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At least 1,279 records · Page 71

Supramolecular assemblies of polybenzimidazole and aromatic polycarboxylic acids with superior mechanical and H 2 /CO 2 separation properties

Aromatic polycarboxylic acids complex with imidazoles, forming supramolecular assemblies. Herein, we demonstrate that polybenzimidazole (PBI) can be augmented by aromatic polycarboxylic acids, including phthalic acid (PA), trimesic acid (TMA), and pyromellitic acid (PMA), and the resulting supramolecular assemblies exhibit attractive H 2 /CO 2 separation performance for precombustion carbon capture. The acid doping decreases the free volume and gas permeability but increases H 2 /CO 2 selectivity, which can be correlated with the molar ratio of the protons to PBI repeating units in the assemblies. Increasing the temperature decreases the H 2 /CO 2 selectivity because of weakened interactions. When challenged with model gas mixtures, a supramolecular assembly based on TMA shows H 2 /CO 2 separation properties superior to state-of-the-art materials and above Robeson's upper bound. Furthermore, this study elucidates the fruitful harnessing of dynamic non-covalent bonds to design robust and highly selective membranes for industrial gas separations.

36 MATERIALS SCIENCE↗

Diet outperforms microbial transplant to drive microbiome recovery in mice

A high-fat, low-fibre Western-style diet (WD) induces microbiome dysbiosis characterized by reduced taxonomic diversity and metabolic breadth, which in turn increases risk for a wide array of metabolic, immune and systemic pathologies. Recent work has established that WD can impair microbiome resilience to acute perturbations such as antibiotic treatment, although little is known about the mechanism of impairment and the specific consequences for the host of prolonged post-antibiotic dysbiosis. Here, in this study, we characterize the trajectory by which the gut microbiome recovers its taxonomic and functional profile after antibiotic treatment in mice on regular chow (RC) or WD, and find that only mice on RC undergo a rapid successional process of recovery. Metabolic modelling indicates that a RC diet promotes the development of syntrophic cross-feeding interactions, whereas in mice on WD, a dominant taxon monopolizes readily available resources without releasing syntrophic byproducts. Intervention experiments reveal that an appropriate dietary resource environment is both necessary and sufficient for rapid and robust microbiome recovery, whereas microbial transplant is neither. Furthermore, prolonged post-antibiotic dysbiosis in mice on WD renders them susceptible to infection by the intestinal pathogen Salmonella enterica serovar Typhimurium. Our data challenge widespread enthusiasm for faecal microbiota transplant (FMT) as a strategy to address dysbiosis, and demonstrate that specific dietary interventions are, at a minimum, an essential prerequisite for effective FMT, and may afford a safer, more natural and less invasive alternative.

Kennedy, M. S. [University of Chicago, IL (United ↗

Holographic scattering requires a connected entanglement wedge

In AdS/CFT, there can exist local 2-to-2 bulk scattering processes even when local scattering is not possible on the boundary; these have previously been studied in con- nection with boundary correlation functions. We show that boundary regions associated with these scattering configurations must have O(1/G N ) mutual information, and hence a connected entanglement wedge. One of us previously argued for this statement from the boundary theory using operational tools in quantum information theory. We improve that argument to make it robust to small errors and provide a proof in the bulk using focusing arguments in general relativity. We also provide a direct link to entanglement wedge reconstruction by showing that the bulk scattering region must lie inside the con- nected entanglement wedge. Our construction implies the existence of nonlocal quantum computation protocols that are exponentially more efficient than the optimal protocols currently known.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Real-Time Acoustic Analysis of Batteries

The project explored development and commercialization of an acoustical approach to battery diagnostics. The technology has significant potential impacts for battery manufacturing and quality assurance, battery management during operation, and could be an enabler for the second-life battery market. Research was focused on inspecting and analyzing the physical condition of batteries using ultrasound. This consisted of designing and building hardware for gathering high-quality acoustic data, as well as using battery charge-discharge cyclers and temperature chambers to operate and age the batteries. Over the course of the 2-year program, we were able to build our first prototypes that are robust enough to be used by industry partners to evaluate our technology. Using the same prototypes, we also showed preliminary evidence that our acoustic inspection method may have distinct advantages over standard electrical methods in terms of detecting differences in the physical quality of battery cells. The project also expanded the participant’s core capabilities beyond time-of-flight acoustic measurements.

25 ENERGY STORAGE↗

Giant Exfoliation Induced Magnetic Coercivity in Fe 3 GaTe 2

Permanent magnets with strong anisotropy and high coercivity underpin modern information and energy technologies, yet rare-earth-free alternatives remain limited. Here, we show that thickness engineering via mechanical exfoliation induces hard magnetic behavior in the van der Waals ferromagnet Fe 3 GaTe 2 . Bulk crystals exhibit Curie temperatures above 350 K but negligible room-temperature coercivity. When thinned below ∼100 nm, the coercive field is dramatically enhanced, reaching nearly 1 T at room temperature for in-plane fields—comparable to conventional hard magnets. Micromagnetic analysis reveals a crossover in magnetization reversal from domain-mediated processes in bulk samples to quasi-coherent rotation in thin flakes, driven by increased effective anisotropy and suppressed domain formation. This thickness-dependent transition enables tuning of magnetic hardness without chemical modification. Combined with high saturation magnetization and robust room-temperature performance, Fe 3 GaTe 2 emerges as a promising rare-earth-free material for spintronic applications. Its layered structure further allows integration into van der Waals heterostructures, where large in-plane coercivity can stabilize magnetic states against perturbations and interlayer coupling, offering potential for high-density nonvolatile memory and domain-wall-based devices.

36 MATERIALS SCIENCE↗

A chemically-defined growth medium to support Lactobacillus-Acetobacter sp. community analysis

Lactobacilli and Acetobacter sp. are commercially important bacteria that often form communities in natural fermentations, including food preparations, spoilage, and in the digestive tract of the fruit fly Drosophila melanogaster. Communities of these bacteria are widespread and prolific, despite numerous strain-specific auxotrophies, suggesting they have evolved nutrient interdependencies that regulate their growth. The use of a chemically-defined medium (CDM) supporting the growth of both groups of bacteria would facilitate the identification of the molecular mechanisms for the metabolic interactions between them. While numerous CDMs have been developed that support specific strains of lactobacilli or Acetobacter , there has not been a medium formulated to support both genera. We developed such a medium, based on a previous CDM designed for growth of lactobacilli, by modifying the nutrient abundances to improve growth yield. We further simplified the medium by substituting casamino acids in place of individual amino acids and the standard Wolfe’s vitamins and mineral stocks in place of individual vitamins and minerals, resulting in a reduction from 40 to 8 stock solutions. These stock solutions can be used to prepare several CDM formulations that support robust growth of numerous lactobacilli and Acetobacter s. Here, we provide the composition and several examples of its use, which is important for tractability in dissecting the genetic and metabolic basis of natural bacterial species interactions.

59 BASIC BIOLOGICAL SCIENCES↗

Alternative Approaches to Traditional Net Energy Metering

Most jurisdictions in the United States originally implemented net energy metering (NEM) tariffs to support the deployment and interconnection of distributed generation (DG) resources (e.g., rooftop solar photovoltaic systems). Since then, NEM has proven effective in promoting adoption of DG resources. Recently, due to concerns about sufficient recovery of utilities’ revenue requirements and cost-shifting, there is increasing interest in—or statutory requirements to pursue—alternative compensation approaches, especially in U.S. states and territories with robust growth in distributed solar. Recent increases in other forms of distributed energy resources (DERs) that can potentially send power to the distribution grid (e.g., distributed battery energy storage system (BESS)) are further driving compensation reforms. This brief provides an overview of design elements associated with alternative approaches to traditional NEM, summarizes common arguments for and against them, and identifies implementation issues that utilities may need to address. Although this brief may be most useful in jurisdictions that are interested in or required to move beyond NEM, it is also applicable to those jurisdictions that have already done so—and are looking to further implement reforms to their existing compensation mechanisms. In the broadest sense, there are three primary tariff-related components when interconnecting a DER onto the local utility’s distribution system (adapted from Zinaman et al., 2017): 1. Metering and Billing Arrangements: How utilities measure and bill electricity consumption and production. 2. DER Export Tariff Design: The structure under which utilities compensate customers for electricity they export to the grid. 3. Consumption Tariff Design: The structure under which customers pay for electricity they consume from the grid. When implementing changes to any of these primary tariff-related components, there are likely implications for a utility’s metering system, billing system, and other technology systems. Where applicable, this brief explicitly identifies such implementation challenges.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

High Strength Steel-Aluminum Components by Vaporizing Foil Actuator Welding

This project aimed to address the challenge of effectively welding dissimilar materials—high-strength steel and high-strength aluminum for creating lightweight, multi-material automotive components. For automotive companies, reducing weight of a vehicle is critical task regulated by the government to solve the issue of greenhouse gas emissions. Production of lightweight cars and trucks can be achieved by substitution of current all-steel structures with multi-material lightweight structures that include high strength-to-weight-ration materials such as high-strength steels, aluminum alloys, magnesium alloys, titanium alloys, coupled with lightweight designs. This requires dissimilar metal welding, which is challenging for state of the art joining processes such as resistance spot welding. The cycle of melting-cooling-freezing during traditional welding that can easily ruin the designed outstanding properties of the advanced base metals, such as aluminum alloys, making the welded area much weaker than the base metals. To weld two different metals with great difference in melting points, such as aluminum and steel, it’s even more difficult or impossible because of the formation of brittle intermetallic compounds at the welded interface. In this project, a novel welding method, developed at OSU, was selected for validation and development. This novel technology enables welding by impact without melting and proves to be robust to join various dissimilar lightweight metals. Termed as vaporizing foil actuator welding or VFAW, the technology uses a thin aluminum foil that is rapidly vaporized by a high current pulse to produce an explosive-like pressure pulse to drive one metallic piece into another at the high speed required for impact welding. This project entailed development of the early-stage welding technology in terms of (a) the consumables, the welding apparatus and the power sources, (b) coupon scale screening of many material combinations including corrosion studies, (c) computational modeling and design of the welded interface as well as of the multi-material prototype component, and (d) mechanical testing for strength and durability at coupon scale and to a certain extent the prototype scale. The all-steel engine cradle of 2016 Chevrolet Cruze was chosen as the baseline prototype component. The target set for the project was to demonstrate a 20% weight reduction at a cost premium of less than $\$ $5/lb saved without compromising on baseline mechanical properties. At project completion, a 12% lighter prototype component was demonstrated with an estimated cost premium of $\$ $9.8/lb saved. Besides prototype level demonstration of the technology, this project also enabled elevation of the technology’s readiness level to where a hydraulically actuated welding head was developed and made ready for deployment at a research and development facility for Tier 1 automotive supplier.

36 MATERIALS SCIENCE↗

DNA Strand Displacement Driven Molecular Additive Manufacturing (DSD-MAM)

The goal of this project was to validate two-dimensional molecular printers, initially selfassembled from DNA and then actuated by externally driven cycles of DNA strand displacement, as prototype integrated nanosystems for molecular additive manufacturing. Novel functionalities of these nanomachines were explored during this project, including the following: nanometer-precision positioning mechanisms based on DNA strand displacement with multivalent interactions for discrete stepping or else diffusive capture; integration of independently moving layers of DNA origami to achieve 2D controllable motion; integration of spatial positioning with deposition functionality. The principal importance of this project was to provide an essential step in the development of a new technology for atomically precise manufacturing. Our first generation molecular 2D printer offers several advantages over conventional DNA-origami patterning, such as faster prototyping, faster dynamic rearrangement of patterns, and the ability to respond with feedback. We anticipate that our first-generation molecular printers may inspire future generations of molecular printers with iterative improvements in robustness and throughput. Potential applications of atomically precise manufacturing include the following: photovoltaics; photosynthetic and fuel cells; thermoelectrics and anisotropic heat spreaders; solid-state lighting; molecular electronic and plasmonic circuits; selectively preamble membranes; self-repairing materials with high strength-to-weight and fracture resistance.

36 MATERIALS SCIENCE↗

Establishing ZIF‐8 as a reference material for hydrogen cryoadsorption: An interlaboratory study

Abstract Hydrogen storage by cryoadsorption on porous materials has the advantages of low material cost, safety, fast kinetics, and high cyclic stability. The further development of this technology requires reliable data on the H 2 uptake of the adsorbents, however, even for activated carbons the values between different laboratories show sometimes large discrepancies. So far no reference material for hydrogen cryoadsorption is available. The metal‐organic framework ZIF‐8 is an ideal material possessing high thermal, chemical, and mechanical stability that reduces degradation during handling and activation. Here, we distributed ZIF‐8 pellets synthesized by extrusion to 9 laboratories equipped with 15 different experimental setups including gravimetric and volumetric analyzers. The gravimetric H 2 uptake of the pellets was measured at 77 K and up to 100 bar showing a high reproducibility between the different laboratories, with a small relative standard deviation of 3–4 % between pressures of 10–100 bar. The effect of operating variables like the amount of sample or analysis temperature was evaluated, remarking the calibration of devices and other correction procedures as the most significant deviation sources. Overall, the reproducible hydrogen cryoadsorption measurements indicate the robustness of the ZIF‐8 pellets, which we want to propose as a reference material.

08 HYDROGEN↗

Self-Healing Lithium Dendrites through Spontaneous Passivating Layer Formation for Stable Solid-State Lithium–Metal Batteries

All-solid-state lithium–metal batteries have attracted significant attention, owing to their high energy density and superior safety. However, lithium–metal penetration through the solid electrolyte, leading to short-circuiting, remains a critical failure mode that demands comprehensive mitigation strategies. Most existing strategies are effective only prior to the initiation of lithium-dendrite formation and fail once dendrites begin to propagate through the electrolyte. In this study, we propose a self-healing mechanism in which the penetrated lithium reacts with a self-healing agent to form a passivating layer along the particle boundaries. Lithium bis(trifluoromethanesulfonyl)imide (LiTFSI) was incorporated into a Li 6 PS 5 Cl solid electrolyte as the self-healing agent to suppress lithium-dendrite propagation even after dendrite formation initiated under high current densities. The self-healing induced by LiTFSI was verified through comprehensive experimental analyses and was further demonstrated in a full-cell configuration. Moreover, LiTFSI incorporation plays an important role in increasing the critical current density by reducing the overall electronic conductivity of the solid electrolyte and facilitating the formation of a robust LiF-containing solid-electrolyte interphase.

25 ENERGY STORAGE↗

Dissipative magnetohydrodynamics for nonresistive relativistic plasmas: An implicit second-order flux-conservative formulation with stiff relaxation

Based on a 14-moment closure for nonresistive (general-) relativistic viscous plasmas, here we describe a new numerical scheme that is able to handle all first-order dissipative effects (heat conduction, bulk and shear viscosities), as well the anisotropies induced by the presence of magnetic fields. The latter is parametrized in terms of a thermal gyrofrequency or, equivalently, a thermal Larmor radius and allows to correctly capture the thermal Hall effect. By solving an extended Israel-Stewart-like system for the dissipative quantities that enforces algebraic constraints via stiff-relaxation, we are able to cast all first-order dissipative terms in flux-divergence form. This allows us to apply traditional high-resolution shock capturing methods to the equations, making the system suitable for the numerical study of highly turbulent flows. We present several numerical tests to assess the robustness of our numerical scheme in flat spacetime. The 14-moment closure can seamlessly interpolate between the highly collisional limit found in neutron star mergers, and the highly anisotropic limit of relativistic Braginskii magnetohydrodynamics appropriate for weakly collisional plasmas in black-hole accretion problems. We believe that this new formulation and numerical scheme will be useful for a broad class of relativistic magnetized flows.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Advanced sorbents for modular oxygen production for REMS gasifiers

Under a DOE funded effort, Thermosolv LLC has been developing a sorbent-based oxygen production technology for gasification and oxy-combustion applications. The sorbents utilize oxygen-storage properties of certain perovskites to (1) selectively adsorb oxygen at moderate temperature from compressed air and (2) release the adsorbed oxygen into a vacuum or a sweep gas such as CO2 and/or steam. Through cyclic operations of multiple sorbent beds such a process can be made continuous. Pressure drop across the sorbent bed and other similar design considerations dictate that the sorbent be in the form of a high surface-area-to-volume pellet and yet still possess sufficient crush strength and integrity. Process efficiency is determined by the sorption and desorption kinetics and sorbent capacity. Typical process involves cycle times in the order of 100 seconds, a time too short to fully utilize the full volume of the sorbent and the sorption capacity of the sorbent pellets. As a part of this project, Thermosolv LLC undertook the development of oxygen sorbents as a high-surface area supported sorbent on a light-weight inert support to (1) reduce the cost, (2) increase the productivity, and (3) reduce the overall weight of the reactor. Using a previously developed perovskite (LSCF 1991) with its well-characterized performance, composite sorbent pellets each consisting of an inert core coated by a thin layer of the functional perovskite material were produced. Several low-density, inexpensive inert solids supports in the 1/8”-1/4” size were selected to keep the pressure drop across the sorbent bed in the acceptable range. A number of commercial technologies including spray coating, dip coating, incipient impregnation of porous substrate followed by thermal annealing at various temperatures and duration were employed and tested to produce robust composite supported sorbent pellets. A sense of optimum coating thickness was developed by testing sorbent pellets of various increasing diameter pellets. LSCF-1991extrudates ranging in size from 1/32” to 3/16” were tested in a TGA and in a fixed-bed pressure swing test set-up for sorption/desorption cycles of interest. The data show that for the operational conditions of interest the coating thickness for a supported sorbent pellet needs to be approximately 1/32” (about 0.8 mm). Subsequent work thereby concentrated on developing composite pellets of various substrates, shapes and sizes with coating layer of about this size range. Candidate support materials were chosen based on cost, inertness, mechanical strength, thermal expansion and chemical stability with sorbent material, and in a size range to give an acceptable pressure drop in fixed-bad reactor configurations. Coating application methods used for application of the sorbent onto the support included precipitation, spray coating and dip coating from sorbent slurries and sol gels. For all coated supports where we could successfully apply a uniform coating of desired thickness with an acceptable handling performance in terms of exfoliation, TGA-based cyclic sorption/desorption testing was performed to determine cycling capacity of oxygen. Among nearly twenty different support materials tested, best adhesion performance was obtained from stainless saddle supports. In the bench-scale fixed-bad tests stainless steel saddle support composite pellets with a coating thickness in the 0.6 mm or so range, the composite sorbent pellet performance approached up to 95% of that of the 2 mm parent material pellets. In a parallel approach to reducing the cost of the sorbent, alternate sorbent formulations replacing/reducing the amount of cobalt in the LSCF family were also investigated. Successful formulations that could match the performance of LSCF 1991 were identified based on TGA cyclic tests as LSCF 1919 and LSF 1910. In the range of operational envelop of cycle times and other relevant process operating conditions, the reduced Co formulations showed comparable performance in the bench-scale fixed-bad cyclic operations. As a part of this project, we also attempted substitution of La and Sr with Ca and Ba, and Co with Mn, Ni and Cu with little success, but the overall project goal of reducing sorbent cost in terms of raw material and manufacturing expenses was successful.

01 COAL, LIGNITE, AND PEAT↗

Random Forest Regressor-Based Approach for Detecting Fault Location and Duration in Power Systems

Power system failures or outages due to short-circuits or “faults” can result in long service interruptions leading to significant socio-economic consequences. It is critical for electrical utilities to quickly ascertain fault characteristics, including location, type, and duration, to reduce the service time of an outage. Existing fault detection mechanisms (relays and digital fault recorders) are slow to communicate the fault characteristics upstream to the substations and control centers for action to be taken quickly. Fortunately, due to availability of high-resolution phasor measurement units (PMUs), more event-driven solutions can be captured in real time. In this paper, we propose a data-driven approach for determining fault characteristics using samples of fault trajectories. A random forest regressor (RFR)-based model is used to detect real-time fault location and its duration simultaneously. This model is based on combining multiple uncorrelated trees with state-of-the-art boosting and aggregating techniques in order to obtain robust generalizations and greater accuracy without overfitting or underfitting. Four cases were studied to evaluate the performance of RFR: 1. Detecting fault location (case 1), 2. Predicting fault duration (case 2), 3. Handling missing data (case 3), and 4. Identifying fault location and length in a real-time streaming environment (case 4). A comparative analysis was conducted between the RFR algorithm and state-of-the-art models, including deep neural network, Hoeffding tree, neural network, support vector machine, decision tree, naive Bayesian, and K-nearest neighborhood. Experiments revealed that RFR consistently outperformed the other models in detection accuracy, prediction error, and processing time.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Navigating Transition-Metal Chemical Space: Artificial Intelligence for First-Principles Design

Conspectus The variability of chemical bonding in open-shell transition-metal complexes not only motivates their study as functional materials and catalysts but also challenges conventional computational modeling tools. Here, tailoring ligand chemistry can alter preferred spin or oxidation states as well as electronic structure properties and reactivity, creating vast regions of chemical space to explore when designing new materials atom by atom. Although first-principles density functional theory (DFT) remains the workhorse of computational chemistry in mechanism deduction and property prediction, it is of limited use here. DFT is both far too computationally costly for widespread exploration of transition-metal chemical space and also prone to inaccuracies that limit its predictive performance for localized d electrons in transition-metal complexes. These challenges starkly contrast with the well-trodden regions of small-organic-molecule chemical space, where the analytical forms of molecular mechanics force fields and semiempirical theories have for decades accelerated the discovery of new molecules, accurate DFT functional performance has been demonstrated, and gold-standard methods from correlated wavefunction theory can predict experimental results to chemical accuracy. The combined promise of transition-metal chemical space exploration and lack of established tools has mandated a distinct approach. In this Account, we outline the path we charted in exploration of transition-metal chemical space starting from the first machine learning (ML) models (i.e., artificial neural network and kernel ridge regression) and representations for the prediction of open-shell transition-metal complex properties. The distinct importance of the immediate coordination environment of the metal center as well as the lack of low-level methods to accurately predict structural properties in this coordination environment first motivated and then benefited from these ML models and representations. Once developed, the recipe for prediction of geometric, spin state, and redox potential properties was straightforwardly extended to a diverse range of other properties, including in catalysis, computational “feasibility”, and the gas separation properties of periodic metal–organic frameworks. Interpretation of selected features most important for model prediction revealed new ways to encapsulate design rules and confirmed that models were robustly mapping essential structure–property relationships. Encountering the special challenge of ensuring that good model performance could generalize to new discovery targets motivated investigation of how to best carry out model uncertainty quantification. Distance-based approaches, whether in model latent space or in carefully engineered feature space, provided intuitive measures of the domain of applicability. With all of these pieces together, ML can be harnessed as an engine to tackle the large-scale exploration of transition-metal chemical space needed to satisfy multiple objectives using efficient global optimization methods. In practical terms, bringing these artificial intelligence tools to bear on the problems of transition-metal chemical space exploration has resulted in ML-model assessments of large, multimillion compound spaces in minutes and validated new design leads in weeks instead of decades.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

AI-assisted detector design for the EIC (AID(2)E)

Artificial Intelligence is poised to transform the design of complex, large-scale detectors like ePIC at the future Electron Ion Collider. Featuring a central detector with additional detecting systems in the far forward and far backward regions, the ePIC experiment incorporates numerous design parameters and objectives, including performance, physics reach, and cost, constrained by mechanical and geometric limits. This project aims to develop a scalable, distributed AI-assisted detector design for the EIC (AID(2)E), employing state-of-the-art multiobjective optimization to tackle complex designs. Supported by the ePIC software stack and using G EANT 4 simulations, our approach benefits from transparent parameterization and advanced AI features. The workflow leverages the PanDA and iDDS systems, used in major experiments such as ATLAS at CERN LHC, the Rubin Observatory, and sPHENIX at RHIC, to manage the compute intensive demands of ePIC detector simulations. Tailored enhancements to the PanDA system focus on usability, scalability, automation, and monitoring. Ultimately, this project aims to establish a robust design capability, apply a distributed AI-assisted workflow to the ePIC detector, and extend its applications to the design of the second detector (Detector-2) in the EIC, as well as to calibration and alignment tasks. Additionally, we are developing advanced data science tools to efficiently navigate the complex, multidimensional trade-offs identified through this optimization process.

97 MATHEMATICS AND COMPUTING↗

Peptoid-Based Nanosheets Exhibiting Broad Antiviral Activity Against Enveloped RNA Viruses

Enveloped RNA viruses, such as Influenza A (H1N1) and Sindbis virus, pose persistent global health threats due to their high mutation rates, efficient transmission, and frequent drug resistance. By mimicking host cell membrane receptors, multivalent virus inhibitors can block viral attachment, making them promising broad-spectrum antiviral agents. However, most of existing antivirals are often limited by strain specificity, short-lived efficacy, and toxicity. Here, we introduce a broad-spectrum antiviral platform based on highly tunable and biocompatible two-dimensional nanomembranes (2DNMs) self-assembled from amphiphilic peptoids, operating via a non-genomic, mutation-insensitive mechanism. By varying peptoid sequence, we design and synthesize over twenty different 2DNMs with various surface charge and high density of viral-attachment ligands (VALs). The self-assembled architecture of these stable 2DNMs provides cooperative noncovalent multivalent binding to virus particles that result in effective inhibition of viral infection. Screening of variants identified three leads that potently suppressed Influenza A (H1N1) and Sindbis virus infection across median tissue culture infectious dose (TCID50), plaque, RT–qPCR, and immunofluorescence assays, while maintaining >90% cell viability. These nanosheets significantly reduced infectious titers, viral RNA replication, and intracellular viral protein expression, indicating inhibition at early stages of viral entry and propagation. The sequence programmability, chemical robustness, and mutation-insensitive antiviral activity distinguish 2DNMs from traditional antivirals and positions them as a versatile materials platform for antiviral coatings, protective barriers, and prophylactic biomedical applications.

Influenza A virus↗