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78 records · Page 5

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DOE OSTI2025

Tuning Molecular Interactions between Peptoids and Substrates to Achieve Surface-Agnostic Coating

Achieving programmable and robust coatings that maintain functionality while adhering to various surface types with molecular-level tunability and programmable features remains challenging. In this study, we develop adaptable and stable surface-agnostic coatings (SACs) based on crystalline peptoid membranes by tuning interpeptoid and peptoid-substrate interactions. We utilize two complementary methods: (1) surfaceinduced assembly, where peptoid membranes form directly on substrates, and (2) depositing preformed peptoid crystalline membranes via an aqueous layer-by-layer (LbL) assembly technique. These strategies are applied to substrates with diverse surface chemistries and topographies, including mica, highly ordered pyrolytic graphite (HOPG), MoS 2 , sapphire, and porous membranes like porous alumina and polysulfide. Atomic force microscopy confirms the formation of peptoid coatings and reveals differences in assembly behavior across surfaces. Moisture vapor transport measurements serve as a proof-of-concept test for membrane continuity and tunable permeance. Together, these findings demonstrate the adaptability and programmability of peptoid-based SACs, enabling rational coating design on surfaces with diverse chemical and topographical features. Furthermore, this work opens pathways for using peptoid membranes as programmable surface modifiers in functional interfaces, protective coatings, and membrane platforms.

biomimetic polymers↗

DOE OSTI2024

A modular and extensible CHARMM-compatible model for all-atom simulation of polypeptoids

Peptoids (N-substituted glycines) are a class of sequence-defined synthetic peptidomimetic polymers with applications including drug delivery, catalysis, and biomimicry. Classical molecular simulations have been used to predict and understand the conformational dynamics of single chains and their self-assembly into morphologies including sheets, tubes, spheres, and fibrils. The CGenFF-NTOID model based on the CHARMM General Force Field has demonstrated success in accurate all-atom molecular modeling of peptoid structure and thermodynamics. Extension of this force field to new peptoid side chains has historically required reparameterization of side chain bonded interactions against ab initio data. This fitting protocol improves the accuracy of the force field but is also burdensome and precludes modular extensibility of the model to arbitrary peptoid sequences. In this work, we develop and demonstrate a Modular Side Chain CGenFF-NTOID (MoSiC-CGenFF-NTOID) as an extension of CGenFF-NTOID employing a modular decomposition of the peptoid backbone and side chain parameterizations, wherein arbitrary side chains within the large family of substituted methyl groups (i.e., –CH 3 , –CH 2 R, –CHRR', and –CRR'R") are directly ported from CGenFF. We validate this approach against ab initio calculations and experimental data to develop a MoSiC-CGenFF-NTOID model for all 20 natural amino acid side chains along with 13 commonly used synthetic side chains and present an extensible paradigm to efficiently determine whether a novel side chain can be directly incorporated into the model or whether refitting of the CGenFF parameters is warranted. We make the model freely available to the community along with a tool to perform automated initial structure generation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

3D pattern formation of a protein–membrane suspension

Many essential cellular processes, including cell division and the establishment of cell polarity during embryogenesis, are regulated by pattern-forming proteins. These proteins often need to bind to a substrate, such as the cell membrane, onto which they interact and form two-dimensional (2D) patterns. It is unclear how the membrane’s continuity and dimensionality impact pattern formation. Here, we address this gap using the MinDE system, a prototypical example of pattern-forming membrane proteins. We show that when the lipid substrate is fragmented into submicrometer-sized diffusive liposomes, adenosine triphosphate-driven protein–protein interactions generate three-dimensional (3D) spatially extended patterns, despite the complete loss of membrane continuity. Remarkably, these 3D patterns emerge at scales four orders of magnitude larger than the individual liposomes. By systematically varying protein concentration, liposome size, and density, we observed and characterized a variety of 3D dynamical patterns not seen on continuous 2D membranes, including traveling waves, dynamical spirals, and a coexistence phase. Simulations and linear stability analysis of a coarse-grained model revealed that the physical properties of the dispersed membrane effectively rescale both the protein–membrane binding rates and diffusion, two key parameters governing pattern formation and wavelength selection. These findings highlight the robustness of Min’s pattern-forming ability, suggesting that protein–membrane suspensions could serve as an adaptable template for studying out-of-equilibrium self-organization in 3D, beyond in vivo contexts.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Closed-Loop Control of Active Nematic Flows

Stabilizing and shaping autonomous flows of active fluids is a fundamental challenge and a prerequisite for applications. We embed a light-responsive microtubule-based nematic in a proportional-integral control loop that adjusts the applied light intensity in response to real-time measurements of the spatially averaged flow speed. The self-regulating hardware-software-wetware system maintains a target flow speed against external or internal perturbations, including protein aging and aggregation, sample-to-sample variability, and temperature variation. Varying the controller’s gains reveals antagonistic roles between feedback and intrinsic processes, leading to nontrivial dynamics observed in fluctuation spectra. In particular, oscillations emerge from the interplay between the controller, motor binding kinetics, and active hydrodynamic relaxation. Accounting for the underlying binding timescale, our coarse-grained model and nematohydrodynamics simulations corroborate these observations. This work provides insight into the coupled dynamics of controlled active matter, laying the foundation for spatiotemporal patterning of active stress to generate and stabilize new dynamical configurations.

Active nematics↗

DOE OSTI2025

Flow-Driven Stretch Fluctuations Govern the Nonlinear Viscoelasticity of Elongating Associative Polymer Networks

We use nonequilibrium molecular dynamics simulations to verify recent tube-model predictions that associative polymer networks exhibit broad stretch fluctuations during elongational flow. Simulations further show that these fluctuating dynamics give rise to the rate-dependent extensional viscosity 𝜂 𝐸 measured in filament stretching experiments on H-bonding networks. Simulations model bivalent associative networks with a reactive bead-spring model for varying association strength and extensional strain rate. We observe that stretch fluctuations are driven by a new form of chain tumbling, where chains continually collapse and elongate as their associations break and reform within the advecting network. This produces a broad, nearly uniform distribution of chain stretch over a wide range of strain rates, manifesting as a rate-independent plateau in the extensional stress. Our results show that the nonlinear viscoelasticity of associative networks is dominated by large fluctuations in molecular response, which cannot be captured by current mean-field models.

biomimetic & bio-inspired materials↗

DOE OSTI2024

Mechanochemical topological defects in an active nematic

We propose a reaction-diffusion system that converts topological information of an active nematic into chemical signals. We show that a curvature-activated reaction dipole is sufficient for creating a system that dynamically senses topology by producing a concentration field possessing local extrema coinciding with ±$\frac{1}{2}$ defects. The enabling term is analogous to polarization charge density seen in dielectric materials. We demonstrate the ability of this system to identify defects in both passive and active nematics. Our results illustrate that a relatively simple feedback scheme, expressed as a system of partial differential equations, is capable of producing chemical signals in response to inherently nonlocal structures in anisotropic media. Here, we posit that such coarse-grained systems can help generate testable hypotheses for regulated processes in biological systems, such as morphogenesis, and motivate the creation of bio-inspired materials that utilize dynamic coupling between nematic structure and biochemistry.

42 ENGINEERING↗