Influence of the Dielectric Constant on the Ionic Current Rectification of Bipolar Nanopores.

In this paper, we investigate how the dielectric constant, ϵ, of an electrolyte solvent influences the current rectification characteristics of bipolar nanopores. It is well recognized that bipolar nanopores with two oppositely charged regions rectify current when exposed to an alternating electric potential difference. Here, we consider dilute electrolytes with NaCl only and with a mixture of NaCl and charged nanoparticles. These systems are studied using two levels of description, all-atom explicit water molecular dynamics (MD) simulations and coarse-grained implicit solvent MD simulations. The charge density and electric potential profiles and current-voltage relationship predicted by the implicit solvent simulations with ϵ = 11.3 show good agreement with the predictions from the explicit water simulations. Under nonequilibrium conditions, the predictions of the implicit solvent simulations with a dielectric constant closer to the one of bulk water are significantly different from the predictions obtained with the explicit water model. These findings are closely aligned with experimental data on the dielectric constant of water when confined to nanometric spaces, which suggests that ϵ decreases significantly compared to its value in the bulk. Moreover, the largest electric current rectification is observed in systems containing nanoparticles when ϵ = 78.8. Using enhanced sampling, we have shown that this larger rectification arises from the presence of a significantly deeper minimum in the free energy of the system with a larger ϵ, and when a negative voltage bias is applied. Since implicit solvent models and mean-field continuum theories are often used to design Janus membranes based on bipolar nanopores, this work highlights the importance of properly accounting for the effects of confinement on the dielectric constant of the electrolyte solvent. The results presented here indicate that the dielectric constant in implicit solvent simulations may be used as an adjustable parameter to approximately account for the effects of nanometric confinement on aqueous electrolyte solvents.

Generation and Propagation of Flexoelectricity-Induced Solitons in Nematic Liquid Crystals.

Solitons in nematic liquid crystals facilitate the rapid transport and sensing in microfluidic systems. Little is known about the elementary conditions needed to create solitons in nematic materials. In this study, we apply a combination of theory, computational simulations, and experiments to examine the formation and propagation of solitary waves, or "solitons", in nematic liquid crystals under the influence of an alternating current (AC) electric field. We find that these solitary waves exhibit "butterfly"-like or "bullet"-like structures that travel in the direction perpendicular to the applied electric field. Such structures propagate over long distances without losing their initial shape. The theoretical framework adopted here helps identify several key factors leading to the formation of solitons in the absence of electrostatic interactions. These factors include surface irregularities, flexoelectric polarization, unequal elastic constants, and negative anisotropic dielectric permittivity. The results of simulations are shown to be in good agreement with our own experimental observations, serving to establish the validity of the theoretical concepts and ideas advanced in this work.

Phase Behavior and Conformational Asymmetry near the Comb-to-Bottlebrush Transition in Linear-Brush Block Copolymers.

This study explores how conformational asymmetry influences the bulk phase behavior of linear-brush block copolymers. We synthesized 60 diblock copolymers composed of poly(trifluoroethyl methacrylate) as the linear block and poly[oligo(ethylene glycol) methyl ether methacrylate] as the brush block, varying the molecular weight, composition, and side-chain length to introduce different degrees of conformational asymmetry. Using small-angle X-ray scattering, we determined the morphology and phase diagrams for three different side-chain length systems, mainly observing lamellar and cylindrical phases. Increasing the side-chain length of the brush block from three to nine ethylene oxide units introduces sufficient asymmetry between the blocks to alter the phase behavior, shifting the lamellar-to-cylindrical transitions toward lower brush block compositions and transitioning the brush block from the dense comb-like regime to the bottlebrush regime. Coarse-grained simulations support our experimental observations and provide a mapping between the composition and conformational asymmetry. A comparison of our findings to strong stretching theory across multiple phase boundary predictions confirms the transition between the dense comb-like regime and the bottlebrush regime.

Synthetic and Computational Design Insights toward Mimicking Protein Binding of Phosphate.

The unique and precise capabilities of proteins are renowned for their specificity and range of application. Effective mimicking of protein-binding offers enticing potential to direct their abilities toward useful applications, but it is nevertheless quite difficult to realize this characteristic of protein behavior in a synthetic material. Here, we design, synthesize, and evaluate experimentally and computationally a series of multicomponent phosphate-binding peptide amphiphile micelles to derive design insights into how protein binding behavior translates to synthetic materials. By inserting the Walker A P-loop binding motif into this peptide synthetic material, we successfully implemented the protein-binding design parameters of hydrogen-bonding and electrostatic interaction to bind phosphate completely and selectively in this highly tunable synthetic platform. Moreover, in this densely arrayed peptide environment, we use molecular dynamics simulations to identify an intriguing mechanistic shift of binding that is inaccessible in traditional proteins, introducing two corresponding new design elements─flexibility and minimization of the loss of entropy due to ion binding, in protein-analogous synthetic materials. We then translate these new design factors to de novo peptide sequences that bind phosphate independent of protein-extracted sequence or conformation. Overall, this work reveals that traditional complex conformational restrictions of binding by proteins can be replaced and repurposed in a multicomponent peptide amphiphile synthetic material, opening up opportunities for future enhanced protein-inspired design.

Control of liquid crystals combining surface acoustic waves, nematic flows, and microfluidic confinement.

The optical properties of liquid crystals serve as the basis for display, diagnostic, and sensing technologies. Such properties are generally controlled by relying on electric fields. In this work, we investigate the effects of microfluidic flows and acoustic fields on the molecular orientation and the corresponding optical response of nematic liquid crystals. Several previously unknown structures are identified, which are rationalized in terms of a state diagram as a function of the strengths of the flow and the acoustic field. The new structures are interpreted by relying on calculations with a free energy functional expressed in terms of the tensorial order parameter, using continuum theory simulations in the Landau-de Gennes framework. Taken together, the findings presented here offer promise for the development of new systems based on combinations of sound, flow, and confinement.

Minimal Model of Solitons in Nematic Liquid Crystals.

Solitons in liquid crystals have generated considerable interest. Several hypotheses of varying complexity have been advanced to explain how they arise, but consensus has not emerged yet about the underlying forces responsible for their formation or their structure. In this work, we present a minimal model for solitons in achiral nematic liquid crystals, which reveals the key requirements needed to generate them in the absence of added charges. These include a surface inhomogeneity, consisting of an adsorbed particle capable of producing a twist, flexoelectricity, dielectric contrast, and an applied ac electric field that can couple to the director's orientation. Our proposed model is based on a tensorial representation of a confined liquid crystal, and it predicts the formation of "butterfly" structures, quadrupolar in character, in regions of a slit channel where the director is twisted by the surface imperfection. As the applied electric field is increased, solitons (or "bullets") become detached from the wings of the butterfly, and then propagate rapidly throughout the system. The main observations that emerge from the model, including the formation and structure of butterflies, bullets, and stripes, as well as the role of surface inhomogeneity and the strength of the applied field, are consistent with experimental findings presented here for nematic LCs confined between two chemically treated parallel plates.

Structural and Mechanical Response of Two-Component Photoswitchable Lipid Bilayer Vesicles.

Optical control of phospholipids is an attractive option for the rapid, reversible, and tunable manipulation of membrane structure and dynamics. Azo-PC, a lipid with an azobenzene group within one acyl chain, undergoes a light-induced trans-to-cis isomerization and thus arises as a powerful tool for manipulating lipid order and dynamics. Here, we report on vesicle-scale micropipette measurements and atomistic simulations to probe the elastic stretching modulus, water permeability, toughness, thickness, and membrane area upon isomerization. We investigated both dynamics and steady-state properties. In pure azo-PC membranes, we found that the molecular area in trans was 16% smaller than that in cis, the membrane's stretching modulus kA was 2.5 ± 0.3 times greater, and the water permeability PW was 3.5 ± 0.5 times smaller. We also studied mixtures of azo-PC with the miscible, unsaturated lipid DOPC. Atomistic molecular dynamics simulations show how the membrane thickness, chain order, and correlations across membrane leaflets explain the experimental data. Together, these data show how one rotating bond changes the molecular- and membrane-scale properties. These results will be useful for photopharmacology and for developing new materials whose permeability, elasticity, and toughness may be switched on demand.

Structure and Dynamics of Hybrid Colloid-Polyelectrolyte Coacervates: Insights from Molecular Simulations.

Electrostatic interactions in polymeric systems are responsible for a wide range of liquid-liquid phase transitions that are of importance for biology and materials science. Such transitions are referred to as complex coacervation, and recent studies have sought to understand the underlying physics and chemistry. Most theoretical and simulation efforts to date have focused on oppositely charged linear polyelectrolytes, which adopt nearly ideal-coil conformations in the condensed phase. However, when one of the coacervate components is a globular protein, a better model of complexation should replace one of the species with a spherical charged particle or colloid. In this work, we perform coarse-grained simulations of colloid-polyelectrolyte coacervation using a spherical model for the colloid. Simulation results indicate that the electroneutral cell of the resulting (hybrid) coacervates consists of a polyelectrolyte layer adsorbed on the colloid. Power laws for the structure and the density of the condensed phase, which are extracted from simulations, are found to be consistent with the adsorption-based scaling theory of hybrid coacervation. The coacervates remain amorphous (disordered) at a moderate colloid charge, Q, while an intra-coacervate colloidal crystal is formed above a certain threshold, at Q > Q*. In the disordered coacervate, if Q is sufficiently low, colloids diffuse as neutral nonsticky nanoparticles in the semidilute polymer solution. For higher Q, adsorption is strong and colloids become effectively sticky. Our findings are relevant for the coacervation of polyelectrolytes with proteins, spherical micelles of ionic surfactants, and solid organic or inorganic nanoparticles.

Entanglements via Slip Springs with Soft, Coarse-Grained Models for Systems Having Explicit Liquid-Vapor Interfaces.

Recent advances in nano-rheology require that new techniques and models be developed to precisely describe the equilibrium and non-equilibrium characteristics of entangled polymeric materials and their interfaces at a molecular level. In this study, a slip-spring (SLSP) model is proposed to capture the dynamics of entangled polymers at interfaces, including those between liquids, liquids and vapors, and liquids and solids. The SLSP model employs a highly coarse-grained approach, which allows for comprehensive simulations of entire nano-rheological characterization systems using a particle-level description. The model relies on many-body dissipative particle dynamics (MDPD) non-bonded interactions, which permit explicit description of liquid-vapor interfaces; a compensating potential is introduced to ensure an unbiased representation of the shape of the liquid-vapor interface within the SLSP model. The usefulness of the proposed MDPD + SLSP approach is illustrated by simulating a capillary breakup rheometer (CaBR) experiment, in which a liquid droplet splits into two segments under the influence of capillary forces. We find that the predictions of the MDPD + SLSP model are consistent with experimental measurements and theoretical predictions. The proposed model is also verified by comparison to the results of explicit molecular dynamics simulations of an entangled polymer melt using a Kremer-Grest chain representation, both at equilibrium and far from equilibrium. Taken together, the model and methods presented in this study provide a reliable framework for molecular-level interpretation of high-polymer dynamics in the presence of interfaces.

Entropic Penalty Switches Li+ Solvation Site Formation and Transport Mechanisms in Mixed Polarity Copolymer Electrolytes.

Emerging solid polymer electrolyte (SPE) designs for efficient Li-ion (Li+) conduction have relied on polarity and mobility contrast to improve conductivity. To further develop this concept, we employ simulations to examine Li+ solvation and transport in poly(oligo ethylene methacrylate) (POEM) and its copolymers with poly(glycerol carbonate methacrylate) (PGCMA). We find that Li+ is solvated by ether oxygens instead of the highly polar PGCMA, due to lower entropic penalties. The presence of PGCMA promotes single-chain solvation, thereby suppressing interchain Li+ hopping. The conductivity difference between random copolymer PGCMA-r-POEM and block copolymer PGCMA-b-POEM is explained in terms of a hybrid solvation site mechanism. With diffuse microscopic interfaces between domains, PGCMA near the POEM contributes to Li+ transport by forming hybrid solvation sites. The formation of such sites is hindered when PGCMA is locally concentrated. These findings help explain how thermodynamic driving forces govern Li+ solvation and transport in mixed SPEs.

Molecular analysis of the type III interferon complex and its applications in protein engineering.

Type III interferons (IFNλs) are cytokines with critical roles in the immune system and are attractive therapeutic candidates due to their tissue-specific activity. Despite entering several clinical trials, results have demonstrated limited efficacy and potency, partially attributed to low-affinity protein-protein interactions (PPIs) responsible for receptor complex formation. Subsequently, structural studies of the native IFNλ signaling complexes remain inaccessible. While protein engineering can overcome affinity limitations, tools to investigate low-affinity systems like these remain limited. To provide insights into previous efforts to strengthen the PPIs within this complex, we perform a molecular analysis of the extracellular ternary complexes of IFNλ3 using both computational and experimental approaches. We first use molecular simulations and modeling to quantify differences in PPIs and residue strain fluctuations, generate detailed free energy landscapes, and reveal structural differences between an engineered, high-affinity complex, and a model of the wild-type, low-affinity complex. This analysis illuminates distinct behaviors of these ligands, yielding mechanistic insights into IFNλ complex formation. We then apply these computational techniques in protein engineering and design by utilizing simulation data to identify hotspots of interaction to rationally engineer the native cytokine-receptor complex for increased stability. These simulations are then validated by experimental techniques, showing that a single mutation at a computationally predicted site of interaction between the two receptors increases PPIs and improves complex formation for all IFNλs. This study highlights the power of molecular dynamics simulations for protein engineering and design as applied to the IFNλ family but also presents a potential tool for analysis and engineering of other systems with low-affinity PPIs.

Measuring response functions of active materials from data.

From flocks of birds to biomolecular assemblies, systems in which many individual components independently consume energy to perform mechanical work exhibit a wide array of striking behaviors. Methods to quantify the dynamics of these so-called active systems generally aim to extract important length or time scales from experimental fields. Because such methods focus on extracting scalar values, they do not wring maximal information from experimental data. We introduce a method to overcome these limitations. We extend the framework of correlation functions by taking into account the internal headings of displacement fields. The functions we construct represent the material response to specific types of active perturbation within the system. Utilizing these response functions we query the material response of disparate active systems composed of actin filaments and myosin motors, from model fluids to living cells. We show we can extract critical length scales from the turbulent flows of an active nematic, anticipate contractility in an active gel, distinguish viscous from viscoelastic dissipation, and even differentiate modes of contractility in living cells. These examples underscore the vast utility of this method which measures response functions from experimental observations of complex active systems.

Development of Masitinib Derivatives with Enhanced Mpro Ligand Efficiency and Reduced Cytotoxicity.

Recently, a high-throughput screen of 1900 clinically used drugs identified masitinib, an orally bioavailable tyrosine kinase inhibitor, as a potential treatment for COVID-19. Masitinib acts as a broad-spectrum inhibitor for human coronaviruses, including SARS-CoV-2 and several of its variants. In this work, we rely on atomistic molecular dynamics simulations with advanced sampling methods to develop a deeper understanding of masitinib's mechanism of Mpro inhibition. To improve the inhibitory efficiency and to increase the ligand selectivity for the viral target, we determined the minimal portion of the molecule (fragment) that is responsible for most of the interactions that arise within the masitinib-Mpro complex. We found that masitinib forms highly stable and specific H-bond interactions with Mpro through its pyridine and aminothiazole rings. Importantly, the interaction with His163 is a key anchoring point of the inhibitor, and its perturbation leads to ligand unbinding within nanoseconds. Based on these observations, a small library of rationally designed masitinib derivatives (M1-M5) was proposed. Our results show increased inhibitory efficiency and highly reduced cytotoxicity for the M3 and M4 derivatives compared to masitinib.

Denoising Autoencoder Trained on Simulation-Derived Structures for Noise Reduction in Chromatin Scanning Transmission Electron Microscopy.

Scanning transmission electron microscopy tomography with ChromEM staining (ChromSTEM), has allowed for the three-dimensional study of genome organization. By leveraging convolutional neural networks and molecular dynamics simulations, we have developed a denoising autoencoder (DAE) capable of postprocessing experimental ChromSTEM images to provide nucleosome-level resolution. Our DAE is trained on synthetic images generated from simulations of the chromatin fiber using the 1-cylinder per nucleosome (1CPN) model of chromatin. We find that our DAE is capable of removing noise commonly found in high-angle annular dark field (HAADF) STEM experiments and is able to learn structural features driven by the physics of chromatin folding. The DAE outperforms other well-known denoising algorithms without degradation of structural features and permits the resolution of α-tetrahedron tetranucleosome motifs that induce local chromatin compaction and mediate DNA accessibility. Notably, we find no evidence for the 30 nm fiber, which has been suggested to serve as the higher-order structure of the chromatin fiber. This approach provides high-resolution STEM images that allow for the resolution of single nucleosomes and organized domains within chromatin dense regions comprising of folding motifs that modulate the accessibility of DNA to external biological machinery.

Scattering evidence of positional charge correlations in polyelectrolyte complexes.

Polyelectrolyte complexation plays an important role in materials science and biology. The internal structure of the resultant polyelectrolyte complex (PEC) phase dictates properties such as physical state, response to external stimuli, and dynamics. Small-angle scattering experiments with X-rays and neutrons have revealed structural similarities between PECs and semidilute solutions of neutral polymers, where the total scattering function exhibits an Ornstein-Zernike form. In spite of consensus among different theoretical predictions, the existence of positional correlations between polyanion and polycation charges has not been confirmed experimentally. Here, we present small-angle neutron scattering profiles where the polycation scattering length density is matched to that of the solvent to extract positional correlations among anionic monomers. The polyanion scattering functions exhibit a peak at the inverse polymer screening radius of Coulomb interactions, q* ≈ 0.2 Å-1. This peak, attributed to Coulomb repulsions between the fragments of polyanions and their attractions to polycations, is even more pronounced in the calculated charge scattering function that quantifies positional correlations of all polymer charges within the PEC. Screening of electrostatic interactions by adding salt leads to the gradual disappearance of this correlation peak, and the scattering functions regain an Ornstein-Zernike form. Experimental scattering results are consistent with those calculated from the random phase approximation, a scaling analysis, and molecular simulations.

Functional soft materials from blue phase liquid crystals.

Blue phase (BP) liquid crystals are chiral fluids wherein millions of molecules self-assemble into cubic lattices that are on the order of hundred nanometers. As the unit cell sizes of BPs are comparable to the wavelength of light, they exhibit selective Bragg reflections in the visible. The exploitation of the photonic properties of BPs for technological applications is made possible through photopolymerization, a process that renders mechanical robustness and thermal stability. We review here the preparation and characterization of stimuli-responsive, polymeric photonic crystals based on BPs. We highlight recent studies that demonstrate the promise that polymerized BP photonic crystals hold for colorimetric sensing and dynamic light control. We review using Landau-de Gennes simulations for predicting the self-assembly of BPs and the potential for using theory to guide experimental design. Finally, opportunities for using BPs to synthesize new soft materials, such as highly structured polymer meshes, are discussed.

Systematic modification of functionality in disordered elastic networks through free energy surface tailoring.

A combined machine learning-physics-based approach is explored for molecular and materials engineering. Specifically, collective variables, akin to those used in enhanced sampled simulations, are constructed using a machine learning model trained on data gathered from a single system. Through the constructed collective variables, it becomes possible to identify critical molecular interactions in the considered system, the modulation of which enables a systematic tailoring of the system's free energy landscape. To explore the efficacy of the proposed approach, we use it to engineer allosteric regulation and uniaxial strain fluctuations in a complex disordered elastic network. Its successful application in these two cases provides insights regarding how functionality is governed in systems characterized by extensive connectivity and points to its potential for design of complex molecular systems.

Curvature and confinement effects on chiral liquid crystal morphologies.

Chiral liquid crystals (ChLCs) exhibit an inherent twist that originates at the molecular scale and can extend over multiple length scales when unconstrained. Under confinement, the twist is thwarted, leading to formation of defects in the molecular order that offer distinct optical responses and opportunities for colloidal driven assembly. Past studies have explored spheroidal confinement down to the nanoscopic regime, where curved boundaries produce surface defects to accommodate topological constraints and restrict the propagation of cuboidal defect networks. Similarly, strict confinement in channels and shells has been shown to give rise to escaped configurations and skyrmions. However, little is known about the role of extrinsic curvature in the development of cholesteric textures and Blue Phases (BP). In this paper, we examine the palette of morphologies that arises when ChLCs are confined in toroidal and cylindrical cavities. The equilibrium morphologies are obtained following an annealing strategy of a Landau-de Gennes free energy functional. Three dimensionless groups are identified to build phase diagrams: the natural twist, the ratio of elastic energies, and the circumscription of a BP cell. Curvature is shown to introduce helical features that are first observed as a Double Twist, and progress to Chiral Ribbons and, ultimately, Helical BP and BP. Chiral ribbons are examined as useful candidates for driven assembly given their tunability and robustness.

Leveraging the Polymer Glass Transition to Access Thermally Switchable Shear Jamming Suspensions.

Suspensions of polymeric nano- and microparticles are fascinating stress-responsive material systems that, depending on their composition, can display a diverse range of flow properties under shear, such as drastic thinning, thickening, and even jamming (reversible solidification driven by shear). However, investigations to date have almost exclusively focused on nonresponsive particles, which do not allow in situ tuning of the flow properties. Polymeric materials possess rich phase transitions that can be directly tuned by their chemical structures, which has enabled researchers to engineer versatile adaptive materials that can respond to targeted external stimuli. Reported herein are suspensions of (readily prepared) micrometer-sized polymeric particles with accessible glass transition temperatures (T g) designed to thermally control their non-Newtonian rheology. The underlying mechanical stiffness and interparticle friction between particles change dramatically near T g. Capitalizing on these properties, it is shown that, in contrast to conventional systems, a dramatic and nonmonotonic change in shear thickening occurs as the suspensions transition through the particles' T g. This straightforward strategy enables the in situ turning on (or off) of the system's ability to shear jam by varying the temperature relative to T g and lays the groundwork for other types of stimuli-responsive jamming systems through polymer chemistry.