Molecules In Aqueous Solution Research Articles

Spontaneous Generation of -CH2CN from Acetonitrile at the Air-Water Interface.

Acetonitrile (CH3CN) is considered a very stable molecule in aqueous solutions, and its deprotonation to produce strongly basic -CH2CN requires harsh conditions. CH3CN is also present in the atmosphere, but its chemical transformation pathway at the air-water interface is unknown. In this study, we discovered and verified the unprecedented spontaneous generation of -CH2CN from the CH3CN-H2O solution at the air-water interface of microdroplets, and revealed the indirect deprotonation mechanism of CH3CN by synergistic redox of •OH and electrons in the microdroplets through the capture of key intermediates and computational chemistry. In addition, the dynamic process of indirect deprotonation-protonation was also observed. The high reactivity of -CH2CN in the droplets was revealed via nucleophilic addition to acetone, benzaldehyde, and the parent CH3CN molecule. Furthermore, the -CH2CN generated in the microdroplets underwent a barrier-free nucleophilic addition reaction with CO2 to produce 2-cyanoacetic acid for CO2 fixation. The synergistic redox reaction process revealed in this study provides new insights into microdroplet chemistry, and the distinctive CH3CN reactions identified may provide new clues to unravel the mystery of the CH3CN transformation in the atmospheric environment.

Synthesis of porous carbons for the fixing of cationic molecules in aqueous solution

In Africa, the calyxes of the Hibiscus sabdariffa are widely used to produce a fresh fruit juice, known in Benin as bissap. The stems from this production have no potential use and are therefore an environmental problem. The parietal composition of these stalks revealed a high level of lignin (31 ± 1 %) and cellulose (35 ± 1 %). They can therefore be converted into activated carbon for various applications. In this study, the stems were transformed into activated carbons at moderate temperature using orthophosphoric acid (H3PO4) as the activating agent. The physicochemical, structural, and textural properties were determined. Adsorption kinetics and isotherms were studied and modelled. Porous carbons give specific surface areas equal to 1066 and 1053 m2.g−1 respectively for 2:1 and 4:1 ratios according to the B.E.T-Rouquerol model. Similarly, the said porous carbons give specific surface areas equal to 991 and 975 m2.g−1 respectively for 2:1 and 4:1 ratios according to the 2D-NLDFT model. Using the latter model, the pore size distribution is predominantly microporous, with the Vµ/VT (%) ratio increasing to 56 %. Thermogravimetric analysis of the porous coals showed favourable fixed carbon levels (≈ 60 %). The adsorption kinetics of methylene blue on activated carbons is governed by the pseudo-second order kinetic model indicating that the dye adsorption process is globally controlled by chemisorption. The results of the modelling of the methylene blue adsorption isotherms shown that the Langmuir model is the most credible model that best describes these experimental results, with 588 and 526 mg.g−1. These activated carbons are good candidates for the development of bio-sourced filters for the treatment of industrial wastewater.

Graph transformer based transfer learning for aqueous pKa prediction of organic small molecules

The acid-base dissociation constant (pKa) is an essential physicochemical parameter that indicates the extent of proton dissociation. However, accurately predicting pKa values is still challenging due to limited data availability for organic small molecules in aqueous solutions. In this work, we propose an open-source pKa prediction tool based on Graph Transformer, which combines the graph neural network and transformer to take both local and global information into account. To address the limitation of data scarcity, the experimental dataset is expanded, while transfer learning is employed by pre-training on the ChEMBL (computational) dataset and fine-tuning on the experimental dataset. The performance and generalization of the obtained models are comprehensively evaluated on both internal and external test sets. Additionally, two exemplary applications, namely the screening of tertiary amines for CO2 absorption and acidic ionic liquids for reactive extraction, are investigated to validate the reliability of our tool. The results show that our model can effectively guide the identification of promising candidates for the target applications by achieving accurate pKa predictions.

Exploring the Application of Terahertz Metamaterials Based on Metallic Strip Structures in Detection of Reverse Micelles.

Terahertz spectroscopy has unique advantages in the study of biological molecules in aqueous solutions. However, water has a strong absorption capability in the terahertz region. Reducing the amount of liquid could decrease interference with the terahertz wave, which may, however, affect the measurement accuracy. Therefore, it is particularly important to balance the amount and water content of liquid samples. In this work, a terahertz metamaterial sensor based on metallic strips is designed, fabricated, and used to detect reverse micelles. An aqueous confinement environment in reverse micelles can improve the signal-to-noise ratio of the terahertz response. Due to "water pool" trapped in reverse micelles, the DOPC (1,2-dioleoyl-sn-glycero-3-phosphocholine) solution and DOPC emulsion can successfully be identified in intensity by terahertz spectroscopy. Combined with the metamaterial sensor, an obvious frequency shift of 30 GHz can be achieved to distinguish the DOPC emulsion (5%) from the DOPC solution. This approach may provide a potential way for improving the sensitivity of detecting trace elements in a buffer solution, thus offering a valuable toolkit toward bioanalytical applications.

Predictions of Colloidal Molecular Aggregation Using AI/ML Models.

To facilitate the triage of hits from small molecule screens, we have used various AI/ML techniques and experimentally observed data sets to build models aimed at predicting colloidal aggregation of small organic molecules in aqueous solution. We have found that Naïve Bayesian and deep neural networks outperform logistic regression, recursive partitioning tree, support vector machine, and random forest techniques by having the lowest balanced error rate (BER) for the test set. Derived predictive classification models consistently and successfully discriminated aggregator molecules from nonaggregator hits. An analysis of molecular descriptors in favor of colloidal aggregation confirms previous observations (hydrophobicity, molecular weight, and solubility) in addition to undescribed molecular descriptors such as the fraction of sp3 carbon atoms (Fsp3), and electrotopological state of hydroxyl groups (ES_Sum_sOH). Naïve Bayesian modeling and scaffold tree analysis have revealed chemical features/scaffolds contributing the most to colloidal aggregation and nonaggregation, respectively. These results highlight the importance of scaffolds with high Fsp3 values in promoting nonaggregation. Matched molecular pair analysis (MMPA) has also deciphered context-dependent substitutions, which can be used to design nonaggregator molecules. We found that most matched molecular pairs have a neutral effect on aggregation propensity. We have prospectively applied our predictive models to assist in chemical library triage for optimal plate selection diversity and purchase for high throughput screening (HTS) in drug discovery projects.

The Dependence of Hydrophobic Interactions on the Shape of Solute Surface.

According to our recent studies on hydrophobicity, this work is aimed at understanding the dependence of hydrophobic interactions on the shape of a solute's surface. It has been observed that dissolved solutes primarily affect the structure of interfacial water, which refers to the top layer of water at the interface between the solute and water. As solutes aggregate in a solution, hydrophobic interactions become closely related to the transition of water molecules from the interfacial region to the bulk water. It is inferred that hydrophobic interactions may depend on the shape of the solute surface. To enhance the strength of hydrophobic interactions, the solutes tend to aggregate, thereby minimizing their surface area-to-volume ratio. This also suggests that hydrophobic interactions may exhibit directional characteristics. Moreover, this phenomenon can be supported by calculated potential mean forces (PMFs) using molecular dynamics (MD) simulations, where different surfaces, such as convex, flat, or concave, are associated with a sphere. Furthermore, this concept can be extended to comprehend the molecular packing parameter, commonly utilized in studying the self-assembly behavior of amphiphilic molecules in aqueous solutions.

Investigations on the Equilibrium, Kinetics and Thermodynamics of Anionic Polyacrylamide-Based Monolith Adsorption of Uranium (VI) From Aqueous Solution

Our previous work discussed synthesizing and characterizing a macroporous anionic polyacrylamide monolith as a new adsorbent. This monolith showed the potential removal of heavy metals and organic dye molecules in aqueous solutions. In this work, we continue our work and study the effectiveness of the synthesized monoliths in removing uranyl ions (UO22+) from aqueous solutions. Our investigation conclusively determined the impact of pH, contact time, monolith dosage, initial metal concentration and temperature on removing uranyl ions. Several isotherm models, including the Langmuir, Freundlich, Temkin and Dubinin-Radushkevich models, were employed to analyze the adsorption data; the Freundlich and Langmuir models were the most suitable for describing the equilibrium data. According to the Langmuir model, the monolith has an adsorption capacity of 111 mg/g of uranyl ions at 25 °C. The pseudo-second-order kinetic model was suitable for describing the uranyl ion adsorption onto the synthesized monolith with an R2 coefficient ³ 0.999. The thermodynamic studies showed that uranyl ions adsorb onto the monolith spontaneously and endothermically.

Concentration-Dependent Diffusion of Monoclonal Antibodies: Underlying Mechanisms of Anomalous Diffusion.

The development, storage, transport, and subcutaneous delivery of highly concentrated monoclonal antibody formulations pose significant challenges due to the high solution viscosity and low diffusion of the antibody molecules in crowded environments. These issues often stem from the self-associating behavior of the antibody molecules, potentially leading to aggregation. In this work, we used a dissipative particle dynamics-based coarse-grained model to investigate the diffusion behavior of IgG1 antibody molecules in aqueous solutions with 15 and 32 mM NaCl and antibody concentrations ranging from 10 to 400 mg/mL. We determined the coarse-grained interaction parameters by matching the calculated structure factor with the computational and experimental data from the literature. Our results indicate Fickian diffusion for antibody concentrations of 10 and 25 mg/mL and anomalous diffusion for concentrations exceeding 50 mg/mL. The anomalous diffusion was observed for ∼0.33 to 0.4 μs, followed by Fickian diffusion for all antibody concentrations. We observed a strong linear correlation between the diffusion behavior of the antibody molecules (diffusion coefficient D and anomalous diffusion exponent α) and the amount of aggregates present in the solution and between the amount of aggregates and the Coulomb interaction energy. The investigation of underlying mechanisms for anomalous diffusion revealed that in crowded environments at high antibody concentrations, the attractive interaction between electrostatically complementary regions of the antibody molecules could further bring the neighboring molecules closer to one another, ultimately resulting in aggregate formation. Further, the Coulomb attraction can continue to draw more molecules together, forming larger aggregates.

Quantitative Analysis of Trace Analytes with Highly Sensitive SERS Tags on Hydrophobic Interface.

Surface-enhanced Raman scattering (SERS) presents a promising avenue for trace matter detection by using plasmonic nanostructures. To tackle the challenges of quantitatively analyzing trace substances in SERS, such as poor enrichment efficiency and signal reproducibility, this study proposes a novel approach using Au@internal standard@Au nanospheres (Au@IS@Au NSs) for realizing the high sensitivity and stability in SERS substrates. To verify the feasibility and stability of the SERS performances, the SERS substrates have exhibited exceptional sensitivity for detecting methyl blue molecules in aqueous solutions within the concentration range from 10-4 M to 10-13 M. Additionally, this strategy also provides a feasible way of quantitative detection of antibiotic in the range of 10-4 M to 10-10 M. Trace antibiotic residue on the surface of shrimp in aquaculture waters was successfully conducted, achieving a remarkably low detection limit of 10-9 M. The innovative approach has great potential for the rapid and quantitative detection of trace substances, which marks a noteworthy step forward in environmental detection and analytical methods by SERS.

Boron nitride nanosheets modified BiOBr photocatalysts for promoting photocatalytic removal of tetracycline under visible light irradiation

A series of BN/BiOBr heterojunctions was constructed using in situ hydrothermal-precipitation method and was employed to remove the tetracycline molecules in aqueous solution. The rate of photocatalytic degradation efficiency of tetracycline by 0.05BN/BiOBr was ensured to be more excellent than that by BiOBr. The heterojunciton fabricated between BN and BiOBr enforced an internal electrons transfer from BiOBr to BN, which remarkably inhibited charge recombination. The major reactive species involved in the photocatalysis system were found to be hydroxyl radicals (•OH) and photo-holes (h+), which was verified by the scavenger tests. 0.05-BN/BiOBr heterojunctions showed remarkable reusability and still could degrade 89.25% of tetracycline after four consecutive cycles. According to the characterization and experimental results, a plausible enhanced photocatalytic mechanism was put forward. This work provided the guidance for rational designing heterojunctions with remarkable performance towards antibiotics elimination from wastewater.

Physico-chemical and spectroscopic study of some biologically potent molecules in aqueous solution of an anti-malarial drug molecule with reference to diverse molecular interactions simultaneously optimized by DFT

The various molecular interactions of amino acids, l-Asparagine (L-Asn) and l-Glutamine (L-Gln) in the aqueous solutions of Chloroquine diphosphate (CDP) had been explored comprehensively by various physicochemical as well as spectroscopic methodologies. Here we exposed the chemistry of l-Asparagine and l-Glutamine in aqueous solution of CDP by means of the apparent molar volume (ϕv), limiting apparent molar volume (ϕv0), viscosity B coefficients, molar refraction (RM), limiting molar refraction (RM0), limiting slope of surface tension and the studies revealed dominancy of solute-solvent interaction, over the solvent-solvent and solute-solute interactions in solution. A significant evidence on the nature of solute – solvent interaction obtained from 1H as well as 13C NMR spectroscopic measurement. CDP – amino acids binding constants were calculated from UV–visible spectroscopic measurement, showing significant binding ability. This work has a theoretical background after the practical outcomes, which was executed by the DFT calculations.

A 3D printed sheath flow interface for surface enhanced Raman spectroscopy (SERS) detection in flow.

Surface enhanced Raman spectroscopy (SERS) is an effective technique for detecting molecules in aqueous solutions due to its insensitivity to water, which makes it especially useful for biological samples. Utilizing SERS in flow can aid in a variety of applications such as metabolomics, pharmaceuticals, and diagnostics. The ability to 3D print complex objects enables rapid dissemination of prototypes. A 3D printed flow cell for sheath flow SERS detection has been developed that can incorporate a variety of planar substrates. The 3D printed flow cell incorporates hydrodynamic focusing, a sheath flow, that confines the analyte near the SERS substrate. Since the SERS signal obtained relies on the interaction between analyte molecules and nanostructures, sheath flow increases the detection efficiency and eliminates many issues associated with SERS detection in solution. This device was optimized by analyzing both molecules and particles with and without using sheath flow for SERS detection. Our results show that the flow rates can be optimized to increase the SERS signal obtained from a variety of analytes, and that the signal was increased when using sheath flow. This 3D printed flow cell offers a straightforward method to disseminate this technology and to facilitate online SERS detection.

Water determines the intramolecular dynamics of proteins. En example of bovine serum albumin.

In this work, the terahertz time-domain spectroscopy method analyzed solutions of bovine serum albumin (BSA) in two high concentrations (50 and 334mg/mL) at three pH values (2.5, 6.5, 8.5) and the same solvents without protein, at 25°C. The spectra of dry BSA were also recorded. For the first time, a method for determining the complex dielectric permittivity of protein molecules in aqueous solutions, without the dielectric contribution of the aqueous phase, is proposed. It is shown that the dielectric permittivity of dissolved and dry BSA (lyophilized, in the native conformation) differ significantly in the terahertz frequency range. These differences are small near 70cm-1, but they increase greatly with decreasing frequency. It was found that the dielectric losses of protein molecules in solution are close to the dielectric losses of the aqueous environment, which in this frequency range are determined by intermolecular relaxation processes of water. Since dielectric losses are directly related to molecular dynamics, this fact shows that the intramolecular dynamics of the protein completely adjusts to the intermolecular dynamics of the aqueous environment. It also indicates that the native conformation does not determine all the fundamental characteristics of a protein molecule, in particular, it does not determine the dynamics of the protein, which significantly depends on the water environment.

Molecular dynamics simulation of oil displacement using surfactant in a nano-silica pore

Molecular Dynamics (MD) simulations of oil droplet displacement have been performed using pressure driven surfactant flooding at a typical reservoir condition (T=330 K and P=20 MPa). The behavior of the micellization of surfactant molecules has been validated. A micelle with a radius of 22.85 Å is formed by 60 anionic sodium dodecyl benzenesulfonate (SDBS) surfactant molecules in aqueous solution. Surfactant additions result in significant reduction of interfacial tension (IFT) for oil/water system and such reduction is dependent on surfactant surface concentration. The microscopic mechanism of IFT reduction is described. Interfacial thickness increases from 3.5 Å to 22.5 Å at T=300 K andP=1 atm after surfactant molecules are adsorbed at oil/water interface, indicating high miscibility of two phases and thus results in interfacial tension reduction; the calculated interface formation energy of a single surfactant molecule is −145.7 Kcal/mol, which means the additions of surfactant would lead to the decrease of system energy and thus a more steady system. For surfactant flooding simulation, oil droplet static contact angle increases with surfactant additions. The larger the static contact angle of oil droplet, the stronger the drop deformation and the higher the displacement speed. Limited deformation is observed as oil droplet detaches from the solid substrate. Compared with water flooding, surfactant additions can significantly increase oil displacement speed by up to 80 %.

Solution-based Supramolecular Hierarchical Assembly of Frenkel Excitonic Nanotubes Driven by Gold Nanoparticle Formation and Temperature.

Translating nature's successful design principle of solution-based supramolecular self-assembling to broad applications─ranging from renewable energy and information technology to nanomedicine─requires a fundamental understanding of supramolecular hierarchical assembly. Though the forces behind self-assembly (e.g., hydrophobicity) are known, the specific mechanism by which monomers form the hierarchical assembly still remains an open question. A crucial step toward formulating a complete mechanism is understanding not only how the monomer's specific molecular structure but also how manifold environmental conditions impact the self-assembling process. Here, we elucidate the complex correlation between the environmental self-assembling conditions and the resulting structural properties by utilizing a well-characterized model system: well-defined supramolecular Frenkel excitonic nanotubes (NTs), self-assembled from cyanine dye molecules in aqueous solution, which further self-assemble into bundled nanotubes (b-NTs). The NTs and b-NTs inhabit distinct spectroscopic signatures, which allows the use of steady-state absorption spectroscopy to monitor the transition from NTs to b-NTs directly. Specifically, we investigate the impact of temperature (ranging from 23 °C, 55 °C, 70 °C, 85 °C, up to 100 °C) during in situ formation of gold nanoparticles to determine their role in the formation of b-NTs. The considered time regime for the self-assembling process ranges from 1 min to 8 days. With our work, we contribute to a basic understanding of how environmental conditions impact solution-based hierarchical supramolecular self-assembly in both the thermodynamic and the kinetic regime.

Physicochemical studies of some bioactive molecules in aqueous solution of tetrabutylammonium methanesulphonate (TBAMS) to investigate assorted molecular interaction at different temperatures simultaneously optimized by computational approach

Aqueous tetrabutylammonium methanesulphonate (TBAMS) solvent was used to solubilize the simplest stable amino acid (AA) Glycine and protein maker amino acid (AA) L-Alanine, and their solution behaviour has been meticulously examined to explore how they interact under various temperature conditions, using parameters like density (ρ), viscosity (η), surface tension (σ), and electrolytic conductivity. 1H NMR was also performed to verify further the mode of interactions prevailing in the solution, which is further supported by the DFT study. This research primarily aims to understand the interactions between biologically significant TBAMS and important amino acids in aqueous solutions, with potential implications for the pharmaceutical field. These results are anticipated to contribute crucial foundational knowledge for grasping the influence of sugar alcohols on the stability of protein structures.

Investigation of intermolecular interactions of l-Valine and l-Phenylalanine with muscle relaxant drug mephenesin molecule prevalent in aqueous solution by various physico-chemical methods at T=298.15K–313.15K

A complete chemical analysis of significant intermolecular interactions of l-Valine (L-Val) and l-Phenylalanine (L-Phe) with Mephenesin (MEPN) molecules in aqueous solution has been studied by different physicochemical methodologies at various temperatures (T = 298.15 K–313.15 K at an interval of 5 K) and concentrations (0.001 mol kg−1, 0.003 mol kg−1, 0.005 mol kg−1) of aqueous MEPN solution. The limiting apparent molar volume (φV0) and experimental slope (SV*) values are found from the equation of Masson, viscosity A and B-coefficient determined using the equation of Jones-Doles, molar refraction (RM) and limiting molar refraction (RM0) derived by the Lorentz-Lorenz equation, express that in our experimental solution of amino acids (AAs) in aqueous MEPN, the solute-solvent interaction predominates over the solute-solute and solvent-solvent interactions for these ternary solutions. These are also justified by the measurement of various thermodynamic parameters, free energy of activation of viscous flow per mole of solvent(Δμ1°#) and solute (Δμ2°#), activation of viscous flow of enthalpies (ΔH°#) and entropies (ΔS°#). The characteristics of structure-breaking of solutes in the aqueous drug solution have been identified by Hepler's method and dB/dT value. The spectroscopic methods like UV–visible and proton-NMR studies help to explicate the strong AA-MEPN interactions in the solution phase and obtain a good correlation with theoretical studies. Theoretical investigations are checked to authenticate the experimental observations and according to both studies, L-Phe-MEPN interaction is greater than L-Val-MEPN interaction. The experimental and correlated research data are useful for the development of model combinations of AAs with drug molecules in pharmaceutical and medicinal chemistry.

Hydrazine Oxidation in Aqueous Solutions I: N4H6 Decomposition

A mixture of nonlabeled (14N2H4) and 15N labeled hydrazine (15N2H4) in an aqueous solution is oxidized to 15N2, 14N2, and 14N15N molecules, indicating the intermediate existence of the 14NH2-14NH-15NH-15NH2 with subsequent hydrogen transfers and splitting of side N-N bonds. The structures, thermodynamics and electron characteristics of various N4H6 molecules in aqueous solutions are investigated using theoretical treatment at the CCSD/cc-pVTZ level of theory to explain the crucial part of the hydrazine oxidation reaction. Most N4H6 structures in aqueous solutions are decomposed during geometry optimization. Splitting the bond between central nitrogen atoms is the most frequent method, but the breakaway of the side nitrogen is energetically the most preferred one. The N-N fissions are enabled by suitable hydrogen rearrangements. Gibbs free energy data indicate the dominant abundance of NH3... N2... NH3 species. The side N atoms have very high negative charges, which should support hydrogen transfers in aqueous solutions. The only stable cyclo-(NH)4…H2 structure has a Gibbs energy that is too high and breaks the H2 molecule. The remaining initial cyclic structures are split into hydrazine and HN≡NH or H2N≡N species, and their relative abundance in aqueous solutions is vanishing.

Fast Diffusion Characterization by Multiphoton Excited Fluorescence Recovery while Photobleaching.

Multiphoton-excited fluorescence recovery while photobleaching (FRWP) is demonstrated as a method for quantitative measurements of rapid molecular diffusion over microsecond to millisecond timescales. Diffusion measurements are crucial in assessing molecular mobility in cell biology, materials science, and pharmacology. Optical and fluorescence microscopy techniques enable non-invasive rapid analysis of molecular diffusion but can be challenging for systems with diffusion coefficients exceeding ∼100 μm2/s. As an example, fluorescence recovery after photobleaching (FRAP) operates on the implicit assumption of a comparatively fast photobleaching step prior to a relatively slow recovery and is not generally applicable for systems exhibiting substantial recovery during photobleaching. These challenges are exacerbated in multiphoton excitation by the lower excitation efficiency and competing effects from local heating. Herein, beam-scanning FRWP with patterned line-bleach illumination is introduced as a technique that addresses FRAP limitations and further extends its application range by measuring faster diffusion events. In FRWP, the recovery of fluorescence is continuously probed after each pass of a fast-scanning mirror, and the upper bound of measurable diffusion rates is, therefore, only limited by the mirror scanning frequency. A theoretical model describing transient fluctuations in fluorescence intensity arising as a result of combined contributions from photobleaching and localized photothermal effect is introduced along with a mathematical framework for quantifying fluorescence intensity temporal curves and recovering room-temperature diffusion coefficients. FRWP is then tested by characterization of normal diffusion of rhodamine-labeled bovine serum albumin, green fluorescence protein, and immunoglobulin G molecules in aqueous solutions of varying viscosity.

Dual-Responsive Supramolecular Chiral Assemblies from Amphiphilic Dendronized Tetraphenylethylenes.

Supramolecular assembly of amphiphilic molecules in aqueous solutions to form stimuli-responsive entities is attractive for developing intelligent supramolecular materials for bioapplications. Here we report on the supramolecular chiral assembly of amphiphilic dendronized tetraphenylethylenes (TPEs) in aqueous solutions. Hydrophobic TPE moieties were connected to the hydrophilic three-fold dendritic oligoethylene glycols (OEGs) through a tripeptide proline-hydroxyproline-glycol (POG) to afford the characteristic topological structural effects of dendritic OEGs and the peptide linker. Both ethoxyl- and methoxyl-terminated dendritic OEGs were used to modulate the overall hydrophilicity of the dendronized TPEs. Their supramolecular aggregates exhibited thermoresponsive behavior that originated from the dehydration and collapse of the dendritic OEGs, and their cloud point temperatures (Tcps) were tailored by solution pH conditions. Furthermore, aggregation-induced fluorescent emission (AIE) from TPE moieties was used as an indicator to follow the assembly, which was reversibly tuned by temperature variation at different pH conditions. Supramolecular assemblies from these dendronized amphiphiles exhibited enhanced supramolecular chirality, which was dominated mainly by the interaction balance between TPE with dendritic OEG and TPE with POG moieties and was modulated through different solvation by changing solution temperature or pH conditions. More interestingly, ethoxyl-terminated dendritic OEG provided a much stronger shielding effect than its methoxyl-terminated counterpart to prevent amino groups within the peptide from protonation, even in strong acidic conditions, resulting in different responsive behavior to the solution temperature and pH conditions for these supramolecular aggregates.