The effect of water on the structure and physical properties of amorphous polysaccharide matrices is investigated by combining a thermodynamic approach including pressure- and temperature-dependent dilatometry with a nanoscale analysis of the size of intermolecular voids using positron annihilation lifetime spectroscopy. Amorphous polysaccharides are of interest because of a number of unusual properties which are likely to be related to the extensive hydrogen bonding between the carbohydrate chains. Uptake of water by the carbohydrate matrices leads to a strong increase in the size of the holes between the polymer chains in both the glassy and rubbery states while at the same time leading to an increase in matrix free volume. Thermodynamic clustering theory indicates that, in low-moisture carbohydrate matrices, water molecules are closely associated with the carbohydrate chains. Based on these observations, we propose a novel model of plasticization of carbohydrate polymers by water in which the water dynamically disrupts chains the hydrogen bonding between the carbohydrates, leading to an expansion of the matrix originating at the nanolevel and increasing the number of degrees of freedom of the carbohydrate chains. Consequently, even in the glassy state, the uptake of water leads to increased rates of matrix relaxation and mobility of small permeants. In contrast, low-molecular weight sugars plasticize the carbohydrate matrix without appreciably changing the structure and density of the rubbery state, and their role as plasticizer is most likely related to a reduction of the number of molecular entanglements. The improved molecular packing in glassy matrices containing low molecular weight sugars leads to a higher matrix density, explaining, despite the lower glass transition temperature, the reduced mobility of small permeants in such matrices.
The translocation of biopolymers, such as DNA and proteins, across cellular or nuclear membranes is essential for numerous biological processes. The translocation dynamics are influenced by the properties of the polymers, such as polymer stiffness, and the geometry of the capsid. In our study, we aim to investigate the impact of polymer stiffness, activity, and different capsid geometries on the packing and ejection dynamics of both passive and active polymers. We employ Langevin dynamics simulations for a systematic investigation. We observe that flexible polymers exhibit packing times that are faster than those of their semi-flexible counterparts. Interestingly, for large polymers compared to the capsid size, sphere facilitates faster packing and unpacking compared to ellipsoid, mimicking the cell nucleus and suggesting a geometrical advantage for biopolymer translocation. In summary, we observe that increasing activity accelerates both the packing and ejection processes for both flexible and semi-flexible polymers. However, the effect is significantly more pronounced for semi-flexible polymers, highlighting the crucial role of polymer flexibility in these dynamics. These finding
Carbohydrates, essential biological building blocks, exhibit functional mechanisms tied to their intricate stereochemistry. Subtle stereochemical differences, such as those between the anomers maltose and cellobiose, lead to distinct properties due to their differing glycosidic bonds; the former is digestible by humans, while the latter is not. This underscores the importance of precise structural determination of individual carbohydrate molecules for deeper functional insights. However, their structural complexity and conformational flexibility, combined with the high spatial resolution needed, have hindered direct imaging of carbohydrate stereochemistry. Here, we employ non-contact atomic force microscopy integrated with a data-efficient, multi-fidelity structure search approach accelerated by machine learning integration to determine the precise 3D atomic coordinates of two carbohydrate anomers. We observe that glycosidic bond stereochemistry regulates on-surface chiral selection in carbohydrate self-assemblies. The reconstructed models, validated against experimental data, provide reliable atomic-scale structural evidence, uncovering the origin of on-surface chirality from carb
Molecular representation learning (MRL) is a powerful tool for bridging the gap between machine learning and chemical sciences, as it converts molecules into numerical representations while preserving their chemical features. These encoded representations serve as a foundation for various downstream biochemical studies, including property prediction and drug design. MRL has had great success with proteins and general biomolecule datasets. Yet, in the growing sub-field of glycoscience (the study of carbohydrates, where longer carbohydrates are also called glycans), MRL methods have been barely explored. This under-exploration can be primarily attributed to the limited availability of comprehensive and well-curated carbohydrate-specific datasets and a lack of Machine learning (ML) pipelines specifically tailored to meet the unique problems presented by carbohydrate data. Since interpreting and annotating carbohydrate-specific data is generally more complicated than protein data, domain experts are usually required to get involved. The existing MRL methods, predominately optimized for proteins and small biomolecules, also cannot be directly used in carbohydrate applications without sp
The use of chemical warfare agents (CWAs) in modern warfare cannot be disregarded due to their ease of use and potential for large-scale incapacitation. An effective countermeasure involves the physical adsorption of these agents, preventing their entry through the respiratory tract by non-specific adsorption. In this study, we investigate the physical interaction between potential adsorbents and model gases mimicking CWAs, thereby identifying sufficient conditions for higher physical adsorption performance. Our findings reveal that the physical adsorption capacity is highly sensitive to the surface properties of the adsorbents, with uniform development of micropores, rather than solely high surface area, emerging as a critical factor. Additionally, we identified the potential of porous organic polymers as promising alternatives to conventional activated carbon-based adsorbents. Through a facile introduction of polar sulfone functional groups on the polymer surface, we demonstrated that these polar surface polymers exhibit physical adsorption capabilities for formaldehyde under ambient conditions comparable to high-performance activated carbons. Notably, the superior activated carb
This work looks at the relationship between the index of hydrogen deficiency (IHD) and the enthalpy of combustion of "sugar propellant," as well as the performance of carbohydrates with similar IHD values. The study used eight different carbohydrate sources as fuels in the propellant, combined with potassium nitrate as an oxidizer in a 35:65 ratio. The IHD of the sugars ranged from 0 (polyols) to 2 (disaccharides). Different propellant mixtures (carbohydrate-KN) were tested using calorimeters and chemical analysis. The results support the hypothesis that IHD is associated with the enthalpy of combustion of sugar propellant, with polyol reactions showing the highest enthalpy change. Moreover, carbohydrates with a higher molar mass and an IHD of 2 exhibit better performance than those with an IHD of 1.
Carbohydrates such as the trisaccharide motif LeX are key constituents of cell surfaces. Despite intense research, the interactions between carbohydrates of apposing cells or membranes are not well understood. In this article, we investigate carbohydrate-carbohydrate interactions in membrane adhesion as well as in solution with extensive atomistic molecular dynamics simulations that exceed the simulation times of previous studies by orders of magnitude. For LeX, we obtain association constants of soluble carbohydrates, adhesion energies of lipid-anchored carbohydrates, and maximally sustained forces of carbohydrate complexes in membrane adhesion that are in good agreement with experimental results in the literature. Our simulations thus appear to provide a realistic, detailed picture of LeX-LeX interactions in solution and during membrane adhesion. In this picture, the LeX-LeX interactions are fuzzy, i.e. LeX pairs interact in a large variety of short-lived, bound conformations. For the synthetic tetrasaccharide Lac 2, which is composed of two lactose units, we observe similarly fuzzy interactions and obtain association constants of both soluble and lipid-anchored variants that are
Carbohydrates, vital components of biological systems, are well-known for their structural diversity. Nuclear Magnetic Resonance (NMR) spectroscopy plays a crucial role in understanding their intricate molecular arrangements and is essential in assessing and verifying the molecular structure of organic molecules. An important part of this process is to predict the NMR chemical shift from the molecular structure. This work introduces a novel approach that leverages E(3) equivariant graph neural networks to predict carbohydrate NMR spectra. Notably, our model achieves a substantial reduction in mean absolute error, up to threefold, compared to traditional models that rely solely on two-dimensional molecular structure. Even with limited data, the model excels, highlighting its robustness and generalization capabilities. The implications are far-reaching and go beyond an advanced understanding of carbohydrate structures and spectral interpretation. For example, it could accelerate research in pharmaceutical applications, biochemistry, and structural biology, offering a faster and more reliable analysis of molecular structures. Furthermore, our approach is a key step towards a new data-
The Martini 3 force field is a full re-parametrization of the Martini coarse-grained model for biomolecular simulations. Due to the improved interaction balance it allows for more accurate description of condensed phase systems. In the present work we develop a consistent strategy to parametrize carbohydrate molecules accurately within the framework of Martini 3. In particular, we develop a canonical mapping scheme that decomposes arbitrarily large carbohydrates into a limited number of fragments. Bead types for these fragments have been assigned by matching physicochemical properties of mono- and disaccharides. In addition, guidelines for assigning bonds, angles, and dihedrals are developed. These guidelines enable a more accurate description of carbohydrate conformations than in the Martini 2 force field. We show that models obtained with this approach are able to accurately reproduce osmotic pressures of carbohydrate water solutions. Furthermore, we provide evidence that the model differentiates correctly the solubility of the poly-glucoses dextran (water soluble) and cellulose (water insoluble, but soluble in ionic-liquids). Finally, we demonstrate that the new building blocks
We generalize the construction of connected branched polymers and the notion of the volume of the space of connected branched polymers studied by Brydges and Imbrie, and Kenyon and Winkler to any hyperplane arrangement A. The volume of the resulting configuration space of connected branched polymers associated to the hyperplane arrangement A is expressed through the value of the characteristic polynomial of A at 0. We give a more general definition of the space of branched polymers, where we do not require connectivity, and introduce the notion of q-volume for it, which is expressed through the value of the characteristic polynomial of A at -q. Finally, we relate the volume of the space of branched polymers to broken circuits and show that the cohomology ring of the space of branched polymers is isomorphic to the Orlik-Solomon algebra.
Due to their unique topology of having no chain ends, dilute solutions of ring polymers exhibit behaviour distinct from their linear chain counterparts. The universality of their static and dynamic properties, as a function of solvent quality $z$ in the thermal crossover regime between $θ$ and athermal solvents, is studied here using Brownian dynamics simulations. The universal ratio $U_{\text{RD}}$ of the radius of gyration $R_g$ to the hydrodynamic radius $R_H$ is determined, and a comparative study of the swelling ratio $α_g$ of the radius of gyration, the swelling ratio $α_H$ of the hydrodynamic radius, and the swelling ratio $α_X$ of the mean polymer stretch $X$ along the $x$-axis, for linear and ring polymers, is carried out. The ratio $U_{\text{RD}}$ for dilute ring polymer solutions is found to converge asymptotically to a constant value as $z \to \infty$, which is a major difference from the behaviour of solutions of linear chains, where no such asymptotic limit exists. Additionally, the ratio of the mean stretch along the $x$-axis to the hydrodynamic radius, $(X/R_H)$, is found to be independent of $z$ for polymeric rings, unlike in the case for linear polymers. These res
Polymers are widely used in industry and in our daily life because of their diverse functionality, light weight, low cost and excellent chemical stability. However, on some applications such as heat exchangers and electronic packaging, the low thermal conductivity of polymers is one of the major technological barriers. Enhancing the thermal conductivity of polymers is important for these applications and has become a very active research topic over the past two decades. In this review article, we aim to: 1). systematically summarize the molecular level understanding on the thermal transport mechanisms in polymers in terms of polymer morphology, chain structure and inter-chain coupling; 2). highlight the rationales in the recent efforts in enhancing the thermal conductivity of nanostructured polymers and polymer nanocomposites. Finally, we outline the main advances, challenges and outlooks for highly thermal-conductive polymer and polymer nanocomposites.
The glass transition is a long-standing unsolved problem in materials science. For polymers, our understanding of glass-formation is particularly poor due to the added complexity of chain connectivity and flexibility; structural relaxation of polymers thus involves a complex interplay between intra- and inter-molecular cooperativity. Here we study how the glass transition temperature Tg varies with molecular weight M for different polymer chemistries and chain flexibilities. We find that Tg(M) is controlled by the average mass (or volume) per conformational degree of freedom, and that a `local' molecular relaxation (involving a few conformers) controls the larger-scale cooperative alpha relaxation responsible for Tg. We propose that dynamic facilitation where a `local' relaxation facilitates adjacent relaxations, leading to hierarchical dynamics, can explain our observations including logarithmic Tg(M) dependences. Our study provides a new understanding of molecular relaxations and the glass transition in polymers, which paves the way for predictive design of polymers based on monomer-scale metrics.
Elucidating the physics of a concentrated suspension of ring polymers, or of an ensemble of ring polymers in a complex environment, is an important outstanding question in polymer physics. Many of the characteristic features of these systems arise due to topological interactions between polymers, or between the polymers and the environment, and it is often challenging to describe this quantitatively. Here we review recent research which suggests that a key role is played by inter-ring threadings (or penetrations), which become more abundant as the ring size increases. As we discuss, the physical consequences of such threadings are far-reaching: for instance, they lead to a topologically-driven glassy behaviour of ring polymer melts under pinning perturbations, while they can also account for the shape of experimentally observed patterns in two-dimensional gel electrophoresis of DNA knots.
We review recent results of the field theoretical renormalization group analysis on the scaling properties of star polymers. We give a brief account of how the numerical values of the exponents governing the scaling of star polymers were obtained as well as provide some examples of the phenomena governed by these exponents. In particular we treat the interaction between star polymers in a good solvent, the Brownian motion near absorbing polymers, and diffusion-controlled reactions involving polymers.
We study an ensemble of branched polymers which are embedded on other branched polymers. This is a toy model which allows us to study explicitly the reaction of a statistical system on an underlying geometrical structure, a problem of interest in the study of the interaction of matter and quantized gravity. We find a phase transition at which the embedded polymers begin to cover the basis polymers. At the phase transition point the susceptibility exponent $γ$ takes the value 3/4 and the two-point function develops an anomalous dimension 1/2.
We investigate polymer partitioning from polymer mixtures into nanometer size cavities by formulating an equation of state for a binary polymer mixture assuming that only one (smaller) of the two polymer components can penetrate the cavity. Deriving the partitioning equilibrium equations and solving them numerically allows us to introduce the concept of "polymers-pushing-polymers" for the action of non-penetrating polymers on the partitioning of the penetrating polymers. Polymer partitioning into a pore even within a very simple model of a binary polymer mixture is shown to depend in a complicated way on the composition of the polymer mixture and/or the pore-penetration penalty. This can lead to enhanced as well as diminished partitioning, due to two separate energy scales that we analyse in detail.
We employ the recently introduced generalized microcanonical inflection point method for the statistical analysis of phase transitions in flexible and semiflexible polymers and study the impact of the bending stiffness upon the character and order of transitions between random-coil, globules, and pseudocrystalline conformations. The high-accuracy estimates of the microcanonical entropy and its derivatives required for this study were obtained by extensive replica-exchange Monte Carlo simulations. We observe that the transition behavior into the compact phases changes qualitatively with increasing bending stiffness. Whereas the $Θ$ collapse transition is less affected, the first-order liquid-solid transition characteristic for flexible polymers ceases to exist once bending effects dominate over attractive monomer-monomer interactions.
We examine the statistics of conformations of a linear polymer in a solvent. The polymer is allowed to form double polymers. We closely follow a classical technique to derive a field theory for the problem from an $O\left(n\right)$ symmetric spin model. The field theory is a model for RNA or DNA with constant binding energy per monomer. It is shown that there is a stable renormalization group fixed point, at which the double polymer decouples from the single-strand polymer and becomes a branched polymer of the conventional type with a three-point interaction. To reach this fixed point, at least one parameter must be adjusted. The critical dimension is eight. Fisher-renormalization, equation of state and critical exponents are reproduced in this limit. The single-strand polymer depends on the double-strand polymer and disappears at the critical point, but has its own critical exponents.
The possibility of carbohydrate separation in BEH HILIC (Ethylene Bridged Hybride, Hydrophilic Interaction Liquid Chromatography) column was studied by ultra-performance liquid chromatography (UPLC) with evaporative light scattering detector (ELSD) and mobile phase containing amine compounds as modifiers. The chromatography conditions and ELSD parameters were optimized to separate five typical carbohydrates and applied to analysis of four infant milk powders. The linear ranges of carbohydrate determination were 20-300mg/L for fructose and glucose, 20-250mg/L for sucrose and lactose, and 35-180mg/L for fructo-oligosaccharide. The LODs were 16.4mg/L for fructose and glucose, 17.3mg/L for sucrose, 20.0mg/L for lactose, and 46.7mg/L for fructo-oligosaccharide. Relative standard deviations (RSDs) ranged between 3.45-4.23%, 1.46-4.17%, 4.14-5.60%, 1.39-4.09%, and 2.49-3.61% for fructose, glucose, sucrose, lactose, and fructo-oilgosaccharide, respectively and recoveries ranged between 95.0 and 105.4%