Molecular Branching Research Articles

Preparation of Ethylene-1-Hexene Copolymers with Bimodal Molecular Weight Distribution and Optimal Branching Distribution on a Highly Active Supported Vanadium-Magnesium Catalyst

Using a new modification of a highly active vanadium-magnesium catalyst (VMC), data were obtained on the effect of hydrogen and hexene-1 content on the catalyst activity and the molecular structure of the resulting polymers. It was found that the formation of polyethylene (PE) with a wide bimodal molecular weight distribution (MWD) on VMC is associated with the presence of two groups of active centers in these catalysts, differing in their reactivity in the polymer chain transfer reaction with hydrogen. It was also found that the presence of hexene-1 during copolymerization leads to an additional broadening of the MWD of the copolymer due to a predominant decrease in the molecular weight of the copolymer in the low-molecular region. At the same time, the active centers of the VMC, producing a high-molecular polymer, practically do not participate in the chain transfer reaction with hexene-1. At the same time, these centers are more reactive in the reaction of insertion of hexene-1, which leads to an increased content of butyl branches in the high-molecular fraction of the copolymers. The kinetic features of highly active VMCs found indicate their promise for the production of pipe and film grades of PE using a one-reactor scheme instead of a two-reactor scheme used to produce bimodal PE on traditional titanium-magnesium catalysts.

Influence of Ligand Complexity on the Spectroscopic Properties of Type 1 Copper Sites: A Theoretical Study.

Multi-copper oxidases (MCOs) are enzymes of significant interest in biotechnology due to their efficient catalysis of oxygen reduction to water, making them valuable in sustainable energy production and bio-electrochemical applications. This study employs time-dependent density functional theory (TDDFT) to investigate the electronic structure and spectroscopic properties of the Type 1 (T1) copper site in Azurin, which serves as a model for similar sites in MCOs. Four model complexes of varying complexity were derived from the T1 site, including 3 three-coordinate models and 1 four-coordinate model with axial methionine ligation, to explore the impact of molecular branches and axial coordination. Calculations using ωB97X-D3 functional, def2-TZVP basis set, and conductor-like polarizable continuum model (CPCM) solvation model reproduced key experimental spectral features, with increased model complexity improving agreement, particularly for the ~400 cm-1 band splitting in resonance Raman spectra. This work enhances our understanding of T1 copper sites' electronic properties and spectra, bridging the gap between simplified models and complex proteins. The findings contribute to the interpretation of spectroscopic data in blue copper proteins and may inform future studies on similar biological systems.

Chemical feature-based machine learning model for predicting photophysical properties of BODIPY compounds: density functional theory and quantitative structure-property relationship modeling.

Boron-dipyrromethene (BODIPY) compounds have unique photophysical properties and have been applied in fluorescence imaging, sensing, optoelectronics, and beyond. In order to design effective BODIPY compounds, it is crucial to acquire a comprehensive understanding of the relationships between the structures of BODIPY and the corresponding photoproperties. Fifteen molecular descriptors were identified to be strongly correlated with the maximum absorption wavelength. The developed ML/QSPR model exhibited good predictive performance, with coefficients of determination (R2) of 0.945 for the training set and 0.734 for the test set, demonstrating robustness and reliability. A posterior analysis of some of the selected descriptors in the model provided insights into the structural features that influence BODIPY compound properties; meanwhile, it also emphasizes the importance of molecular branching, size, and specific functional groups. This work shows that applied combined cheminformatics and machine learning approach is robust to screen the BODIPY compounds and design novel structures with enhanced performance. In the present study, all the BODIPY models studied were fully optimized, and the corresponding absorption spectrum was obtained at DFT/TDDFT//B3LYP/6-311G(d,p) level. All the above calculations were executed by the Gaussian 16 program. Based upon the theoretical computational results, the machine learning-based quantitative structure-property relationship (ML/QSPR) model was employed for predicting the maximum absorption wavelength (λ) of BODIPY compounds by combining hand-crafted molecular descriptors (MD) and explainable machine learning (EML) techniques using Scikit-learn python library. A dataset of 131 BODIPY compounds with their experimental photophysical properties was used to generate a diverse set of molecular descriptors capturing information about the size, shape, connectivity, and other structural features of these compounds using Chemaxon and Alvadesc software. A genetic algorithm (GA) variable selection together with the multi-linear regression (MLR) method were applied to develop the best predictive model using the Genetic Selection python library.

Investigating the hydrolysis of complex carbohydrates with salivary α-amylase.

Currently, little is known about how complex carbohydrates (maltodextrins) with varying degrees of polymerisation (DP) and molecular branching interact with α-amylase in human saliva and the associated amounts and structures of generated reducing sugars. Therefore, this study aimed to investigate salivary α-amylase and the subsequent reducing sugars generated with complex carbohydrate stimuli. A secondary aim was to investigate reducing sugar generation and complex carbohydrate taste sensitivity. Whole, stimulated saliva was collected from 32 participants. Two maltodextrin samples were used (short chain maltodextrin (SCM), average DP 6, and long chain maltodextrin (LCM), average DP 20) with and without the α-amylase inhibitor, acarbose. The concentration of reducing sugars generated by the salivary α-amylase was determined and high performance anion exchange chromatography with pulsed amperometric detection (HPAEC-PAD) was used to investigate their molecular chain profiles. Complex carbohydrate taste sensitivity was measured using detection threshold (DT) and suprathreshold intensity perception methods (ST). The addition of acarbose significantly reduced the amount of reducing sugars generated for both LCM and SCM samples (p=0.0001). The LCM sample produced a significantly higher amount of reducing sugars than the SCM sample (p=0.0001). For the LCM sample, there was no effect of complex carbohydrate taste sensitivity on reducing sugar generation (all p>0.05). For the SCM sample, evidence suggests that reducing sugar generation may be impact complex carbohydrate sensitivity (DT: p=0.059, ST: p=0.076). In conclusion, DP of the maltodextrins impacted the amount of reducing sugars generated. Furthermore, there was evidence to suggest that an interaction exists between complex carbohydrate taste sensitivity and the generation of reducing sugars.

Elucidation of molecular mechanisms involved in tadpole toxicity employing QSTR and q-RASAR approach

Tadpoles, as early developmental stages of frogs, are vital indicators of toxicity and environmental health in ecosystems exposed to harmful organic compounds from industrial and runoff sources. Evaluating each compound individually is challenging, necessitating the use of in silico methods like Quantitative Structure Toxicity-Relationship (QSTR) and Quantitative Read-Across Structure-Activity Relationship (q-RASAR). Utilizing the comprehensive US EPA's ECOTOX database, which includes acute LC50 toxicity and chronic endpoints, we extracted crucial data such as study types, exposure routes, and chemical categories. Regression-based QSTR and q-RASAR models were developed from this dataset, emphasizing key chemical descriptors. Lipophilicity and unsaturation were significant for predicting acute toxicity, while electrophilicity, nucleophilicity, and molecular branching were crucial for chronic toxicity predictions. Additionally, q-RASAR models integrated with the "intelligent consensus" algorithm were employed to enhance predictive accuracy. The performance of these models was rigorously compared across various approaches. These refined models not only predict the toxicity of untested compounds but also reveal underlying structural influences. Validation through comparison with existing literature affirmed the relevance and robustness of our approach in ecotoxicology.

Upcycling of polyethylene waste to biodegradable adhesive and coating via Baeyer-Villiger reaction: A new view on oxidation-fracture mechanism and structure-function relationship

Non-biodegradable polyethylene waste accumulates in large quantities in the environment posing a serious threat to the survival of creatures. Meanwhile, polyethylene suffers from inherent polarity limitations that curtails its application scope. Oxidation is an efficient approach of upcycling waste polyethylene through introduction of hydrophilic functional groups (such as –COOH, –OH), yet often at the expense of their original hydrophobicity. Herein, the hydrophobic ester groups, were introduced via Baeyer-Villiger oxidation to ingeniously balance the contradiction among hydrophobicity, interfacial forces and sustainability of polyethylene oxidation products. A tandem conversion mechanism among the oxidative groups was proposed while the decrease in molecular weight and branching degree was clarified to be a result of β-scissions occurring the branches during the oxidation. Meanwhile, the effect of oxidation degree and molecular weight on interfacial forces was revealed. The excellent hydrophobicity and corrosion resistance of the oxidized polyethylene coating can be attributed to the low content of carboxyl/hydroxyl groups, rich hydrophobic ester groups and the retained long carbon chain structure. Besides, the introduced ester groups and lower molecular weight also provided the oxidation products with potential biodegradability. This work provided a new insight on the Baeyer-Villiger oxidation of polyethylene and the potential for upcycling of polyethylene waste into sustainable materials.

Characteristic of fluoroether gum via non-linear rheological approaches

Abstract Large amplitude oscillatory shear (LAOS) tests were conducted on four types of fluoroether elastomer gum, namely VPL-85540, VPL-75545, VPL-65455, and VPL-55540 in order to study their molecular weight, chain structure, and branching degree from the perspective of rubber rheology. For the setting of shear rate in varied LAOS measurements, frequency and angular velocity controlling modes were attempted and compared. Non-linear rheological parameters showed that VPL-65455 possessed significant polymeric branching characteristics. VPL-55540 possessed the lowest molecular weight, and VPL-75545 was detected with higher long-pendant monomer content in its polymer chain. Rheological properties concluded from the analysis of two shear rate controlling modes of LAOS tests exhibited great consistency, which confirmed the reliability of LAOS tests in the characterization of fluoroether gum.

Designing of imine thiophene-ligated metal-complexes and implication in ethylene polymerization

Polyethylene is the single largest volume polymer produced globally using Ziegler-type catalysts. Numerous modifications have been reported in search of a better catalyst that can control molecular weight, polydispersity, and branching. In our attempts to identify a suitable imine thiophene-ligated chromium complex, we examined 9 different titanium complexes computationally. The DFT investigations considered barriers for insertion, propagation, and termination by β-H elimination or chain transfer, and identified N-(4-methoxyphenyl)-2-phenyl-1-(thiophen-2-yl)ethan-1-imine(L9) as the most suitable ligand. Subsequently, L9 was prepared in good yield (70%) by condensing 2-phenyl-1-(thiophen-2-yl)ethan-1-one with 4-methoxyaniline. Ligand L9 was treated with early transition metal precursors (Ti, Cr, Zr) to generate a homogenous catalyst. The identity of these catalysts was unambiguously ascertained using a combination of NMR, ICP, FT-IR, UV-Vis spectroscopy, and ESI-MS. The performance of L9-ligated titanium complex [Cat.1] was examined in ethylene polymerization using MMAO as a co-catalyst. Insertion of ethylene was tracked using high-pressure NMR experiments and Cat.1 was found to be active in the polymerization. Ethylene polymerization conditions were optimized to obtain high activity and molecular weight polyethylene. The chromium complex [Cat.2] outperformed the Ti and Zr-derived catalysts with the highest TOF of 6294 mol of PE/mol of Cr/h. Cat.2 produced high molecular weight, high-density polyethylene.

Faster and greater moisture curing ethylene‐silane copolymers with good shelf stabilities

AbstractVinyltrimethoxysilane (VTMS) functionalized ethylenic polymers, in the form of reactor‐made ethylene‐silane copolymers as well as post‐reactor made silane‐grafted ethylene polymers, were evaluated for the purpose of moisture‐induced crosslinking through hydrolysis and condensation reactions. The copolymers were of 1.6 wt% or 4.2 wt% VTMS contents, and the silane‐grafted resins ranged in VTMS contents from 1.1 to 3.7 wt%. The silane‐grafted materials were very reactive under humid conditions at room temperature, resulting in very poor shelf stabilities manifested in sharp drops in their melt indices over time (changes that in the early stages were dominated mostly by resin molecular weight distribution and/or branching, and in the later stages much more by silane content). In sharp contrast, the ethylene‐silane copolymers exhibited outstanding shelf stabilities over time even at relatively high silane content, indicating desirably low reactivities in the absence of moisture‐cure catalyst. When formulated with catalyst, and exposed to humid conditions, the cure characteristics of the silane functionalized ethylene polymers varied significantly, with the fastest and greatest crosslinking observed using the ethylene‐silane copolymer of 4.2 wt% VTMS content and remarkably excellent shelf stability. Analyses of reaction rates revealed very interesting trends, depending on type of catalyst (tin or sulfonic acid) and resin.Highlights Ethylene‐silane copolymers and silane‐grafted ethylene polymers were studied. Copolymers exhibited vastly superior shelf stabilities than grafted materials. Catalyst type and loading affected moisture‐induced crosslinkability. Increased silane content in copolymer led to faster and greater crosslinking. Best balance of crosslinkability and shelf stability obtained with copolymers.

A Note on Wiener and Hyper-Wiener Indices of Abid-Waheed Graph

A Hosoya polynomial is a polynomial connected to a molecular graph, which is a graph representation of a chemical compound with atoms as vertices and chemical bonds as edges. A graph invariant is the Hosoya polynomial; it is a graph attribute that does not change under graph isomorphism. It provides information about the number of unique non-empty subgraphs in a given graph. A molecular graph's size and branching complexity are determined by a topological metric known as the Wiener index. The Wiener index of each pair of vertices in a molecular network is the sum of those distances. The topological index, one of the various classes of graph invariants, is a real number related to a connected graph's structure .The goal of this article is to compute the Hosoya polynomial of some class of Abid-Waheed graph. Further, this research focused on a C++ algorithm to calculate the wiener index of and . The Wiener index (W∗I) and Hyper-Wiener index (H∗W∗I) are calculated using Hosoya polynomial (H∗-polynomial) of some family of Abid-Waheed graphs and . Illustrations and applications are given to enhance the research work.

Lattice-Cluster-Theory-Informed Cross-Fractionation Chromatography Revealing Degree of Crystallinity of Single Macromolecular Species.

The relationship between macromolecular architecture and crystallization properties is a relevant research topic in polymer science and technology. The average degree of crystallinity of disperse polymers is a well-studied quantity and is accessible by various experimental methods. However, how the different macromolecular species contribute to the degree of crystallinity and, in particular, the relationship between a certain macromolecular architecture and the degree of crystallinity are not accessible today, neither experimentally nor theoretically. Therefore, in this work, a lattice cluster theory (LCT)-informed cross-fractionation chromatography (CFC) approach is developed to access the degree of crystallinity of single and nonlinear macromolecular species crystallizing from solution. The method entangles high-throughput experimental data from CFC with the LCT for semicrystalline polymers to predict the degree of crystallinity of polymer species with different molecular weights and branching. The approach is applied to a linear low-density polyethylene (ethylene/1-octene copolymer) and a high-density polyethylene, which have specific and different bivariate distributions. The degree of crystallinity of individual macromolecular species of these polymer samples is calculated, and the predicted average degree of crystallinity is compared with experimental measurements, thus successfully validating the approach. Furthermore, the average segment length between branches is introduced as a characteristic molecular feature of branched polyethylene, and its relationship with the degree of crystallinity of certain species is established.

Aggregation behaviour of paraffin molecules with different branched distributions during crude oil gelling: A molecular dynamics study

Revealing the microdynamic mechanism and thermodynamic properties of the gelling process of waxy crude oil at the microscale plays an important role in ensuring the safe production and transport of waxy crude oil. However, few studies have dealt with the influence of paraffin molecular branching position on the gelling process. The focus of this study is to clarify the influence of branching distribution on molecular aggregation through molecular simulation, so as to further improve the mechanistic study of the gelling process of waxy crude oil. A variety of molecular models of crude oil systems containing paraffin molecules with different distributions of branched chains, asphaltenes, and light oils are developed to analyse the molecular aggregation and wax precipitation characteristics during the gelling process.The results show that the paraffin molecular chain morphology gradually from stretching to curling and the molecules gradually from dispersing to aggregating during the temperature drop process. From the van der Waals force analysis, it is concluded that isomeric alkanes with a close branching distribution form the weakest gelling structures. In addition, the phase transition temperature difference between n-alkanes and isoalkanes is large about 9 K, but the phase transition temperature difference between the two isoalkanes with different distributions of branched chains is small only about 3 K. This indicates that for alkanes with the same molecular formula, the length of the main carbon chain is a dominant factor in influencing the aggregation of the molecules and the gelling properties of the crude oil system. Under high temperature conditions, isomeric alkanes have the best mobility and are most sensitive to temperature. The results of the study can provide help for the mechanism of the gelling process of waxy crude oil to ensure the safety of the pipeline transmission process, and provide theoretical guidance for the production of depressants and catalysts.

Quantitation of polystyrene by pyrolysis-GC-MS: The impact of polymer standards on micro and nanoplastic analysis

The analytical method for detecting and quantifying micro and nanoplastics (MNPs) using Pyrolysis-Gas Chromatography-Mass Spectrometry (Py-GC-MS) is evolving and continuously refined. The requirement for accurate analytical methods faces challenges during method validation due to the scarcity of relevant reference materials. Additionally, the wide array of polymer types and their diverse characteristics further complicate this validation process. This study evaluated the impact of using diverse polystyrene (PS) standards with different molecular weights, polydispersity indexes, tacticity, endcapping, and chain branching, on quantifying the mass concentration of PS in various products. The results for the PS-based products showed inconsistencies across different standards, indicating that the measurements for a single product varied substantially when different polystyrene (PS) standards were applied. The influence of sample quantity on pyrolysis revealed differences in the ratios of pyrolysis products among various PS standards and different sample amounts. This research emphasizes the complexities involved in the precise quantification of polymers using Py-GC-MS. It provides valuable insights crucial for quantitative MNP analysis, highlighting the need for refined calibration strategies and standardised reference materials to improve the reliability of the MNP analysis method.

Advanced properties of gold nanoparticles obtained by using long-chain secondary amine for phase transfer from water to chloroform

We have conducted a new comparison of gold nanoparticles functionalized by primary- and secondary amine with the same chain length. Our hypothesis suggests that the adaptive steric conformation of the secondary amine molecular branches makes a marked additional contribution to the well-established role of the ligand chain length. We characterize the importance of this factor based on diOctadecylamine (diODA) and Octadecylamine (ODA) passivated gold nanoparticles by using high-resolution transmission electron microscopy (HR-TEM) and selective area electron diffraction (SAED). The results evidenced that the diODA coordination to the inorganic core forms a more efficient and impenetrable protective coating. The SAED patterns show a more homogeneous distribution of the small crystalline domains in the gold core. TEM images show a smooth spherical shape of the diODA nanoparticles and a lack of interparticle coalescence cases. The diODA-passivation provides nanoparticles with nearly twice the effective ligand length than its ODA equivalent. This results in their spontaneous arrangement in domains with expressed crystal-like order despite the relatively large size-dispersity before passivation. The surface free energy of coatings, formed by diODA passivated gold nanoparticles, is twice as small as measured on the ODA-nanoparticle-coated surfaces.

Congestion of steric and electronic factors in α-diimine nickel precatalysts for high-temperature ethylene polymerization in accessing direct PE elastomer

In α-diimine-nickel catalysts mediated ethylene polymerization, the synergistic impact of steric and electronic factors plays an instrumental role in fine-tuning catalytic activity, polymer molecular weights, microstructure, as well as mechanical and elastic properties. In this study, a new series of nonsymmetrical bis(arylimino)-acenaphthene-nickel complexes was prepared and investigated for ethylene polymerization. These complexes feature both bulky N-2,6-dibenzhydryl-3,4,5-fluorophenyl imine and smaller N-2,6-di(R)-4-(R1)phenyl imine units [Ni2Me (R, = Me, R1 = H), Ni2Et (R, = Et, R1 = H) and Ni2iPr (R, = iPr, R1 = H), Ni3Me (R, R1 = Me), Ni2Et,Me (R, = Et, R1 = Me)]. The incorporation of both steric congestion and strong electronic withdrawal groups into the catalyst structure resulted in significantly improved catalytic performance: high thermal stability and exceptional activity were observed at both ambient temperature (21.24 × 106 at 30 °C) and industrially relevant temperatures (1.65 × 106 at 100 °C). Polymer molecular weights and branching degree were tunable by adjusting the ligand structure and reaction conditions. This correlation extended to mechanical and elastic properties, demonstrating high tensile strength at low temperatures and good elastic recovery at high reaction temperatures, consistent with typical polyolefin elastomers.

Comprehensive ecotoxicological assessment of pesticides on multiple avian species: Employing quantitative structure-toxicity relationship (QSTR) modeling and read-across

The rapid increase in the use of pesticides is driven by the growing demand in the agricultural sector. However, the widespread application of these pesticides and their inherent toxicity have significant repercussions on the ecosystem, particularly impacting animal and bird species. In this present study, we have developed four 2D quantitative structure-toxicity relationships (QSTRs) models for four different avian species using the largest number of available experimental data points to date employing the partial least squares (PLS) algorithm. Furthermore, we have also performed the read-across algorithm to improve the test set results. Based on the information derived from the models, it was found that hydrophilic characteristics, the presence of molecular branching and thio imide groups impact negatively to the pesticide toxicity, while the presence of phosphate group, presence of halogens viz. chlorine and bromine atoms, presence of hetero atoms, high molecular weight, presence of bridgehead atoms, presence of secondary aliphatic amide and fragments like RCONHR escalates avian toxicity. The developed QSTR models were further employed to predict the Pesticide Properties DataBase (PPDB) for all four avian species as a measure of data gap-filling and risk assessment. Thus, the developed models can be utilized for eco-toxicological data-gap filling, prediction of toxicity of untested pesticides as well as the development of novel and safe environmental-friendly pesticides.

Control of chain transfer and chain walking by tailored metal–π interactions in polymerization catalysis

Chain walking and chain transfer are pivotal processes that govern the microstructure and molecular weight of polyolefins synthesized via late transition metal-catalyzed ethylene (co)polymerization. In this study, we demonstrate that tailored metal–π interactions using heteroatomic dibenzosuberyl substituents can effectively modulate both chain transfer and chain walking in α-diimine nickel- and palladium-catalyzed systems. This modulation leads to significant reductions in the molecular weight and branching density of the resulting polyethylenes and copolymers. To achieve this, we designed, synthesized, and characterized a series of α-diimine Ni(II) and Pd(II) complexes bearing diverse heteroatomic dibenzosuberyl substituents. In nickel-catalyzed ethylene polymerization, the heteroatomic dibenzosuberyl Ni(II) catalysts showed lower catalytic activities and produced polyethylenes with fewer branches (21–48/1000C vs 83–90/1000C) and an order of magnitude lower molecular weight (2.3–6.5 kg/mol vs 54.6–89.1 kg/mol) than the non-heteroatomic dibenzosuberyl Ni(II) catalyst. Comparable trends were observed in palladium-catalyzed ethylene polymerization and ethylene-MA copolymerization, with sulfur-containing substituents exerting more pronounced effects. We propose a mechanism where the weak metal–π interactions between the dibenzosuberyl substituents and the metal center during polymerization catalysis suppress β-H elimination and promote synergistic chain transfer. This provides a rationale for the observed reductions in molecular weight and branching density, offering valuable insights for the rational design of catalysts for tailored polyolefin synthesis.

Application of hyperbranched polysiloxanes in biomedical materials based on AIE polymer properties

Application of hyperbranched polysiloxanes in biomedical materials based on AIE polymer properties

Modelling of chromatographic and electrophoretic behaviour of imidazoline and alpha adrenergic receptors ligands under different acid-base conditions.

The ligands of the imidazoline and α-adrenergic receptors are mainly imidazoline and guanidine derivatives, known as centrally-acting antihypertensives and compounds with potential use in various neurological disorders. The extent of their ionisation has a major influence on their behaviour in the different analytical systems. The main objective of this work was to compare the mechanism of chromatographic retention and electrophoretic mobility under acidic, neutral and basic conditions. Multiple Linear Regression and Partial Least Squares Regression were applied for the QSRR (quantitative structure-retention relationship) and QSMR (quantitative structure-mobility relationship) modelling and to select the most important molecular parameters describing the chromatographic and electrophoretic behaviour of the investigated compounds. The most important molecular descriptors, such as the chemical composition of the compounds, lipophilicity, polarizability and molecular branching, in the selected QSRR models showed that an important insight into the retention behaviour can be derived from the 0D-, 1D- and 2D-descriptors. The electrophoretic mobility could be explained by 2D- and 3D-descriptors, which provide information on the molecular mass, size and complexity, as well as on the influence of charge transfer and electronic properties on the migration behaviour. All created QSRR/QSMR models met the stringent validation criteria and showed high potential in describing the chromatographic and electrophoretic behaviour of investigated compounds.

The impact of ultrasonic-assisted extraction on the in vitro hypoglycemic activity of peach gum polysaccharide in relation to its conformational conversion.

Peach gum (PG) is an exudate of the peach tree (Prunus persica of the Rosaceae family), which consists primarily of polysaccharides with a large molecular weight and branching structure. Consequently, PG can only swell in water and does not dissolve easily, which severely limits its application. Current conventional extraction methods for PG polysaccharide (PGPS) are time consuming and inefficient. This study investigated the impact of ultrasonic-assisted extraction (UAE) on PGPS structure and conformation, and their relationship to hypoglycemic activity in vitro. In comparison with conventional aqueous extraction, UAE enhanced PGPS yielded from 28.07-32.83% to 80.37-84.90% (w/w) in 2 h. It drastically decreased the molecular size and conformational parameters of PGPS, including weight-average molecular weight (Mw), number-average molecular weight (Mn), z-average radius of gyration (Rg), hydrodynamic radius (Rh) and instrinsic viscosity ([η]) values. Peach gum polysaccharide conformation converted extended molecules to flexible random coil chains or compact spheres with no obvious primary structure alteration. Furthermore, UAE altered the flow behavior of PGPS solution from that of a non-Newtonian fluid to that of a Newtonian fluid. As a result, PGPS treated with UAE displayed weaker inhibitory activity than untreated PGPS, mostly because UAE weakens the binding strength of PGPS to α-glucosidase. However, this negative effect of UAE on PGPS activity was compensated by the increased solubility of polysaccharide. This enabled PGPS to achieve a wider range of doses. Ultrasonic-assisted extraction is capable of degrading PGPS efficiently while preserving its primary structure, resulting in a Newtonian fluid solution. The degraded PGPS conformations displayed a consistent correlation with their inhibitory effect on α-glucosidase activity. © 2024 Society of Chemical Industry.