Accelerated directional growth of seaweed-like iron oxide branches driven by localized electric fields of gold nanoparticles in liquid

Domain: biology
Published: 2026-03-31
Editorial outcome: major_revision

Abstract
Branched nanostructures have attracted significant attention due to their potential applications across diverse fields. Precise control over branched morphology is essential for enhancing their functionality, yet it remains a considerable challenge. In this work, in-situ liquid-cell transmission electron microscopy (LCTEM) is employed to investigate the controllable growth of seaweed-like iron oxide branches in the presence of charged gold nanoparticles (Au NPs) within an organic solution. In contrast to the conventional tip-splitting behavior observed in the absence of Au NPs, the branches exhibit directional and accelerated growth toward the Au NPs without further splitting. Finite-element analysis reveals that the local electric field between the charged Au NPs and the branches promotes reactant aggregation at the branch tips, thereby driving their directional and accelerated growth. This study provides insights into the growth mechanisms of seaweed-like nanostructures and highlights the potential of local electric fields for morphological control of branched structures.

Introduction
Branched nanostructures have attracted increasing attention due to their distinctive structural feature and have found widespread applications in various fields1, 2, 3, 4, including catalysis, energy storage, environmental protection, and sustainable remediation, etc. The functional properties of branched structures are largely influenced by their structural characteristics4, 5, 6 such as morphology, fractal dimension, and specific surface area. Consequently, precise control over the morphology of branched structures is essential for optimizing their performance in various applications.

Extensive efforts have been made to regulate the growth of branched structures by tuning growth parameters and applying external fields7, 8, 9, 10, 11, 12. For example, modulation of precursor concentration can improve the control over fractal dimensions and surface areas of dendrites, thereby enhancing their effectiveness in water filtration and electrocatalytic applications10, 11. The application of an electric field can guide the lateral growth of metal branches, representing a significant advancement towards safer battery technologies12. Despite these advances, the fundamental mechanisms governing branched structure growth at the nanoscale remain insufficiently understood, thereby limiting the rational design and synthesis of desired nanostructures.

The mechanisms governing branched morphology and growth dynamics have been extensively investigated through theoretical approaches. The morphological instability theory raised by Mullins and Sekerka attributes branched nanostructures growth to interfacial instabilities13, 14, 15, whereas the microscopic solvability theory emphasizes that crystal anisotropy determines the growth rate and tip morphology16, 17, 18. If there is little or no anisotropy in the growth kinetics or interfacial energy, branches tend to undergo continuous tip splitting, ultimately evolving into a seaweed morphology19. The theoretical predictions of morphology development have been extensively verified at the microscale by simulations and experiments20, 21, 22. However, it remains unclear whether theoretical predictions of morphology control can be reliably extended to the nanoscale, since certain assumptions and derivations in classical theories may not hold at this scale. A comprehensive understanding of morphology evolution at the nanoscale requires the use of advanced in-situ visualization techniques to reveal dynamic growth behaviors.

Recent advances in LCTEM enable the visualization of nanomaterial dynamics in liquid with high spatiotemporal resolution23, 24, 25, 26, 27, 28, providing an opportunity to study branched structures growth mechanisms at the nanoscale. In this study, LCTEM was employed to systematically investigate the growth dynamics of seaweed-like iron oxide nanostructures, while charged Au NPs were introduced into the reaction solution to modulate the branch formation. Observations revealed that the Au NPs guided the directional and accelerated growth of the branches, in contrast to the tip-splitting growth pattern observed in their absence. Finite-element analysis indicated that the local electric field between the charged Au NPs and the branches governs this directional and accelerated growth behavior.

Results
In-situ observation of seaweed-like nanostructure growth. In-situ LCTEM experiments were conducted by sealing the reaction solution within a silicon nitride (SiN ) liquid cell (Fig. 1a and Methods). The reaction solution was prepared by dissolving Fe(acac) in a mixture of oleylamine (OAm), oleic acid (OAc), and benzyl ether, followed by the addition of Au NPs. Iron oxide clusters were nucleated and grown into branched structures via OAm-promoted electron-beam reduction, consistent with the methodology reported by Hauwiller et al.29. This growth pathway has been previously demonstrated to closely mimic conventional thermally activated synthesis processes of Fe₃O₄30, 31. Post-analysis indicated that the product contains Fe₃O₄, but the presence of FeO cannot be excluded (see Supplementary Note 3 and Supplementary Figs. 1, 2). Herein, we refer to the product as iron oxide, and subsequent analysis reveals that the specific composition makes little sense to growth mechanisms. Morphologically, the iron oxide branches observed in LCTEM do not exhibit a well-defined primary growth direction or a distinct columnar trunk32. As a result, the overall growth of iron oxide is described as seaweed-like growth. To enable accurate tracking and analysis of the growth dynamics, a deep learning-based method was developed to extract the contours of the nanostructure throughout the growth process (Fig. 1b and Supplementary Note 1).

Figure 1c (see Supplementary Movie 1) illustrates a typical growth sequence of iron oxide seaweed nanostructures. Interestingly, when Au NPs are present near the branch tips, the branch growth exhibits a directed growth toward the Au NPs, accompanied by suppression of tip splitting and lateral widening, ultimately leading to contact between the branch and the particle (marked by the blue dashed line). In contrast, branches lacking Au NPs ahead of the growth front (highlighted by the red dashed line) undergo pronounced tip splitting and develop multi-branches, reflecting a more conventional dendrite growth mode29 (additional comparative examples are provided in Supplementary Figs. 3–6 and Supplementary Notes 4, 5). This distinct modulation of growth behavior by Au NPs highlights their role in guiding nanostructure formation. Fig. 1d shows the growth trajectories of the iron oxide nanostructures, where the color gradient from pink to red indicates the temporal evolution from the beginning to the end. It is worth noting that branched structure growth is predominantly two-dimensional (2D) on the SiN membrane, with only the Au NPs located on the same membrane (identified by their high contrast and well-defined contour, see Supplementary Fig. 7) exerting a significant influence on the growth behavior.

Growth kinetics of seaweed-like nanostructures. To elucidate the role of Au NPs in branch growth, a comprehensive analysis of branch growth behavior was first conducted in the absence of Au NPs. Within NP-free regions, the branches exhibit non-directional and highly branched growth. The contours of these branches throughout the growth process were extracted and are presented in Fig. 2a, b. For branch 1, the growth front initially undergoes flattening and lateral widening before splitting into two new tips, ultimately forming a small, multi-branched structure. The temporal evolution of the tip radius was quantified, revealing that the curvature radius increases during the tip-widening and subsequently decreases as splitting occurs (Fig. 2c). Pattern formation from a homogeneous liquid solution is generally governed by the competition between interfacial energy and interfacial instability. The initial broadening of the tips may be attributed to fluctuations occurring during growth. Subsequently, tip splitting occurs when the tip radius exceeds the critical threshold for morphological instability in iron oxide domains, which is ≈ 5 nm29.

It is worth noting that not all growth fronts exhibit splitting behavior, as shown in Fig. 2b. This variation may be attributed to substantial precursor depletion during the growth process. As reported in refs.19, 33, seaweed-like morphology can only be achieved when the supersaturation reaches a sufficiently large level.

Furthermore, the correlation between the growth rate and tip radius in the absence of Au NPs was quantitatively analyzed. The growth rate was estimated based on the assumption of approximately unidimensional tip extension by measuring the displacement of each tip along the growth direction in each frame of the image sequence. The logarithmic correlation between growth rate and tip curvature radius displays a linear trend with a slope of ≈ -1.1 (Fig. 2d), consistent with a diffusion-controlled model for 2D dendritic growth15. It is obvious that a smaller tip curvature radius correlates with faster branch growth, likely due to an enhanced local concentration gradient induced by higher curvature, which facilitates more efficient material accumulation at the growth front.

In contrast, when Au NPs are present in the vicinity of the branch tip, the tip undergoes a local deflection and exhibits a growth tendency toward the direction where the NPs are located. As shown in Fig. 3a, the branches maintain a sharp forefront until making contact with Au NPs. Specifically, Fig. 3b intuitively illustrates how the NP guides the growth of the branch. Here, θ₁ denotes the angle between the horizontal axis and the branch’s growth direction, while θ₂ represents the angle between the horizontal axis and the line connecting the center of the Au NP to the branch’s initial growth point. It is evident that the initial growth is not oriented toward the particle, as indicated by the discrepancy between θ₁ and θ₂. The branch subsequently adjusts its trajectory to align with the position of the NP. When the NP shifts, the branch’s growth direction changes accordingly. Supplementary Fig. 8 shows a strong correlation between the variations of θ₁ and θ₂. In addition, it is found that the local morphology of the nanostructures varies with the positioning of the NPs, as shown in Fig. 3c (see more information in Supplementary Movie 2, Supplementary Fig. 9 and Supplementary Note 6). When multiple Au NPs are located in front of the tips, it can give rise to a corresponding number of growing branches. These phenomenon supports the conclusion that the Au NP serves as a guide for the directional growth of branches.

In the presence of Au NPs, the logarithmic correlation between the growth rate and tip radius remains linear (Fig. 3d), with slopes ranging from -2.1 to -2.4 (-2.12 for branch 3, -2.31 for branch 4, -2.30 for branch 5, and -2.13 for branch 6). These values deviate significantly from the characteristic slope of -1, which is commonly associated with diffusion-controlled dendritic growth, suggesting a distinct growth mechanism of branches influenced by Au NPs.

To further confirm the influence of Au NPs, a comparative analysis was conducted on branches from the same primary branch under identical external conditions (e.g., liquid-layer thickness, electron-beam flux), with the sole variable being the presence or absence of NPs at the growth tip. The morphological evolution revealed a remarkable contrast. Without Au NPs, structures underwent tip-splitting, forming densely branched, seaweed-like patterns (Fig. 4a, b), a phenomenon consistently observed in control experiments where Au NPs were completely absent (Supplementary Note 5 and Supplementary Figs. 4–6). In contrast, the presence of Au NPs promoted directional growth toward the NPs and suppressed tip-splitting, resulting in sparsely branched patterns (Fig. 4a, b). To quantify these morphological differences, we calculated the fractal dimensions of the resulting structures. The absence of Au NPs yielded a fractal dimension of ≈ 1.6 (Supplementary Fig. 5), consistent with diffusion-limited aggregation (DLA) for two-dimensional growth34, 35, 36. By comparison, the presence of Au NPs reduced the fractal dimension to ≈ 1.4. This quantitative analysis confirms that Au NPs alter the growth kinetics of the seaweed-like nanostructures, leading to sparser branching.

As previously noted, in the absence of Au NPs, the tip radius increases continuously until it exceeds the threshold for morphological instability, after which it rapidly decreases due to tip splitting. In contrast, branches growing toward Au NPs maintain sharp tip geometries, with the tip radius generally remaining below 1.5 nm (Fig. 4c). This behavior suggests that Au NPs enhance interfacial stability in some way, thereby inhibiting tip widening and subsequent splitting.

In addition to morphological evolution, the growth dynamics were quantitatively assessed. Branches in the NP-free region display an approximately linear increase in length over time (Fig. 4d). As shown in Fig. 4e, the growth rate fluctuates within the range of 0–0.5 nm s-¹ and gradually decreases over time. This temporal evolution indicates that the interfacial growth becomes limited by mass transport. As the precursor is continuously consumed, the growth rate slows down and eventually ceases. This behavior is consistent with the characteristics of diffusion-controlled growth37.

In contrast, Au NP-guided branch growth exhibits a nonlinear increase in length, with the growth rate gradually accelerating as the growth front approaches the Au NPs. This behavior differs markedly from unguided growth and is likely driven by external forces associated with the Au NPs, which facilitate mass transport and promote directional, accelerated growth.

Methods
Liquid-cell experimental setup. The reaction solution was prepared by dissolving 0.5 mmol of iron acetylacetonate (99%) in a solvent mixture of OAm (90%), OAc (99%) and benzyl ether (95%) (volume ratio of 3:1:6 and 10 mL in total). A substantial quantity of Au NPs was then mixed into the liquid precursor. ≈ 50 nL of the final solution was loaded into a reservoir of the liquid cell, forming a ≈ 100 nm liquid layer sandwiched between two SiN membranes (20 nm thick each) at the observation window.

Liquid-cell fabrication. The liquid cell used in this study was fabricated based on SiN membranes using standard silicon microfabrication techniques (Supplementary Fig. 16). Briefly, ultrathin silicon wafers (100 μm thick, 4-inch diameter, p-type) served as substrates. A layer of SiN (≈ 15 nm) was deposited on both sides via low-pressure chemical vapor deposition (LPCVD). The cell was then constructed through sequential photolithography, wet etching to define the viewing windows and reservoirs, thermal deposition of a metallic spacer to create the cavity, and final bonding.

For liquid loading, ≈ 100 nL of the reaction solution was introduced into the reservoir via a syringe equipped with a Teflon tube. The liquid was spontaneously drawn into the viewing window by capillary force, forming a thin layer confined between the two SiN membranes. The thickness of this liquid layer, ≈ 100 nm, was precisely defined by the height of the deposited spacer. Finally, the injection port was sealed with epoxy resin, passed a vacuum leak test, and loaded into the electron microscope for observation. During TEM imaging, the electron beam traverses this thin liquid layer sandwiched within the observation window.

TEM characterization. A JEOL 3010 TEM equipped with Gatan Orius 833 camera was used in our experiment, operating at 300 kV with an electron beam current density of ~ 103–104 A m-2.

Image processing and analysis. A deep learning approach based on the UNet++ architecture was employed to extract the contours of iron oxide nanostructures. A set of 20 images acquired during the branch growth process was manually annotated to construct the training dataset. Given the limited dataset size, various data augmentation techniques, including rotation, translation, scaling, flipping and cropping, were applied to expand the dataset and enhance the model’s performance. Image alignment across successive frames was achieved using a sliding window approach. Finally, the contours were extracted to determine the position coordinates of branch tips, which were subsequently used for quantitative analysis.

Calculation of fractal dimension. The fractal dimension was analyzed via the box-counting method with an ImageJ plugin.

Statistics and Reproducibility. To ensure the reliability of our observations, all key experiments were independently repeated and carefully validated. For the tip-splitting growth behavior in the absence of Au NPs, this phenomenon was reproduced in five independent experiments. In each experiment, multiple branches were examined, and the branches consistently exhibited the two characteristic growth modes (i.e., tip-splitting or tip-widening). Representative examples are presented in the Fig. 2a, b (see Supplementary Figs. 4–6 for additional examples). For the growth with Au NPs, the experiment was repeated four times independently with similar results. In each experiment, all branches with Au NPs located near the branch tip exhibited directional growth toward the NPs, accompanied by suppression of tip-splitting. Representative examples from the total of 38 branches exhibiting this behavior are shown in Fig. 3a–c (see Supplementary Figs. 3, 9, 13, and 14 for additional examples).

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "Summary of the Work\nThis manuscript explores the controlled growth of iron oxide nanodendrites in an organic solution using charged gold\nnanoparticles (Au NPs). Using liquid cell transmission electron microscopy (LCTEM), the authors systematically examine\nthe growth behavior of nanodendrites, both in the presence and absence of Au NPs. Without Au NPs, dendrites develop into\na seaweed-like, nondirectional morphology via a sequence of tip widening followed by tip splitting. During widening, the tip\nradius increases, which subsequently decreases during the splitting phase. Notably, smaller tip radius is associated with\nfaster growth rates.\nIn contrast, when Au NPs are introduced, dendrites grow directionally toward the nanoparticles. The Au NPs serve as\nguides that promote directional growth while maintaining sharp tip geometries, typically with radius under 1.5 nm. This\nindicates that Au NPs improve interfacial stability, effectively suppressing the tip widening and splitting seen in unassisted\ngrowth. Furthermore, dendrite length increases nonlinearly under the influence of Au NPs, with growth rates accelerating as\nthe dendrite approaches the particles.\nFinite element analysis supports the hypothesis that a local electric field forms between the positively charged Au NPs and\nthe negatively charged dendrites, encouraging reactant accumulation at the dendrite tips and driving accelerated, directional\ngrowth. This work offers valuable insights into the fundamental mechanisms of nanodendritic growth shaped by localized\nelectrostatic fields and suggests that applying such fields could be a promising strategy for precise morphological control.\nThe comparative and quantitative analysis of tip radius and growth rate, along with solid theoretical analysis of the Au NP-\nguided growth process, strengthens the manuscript’s contribution.\n• What are the noteworthy results?\nThe authors investigate the controllable growth of iron oxide nanodendrites using charged Au NPs in an organic solution. A\nkey contribution of this work is the comparative analysis of dendrite morphology in the absence and presence of Au NPs.\nThe method proposed—using Au NPs to guide dendrite growth—is noteworthy because it yields directional growth while\nmaintaining sharp tip geometries. In contrast, growth without Au NPs is nondirectional and characterized by tip widening and\nsplitting. The qualitative analysis of changes in tip radius and growth rate substantiates the effectiveness of the proposed\nmethod.\n• Will the work be of significance to the field and related fields? How does it compare to the established literature?\nThe work has the potential to be significant for the field and related disciplines. However, additional experimental data are\nneeded to confirm the robustness of the findings. While it is assumed that the authors conducted repeated experiments, they\nshould provide more results to demonstrate that Au NPs consistently suppress nondirectional dendrite growth.\n• Does the work support the conclusions and claims, or is additional evidence needed?\nThe conclusions are well supported by the presented data. It is recommended that the authors highlight the novelty of their\napproach by comparing it with existing methods for dendrite control or suppression and explaining how their method could\nbe utilized in future research.\n• Are there any flaws in the data analysis, interpretation and conclusions? Do these prohibit publication or require revision?\nThe data analysis and theoretical interpretation are solid and logical. However, additional experimental validation would\nstrengthen the manuscript.\n• Is the methodology sound? Does the work meet the expected standards in your field?\nThe methodology section lacks sufficient detail, making it difficult to assess its rigor.\n• Is there enough detail provided in the methods for the work to be reproduced?\nThe authors should elaborate on how the experimental setup was configured and how the experiments were conducted to\nensure reproducibility.\nTechnical Comments\n1. In Fig. 4d, the growth length with Au NPs increases exponentially, while growth without Au NPs appears linear. There\nmay be advantages and disadvantages to excessive growth lengths. For example, if the dendrite in lithium-ion battery grows\nexponentially, a short circuit might occur.\n2. In Fig. 4a, the dendrite evolves to cover the Au NPs and continues growing. What is the long-term behavior (after 70\nseconds)? Without Au NPs, dendrite growth eventually transitions to a seaweed-like morphology. The authors should\nprovide results over longer time periods.\n3. The authors should consider how to control the positioning of Au NPs. Dendrite morphology could vary significantly\ndepending on NP positioning. The distance between Au NPs may also affect performance. For example, closely spaced Au\nNPs may lead to branched growth similar to the unassisted dendrite growth. Fig. 4a shows two branches.\n4. Electric field analysis should also be conducted with multiple Au NPs to reflect more realistic conditions.\nMinor Comments\n1. Typo: In Fig. 4(e), \"Growth Rateh\" should be corrected to \"Growth Rate.\"", "reviewer_2": "Comments to the manuscript:\nThe work studied the iron oxide growth dynamics in presence of Au NPs using the LCTEM. The found NPs promote the\noxide growth due to a local electric field generated by these particles, and changes the growth morphology from seaweed to\ndendrite. This work is interesting to the understand of the nanoscale oxide growth , but I did not found the big breakthrough\nand general advancement in the crystal growth from this work. And also it is not clear whether this change of the morphology\nwill lead to apparent change of the properties of iron oxides.\n1.In the experimental results, it is not clear which kind of iron oxide was formed, Fe2O3, FeO or Fe3O4？Is t possible to give\nthe chemical reaction equation of the solution.\n2.I agreed that the formation mechanism of seaweed of this oxide is similar to the micro-scale dendrite growth during\nsolidification of metallic alloys. The tip first flattened and then spitted. For the diffusion-controlled dendrite growth during\nsolidification, the relationship between tip growth rate(V) and radius (R) at certain undercooling or supersaturation is R^2V=\nConstant, also similar to Langer derivation(4.27) in the Ref.[15]. But here they got a logV/logR=-1.12 to illustrate that the\ngrowth is diffusion controlled seems to be not reasonable. Maybe this process is diffusion-controlled, but also please notice\nthat this is solution with chemical reaction. Convection may also help the transport of substance for growth.\n3. “In contrast, when Au NPs are in proximity, the branches exhibit directional growth toward the nanoparticles”. Here, please\nnotice that since the solid particles were randomly distributed in the solution, the growth direction is still random, but will\nchange the local growth direction and decrease the splitting frequency. Meanwhile, in the subpplementary movie or in the\nFig.1, the tip is not always grow towards to the nearest particle, this should be illustrated in detail.\n4.To comparative study the NPs effect it is strongly suggested to conduct a study without addition of particles rather than\nusing the same experiment. As can be seen in Fig.4a without Au NPs , there is still one Au NP. Its effect on growth is not\npossible to be ignored.\n5.This paragraph “As previously noted, in the absence of Au NPs, branch tips progressively widen prior to undergoing\nsplitting. During this process, the tip radius increases continuously until it exceeds the threshold for morphological instability,\nafter which it rapidly decreases due to tip splitting. In contrast, branches growing toward Au NPs maintain sharp tip\ngeometries, with the tip radius generally remaining below 1.5 nm (Fig. 4c). This behavior suggests that Au NPs enhance\ninterfacial stability in some way, thereby inhibiting tip widening and subsequent splitting.” is a repeted illustration, which can\nbe simplified.\n6.“ The corresponding growth rate fluctuates between 0 and 0.5 nm/s, with an average value of 0.15 nm/s (Fig. 4e),\nconsistent with diffusion-limited growth”Why this growth rate can be attributed to be diffusion controlled? The growth rate\ncontrolled by diffusion can varying with different applied condition, the undercooling or supersaturation. It can be very fast or\nvery slow depends on the thermal gradient of concentration gradient of the transported substance ahead of the growth front.\n7.I’m crucial that how these Au particles can be passivated and charged with a positive electrons, and these electrons can\nbe kept when they were added into the solution?\n8.Will the dendritic structure induced by the NPs lead to different properties of this iron oxide compared with that without\nNPs?", "reviewer_3": "Summary\nThis paper presents in situ transmission electron microscopy (TEM) observations of the growth of iron oxide nanowires in a\nliquid environment, where the growth is induced by precursor reduction under electron-beam irradiation. The authors\ncompare the growth process with and without Au nanoparticles. Without Au, the nanowires develop into dendritic structures\nwith tips exhibiting a relatively large curvature radius; these tips later split into new dendrites. In contrast, when Au\nnanoparticles are present, the dendrite branches are fewer and thinner. Real-time TEM shows an attraction between the\nnanoparticles and the growing oxide. The authors analyse this effect using voltammetry measurements and finite-element\nsimulations of the electric field generated by the charges. The interpretation—that charge interactions explain both the\nattraction and the reduced branching—is convincing. The experiments are carefully performed, and the manuscript is\nconcise and clear.\nMajor Comments\nIdentification of the oxide phase\nWhile the paper discusses growth physics without requiring detailed knowledge of the internal branch structure, it is\nnevertheless unsatisfactory that the exact phase of the grown material remains unidentified. Iron oxides exist in several\nstructures and compositions (hematite, magnetite, maghemite, etc.), each with distinct properties. The phase obtained under\nthe specific precursor and reduction conditions used here may not be standard.\nIf the phase is well known in the community under these experimental conditions, the authors should explicitly state this and\nprovide appropriate references.\nIdeally, the authors should provide TEM data (e.g., diffraction patterns or EDX spectra) to give direct evidence of the grown\nphase.\nDetails of the liquid cell\nThe Methods section should include more information about the liquid cell used. It appears to be of the static type: was it\ncustom-built, or commercially available? If purchased, the brand and model should be specified, together with the spatial\nresolution attainable under the reported conditions.\nMinor Comment\nIn the conclusion, it should be clarified that the finite-element simulations do not demonstrate the existence of an electric\nfield between the nanoparticle and the growing oxide. The presence of opposite charges already establishes this fact. The\nsimulation provides a quantitative evaluation of the field strength, which is an important and valuable addition."}, "author_response": "Response： We sincerely thank Reviewer #1 for the thorough and positive evaluation\nof our manuscript. The constructive questions regarding the theoretical framework and\ncontrol experimental design have prompted us to perform additional analyses, which\nhave significantly deepened the discussion and strengthened the evidence supporting\nour conclusions. We have addressed each technical comment in detail below.\nTechnical Comments\n1. In Fig. 4d, the growth length with Au NPs increases exponentially, while growth\nwithout Au NPs appears linear. There may be advantages and disadvantages to\nexcessive growth lengths. For example, if the dendrite in lithium-ion battery grows\nexponentially, a short circuit might occur.\nResponse： We thank the reviewer for their thoughtful comments. The concern about\npotential short-circuiting, as seen in lithium-ion batteries, is indeed critical. However,\nwe wish to clarify that the gold nanoparticle (Au NP)-induced exponential growth\nobserved in our system is fundamentally different and deliberately controllable.\nIn lithium-ion batteries, dendrite growth is a spontaneous and global phenomenon\ndriven by bulk ion concentration gradients and electrode overpotential, often leading to\nuncontrolled penetration. By contrast, in our experiments, accelerated growth occurs\nwhen Au NPs are present near the advancing dendrite tip. This behavior is governed by\nlocalized electric fields generated by the ligands on the Au NP surface. In regions\nwithout Au NPs nearby, growth reverts to a linear, diffusion-limited mode,\ndemonstrating that the process is locally controllable.\nWe appreciate the reviewer’s perspective on weighing the advantages and\ndisadvantages. Our work primarily demonstrates a method for achieving controlled\nnanomaterial synthesis by introducing local electric fields generated by metallic NPs.\nA key advantage of this strategy is the ability to precisely regulate dendritic growth\npathways and morphologies via such localized fields. Specifically, the surface ligands\non the Au NPs create confined electric field distributions that direct the orientation and\nmorphological evolution of the growing dendrites. This results in directional growth\nfeatures that enhance the specific surface area of the structures, offering potential\nbenefits for sensing-related applications. Furthermore, such branch-limited and aligned\ndendritic architectures facilitate mass transport more effectively than highly branched,\nrandomly oriented morphologies.\n2. In Fig. 4a, the dendrite evolves to cover the Au NPs and continues growing. What is\nthe long-term behavior (after 70 seconds)? Without Au NPs, dendrite growth eventually\ntransitions to a seaweed-like morphology. The authors should provide results over\nlonger time periods.\nResponse: We thank the reviewer for this suggestion regarding long-term growth\nbehavior. We have provided additional videos and images acquired over long-time\nscales, enabling a more detailed analysis and discussion of the dendritic growth kinetics.\nAs shown in Figs. R1a, b and R2a, when Au NPs are present, the dendrites maintain\nsustained directional growth guided by the spatial distribution of NPs. For instance,\nafter a branch passes over one NP (e.g., NP A in Fig. R2a), its growth direction reorients\ntoward an adjacent particle (NP B). Contour analyses (Figs. R1c, d) further confirm that\nthe growth trajectory closely follows the arrangement of Au NPs.\nIn contrast, when there are no other Au NPs in the front of the branch’s tips, as shown\nin Fig. R2b, the tips undergo frequent splitting events over time, generating multiple\nsecondary branches. Under conditions of relatively low precursor concentration, this\nunguided growth is also associated with tip widening, consistent with observations in\nthe main text (Fig. 2a).\nLonger-time videos and images have been included in the Supplementary Materials\n(Supplementary Movie 2, Supplementary Fig. S3 and Supplementary Note2), and the\ncorresponding descriptions have been added to the main text (Page 4, Line 96-104).\nFig. R1. Directed growth of iron oxide dendrites with the presence of Au NPs. a\nImage sequence over 120 s extracted from Supplementary Video S1, showing the\ndirectional growth of iron oxide dendrite toward an Au NP. b Image sequence over 140\ns extracted from Supplementary Video S2, showing directional growth of another iron\noxide dendrite toward an Au NP over 140 s. c Corresponding contour outline of the iron\noxide dendrite shown in a. d Corresponding contour outline of the iron oxide dendrite\nshown in b.\nFig. R2. Local dendritic growth behaviors with and without Au NPs. a Directional\ngrowth of a branch toward an Au NP and the corresponding contour map, illustrating\npersistent guidance by NPs ahead of the advancing tip even at later stages. b The\nformation of multiple branches in the absence of Au NPs, along with the corresponding\ncontour map.\n3. The authors should consider how to control the positioning of Au NPs. Dendrite\nmorphology could vary significantly depending on NP positioning. The distance\nbetween Au NPs may also affect performance. For example, closely spaced Au NPs\nmay lead to branched growth similar to the unassisted dendrite growth. Fig. 4a shows\ntwo branches.\nResponse: We thank the reviewer for this insightful comment regarding the critical role\nof Au NP positioning. We fully agree that the spatial distribution and inter-particle\ndistance of Au NPs are key factors determining dendritic morphology. Our\nexperimental results demonstrate that the dendritic growth path can be effectively\n“programmed” by the arrangement of Au NPs.\nFig. R3. Effect of Au NP number and position on dendritic growth. a One Au NP\nposition in the direction of branch growth, and no branch growth occurs. b One Au NP\nposition at the side of the branch induces the formation of a single branch. c. Two Au\nNPs in front of the dendrite induce the formation of two branches.\nAs shown in Fig. R3, we observed branch growth under different NP configurations.\nWhen a single NP is present at the growth front, the dendrite extends directionally\ntoward it without forming additional branches (Fig. R3a). In contrast, when two or more\nNPs are present along the path, corresponding branches emerge (Figs. R3b, c). This\nconfirms a direct correlation between NP distribution and branch morphology,\nhighlighting the potential for morphological control by designing NP layouts.\nTo quantitatively assess the effect of NP density, we calculated the fractal dimensions\nof dendrites formed with different NP densities (Fig. R4). The fractal dimensions for\ndendrites with 22 and 31 NPs in a 175 nm × 175 nm region were 1.41 and 1.47,\nrespectively. This modest increase indicates that higher NP density promotes local\nbranching, as the reviewer suggested. However, the relatively low fractal dimensions\nconfirm that the overall dendritic structure remains distinctly different from the highly\nbranched morphology observed in the absence of NPs. Therefore, even with closely\nspaced NPs, the growth is still guided and constrained by the NPs, rather than becoming\nentirely random.\nFig. R4. Effect of Au NP density on dendrite morphology and fractal dimension. a\nDendrites exhibit a fractal dimension of 1.41 when 22 Au NPs are present within an\narea of 175 nm × 175 nm. b Dendrites exhibit a higher fractal dimension of 1.47 when\nIn summary, our work establishes that controlling Au NP spatial distribution is a\npowerful strategy for directing dendritic growth. Guided by this principle, future studies\ncould explore several potential approaches to achieve such spatial control in liquid-cell\ntransmission electron microscopy LCTEM. For instance, pre‑treating silicon nitride\nsubstrates to create charged regions may enable the immobilization of\nligand‑functionalized NPs via electrostatic interactions1. Additionally, focused electron\nbeams can be used to induce in-situ fixation of NPs at predetermined positions. And the\ncombination with automated control or algorithmic optimization, may enable precise\narrayed arrangement of NPs2.\nCorresponding figures and descriptions have been added to the main text (Fig.3c and\nPage 7, line 154-158) and Supplementary Information (Page 9, line 159, Supplementary\nNote 4 and Supplementary Fig. S9).\n4. Electric field analysis should also be conducted with multiple Au NPs to reflect more\nrealistic conditions.\nResponse: We thank the reviewer for this valuable suggestion. To address it, we\nperformed additional simulations to investigate the electric field distribution in the\npresence of multiple Au NPs.\nFirst, we compared systems with one, two, and three NPs ahead of the branch tip (Fig.\nR5). The results show that the overall electric field distribution is not substantially\naltered by increasing the number of NPs, confirming that the key features captured by\nthe single‑NP model remain valid.\nFig. R5. The distribution of the local electric field when there are different\nnumbers of Au NPs in front of the dendrite tip. The addition of the particles did\nnot weaken the electric field between the branch tips and the particles.\nThen, two NPs (NPs) were placed on both sides of the dendrite tip, as shown in Fig.\nR6a. Under this configuration, local electric field regions form between the dendrite tip\nand each Au NP respectively. This simulation result is consistent with the experimental\nobservations in Fig. R6b, where two branches emerge from the dendrite tip and extend\ntoward the respective Au NPs.\nFig. R6. This simulated the local electric field distribution caused by NPs\ndistributed on both sides of the dendritic branch. a Local electric field distribution\nwhen two NPs are positioned in front of the branch tip. b Corresponding TEM image\nshowing a representative growth process with a configuration analogous to the\nsimulation.\nFurthermore, an additional simulation was performed in which one NP was positioned\ndirectly in front of the dendrite tip (Fig. R7, denoted as NP A), while another NP was\npositioned laterally to the side of the tip (denoted as NP B). When the distance between\nthe two NPs and the dendrite tip was identical ( 𝐷 = 𝐷 ), quantitative analysis reveals\n𝐴 𝐵\nthat NP A produces a stronger enhancement of the local electric field (1.3×107 mV/nm)\nat the tip than NP B (9.8×106 mV/nm). Even when the distance between NP A and the\ndendrite tip is slightly larger than that between NP B and the tip (Fig. R7b), the local\nelectric field induced by NP A (1.27×107 mV/nm) at the dendrite front remains stronger\nthan that induced by NP B at the lateral side (9.1×106 mV/nm).\nFig. R7. Simulated electric field distribution around a dendritic tip with multiple\nAu NPs. a Field distribution when the distances from the tip to the front NP (NP A, D )\nA\nand the lateral NP (NP B, D ) are equal (D = D ). b Field distribution when D > D .\nB A B A B\nc Corresponding TEM image showing dendritic growth under a configuration similar\nto the simulation. The simulations demonstrate that the tip preferentially grows toward\nthe NP inducing the strongest local field, which is determined by the combined effect\nof NP position and tip curvature.\nThis difference primarily originates from the higher curvature at the front of the\ndendrite tip, which leads to more pronounced charge accumulation and consequently a\nstronger local electric field. These simulation results are in great agreement with the\nexperimental observations (Fig. R7c). Owing to the stronger local electric field at the\nfront, the dendrite branch preferentially grows toward the Au NP located directly ahead\nof the tip. Therefore, the branch does not always grow preferentially toward the nearest\nNP. When the curvature radius of the branch tip becomes small, the localized electric\nfield at the tip is significantly enhanced, causing NPs located directly ahead of the tip\nto contribute more strongly to the local field and thereby dominate the growth direction.\nIn summary, as the reviewer insightfully suggested, we have performed additional\nfinite-element simulations under multi-particle configurations. These new simulations\nconfirm that, even in the presence of multiple, competing NPs, the ultimate growth\ndirection is still governed by the maximum local electric field intensity at the dendrite\ntip, which is co-determined by the tip curvature and the relative spatial positioning of\nthe NPs. This finding robustly validates our proposed core mechanism that the NP-\nguided directional growth is driven by localized electric field enhancement.\nThe multi-particle simulation results mentioned above have been added to the main text\n(Page 12, line 263) and Supplementary Information (Page 11, line 199, Supplementary\nNote 6 and Supplementary Fig. S12-S14) to describe the influence of particle spatial\ndistribution on branching growth behavior. The relevant changes have been marked in\nred.\nMinor Comments\n1. Typo: In Fig. 4(e), “Growth Rateh” should be corrected to “Growth Rate.”\nResponse: We sincerely thank the reviewer for the careful reading and for pointing out\nthis typographical error. The label in Fig. 4(e) has been corrected from “Growth Rateh”\nto “Growth Rate” in the revised manuscript.\nReviewer #2\nComments to the manuscript:\nThe work studied the iron oxide growth dynamics in presence of Au NPs using the\nLCTEM. The found NPs promote the oxide growth due to a local electric field\ngenerated by these particles, and changes the growth morphology from seaweed to\ndendrite. This work is interesting to the understand of the nanoscale oxide growth, but\nI did not found the big break through and general advancement in the crystal growth\nfrom this work. And also it is not clear whether this change of the morphology will lead\nto apparent change of the properties of iron oxides.\nResponse: We sincerely thank Reviewer #2 for the thorough review and for the positive\ncomment on the interest of our work. These comments have been invaluable in helping\nus significantly improve the manuscript. To address all points raised, we have\nperformed extensive revisions, including additional material characterizations, finite-\nelement simulations, new control experiments, and quantitative analyses. These efforts\nhave substantially deepened the study and clarified our conclusions. Besides, we wish\nto emphasize that the key contribution of our work is the demonstration that a local\nelectric field, generated by charged nanoparticles, can act as a dominant factor to\nprecisely guide the growth at the nanoscale. This effect offers a novel strategy for\nmorphology control that advances our understanding of nanoscale crystal growth.\nWhile a full property characterization is beyond the scope of this growth mechanism\nstudy, we have strengthened the discussion to explicitly link the Au NP-induced\nmorphological changes (e.g., reduced fractal dimension, maintained sharp tips) to key\nstructural parameters that are well-established determinants of functional properties,\nthereby highlighting the potential for tailoring material properties through the growth\npathway we report.\nOur detailed point-by-point responses are provided below.\n1. In the experimental results, it is not clear which kind of iron oxide was formed, Fe O ,\n2 3\nFeO or Fe O ? Is it possible to give the chemical reaction equation of the solution.\n3 4\nResponse: Thank you for your suggestions. The precursor composition and solution\nratio were adapted from established thermal synthesis routes for magnetite (Fe₃O₄)3, 4.\nFor the obtained Fe₃O₄, the chemical reaction process can be represented by the\nfollowing equation:\n𝑂𝐴𝑚+𝑂𝐴𝑐\n𝐹𝑒𝐼𝐼𝐼+𝑒− → 𝐹𝑒 𝑂\n3 4\nThe formation of Fe₃O₄ in our system proceeds via a similar pathway to these thermal\nsynthesis routes. Briefly, the precursor Fe(acac)₃ undergoes ligand exchange with oleic\nacid and oleylamine to form an intermediate iron oleate complex. Under the conditions\nof in situ TEM, the electron beam provides both the energy and the reducing\nenvironment (supplying electrons) necessary for the decomposition of this complex,\nleading to the nucleation and growth of Fe₃O₄.\nIn the main text, we refer to the resulting product broadly as “iron oxide” because the\nsolid formed in solution may not be phase-pure and could contain minor intermediate\nor by-product phases. Nevertheless, the predominant phase is expected to be Fe₃O₄. It\nshould be emphasized that the exact crystal phase does not influence the analysis of\ngrowth dynamics presented in this study, as the focus is on the morphological evolution\nprocess. Furthermore, the directed dendritic growth mechanism explored here is driven\nby the negatively charged iron oxide surface, which results from its interaction with\noleic acid carboxyl groups and is independent of the specific iron oxide phase.\nTo further address the phase composition, we performed additional characterizations.\nHigh-resolution TEM images of the in situ product were obtained, and the\ncorresponding Fast Fourier Transform (FFT) patterns and measured lattice spacings are\nconsistent with those of Fe₃O₄5, 6 (Fig. R6a). Additionally, ex situ X-ray photoelectron\nspectroscopy (XPS) was conducted on products synthesized by heating under identical\nchemical conditions (Fig. R6b). Quantitative analysis reveals a Fe³⁺ to Fe²⁺ ratio of\napproximately 1.88:1, which is close to the stoichiometric ratio of Fe₃O₄ (2:1).\nTherefore, while trace amounts of other iron oxides might be present, Fe₃O₄ is\nconfirmed as the dominant phase.\nDescriptions related to the iron oxide phases and chemical reactions have been added\nto the Supplementary Information (Supplementary Note 1, Page 3, line 59).\nCorresponding figures have been included in the Supplementary Information (Page 3,\nSupplementary Fig. S1-S2).\nFig. R6. Analysis of nanodendrite material phases. a High-resolution TEM images\nof Au NP-induced nanodendrite and its corresponding FFT patterns. The measured\nlattice spacing of ~0.298 nm can be indexed to the {220} family of planes of magnetite\n(Fe₃O₄). b Fe 2p XPS spectra of experimental products.\n2. I agreed that the formation mechanism of seaweed of this oxide is similar to the\nmicro-scale dendrite growth during solidification of metallic alloys. The tip first\nflattened and then spitted. For the diffusion-controlled dendrite growth during\nsolidification, the relationship between tip growth rate(V) and radius (R) at certain\nundercooling or supersaturation is R2V= Constant, also similar to Langer derivation\n(4.27) in the Ref.[15]. But here they got a logV/logR=-1.12 to illustrate that the\ngrowth is diffusion controlled seems to be not reasonable. Maybe this process is diffusion-\ncontrolled, but also please notice that this is solution with chemical reaction.\nConvection may also help the transport of substance for growth.\nResponse: Thank you for this insightful comment. The classical Langer theory (R²V =\nconstant), which describes diffusion-controlled dendritic growth in three-dimensional,\nbulk systems. However, our experiments are conducted within a quasi-two-dimensional,\nspatially confined liquid cell. In such a thin-layer environment, the diffusion field and\ngrowth dynamics differ substantially, making the classical bulk theory not directly\napplicable7. Instead, for dendritic growth in confined liquid-phase systems, the Ivantsov\nmodel has been widely adopted as a more suitable theoretical framework for identifying\ndiffusion-dominated steady-state growth, as supported by prior LCTEM studies8, 9, 10.\nWithin this context, our experimental data show a clear linear relationship between\nlog(V) and log(R) with a slope of approximately -1.12. This scaling is consistent with\nthe behavior expected for diffusion-controlled growth under our confined conditions\nper the Ivantsov-type analysis, thereby supporting our conclusion.\nRegarding the potential influences of chemical reaction and convection, we argue that\nneither is rate-limiting in our confined system. The precipitation reaction at the growing\ninterface is sufficiently fast compared to mass transport. Furthermore, convective flow\nis strongly suppressed by the extreme spatial confinement of the liquid cell, which\nensures that diffusion remains the dominant mass-transport mechanism. Any residual\nflow would primarily assist in solute delivery to the growth front without altering the\nfundamental diffusion-controlled growth kinetics.\n3. “In contrast, when Au NPs are in proximity, the branches exhibit directional growth\ntoward the nanoparticles.”. Here, please notice that since the solid particles were\nrandomly distributed in the solution, the growth direction is still random, but will\nchange the local growth direction and decrease the splitting frequency. Meanwhile, in\nthe supplementary movie or in the Fig.1, the tip is not always grow towards to the\nnearest particle, this should be illustrated in detail.\nResponse：We thank the reviewer for this insightful comment regarding the precise\ndescription of directional growth. The original phrasing “In contrast, the branches\nexhibit directional growth toward the nanoparticles” was not intend to imply a\ndeterministic or global alignment of nanodendrite growth toward the Au NPs. Instead,\nwe intended to convey that, in the presence of Au NPs within the vicinity of the\nadvancing branch tip, the dendritic tip can undergo a local deflection and preferentially\ngrow toward the particle position. Such NP-induced directional growth is inherently a\nlocal effect, arising from the introduction of a local electric field that modifies the\ngrowth direction on a local scale. This sentence has been revised in the main text to “In\ncontrast, when Au NPs are present in the vicinity of the branch tip, the dendrite tip\nundergoes a local deflection and exhibits a growth tendency toward the direction where\nthe NPs are located”.\nAs the reviewer pointed out, in our experiment the dendrite did not always grow toward\nthe nearest particle (NP B). Instead, it grew toward NP A, which was slightly farther\nahead but directly in front of the tip (Fig. R7a). To clarify the underlying mechanism of\nthis phenomenon, we performed additional finite-element simulations based on the\nbranch geometry according to the experiment results (Fig. R7b). NP A is positioned\ndirectly in front of the dendritic tip at a high-curvature region, while the other NP B is\nlocated laterally with respect to the tip. Although the distance between NP A and the\nbranch tip (17.5 nm) is slightly larger than that between NP B and the tip (16.7 nm),\nthe contribution of NP A to the local electric field (1.1 × 10⁷ mV nm⁻¹) remains appreciably\nhigher than that of NP B (9.1 × 106 mV nm⁻¹). As a consequence, the dendritic branch\nexhibits a preferential tendency to propagate toward the Au NP positioned directly\nahead of the tip during the subsequent growth process. Furthermore, as the tip-particle\ndistance decreases, this field becomes increasingly dominant.\nFig. R7. Analysis of the influence factors of nanodendrite branch growth direction.\na Experimental TEM image showing a branch growing toward a more distant NP (NP\nA) instead of the closer lateral NP (NP B). b Corresponding simulation of the local\nelectric field distribution, revealing a stronger field at the tip front induced by NP A. c\nStatistical relationship confirming that the local electric field intensity increases as the\ntip curvature radius decreases. Together, these results demonstrate that the growth\ndirection is governed by the maximum local electric field, which is co-determined by\nthe tip curvature and NP position.\nThese results provide an explanation for the behavior observed during the actual growth\nprocess, in which the dendrite does not preferentially grow toward the nearest particle.\nIt can be attributed to the pronounced influence of tip curvature on the local electric\nfield distribution. Owing to the high curvature at the dendrite tip, electric charges tend\nto accumulate in this region, leading to the formation of a locally intensified electric\nfield in front of the tip. To further elucidate the relationship between curvature and\nelectric field strength, we systematically varied the curvature radius of the branch tip\nand measured the corresponding maximum local electric field (Fig. R7c). The results\nreveal an inverse relationship between the maximum local electric field intensity and\nthe tip curvature radius. A smaller curvature radius, meaning a sharper tip, leads to a\nmore pronounced enhancement of the local electric field. This finding strongly supports\nour previous conclusion that dendritic tips preferentially grow towards particles located\ndirectly in front of them.\nIn summary, the growth direction of the dendritic tip is not determined solely by its\ndistance from the Au NPs. Both the curvature characteristics of the branch tip and the\nspatial distribution of the Au NPs play critical roles in modulating the local growth\nbehavior.\nThe above discussions and figures have been added to the main text (Page 6, line 143\nand Page 12, line 267) and Supplementary Information (Page 11, line 199,\nSupplementary Note 6 and Supplementary Fig. S14). The relevant changes have been\nmarked in red.\n4. To comparative study the NPs effect it is strongly suggested to conduct a study\nwithout addition of particles rather than using the same experiment. As can be seen in\nFig.4a without Au NPs, there is still one Au NP. Its effect on growth is not possible to\nbe ignored.\nResponse: Thank you for your suggestions. We have conducted additional control\nexperiments to systematically study dendrite growth in the complete absence of Au NPs,\nas shown in Fig. R8. These new data clearly show that without Au NPs near the\nnanodendrite, the nanodendrites develop a densely branched, seaweed-like morphology\nwith no preferred growth direction, expanding in multiple directions simultaneously.\nThis pattern is distinctly different from the directed growth observed when Au NPs are\npresent.\nFig. R8 Dendritic growth in the complete absence of Au NPs. TEM image showing\nthe formation of a densely branched, seaweed-like morphology when no Au NPs\nare present (electron beam dose rate: 904 e⁻/Å²·s).\nIn addition, we systematically investigated dendritic growth in the absence of Au NPs\nunder different electron beam dose rates (Fig. R9a). The results show that as the dose\nrate increases, the dendrite branches become progressively wider. Meanwhile, the\nspacing between adjacent branches decreases, leading to a denser branching\nmorphology. The dose rate was identified as a critical parameter, as it facilitates the\nprecursor reduction and enables modulation of the iron oxide formation rate.\nTo quantify the morphological differences, we introduced dendrite density, defined as\nthe area fraction occupied by dendritic branches within a circular region of a given\ndiameter (30 nm) centered at the growing tip. This density was measured at multiple\nlocations and averaged to minimize statistical error. Quantitative analysis reveals that\ndendrites formed under higher electron-beam dose rates exhibit a significantly greater\ndendrite density. The respective area fractions under the three tested conditions (from\nleft to right in Fig. S6b) are 36%, 46%, and 51%. This trend is attributed to the enhanced\nprecursor reduction probability at higher dose rates, which increases the production rate\nof iron oxide.\nFig. R9 Comparison of dendritic growth morphologies in the absence of Au NPs\nat different electron beam dose rates. a TEM images showing highly-branched\ndendrite morphologies at varying electron beam dose rates. b Contours of the dendrites.\nThe blue dashed circles indicate the regions used to calculate the local branch density.\nRegarding the specific image in Fig. 4a of the main text, its purpose was to provide a\ntightly controlled dynamic comparison. The branch shown originates from the same\nprimary dendrite and experiences identical external conditions (e.g., liquid-layer\nthickness, electron-beam flux) as the NP-guided branch, with the presence or absence\nof NPs at the growing front being the sole variable. Our analysis indicates that the single\nNP visible in this field influences the dendrite’s path only as the tip approaches and\npasses over it. Once the dendrite grows beyond this particle, its subsequent evolution is\nno longer guided by the NP and reverts to a random branching mode, consistent with\nthe morphology observed in our new NP-free controls (Fig. R8).\nIn summary, the new data fully address the growth behavior of the iron oxide dendrites\nin a NP-free environment. The comparison in Fig. 4a remains valid for illustrating the\nunderlying growth mechanism by contrasting conditions with and without NPs at the\nbranch front, under otherwise identical experimental conditions.\nCorresponding figures have been added to the Supplementary Information (Page 5,\nSupplementary Fig. S4 and S6). Related content has been included in the main text\n(Page 8, line 172) and Supplementary Information (Page 5, line 103, Supplementary\nNote 3).\n5. This paragraph “As previously noted, in the absence of Au NPs, branch tips\nprogressively widen prior to undergoing splitting. During this process, the tip radius\nincreases continuously until it exceeds the threshold for morphological instability, after\nwhich it rapidly decreases due to tip splitting. In contrast, branches growing toward Au\nNPs maintain sharp tip geometries, with the tip radius generally remaining below 1.5\nnm (Fig. 4c). This behavior suggests that Au NPs enhance interfacial stability in some\nway, thereby inhibiting tip widening and subsequent splitting.” is a repeted illustration,\nwhich can be simplified.\nResponse: Thank you for this suggestion. The original phrasing in the manuscript has\nbeen revised to: “As previously noted, in the absence of Au NPs, the tip radius increases\ncontinuously until it exceeds the threshold for morphological instability, after which it\nrapidly decreases due to tip splitting. In contrast, branches growing toward Au NPs\nmaintain sharp tip geometries, with the tip radius generally remaining below 1.5 nm\n(Fig. 4c). This behavior suggests that Au NPs enhance interfacial stability in some way,\nthereby inhibiting tip widening and subsequent splitting.”\nThe changes have been highlighted in the revised manuscript (Line 193, Page 9).\n6. “The corresponding growth rate fluctuates between 0 and 0.5 nm/s, with an average\nvalue of 0.15 nm/s (Fig. 4e), consistent with diffusion-limited growth” Why this growth\nrate can be attributed to be diffusion controlled? The growth rate controlled by diffusion\ncan varying with different applied condition, the undercooling or supersaturation. It can\nbe very fast or very slow depends on the thermal gradient of concentration gradient of\nthe transported substance ahead of the growth front.\nResponse: Thank you for this insightful comment. We agree that the absolute growth\nrate alone is not a definitive indicator, as diffusion-limited kinetics can indeed yield a\nwide range of rates depending on the specific supersaturation and transport gradients.\nOur attribution to diffusion-limited growth is based primarily on the temporal\ncharacteristics of the kinetics, specifically the observable fluctuations in growth rate\nbetween 0 and 0.5 nm/s around the mean value. This type of instability is characteristic\nof diffusion-limited processes, where growth is sensitive to the continuous depletion\nand stochastic replenishment of the local concentration field at the advancing tip11,12.In\ncontrast, interface or reaction-controlled growth under similar conditions typically\nexhibits a more stable and regular rate.\nTherefore, it is this fluctuating behavior, rather than the specific average rate of 0.15\nnm/s, that we consider consistent with a diffusion-limited regime in our experimental\ncontext. To further substantiate the role of Au NPs, the main text provides a direct\ncomparison of growth kinetics under nearly identical conditions with and without NPs,\nas shown in Fig. 4a, which we believe offers more compelling evidence.\nThe relevant changes have been added to the main text (Page 9, line 201) and\nhighlighted in red.\n7. I’m crucial that how these Au particles can be passivated and charged with a positive\nelectrons, and these electrons can be kept when they were added into the solution?\nResponse: Thank you for this question regarding the surface passivation mechanism\nand the origin of the positive charge on our Au NPs, as well as their stability in solution.\nThe Au NPs used in our experiments were synthesized by dissolving HAuCl₄·3H₂O in\na mixture of oleylamine and tetralin, followed by reduction with tert-butylamine borane\n(TBAB) under a N₂ atmosphere. After the reaction, the resulting Au NPs were isolated\nby adding acetone and centrifugation, then redispersed in a nonpolar organic solvent\n(such as toluene or hexane). Finally, the NPs were introduced into a solution containing\noleic acid, oleylamine, and diphenyl ether.\nDuring the synthesis process, oleylamine functions as both a capping ligand and a mild\nreducing agent, leading to the formation of oleylamine-terminated Au NPs that are\nuniformly dispersed in the solution. In the solution phase, oleylamine can chemically\nadsorb onto the Au surface in the form of ammonium-like ligands, which may become\nprotonated (–NH₃⁺) or form positively charged ligand–Au electrostatic complexes. The\ncorresponding reaction process is illustrated in Fig. R10. Consequently, the resulting\nNPs exhibit a positive potential. Numerous studies have reported that ammonium\nspecies can shift the surface charge of Au NPs toward a positive (or weakly positive)\nstate. Furthermore, redispersing the passivated Au NPs in nonpolar solvents helps\nmaintain the integrity of the ligand shell, because the hydrophobic tails of the ligands\nare compatible with nonpolar media, and the ligand layer is not disrupted by polar\nsolvents (such as water) or ions. The TEM images show well-dispersed Au NPs,\nindicating effective surface ligand coverage (Fig. R11a). Consistently, the\ncorresponding ζ-potential measurements demonstrate that the Au NPs retain a positive\ncharge when dispersed in solution (Fig. R11b).\nFig. R10 Schematic diagram illustrating the mechanism by which Au NPs acquire\npositive charges on their surface. The oleylamine ligands on the surface of the Au\nNPs tend to undergo protonation, transforming into ammonium cations.\nFig. R11 Surface state analysis of Au NPs. a Ligand-capped Au NPs exhibit good\ndispersion in solution. b Measurement of the zeta potential of the Au NP surface. ζ-\npotential measurements indicate that the as-synthesized Au NPs retain a positive\nsurface charge even after precipitation, washing, and redispersion.\n8. Will the dendritic structure induced by the NPs lead to different properties of this\niron oxide compared with that without NPs?\nResponse: Thank you for this insightful question. We agree that the NP-directed\ndendritic structures are likely to exhibit significantly different properties, while a full\ncharacterization of the property differences is beyond the scope of the present study,\nwhich focuses on the growth mechanism.\nOur results demonstrate that Au NPs guide dendrite formation. This leads to distinct\nmorphological outcomes such as reduced tip splitting, altered branch density, and\nmodified fractal dimensions, in contrast to the randomly branched structures formed\nwithout NPs. These structural parameters are known to critically influence material\nproperties. Specifically, parameters such as the specific surface area, fractal dimension,\ntip curvature radius and porosity are significantly affected by changes in branching\nmorphology. These parameters are key factors governing diffusion behavior, interfacial\nreaction rates and catalytic activity. Previous studies have demonstrated that dendritic\niron oxides can exhibit excellent performance in electromagnetic properties (e.g.,\nmicrowave absorption), electrochemical behavior (e.g., specific capacity and cycling\nstability in lithium-ion batteries) and photocatalytic efficiency. These performances can\nalso be modulated by adjusting structural parameters13, 14, 15, 16. For example, a larger\nspecific surface area provides more active sites, enhancing electrode reaction rates and\nstability, while more branched and open dendritic structures facilitate the transport of\nions and molecules.\nTherefore, the growth pathway we report directly determines the key structural features\nthat govern subsequent functionality. We believe this work establishes a foundational\nunderstanding for future targeted investigations into the properties of these novel\nnanostructures.\nWe have added the relevant content to the main text (Page 13, line 295).\nReviewer #3\nSummary\nThis paper presents in situ transmission electron microscopy (TEM) observations of the\ngrowth of iron oxide nanowires in a liquid environment, where the growth is induced\nby precursor reduction under electron-beam irradiation. The authors compare the\ngrowth process with and without Au nanoparticles. Without Au, the nanowires develop\ninto dendritic structures with tips exhibiting a relatively large curvature radius; these\ntips later split into new dendrites. In contrast, when Au nanoparticles are present, the\ndendrite branches are fewer and thinner. Real-time TEM shows an attraction between\nthe nanoparticles and the growing oxide. The authors analyse this effect using\nvoltammetry measurements and finite-element simulations of the electric field\ngenerated by the charges. The interpretation-that charge interactions explain both the\nattraction and the reduced branching-is convincing. The experiments are carefully\nperformed, and the manuscript is concise and clear.\nResponse：We sincerely thank Reviewer #3 for the positive assessment of our\nmanuscript as \"concise and clear\" and for the convincing interpretation of our proposed\nmechanism. The technical suggestions regarding material phase identification and\nliquid cell specifications have been fully addressed with additional characterizations\nand detailed methodological descriptions, further enhancing the robustness and\nreproducibility of our study. We have responded to each point below.\nMajor Comments\n1. Identification of the oxide phase.\nWhile the paper discusses growth physics without requiring detailed knowledge of the\ninternal branch structure, it is nevertheless unsatisfactory that the exact phase of the\ngrown material remains unidentified. Iron oxides exist in several structures and\ncompositions (hematite, magnetite, maghemite, etc.), each with distinct properties. The\nphase obtained under the specific precursor and reduction conditions used here may not\nbe standard.\nIf the phase is well known in the community under these experimental conditions, the\nauthors should explicitly state this and provide appropriate references.\nIdeally, the authors should provide TEM data (e.g., diffraction patterns or EDX spectra)\nto give direct evidence of the grown phase.\nResponse：Thank you for your suggestions. The precursor composition and solution\nratio were adapted from established thermal synthesis routes for magnetite (Fe₃O₄)3, 4.\nFor the obtained Fe₃O₄, the chemical reaction process can be represented by the\nfollowing equation:\n𝑂𝐴𝑚+𝑂𝐴𝑐\n𝐹𝑒𝐼𝐼𝐼+𝑒− → 𝐹𝑒 𝑂\n3 4\nThe formation of Fe₃O₄ in our system follows a pathway analogous to those reported\nfor thermal synthesis routes. Briefly, the precursor Fe(acac)₃ first undergoes ligand\nexchange with oleic acid and oleylamine, forming an intermediate iron oleate complex.\nIn the TEM conditions, the electron beam supplies both the energy and a reducing\nenvironment through electron injection, thereby inducing the decomposition of this\ncomplex and ultimately leading to the nucleation and growth of Fe₃O₄.\nIn the main text, we refer to the resulting product broadly as “iron oxide” because the\nsolid formed in solution may not be phase-pure and could contain minor intermediate\nor by-product phases. Nevertheless, the predominant phase is expected to be Fe₃O₄. It\nshould be emphasized that the exact crystal phase does not influence the analysis of\ngrowth dynamics presented in this study, as the focus is on the morphological evolution\nprocess. Furthermore, the directed dendritic growth mechanism explored here is driven\nby the negatively charged iron oxide surface, which results from its interaction with\noleic acid carboxyl groups and is independent of the specific iron oxide phase.\nTo further address the phase composition, we performed additional characterizations.\nHigh-resolution TEM images of the in situ product were obtained, and the\ncorresponding FFT patterns and measured lattice spacings are consistent with those of\nFe₃O₄5, 6 (Fig. R6a). Additionally, ex situ XPS was conducted on products synthesized\nby heating under identical chemical conditions (Fig. R6b). Quantitative analysis reveals\na Fe³⁺ to Fe²⁺ ratio of approximately 1.88:1, which is close to the stoichiometric ratio\nof Fe₃O₄ (2:1). Therefore, while trace amounts of other iron oxides might be present,\nFe₃O₄ is confirmed as the dominant phase.\nDescriptions related to the iron oxide phases and chemical reactions have been added\nto the Supplementary Information (Supplementary Note 1, Page 3, line 59).\nCorresponding figures have been included in the Supplementary Information (Page 3,\nSupplementary Fig. S1-S2).\nFig. R12 Analysis of nanodendrite material phases. a High-resolution TEM image\nof the nanodendrite in the presence of Au NPs and its FFT image. b Fe 2p XPS spectra\nof experimental products.\n2. Details of the liquid cell.\nThe Methods section should include more information about the liquid cell used. It\nappears to be of the static type: was it custom-built, or commercially available? If\npurchased, the brand and model should be specified, together with the spatial\nresolution attainable under the reported conditions.\nResponse：Thank you for your suggestion. The liquid cell used in our experiments\nwas fabricated using silicon nitride (SiNₓ) membranes fabricated through standard\nsilicon microfabrication techniques. As shown in Fig. R13, ultrathin silicon wafers (100\nµm, 4-inch, p-doped) were used as the substrates. A layer of SiNₓ (~15 nm) was\ndeposited on both sides of the wafers via low-pressure chemical vapor deposition\n(LPCVD). The liquid cell was then fabricated through successive steps of\nphotolithography, wet etching, thermal deposition, and assembly. Liquid loading was\nperformed using a syringe equipped with a small Teflon tube to control droplet size.\nApproximately 100 nL of liquid was introduced from the liquid injection port into the\nliquid chamber through a reservoir, forming a thin liquid layer sandwiched between the\ntwo SiN membranes at the observation window. The thickness of the liquid layer was\nx\ndefined by spacer height, reaching ~100 nm. The liquid chamber was subsequently\nsealed with epoxy resin and loaded into the electron microscope for observation. During\nimaging, the electron beam passes through the thin liquid layer confined between the\ntwo SiN membranes of the observation window. The electron dose rate was maintained\nx\naround 103~104 A/m2·s to enable both imaging and initiation of the reaction.\nThe above content has been added to the “Methods” section in the main text (Page 13,\nline 307) and highlighted in red. The Image of the liquid cell set up has been included\nin the Supplementary Information (Page 15, Supplementary Fig. S16).\nFig. R13 Schematic diagram of the liquid cell chip structure. A liquid cell employs\nultrathin silicon nitride membranes with a thickness of only 15 nm, while the\nupper and lower chips are bonded using an In pad to form a liquid cell.\nMinor Comment\nIn the conclusion, it should be clarified that the finite-element simulations do not\ndemonstrate the existence of an electric field between the nanoparticle and the growing\noxide. The presence of opposite charges already establishes this fact. The\nsimulation provides a quantitative evaluation of the field strength, which is an important\nand valuable addition.\nResponse: We thank the reviewer for this insightful comment, which helps clarify the\nrole of our simulations. We fully agree that the existence of an electric field is\nfundamentally a consequence of the opposite charges present on the nanodendrites and\nNPs, as analysed in the main text.\nThe primary objective of our finite-element simulations was not to prove the existence\nof this field, but to quantitatively evaluate its strength and spatial distribution under\nrealistic geometric conditions, and to test whether this quantitative assessment is\nconsistent with experimental observations. The simulations reveal that the decay of the\nlocal electric field strength with distance aligns well with the experimentally measured\ndistance dependence of the growth velocity gradient. This strong correlation provides\nindependent, quantitative support for the hypothesis that the local electric field strength\n(not merely its presence) is a dominant factor regulating branch growth.\nFurthermore, we performed the multi-particle simulations (Supplementary Fig. S12,\nS13 and S14), demonstrating that the quantitatively predicted field asymmetries,\narising from specific particle-tip configurations, can explain the complex growth directions and\nmorphological evolution observed in experiments. And these results and discussions\nwere added to the main text and supplementary materials.\nIn summary, while the electric field’s origin is electrostatic, its quantitative magnitude\nand configuration-dependent effects which are critical for understanding the growth\nmechanics are compellingly elucidated by our finite-element simulations. The\nconsistency between these quantitative simulations and experimental observations\nstrongly supports our proposed mechanism.\nCorresponding images have been added to the Supplementary Information (Page 12,\nSupplementary Fig. S12, S13 and S14). We have added corresponding description in\nthe main text(Page 10, line 229; Page 12, line 260)."}, {"round": 2, "reviewer_comments": {"reviewer_1": "The authors have address my comments. I now recommend publication in Nature Communications.", "reviewer_2": "Comments\nThe authors have revised the manuscript substantially according to the first-round review. I still have one comments.\n1. According to Fig. R1. of the long-term growth morphology, the growth morphology with the presence of Au NPs should be\nstill seaweed rather than dendrite. Even though the local Au NPs can guide the tip growth but here apparently there is no\nleading tip of an oxide crystal. The most different feature between dendrite and seaweed is that a dendrite has a leading tip\nand apparent sidebranches which are nearly normal to the main trunk. And mostly, the growth direction of main trunk is\ntowards to the preferred growth direction due to the anisotropy of interfacial energy , for example of the cubic crystal, it is\nalways along the <100> direction. But here I can not identify the main trunk. It is more likely that the Au NPs have significant\nimpacts on slowing the splitting frequency and guiding the growth direction of newly formed tips. Since the Au NPs particles\nwere distributed randomly in the solution, it exhibits directional growth just in a very local zone. When evaluating the growth\nmorphology on the whole in a large scale, the branches still show random growth in a form more like seaweed. So I do not\nagree to using dendrite to describe the morphology, it should be still seaweed.\nThe authors may have a look of the dendrites in detail which form during solidification of metals , too see the exact\nmorphology of dendrites.\nSome conditions to form dendrites: (1) the anistropy of interfacial energy should be sufficient high; (2) the solute or heat is\ntransported directionally for diffusion-limited growth. But here, Au NPs particles can lead to directional growth in local zone,\nbut their distribution is quite randomly in the whole solution.", "reviewer_3": "My main remark was that the authors should mention the kind of iron oxide they are growing. The present version of their\nmanuscript now mentions it, but only in the Supplementary information, with no reference to this mention in the main text. I\ncould find no comment on the oxide phase in the main text of the article. Thus, this remark still holds.\nI’m renewing my recommendation of major revision."}, "author_response": "Reviewer #1 (Remarks to the Author):\nComment: “The authors have addressed my comments. I now recommend publication in Nature\nCommunications.”\nResponse: We thank the reviewer for their positive feedback and final recommendation for\npublication.\nReviewer #2 (Remarks to the Author):\nThe authors have revised the manuscript substantially according to the first-round review. I still have one\ncomments.\n1. According to Fig. R1. of the long-term growth morphology, the growth morphology with the presence of Au NPs should be\nstill seaweed rather than dendrite. Even though the local Au NPs can guide the tip growth but here apparently there is no\nleading tip of an oxide crystal. The most different feature between dendrite and seaweed is that a dendrite has a leading tip\nand apparent side branches which are nearly normal to the main trunk. And mostly, the growth direction of main trunk is\ntowards to the preferred growth direction due to the anisotropy of interfacial energy, for example of the cubic crystal, it is\nalways along the <100> direction. But here I can not identify the main trunk. It is more likely that the Au NPs\nhave significant impacts on slowing the splitting frequency and guiding the growth direction of newly\nformed tips. Since the Au NPs particles were distributed randomly in the solution, it exhibits directional\ngrowth just in a very local zone. When evaluating the growth morphology on the whole in a large scale,\nthe branches still show random growth in a form more like seaweed. So I do not agree to using dendrite\nto describe the morphology, it should be still seaweed.\nThe authors may have a look of the dendrites in detail which form during solidification of metals, too\nsee the exact morphology of dendrites.\nSome conditions to form dendrites: (1) the anistropy of interfacial energy should be sufficient high; (2)\nthe solute or heat is transported directionally for diffusion-limited growth. But here, Au NPs particles\ncan lead to directional growth in local zone, but their distribution is quite randomly in the whole solution.\nResponse: We sincerely thank the reviewer for this insightful comment and the thorough explanation\nregarding the classification of growth morphologies. We agree with the reviewer’s assessment.\nAccording to previous reports, a key morphological distinction between dendrites and seaweed\nstructures lies in the presence of a well-defined primary growth axis and a distinct trunk with side\nbranches for dendrites, whereas seaweed structures are characterized by a more isotropic, branching\npattern without a dominant growth direction1, 2, 3. The iron oxide nanostructures observed in our\nexperiments do not exhibit a clearly defined primary growth direction or a columnar main trunk.\nThe branching pattern appears more isotropic. Therefore, we agree that “seaweed-like” is a more\naccurate description for the observed morphology.\nAs suggested, we have revised the manuscript. We have added the discussion on the morphology of\niron oxide in the main text (page 3, line 87-90). Descriptions have been changed from “dendritic”\nto “seaweed-like nanodendrite” or “seaweed structure” where appropriate, and these changes are\nhighlighted in red in the revised manuscript and supporting information.\nReviewer #3 (Remarks to the Author):\nComment 1: My main remark was that the authors should mention the kind of iron oxide they are\ngrowing. The present version of their manuscript now mentions it, but only in the Supplementary\ninformation, with no reference to this mention in the main text. I could find no comment on the\noxide phase in the main text of the article. Thus, this remark still holds.\nI’m renewing my recommendation of major revision.\nResponse: We thank the reviewer for emphasizing this point. In our work, we performed high-\nresolution transmission electron microscopy (HRTEM) characterization on the dried samples. Based\non the analysis combined with fast Fourier transform (FFT) patterns identifies that our product\ncontains the crystalline Fe₃O₄.\nFurthermore, relevant literature indicates that the reactions in the liquid cell follow pathways similar\nto those reported for conventional thermally activated synthesis processes4. Previous studies have\nobserved intermediate phases and minor byproducts under comparable conditions; therefore, the\npresence of other FeOₓ species cannot be entirely excluded in our experiments. However, this does\nnot affect our subsequent dynamic analysis. Accordingly, the products are collectively referred to as\n“iron oxides” throughout the manuscript.\nAs suggested, we have now explicitly mentioned the specific phase of the iron oxide in the main\ntext. The relevant addition has been made on page 3, line 82-87 of the revised manuscript."}, {"round": 3, "reviewer_comments": {"reviewer_2": "The authors have replaced the \"dendritic\" with seaweed-like in the revised text, but in the title they still used dendrite, is this appropriate?\nIndeed, I do not like using seaweed-like nanodendrite to describe this morphology. The important innovation of the work is\nthe finding of the local directional growth of iron oxide seaweed branches driven by electrical field.", "reviewer_3": "My main remark has now been taken into account. I recommend publication in Nature Communications."}, "author_response": "Reviewer #2:\nThe authors have replaced the “dendritic” with seaweed-like in the revised text, but in the title\nthey still used dendrite, is this appropriate?\nIndeed, I do not like using seaweed-like nanodendrite to describe this morphology. The important\ninnovation of the work is the finding of the local directional growth of iron oxide seaweed\nbranches driven by electrical field.\nResponse: We sincerely appreciate your helpful feedback. In agreement with your suggestion, and\nas also recommended by the editorial team, we have revised the manuscript title to: “Accelerated\ndirectional growth of seaweed-like iron oxide branches driven by localized electric fields of gold\nnanoparticles in liquid”. Throughout the manuscript, the term “nanodendrite” has been consistently\nreplaced with more precise descriptions such as “branched nanostructures” or “seaweed-like\nstructures” where appropriate.\nReviewer #3:\nMy main remark has now been taken into account. I recommend publication in Nature\nCommunications.\nResponse: We thank the reviewer for the constructive comments and for supporting the publication\nof our manuscript in Nature Communications. Your feedback has been valuable in strengthening our\nwork, and we greatly appreciate the time and effort you dedicated to the review process."}]

Decision letter