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125 records · Page 7

Imaging a solvent-swollen polymer gel network by open liquid transmission electron microscopy

Visualizing the network of a solvent-swollen polymer gel remains problematic. To address this challenge, open transmission electron microscopy (TEM) was applied to thin gel films permeated by a nonvolatile ionic liquid. The targeted physical gels were prepared by cooling concentrated solutions of poly(ethylene glycol) in 1-ethyl-3-methyl imidazolium ethyl sulfate [EMIM][EtSO 4 ]. During the cooling, gelation occurred by a frustrated crystallization of the dissolved polymer, leading to a percolated, solvent-permeated semicrystalline network in which nanoscale polymer crystals acted as crosslinks. Crystalline features ranging from ~5 to ~200 nm were observed, with the visible network strands dominantly consisting of long curvilinear crystallites of ~15–20 nm diameter. Nascent spherulites irregularly decorated the network, creating a complex structural hierarchy that complicated analyses. Lacking diffraction contrast, TEM did not visualize the many disordered, fully solvated PEG chains present in the voids between crystals. Finally, recognizing that a network's three dimensionality is ambiguous when assessed through two-dimensional microscopy projections, a small gel region was studied by TEM tomography, revealing a nearly isotropic three-dimensional arrangement of the curvilinear crystallites, which displayed remarkably uniform cylindrical cross sections.

36 MATERIALS SCIENCE↗

Tubulin Double Helix: Lateral and Longitudinal Curvature Changes of Tubulin Protofilament

By virtue of their native structures, tubulin dimers are protein building blocks that are naturally pre-programmed to assemble into cytoskeletal polymers known as microtubules (MTs). Here we demonstrate polycation-directed (i.e. electrostatically tunable) assembly of tubulins through tubulin protofilament conformational changes in the longitudinal and lateral directions, creating novel tubulin double helices and various tubular architectures. Synchrotron small angle X-ray scattering and transmission electron microscopy reveal a remarkable range of nanoscale assembly structures: single- and double-layered double-helix tubulin tubules. The phase transitions from MTs into the new assemblies are dependent on the size and concentration of polycations. Two characteristic scales that determine the number of observed phases are the size of polycation compared to the size of tubulin (≈4 nm) and MT diameter (≈25 nm). This work suggests the feasibility of “programmable breakdown” of protein nanotubes, tearing MTs into double-stranded tubulins and building up previously undiscovered nanostructures, by using polycations with scissor- and glue-like properties. Importantly, we define a new role of tubulins as two-dimensionally shape-controllable building blocks for novel supramolecular architectures. Furthermore, these findings provide insight into the design of protein-based functional materials, for example, as metallization templates for nanoscale electronic devices, kinesin motor-driving molecular screws, and anticancer drug delivery vehicles.

2D shape‐control↗

Non-close-packed plasmonic Bravais lattices through a fluid interface-assisted colloidal assembly and transfer process

Abstract The assembly of colloids at fluid interfaces followed by their transfer to solid substrates represents a robust bottom-up strategy for creating colloidal monolayers over large, macroscopic areas. In this study, we showcase how subtle adjustments in the transfer process, such as varying the contact angle of the substrate and controlling deposition speed and direction, enable the realization of all five two-dimensional Bravais lattices. Leveraging plasmonic core–shell microgels as the building blocks, we successfully engineered non-close-packed plasmonic lattices exhibiting hexagonal, square, rectangular, centered rectangular, and oblique symmetries. Beyond characterizing the monolayer structures and their long-range order, we employed extinction spectroscopy alongside finite difference time domain simulations to comprehensively investigate and interpret the plasmonic response of these monolayers. Additionally, we probed the influence of the refractive index environment on the plasmonic properties by two methods: first, by plasma treatment to remove the microgel shells, and second, by overcoating the resulting gold nanoparticle lattices with a homogeneous refractive index polymer film. Graphical Abstract

Chemistry↗

The high explosives & affected targets (HEAT) dataset

Artificial Intelligence (AI) surrogate models offer a computationally efficient alternative to full-physics simulations, yet no existing datasets are publicly available for training, testing, and validation of machine learning models of the dynamics of high-explosive driven shocks through multiple materials. Shock propagation through materials is a computationally challenging problem because simulations must include material-specific equations of state (EOS) along with descriptions of other physical processes such as plastic deformation, phase change, damage processes, fluid instabilities, and multi-material interactions. Shocks are typically initiated by high-velocity impacts or explosive loading. The latter case necessitates the addition of models of reactive materials to represent high-explosive (HE) detonation. Here, to address the lack of an expansive dataset for multi-material shock propagation in the AI/ML community, we present the High-Explosives and Affected Targets (HEAT) Dataset. HEAT is a physics-rich collection of two-dimensional, cylindrically symmetric, simulations generated using an Eulerian, multi-material, shock-propagation code developed at Los Alamos National Laboratory. The dataset includes two partitions: (1) the expanding shock-cylinder (CYL) simulations, Figs. 1, and (2) the Perturbed Layered Interface (PLI) simulations, Fig. 2. Entries in both partitions consist of time series of arrays of thermodynamic fields (pressure, density, and temperature), kinematic fields (position and velocity), and additional fields that depend on thermodynamic and/or kinematic fields (e.g., material stress). Materials in the CYL partition include solids (aluminium, copper, depleted uranium, stainless steel, tantalum, and a generic polymer), a liquid (water), gases (air, nitrogen), and a generic detonating material (high explosive, HE). The PLI partition spans a highly varying geometry but consists of fixed materials across entries: Copper, aluminium, stainless steel, generic polymer, and generic HE. HEAT captures critical phenomena such as momentum transfer, shock propagation, plastic deformation, and thermal effects, making HEAT a valuable benchmark for development of AI/ML emulation of multi-material shock propagation.

36 MATERIALS SCIENCE↗

Access to Advanced Functional Materials through Postmodification of Biomimetic Assemblies via Click Chemistry

The design, synthesis, and fabrication of functional nanomaterials with specific properties remain a long-standing goal for many scientific fields. The self-assembly of sequence-defined biomimetic synthetic polymers presents a fundamental strategy to explore the chemical space beyond biological systems to create advanced nanomaterials. Moreover, subsequent chemical modification of existing nanostructures is a unique approach for accessing increasingly complex nanostructures and introducing functionalities. Of these modifications, covalent conjugation chemistries, such as the click reactions, have been the cornerstone for chemists and materials scientists. Herein, we highlight some recent advances that have successfully employed click chemistries for the postmodification of assembled one-dimensional (1D) and two-dimensional (2D) nanostructures to achieve applications in molecular recognition, mineralization, and optoelectronics. Specifically, biomimetic nanomaterials assembled from sequence-defined macromolecules such as peptides and peptoids are described.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Selective One-Dimensional 13 C– 13 C Spin-Diffusion Solid-State Nuclear Magnetic Resonance Methods to Probe Spatial Arrangements in Biopolymers Including Plant Cell Walls, Peptides, and Spider Silk

Two-dimensional (2D) and 3D through-space 13 C– 13 C homonuclear spin-diffusion techniques are powerful solid-state nuclear magnetic resonance (NMR) tools for extracting structural information from 13 C-enriched biomolecules, but necessarily long acquisition times restrict their applications. In this work, we explore the broad utility and underutilized power of a chemical shift-selective one-dimensional (1D) version of a 2D 13 C– 13 C spin-diffusion solid-state NMR technique. The method, which is called 1D dipolar-assisted rotational resonance (DARR) difference, is applied to a variety of biomaterials including lignocellulosic plant cell walls, microcrystalline peptide fMLF, and black widow dragline spider silk. 1D 13 C– 13 C spin-diffusion methods described here apply in select cases in which the 1D 13 C solid-state NMR spectrum displays chemical shift-resolved moieties. Furthermore, this is analogous to the selective 1D nuclear Overhauser effect spectroscopy (NOESY) experiment utilized in liquid-state NMR as a faster (1D instead of 2D) and often less ambiguous (direct sampling of the time domain data, coupled with increased signal averaging) alternative to 2D NOESY. Selective 1D 13 C– 13 C spin-diffusion methods are more time-efficient than their 2D counterparts such as proton-driven spin diffusion (PDSD) and dipolar-assisted rotational resonance. The additional time gained enables measurements of 13 C– 13 C spin-diffusion buildup curves and extraction of spin-diffusion time constants TSD, yielding detailed structural information. Specifically, selective 1D DARR difference buildup curves applied to 13 C-enriched hybrid poplar woody stems confirm strong spatial interaction between lignin and acetylated xylan polymers within poplar plant secondary cell walls, and an interpolymer distance of ~0.45–0.5 nm was estimated. Additionally, Tyr/Gly long-range correlations were observed on isotopically enriched black widow spider dragline silks.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Ionic-like Superlattices by Charged Nanoparticles: A Step Toward Photonics Applications

Controlling interactions among nanoparticles is paramount to achieving assemblies vital to technologies seeking to exploit their cutting-edge collective properties. Although various techniques have been advanced, robust ones are necessary for upscaling nanoparticle assembly and crystallization. Here, we show that by grafting gold nanoparticles (AuNPs) with charge-end-group-thiolated poly(ethylene glycol), we control the charge of each AuNP. Such control facilitates the formation of various two-dimensional structures of oppositely charged binary constituents at vapor/liquid interfaces. Using surface-sensitive synchrotron X-ray diffraction techniques, we established the formation of distinct checkerboard square lattice structures at a range of pH values and molar ratios of the constituents. By regulating pH, the superlattices can transform from a square to a hexagonal lattice, or vice versa, and to a single-component superstructure at the interface. In conclusion, our recipe for the control of charges and their consequent interactions among nanoparticles can be readily exploited in the assembly of photonics and plasmonics devices in two and three dimensions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Spontaneous Formation of Single-Crystalline Spherulites in a Chiral 2D Hybrid Perovskite

In two-dimensional (2D) chiral metal-halide perovskites (MHPs), chiral organic spacers induce structural chirality and chiroptical properties in the metal-halide sublattice. This structural chirality enables reversible crystalline-glass phase transitions in (S-NEA) 2 PbBr 4 , a prototypical chiral 2D MHP where NEA + represents 1-(1-naphthyl)ethylammonium. Here, in this study, we investigate two distinct spherulite states of (S-NEA) 2 PbBr 4 , exhibiting either radial-like or stripe-like banded patterns depending on the annealing conditions of the amorphous film. Despite similarities in optical absorption and photoluminescence, the stripe-like, banded spherulite exhibits higher crystallinity and improved optical transparency compared to those of radial-like spherulite. X-ray nanoprobe measurements reveal tilting-angle modulations in the octahedral plane of stripe-like spherulites, correlating with the film’s surface geometry. Transfer matrix calculations indicate that the optical contrast in stripe-like patterns, seen in bright-field optical microscopy, arises from optical interference effects, differing from the contrast mechanism observed in polymer spherulites. Ultrafast carrier dynamics experiments suggest that the stripe-like spherulites resemble single crystals more closely than radial-like spherulites, while electrical conductivity measurements show enhanced charge carrier transport in stripe-like spherulites. These findings offer insights into MHP spherulite states with a single composition but different morphologies, previously observed only in polymers, highlighting their potential for optoelectronic applications.

36 MATERIALS SCIENCE↗

Seeking regularity from irregularity: unveiling the synthesis–nanomorphology relationships of heterogeneous nanomaterials using unsupervised machine learning

Nanoscale morphology of functional materials determines their chemical and physical properties. However, despite increasing use of transmission electron microscopy (TEM) to directly image nanomorphology, it remains challenging to quantify the information embedded in TEM data sets, and to use nanomorphology to link synthesis and processing conditions to properties. We develop an automated, descriptor-free analysis workflow for TEM data that utilizes convolutional neural networks and unsupervised learning to quantify and classify nanomorphology, and thereby reveal synthesis–nanomorphology relationships in three different systems. While TEM records nanomorphology readily in two-dimensional (2D) images or three-dimensional (3D) tomograms, we advance the analysis of these images by identifying and applying a universal shape fingerprint function to characterize nanomorphology. After dimensionality reduction through principal component analysis, this function then serves as the input for morphology grouping through unsupervised learning. We demonstrate the wide applicability of our workflow to both 2D and 3D TEM data sets, and to both inorganic and organic nanomaterials, including tetrahedral gold nanoparticles mixed with irregularly shaped impurities, hybrid polymer-patched gold nanoprisms, and polyamide membranes with irregular and heterogeneous 3D crumple structures. In each of these systems, unsupervised nanomorphology grouping identifies both the diversity and the similarity of the nanomaterial across different synthesis conditions, revealing how synthetic parameters guide nanomorphology development. Our work opens possibilities for enhancing synthesis of nanomaterials through artificial intelligence and for understanding and controlling complex nanomorphology, both for 2D systems and in the far less explored case of 3D structures, such as those with embedded voids or hidden interfaces.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Light-activated microtubule-based two-dimensional active nematic

We assess the ability of two light responsive kinesin motor clusters to drive dynamics of microtubule-based active nematics: opto-K401, a processive motor, and opto-K365, a non-processive motor. Measurements reveal an order of magnitude improvement in the contrast of nematic flow speeds between maximally- and minimally-illuminated states for opto-K365 motors when compared to opto-K401 construct. For opto-K365 nematics, we characterize both the steady-state flow and defect density as a function of applied light. We also examine the transient behavior as the system switches between steady-states upon changes in light intensities. Although nematic flows reach a steady state within tens of seconds, the defect density exhibits transient behavior for up to 10 minutes, showing a separation between small-scale active flows and system-scale structural states. Furthermore, our work establishes an experimental platform that can exploit spatiotemporally-heterogeneous patterns of activity to generate targeted dynamical states.

42 ENGINEERING↗

Validation of a detonation product equation of state for an insensitive high explosive via slab geometry expansion tests

Slab expansion (SLABEX) tests are conducted to validate a process for calibrating the detonation products equation of state (EOS) of a high explosive (HE). The SLABEX tests use rectangular slabs of PBX 9502, a polymer-bonded HE formulation consisting of 95 wt.% 1,3,5-triamino-2,4,6-trinitrobenzene bound with Kel F-800, a co-polymer of chlorotrifluoroethylene and vinylidene-fluoride. Three PBX 9502 slab thicknesses are examined, each confined symmetrically by two rectangular copper (Cu) plates approximately one-tenth the thickness of the HE slab. For the duration of each experiment, the detonation flow along the central axis of the PBX 9502 slab remains two-dimensional. The lateral flow velocity component of the outer surfaces of the expanding Cu plates is measured, along with the steady axial detonation speed along the central axis of the SLABEX. Hydrodynamic simulations of the Cu plate expansion in the SLABEX geometry, driven by the energy stored in the detonation products by the detonation combustion event, are conducted using a Jones–Wilkins–Lee EOS for the detonation products. This EOS form was recently parameterized for PBX 9502 in the cylinder expansion test geometry using a newly developed calibration technique [Voelkel et al., Combust. Flame 246, 112373 (2022)]. Good agreement between the experiment and prediction is found in each SLABEX test, demonstrating that the detonation product EOS calibration technique produces EOSs that are predictive when applied to other geometries.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Improving indirect-drive ablator performance through pulse shaping and material selection in double shell implosions

The double shell path to inertially confined volumetric thermonuclear burn relies on efficient kinetic energy transfer from an outer ablator shell to an inner shell containing DT fuel at implosion velocities near 250 km/s. In order to experimentally realize adequate compression, target imperfections and assembly features must be tightly controlled. Pulse shape and ablator material are critical design choices that impact all aspects of the implosion. In this article, we evaluate three designs: an Al ablator with single-shock radiation drive, a CH ablator with single-shock drive, and a CH ablator with reduced-adiabat 2-shock drive. All designs use the same W inner (pusher) shell overcoated with a glow discharge polymer tamper and filled with liquid-density DT. One-dimensional HYDRA simulations revealed that the plastic ablator design required the use of the 2-shock drive to match the performance of the Al design. Two-dimensional simulations resolving broadband surface roughness up to modes of several hundred placed only on the ablator showed plastic to greatly outperform Al. The plastic ablator designs did exhibit higher levels of inner shell instability growth when surface roughness was only placed at the pusher/tamper interface, which was mitigated with higher foam cushion densities. A unique and additional benefit of a plastic ablator is also discussed, where heating of the ablator by Au M-band radiation is predicted to rapidly expand the hemi-shell surfaces, closing the equatorial joint gap ahead of the first shock. Taken together, the properties of the plastic ablator for indirect-drive double shell implosions appear promising in removing several long-standing fabrication challenges.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Entanglement phase transitions in random stabilizer tensor networks

Here we explore a class of random tensor network models with “stabilizer” local tensors which we name random stabilizer tensor networks (RSTNs). For RSTNs defined on a two-dimensional square lattice, we perform extensive numerical studies of entanglement phase transitions between volume-law and area-law entangled phases of the one-dimensional boundary states. These transitions occur when either (a) the bond dimension D of the constituent tensors is varied or (b) the tensor network is subject to random breaking of bulk bonds, implemented by forced measurements. In the absence of broken bonds, we find that the RSTN supports a volume-law entangled boundary state with bond dimension D ≥ 3 where D is a prime number, and an area-law entangled boundary state for D = 2. Upon breaking bonds at random in the bulk with probability p, there exists a critical measurement rate p c for each D ≥ 3 above which the boundary state becomes area-law entangled. To explore the conformal invariance at these entanglement transitions for different prime D, we consider tensor networks on a finite rectangular geometry with a variety of boundary conditions, and extract universal operator scaling dimensions via extensive numerical calculations of the entanglement entropy, mutual information, and mutual negativity at their respective critical points. Our results at large D approach known universal data of percolation conformal field theory, while showing clear discrepancies at smaller D, suggesting a distinct entanglement transition universality class for each prime D. We further study universal entanglement properties in the volume-law phase and demonstrate quantitative agreement with the recently proposed description in terms of a directed polymer in a random environment.

36 MATERIALS SCIENCE↗

From 2D to 4D: a containerized workflow and browser to explore dynamic chromatin architecture

Background Characterizing the physical organization of the genome is essential for understanding long-range gene regulation, chromatin compartmentalization, and epigenetic accessibility. Hi-C experiments generate two-dimensional (2D) genome-wide contact maps of chromatin interactions by capturing the spatial proximity between genomic loci, which reveal interaction frequencies but lack the spatial resolution needed to interpret the three-dimensional (3D) genome structure(s). Emerging evidence suggests that epigenetic regulation is closely linked to 3D genome architecture, and that structural changes over time (4D) drive key biological processes in development, disease, and environmental response. Thus, integrating 3D structure with functional data is critical for a more complete understanding of genome regulation. Previous work, most notably the 4DHiC chromosome modeling framework, has shown that physical multi-dimensional modeling approaches rooted in polymer physics and molecular dynamics can resolve these structures at biologically meaningful resolutions by integrating temporal Hi-C data with physical constraints to uncover dynamic chromosome reorganization. Thus, molecular dynamics simulations, constrained by Hi-C contact matrices, can resolve fine-scale structural changes and reveal functionally significant transitions in chromatin conformation. Results Herein, we present the 4D Genome Browser Workflow (4DGBWorkflow) and the 4D Genome Browser (4DGB). The algorithm is based on the 4DHiC method, and the containerized tool is an end-to-end workflow that can transform, filter, and view 4D epigenomics and chromatin datasets, allowing non-specialists to apply three-dimensional modeling principles to diverse datasets and experimental conditions. The software executes on a laptop running macOS, Linux or Windows. From input Hi-C files (.hic), the 4DGBWorkflow produces 3D reconstructions of chromosomes, integrates the reconstruction with track data (e.g., epigenetic marks, transcriptome profiles), and provides comparative visualization of the results in a single workflow. Conclusions The 4DGBWorkflow and 4D Genome Browser are open-source tools for comparative analysis and visualization of 4D chromosome datasets, including chromatin architecture and epigenomic signals. Automatic integration of Hi-C data with molecular dynamics democratizes the construction of time resolved 3D genome structures, simplifying complex simulations and data integration schemes.

3D Genome Browser↗

Measurement of Local Impedance Characteristics of In-Plane PEM Electrolyzer Component Features via Segmented Cell

Segmented cells are a class of advanced diagnostic devices that enable the measurement of current distribution within the active area of an electrochemical cell, allowing for the evaluation of localized impacts from operating conditions, flow fields and component inhomogeneities. Segmented cell devices have been applied to support R&D efforts for the advancement of polymer electrolyte membrane fuel cell technologies and more recently proton exchange membrane water electrolysis (PEMWE). Beyond current density distributions, segmented cells have been successfully deployed to collect the distribution of other relevant parameters such as high frequency resistance and electrode potentials. Very recently, a promising impedance method has been reported for water electrolysis where a one-dimensional segmented cell is coupled to a multichannel potentiostat, to enable the measurement of local cell impedances, further expanding the diagnostic capabilities of the segmented cell. In this study, we will present recent efforts to accurately measure local impedance characteristics for a PEMWE cell using a two-dimensional segmented cell device coupled with a multichannel potentiostat. The distribution of local resistances, i.e. high frequency, charge transfer, mass transport and catalyst layer, and iR-free overpotentials were successfully measured after eliminating sources of random and systematic error. We will discuss the application of this diagnostic on a cell containing a 1 cm feature simulating an ionomer skin. The results from these tests give insights if such an irregularity needs to be classified as a defect, and highlight the usefulness of coupling impedance spectroscopy with segmented cells for holistic spatial diagnostics of electrochemical devices.

08 HYDROGEN↗

Finite Element Modeling of the Fiber-Matrix Interface in Polymer Composites

Polymer composites are used in numerous industries due to their high specific strength and high specific stiffness. Composites have markedly different properties than both the reinforcement and the matrix. Of the several factors that govern the final properties of the composite, the interface is an important factor that influences the stress transfer between the fiber and matrix. The present study is an effort to characterize and model the fiber-matrix interface in polymer matrix composites. Finite element models were developed to study the interfacial behavior during pull-out of a single fiber in continuous fiber-reinforced polymer composites. A three-dimensional (3D) unit-cell cohesive damage model (CDM) for the fiber/matrix interface debonding was employed to investigate the effect of interface/sizing coverage on the fiber. Furthermore, a two-dimensional (2D) axisymmetric model was used to (a) analyze the sensitivity of interface stiffness, interface strength, friction coefficient, and fiber length via a parametric study; and (b) study the shear stress distribution across the fiber-interface-matrix zone. It was determined that the force required to debond a single fiber from the matrix is three times higher if there is adequate distribution of the sizing on the fiber. The parametric study indicated that cohesive strength was the most influential factor in debonding. Moreover, the stress distribution model showed the debonding mechanism of the interface. It was observed that the interface debonded first from the matrix and remained in contact with the fiber even when the fiber was completely pulled out.

36 MATERIALS SCIENCE↗