Diffusion Research Articles

Diffusion Mechanism of Waste Crumb Rubber Composite Modified Asphalt Based on Molecular Dynamics Simulation

Waste crumb rubber composite modified asphalt (CRCMA), composed of base asphalt, waste rubber powder, and several additives (softener, activator, and cross-linking agent), has been shown to effectively improve asphalt properties. The interactions between the components in CRCMA are complex, involving molecular diffusion that significantly impacts its performance. The diffusion behavior in asphalt molecules will affect various properties of asphalt and the reasons for the different properties of asphalt can be explained by studying its diffusion mechanism. Therefore, understanding the diffusion mechanism of CRCMA is essential. The molecular dynamics simulation was employed to analyze the factors influencing the diffusion mechanism, using the diffusion coefficient as a key indicator of molecular mobility. The findings showed that the diffusion coefficient of the asphalt system decreased over time but increased with temperature. The rubber composition type also had a significant impact on diffusion, with butadiene rubber (BR) showing the highest coefficient, followed by natural rubber (NR), crumb rubber (CR), and styrene-butadiene rubber (SBR). The diffusion coefficient was the lowest and the diffusion rate was slowest after adding softeners. The diffusion coefficient increased slightly with the addition of CR, and the diffusion rate was slightly accelerated but not significantly. The diffusion coefficient increased rapidly with adding activator and the diffusion rate increased significantly. With the addition of cross-linking agent, the diffusion coefficient began to decrease and the diffusion rate became slower. The CRCMA microscopic performance tests indicated that the swelling effect of CR limits diffusion, while activators promote degradation and desulfurization of CR due to the large molecule structure getting smaller, enhancing diffusion. The S=O bond in the asphalt system was regenerated and re-crosslinked to create a mesh after adding the cross-linking agent. The small molecule structure was transformed into large one. The molecular diffusion was restricted partly and thus the diffusion rate was slowed down.

Environmental modification of cellulose fibers for reducing dye diffusion rate by anionic polyacrylamide

Reactive dyeing is the primary method for coloring cellulose fibers due to its vibrant colors, various hues, excellent colorfastness, and cost-effectiveness. However, this process consumes a large amount of water and chemicals, leading to significant environmental concerns due to the wastewater. Non-aqueous media/less water dyeing has emerged as a cleaner alternative, showing promising results in dyeing cotton fibers with reactive dyes. Nevertheless, the rapid adsorption rate of dyes can impact the evenness of dyeing. This study explores the use of anionic polyacrylamide (APAM) in the modification bath to reduce dye adsorption rate and enhance dye desorption during cellulose fibers dyeing. Fourier transform infrared spectroscopy (FT-IR) and field-emission scanning electron microscope (FSEM) analysis revealed effective interaction between APAM and cellulose fibers. Thermal gravimetric analysis (TGA), X-ray diffraction (XRD), and breaking strength tests indicated minimal impact on the thermal stability and physical properties of cellulose fibers with APAM modification. Zeta potential testing demonstrated that APAM modification reduced the surface potential of cellulose fibers and increased their negative charge. The adsorption rate of reactive dye decreased with APAM modification, while dye fixation, washing, and rubbing fastness remained largely unaffected. Adsorption isotherm results supported the weakening of the affinity between dyes and fibers after APAM treatment. Furthermore, the electrostatic potentials of fibers decreased after APAM modification. Compared to salt-free dyeing in non-aqueous media dyeing systems, anionic polymer modification not only improves the level dyeing performance of cotton fiber and reduces 0.9% in dyeing costs, but also increases production efficiency.

Effect of Flash-Ni Plating Layer on Interfacial Behavior of Zn-Al-Mg Coating/DH780 Steel

The Zn-Al-Mg coated DH780 high-strength steel with a flash-Ni plating layer was used in this study. The occurrence state of Ni element at the coating/steel interface was investigated, and the relationship between Mn and Si elements and the internal oxidation at the interface was discussed. The results show that Ni existed between the Fe2Al5 layer and the steel substrate in the form of Fe(Ni) solid solution and Ni elemental substance. The mutual diffusion rate between Fe and Al was greatly reduced after flash-Ni plating, and the continuity of Fe2Al5 layer of the flash-Ni-plated steel was slightly lower than that of the Ni-free steel. Moreover, the diffusion coefficients of Mn and Si in the Ni layer were lower than those in the steel substrate, which indicated that the Ni layer significantly inhibited the diffusion of Mn and Si to the surface. The average depth of internal oxidation was reduced by 70.8% after flash-Ni plating, the average Mn, Si and O contents at the interface after flash-Ni plating were reduced by 19.6%, 6.1% and 22.7%, respectively, which indicated that the flash-Ni plating layer can isolate the steel substrate from the annealing atmosphere, inhibit the internal oxidation and interfacial enrichment of Mn and Si, especially for Mn. Therefore, the flash-Ni plating layer can improve the wettability of high-strength steel sheets during continuous annealing.

Tribo-oxidation mechanism of gradient nanostructured Inconel 625 alloy during high-temperature wear

The tribo-oxidation layer is typically formed at the contact interface of high temperature wear, which exhibits a significant effect on the friction behavior of gradient nanostructured (GNS) materials. This study systematically investigated the wear resistance, near-surface microstructure, and compositional changes of ultra-thick GNS Inconel 625 alloy subjected to surface mechanical rolling treatment (SMRT) under high-temperature sliding wear conditions. The experimental results indicated that as the temperature increased to 500 °C, a tribo-oxidation layer was formed on the surface of the GNS sample, thereby resulting in an abnormal increase in the coefficient of friction (COF) and a rapid decrease in the wear rate. The gradient nanostructures facilitated oxidation diffusion channels, promoting the formation of a protective Cr2O3 film and spinel oxides, reducing the wear rate. At lower temperatures, a rapidly formed Cr2O3 film shielded the matrix, forming a tribo-oxidation layer composed of Cr2O3 and nickel. At 800 °C, the tribo-oxidation layer exhibited complex structures, including glaze, spinel oxide, Cr2O3, and Cr2O3/Ni mixed layers. This complexity was attributable to the oxidation diffusion rate of the gradient nanostructures and tribo-oxide layers. The findings not only elucidated the tribo-oxidation mechanism of GNS nickel-based superalloys but also offered valuable insights for designing wear-resistant materials.

Evolution of strengthening precipitates in Al-4.0Zn-1.8Mg-1.2Cu (at.%) alloy with high Zn/Mg ratio during artificial aging

Evolution of strengthening precipitates, including their types, sizes, volume fraction, and chemical compositions in Al-4.0Zn-1.8Mg-1.2Cu (at.%) alloy during artificial aging, were investigated using anomalous small-angle X-ray scattering (ASAXS), three-dimensional atom probe techniques (APT), high-angle annular dark-field scanning transmission electron microscopy (HAADF-STEM) and density functional theory (DFT) calculation. Upon aging, Cu-containing clusters merge with adjacent clusters to form larger clusters, which then act as nucleation sites for GPη' zones. As aging proceeds, GPη' zones grow up to η'I metastable phase with seven atomic layers on {111}Al planes, and this process is controlled by diffusion of Mg atoms. Cu atoms have a low diffusion rate and do not participate into the growth of precipitates within the first 60mins of aging. As aging time increases, Cu atoms enter the η'I metastable phase, leading to a significant increase in Cu content and (Zn+Cu)/Mg ratio; η'I metastable phase grow, and after exceeding about 7nm, gradually transform into the η'II metastable phase with ten atomic layers by adding three new atomic layers at one side. GPη' zones, η'I metastable phase and η'II metastable phase have symmetric interface structures. The precipitation sequence during aging to peak state can be summarized as: atomic clusters → GPη' zones → η'I metastable phase → η'II metastable phase.

Diffusion of radioactive anion and cation in silver-calcium-bentonite

AbstractIn the geological disposal of nuclear waste, the simultaneous reduction of diffusion rate of cationic and anionic radioactive species is essential. Natural calcium-bentonite only reduces the diffusion rate of cations, not anions. In this study, the half of calcium ions is bentonite was exchanged to silver ions to reduce diffusion rates of both of radioactive cation (137Cs+) and anions (36Cl−, 131I−) at the same time. This is due to the precipitation of silver halides in the interlayer space. The diffusion rate of both anionic and cationic radioactive species are small in compacted the silver-calcium bentonite.

Hydrogen diffusion on Ni(100): A combined machine-learning, ring polymer molecular dynamics, and kinetic Monte Carlo study.

We introduce a methodological framework coupling machine-learning potentials, ring polymer molecular dynamics (RPMD), and kinetic Monte Carlo (kMC) to draw a comprehensive physical picture of the collective diffusion of hydrogen atoms on metal surfaces. For the benchmark case of hydrogen diffusion on a Ni(100) surface, the hydrogen adsorption and diffusion energetics and its dependence on the local coverage is described via a neural-network potential, where the training data are computed via periodic density functional theory (DFT) and include all relevant optimized diffusion and desorption paths, sampled by nudged elastic band optimizations and molecular dynamics simulations. Nuclear quantum effects, being crucial for processes involving hydrogen at low temperatures, are treated by RPMD. The diffusion rate constants are calculated with a combination of umbrella samplings employed to map the free energy profile and separate samplings of recrossing trajectories to obtain the transmission coefficient. The calculated diffusion rates for different temperatures and local environments are then combined and fitted into a kMC model allowing access to larger time and length scales. Our results demonstrate an outstanding performance for the trained neural network potential in reproducing reference DFT energies and forces. We report the effective diffusion rates for different temperatures and hydrogen surface coverages obtained via this recipe in good agreement with the experimental results. The method combination proposed in this study can be instrumental for a wide range of applications in materials science.

Impact of the innovation promotion strategy on digital technology diffusion in regional innovation ecosystems

ABSTRACT From the external perspective of digital technology diffusion in regional innovation ecosystems, this study divides innovation promotion into information dissemination and precision subsidy promotion strategies, and uses multi-agent modelling and simulation method to analyse the impact of innovation promotion strategies on digital technology diffusion in regional innovation ecosystems. The results are as follows. (1) The diffusion rate and depth of digital technology in regional innovation ecosystems with an information dissemination promotion strategy are better than those without this strategy. Early, high-strength centralised promotion strategy has the highest rate and depth of digital technology diffusion, and implementing distributed information promotion strategy in the late stage can maximise the rate and depth of digital technology diffusion. (2) When the number of target enterprises is insufficient, the precision subsidy promotion strategy cannot achieve the desired effect. With an increase in the number of target enterprises, the diffusion rate and depth of digital technology in regional innovation ecosystems gradually increased and showed a classic ‘S’-type diffusion curve. By focusing on the overall trend, the average rate and depth of digital technology diffusion in regional innovation ecosystems with a relationship embeddedness strategy are the best.

Low Molecular Weight Alginate Oligosaccharides as Alternatives to PEG for Enhancement of the Diffusion of Cationic Nanoparticles Through Cystic Fibrosis Mucus.

Airway mucus is a major barrier to the delivery of lipid-based nanoparticles in chronic airway diseases such as cystic fibrosis (CF). Receptor-Targeted Nanocomplexes (RTN), comprise mixtures of cationic lipids and bifunctional peptides with receptor-targeting and nucleic acid packaging properties. The aim of this study is to improve the mucus-penetrating properties of cationic siRNA and mRNA RTNs by combining them with low molecular weight alginate oligosaccharides, OligoG and OligoM. Cationic RTNs formulated with either alginate become strongly anionic, while PEGylated messenger RNA (mRNA) and short interfering RNA (siRNA) RTNs remain cationic. Both alginates enhance mucus diffusion rates of cationic siRNA and mRNA RTNs in a static mucus barrier diffusion model, with OligoG particularly effective. PEGylation also enhance mucus diffusion rates of siRNA RTNs but not mRNA RTNs. Electron microscopy shows that RTNs remained intact after mucosal transit. The transfection efficiency of OligoM-coated mRNA RTNs is better than those coated with OligoG or PEG, and similar to cationic RTNs. In siRNA RTN transfections, OligoM is better than OligoG although 1% PEG is slightly better than both. The combination of cationic RTNs and alginate oligosaccharides represents a promising alternative to PEGylation for epithelial delivery of genetic therapies across the mucus barrier while retaining transfection efficiency.

EXTH-28. DEVELOPING A NOVEL INJECTABLE IMMUNOTHERAPEUTIC GEL FOR ENCAPSULATION OF NATURAL KILLER CELLS FOR POST-SURGICAL GLIOBLASTOMA TREATMENT

Abstract Malignant brain tumors are one of the leading causes of death among all cancers. Approximately 40,000 people are diagnosed with malignant brain tumors every year. Among these patients, 15,000 cases are glioblastoma (GBM) with a very poor prognosis; even after aggressive surgical resection and adjuvant chemo/radiotherapy, the median survival is only 14.6 months. The major reason for poor prognosis is the blood-brain barrier, which prevents therapeutic agents from reaching the target area. Therefore, there are only a few choices of drugs available for brain tumor treatment. To date, temozolomide (TMZ) and the Gliadel wafer have been clinically used as standard chemotherapy agents after brain tumor resection. However, drug resistance to TMZ and the poor drug diffusion rate of the Gliadel wafer still result in ineffective suppression of residual cancer cells. To overcome the above-mentioned difficulties in clinical brain tumor treatment, in situ self-crosslinking multifunctional hydrogels was developed to carry natural killer cells (NK cells) and radiosensitizers as a novel brain tumor treatment system. Unlike traditional hydrogels catalyzed by pH value or temperature, this new system is stable and consistent as an immune cell carrier. We used fibrinogen, thrombin, and alginic acid as the backbone of the in situ self-crosslinking hydrogel, tested the properties of the synthesized hydrogel, and analyzed the gel-formation time and swelling rate. The release rate of NK cells was also examined. In a brain tumor animal model, the use of hydrogel-NK cells significantly inhibited tumor proliferation and prolonged animal survival time. In conclusion, this therapeutic hydrogel carrying NK cells can serve as a novel post-operation adjuvant therapeutic tool for malignant brain tumors.

Effects of Ion Valence States and Radii on the Performance of Solid-State PEDOT:PSS Electrochromic Devices.

Ion transport is a critical factor influencing the performance of electrochromic devices (ECDs). In this work, the effects of the valence state and ionic radius of six cations, Li+, Na+, K+, Mg2+, Zn2+, and Al3+, on the performance of poly(3,4-ethylenedioxythiophene)-polystyrene sulfonic acid (PEDOT:PSS)-based ECDs are investigated. Both ion migration and diffusion are discussed as processes that were analyzed, with results indicating that the primary contributor to the response of ECDs is ion migration. The response time decreases with increasing ionic valence and ionic radius, with the valence state having the predominant effect on response speed. Multivalent ions, due to strong electric field forces, migrate more rapidly and intercalate fewer ions at equivalent reaction charges, thereby facilitating a faster response. ECDs with larger-radius ions, which exhibit slower diffusion rates, also achieve faster response speeds. Among the tested ECDs with various electrolytes, the Al3+-based ECD demonstrates the fastest colored/bleached response time of 0.36/0.4 s. In addition, ions with larger radii introduce greater steric hindrance and structural damage during insertion and extraction, leading to ion retention issues and reduced cycling stability. After 500 cycles (2025 s) under a square wave voltage of ±1.5 V, the peak current of ECDs with Li+ (0.60 Å) electrolyte decreased by only 5.07/5.66%, whereas for K+ (1.33 Å) electrolyte, the decrease was 11.55/12.37%. ECDs utilizing small-radius, higher-valence ions, such as Al3+, achieved both fast response and high cycling stability, with peak current reductions of only 6.98/5.01%. Additionally, the charge storage dynamics were examined by analyzing the contributions from surface-controlled and diffusion-controlled charges, further confirming that ion migration dominates in ECDs. The high contribution of surface-controlled charges (80%) supports the fast response of ECDs and contributes to the high coloration efficiency (592.6 cm2/C for Al3+-based devices).

Waxberry-like TiO2 with Synergistic Surface Modification of Pyrolytic Carbon Coating and Carbon Nanotubes as an Anode for Li-Ion Battery.

Titanium dioxide (TiO2) as an anode material for lithium-ion batteries (LIBs) has the advantages of tiny volume expansion, high operating voltage, and outstanding safety performance. However, due to the low conductivity of TiO2 and the slow diffusion rate of lithium ions (Li+), it is limited in the application of LIBs. Therefore, waxberry-like TiO2 comodified by pyrolytic carbon coating and carbon nanotubes was prepared in this work. The waxberry-like TiO2 with nanorods on its surface shortens the diffusion distance of Li+. Carbon nanotubes and waxberry-like TiO2 are tightly combined through electrostatic assembly and form a cross-linked conductive network to provide more electron transmission paths. A thin layer of pyrolytic carbon wraps carbon nanotubes and waxberry-like TiO2, which enhance the conductivity of the composites and ensure the structural integrity of the materials throughout the cycling process. The experimental data revealed that the discharge-specific capacity of TiO2@CNT@C is 170.5 mAh g-1 after 3000 cycles at a large current density of 5 A g-1, and the discharge-specific capacity is still 143 mAh g-1 at the superhigh rate of 10 A g-1, which provides excellent rate performance and cyclic stability. The efficient dual-carbon modification strategy could potentially be extended to other materials.

Comparison of Convergence for Different Models and Loss Function: Evidence from Transformer, Diffusion and RNN

Abstract. With the development of science and technology, people are using machine learning as a method to make life easier. However, the performance corresponding to different models will produce different predictions and results for one thing. In order to improve the performance of the model, this paper investigates the influence of the learning rate hyperparameter on the model's performance, and demonstrates it through the convergence of the loss function. After experimental research, it has been found that different models exhibit significant differences in their performance when processing the same dataset. Meanwhile, different learning rates also have a significant impact on the performance of the model. Therefore, after selecting the correct model for machine learning, one should also adjust a relatively good hyperparameter to make the entire process smoother. Based on the analysis, one will gain a basic understanding of the optimal learning rates for transformer, diffusion, and RNN models when training MNIST. It is convenient for people to set better hyperparameters and obtain better prediction and decision-making results when using these three models, so that one can demonstrate better performance when using these three models.

Simulation Analysis of the Annular Liquid Disturbance Induced by Gas Leakage from String Seals During Annular Pressure Relief

Due to the failure of string seals, gas can leak and result in the abnormal annulus pressure in gas wells, so it is necessary to relieve the pressure in gas wells. In the process of pressure relief, the leaked gas enters the annulus, causes a the great disturbance to the annulus flow field, and thus reduces the protection performance of the annular protection fluid in the string. In order to investigate the influence of gas leakage on the annular flow field, a VOF finite element model of the gas-liquid two-phase flow disturbed by gas leakage in a casing was established to simulate the transient flow field in the annular flow disturbed by gas leakage, and the influences of leakage pressure differences, leakage direction, and leakage time on annular flow field disturbance and wall shear force were analyzed. The analysis results showed that the larger leakage pressure difference corresponded to the faster diffusion rate of the leaked gas in the annulus, the faster the flushing rate of the leaked gas against the casing wall, and a larger shear force on the tubing wall was detrimental to the formation of the corrosion inhibitor film on the tubing wall and casing wall. Under the same conditions, the shear action on the outer wall of tubing in the leakage direction of 90° was stronger than that in the leakage directions of 135° and 45° and the diffusion range was also larger. With the increase in leakage time, leaked gas further moved upward in the annulus and the shear effect on the outer wall of tubing was gradually strengthened. The leaked acid gas flushed the outer wall of casing, thus increasing the peeling-off risk of the corrosion inhibitor film. The study results show that the disturbance law of gas leakage to annular protection fluid is clear, and it was suggested to reduce unnecessary pressure relief time in the annulus to ensure the safety and integrity of gas wells.

The Throttle Effect in Metal-Organic Frameworks for Distinguishing Water Isotopes.

Metal-organic frameworks (MOFs) have been widely used for separation, but amplifying subtle differences between similar molecules to achieve effective separation remains a great challenge. In this study, we utilize the fluorescent molecule uranine (Ura) to modulate the pores of zeolitic-imidazolate framework 8 (ZIF8), creating an unusual throttle effect. By monitoring fluorescence intensity changes in Ura, the transport diffusion process could be quantified to reveal the diffusion constant of solvents. When we pushed the Ura occupancy to its limit (from 59% to 76% and 98%), the diffusion rate decreases by 2 orders of magnitude. Most importantly, there is a significant dissymmetry between the two-way exchange rates of solvents, and the rates of H2O and D2O became distinguishable. Such unusual throttle effects disappear at low Ura occupancy of 59% and 76%. We believe that the throttle effect with small-molecule loading could provide a universal design principle for MOF-based applications, especially for isotope separation.

The MoS2/rGO embed in macro-porous PAN gel as a novel DGT binding phase for the rapid and accurate detection of trace Hg(II)

The development of binding gels with a fast uptake rate, high capacity, and good selectivity could be beneficial for trace Hg(II) detection based on the DGT technology. In this study, a novel PAN@MoS2/rGO-DGT was assembled by using the nanocomposite embedded in polyacrylonitrile membrane (PAN@MoS2/rGO) as the binding phase. The interior regular finger-like macropore of the gel provided a convenient channel for the rapid mass diffusion of Hg(II), and the abundant sulfur offered the paramount driving force for trapping Hg(II). These endowed the PAN@MoS2/rGO with an impressive reaction rate, capacity, and selectivity toward Hg(II) and featured the PAN@MoS2/rGO-DGT with excellent diffusion rate (D) and adaptability in the complex matrixes across a wide range of pH, ion strength, common cations. However, the uptake of Hg(II) was influenced by the high content of chloride, thus a calibrated model was established based on the chloride concentration to correct the accumulated mass and D. After that, the high accuracy of this method was confirmed through the good consistency between Hg(II) concentration assessed by DGT and in bulk solution when the DGT was deployed to the river water, seawater, and domestic wastewater at the static and dynamic Hg(II) concentration. Field trials in the prawn farming seawater and lake water also showed a negligible deviation of Hg(II) content from the DGT and the conventional method, acquiring the actual Hg(II) level as 1.07–3.69 ng/L. The findings highlighted the application potential of macropore PAN gel hybrid with nanocomposite as a promising binding phase for trace Hg(II) or other pollutant detection.

Enhancing nanofiltration performance with tannic acid and polyvinyl alcohol interlayers for improved water permeability and selective solute rejection

Global water shortages have significantly intensified the demand for efficient and sustainable water purification technologies. Nanofiltration (NF) plays a crucial role in desalination, providing distinct advantages by removing a variety of pollutants including heavy metals and organic compounds, all while consuming minimal energy. Traditional NF membranes often struggle to balance high rejection with satisfactory permeability. This study advances NF technology by utilizing polysulfone as a durable substrate and introducing tannic acid (TA)-polyvinyl alcohol (PVA) interlayer to enhance structural robustness and functional capabilities of membranes. Through streamlined one-step coating followed by precise interfacial polymerization, this approach optimizes monomer piperazine storage and dispersion on substrate, effectively controlling its diffusion rate, resulting in a thinner polyamide (PA) layer. These strategic enhancements not only lead to a significant increase in permeability to 216.3 L·m−2·h−1·MPa−1 and an impressive rejection for Na2SO4 of 99.04 % but also ensure enhanced long-term operational stability. The innovative TA-PVA interlayer sets new benchmarks for high-performance NF membranes by combining environmental friendliness with cost-effectiveness, making it ideal for large-scale industrial applications. This unique composition promotes sustainability and economic efficiency in water treatment technologies, and underscoring the vast potential for expanding the production and application of advanced NF systems.

Insights into the Pickering emulsions stabilized by yeast dietary fiber: Interfacial adsorption kinetics, rheological characteristics, and stabilization mechanisms

This study developed Pickering emulsions based on yeast dietary fiber (YDF) and investigated the interfacial adsorption kinetics of YDF, rheological properties and stabilization mechanisms of emulsions. Results indicated that increasing YDF concentration enhanced its diffusion and rearrangement at the oil-water interface. At a concentration of 8 %, YDF exhibited the highest diffusion rate (0.1406 mN·m−1·s-0.5) and rearrangement rate (18.8 s−1). The emulsion stabilized at this concentration had the smallest droplet size (1.55 μm) and the slowest droplet migration rate (0.34 mm/h), effectively suppressing droplet aggregation due to collisions and thereby improving the overall emulsion stability. Confocal laser scanning microscopy results confirmed that emulsion stability relied on the co-adsorption of proteins and polysaccharides from YDF at the interface, with proteins primarily adsorbed at the oil-water interface and polysaccharides responsible for the continuous phase network formation. This study demonstrates YDF's potential as an emulsion stabilizer and elucidates the stabilization mechanism of YDF-induced emulsion.

Early Stages of High‐Temperature Oxidation Behavior and Its Phase Evolution of 9% Ni Steel

Herein, the effects of oxygen partial pressure (5–20%) and oxidation time (0.5–6 h) on the growth behavior and phase structure of 9% Ni steel oxide layer are studied by means of high‐temperature oxidation experiment, scanning electron microscopy, and X‐ray diffraction. The results show that the inner and outer oxide layers of 9% Ni steel grow opposite to each other along the initial surface direction of the vertical matrix during the high‐temperature oxidation process. From the perspective of the phase, the phase transition of Fe2O3→Fe3O4→FeO mainly undergoes from the outside and the inside, the results of thermodynamic calculations show that <<<0, and the main factor affecting the phase transition is the diffusion concentration of free O and Fe atoms. During the high‐temperature oxidation process of 9% Ni steel, the diffusion of O and Fe atoms along grain boundaries promotes preferential oxidation at these boundaries. The columnar structure formed in the outer oxide layer of 9% Ni steel may be related to the uneven diffusion rate of Fe atoms at different positions at the interface between the inner and outer oxide layers.

Electrostatic Assembly of Gold Nanoclusters in Reverse Emulsion Enabling Nanoassemblies with Tunable Structure and Size for Enhanced NIR-II Fluorescence Imaging.

The precise control of the assembly structure and size of gold nanoclusters (AuNCs) can potentially amplify their near-infrared II (NIR-II) fluorescence imaging and targeting properties. However, the conventional electrostatic assembly of AuNCs and charged molecules faces challenges in balancing the inherent electrostatic repulsions among charged units and regulating the diffusion of assembly units. These difficulties limit precise control over assembly size and structure, along with limited options for coassembled molecules, thereby restricting imaging properties and targeting capability. To circumvent this challenge, we developed a reverse emulsion-confined electrostatic assembly method. This technique efficiently constructs AuNC nanoassemblies with diverse coassembled molecules, allowing for the fine-tuning of assembly size and structure, including both core-satellite and homogeneous AuNC nanoassemblies. The development of two distinct nanoassemblies can be partially attributed to the varying diffusive rates of AuNCs or the AuNCs/polymer complex within the fused emulsion droplets. This variance arises from steric hindrances encountered during the emulsion fusion process. Interestingly, core-satellite nanoassemblies exhibit the strongest NIR-II fluorescence enhancement. Finally, the introduction of a hyaluronic acid coating on the surfaces of nanoassemblies with varying sizes enables the nanoprobes to achieve enhanced lymph node imaging through size modulation and macrophage targeting, which are used for surgical navigation to remove lymph node metastases. We envision that this self-assembly strategy can be extended to a wide range of electrostatic assembly systems for the development of multicomponent functional materials.