Amine Solutions Research Articles

Synthesis of amino acids in intense laser-irradiated primary amine solutions.

Mechanical interatomic bond formation under ultrahigh pressure induced by laser-driven shock waves has been demonstrated for C-C, C-O, and O-O bonds. In this study, molecules generated in primary amine solutions irradiated with high-intensity lasers were identified. When methylamine or ethylamine was dissolved in methanol or ethanol, molecules likely formed through C-C or O-N bonds between the amine and alcohol were detected. Additionally, molecules thought to be formed through the bonding of amines were confirmed. In mixed solutions of amine and formic acid, the formation of amino acids, such as glycine and alanine, which are presumed to result from C-C bond formation, was also confirmed. The generation of these molecules is attributed to mechanical bond formation due to the ultrahigh pressure generated by laser shock waves. This phenomenon is expected to offer a new perspective on the synthesis of complex organic molecules, particularly in relation to the origins of life in space and on Earth.

Thermal degradation of tertiary amine for CO2 capture: Structure–activity relationships and density functional theory calculations

AbstractAqueous amine solution is a promising absorbent for CO2 capture, yet irreversible reaction, that is, degradation can happen for amine and leads to performance decrease and many operating difficulties. Despite numerous research on reaction between amine and CO2 for absorption, the reaction of amine degradation is not fully understood, especially for tertiary amine which is a vital component in constructing high‐performance CO2 absorbent. Considering the variety of tertiary amines, this article studied the thermal stability of five tertiary amine solutions at different temperatures to mimic the regeneration condition. The density functional theory (DFT) calculation was applied to reveal the degradation mechanism. The alkylation reaction that triggered the degradation of tertiary amine was deemed as the limiting step. Then the molecular simulation method was extended to 12 tertiary amines, aiming to further illustrate the influence of molecular structure on the alkylation reaction. These results provide basic data and theoretical guidance for developing the anti‐degradation CO2 absorbent.

Soft-Rigid Construction of Mechanically Robust, Thermally Stable, and Self-Healing Polyimine Networks with Strongly Recyclable Adhesion.

Reversible and recyclable thermosets have garnered increasing attention for their smart functionality and sustainability. However, they still face challenges in balancing comprehensive performance and dynamic features. Herein, silicon (Si)─oxygen (O) and imidazole units covalent bonds are coupled to generate a new class of bio-polyimines (Bio-Si-PABZs), to endow them with high performance and excellent reprocessing capability and acid-degradability. By tailoring the molar content of diamines, this Bio-Si-PABZs displayed both a markedly high glass transition temperature (162°C) and a high char yield at 800°C in an oxygen atmosphere (73.1%). These Bio-Si-PABZs with their favorable properties outperformed various previously reported polyimines and competed effectively with commercial fossil-based polycarbonate. Moreover, the scratch (≈10µm) on the surface of samples can be self-healing within only 2min, and an effective "Bird Nest"-to-"Torch" recycling can also be achieved through free amines solution. Most importantly, a bio-based siloxane adhesive derived from the intermediate Bio-Si-PABZ-1 by acidic degradation demonstrated broad and robust adhesion in various substrates, with values reaching up to ≈3.5MPa. For the first time, this study lays the scientific groundwork for designing robust and recyclable polyimine thermosets with Si─O and imidazole units, as well as converting plastic wastes into thermal-reversibility and renewable adhesives.

Selective SNH Alkylamination of 3(5,6,7,8)‐Nitroquinoline and 5‐Nitroisoquinoline in an Aqueous Medium

AbstractDirect oxidative SNH alkylamination of 3‐, 5‐, 6‐, 7‐, 8‐nitroquinolines and 5‐nitroisoquinoline in an aqueous solution of an aliphatic amines gives rise to the corresponding alkylamino and dialkylamino derivatives of these nitrohetarenes. The nitro group solely dictates the regioselectivity of reactions. The antibacterial activity of some of them has been studied.

Origin of Copper Dissolution in Electrocatalytic Reduction Conditions Involving Amines

Cu dissolution has been identified as the dominant process that causes cathode degradation and losses even under cathodic conditions involving . Despite extensive experimental research, our fundamental and theoretical understanding of the atomic-scale mechanism for Cu dissolution in electrochemical conditions, eventually coupled with surface restructuring processes, is limited. Here, driven by the observation that the working Cu electrode is corroded using mixtures of acetone and methylamine even under reductive potential conditions (-0.75V vs RHE), we employed Grand Canonical density functional theory to understand this dynamic process under potential from a microscopic perspective. We show that amine ligands in solution directly adsorb on the electrode, coordinate with the metal center, drive the rearrangement of the copper surface by extracting Cu atoms in low coordination positions, where other ligands can coordinate and stabilize a surface copper-ligands complex, finally forming a detached Cu-tetramine di-cation complex in solution, even at negative potential conditions. Calculations predict that dissolution would occur for a potential of -0.7 V vs RHE or above. Our work provides a fundamental understanding of Cu dissolution facilitated by surface restructuring in amine solutions under electroreduction conditions, which is required for the rational design of durable Cu-based cathodes for electrochemical amination or other amine involving reduction processes.

Assessment of mass transfer performance using the two-film theory and surrogate models for intensified CO2 capture process by amine solutions in rotating packed beds

CO2 capture is a crucial aspect of attempts to mitigate climate change. The purpose of this study is to investigate the impacts of essential operating parameters on the mass transfer performance of absorbing CO2 in rotating packed beds (RPBs). A multilayer perceptron neural network (MLPNN) model with the Levenberg-Marquardt learning algorithm, a mass transfer model using the two-film theory, and an empirical correlation model were developed to predict the overall gas-phase volumetric mass-transfer coefficient (KGaV) for RPB-based CO2 absorption. The developed MLPNN model showed excellent agreement with the actual data, with an MSE of 0.0357, an AARD of 7.4%, and an R2 of 0.9839. A sensitivity analysis was conducted using Taguchi orthogonal array design on distinct mass transfer correlations. The results of the two-film theory and surrogate models for the diethylenetriamine (DETA) solvent were compared. The MLPNN model provided better predictions than other developed models with an AARD of 13% for CO2H2O-DETA system. Therefore, the effects of operating parameters such as concentration, temperature, solvent flow rate, and rotational speed on KGaVand CO2 removal efficiency were evaluated using the MLPNN model. Finally, an empirical correlation was proposed to predict KGaVas a function of operational parameters.

Compartmental modeling of CO2 absorption in a rotating packed bed

Capturing carbon dioxide (CO2), i.e., the primary greenhouse gas that contributes to climate change, from CO2 containing gas mixtures in various industrial sectors, e.g., natural gas processing and treating refinery off-gases, is necessary. Rotating packed beds (RPBs) have shown great efficiency in CO2 capture from flue gases with an appreciable intensification in the absorber size compared to the conventional packed bed absorbers. Successful commercialization of an RPB technology requires a comprehensive understanding of its performance under various operating conditions, process configurations, and for different solvents. In this study, we presented a mathematical model describing the performance of an RPB absorber for CO2 capture by aqueous amine solutions. We established the compartmental model based on two plug-flow reactors for gas and liquid phases. We validated this model adopting two sets of experimental data from literature. We considered reaction rates of all compounds in the system in the model. We, subsequently, employed the validated model to highlight the potential parameters in enhancing the overall CO2 recovery by an RPB absorber. The developed model takes advantage of acquired knowledge and data from literature based on years of numerical studies on RPBs. We studied the effects of operating conditions, such as inlet gas and liquid flow rates, amine fraction, rotating speed, and inlet liquid and gas temperatures on the performance of an RPB by the validated model. Although we initially developed the model for the CO2-monoethanolamine (MEA) solvent, we also studied the effect of changing the solvent to methyl diethanolamine (MDEA) and piperazine (PZ) on the overall absorption performance of an RPB absorber. We further adopted the developed model as a design tool to assist us in replacing a pilot- and an industrial-scale packed bed absorber with corresponding single RPB absorbers.

One-step synthesis of SO42−/ZrO2‑SEP solid-acid catalyst for energy-efficient CO2 capture

The application of solid-acid catalysts in the regeneration process of CO2-rich amine solutions is currently considered as a promising method for reducing the relative heat duty of CO2 capture processes. In this study, sepiolite (SEP) was selected as a cost-efficient catalyst carrier to support the solid superacid SO42-/ZrO2 (SZ) for preparing a series of composite SO42−/ZrO2‑SEP (SZ@SEP) catalysts with different SZ/SEP ratios. The physical–chemical properties of the prepared catalysts were carefully studied using various characterization techniques. The catalytic CO2 desorption performance was tested in the conventional 5 M MEA solution at 88 °C. The amount of desorbed CO2, desorption rate and relative heat duty were accurately measured for each catalyst and a potential catalytic reaction mechanism was proposed. The results indicated that all catalysts significantly enhanced CO2 desorption performance. Specifically, SZ@SEP-1/2 achieved a 37.3 % increase in average desorption rate and a 48.6 % decrease in heat duty compared to the blank solvent. Furthermore, SZ@SEP-1/2 demonstrated excellent stability over 20 cycles, suggesting its potential as an energy-efficient catalyst for CO2 capture.

Rapid solvent transport and tunable molecular sieving enabled by ultrathin alkyl-chain-engineered polyamide membranes

Organic solvent nanofiltration (OSN) has emerged as a promising separation technology for the chemical and pharmaceutical industries due to its low energy consumption and eco-friendliness. However, traditional polyamide-based membranes used in OSN often exhibit low permeance for organic solvents and it is difficult to precisely control the pore structure. In this study, we report a facile approach to fabricate ultrathin alkyl-chain-engineered polyamide nanofilms via free-standing interfacial polymerization for high-performance selective separations. The membranes were prepared via a “two birds one stone” strategy, enabled by post-treatment in aliphatic amine solution, simultaneously regulating the pore size and optimizing the membrane chemical property. This enables the membrane with high solvent permeance, especially for non-polar solvents (heptane at ∼22.2 L m−2h−1 bar−1, toluene at ∼16.8 L m−2h−1 bar−1), while maintaining excellent molecular sieving capability. Notably, the molecular weight cut-off (MWCO) can be regulated by introducing alkyl chains of varying lengths to their pores. The exceptional solvent permeance and tunable molecular sieving property make the membranes promising for high value-added products purification in the pharmaceutical industry and crude oil separation.

Parameters of Collision and Adhesion Process Between a Rising Bubble and Quartz in Long-Chain Amine Solution and Their Correlation with Flotation

The successful adhesion of air bubbles to mineral particles is the crucial to flotation technology. This paper systematically investigates the parameters variation in the dynamic interaction process between a rising bubble and a quartz plate in long-chain amine solutions (dodecylamine, tedecylamine, and octadecylamine). The results show that the type and concentration of long-chain amine affected the collision and adhesion process between bubbles and quartz plates remarkably. The maximum rebound distance (rebound distance after the first collision) of bubbles and the stable-state liquid film thickness gradually decreases with the increase of reagent concentration. Additionally, the collision-rebound duration and induction time shorten accordingly, the surface tension of the solution decreases, the surface hydrophobicity of quartz increases, and the deformation degree and average movement velocity of bubbles decrease. With the increase in carbon chain length, the adsorption form of the amine collector and quartz surface becomes closer to vertical, and the density of water molecules decreases. The recovery of quartz particles is highest with octadecylamine systems, corresponding well with the changing trend in steady-state liquid film thickness. This research provides an effective method for in-depth analysis of the microscopic interaction mechanism between bubbles and mineral surfaces and the prediction of flotation results.

Predictive modeling of CO2 capture efficiency using piperazine solutions: a comparative study of white-box algorithms

The urgency to mitigate carbon dioxide (CO2) emissions and combat climate change has spurred the development of effective CO2 capture technologies. One of the industry’s most well-known CO2 collection processes is CO2 absorption utilizing amine solvents. However, designing a successful amine scrubbing system in power plants requires precise prediction of CO2 absorption in aqueous amine solutions under various operating circumstances. Using aqueous piperazine (PZ) solutions for chemical absorption is promising due to the favorable reactivity of PZ with CO2. In this study, a comprehensive evaluation of PZ solution performance in CO2 capturing, employing the white-box algorithms, namely, Genetic Programming (GP), Gene Expression Programming (GEP), and Group Method of Data Handling (GMDH), was performed. Through extensive experimentation and data analysis, several correlations were developed with high and acceptable R2 values, such as 0.933 for GP, 0.949 for GEP, and 0.889 for GMDH, which shows high accuracy and reliability in predicting the CO2 capture efficiency of PZ solutions under varying operating conditions. The results of sensitivity analysis revealed that CO2 partial pressure increased CO2 absorption, while PZ concentration and temperature had negative and decreasing effects. These insights provide essential guidance for optimizing process conditions to enhance the CO2 capture efficiency. Finally, the leverage method was used to assess the reliability of both experimental and predicted data from white-box algorithms. This analysis identified potential outliers and validated the accuracy of the model’s predictions, enhancing the credibility of developed correlations and demonstrating the robustness of the approach.

Modeling CO2 loading capacity of triethanolamine (TEA) aqueous solutions via a deep learning approach

Capturing carbon dioxide (CO2) from natural gas is essential for reducing CO2 emissions as a greenhouse gas as well as increasing the gas heating value. Absorption of CO2 by amine solutions is a method that has seen a widespread use as a CO2 collection technique. In this research, advanced ML approaches are utilized to simulate the CO2 loading capacity of triethanolamine (TEA) aqueous solutions as a function of system temperature, CO2 partial pressure, and amine concentration in the aqueous phase. Deep neural network (DNN), Gaussian process regressor (GPR), deep belief network (DBN), and bagging regressor (BR) are the models that have been developed. The DNN model with the coefficient of determination (R2) of 0.9990 as well as the root mean square error (RMSE) of 0.0073 outperformed other models in terms of accuracy and validity. The R2 values of 0.9911, 0.9861, and 0.9745 for DBN, BR, and GPR, accordingly, showed that other models could likewise perform with high accuracy. Moreover, trend analysis of the results confirmed that the DNN method can correctly estimate the behavior of CO2 loading with variations in the input parameters. Furthermore, sensitivity analysis showed that temperature has a decreasing effect on the CO2 loading, while amine concentration and CO2 partial pressure exhibited to have an incremental effect. Herein, the temperature had the greatest influence on the amount of CO2 loading. The final stage of the research was the leverage approach, which stated that about 99 % of the data are statistically valid and the DNN model is reliable to be replaced by experimental approaches in the prediction of CO2 absorption into certain type of solutions.

Направления совершенствования сероочистки, осушки и переработки природного газа

The results of the work of the staff of the Department of “Chemical Technology of Oil and Gas Refining” of Astrakhan State Technical University in the field of separation of three-phase reservoir mixture, increasing the efficiency of desulfurization, improving the process of drying gas and the production of continuous hydrocarbons – raw materials for petrochemistry. The influence of the quality of raw materials entering processing on the formation of deposits in technological equipment has been studied. Reconstruction of the inlet and three-phase separators of high-pressure reservoir mixture separation plants by installing a vibration damper and a depulsor on the reservoir mixture supply line to the installation, as well as reconstruction of the input of raw materials into the separator of the installation. The use of the KPG-200 defoamer and the KPG-200 AV antifoamer made it possible to reduce the consumption rate of defoaming reagents several times in gas purification plants from acidic components. The influence of various impurities on the foaming of working amine solutions (mechanical impurities, coal dust, products of thermal destruction of amine, thermostable salts, corrosion inhibitors) has been determined. It was revealed that the products of thermal degradation of amine have the greatest effect at concentrations above 3% by weight. A method for reducing the content of mechanical impurities in a solution of diethanolamine in a constant magnetic field has been developed and introduced into an industrial desulfurization plant. The filtration efficiency increases 2.6 times, the foam height is halved, and the foam stability is quadrupled. At the same time, the activity of the defoamer increases by 1.7 times. The mathematical dependence of the height of the protective layer of aluminum oxide in an adsorber with zeolite on impurities of diethanolamine has been experimentally found. The effectiveness of the developed improved distribution ring device is shown, the use of which makes it possible to practically eliminate dead zones in the zeolite layer and thereby increase the efficiency of the adsorption process and increase the inter-regeneration period on the drying unit. Studies of the catalytic pyrolysis of the butane fraction using CVM-type pentasils modified with the introduction of chromium can reduce the process temperature compared with the thermal decomposition of raw materials by more than one hundred degrees 100 °C.

Experimental investigation of CO2 capture at high pressure using energy-efficient amino acid salt solvents

The increase in energy consumption has led to greenhouse gas emissions, specifically CO2. This has caused many researchers to explore the possibility of capturing CO2 emissions. The utilization of typical water-based solvents, such as amine solutions, poses challenges in large-scale operations owing to the substantial energy consumption associated with their regeneration process. To decrease the energy required to regenerate the solvent, new types of phase change solvents, known as lean water amino acid-based phase change solvents, were invented. This study investigated the absorption capacity of an amino acid salt made up of glutamine and potassium hydroxide in a water-based solution including N,N-dimethylformamide (DMF) as a co-solvent. The measurement of absorption capacity was conducted under elevated pressures ranging from 5 to 30 bar. Additionally, an investigation was conducted to assess the impact of DMF volumetric concentration on absorption capacity. The findings of the study indicated that augmenting both the pressure and concentration of DMF increased the capacity for CO2 absorption. This enhancement was achieved by simultaneously raising the rates of physical and chemical absorption. The results obtained from the C NMR phase analysis revealed that the solid phase had carbon bonds that were related to the absorption of CO2, whilst the upper liquid phase did not contain any CO2. This phase might readily be recycled into the absorption process without the need for regeneration. The absorption capacity of this solvent was also assessed following three absorption-reduction cycles. The results indicated a decrease in absorption capacity by only 6.6 %.

CO2 gas-liquid equilibrium study and machine learning analysis in MEA-DMEA blended amine solutions

The combination of primary and tertiary amines represents a promising approach to improve sorbent performance in CO2 capture by enhancing absorption efficiency and reducing regeneration energy. This study focuses on investigating the absorption performance of binary mixtures of ethanolamine (MEA) and N,N-dimethylethanolamine (DMEA) at temperatures between 298–323 K and CO2 partial pressures between 5–60 kPa. The species generated during the absorption were analyzed using 13C NMR spectroscopy, to clarify the intricate role of MEA and DMEA in the capture process. A developed excess property model for MEA-DMEA, based on excess CO2 loading, predicted equilibrium CO2 solubility data with an average absolute relative deviation (AARD) of 1.6 %. Additionally, the machine learning models XGBoost, RBFNN, and SVR were applied, providing AARD values between 0.86 % and 1.28 %, demonstrating strong agreement between experimental and predicted outcomes. These comprehensive findings enhance our understanding of mixed amines’ mechanisms and practical applications, contributing to ongoing research development.

Predictive modeling of CO2 solubility in piperazine aqueous solutions using boosting algorithms for carbon capture goals

Carbon dioxide (CO2) is the main greenhouse gas that drives global warming, climate change, and other environmental issues. CO2 absorption using amine solvents stands out as one of the most well-known industrial technologies of CO2 capture. However, accurate prediction of CO2 absorption in aqueous amine solutions under different operating conditions is crucial for designing an efficient amine scrubbing system in power plants. In this work, CO2 solubility in aqueous piperazine (PZ) solutions was modeled using 517 experimental data points covering a temperature range of 298 to 373 K, PZ concentration of 0.1 to 6.2 mol/L (M), and CO2 partial pressure of 0.03 to 7399 kPa. To this end, four robust machine learning algorithms, including gradient boosting with categorical features support (CatBoost), light gradient boosting machine (LightGBM), extreme gradient boosting (XGBoost), and adaptive boosting decision trees (AdaBoost-DT) were utilized. Among the developed models, the CatBoost model presented the highest accuracy with an overall determination coefficient (R2) of 0.9953 and an average absolute relative error of 2.36%. Sensitivity analysis revealed that CO2 partial pressure had the greatest influence on CO2 absorption in aqueous PZ solutions, followed by PZ concentration and temperature. Moreover, CO2 partial pressure positively influenced CO2 absorption in aqueous PZ solutions, while PZ concentration and temperature exhibited negative effects. Finally, the leverage technique indicated that both the experimental data bank used for modeling and the model’s estimates were statistically acceptable and valid showing only 8 points (∼1.5% of total data) as possible suspected data.

Fluorescent-based bile acid triazole-phenothiazine derivatives: Multiphase detection of biogenic amines and application in spoiled foods

Amines are ubiquitous in biological world, yet are toxic and harmful in nature. To preserve the quality and safety of these packaged meals, it’s critical to identify biogenic amines that are emitted from spoiled meat, fish, or dairy products. To this endeavour, herein we report bile acid based triazole derivative with phenothiazine that are capable of sensing various amines by rapid change of fluorescence colour or intensity. The triazole derivatives exhibit a multiphase sensing platform by effectively sensing amine vapours or solutions in both solid and solution phases. Probes in the vapour state exhibit very quick interaction to primary amines (26 s for CTPTZ) and strong sensitivity to putrescine, which is a common example of biogenic amines (BAs). We have employed our unique sensing triazole derivative as a spoilage indication for meat. It detects biogenic amines from spoiled food and produces an optical response. Significant changes in both visual and luminescent were noted within 4–18 h of packaging at room temperature (∼25 °C). The rapid response that biogenic amines provide to these molecular sensors makes them highly promising for applications in the food packaging industry, medical diagnostics, and other sensory devices.

CO2 capture performance of AMP-EAE amine blends: Absorption in the microchannel and desorption from saturated solutions

Blended organic amine solutions are considered an effective strategy for developing highly efficient and low energy-consuming absorbents due to the possibility of combining the advantages of single amine. The 2-amino-2-methyl-1-propanol (AMP) and 2-(ethylamino)ethanol (EAE) amine blends were prepared in three molar ratios: blend-1 (nAMP:nEAE = 3:1), blend-2 (nAMP:nEAE = 1:1), and blend-3 (nAMP:nEAE = 1:3). The impacts of gas-liquid flow rate, amine concentration, molar ratio, temperature, and CO2 concentration on absorption performance were investigated using the serpentine microchannel. Additionally, the effects of amine concentration and molar ratio on the desorption performance of saturated solutions were also explored. The performance of amine blends in absorption and desorption was evaluated by measuring absorption rate, efficiency, and loading, as well as desorption efficiency, energy consumption, cycle capacity, and average desorption rate. The desorption results were compared to those of the benchmark solvent, 30 wt% MEA, under identical operating conditions. The results indicate that the 25 wt% blend-2 solution performs exceptionally well, exhibiting a 15 % increase in absorption efficiency compared to the AMP aqueous solution at a gas-liquid ratio of 20. Additionally, the cycle capacity and average desorption rate are 1.7 times higher than those of the 30 wt% MEA solution. Notably, the energy consumption of the 25 wt% blend-2 solution for desorption is only 60 % of the 30 wt% MEA solution.

Silicon quantum dot-enhanced thin-film nanocomposite membranes for efficient alcohol dehydration via pervaporation: A sustainable approach

This study explores the effectiveness of silicon quantum dots (SiQDs)—specifically, amine-functionalized (NSiQDs) and amine-hydroxyl-functionalized (NOSiQDs)—in optimizing thin-film nanocomposite (TFN) membranes for pervaporation dehydration of various alcohols. The SiQDs were integrated into the membranes via an innovative interfacial polymerization technique, involving the dispersion of SiQDs in an aqueous amine solution followed by polymerization with trimesoyl chloride. This approach ensured uniform integration of SiQDs, significantly enhancing the nanostructure and surface characteristics of the membranes. Such modifications led to improved water transport capabilities, substantially boosting pervaporation efficiency. Exceptional performance was demonstrated by the TFN-NOSiQDs(400) membranes, which achieved a peak permeation flux of 4195.8 g·m−2·h−1 and maintained over 99 wt% water concentration in the permeate when tested with a 70 wt% isopropanol/water solution at 25°C. Comprehensive long-term stability assessments confirmed the robustness and consistent functionality of the membranes, highlighting their suitability for industrial applications that demand reliable and efficient alcohol separation processes.

Systematic Study on Swelling/Delamination of Layered Metal Oxides with Quaternary Ammonium Ions: Production of Well-Shaped/Oversized Unilamellar Nanosheets.

Enormous swelling of layered host compounds in an aqueous solution of various amines has been investigated as an important step in the synthesis of molecularly thin 2D nanosheets. However, a complete understanding of the reaction process has not been attained, which is the barrier for producing high-quality unilamellar nanosheets. Here, the swelling and delamination behaviors of platelet single crystals of protonated layered metal oxides are systematically examined with a series of tetraalkylammonium (TAA) hydroxide solutions. Upon contact with the solutions, the crystals immediately underwent massive expansion by several tens to hundreds of times. The swollen crystals can be delaminated into elementary layers by the application of external shear force. The exfoliation behavior is dependent on TAA ions, especially in terms of yield and lateral size/shape of the delaminated nanosheets. The swollen crystals with TAA ions with longer alkyl chains are delaminated almost completely, but irregular and fractured small sheets are yielded. Such long alkyl chains become entangled on the oxide layer and resulting hydrophobic interactions may be responsible for the lateral fragmentation. It is found that replacement of aqueous solutions with organic solvents to suppress the hydrophobic interactions is effective to produce oversized nanosheets in rectangular shape with sharp edges.