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DOE OSTI2025

Enhanced Interfacial Bonding of Graft Copolymers

To understand how thermoplastic welding strength can be tuned through chemical modifications and macromolecular topology, we combined coarse-grained molecular dynamics (MD) simulations with experimental validation. Our simulations examined the diffusion dynamics of both linear and graft polymers across representative interfaces, revealing that diffusion-controlled interdigitation follows a power law, with the exponent decreasing from 0.34 to 0.11 as grafting density increases from 7.5 to 196% (with side chains grafted to both sides of a monomer unit). The addition of side chains enhances welding efficiency, as dense bottlebrush polymers with high grafting density reach maximum rupture strength faster than linear polymers. However, their saturated rupture strength is lower. This observation is subsequently corroborated by experimental lap-shear tests comparing linear polyethylene with octene grafted polyethylene elastomers. Our MD simulations show that unlike linear polymers, where backbone entanglements dominate, the grafted side chains introduce mechanisms in addition to entanglement dilution. The rapid interdigitation of side chains creates a dense mesh of entropic van der Waals contacts, which can also enhance the film welding. Furthermore, our MD simulations reveal a brittle rupture behavior in linear and comb-like (mildly grafted) polymers, while bottlebrush (densely grafted) polymers display elastomeric behavior with a pronounced stress plateau prior to fracture. Our simulations deconvolute the influence of polymer topology on deformation behavior. The rate of polymer deformation becomes lower than the applied strain rate prior to rupture, and the onset of this deviation is progressively delayed from linear to bottlebrush polymers. This trend highlights the critical role of molecular architecture in governing the mechanical response. In conclusion, these results provide deeper insight into the underlying welding mechanisms of topological polymers and present a potential approach for mitigating the interface anisotropy that is inherent in advanced manufacturing techniques such as fused filament fabrication.

graft copolymers↗

DOE OSTI2026

Molecular Mechanisms Underlying Surfactant-Based Plastics De-Inking

Surfactant-mediated binder removal is critical for de-inking pretreatment in plastics recycling, yet the molecular mechanisms governing surfactant performance remain poorly understood. We used all-atom (AA) and coarse-grained (CG) molecular dynamics (MD) simulations alongside alkaline surfactant washing experiments to investigate interactions between a series of surfactants and a polyether urethane (PEU) binder in solution and on a polyethylene (PE) surface. Experiments reveal a range of de-inking efficiencies, ranging from <25 to >95% depending upon surfactant headgroup charge and tail length. AA simulations reveal that charged surfactants reach stable levels of surfactant coverage, while nonionic surfactants aggregate on the binder. CG umbrella sampling calculations quantify the thermodynamics of binder desorption in water. In ∼0.25 M surfactant solutions, up to a 52% reduction in the free energy barrier is computed, with trends in good agreement (R 2 = 0.92, Pearson’s r = –0.96, Spearman’s ρ = –0.83) with experimental de-inking efficiencies. We find that charged surfactants are more effective than nonionic surfactants for de-inking and propose three regimes of surfactant de-inking processes: good de-inking occurs in surfactants that promote PEU desorption with a low radius of gyration (R g ); moderate de-inking occurs when surfactants stabilize PEU but increase R g ; poor de-inking occurs in surfactants that aggregate on the binder and promote extensive anchoring to the surface. Overall, these molecular-level insights have the potential to guide the design of surfactant formulations for plastics recycling applications.

ink removal↗

DOE OSTI2025

The Martini 3 Lipidome: Expanded and Refined Parameters Improve Lipid Phase Behavior

Lipid membranes are central to cellular life. Complementing experiments, computational modeling has been essential in unraveling complex lipid-biomolecule interactions, crucial in both academia and industry. The Martini model, a coarse-grained force field for efficient molecular dynamics simulations, is widely used to study membrane phenomena but has faced limitations, particularly in capturing realistic lipid phase behavior. Here, we present refined Martini 3 lipid models with a mapping scheme that distinguishes lipid tails that differ by just two carbon atoms, enhancing the structural resolution and thermodynamic accuracy of model membrane systems including ternary mixtures. The expanded Martini lipid library includes thousands of models, enabling simulations of complex and biologically relevant systems. These advancements establish Martini as a robust platform for lipid-based simulations across diverse fields.

Lipids↗

DOE OSTI2025

Shear-Induced Conformations of Salt-Free Polyelectrolytes in Semidilute Solutions

Here, we present coarse-grained molecular dynamics simulations of salt-free polyelectrolyte chains in semidilute solutions under simple shear flow, with full hydrodynamic interactions and explicit dipolar solvent. At equilibrium, chain orientation statistics follow a pseudo-Voigt distribution, and the structural correlation length and chain end-to-end vector autocorrelation function exhibit scaling behavior consistent with theoretical predictions for polyelectrolytes. Under shear, chains transition from coiled to stretched states and the end-to-end vector autocorrelation function reveals oscillatory dynamics at high Weissenberg numbers. Analysis of the gyration tensor and shear strain distributions identified three distinct chain populations with directional alignment along and against the shear gradient. Compared with their neutral polymer counterparts, polyelectrolytes exhibit stronger shear thinning and enhanced chain alignment under the same Weissenberg number, which is attributed to electrostatic interactions and shear-induced counterion release. These findings provide molecular insight into the distinct flow response of charged polymers and have implications for tailoring the rheological properties of polyelectrolyte-based materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2026

Influence of Rigidity–Hydration Coupling on Size-Dependent Diffusion in Hydrated Polymer Membranes

Selective ion transport in polymer membranes depends critically on how penetrant motion couples to polymer dynamics and hydration. Yet, the mechanistic interplay between polymer rigidity, water content, and penetrant size remains poorly understood, especially in the regime where the penetrant diameter, polymer Kuhn length, and correlation length are comparable. Here, we employ coarse-grained molecular dynamics simulations to systematically investigate penetrant diffusion in hydrated polymer networks across a broad range of water volume fractions, chain rigidities, and penetrant sizes. The results reveal a transition from a decoupled regime, where small penetrants diffuse nearly independently of polymer relaxation, to a coupled regime in which large penetrants require cooperative polymer motion for transport. Increasing polymer rigidity amplifies the sensitivity of diffusivity to hydration, particularly at low water content, leading to pronounced deviations from Stokes−Einstein scaling. Comparison with scaling theories and free-volume models shows that classical nanoparticle-based frameworks fail to capture this intermediate regime. To address this gap, we extend the Yasuda model to incorporate polymer rigidity through a single parameter that quantifies the dynamic contribution of chain stiffness to free-volume fluctuations. The resulting model collapses diffusivity data across all sizes, water contents, and rigidities, providing a unified description of penetrant transport in hydrated polymer matrices. Furthermore, these findings establish polymer rigidity as a key, tunable determinant of diffusion and offer a framework for interpreting size-dependent transport in ion-selective membranes.

diffusion↗

DOE OSTI2025

Nanoscale Miscibility in In Situ Polymerized Hybrid Electrolytes Speeds Up Ion Dynamics and Enables Stable Cycling of Li Metal Batteries

While the potential use of copolymerized electrolytes in Li metal batteries is subject to intense investigation, the fundamental understanding of the nanoscale domain formation and its effect on Li + transport is still lacking. In this study, we investigated the correlation between the Li + transport mechanism and the miscibility of monomers in polymer blend electrolytes derived from the in situ copolymerization of methyl methacrylate (MMA) and vinylene carbonate (VC) in the presence of polyethylene glycol dimethyl ether (PEGDME) plasticizer and bis(trifluoromethanesulfonyl)imide (LiTFSI) salt. The addition of a polar short chain plasticizer reduced the dynamic and structural heterogeneities of the electrolyte. Small-angle X-ray scattering (SAXS) measurements and coarse-grained molecular dynamics (MD) simulations were used to investigate the nanoscale structure of the electrolytes. The distribution of relaxation times corresponding to the three distinct diffusion mechanisms of the free and interfacial Li + ions at the copolymer/plasticizer and electrolyte/SEI boundaries was analyzed in a broad temperature range to elucidate the Li + transport mechanism. Furthermore, the chemical composition of the SEI and the contribution of a ceramic lithium lanthanum zirconium oxide (LLZO, Li 7 La 3 Zr 2 O 12 ) phase on the interfacial resistance, salt degradation, and SEI stability were studied by X-ray photoelectron spectroscopy (XPS) depth profile analysis and electrochemical testing.

Li metal↗

DOE OSTI2026

A Robotic High-Throughput Grid-Search Platform for Mapping Phase Behavior in Triblock Copolymer–Homopolymer Blends

We present a high-throughput experimental investigation of the phase behavior in triblock copolymers (PS-b-PB-b-PS and PS-b-PI-b-PS) and polystyrene (PS) homopolymer blends as a function of homopolymer molecular weight (MW) and blend ratio. Using a robotic thin-film processing platform (NOVA) integrated with Grazing Incidence Small-Angle X-ray Scattering (GISAXS) and Atomic Force Microscopy (AFM), we systematically mapped the order–disorder transition (ODT) boundaries and domain spacing evolution across a broad MW range (4.0–101.3 kDa) with varying homopolymer loadings (10% to 90%). The results reveal three distinct regimes: low-MW homopolymers, corresponding to the wet-brush regime produced only gradual domain swelling before disordering at high blend ratios (weight fraction); medium-MW homopolymers, corresponding to thedry-brush regime induced significant domain spacing increase up to 80% followed by earlier disordering, while high-MW homopolymers led to macrophase separation with minimal changes in domain spacing. Additionally, coarse-grained molecular dynamics simulations confirmed our experimental finding that in the low-MW region, the PS homopolymer uniformly distributed in the PS domain. These findings demonstrate that homopolymer molecular weight critically governs both the extent of domain swelling and the onset of disorder in triblock copolymer systems. This high-throughput platform enables the rapid mapping of composition–morphology relationships and can be integrated with AI/ML tools for designing next-generation nanostructured polymers.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Insights into the Structure of Ultrasmall Fluorescent Core–Shell Silica Nanoparticles

Ultrasmall fluorescent core–shell nanoparticles (NPs) with a silica core and poly(ethylene glycol) ligand shell are the earliest example of hybrid NPs that have received U.S. investigational new drug FDA approval. They are among only a few inorganic NPs translated to safety, diagnostic, and therapeutic human clinical trials. Despite these achievements, little is known about the exact structure of their 3–4 nm sized silica cores. We report the surprising discovery of a well-defined pentagonal bipyramidal core structure preferentially formed in the aqueous synthesis built from seven primary silica NPs. A combination of reverse-phase high-performance liquid chromatography, cryogenic transmission electron microscopy, and coarse-grained simulations provides fundamental insights into this magic-size cluster formation and its unusual stability. Here, results rationalize the successful NP synthesis scale-up from 1 mL to 50 L, provide clues to the recent discovery of their self-therapeutic properties in oncology via ferroptosis, an iron-dependent cell death mechanism, and promise improved control of particle size distribution via chromatographic separations.

cluster chemistry↗

DOE OSTI2024

How Does Escherichia coli Allocate Proteome?

Microorganisms are shown to actively partition their intracellular resources, such as pro- teins, for growth optimization. Recent experiments have begun to reveal molecular com- ponents unpinning the partition; however, it remains unclear quantitatively how individual parts orchestrate to yield precise resource allocation that is both robust and dynamic. Here we developed a coarse-grained mathematical framework that centers on guanosine pentaphosphate (ppGpp)-mediated regulation, and used it to systematically uncover the design principles of proteome allocation in Escherichia coli. Our results showed that cellular ability of resource partition lies in an ultrasensitive, negative feedback control- ling topology with the ultrasensitivity arising from zero-order amino acid kinetics and the negative feedback from ppGpp-controlled ribosome synthesis. In addition, together with the time-scale separation between slow ribosome kinetics and fast turnovers of ppGpp and amino acids, the network topology confers the organism an optimization mechanism which mimics sliding mode control, a nonlinear optimization strategy that is widely used in man-made systems. We further showed that such a controlling mechanism is robust against parameter variations and molecular fluctuations, and is also efficient for biomass production over time. Furthermore, this work elucidates the fundamental controlling mechanism of E. coli proteome allocation, thereby providing insights into quantitative microbial physiology as well as the design of synthetic gene networks.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

Impact of Grafting Density on the Assembly and Mechanical Properties of Self-Assembled Metal–Organic Framework Monolayers

Polymer-grafted metal–organic frameworks (MOFs) can be used to form free-standing self-assembled MOF monolayers (SAMMs). Polymer chains can be introduced onto MOF surfaces through either the ligands or metal nodes using both grafting-to and grafting-from approaches. However, controlling the grafting density of polymer-grafted MOFs has not yet been achieved, because a means to control the density of grafting sites on the MOF surface has not been developed. In this study, the grafting density of polymer-grafted UiO-66 (UiO = University of Oslo) was controlled by functionalizing a portion of the Zr(IV) secondary building units (SBUs) on a UiO-66 surface with a so-called blocking agent. The remaining sites on the UiO-66 SBUs were functionalized with polymerization initiation groups, and polymers were grown from these sites to obtain particles with variable grafting densities and chain lengths that form SAMMs at an air–water interface. Even under conditions of low grafting density, these materials retain the ability to form SAMMs and their free-standing ability. Changes in particle arrangement within the monolayers were investigated using SEM imaging, and the toughness of the monolayers was evaluated using a film-on-water (FOW) method. Furthermore, coarse-grained molecular dynamics simulations were carried out to elucidate the morphology and mechanical properties of the monolayers. Findings from both experiments and simulations indicate that the toughness of SAMMs is more heavily influenced by the chain length of the grafted polymers than by the overall polymer content in the composite.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Functional Design of Peptide Materials Based on Supramolecular Cohesion

Peptide materials offer a broad platform to design biomimetic soft matter, and filamentous networks that emulate those in extracellular matrices and the cytoskeleton are among the important targets. Given the vast sequence space, a combination of computational approaches and readily accessible experimental techniques is required to design peptide materials efficiently. Here, we report here on a strategy that utilizes this combination to predict supramolecular cohesion within filaments of peptide amphiphiles, a property recently linked to supramolecular dynamics and consequently bioactivity. Using established coarse-grained simulations on 10,000 randomly generated peptide sequences, we identified 3500 likely to self-assemble in water into nanoscale filaments. Atomistic simulations of small clusters were used to further analyze this subset of sequences and identify mathematical descriptors that are predictive of intermolecular cohesion, which was the main purpose of this work. We arbitrarily selected a small cohort of these sequences for chemical synthesis and verified their fiber morphology. With further characterization, we were able to link the latent heat associated with fiber to micelle transitions, an indicator of cohesion and potential supramolecular dynamicity within the filaments, to calculated hydrogen bond densities in the simulation clusters. Based on validation from in situ synchrotron X-ray scattering and differential scanning calorimetry, we conclude that the phase transitions can be easily observed by very simple polarized light microscopy experiments. We are encouraged by the methodology explored here as a relatively low-cost and fast way to design potential functions of peptide materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2026

Structural Heterogeneity and Hydrodynamics of an Intrinsically Disordered Protein Condensate

Biology demonstrates precise control over the free-energy landscape through the selective partitioning of biomacromolecules into membraneless organelles, enabling essential functions such as biochemical transformations, signaling cascades, and mechanical reinforcement. Although the function of these condensates depends on their underlying structure and hydrodynamics, molecular-scale information on these systems remains sparse. Here, in this study, neutron scattering is used to probe the organization and dynamics of the intrinsically disordered N-terminal domain of Galectin-3, an extracellular lectin responsible for facilitating liquid–liquid phase separation on the cellular surface, in both dilute and condensed phases. Dilute solutions contain isolated protein chains in equilibrium with mesoscopic clusters, whereas the condensed phase adopts a bicontinuous, microemulsion-like morphology. The dilute phase behavior is quantitatively described by coarse-grained polymer models from soft-matter physics, demonstrating their predictive power for complex biological proteins. At elevated concentrations, the proteins self-assemble akin to block copolymers, microphase separating through the aggregation of hydrophobic domains along the protein contour. The resulting condensate remains fluid-like despite a 25-fold increase in concentration; its internal hydrodynamics slow by only a factor of 3 relative to dilute protein chains. These results provide a molecular-level framework for how disordered proteins achieve both the structural complexity and dynamic fluidity of biomolecular condensates.

Carrick, Brian R. [Massachusetts Inst. of Technolo↗

DOE OSTI2026

Why Seeding Works When Nucleation Barriers Vanish

Crystallization is a process governed by the interplay between nucleation and growth. While crystalline seeds are known to reduce nucleation barriers and accelerate crystallization under nucleation-limited conditions, their influence when nucleation is not the limiting step remains poorly understood. This creates a mechanistic puzzle in systems where nucleation barriers are already negligible, yet seeding still accelerates crystallization. Here, the synthesis of zeolites is a quintessential example of growth-limited crystallization in which seeds accelerate the process despite negligible homogeneous nucleation barriers. Using coarse-grained molecular dynamics simulations─validated across two zeolites and the unrelated case of ice crystallization─we establish that growth-limited crystallization produces many small, misoriented crystallites whose slow coarsening into larger domains controls the emergence of X-ray-detectable crystallinity. Local crystalline order, structural coherence, and X-ray detectability are therefore kinetically decoupled milestones: the first can be reached rapidly while the latter two lag significantly. Seeds resolve this lag by imposing a common orientational registry on nascent crystallites, enabling their coherent coalescence into large seed-bound domains. This early coherence-building step produces a crystallite-size asymmetry that accelerates subsequent coarsening, advancing the onset of X-ray-detectable crystallinity without necessarily increasing the nucleated fraction. We conclude that under growth-limited conditions, the apparent induction period observed in powder X-ray diffraction reflects the time required to build long-range coherence, not the time to form crystalline material. Accordingly, seeds function not primarily by reducing nucleation barriers but by enforcing spatial coherence, thereby shortening the time required to develop long-range order detectable by X-ray diffraction.

Growth-Limited Crystallization↗

DOE OSTI2026

Interfacial Inversion of Stealth Surfactants

Amphiphilic macromolecular surfactants segregate to liquid–liquid interfaces, thereby reducing the interfacial tension and free energy. Here, we investigated “stealth surfactants” in the form of core–shell bottlebrush polymers comprised of pH-responsive diblock copolymer side chains forming a hydrophilic core and a hydrophobic shell, enabling solubility in oil. At liquid–liquid interfaces, these polymers undergo a structural “inversion”, with hydrophilic blocks segregating into the aqueous phase and hydrophobic blocks residing in the oil phase. The reconfiguration kinetics and surfactant properties are influenced by multiple factors, including the molecular weights of the backbone and side chain components, the hydrophilic-to-hydrophobic balance of the side chains, and the pH of the aqueous phase. An observed nonmonotonic dependence of interfacial tension with time is attributed to a progressive structural inversion, where the projected area of the macromolecule onto the interface decreases. To validate this inversion hypothesis, interfacial properties were characterized by sum-frequency generation vibrational spectroscopy, which revealed configurational changes of the core–shell bottlebrush polymers at the fluid interface and revealed a pH-dependent interfacial coverage. Coarse-grained molecular dynamics simulations supported these experimental findings, showing that the pH-responsive core and hydrophobic shell assume a time-averaged configuration with orientations parallel and perpendicular to the plane of the interface, respectively. These findings open routes to design multistimuli-responsive polymeric surfactants and compatibilizers, expanding their potential applications in advanced interfacial systems.

Stealth surfactants↗

DOE OSTI2024

Convective and Orographic Origins of the Mesoscale Kinetic Energy Spectrum

The mesoscale spectrum describes the distribution of kinetic energy in the Earth's atmosphere between length scales of 10 and 400 km. Since the first observations, the origins of this spectrum have been controversial. At synoptic scales, the spectrum follows a –3 spectral slope, consistent with two-dimensional turbulence theory, but a shallower –5/3 slope was observed at the shorter mesoscales. The cause of the shallower slope remains obscure, illustrating our lack of understanding. Through a novel coarse-graining methodology, we are able to present a spatio-temporal climatology of the spectral slope. We find convection and orography have a shallowing effect and can quantify this using “conditioned spectra.” These are typical spectra for a meteorological condition, obtained by aggregating spectra where the condition holds. This allows the investigation of new relationships, such as that between energy flux and spectral slope. Potential future applications of our methodology include predictability research and model validation.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Structural basis of undecaprenyl phosphate glycosylation leading to polymyxin resistance in Gram-negative bacteria

In Gram-negative bacteria, the enzymatic modification of Lipid A with aminoarabinose (L-Ara4N) leads to resistance against polymyxin antibiotics and cationic antimicrobial peptides. ArnC, an integral membrane glycosyltransferase, attaches a formylated form of aminoarabinose to the lipid undecaprenyl phosphate, enabling its association with the bacterial inner membrane. Here, we present cryo-electron microscopy structures of ArnC from S. enterica in apo and nucleotide-bound conformations. These structures reveal a conformational transition that takes place upon binding of the partial donor substrate. Using coarse-grained and atomistic simulations, we provide insights into substrate coordination before and during catalysis, and we propose a catalytic mechanism that may operate on all similar metal-dependent polyprenyl phosphate glycosyltransferases. The reported structures provide a new target for drug design aiming to combat polymyxin resistance.

Ashraf, Khuram U. [Rutgers University, Newark, NJ ↗

DOE OSTI2025

Dissipative ground state preparation in ab initio electronic structure theory

Dissipative engineering is a powerful tool for quantum state preparation, and has drawn significant attention in quantum algorithms and quantum many-body physics in recent years. In this work, we introduce a novel approach using the Lindblad dynamics to efficiently prepare the ground state for general ab initio electronic structure problems on quantum computers, without variational parameters. These problems often involve Hamiltonians that lack geometric locality or sparsity structures, which we address by proposing two generic types of jump operators for the Lindblad dynamics. Type-I jump operators break the particle number symmetry and should be simulated in the Fock space. Type-II jump operators preserves the particle number symmetry and can be simulated more efficiently in the full configuration interaction space. For both types of jump operators, we prove that in a simplified Hartree-Fock framework, the spectral gap of our Lindbladian is lower bounded by a universal constant. For physical observables such as energy and reduced density matrices, the convergence rate of our Lindblad dynamics with Type-I jump operators remains universal, while the convergence rate with Type-II jump operators only depends on coarse grained information such as the number of orbitals and the number of electrons. To validate our approach, we employ a Monte Carlo trajectory-based algorithm for simulating the Lindblad dynamics for full ab initio Hamiltonians, demonstrating its effectiveness on molecular systems amenable to exact wavefunction treatment.

Quantum chemistry↗

DOE OSTI2025

Block segmentation in feature space for realtime object detection in high granularity images

Computer vision has applications in object detection, image recognition and classification, and object tracking. One of the challenges of computer vision is the presence of useful information at multiple distance scales. Filtering techniques may sacrifice details at small scales in order to prioritize the analysis of large-scale features of the image. We present a strategy for coarse-graining multidimensional data while maintaining fine-grained detail for subsequent analysis. The algorithm is based on fixed-size block segmentation in the feature space. We apply this strategy to solve the long-standing challenge of detecting particle trajectories at the Large Hadron Collider in real time.

Computer vision↗