Scholarly Works, Center for Soft Matter and Biological Physics
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- Signals of detailed balance violation in nonequilibrium stationary states: subtle, manifest, and extraordinaryZia, Royce K. P. (IOP Publishing, 2024-07-12)The evolution of physical systems are often modeled by simple Markovian processes. When settled into stationary states, the probability distributions of such systems are time independent, by definition. However, they do not necessarily fall within the framework of equilibrium statistical mechanics. Instead, they may be non-equilibrium steady states (NESS). One distinguishing feature of NESS is the presence of time reversal asymmetry (TRA) and persistent probability current loops. These loops lead naturally to the notion of probability angular momenta, which play a role on the same footing as the noise covariance in stochastic processes. Illustrating with simulations of simple models and physical data, we present ways to detect these signals of TRA, from the subtle to the prominent.
- Membrane Composition Modulates Vp54 Binding: A Combined Experimental and Computational StudyGuo, Wenhan; Dong, Rui; Okedigba, Ayoyinka O.; Sanchez, Jason E.; Agarkova, Irina V.; Abisamra, Elea-Maria; Jelinsky, Andrew; Riekhof, Wayne; Noor, Laila; Dunigan, David D.; Van Etten, James L.; Capelluto, Daniel G. S.; Xiao, Chuan; Li, Lin (MDPI, 2025-10-03)The recruitment of peripheral membrane proteins is tightly regulated by membrane lipid composition and local electrostatic microenvironments. Our experimental observations revealed that Vp54, a viral matrix protein, exhibited preferential binding to lipid bilayers enriched in anionic lipids such as phosphatidylglycerol (PG) and phosphatidylserine (PS), compared to neutral phosphatidylcholine/phosphatidylethanolamine liposomes, and this occurred in a curvature-dependent manner. To elucidate the molecular basis of this selective interaction, we performed a series of computational analyses including helical wheel projection, electrostatic potential calculations, electric field lines simulations, and electrostatic force analysis. Our results showed that the membrane-proximal region of Vp54 adopted an amphipathic α-helical structure with a positively charged interface. In membranes containing PG or PS, electrostatic potentials at the interface were significantly more negative, enhancing attraction with Vp54. Field line and force analyses further confirmed that both the presence and spatial clustering of anionic lipids intensify membrane–Vp54 electrostatic interactions. These computational findings align with experimental binding data, jointly demonstrating that membrane lipid composition and organization critically modulate Vp54 recruitment. Together, our findings highlight the importance of electrostatic complementarity and membrane heterogeneity in peripheral protein targeting and provide a framework applicable to broader classes of membrane-binding proteins.
- Implicit Solvent with Explicit Ions Generalized Born Model in Molecular Dynamics: Application to DNAKolesnikov, Egor S.; Xiong, Yeyue; Onufriev, Alexey V. (American Chemical Society, 2024-09-16)The ion atmosphere surrounding highly charged biomolecules, such as nucleic acids, is crucial for their dynamics, structure, and interactions. Here, we develop an approach for the explicit treatment of ions within an implicit solvent framework suitable for atomistic simulations of biomolecules. The proposed implicit solvent/explicit ions model, GBION, is based on a modified generalized Born (GB) model; it includes separate, modified GB terms for solute-ion and ion-ion interactions. The model is implemented in the AMBER package (version 24), and its performance is thoroughly investigated in atomistic molecular dynamics (MD) simulations of double-stranded DNA on a microsecond time scale. The aggregate characteristics of monovalent (Na+ and K+) and trivalent (Cobalt Hexammine, CoHex(3+)) counterion distributions around double-stranded DNA predicted by the model are in reasonable agreement with the experiment (where available), all-atom explicit water MD simulations, and the expectation from the Manning condensation theory. The radial distributions of monovalent cations around DNA are reasonably close to the ones obtained using the explicit water model: expressed in units of energy, the maximum deviations of local ion concentrations from the explicit solvent reference are within 1 k(B)T, comparable to the corresponding deviations expected between different established explicit water models. The proposed GBION model is able to simulate DNA fragments in a large volume of solvent with explicit ions with little additional computational overhead compared with the fully implicit GB treatment of ions. Ions simulated using the developed model explore conformational space at least 2 orders of magnitude faster than in the explicit solvent. These advantages allowed us to observe and explore an unexpected "stacking" mode of DNA condensation in the presence of trivalent counterions (CoHex(3+)) that was revealed by recent experiments.
- Optimal Dielectric Boundary for Binding Free Energy Estimates in the Implicit SolventForouzesh, Negin; Ghafouri, Fatemeh; Tolokh, Igor S.; Onufriev, Alexey V. (American Chemical Society, 2024-12-10)Accuracy of binding free energy calculations utilizing implicit solvent models is critically affected by parameters of the underlying dielectric boundary, specifically, the atomic and water probe radii. Here, a multidimensional optimization pipeline is used to find optimal atomic radii, specifically for binding calculations in the implicit solvent. To reduce overfitting, the optimization target includes separate, weighted contributions from both binding and hydration free energies. The resulting five-parameter radii set, OPT_BIND5D, is evaluated against experiment for binding free energies of 20 host-guest (H-G) systems, unrelated to the types of structures used in the training. The resulting accuracy for this H-G test set (root mean square error of 2.03 kcal/mol, mean signed error of -0.13 kcal/mol, mean absolute error of 1.68 kcal/mol, and Pearson's correlation of r = 0.79 with the experimental values) is on par with what can be expected from the fixed charge explicit solvent models. Best agreement with the experiment is achieved when the implicit salt concentration is set equal or close to the experimental conditions.
- Mechanistic modeling of mitosis: Insights from three collaborative case studiesChen, Jing; Cimini, Daniela (Elsevier, 2025-11-01)Mechanistic mathematical modeling has become an essential tool in modern biological research due to its powerful ability to integrate diverse data, generate hypotheses, and guide experimental design. It is particularly valuable for studying complex cellular mechanisms involving numerous interacting components. While the full dynamics of such systems usually elude direct experimental observation, modeling provides a means to integrate fragmented data with reasonable and/or informed assumptions into coherent mechanistic frameworks, simulate system behavior, and identify promising directions for further experimentation. When closely integrated with experiments, modeling can greatly accelerate progress in cell biology. However, the value of modeling is not automatic—it must be earned through careful model construction, critical interpretation of results, and thoughtful design of follow-up experiments. To demystify this process, we review three of our collaborative projects in mitosis, drawing on our experiences as a modeler and an experimentalist. We describe how the projects were initiated, why specific modeling approaches were chosen, how models were developed and refined, how model predictions guided new experiments, and how integrated modeling and experimentation led to deeper mechanistic insights. Finally, we emphasize that at the heart of every successful collaboration lies human connection. Productive cross-disciplinary communication is fundamental to bridging experimental and modeling perspectives and fully realizing the potential of integrative approaches in modern cell biology.
- Cholesterol modulates membrane elasticity via unified biophysical lawsKumarage, Teshani; Gupta, Sudipta; Morris, Nicholas B.; Doole, Fathima T.; Scott, Haden L.; Stingaciu, Laura-Roxana; Pingali, Sai Venkatesh; Katsaras, John; Khelashvili, George; Doktorova, Milka; Brown, Michael F.; Ashkar, Rana (Springer, 2025-07)Cholesterol and lipid unsaturation underlie a balance of opposing forces that features prominently in adaptive cell responses to diet and environmental cues. These competing factors have resulted in contradictory observations of membrane elasticity across different measurement scales, requiring chemical specificity to explain incompatible structural and elastic effects. Here, we demonstrate that - unlike macroscopic observations - lipid membranes exhibit a unified elastic behavior in the mesoscopic regime between molecular and macroscopic dimensions. Using nuclear spin techniques and computational analysis, we find that mesoscopic bending moduli follow a universal dependence on the lipid packing density regardless of cholesterol content, lipid unsaturation, or temperature. Our observations reveal that compositional complexity can be explained by simple biophysical laws that directly map membrane elasticity to molecular packing associated with biological function, curvature transformations, and protein interactions. The obtained scaling laws closely align with theoretical predictions based on conformational chain entropy and elastic stress fields. These findings provide unique insights into the membrane design rules optimized by nature and unlock predictive capabilities for guiding the functional performance of lipid-based materials in synthetic biology and real-world applications.
- Soybean Lectin Cross-Links Membranes by Binding Sulfatide in a Curvature-Dependent MannerOkedigba, Ayoyinka O.; Ng, Emery L.; Deegbey, Mawuli; Rosso, M. Luciana; Ngo, William; Xiao, Ruoshi; Huang, Haibo; Zhang, Bo; Welborn, Valerie; Capelluto, Daniel G. S. (American Chemical Society, 2025-05-24)Soybean (Glycine max) is a key source of plant-based protein, yet its nutritional value is impacted by antinutritional factors, including lectins. Whereas soybean lectin is known to bind N-acetyl-d-galactosamine (GalNAc), its lipid interactions remain unexplored. Using a novel purification method, we isolated lectin from soybean meals and characterized its interactions with GalNAc and the glycosphingolipid sulfatide. Isothermal titration calorimetry revealed micromolar affinity for GalNAc, whereas most GalNAc derivatives displayed weak or no binding. Lectin exhibited high-affinity binding to sulfatide in a membrane curvature-dependent manner. Binding of lectin to sulfatide promoted cross-linking of sulfatide-containing vesicles. Whereas sulfatide interaction was independent of GalNAc binding, suggesting distinct binding sites, vesicle cross-linking was inhibited by the sugar. Molecular dynamics simulations identified a consensus sulfatide-binding site in lectin. These findings highlight the dual ligand-binding properties of soybean lectin and may provide strategies to mitigate its antinutritional effects and improve soybean meal processing.
- Extreme Value Statistics of Community Detection in Complex Networks with Reduced Network Extremal Ensemble Learning (RenEEL)Ghosh, Tania; Zia, Royce K. P.; Bassler, Kevin E. (MDPI, 2025-06-13)Arguably, the most fundamental problem in Network Science is finding structure within a complex network. Often, this is achieved by partitioning the network’s nodes into communities in a way that maximizes an objective function. However, finding the maximizing partition is generally a computationally difficult NP-complete problem. Recently, a machine learning algorithmic scheme was introduced that uses information within a set of partitions to find a new partition that better maximizes an objective function. The scheme, known as RenEEL, uses Extremal Ensemble Learning. Starting with an ensemble of K partitions, it updates the ensemble by considering replacing its worst member with the best of L partitions found by analyzing a reduced network formed by collapsing nodes, which all the ensemble partitions agree should be grouped together, into super-nodes. The updating continues until consensus is achieved within the ensemble about what the best partition is. The original K ensemble partitions and each of the L partitions used for an update are found using a simple “base” partitioning algorithm. We perform an empirical study of how the effectiveness of RenEEL depends on the values of K and L and relate the results to the extreme value statistics of record-breaking. We find that increasing K is generally more effective than increasing L for finding the best partition.
- Red blood cell aggregation within a blood clot causes platelet-independent clot shrinkagePeshkova, Alina; Rednikova, Ekaterina; Khismatullin, Rafael; Kim, Oleg; Muzykantov, Vladimir; Purohit, Prashant; Litvinov, Rustem; Weisel, John (American Society of Hematology, 2025-04-16)Platelet-driven blood clot contraction (retraction) is important for hemostasis and thrombosis. RBCs occupy about half of the clot volume, but their possible active contribution to contraction is unknown. The work was aimed at elucidating the ability of RBCs to promote clot shrinkage. To distinguish effects of platelets and RBCs, we formed thrombin-induced clots from reconstituted human samples containing platelet-free plasma and platelet-depleted RBCs, followed by tracking the clot size. The clots before and after RBC-induced shrinkage were analyzed using histology and scanning electron microscopy. Tension developed in the RBC-containing plasma clots was measured with rheometry and theoretical modeling was used to elucidate the clot shrinkage mechanisms. Platelet-depleted clots formed in the presence of RBCs exhibited >20% volume shrinkage within one hour. This process was insensitive to blebbistatin, latrunculin A, and abciximab. At a higher RBC count clot shrinkage increased, whereas in the absence of RBCs no plasma clot shrinkage was observed. At low platelet counts RBCs stimulated clot contraction proportionately to the platelet level. Inside the shrunken clots, RBCs formed aggregates. The average tensile force per one RBC was ~120±100 pN. Clots from purified fibrinogen formed in the presence of RBCs did not change in size, but underwent shrinkage in the presence of osmotically active dextran. Blood clot shrinkage can be caused by RBCs alone and this effect is due to the RBC aggregation driven mainly by osmotic depletion. The RBC-induced clot shrinkage may reinforce platelet-driven blood clot contraction and promote clot compaction when there are few and/or dysfunctional platelets.
- High-Efficiency Multilevel Phase Lenses with Nanostructures on Polyimide MembranesHowe, Leslie; Rajapaksha, Tharindu D.; Ellepola, Kalani H.; Ho, Vinh X.; Aycock, Zachary; Nguyen, Minh L. P.; Leckey, John P.; Macdonnell, Dave G.; Kim, Hyun Jung; Vinh, Nguyen Q. (Wiley- VCH, 2024-07-16)The emergence of planar meta-lenses on flexible materials has profoundly impacted the long-standing perception of diffractive optics. Despite their advantages, these lenses still face challenges in design and fabrication to obtain high focusing efficiency and resolving power. A nanofabrication technique is demonstrated based on photolithography and polyimide casting for realizing membrane-based multilevel phase-type Fresnel zone plates (FZPs) with high focusing efficiency. By employing advantageous techniques, these lenses with nanostructures are directly patterned into thin polyimide membranes. The computational and experimental results have indicated that the focusing efficiency of these nanostructures at the primary focus increases significantly with increasing the number of phase levels. Specifically, 16-level phase lenses on a polyimide membrane can achieve a focusing efficiency of more than 91.6% of the input signal (9.5 times better than that of a conventional amplitude-type FZP) and focus light into a diffraction-limited spot together with very weak side-lobes. Furthermore, these lenses exhibit considerably reduced unwanted diffraction orders and produce extremely low background signals. The potential impact of these lenses extends across various applications and techniques including microscopy, imaging, micro-diffraction, remote sensing, and space flight instruments which require lightweight and flexible configurations.
- Aurora B inhibition induces hyper-polyploidy and loss of long-term proliferative potential in RB and p53 defective cellsVora, Shivam; Chatterjee, Saptarshi; Andrew, Ariel; Kumar, Ramyashree Prasanna; Proctor, Martina; Zeng, Zhen; Bhatt, Rituparna; Nazareth, Deborah; Fernando, Madushan; Jones, Mathew J. K.; He, Yaowu; Hooper, John D.; McMillan, Nigel A. J.; Urosevic, Jelena; Saeh, Jamal; Travers, Jon; Cimini, Daniela; Chen, Jing; Gabrielli, Brian (Springer Nature, 2025-01-08)Polyploidy is a common outcome of chemotherapies, but there is conflicting evidence as to whether polyploidy is an adverse, benign or even favourable outcome. We show Aurora B kinase inhibitors efficiently promote polyploidy in many cell types, resulting in the cell cycle exit in RB and p53 functional cells, but hyper-polyploidy in cells with loss of RB and p53 function. These hyper-polyploid cells (>8n DNA content) are viable but have lost long-term proliferative potential in vitro and fail to form tumours in vivo. Investigation of mitosis in these cells revealed high numbers of centrosomes that were capable of supporting functional mitotic spindle poles, but these failed to progress to anaphase/telophase structures even when AURKB inhibitor was removed after 2–3 days. However, when AURKB inhibitor was removed after 1 day and cells had failed a single cytokinesis to become tetraploid, they retained colony forming ability and long-term proliferative potential. Mathematical modelling of the potential for polyploid cells to produce viable daughter cells demonstrated that cells with >8n DNA and >4 functional spindle poles approach zero probability of a viable daughter, supporting our experimental observations. These findings demonstrate that tetraploidy is tolerated by tumour cells, but higher ploidy states are incompatible with long-term proliferative potential.
- Durotaxis and extracellular matrix degradation promote clustering of cancer cellsPotomkin, Mykhailo; Kim, Oleg V.; Klymenko, Yuliya; Alber, Mark; Aronson, Igor S. (Elsevier, 2025-01-24)Early stages of metastasis depend on the collective behavior of cancer cells and their interaction 23 with the extracellular matrix (ECM). Cancer cell clusters are known to exhibit higher metastatic 24 potential than single cells. To explore clustering dynamics, we developed a calibrated computa- 25 tional model describing how motile cancer cells biochemically and biomechanically interact with 26 the ECM during the initial invasion phase, including ECM degradation and mechanical remod- 27 eling. The model reveals that cluster formation time, size, and shape are influenced by ECM 28 degradation rates and cellular responsiveness to external stresses (durotaxis). The results align 29 with experimental observations, demonstrating distinct cell trajectories and cluster morphologies 30 shaped by biomechanical parameters. These simulations provide valuable insights into cancer 31 invasion dynamics and may suggest potential therapeutic strategies targeting early-stage inva- 32 sive cells.
- Computing macroscopic reaction rates in reaction-diffusion systems using Monte Carlo lattice simulationsSwailem, Mohamed; Täuber, Uwe C. (American Physical Society, 2024-07-17)Stochastic reaction-diffusion models are employed to represent many complex physical, biological, societal, and ecological systems. The macroscopic reaction rates describing the large-scale, long-time kinetics in such systems are effective, scale-dependent renormalized parameters that need to be either measured experimentally or computed by means of a microscopic model. In a Monte Carlo simulation of stochastic reaction-diffusion systems, microscopic probabilities for specific events to happen serve as the input control parameters. To match the results of any computer simulation to observations or experiments carried out on the macroscale, a mapping is required between the microscopic probabilities that define the Monte Carlo algorithm and the macroscopic reaction rates that are experimentally measured. Finding the functional dependence of emergent macroscopic rates on the microscopic probabilities (subject to specific rules of interaction) is a very difficult problem, and there is currently no systematic, accurate analytical way to achieve this goal. Therefore, we introduce a straightforward numerical method of using lattice Monte Carlo simulations to evaluate the macroscopic reaction rates by directly obtaining the count statistics of how many events occur per simulation time step. Our technique is first tested on well-understood fundamental examples, namely, restricted birth processes, diffusion-limited two-particle coagulation, and two-species pair annihilation kinetics. Next we utilize the thus gained experience to investigate how the microscopic algorithmic probabilities become coarse-grained into effective macroscopic rates in more complex model systems such as the Lotka-Volterra model for predator-prey competition and coexistence, as well as the rock-paper-scissors or cyclic Lotka-Volterra model and its May-Leonard variant that capture population dynamics with cyclic dominance motifs. Thereby we achieve a more thorough and deeper understanding of coarse graining in spatially extended stochastic reaction-diffusion systems and the nontrivial relationships between the associated microscopic and macroscopic model parameters, with a focus on ecological systems. The proposed technique should generally provide a useful means to better fit Monte Carlo simulation results to experimental or observational data.
- Stochastic spatial Lotka-Volterra predator-prey modelsTäuber, Uwe C. (World Scientific, 2024-10-15)Dynamical models of interacting populations are of fundamental interest for spontaneous pattern formation and other noise-induced phenomena in nonequilibrium statistical physics. Theoretical physics in turn provides a quantitative toolbox for paradigmatic models employed in (bio-)chemistry, biology, ecology, epidemiology, and even sociology. Stochastic, spatially extended models for predator-prey interaction display spatio-temporal structures that are not captured by the Lotka– Volterra mean-field rate equations. These spreading activity fronts reflect persistent correlations between predators and prey that can be analyzed through field-theoretic methods. Introducing local restrictions on the prey population induces a predator extinction threshold, with the critical dynamics at this continuous active-to-absorbing state transition governed by the scaling exponents of directed percolation. Novel features in biologically motivated model variants include the stabilizing effect of a periodically varying carrying capacity that describes seasonally oscillating resource availability; enhanced mean species densities and local fluctuations caused by spatially varying reaction rates; and intriguing evolutionary dynamics emerging when variable interaction rates are affixed to individuals combined with trait inheritance to their offspring. The basic susceptible-infected-susceptible and susceptible-infected-recovered models for infectious disease spreading near their epidemic thresholds are respectively captured by the directed and dynamic isotropic percolation universality classes. Systems with three cyclically competing species akin to spatial rock-paper-scissors games may display striking spiral patterns, yet conservation laws can prevent such noise-induced structure formation. In diffusively coupled inhomogeneous settings, one may observe the stabilization of vulnerable ecologies prone to finite-size extinction or fixation due to immigration waves emanating from the interfaces.
- Computing macroscopic reaction rates in reaction-diffusion systems using Monte Carlo simulationsSwailem, Mohamed; Täuber, Uwe C. (2024-07-17)Stochastic reaction-diffusion models are employed to represent many complex physical, biological, societal, and ecological systems. The macroscopic reaction rates describing the large-scale, longtime kinetics in such systems are effective, scale-dependent renormalized parameters that need to be either measured experimentally or computed by means of a microscopic model. In a Monte Carlo simulation of stochastic reaction-diffusion systems, microscopic probabilities for specific events to happen serve as the input control parameters. To match the results of any computer simulation to observations or experiments carried out on the macroscale, a mapping is required between the microscopic probabilities that define the Monte Carlo algorithm and the macroscopic reaction rates that are experimentally measured. Finding the functional dependence of emergent macroscopic rates on the microscopic probabilities (subject to specific rules of interaction) is a very difficult problem, and there is currently no systematic, accurate analytical way to achieve this goal. Therefore, we introduce a straightforward numerical method of using lattice Monte Carlo simulations to evaluate the macroscopic reaction rates by directly obtaining the count statistics of how many events occur per simulation time step. Our technique is first tested on well-understood fundamental examples, namely restricted birth processes, diffusion-limited two-particle coagulation, and two-species pair annihilation kinetics. Next we utilize the thus gained experience to investigate how the microscopic algorithmic probabilities become coarse-grained into effective macroscopic rates in more complex model systems such as the Lotka–Volterra model for predator-prey competition and coexistence, as well as the rock-paper-scissors or cyclic Lotka–Volterra model as well as its May–Leonard variant that capture population dynamics with cyclic dominance motifs. Thereby we achieve a more thorough and deeper understanding of coarse-graining in spatially extended stochastic reaction-diffusion systems and the nontrivial relationships between the associated microscopic and macroscopic model parameters, with a focus on ecological systems. The proposed technique should generally provide a useful means to better fit Monte Carlo simulation results to experimental or observational data.
- Molecular modeling of Poly(methyl methacrylate-block-acrylonitrile) as Precursors of Porous Carbon FibersHao, Xi; Serrano, Joel; Liu, Guoliang; Cheng, Shengfeng (2023-04-22)
- Inducing stratification of colloidal mixtures with a mixed binary solventLiu, Binghan; Grest, Gary S.; Cheng, Shengfeng (Royal Society of Chemistry, 2023-12-06)Molecular dynamics simulations are used to demonstrate that a binary solvent can be used to stratify colloidal mixtures when the suspension is rapidly dried. The solvent consists of two components, one more volatile than the other. When evaporated at high rates, the more volatile component becomes depleted near the evaporation front and develops a negative concentration gradient from the bulk of the mixture to the liquid-vapor interface while the less volatile solvent is enriched in the same region and exhibit a positive concentration gradient. Such gradients can be used to drive a binary mixture of colloidal particles to stratify if one is preferentially attracted to the more volatile solvent and the other to the less volatile solvent. During solvent evaporation, the fraction of colloidal particles preferentially attracted to the less volatile solvent is enhanced at the evaporation front, whereas the colloidal particles having stronger attractions with the more volatile solvent are driven away from the interfacial region. As a result, the colloidal particles show a stratified distribution after drying, even if the two colloids have the same size.
- Chain conformations and phase separation in polymer solutions with varying solvent qualityHuang, Yisheng; Cheng, Shengfeng (Wiley, 2021-10-02)Molecular dynamics simulations are used to investigate the conformations of a single polymer chain, represented by the Kremer-Grest bead-spring model, in a solution with a Lennard-Jones liquid as the solvent when the interaction strength between the polymer and solvent is varied. Results show that when the polymer-solvent interaction is unfavorable, the chain collapses as one would expect in a poor solvent. For more attractive polymer-solvent interactions, the solvent quality improves and the chain is increasingly solvated and exhibits ideal and then swollen conformations. However, as the polymer-solvent interaction strength is increased further to be more than about twice the strength of the polymer-polymer and solvent-solvent interactions, the chain exhibits an unexpected collapsing behavior. Correspondingly, for strong polymer-solvent attractions, phase separation is observed in the solutions of multiple chains. These results indicate that the solvent becomes effectively poor again at very attractive polymer-solvent interactions. Nonetheless, the mechanism of chain collapsing and phase separation in this limit differs from the case with a poor solvent rendered by unfavorable polymer-solvent interactions. In the latter, the solvent is excluded from the domain of the collapsed chains while in the former, the solvent is still present in the pervaded volume of a collapsed chain or in the polymer-rich domain that phase separates from the pure solvent. In the limit of strong polymer-solvent attractions, the solvent behaves as a glue to stick monomers together, causing a single chain to collapse and multiple chains to aggregate and phase separate.
- The effects of molecular and nanoscopic additives on phospholipid membranesKumarage, Teshani; Morris, Nicholas B.; Ashkar, Rana (Frontiers, 2023-11-20)Lipid bilayers—the main matrix of cell membranes—are a paradigm of soft molecular assemblies whose properties have been evolutionarily optimized to satisfy the functional requirements of cells. For instance, lipid bilayers must be rigid enough to serve as the protective barrier between cells and their environment, yet fluid enough to enable the diffusion of proteins and molecular clusters necessary for biological functions. Inspired by their biological multifunctionality, lipid membranes have also been used as a central design element in many practical applications including artificial cells, drug nanocarriers, and biosensors. Whether biological or synthetic, lipid membranes often involve molecular or nanoscopic additives that modulate the membrane properties through various mechanisms. Hence, how lipid membranes respond to additives has justifiably drawn much attention in recent years. This review summarizes findings and observations on different classes of additives and their effects on structural, thermodynamic, elastic, and dynamical membrane properties that are central to biological function or synthetic membrane performance. The review primarily focuses on phospholipids as a major component of cell membranes and a widely used lipid type in synthetic membrane designs.
- Diffusiophoresis as a physical mechanism underlying small-on-top stratification in evaporating bidisperse nanoparticle suspensionsLiu, Binghan; Grest, Gary; Cheng, Shengfeng (2023-05-17)