Unraveling thermodynamic anomalies of water: A molecular simulation approach to probe the two-state theory with atomistic and coarse-grained water models.

Thermodynamic and dynamic anomalies of water play a crucial role in supporting life on our planet. The two-state theory attributes these anomalies to a dynamic equilibrium between locally favored tetrahedral structures (LFTSs) and disordered normal liquid structures. This theory provides a straightforward, phenomenological explanation for water's unique thermodynamic and dynamic characteristics. To validate this two-state feature, it is critical to unequivocally identify these structural motifs in a dynamically fluctuating disordered liquid. In this study, we employ a recently introduced structural parameter (θavg) that characterizes the local angular order within the first coordination shell to identify these LFTSs through molecular dynamics simulations. We employ both realistic water models with a liquid-liquid critical point (LLCP) and a coarse-grained water model without an LLCP to study water's anomalies in low-pressure regions below 2 kbar. The two-state theory consistently describes water's thermodynamic anomalies in these models, both with and without an LLCP. This suggests that the anomalies predominantly result from the two-state features rather than criticality, particularly within experimentally accessible temperature-pressure regions.

Advancements in Characterization Techniques for Microemulsions: From Molecular Insights to Macroscopic Phenomena.

Microemulsions are thermodynamically stable, optically isotropic, transparent, or semi-transparent mixed solutions composed of two immiscible solvents stabilized by amphiphilic solutes. This comprehensive review explores state-of-the-art techniques for characterizing microemulsions, which are versatile solutions essential across various industries, such as pharmaceuticals, food, and petroleum. This article delves into spectroscopic methods, nuclear magnetic resonance, small-angle scattering, dynamic light scattering, conductometry, zeta potential analysis, cryo-electron microscopy, refractive index measurement, and differential scanning calorimetry, examining each technique's strengths, limitations, and potential applications. Emphasizing the necessity of a multi-technique approach for a thorough understanding, it underscores the importance of integrating diverse analytical methods to unravel microemulsion structures from molecular to macroscopic scales. This synthesis provides a roadmap for researchers and practitioners, fostering advancements in microemulsion science and its wide-ranging industrial applications.

Molecular Dynamics Simulation Insight into Interfacial Stability and Fluidity Properties of Microemulsions.

Although the interfacial properties of microemulsions have been extensively studied in both experimental and simulation research studies, the molecular mechanisms of stability and fluidity about microemulsion are still poorly understood. Herein, we report a molecular dynamics simulation study to elaborate the motion of an emulsion droplet involving dichain surfactant Aerosol OT (AOT) and its dynamics evolution at the oil-water interface. By varying the concentrations of AOT, we show that the interfacial thickness and emulsification rate display a piecewise change as the interfacial coverage increases and the W/O emulsion is more stable than the O/W one while O/W emulsion presents better fluidity. In addition, the dispersed system combined with water/AOT/n-heptane tends to form a W/O microemulsion instead of an O/W microemulsion due to the structural collapse of the latter. This work provides a molecular understanding of microemulsion interfacial stability and fluidity.

Amphiphilic Cellulose Nanocrystals for Enhanced Pickering Emulsion Stabilization.

Sulfated cellulose nanocrystals (CNC) with high surface charge density are inadequate for stabilizing oil-water emulsions, which limits their applications as interfacial stabilizers. We performed end-group modification by introducing hydrophobic chains (polystyrene) to CNC. Results showed that the modified CNC are more effective in emulsifying toluene and hexadecane than pristine CNC. Various parameters were investigated, such as concentration of particles, electrolytes, and polarity of solvents on the characteristics of the emulsions. This study provides strategies for the modification of cellulose nanocrystals to yield amphiphilic nanoparticles that enhance the stability of emulsions. Such systems, bearing biocompatible and environmentally friendly characteristics, are attractive for use in a wide range of industries spanning food, biomedicine, pharmaceuticals, cosmetics, and petrochemicals.

Electrostatic-Driven Dynamic Jamming of 2D Nanoparticles at Interfaces for Controlled Molecular Diffusion.

Dynamically engineering the interfacial interaction of nanoparticles has emerged as a new approach for bottom-up fabrication of smart systems to tailor molecular diffusion and controlled release. Janus zwitterionic nanoplates are reported that can be switched between a locked and unlocked state at interfaces upon changing surface charge, allowing manipulation of interfacial properties in a fast, flexible, and switchable manner. Combining experimental and modeling studies, an unambiguous correlation is established among the electrostatic energy, the interface geometry, and the interfacial jamming states. As a proof-of-concept, the well-controlled interfacial jamming of nanoplates enabled the switchable molecular diffusion through liquid-liquid interfaces, confirming the feasibility of using nanoparticle-based surfactants for advanced controlled release.

Interactions between a series of pyrene end-labeled poly(ethylene oxide)s and sodium dodecyl sulfate in aqueous solution probed by fluorescence.

The interactions between a series of poly(ethylene oxide)s covalently labeled at both ends with pyrene pendants (PEO(X)-Py2, where X represents the number-average molecular weight of the PEO chains and equals 2K, 5K, 10K, and 16.5K) and an ionic surfactant, namely, sodium dodecyl sulfate (SDS), in water were investigated at a fixed pyrene concentration of 2.5 µM corresponding to polymer concentrations smaller than 21 mg/L and with an SDS concentration range between 5 × 10(-6) and 0.02 M, thus encompassing the 8 mM critical micelle concentration (CMC) of SDS in water. The steady-state fluorescence spectra showed that the I1/I3 ratio decreased from 1.73 ± 0.06 for SDS concentration smaller than 2 mM where pyrene was exposed to water to 1.43 ± 0.03 for SDS concentration greater than 6 mM where pyrene was incorporated inside SDS micelles. The ratio of excimer-to-monomer emission intensities (the IE/IM ratio) of all PEO(X)-Py2 samples remained constant at low SDS concentrations, then increased, passed through a maximum at the same SDS concentration of 4 mM before decreasing to a plateau value that is close to zero for PEO(10K)-Py2 and PEO(16.5K)-Py2 but nonzero for PEO(2K)-Py2 and PEO(5K)-Py2. The pyrene end groups of these two latter samples could not bridge two different micelles due to the short PEO chain, and excimer was formed by intramolecular diffusion inside the same SDS micelle. Time-resolved fluorescence decays of the pyrene monomer and excimer of the PEO(X)-Py2 samples were acquired at various SDS concentrations and globally fitted according to the "Model Free" analysis over the entire range of SDS concentration. The molar fractions of various excited pyrene species and the rate constant of pyrene excimer formation retrieved from the analysis of fluorescence decays were obtained as a function of SDS concentration. Interactions between SDS and PEO could not be detected by isothermal titration calorimetry, potentiometry with a surfactant selective electrode, and conductance measurements.

Surfactant Synergistic Effect and Interfacial Properties of Microemulsions Compounded with Anionic and Nonionic Surfactants Using Dissipative Particle Dynamics.

Microemulsions are one of the most promising directions in enhanced oil recovery, but conventional screening methods are time-consuming and labor-intensive and lack the means to analyze them at the microscopic level. In this paper, we used the Clint model to predict the changes in the synergistic effect of the mixed system of anionic surfactant sodium dodecyl benzenesulfonate and nonionic surfactant polyethoxylated fatty alcohols (C12E6), generated microemulsions using surfactant systems with different mole fractions, and used particle size to analyze the performance and stability of microemulsions, analyze the properties and stability of microemulsions using particle size, and analyze the interfacial behaviors and changes of microemulsions when different systems constitute microemulsions from the point of view of mesoscopic microemulsion self-assembly behaviors by combining with dissipative particle dynamics. It has been shown that microemulsion systems generated from anionic and nonanionic surfactants with a synergistic effect, based on the Clint model, exhibit excellent performance and stability at the microscopic level. The method proposed in this paper can dramatically improve the screening efficiency of microemulsions of anionic and nonanionic surfactants and accurately analyze the properties of microemulsions, so as to provide a theoretical basis for the subsequent research on microemulsions.

Molecular dynamics simulations of aggregation and viscosity properties of model asphaltene molecules containing a polycyclic hydrocarbon nucleus with toluene additive under shear interactions.

Reducing the viscosity of heavy oil is beneficial to the process of oil recovery, so it is of great significance to explore the influence of different factors on the viscosity of heavy oil. In this study, molecular dynamics (MD) simulations were carried out to study the viscosity properties of 15 structurally homologous model polycyclic molecules under shear conditions and with a toluene additive with different concentrations. Over 50 sets of simulation systems were constructed and simulated in this work. The molecular structure effect including the phenyl ring arrangements, alkyl side chain decorations, and heteroatoms, as well as the solvent effect such as the concentration of the toluene additive was comprehensively studied. It was found that under the shear conditions, the more branched the benzene ring in the polycyclic hydrocarbon nucleus, the greater the molecular steric hindrance generated, resulting in higher viscosity compared to O-shaped polycyclic hydrocarbon nucleus molecules. The introduction of alkyl side chains and heteroatoms leads to increased intermolecular interactions and more face-to-face stacking configurations, resulting in an increase in viscosity. However, in comparison, the heteroatoms effect is more pronounced in intermolecular interactions and increases in viscosity. Molecular trajectory analysis further indicates the molecular aggregates undergo continuous fracture and recombination under shear interaction, which is related to the trend of changes in viscosity properties. The current research provides new atomic-level insights into the molecular motion of heavy oil components under shear interaction in the presence of a toluene additive.

Advance of Microemulsion and Application for Enhanced Oil Recovery.

With the ongoing advancement in oil exploration, microemulsion, as an innovative oil displacement method, has garnered considerable attention owing to its exceptional physicochemical properties in enhancing crude oil recovery. As such, this study initially delineates the fundamental concepts, classifications, formation mechanisms, advantages, and preparation methodologies of microemulsions. Subsequently, it introduces the selection criteria for microemulsion components, followed by an elucidation of the characterization methods for microemulsions based on these criteria. Furthermore, it examines the factors influencing the efficacy of microemulsions in enhancing oil recovery through two distinct methods, along with the effects of various formulation microemulsions under laboratory and oilfield conditions. Additionally, it outlines prospects, challenges, and future development trends pertaining to microemulsions.

Structures and diversities of bacterial communities in oil-contaminated soil at shale gas well site assessed by high-throughput sequencing.

Currently, there is limited understanding of the structures and variabilities of bacterial communities in oil-contaminated soil within shale gas development. The Changning shale gas well site in Sichuan province was focused, and high-throughput sequencing was used to investigate the structures of bacterial communities and functions of bacteria in soil with different degrees of oil pollution. Furthermore, the influences of the environmental factors including pH, moisture content, organic matter, total nitrogen, total phosphorus, oil, and the biological toxicity of the soil on the structures of bacterial communities were analyzed. The results revealed that Proteobacteria and Firmicutes predominated in the oil-contaminated soil. α-Proteobacteria and γ-Proteobacteria were the main classes under the Proteobacteria phylum. Bacilli was the main class in the Firmicutes phylum. Notably, more bacteria were only found in CN-5 which was the soil near the storage pond for abandoned drilling mud, including Marinobacter, Balneola, Novispirillum, Castellaniella, and Alishewanella. These bacteria exhibited resilience to higher toxicity and demonstrated proficiency in oil degradation. The functions including carbohydrate transport and metabolism, energy metabolism, replication, recombination and repair replication, signal transduction mechanisms, and amino acid transport and metabolism responded differently to varying concentrations of oil. The disparities in bacterial genus composition across samples stemmed from a complex play of pH, moisture content, organic matter, total nitrogen, total phosphorus, oil concentration, and biological toxicity. Notably, bacterial richness correlated positively with moisture content, while bacterial diversity showed a significant positive correlation with pH. Acidobacteria exhibited a significant positive correlation with moisture content. Litorivivens and Luteimonas displayed a significant negative correlation with pH, while Rhizobium exhibited a significant negative correlation with moisture content. Pseudomonas, Proteiniphilum, and Halomonas exhibited positive correlations not only with organic matter but also with oil concentration. Total nitrogen exhibited a significant positive correlation with Taonella and Sideroxydans. On the other hand, total phosphorus showed a significant negative correlation with Sphingomonas. Furthermore, Sphingomonas, Gp6, and Ramlibacter displayed significant negative correlations with biological toxicity. The differential functions exhibited no significant correlation with environmental factors but displayed a significant positive correlation with the Proteobacteria phylum. Aridibacter demonstrated a significant positive correlation with cell motility and cellular processes and signaling. Conversely, Pseudomonas, Proteiniphilum, and Halomonas were negatively correlated with differential functions, particularly in amino acid metabolism, carbohydrate metabolism, and membrane transport. Compared with previous research, more factors were considered in this research when studying structural changes in bacterial communities, such as physicochemical properties and biological toxicity of soil. In addition, the correlations of differential functions of communities with environmental factors, bacterial phyla, and genera were investigated.

Kinematic analysis and process optimization of root-cutting systems in field harvesting of garlic based on computer simulation technology.

Introduction: Root cutting is an important process in garlic field harvesting but is the weakest link in the full mechanization of garlic production. To improve the current situation of technological backwardness and poor operational quality of mechanized garlic root-cutting in the main garlic-producing regions of China, this study combined the physical characteristics and agronomic requirements of garlic plants, and proposed an innovative floating root-cutting technology for garlic combine harvesters that enables the top alignment of bulb, adaptive profiling floating of cutter, and embedded cutting of roots. Methods: Through the kinematic analysis of the floating cutting process, the coordinate equations of the initial contact point of the bulb, the mathematical model of the floating displacement of the cutting component. Using computer simulation techniques, the dynamic simulation study of the floating cutting process was carried out in the rigid-flexible coupling numerical simulation model of root-cutting mechanism and garlic plant. The influence law of garlic conveying speed, extension spring preload force and stiffness on the floating displacement of the cutting component and the angular velocity of swing arm reset and its formation causes were analyzed by a single-factor simulation test. The key operating parameters of the root-cutting mechanism were optimized through the computerized virtual orthogonal test and fuzzy comprehensive evaluation. Results and discussion: The significance of the factors affecting the floating cutting performance decreased in the following order: extension spring preload force, garlic conveying speed and extension spring stiffness. The optimal parameter combination of the root cutting mechanism obtained from the optimization were as follow: extension spring preload force was 16 N, garlic conveying speed was 0.8 m/s, and extension spring stiffness was 215 N/m. Tests conducted with the optimal parameter combination yielded a root excision rate of 92.72%, which meets the requirements of Chinese garlic field harvesting quality. This study provides computer simulation optimization methods for the optimal design of the root-cutting mechanism, and also provides technical and equipment support for the full mechanization of garlic production in China.

Convolutional Neural Network for Object Detection in Garlic Root Cutting Equipment.

Traditional manual garlic root cutting is inefficient and can cause food safety problems. To develop food processing equipment, a novel and accurate object detection method for garlic using deep learning-a convolutional neural network-is proposed in this study. The you-only-look-once (YOLO) algorithm, which is based on lightweight and transfer learning, is the most advanced computer vision method for single large object detection. To detect the bulb, the YOLOv2 model was modified using an inverted residual module and residual structure. The modified model was trained based on images of bulbs with varied brightness, surface attachment, and shape, which enabled sufficient learning of the detector. The optimum minibatches and epochs were obtained by comparing the test results of different training parameters. Research shows that IRM-YOLOv2 is superior to the SqueezeNet, ShuffleNet, and YOLOv2 models of classical neural networks, as well as the YOLOv3 and YOLOv4 algorithm models. The confidence score, average accuracy, deviation, standard deviation, detection time, and storage space of IRM-YOLOv2 were 0.98228, 99.2%, 2.819 pixels, 4.153, 0.0356 s, and 24.2 MB, respectively. In addition, this study provides an important reference for the application of the YOLO algorithm in food research.

Structural characteristics of low-density environments in liquid water.

The existence of two structural forms in liquid water has been a point of discussion for a long time. A phase transition between these two forms of liquid water has been proposed based on evidence from molecular simulations, and experiments have also been very recently able to track the proposed transition of the low-density liquid form to the high-density liquid form. We propose to use the average angle an oxygen atom makes with its neighbors to describe the structural environment of a water molecule. The distribution of this order parameter is observed to have two peaks with one peak at ∼109.5^{∘}, corresponding to the internal angle of a regular tetrahedron, indicating tetrahedral arrangement. The other peak corresponds to an environment with a tighter arrangement of neighboring molecules. The distribution of O-O-O angles is decomposed into two skewed distributions to estimate the fractions of the two liquid forms in water. A good similarity is observed between the temperature and pressure trends of fractions of locally favored tetrahedral structure (LFTS) form estimated using the new order parameter and the reports in the literature, over a range of temperatures and pressures. We also compare the structural environments indicated by different order parameters and find that the order parameter proposed in this paper captures the structure of first solvation shell of the LFTS accurately.

Experimental Study of Garlic Root Cutting Based on Deep Learning Application in Food Primary Processing.

Garlic root cutting is generally performed manually; it is easy for the workers to sustain hand injuries, and the labor efficiency is low. However, the significant differences between individual garlic bulbs limit the development of an automatic root cutting system. To address this problem, a deep learning model based on transfer learning and a low-cost computer vision module was used to automatically detect garlic bulb position, adjust the root cutter, and cut garlic roots on a garlic root cutting test bed. The proposed object detection model achieved good performance and high detection accuracy, running speed, and detection reliability. The visual image of the output layer channel of the backbone network showed the high-level features extracted by the network vividly, and the differences in learning of different networks clearly. The position differences of the cutting lines predicted by different backbone networks were analyzed through data visualization. The excellent and stable performance indicated that the proposed model had learned the correct features in the data of different brightness. Finally, the root cutting system was verified experimentally. The results of three experiments with 100 garlic bulbs each indicated that the mean qualified value of the system was 96%. Therefore, the proposed deep learning system can be applied in garlic root cutting which belongs to food primary processing.

Multiple insights call for revision of modern thermodynamic models to account for structural fluctuations in water.

Modern thermodynamic models incorporate the concept of association (hydrogen bonding) and they can describe very satisfactorily many properties of water containing mixtures. They have not been successful in representing water's anomalous properties and this work provides a possible explanation. We have analyzed and interpreted recent experimental data, molecular simulation results, and two-state theory approaches and compared against the predictions from thermodynamic models. We show that the dominance of the tetrahedral structure implemented in modern thermodynamic models may be the reason for their failure for describing water systems. While this study does not prove the two-state theories for water, it indicates that a high level of tetrahedral structure of water is not in agreement with water's anomalous properties when used in thermodynamic models.

Distinguishing Weak and Strong Hydrogen Bonds in Liquid Water-A Potential of Mean Force-Based Approach.

The ability to form hydrogen bonds is one of the most important factors behind water's many anomalous properties. However, there is still no consensus on the hydrogen bond structure of liquid water, including the average number of hydrogen bonds in liquid water. We use molecular dynamics simulations of the polarizable iAMOEBA water model for investigating the hydrogen bond characteristics of liquid water over a wide range of temperatures and pressures. Geometric definitions of a hydrogen bond often use a rectangular region on the plane of hydrogen bond distances and angles. In this work, we find that an elliptical region is more appropriate for the identification of hydrogen bonds, based on statistically favorable molecular configurations. The two-dimensional potential of mean force (PMF) landscape along the hydrogen bond distance (O-H) and angle (O-H-O) is calculated for identifying the statistically favored molecular configurations, which is then used for defining hydrogen bond formation as well as the strength of a hydrogen bond. We further propose a new approach to characterize the hydrogen bonds as strong when the PMF is lower than -2 kT. Using this definition, a consistent explanation for the different average numbers of hydrogen bonds in water is obtained in agreement with the literature. Simulations are also performed with the rigid and nonpolarizable TIP4P/2005 water model. Both water models are qualitatively consistent in predicting the distribution of double-, single-, and non-donor configurations, in line with experimental data, while the iAMOEBA water model yields more quantitatively precise results, including a 10-15% double-donor fraction at 90 °C and 1 atm. The method is also demonstrated to be applicable to the recent, and more general, three-dimensional PMF-based definition of hydrogen bonds.

Hemishell Zeolites Synthesized by Asymmetric Modification as Biphasic Nanoreactors with Tunable Amphiphilicity for Catalysis of Cascade Reactions.

It is strongly desired to design and synthesize amphiphilic nanoreactors with tunable compatibility, which are stable at the biphasic interface in both acidic and alkaline environments. Herein, a novel amphiphilic R1-ZSM-5-R2 nanoreactor with adjustable hydrophilic-lipophilic balance (solid) (HLB(S)) values has been successfully synthesized by hydrophilic/lipophilic asymmetric modification of the surface of hemishell zeolites. The hemishell zeolites obtained by alkali etching have different surfaces for this asymmetric modification. Owing to the unique hemishell structures and asymmetric modification, the R1-ZSM-5-R2 nanoreactors with an optimized type and amount of modified organosilanes show excellent stability and emulsifying properties under extreme environments, which is important for cascade reactions in a biphasic system. The modified amino groups on the surface of the nanoreactors not only enhance the hydrophilicity of the hemishell zeolites and stabilize ultrasmall Pt nanoparticles (1.90 nm) but also used for the catalytic synthesis of trans-cinnamaldehyde. The Pt@R1-ZSM-5-R2 amphiphilic catalysts fabricated through a one-step reduction of Pt nanoparticles present outstanding performances in the biphasic cascade synthesis of cinnamic acid, achieving a very high turnover frequency (TOF) of 978 h-1. The TOF values of the catalysts correspond well to the HLB(S) values of the R1-ZSM-5-R2 nanoreactors.

Natural Halloysites-Based Janus Platelet Surfactants for the Formation of Pickering Emulsion and Enhanced Oil Recovery.

Janus colloidal surfactants with opposing wettabilities are receiving attention for their practical application in industry. Combining the advantages of molecular surfactants and particle-stabilized Pickering emulsions, Janus colloidal surfactants generate remarkably stable emulsions. Here we report a straightforward and cost-efficient strategy to develop Janus nanoplate surfactants (JNPS) from an aluminosilicate nanoclay, halloysite, by stepwise surface modification, including an innovative selective surface modification step. Such colloidal surfactants are found to be able to stabilize Pickering emulsions of different oil/water systems. The microstructural characterization of solidified polystyrene emulsions indicates that the emulsion interface is evenly covered by JNPS. The phase behaviors of water/oil emulsion generated by these novel platelet surfactants were also investigated. Furthermore, we demonstrate the application of JNPS for enhanced oil recovery with a microfluidic flooding test, showing a dramatic increase of oil recovery ratio. This research provides important insights for the design and synthesis of two-dimensional Janus colloidal surfactants, which could be utilized in biomedical, food and mining industries, especially for circumstances where high salinity and high temperature are involved.

Molecular Dynamics Simulation of Surfactant Flooding Driven Oil-Detachment in Nano-Silica Channels.

Recovery of crude oil in rock nanopores plays an important role in the petroleum industry. In this work, we carried out molecular dynamics (MD) simulations to study the process of ionic surfactant solution driven oil-detachment in model silica (SiO2) nanochannels. Our MD simulation results revealed that the oil-detachment induced by the ionic surfactant flooding can be described by a three-stage process including the formation and delivery of surfactant micelles, the surfactant micelle disintegration-spread and migration on the oil-aggregate surface, and oil molecular aggregate deformation-to-detachment. A flooding from rear (FFR) phenomenon is revealed that the surfactant molecules tend to migrate to the rear bottom of the oil molecular aggregate caused by the water flow effect and hydration of polar head groups of surfactants, which facilitate the penetration of water molecules into the oil-rock interface, and the oil molecule detachment occurs at the rear bottom of the oil molecular aggregate. The present MD simulation results also indicate that the dodecyl benzenesulfonate (SDBS) has higher oil-driven efficiency than that of dodecyl trimethylammonium bromide (DTAB). The difference of oil displacement efficiency between the two surfactants is attributed to the hydration property of the polar head groups. Compared with the -N(CH3)3+ headgroup in DTAB, the bare O atom in the -SO3- group has a stronger H bond interaction with the surrounding water molecules. The stronger interaction between the headgroup of SDBS and the adjacent water molecule results in the surfactant migrating to the rear bottom of the oil molecules more quickly, thus accelerating the detachment of oil molecules.

ARGET ATRP of Triblock Copolymers (PMMA-b-PEO-b-PMMA) and Their Microstructure in Aqueous Solution.

Triblock copolymers poly(methyl methacrylate)-b-poly(ethylene oxide)-b-poly(methyl methacrylate) (PMMA-b-PEO-b-PMMA) with designed molecular weight of PMMA and PEO blocks were synthesized via the activator regenerated by electron transfer (ARGET) atom transfer radical polymerization (ATRP) of MMA. The Br-terminated Br-PEO-Br with the molecular weights of 20k and 100k were used as  macroinitiators. ARGET ATRP was performed with ppm level amount CuBr2 as the catalyst and ascorbic acid as the reducing agent to overcome the sensitivity to oxygen in a traditional ATRP. The molecular weight of the PMMA block was manipulated by changing the molar ratio of monomers to the Br-PEO-Br macroinitiators. The synthesis of PMMA-b-PEO-b-PMMA and its structure was confirmed by Fourier transform infrared and 1H NMR, and the molecular weight of the PMMA block was determined by 1H NMR. Aqueous solutions of PMMA-b-PEO-b-PMMA were prepared by solvent-exchange, and their microstructures were examined by tensiometry, static light scattering, and transmission electron microscopy. The effects of molecular weight of the PMMA and PEO blocks on the microstructure were elucidated.