additional nucleation sites, promoting crystal formation throughout the thickness of the fouling layer.

Correlation analysis between the signal intensities of gypsum and organic foulant at different locations (Figure 6e) revealed that BSA had the lowest correlation with gypsum at 0.22, indicating that their distributions were largely exclusive. BSA, being a large molecule with a low density of surface functional groups, segregated gypsum precursors, preventing their aggregation and crystallization. In contrast, HA and SA showed higher correlations with gypsum, at 0.55 and 0.61, respectively. These smaller molecules, rich in carboxyl functional groups, had less steric hindrance and were able to form clusters or gels with calcium ions, leading to their co-occurrence with gypsum during fouling.

Methods
Membrane fouling experiments.
Fouling experiments were conducted in a laboratory-scale reverse osmosis (RO) system with an effective membrane area of 19.5 cm2 (65 mm × 30 mm). The system temperature was maintained at 25 ± 0.3 ℃ by an industrial chiller (BL-1FCS, Baoli, China). Feed solution contained 30 mM sodium sulfate (Na SO ) and 30 mM calcium chloride (CaCl ), leading to gypsum (CaSO ) concentration of 30 mM. In CaSO -organic mixed fouling experiments, an additional 100 mg L–1 of organic foulant, including bovine serum albumin (BSA), humic acid (HA), and sodium alginate (SA), was respectively added to the feed solution. Before each fouling experiment, a membrane coupon was compacted with deionized (DI) water at 25 bar for 8 hours, with a crossflow velocity of 30.86 cm s–¹. Following the compaction, the crossflow velocity was reduced to 9.26 cm s–¹, and the fouling experiment was initiated by sequentially adding sodium sulfate, organic foulant, and calcium chloride stock solutions. Precise hydraulic control was established using a variable frequency pump, which was continuously regulated to maintain the membrane inlet pressure at a consistent value of 25 bar. Concurrently, a constant flow control valve installed on the feed line ensured the cross-flow velocity remained fixed at 30.86 cm s–1 throughout the experiment. Under these conditions, the initial water flux achieved was 54 L m–2 h–1. Experiment was conducted over a 24-hour period to assess the impact of different feed water compositions on permeate flux. Both the permeate and concentrate streams were continuously recirculated back to the feed tank. To verify experimental reproducibility, replicate fouling experiments were conducted under identical conditions. The resulting individual flux decline curves, presented in Supplementary Figure 4, exhibit a high degree of consistency, confirming the reliability of the experimental results.

Effect of organic foulants on gypsum surface crystallization was evaluated through membrane conditioning and scaling experiments. Membranes were compacted following the same protocol as in the fouling experiments. To initiate the conditioning experiment, 60 mM sodium chloride, 100 mg L–1 organic foulants (BSA, HA, or SA), and 30 mM calcium chloride were sequentially added to the feed solution. Sodium sulfate was replaced with an equivalent ionic strength (double the concentration of sodium chloride) to prevent sodium sulfate precipitation. Crossflow velocity and initial flux were maintained as in the fouling experiments, with a conditioning duration of one hour. Then, the membrane underwent backwashing with pure water for 15 minutes to remove ions and loosely adsorbed organic matter. During backwashing, crossflow velocity was 30.86 cm s–1, and the pressure was set to 0.2 bar. Subsequently, a pure gypsum scaling experiment, without adding organic foulants, was conducted under the identical conditions and feed solution composition as in the fouling experiments.

Interaction energy calculated by XDLVO model.
According to extended Derjaguin-Landau-Verwey-Overbeek (XDLVO) theory, the total interaction energy, E , between the foulant and the membrane surface is the sum of three components: electrostatic interaction energy (E ), Lifshitz-van der Waals interaction energy (E ), and Lewis acid-base interaction energy (E ). At a separation distance h between foulant and membrane interface, the total interaction energy and each of these components can be expressed as:

E = E + E + E (1)
E (h) = − A / (12πh^2) (2)
E (h) = ΔG exp((h - h ) / λ) (3)
E (h) = (r ε ε ξ ξ / (4π)) * (2ξ ξ / (ξ + ξ ) * ln((1 + exp(-kh)) / (1 - exp(-kh))) + ln(1 - exp(-2kh))) (4)

where A = −12πh ΔG represents the Hamaker constant, h is the minimum cutoff distance due to Born repulsion; λ is the characteristic decay constant for polar interactions in aqueous solutions; εᵣ is the dielectric constant of water; ε₀ is the permittivity of free space; ξ₁ and ξ₃ denote the surface potentials of the membrane and gypsum, respectively; k is the Debye screening constant, and 1/k represents the Debye length, which is 0.104 nm at room temperature. ∆𝐺LW and ∆𝐺AB represent the LW and AB components of the Gibbs free energy between surface and foulant at contact, respectively, and are calculated as follows:

ΔG = 2(sqrt(γ ) - sqrt(γ ))(sqrt(γ ) - sqrt(γ )) (5)
ΔG = 2 [sqrt(γ+ ) (sqrt(γ- ) + sqrt(γ- ) - sqrt(γ- )) + sqrt(γ- ) (sqrt(γ+ ) + sqrt(γ+ ) - sqrt(γ+ )) - (sqrt(γ+ γ- ) + sqrt(γ- γ+ ))] (6)

where 𝛾𝐿𝑊, 𝛾+, and 𝛾−, represent the Lifshitz-van der Waals component of surface energy, and the Lewis acid and Lewis base components, with subscripts L, M, and F representing the liquid, membrane, and gypsum, respectively. The surface energy components of the virgin membrane and the membrane conditioned with organic foulants were determined using the Young-Dupré equation, based on contact angle measurements with three liquids of known surface tension properties (Supplementary Tables 2 and 3):

(1 + cosθ)γ = 2(sqrt(γ γ ) + sqrt(γ+ γ- ) + sqrt(γ- γ+ )) (7)

Quartz crystal microbalance with dissipation monitoring analysis.
Gold sensors (QSX 301 gold, Nanoscience Instruments, USA) were subjected to a two-step cleaning process. First, the sensors were exposed to UV/ozone (ProCleaner, BioForce Nanosciences, USA) for 10 minutes. Following this, the sensors were immersed in a solution of DI water, ammonia (25%), and hydrogen peroxide (30%) in a 5:1:1 volume ratio at 75 ℃ for 15 minutes. The sensors were then rinsed with DI water, dried using pure, oil-free nitrogen gas, and subjected to a second 10-minute UV/ozone treatment.

Membrane coupons were pretreated with isopropanol and water, then cut into squares slightly larger than the gold sensor. The PET backing layer of the membrane was carefully removed using tweezers, leaving the polysulfone support layer and polyamide functional layer intact. The membrane was then placed on the sensor with the polyamide layer facing the sensor surface, and secured with a glass slide and binder clip. To dissolve the polysulfone layer, DMF was added dropwise onto the membrane surface in a 65 ℃ forced-air drying oven until dissolution was complete. The sensor was then annealed at 65 ℃ for five minutes to ensure thorough drying, leaving only the polyamide layer adhered to the surface.

Mass accumulation of foulants on the sensor was measured using quartz crystal microbalance with dissipation monitoring (QCM-D, QSense Explorer, Biolin Scientific, Sweden). The mass change and frequency change detected by the sensor can be described by the Sauerbrey equation:

Δm = -C * (1/n) * Δf (8)

where Δf is the frequency change, f is the resonant frequency of the fundamental mode, A is the piezoelectrically active crystal area, ρ is the density of quartz, μ is the shear modulus of quartz for the AT-cut crystal, and Δm is the mass change on the sensor.

Since the same polyamide-coated sensor was used in all experiments, sensor-related parameters were assumed to remain consistent. Therefore, the mass of the foulants deposited on the sensor (Δm) was directly inferred by the frequency change (Δf). Before each test, the polyamide-coated sensor was installed in a flow chamber, where DI water was circulated for at least four hours to stabilize the frequency (f-value) with a drift of less than 0.1 Hz min–1.

To establish a baseline, pure water was initially introduced, followed by addition of 100 mM sodium chloride to further stabilize the baseline. For the pure gypsum group, a 50 mM gypsum solution (composed of 50 mM calcium chloride and 50 mM sodium sulfate) was subsequently added. For the organic foulant conditioning groups, a solution containing 100 mg L–1 of either BSA, HA, or SA was introduced, along with 10 mM magnesium chloride as a divalent ion to simulate the effects of calcium on organic foulants, and 80 mM sodium chloride to maintain ionic strength. After a 30-minute exposure to the organic foulant solution, the system was switched back to 100 mM sodium chloride to rinse away any loosely adsorbed foulants. Once the signal stabilized, a 50 mM gypsum solution was introduced. All QCM-D experiments were performed at 25 ℃, with a flow rate of 100 µL min–1.

Operating protocol for synchrotron infrared mapping.
Synchrotron infrared spectra were collected at the National Synchrotron Radiation Laboratory (NSRL, Hefei, China) on the Beamline of Infrared Spectroscopy and Microspectroscopy (BL01B). Infrared radiation was sourced from a bending magnet with an acceptance angle of 65(H) × 55(V) mrad², capturing both edge and constant field radiation63. The setup includes a Bruker IFS 66v Fourier transform spectrometer and a Bruker Hyperion 3000 microscope, with infrared imaging conducted in transmission mode employing a spectral resolution of 4 cm–1 over the 700–8000 cm–1 range, and a mapping step size of 4 μm (with a diffraction-limited spot size of ∼10 μm at 1000 cm–1) to achieve high spatial and spectral resolution. The synchrotron IR measurements were conducted on fouled membranes collected from the membrane fouling experiments (corresponding to the conditions shown in Figure 1). Sliced samples were positioned on a motorized x-y stage, and background spectra were recorded from the CaF window (Figure 1a). Sample cross-section structure, including both the membrane and the fouling layer on top, was identified under an optical microscope, and spectral mapping was performed covering a 10 × 40-pixel area with a step size of 4 microns. Each pixel was scanned 64 times. The mapping data were processed using OPUS software (Version 7.5, Bruker, Germany).

Simulation of concentration polarization layer.
The concentration of solute at the membrane surface (c ) is described by:

c = c * exp(J/k) (9)

where c represents the concentration of the substance at the membrane surface, c is the solute concentration in the bulk solution, c is the concentration in the permeate, J is the water flux, δ is the thickness of the concentration polarization layer, D is the diffusion coefficient of the substance in water, and k is the kinematic viscosity.

Assuming complete retention of divalent ions and organic molecules by the BW30 membrane, the concentration at the permeate side (c ) is considered to be zero. The mass transfer coefficient (k) can be calculated by:

k = (D/d ) * Sh = 1.85 * (D/d ) * (Re * Sc * d /L) (10)

where Sh is the Sherwood number, d is the wetted perimeter related to membrane module’s dimensions, Re is the Reynolds number, and Sc is the Schmidt number.

The thickness of the concentration polarization layer (δ) for each solute at the membrane surface is related to its diffusion coefficient (D) in water, while the kinematic viscosity (k) depends on the solute concentration in the feed solution. Other parameters, associated with membrane cell dimensions and operating conditions, remain consistent across all experiments. Therefore, the concentration of a substance at any position within the concentration polarization layer can be calculated by:

c(x) = c * exp(J * (δ - x) / D) (11)

where x is the distance from the membrane surface. Details of the calculation of wetted perimeter (d ), Sherwood number (Sh), Reynolds number (Re), crossflow velocity (Q and u), kinematic viscosity (k), and Schmidt number (Sc), are provided in the Supplementary Information (Supplementary Note 2).

Procedures for synchrotron X-ray scattering/diffraction measurements.
Sample preparation. The simulated concentration polarization layer solutions were prepared based on the calculated membrane surface concentration (c ), with the concentration of each component in each solution group detailed in Table 1. The pure gypsum group was created by mixing equal volumes of CaCl ·2H O and Na SO solutions. For the gypsum-organic mixture groups, the organic foulant was first mixed with the Na SO solution, and pH was adjusted to 7 before mixing with the CaCl solution. For BSA, since the calculated c concentration was too high, we reduced it to 1/20 of the original value during preparation. The saturation index (SI) of the solutions was calculated using Visual MINTEQ software (version 3.1), with an SI greater than zero under the specified physicochemical conditions indicating that the mixed solution was supersaturated with respect to gypsum (Supplementary Note 2).

In situ device set up. The induction time was determined by in situ, time-resolved synchrotron SAXS/WAXS measurements, in which the simulated concentration polarization layer solution was reacted under well-mixed, flow-controlled conditions. Specifically, 100 mL of Na SO (or mixture solution of Na SO and organic foulant) was first added to a 250 mL polypropylene beaker, continuously stirred at 500 rpm, and circulated through a quartz capillary (Φ1.86/φ 1.46, Hirschmann, German) on the sample holder using a peristaltic pump at a flow rate of 10 mL min–1. This flow rate corresponds to a crossflow velocity of 9.96 cm s–1, which is largely comparable to the 9.26 cm s–1 crossflow velocity used in the laboratory-scale RO fouling experiments, thereby ensuring that the hydrodynamic shear conditions are well-aligned with those near the membrane surface. A remote-controlled syringe pump was then used to rapidly inject 100 mL of CaCl solution into the beaker within 30 seconds to initiate the scaling. The experiment lasted for forty minutes, during which the synchrotron X-ray beam was directed through the quartz capillary, continuously collecting scattering patterns, with each exposure lasting five seconds. In situ SAXS/WAXS measurements were performed under a highly stable ambient temperature of 25 °C at the beamline, with continuous monitoring in replicate experiments confirming a minimal reaction temperature variation of ± 0.3 °C, ensuring thermal stability. It should be emphasized that no membrane substrate was involved in this in situ SAXS/WAXS setup; the capillary-based configuration was solely designed to probe homogeneous crystallization kinetics within the simulated concentration polarization solution.

Scattering Protocol. In situ time-resolved ultra-small-angle X-ray scattering (USAXS) was conducted on the Time-Resolved Ultra-Small-Angle X-ray Scattering Beamline (BL10U1) at the Shanghai Synchrotron Radiation Facility (SSRF, Shanghai, China)64. A monochromatic X-ray beam with an energy of 10 keV (1.24 Å) was used, and scattering intensity at ultra-small angles was recorded by an Eiger 4M detector. Calibration was conducted using dry collagen as the standard, with a sample-to-detector distance of 27 m, yielding a scattering vector, q, in a range of 0.0125 < q < 0.2 nm–1.

Small-angle X-ray scattering (SAXS) and wide-angle X-ray scattering (WAXS) measurements were performed at the Biological Small Angle X-ray Scattering Beamline (BL19U2)36 at SSRF. The X-ray beam energy was 12 keV (1.033 Å). SAXS data were collected using a Pilatus 2M detector, calibrated with a silver behenate standard, with a sample-to-detector distance of 2.725 m, covering a q range of 0.08 < q < 4 nm–1. WAXS data were collected using a Pilatus 300kW detector, calibrated using a highly crystalline silicon standard, with a sample-to-detector distance of 0.213 m, covering a q range of 4.5 < q < 50 nm–1. The SAXS and WAXS detectors were synchronized to ensure that each frame in SAXS corresponds directly to the same frame in WAXS. Scattering data were corrected for absolute intensity using water as the standard65.

Data processing. In all datasets from each group of samples, the scattering patterns were circular and independent of the azimuthal angle in the detector plane, indicating an isotropic system. As a result, the two-dimensional patterns were directly integrated over the scattering vector q to produce one-dimensional curves. USAXS data processing included several steps: detector calibration, masking of the beamstop and detector gap, background subtraction, and azimuthal integration, all performed using the Data Analysis Workbench (DAWN) software package (Version 2.28, Diamond Light Source, UK)66. In the Guinier region (qR < 1.3), the radius of gyration (R ) was calculated using the Guinier Law:

ln[I(q)] ≅ - (q^2 * R^2) / 3 + ln[I(0)] (12)

where q is the scattering vector, defined as q = (4π/λ) sin(θ), where λ is the wavelength of the X-ray, and 2θ is the scattering angle. I(q) represents the scattering intensity at a given scattering vector q, I(0) is the intensity extrapolated to zero angle, and R is the radius of gyration of the scatterers.

SAXS data were processed using BioXTAS RAW software (Version 2.2.1)67, with absolute intensity correction using water before integration. After generating one-dimensional curves, profile comparison with residuals was performed. WAXS data were calibrated and integrated using pyFAI (Version 2023.9)68. The induction time t of crystallization was defined by the following equation: t = t - t , where t is the elapsed time until the first detectable appearance of the characteristic gypsum (020) diffraction peak in the time-resolved WAXS frames, and t represents the time of initial supersaturation (i.e., CaCl₂ injection). The gypsum crystallinity (α) at a specific time was calculated by normalizing the peak area of the gypsum (020) peak reflection to the maximum peak area observed in the pure gypsum group. The average grain size in the direction perpendicular to the (020) plane was calculated using the Scherrer equation:

τ = (K * λ) / (β * cosθ) (13)

where τ represents the average crystallite size; K is the Scherrer constant (shape factor) set to 1; β denotes the full width at half maximum (FWHM) of the (020) peak, and θ is the Bragg angle corresponding to that peak. Due to the uneven growth of polycrystals, the average crystal grain size is capped at 8 nm to ensure it falls within the applicable range of the Scherrer equation.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "In this manuscript, Feng et al. present a novel methodology integrating in situ time-resolved X-ray scattering techniques (SAXS and WAXS) to elucidate the crystallization pathways and mechanisms of gypsum scaling under mixed fouling conditions. The authors first determined the surface concentration profiles of calcium and sulfate ions within the concentration polarization layer, which were then used as representative local concentrations for the in situ X-ray measurements. This approach enables real-time tracking of gypsum crystallization from nanoscale precursor clusters to mature crystals under complex conditions, effectively decoupling nucleation–crystallization dynamics in the bulk solution from those occurring at the membrane surface. Additionally, the authors employed synchrotron FTIR mapping and XDLVO theory calculations to support their observations. Their results provide compelling evidence that gypsum scaling under RO conditions proceeds via a non-classical, cluster-mediated nucleation pathway, offering critical insights for the design of scaling control strategies. Overall, this study represents the first demonstration of using X-ray scattering techniques to reveal membrane scaling mechanisms, particularly under mixed fouling conditions highly relevant to real-world applications. I believe the methodological innovation of in situ SAXS/WAXS will greatly benefit fouling studies in the membrane field, and the insights into non-classical nucleation will advance knowledge in related research areas. The manuscript is well-written, and the figures and schematics are clear and informative. Some specific comments for clarification and improvement include: 1. For the in situ SAXS/WAXS measurements, it would be helpful to specify whether the 10 mL/min flow rate through the quartz capillary corresponds to shear conditions comparable to those near the membrane surface in actual RO modules. 2. Regarding the SAXS and WAXS detector calibration, the authors used silver behenate and silicon standards. Could the authors include the measured calibration accuracy of the q-range to inform data precision? 3. For the SAXS/WAXS data processing, please provide details on the background subtraction procedure—specifically, whether background scattering was measured from pure solvent or from the initial pre-reaction solution, and how possible background changes over time were accounted for. 4. In determining crystallinity from the (020) peak area, please specify whether a particular peak fitting model (e.g., Gaussian, Lorentzian) was used or if a simple integration was applied. Including this detail would improve reproducibility. 5. For the synchrotron FTIR measurements, the authors used paraffin as an embedding medium. Please clarify whether control experiments were conducted to ensure that paraffin did not interfere with the FTIR spectra of interest. 6. In Figure 6b/c, the assignments of specific IR peaks (e.g., 1687 cm⁻¹ for BSA) are key to the conclusions. It would strengthen the manuscript to provide a brief justification or relevant references for these peak assignments in the main text or Supplementary Materials. 7. The authors used Visual MINTEQ to calculate the saturation index of salts. Please specify the assumed pH, temperature, and ionic strength parameters used in the software to allow reproducibility.", "reviewer_2": "This manuscript presents an innovative and comprehensive study that integrates in situ synchrotron SAXS/WAXS with FTIR mapping and interfacial energy analyses to investigate the mechanisms of gypsum scaling under mixed fouling conditions. By employing in situ SAXS and WAXS to directly probe the concentration polarization layer and track the evolution from nanoscale precursors to mature crystals, the authors provide valuable insights into non-classical nucleation pathways relevant to reverse osmosis desalination. The integration of time-resolved scattering with complementary techniques represents a significant advancement in the study of complex fouling phenomena. The manuscript is scientifically sound and includes analyses that effectively convey the key findings. The work has high significance for understanding and controlling inorganic scaling in membrane processes. I have the following comments for the authors’ consideration: 1. The manuscript describes how organic foulants influence the morphology of gypsum crystals observed by SEM. Providing average crystal sizes or aspect ratios with standard deviations would strengthen the quantitative support for these observations. 2. In the Methods section, please provide more details on temperature stability during the in situ SAXS/WAXS measurements. Specifically, how was the temperature actively controlled, and what was the observed variation range? 3. For the flux decline curves in Figure 1, I suggest including error bars representing replicate experiments, or presenting replicate results separately in the Supplementary Information to verify reproducibility. 4. In the QCM-D section, the manuscript describes frequency and dissipation changes upon foulant adsorption. Including representative raw QCM-D curves would help readers assess the quality and reliability of these measurements. 5. In the Discussion, the manuscript notes discrepancies between classical predictions and the observed scaling behavior. It would strengthen the paper to briefly discuss potential implications for current industrial antiscalant applications—for example, whether certain classes of inhibitors may be less effective if non-classical nucleation dominates. 6. For the FTIR mapping data, please indicate the spectral resolution used during the scans, as this parameter affects the precision of peak assignments. 7. Regarding the calculation of interfacial energies using XDLVO theory, please specify whether the van der Waals components were calculated directly or estimated from literature values, and consider including these parameter values to improve reproducibility.", "reviewer_3": "CaSO4 scaling and organic effect were studied in RO process, and time-resolved synchrotron X-ray scattering within the concentration polarization layer was used. But CaSO4 scaling, the effect of HA, SA, BSA and other organics on the scaling, non-classical nucleation theory (CNT) have been studied extensively in different membranes, RO, NF, MD, UF, and so on. This manuscript lacks novelty. The organic and inorganic substances in actual wastewater are highly complex, with water quality varying significantly across different industries and processes, and scaling mechanisms also differing accordingly. Therefore, experiments must be conducted using actual wastewater. Using only three simple organic compounds to study the impact on scaling offers limited practical guidance, as it merely provides a research methodology. Membrane: Why the RO membranes were immersed in a 25 v% isopropanol aqueous solution before test? Fig.S1, Fig.2d, it looks like a porous membrane, not dense RO membrane in the first figure. Could you provide the inlet pressure of the membrane and feed velocity in situ microscopic monitoring, which were 25 bar and 30.86 cm s–¹ in the fouling test and the initial water flux get to 54 L m–2h. Pressure and velocity greatly affect the thickness of boundary lay. HA, SA and BSA: For a RO membrane, it is impossible to treat a feed solution with BSA. What is the difference among the three organics? Why you choose them? For an actual RO application, what are the main organics? Scaling mechanism: Crystal shape is related with crystal style and crystallization process. Membrane material and morphology also greatly affect heterogeneous nucleation on the membrane surface, the research conclusion lacks universality. It is difficult to understand Figure S12a. what is the particle in the membrane in Figure S12e when sodium chloride + 30 mM calcium chloride is the feed solution?", "reviewer_4": "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_5": "This paper titled with \"Non-Classical Nucleation Governs Inorganic Scaling in Membrane Desalination\" utilizes in-situ real-time SAXS and WAXS analysis, coupling with FTIR, XRD, and interfacial energy analysis, to study the crystallization process of gypsum in the membrane system, with or without the presence of three typical organic compounds. Such experimental setup is a pioneering approach that can facilitate monitoring mineral crystallization process with both high temporal (seconds level) and spatial resolutions (nm level). Such efforts from the authors will be widely appreciated from scientists in this discipline, and can potentially improve the research in this field. The experimental results also provide valuable data for further studies in this area. On the other hand, however, in terms of analyzing the nucleation (actually crystallization in this study) process of gypsum in the RO process, more efforts might be needed to draw convincing conclusions. Listed below are the major and minor concerns I have. ================= Major concerns: 1. The authors should give clear definitions of \"induction time\", \"nucleation\" versus \"crystallization\", \"scatters\", \"nuclei\", \"clusters\", \"foulant\", etc., without which unnecessary confusion may exist. Actually, most of them have very strict definitions. The authors may want to be more accurate especially when discussing about CNT and N-CNT pathways. 2. The authors seem to differentiate CNT and N-CNT using a wrong criterion. For example, the authors stated, \"... follow a non-classical three-phase pathway. This pathway involves the formation of supersaturated solutions containing nanoscale anhydrous CaSO4 precursor clusters, which grow to critical sizes, aggregate, and rearrange into ordered structures with the incorporation of water molecules.\" In this paragraph, the authors suggest that the observation of amorphous phase is the evidence of N-CNT, which is not true, instead, key difference of N-CNT from CNT is the occurrence of a metastable phase (e.g., pre-nucleation clusters, PNC, proposed by Gebauer et al. (2008)), rather than size threshold (i.e., critical nuclei size, larger than which is stable, vice versa). Gebauer suggested that such PNC can stably occur in solution even in under-saturated solutions. As a result, one of the main conclusions of this paper, i.e., gypsum nucleation in the membrane system follows a N-CNT process, cannot be fully supported by the evidences. 3. The authors suggested that \"in CNT-governed systems, inhibitors function primarily by reducing supersaturation or chelating free ions to suppress nucleation22, while in NCNT-governed systems, inhibitors could elevate interfacial energy barriers to prevent lattice matching and subsequent crystal growth on surfaces23. \" This statement is not all true. Many papers have suggested that inhibitors can also inhibit nucleation via the increase of surface tension or the decrease of supersaturation (the two major energy changes during CNT), as well molar volume change in CNT-governed systems. It is true, though, that many scientists have found that many CNT-governed systems are actually N-CNT when PNC was observed, we cannot achieve the statement cited above. In another way of saying, how inhibitors work does not necessarily indicate the crystallization pathways. 4. The authors stated that \"The feed solutions consisted of 30 mM calcium chloride (CaCl2) and 30 mM sodium sulfate (Na2SO4), resulting in a supersaturation index (SI) of 1.71 . Under these conditions, the theoretical induction time for gypsum scaling would be on the order of thousand years. However, due to the presence of concentration polarization at the membrane surface, the gypsum SI rose to 10.05 (Supplementary Note 2), significantly reducing the induction time to ~4 minutes43,44. This finding indicates that gypsum scaling occurs exclusively within the concentration polarization layer, rather than from spontaneous crystallization in the bulk solution. \" Such statements go against with experimental results and model predictions in the following papers. All these papers suggested that, even at a lower saturation status (i.e., about 25 mM of Ca and SO4 with SR of 1.41 (SI = log10(SI) = 0.15), the induction time measured by both turbidity meter and QCM-D is about 10 hours, orders of magnitudes shorter than \"thousand years\". As a result, gypsum scaling does NOT occur exclusively within the concentration polarization layer. The authors may want to double check the experimental conditions, redesign the experiments and also re-check the conclusions. He, Shiliang, J. E. Oddo, and M. B. Tomson. 1994. “The Inhibition of Gypsum and Barite Nucleation in NaCl Brines at Temperatures from 25 to 90 °C.” Applied Geochemistry 9 (5): 561–67. https://doi.org/10.1016/0883-2927(94)90018-3. Huang, Xiaochuan, Chen Li, Kuichang Zuo, and Qilin Li. 2020. “Predominant Effect of Material Surface Hydrophobicity on Gypsum Scale Formation.” Environmental Science & Technology 54 (23): 15395–404. https://doi.org/10.1021/acs.est.0c03826. Dai, Zhaoyi, Yue Zhao, Samridhdi Paudyal, Xin Wang, Chong Dai, Saebom Ko, Wei Li, Amy T. Kan, and Mason B. Tomson. 2022. “Gypsum Scale Formation and Inhibition Kinetics with Implications in Membrane System.” Water Research 225 (October):119166. https://doi.org/10.1016/j.watres.2022.119166. 5. How reproducible are these experiments? It is well-known that extensive attention is needed for nucleation experiments to ensure reproducibility. 6. The author suggested \"The process of inorganic scaling is time-dependent and progresses through distinct stages—induction, nucleation, crystal formation, and growth\". By definition from many papers and Mullin's book \"Crystallization\", induction time is from the occurrence of supersaturation to the observation of minerals, which can include nucleation, crystal growth, aggregation, etc. Therefore, the stages listed above are NOT distinct stages and they do not necessarily happen one after another. They authors need to check such definitions throughout the paper. 7. In Figure 3 a, the stage boundaries are not clear, and the criteria of setting stage boundaries are not clearly stated. Furthermore, more details are needed to explain how the conclusions are drawn, e.g., \"... Figure 3b, in Stage I, the increase in scattering intensity indicates the formation of scatterers with electron densities distinct from the background solution. In Stage II, interactions among primary species led to the formation of small clusters and the development of the system’s structure factor, resulting in a slight decrease in scattering intensity. \", \"In Stage III, BSA strongly delayed the formation of larger nuclei, thus effectively inhibiting the aggregation and growth of clusters (Figure 3a2).\", \"This behavior is likely due to the weaker ionic binding capacities of HA molecules, which prevented significant suppression of supersaturation. \", etc. In another way of saying, the current arguments are not strongly supported by the experimental evidences or theoretical derivations. Actually, I much appreciated the authors efforts in running in-situ real time testings from different perspectives. It is strongly recommended that the authors can couple these properties (turbidity, conductivity, interfacial energy, crystal size, Rg, etc.) and fit them into a well explained mechanism. 8. The authors tried to divide the crystallization process in different stages, however, the stage boundaries in figures 3 and 4 are very different. The authors may want to be very clear about how stages are defined, what exactly happened in each stage, and how they can compare with each other. 9. It is a nice experimental setup using peristatic pump to circulate solutions through quartz tube. When organic molecules are present, the observed crystallization signals varied significantly. However, will such organic molecules change the flow conditions, influence the adsorbed crystal mass onto quartz tube, in addition to changes on the crystallization process? 10. A comparison between figure 1a and figure 5a might be interesting to show the impacts of organic foulants. =================== Minor concerns: 1. By convention, saturation ratio (SR) is defined as ion activity product over solubility product (IAP/Ksp), and SI is defined as the base ten logarithm of SR (SR = log10(IAP/Ksp)), though different conventions have been followed. At least, the authors are suggested to give the equations. 2. There are two figure 2. 3. Since the stages are critical for the discussions in figures 3 - 5, it is suggested the authors make the stage boundaries much clearer in each subplot, e.g., 1a, 3b, 3c, 3d, 3e, 4c. 4. More details should be included in the interaction energy calculations in figure 5. 5. In figure 3e, the Rg of pure gypsum fluctuates significantly (from 3 - 7 nm). What happened, and is there any other evidence to support your hypothesis, and how reproducible are such testings?"}, "author_response": "Before our response to the specific comments of the reviewer, we would like to highlight the key revisions made: 1. Verified SAXS/WAXS measurement accuracy through detector calibration using standard references (i.e., silver behenate and silicon), and elaborated the background subtraction protocol to strengthen the reliability of the in situ synchrotron X-ray scattering data. 2. Conducted experiments to demonstrate that paraffin embedding did not interfere with FTIR spectra and strengthened IR band assignments with literature-supported references. 3. Clarified the hydrodynamic conditions of the in situ SAXS/WAXS setup to demonstrate its consistency with operating conditions of RO crossflow experiments. 4. Refined theoretical framework and terminology to improve conceptual clarity and ensure alignment with established crystallization theories. 5. Revised the title and relevant analyses to better emphasize the key innovation of this study—the development of in situ, time-resolved synchrotron X-ray scattering techniques for mechanistic elucidation of interfacial scaling dynamics. General Comment: In this manuscript, Feng et al. present a novel methodology integrating in situ time-resolved X-ray scattering techniques (SAXS and WAXS) to elucidate the crystallization pathways and mechanisms of gypsum scaling under mixed fouling conditions. The authors first determined the surface concentration profiles of calcium and sulfate ions within the concentration polarization layer, which were then used as representative local concentrations for the in situ X-ray measurements. This approach enables real-time tracking of gypsum crystallization from nanoscale precursor clusters to mature crystals under complex conditions, effectively decoupling nucleation–crystallization dynamics in the bulk solution from those occurring at the membrane surface. Additionally, the authors employed synchrotron FTIR mapping and XDLVO theory calculations to support their observations. Their results provide compelling evidence that gypsum scaling under RO conditions proceeds via a non-classical, cluster-mediated nucleation pathway, offering critical insights for the design of scaling control strategies. Overall, this study represents the first demonstration of using X-ray scattering techniques to reveal membrane scaling mechanisms, particularly under mixed fouling conditions highly relevant to real-world applications. I believe the methodological innovation of in situ SAXS/WAXS will greatly benefit fouling studies in the membrane field, and the insights into non-classical nucleation will advance knowledge in related research areas. The manuscript is well-written, and the figures and schematics are clear and informative. Our Response: We sincerely thank the reviewer for the thoughtful and encouraging evaluation of our manuscript. We are also grateful for the reviewer’s compliments on the relevance of our approach to membrane fouling studies and the broader implication of our findings in revealing non-classical nucleation pathways. We have carefully revised the manuscript to further enhance its clarity, rigor, and completeness. Specific responses to all comments are provided below, along with detailed explanations of corresponding modifications made to the manuscript. Comment 1: For the in situ SAXS/WAXS measurements, it would be helpful to specify whether the 10 mL/min flow rate through the quartz capillary corresponds to shear conditions comparable to those near the membrane surface in actual RO modules. Our Response: We thank the reviewer for raising this important point regarding the hydrodynamic relevance of our in situ SAXS/WAXS characterization approach to real RO operating conditions. In our synchrotron experiments, the flow rate through the quartz capillary was set at 10 mL/min, with an inner diameter of 1.46 mm, yielding a crossflow velocity of approximately 9.96 cm/s. This value is highly comparable to the crossflow velocity of 9.26 cm/s used in our laboratory-scale RO membrane fouling experiments. Therefore, the shear conditions generated within the capillary closely mimic those at the membrane surface in actual RO modules operating under similar conditions. To clarify this point for readers, we have revised the Methods section of the manuscript as follows: Manuscript: Page 23, Line 667: “First, 100 mL of Na SO (or mixture solution of Na SO 2 4 2 4 and organic foulant) was added to a beaker. The solution was stirred continuously at 500 rpm and circulated through a quartz capillary (Φ1.86 /φ1.46, Hirschmann, German) mounted on the sample holder using a peristaltic pump at a flow rate of 10 mL min–1. This flow rate corresponds to a crossflow velocity of 9.96 cm/s, which is largely comparable to the 9.26 cm/s crossflow velocity used in the laboratory-scale RO fouling experiments, thereby ensuring that the hydrodynamic shear conditions are well-aligned with those near the membrane surface.” Comment 2: Regarding the SAXS and WAXS detector calibration, the authors used silver behenate and silicon standards. Could the authors include the measured calibration accuracy of the q-range to inform data precision? Our Response: We thank the reviewer for this helpful suggestion. In our study, silver behenate was used for SAXS detector calibration, and crystalline silicon powder was employed for WAXS calibration. The calibration accuracy was carefully verified by comparing the measured peak positions of the standards with their known theoretical values (as shown in Figure R1). For the WAXS measurements, the resulting sample-to-detector distance was calibrated to be 0.213383543 ± 6.99737 × 10−5 m, yielding a coefficient of variation of 0.03279%, which reflects a high degree of measurement precision. For the SAXS measurements, the sample-to-detector distance was consistently determined to be 2.725298 m, with no measurable deviation observed within the resolution limit of the calibration software (as shown in Figure R2). This level of accuracy ensures the reliability of the extracted structural parameters such as cluster radius and crystal lattice spacing. To address the reviewer’s comment, we have added the following clarification to the revised Supplementary Information: Supplementary Information, Page S6, Line 159: “To ensure accurate structural parameter extraction, the q-range of the SAXS detector was calibrated using silver behenate, yielding a sample-to-detector distance of 2.725298 m. The WAXS detector was calibrated using crystalline silicon powder, providing a highly precise sample-to-detector distance of 0.213383543 ± 6.99737 × 10−5 m, corresponding to a relative standard deviation (RSD) of 0.03279%. These calibrations confirm the accuracy and reliability of the extracted structural parameters used in the data analysis.” Comment 3: For the SAXS/WAXS data processing, please provide details on the background subtraction procedure—specifically, whether background scattering was measured from pure solvent or from the initial pre-reaction solution, and how possible background changes over time were accounted for. Our Response: We thank the reviewer for this important question regarding our background subtraction procedure in the SAXS/WAXS data analysis. For both SAXS and WAXS experiments, background scattering was subtracted using a reference frame acquired immediately after mixing the reaction solution. Specifically, once calcium chloride was injected into the premixed solution containing sodium sulfate (with or without organic foulants), the reaction mixture entered the quartz capillary, and we monitored the scattering intensity in real time. Notably, the intensity initially decreased and then began to rise as crystallization progressed. The frame corresponding to the lowest scattering intensity was designated as the “initial frame”, representing a state where the solution was fully mixed and diluted but before any nucleation or aggregation had occurred. This frame effectively accounts for scattering contributions from the solvent, dissolved salts, and any present organic additives. Notably, to ensure robustness, we also measured several additional reference backgrounds: (1) empty capillary (air), (2) ultrapure water, and (3) the pre-reaction solution containing all components except calcium chloride. In all cases, the measured signal intensities were significantly lower than those observed during active crystallization, confirming that background contributions from non-crystallizing components were negligible. For time-resolved datasets, this initial blank measurement was consistently used for background subtraction across all time points. This methodology relies on the assumption that the background scattering from non-crystallizing components remained stable during the relatively short duration of each scaling experiment. Furthermore, to minimize the influence of any potential long-term drift or significant changes in the background, we routinely checked and re-measured the blank background were routinely re-validated before each new experiment. We have added a more detailed explanation of this background subtraction protocol to the revised Supplementary Information, ensuring full transparency and reproducibility of our SAXS/WAXS analysis. Supplementary Information, Page S6, Line 165: “For the analysis of the time-resolved SAXS and WAXS data, rigorous background subtraction was performed to isolate the scattering signals originating from the forming crystalline phases. The background reference was acquired from a frame collected immediately after the complete mixing of the reactants (i.e., sodium sulfate, calcium chloride, and where applicable, the selected organic foulants).” Comment 4: In determining crystallinity from the (020) peak area, please specify whether a particular peak fitting model (e.g., Gaussian, Lorentzian) was used or if a simple integration was applied. Including this detail would improve reproducibility. Our Response: We thank the reviewer for raising this important point regarding the determination of crystallinity from the (020) diffraction peak. In our analysis, a simple numerical integration was used to quantify the area under the (020) peak. This choice was based on the fact that the (020) peak observed in our WAXS data was a sharp and well-resolved Bragg diffraction peak, characteristic of highly crystalline gypsum. The full width at half maximum (FWHM) was narrow, and there was negligible overlap with adjacent peaks or background fluctuations. As such, peak fitting using Gaussian or Lorentzian models was not necessary, and direct integration provided a sufficiently accurate and reproducible measure of the crystalline content. We have now clarified this methodological detail in the revised Supplementary Information to enhance transparency and reproducibility. Supplementary Information, Page S6, Line 170: “The crystallinity was quantified by determining the integrated area of the characteristic gypsum (020) diffraction peak in the WAXS patterns. Due to the sharp and well-resolved nature of this peak, and the absence of overlapping signals in this region, a numerical integration method was applied to calculate the peak area, providing a direct and reproducible measure of the relative crystalline content across different experimental conditions.” Comment 5: For the synchrotron FTIR measurements, the authors used paraffin as an embedding medium. Please clarify whether control experiments were conducted to ensure that paraffin did not interfere with the FTIR spectra of interest. Our Response: We thank the reviewer for this important and insightful comment. To confirm that the use of paraffin as an embedding medium did not interfere with the interpretation of FTIR spectra, we conducted control measurements on paraffin-only sections, which were prepared under identical embedding and microtome-sectioning conditions as the membrane fouling samples. The resulting spectra were directly compared with those from membrane samples containing gypsum and other foulants (Figure R3). We have now included these spectra in the revised Supporting Information as Figure S16, which shows the infrared absorption profiles of paraffin, the pristine membrane, and key foulants. This comparison confirmed that the characteristic vibrational bands of the TFC membrane and the foulants are clearly distinguishable from the dominant paraffin adsorption signals, which are primarily confined to the 2957.17−2849.38 cm−1 region corresponding to C–H stretching vibrations of alkane. The result confirms that the paraffin embedding process did not obscure or overlap with the spectral features of interest. We have now added this information to the revised Supplementary Information Supporting Information: Page S9, Line 341: “To ensure that the paraffin embedding medium did not interfere with the spectral analysis of foulants on the membrane, control Fourier-Transform Infrared (FTIR) measurements were conducted on paraffin-only sections prepared under identical conditions as those applied to the membrane samples. Figure S21 presents a comparison of the infrared absorption profiles for the paraffin matrix, the pristine TFC membrane, and the key organic foulants. In particular, the spectral analysis confirmed that the characteristic vibrational bands of the TFC membrane and the organic foulants were clearly distinguishable from the absorption signals originating from the paraffin. The dominant paraffin signals, characteristic of C–H alkane stretching, occur primarily in the 2957.17−2849.38 cm−1 region. Importantly, the analytical bands used for foulant identification and quantification fall outside or are sufficiently resolved from this range, ensuring that the paraffin embedding process did not obscure or overlap with the spectral features of interest.” Comment 6: In Figure 6b/c, the assignments of specific IR peaks (e.g., 1687 cm⁻¹ for BSA) are key to the conclusions. It would strengthen the manuscript to provide a brief justification or relevant references for these peak assignments in the main text or Supplementary Materials. Our Response: We thank the reviewer for raising this important point regarding the justification of specific infrared peak assignments shown in Figures 6b/c. We fully agree that providing explicit evidence and literature support is essential for transparency and reproducibility. To strengthen our spectral interpretation, we performed FTIR characterization on standard samples of common organic foulants, including bovine serum albumin (BSA), humic acid (HA), and sodium alginate (SA), as well as the pristine membrane. These spectra were systematically analyzed and cross-referenced with peak assignments reported in prior literature to ensure consistency and accuracy. Specifically, the peak at 1687 cm–1 was assigned to the amide I α-helix band of BSA, a well-established marker of protein secondary structure. The peak at 1012 cm–1 corresponds to O–H deformation vibrations of HA. The peak at 1048 cm–1 is attributed to the C–O stretching of SA polysaccharide structures. Furthermore, we confirmed that these peaks do not exhibit significant overlap, allowing for unambiguous identification of each foulant’s spectral signature. We have now incorporated this justification into the revised Results section and provided the reference spectra in the updated Supplementary Information. Supporting Information, Page S9, Line 369: “Characteristic peaks for various samples were identified as follows: 1587 cm−1 for TFC membrane, 3395 cm−1 for gypsum, 1687 cm−1 for BSA, 1012 cm−1 for humic acid, and 1148 cm−1 for sodium alginate. In particular, the peak at 1587 cm−1 is attributed to the coupling of in-plane N–H bending and C–N stretching vibrations of the amide group in the polyamide layer. The peak at 3395 cm−1 corresponds to the O–H stretching vibration of crystal water in gypsum. The peak at 1687 cm−1 is associated with the BSA amide (I) α-helix, while the 1012 cm−1 peak is due to the O–H deformation of phenolic functional groups in humic acid. The peak at 1148 cm−1, assigned to elongation of C–O groups in sodium alginate, was selected over the expected 1050 cm−1 to avoid overlap with the polyamide membrane signal.” Comment 7: The authors used Visual MINTEQ to calculate the saturation index of salts. Please specify the assumed pH, temperature, and ionic strength parameters used in the software to allow reproducibility. Our Response: We thank the reviewer for highlighting the need to clarify the modeling parameters used in our Visual MINTEQ calculations. In particular, we used the following settings to match our experimental conditions: a fixed pH of 7.0, a temperature of 25.0 °C, and the ionic strength was calculated directly from the complete feedwater composition, derived from the known concentrations of all added salts. These values reflect the condition used in our RO fouling experiments. For instance, the feed solution was freshly prepared using ultrapure water and analytical-grade salts. The pH was adjusted to 7.0 using HCl or NaOH, and the solution temperature was maintained at 25.0 ± 0.3 °C using a recirculating chiller throughout the entire experiment. Moreover, during each RO run, the system was operated in closed-loop mode, where both permeate and concentrate were continuously recirculated to the feed tank. This configuration ensured that the bulk composition and ionic strength of the feedwater remained constant over time, which is critical for consistency between experimental and modeled saturation index values. With the reviewer’s comment, we have now included these detailed assumptions and procedures in the revised Supporting Information to enhance transparency and allow full reproducibility of the modeling results. Supporting Information: Page S4, Line 100: “The saturation index (SI) of the scaling salts was calculated using the Visual MINTEQ chemical equilibrium software (version 3.1). All modeling parameters were selected to replicate the conditions used in the RO fouling experiments, ensuring reproducibility of the results. Specifically, the pH was fixed at 7.0 and the temperature at 25.0 ℃, consistent with the controlled pH and thermal conditions in the experimental setup. The ionic strength was each feed solution was calculated by the software based on the complete chemical composition of the feedwater, which was derived from the known concentrations of all analytical-grade salts added to the ultrapure water. Since the RO system was operated in a closed-loop configuration with continuous recirculation of both permeate and concentrate to the feed tank, the bulk composition of the feedwater remained stable throughout each experiment. Consequently, the calculated ionic strength and corresponding saturation index were assumed constant during the entire operational period.”"}, {"round": 2, "reviewer_comments": {"reviewer_1": "I reckon that the revised manuscript has addressed all my comments and is up to publishing standard.", "reviewer_2": "The authors have addressed all concerns that I and other re viewers raised. The manuscript is ready for acceptance for publication.", "reviewer_4": "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_5": "Thanks a lot to revise the manuscript according to the reviewers' comments and suggestions. Their replies solved most of the concerns, and the revisions have improved the paper significantly. However, some key issues still remain unresolved. Further clarifications and revisions might be needed. 1. The authors converted all statements of CNT to \"single-step crystallization\", and non-classical process as \"multiple-step crystallization\". This might not be all true. CNT or non-classical nucleation refer to the different paths of nucleation, both of which can be followed with aggregation, crystal growth, ripening, phase transition, etc. Therefore, I think the authors are unclear or confusing the audience about what exactly the crystallization processes they are studying. 2. Similarly, while the authors introduced the results from SAXS and WAXS, the fouling process has been divided into four \"phases\" and three \"stages\". Is phase 1 the same as stage I? If not, what happened differently in these two different steps? In other words, mechanistically, what is the fouling process, what do different measurements mean, and more importantly, how are they related to each other? 3. The induction time measurement performed by the author might not be accurate enough without stirring and high resolution detection methods (e.g., QCM-D). Also, the authors need to be more specific about how do they calculate the induction time, as the authors mentioned several times in the paper. Actually, the key issue is, if the solution has an induction time of less than 10 hours, as the polarization layer is more than 80 micrometers thick, it is challenging to assume that crystallization happens only homogeneously or heterogeneously. Furthermore, why is testing in figure 3 run with 85 mM Ca/SO4 instead of other concentrations shown in Fig. 2b? 4. I believe the authors still used SI and SR wrong. Please take a check again. I strongly suggested that the authors keep the equation (in-line) in the main text to avoid such confusion. 5. Fig 1a shows BSA has the best inhibition efficiency, but Fig. 5a shows HA is the best with significant improvement. It is explained that BSA inhibits homogenous nucleation but HA inhibits heterogeneous nucleation (in Discussion session). What are the differences of these two processes, i.e., homogeneous versus heterogenous? Though I'm really impressed by the in-situ analysis results, I cannot picture how these three molecules work differently in the fouling process. 6. As mentioned in comment 3, can you confidently assume that experiments run in Fig.5 is heterogeneous nucleation? Or, does that really matter? 7. Has the membrane tested in Fig 2 and 3 also examined with FTIR? 8. The authors mentioned several times that SA forms a \"gel-like structure\". What exactly is this gel-like structure? How it works and how can we draw such conclusion from the experimental data? Overall, this paper provides very important data, but it seems that the authors has not clearly explained the mechanisms of gypsum crystallization nor the inhibition process."}, "author_response": "Thanks a lot to revise the manuscript according to the reviewers' comments and suggestions. Their replies solved most of the concerns, and the revisions have improved the paper significantly. However, some key issues still remain unresolved. Further clarifications and revisions might be needed. Overall, this paper provides very important data, but it seems that the authors has not clearly explained the mechanisms of gypsum crystallization nor the inhibition process. Our Response: We sincerely thank the reviewer for his/her continued engagement with our manuscript and for acknowledging that the revised version has significantly improved. We understand the reviewer’s comments that the earlier version of the manuscript did not sufficiently match the depth of experimental observation with a rigorous and transparent explanation of the underlying mechanisms. In this revised version, we have therefore provided a strong emphasis on mechanistic clarity and theoretical precision. Specifically, we have implemented the following improvements: Refinement of Nucleation Terminology: We have moved away from the previously vague terminology (e.g., “single-step” vs. “multi-step” nucleation) and instead adopted more precise descriptors, such as ion-by-ion (classical) and precursor-mediated (non-classical) nucleation, clearly delineating nucleation from subsequent growth and aggregation. Established direct correlations between SAXS and WAXS observations by aligning SAXS-detected amorphous precursor formation with WAXS-defined crystallization stages. Defined induction time as the interval from supersaturation onset to the appearance of the gypsum Bragg peak in WAXS under controlled flow conditions. Distinguished between bulk-phase kinetically controlled precursor formation and interfacial thermodynamically governed crystal adhesion, resolving inconsistencies in inhibition performance. Integrated SAXS/WAXS, interfacial energy analysis, QCM-D, synchrotron FTIR mapping, and microscopy into a cohesive mechanism-driven interpretation of scaling and inhibition. Together, these revisions aim to provide a clear, evidence-based mechanistic insight that fully leverages the high-resolution structural data collected in this study and analytical elucidation of scaling mechanisms. Detailed responses to each of the reviewer’s specific comments are provided below."}, {"round": 3, "reviewer_comments": {"reviewer_5": "Thanks a lot for the authors' responses and revisions. For most comments, the authors have addressed my concerns. I recommend the acceptance of this paper after minor revisions and no need for my further review. However, in comment 3, I mean the supplementary experiment run in the bulk beaker. In addition, the authors still did not introduce the equation they use to \"calculate\" the induction time. Please correct those issues as well. Thanks again for the opportunity for us to be engaged in the publication process of this nice paper."}, "author_response": "We sincerely appreciate Reviewer #5’s positive evaluation of our previous revisions and for pointing out these two specific points for further clarification. We now understand that the concerns regarding induction time accuracy and methodology primarily targeted the supplementary experiments conducted in the bulk beaker (Supplementary Note 3). We have addressed these issues as follows: Regarding stirring and homogenization, we have explicitly emphasized in Supplementary Note 3 that the bulk beaker experiments were conducted under continuous magnetic stirring at 500 rpm. This high stirring rate was specifically chosen to ensure rapid homogenization of the reactants and to minimize local concentration gradients, thereby ensuring that the induction time measured via macroscopic sensors (conductivity and turbidity) is representative of the entire volume. Regarding the calculation of induction time, following the reviewer's suggestion to be more specific, we have introduced a formal equation for t in Supplementary Note 3. The induction time is defined as: t = t -t where t is the timestamp of the first detectable deviation from the baseline (e.g., the onset of conductivity decline or turbidity increase) and t is the time when initial supersaturation was achieved upon completion of the CaCl injection."}]

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