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At least 145 records · Page 8

Tubular Nanostructures from Large‐Pore 2D Covalent Organic Frameworks

Abstract The synthesis of a wavy mesoporous 2D covalent organic framework (COF) with a 6‐nm hexagonal pore lattice ( Joa‐COF‐1 ) is reported. This has been achieved by the synthesis of a terpyrenyl linker of approximately 2.7 nm in length and its subsequent condensation with a 3‐connected non‐planar cata‐hexabenzocoronene. Joa‐COF‐1 exists as non‐covalent tubular domains composed of π‐stacked 4 to 5 pores in 2D COF sections that can be separated by mild sonication, resulting in a family of tubular COF nanostructures that combine a 1D morphology with accessible mesopores.

Almarza, Joaquín [POLYMAT University of the Basque↗

Self‐Limiting Polymerization‐Induced Crystallization‐Driven Self‐Assembly (SL‐PI‐CDSA) Enables Templated Synthesis of Chiral Plasmonic, Hybrid 2D Hexagonal Assemblies

Examples of self-regulating synthetic self-assembly are relatively few, with most known chemical systems relying on kinetic rather than thermodynamic control. Herein, we demonstrate the rapid generation (t ≤ 5 min) of size-tunable ultralow dispersity (Ð ≤ 1.01) 2D hexagonal nanosheets governed by self-limiting self-assembly (SLSA). Self-assembly in natural systems occurs with exquisite control of structure, function, and dimension. We demonstrate that key aspects of biological assembly can be rationally applied toward the development of bottom-up approaches for the construction of chiral nanomaterials. To this end, self-limiting polymerization-induced crystallization-driven self-assembly (SL-PI-CDSA) of modular and templating aryl isocyanide (AIC) monomers yields functional 2D assemblies permitting post-polymerization/assembly modifications. Detailed study of the internal and external structure of the hexagonal nanosheets reveals topological defects which offer mechanistic insights into both their assembly and subsequent utilization. Specifically, these features enable fabrication of chiral hybrid organic–inorganic nanomaterials incorporating chiral plasmonic metal nanoparticles (MNPs). Our results suggest that the synergistic interplay of template-driven confinement and hierarchical chirality induce symmetry breaking of in situ-generated gold MNPs. We anticipate that the platform presented will facilitate fabrication of new hybrid, chiral organic–inorganic nanostructures.

36 MATERIALS SCIENCE↗

A universal inequality on the unitary 2D CFT partition function

We prove the conjecture proposed by Hartman, Keller and Stoica (HKS) [1]: the grand-canonical free energy of a unitary 2D CFT with a sparse spectrum below the scaling dimension $\frac{c}{12}$ + ϵ and below the twist $\frac{c}{12}$ is universal in the large c limit for all β L β R ≠ 4π 2 . The technique of the proof allows us to derive a one-parameter (with parameter α ∈ (0, 1]) family of universal inequalities on the unitary 2D CFT partition function with general central charge c ⩾ 0, using analytical modular bootstrap. We derive an iterative equation for the domain of validity of the inequality on the (β L , β R ) plane. The infinite iteration of this equation gives the boundary of maximal-validity domain, which depends on the parameter α in the inequality.

AdS-CFT Correspondence↗

2D kinetic-ion simulations of inverted corona fusion targets

Laser-driven “inverted corona” fusion targets have attracted interest as a low-convergence neutron source and platform for studying kinetic physics. The scheme consists of a hollow or gas-filled spherical shell made of deuterated plastic. The shell has one or more laser entrance holes (LEH), resembling a spherical hohlraum. The laser passes through the LEH’s and illuminates the interior surface of the shell, ablating a plasma that travels inward towards the target center. Long ion mean free paths in the converging plasma can lead to significant interpenetration, atomic mix, and other kinetic effects. Here, in this work we report on numerical simulations of inverted corona targets using the kinetic-ion, fluid–electron hybrid particle-in-cell (PIC) approach in 2D RZ geometry. 2D simulations suggest that shape effects do not have a significant impact on plasma evolution and observed yield trends are primarily the result of 1D kinetic mix mechanisms. Simulations are also compared against available experimental data recorded at the OMEGA laser facility. In particular, synthetic x-ray emission images show good qualitative agreement with experimental results, albeit with an apparent timing discrepancy for the two-sided vacuum target. More generally, we demonstrate the potential of hybrid-PIC simulations for full-system modeling and experimental design, including collisional absorption of laser energy, plasma evolution, mix, and fusion burn.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Single-source pulsed laser-deposited perovskite solar cells with enhanced performance via bulk and 2D passivation

Single-source vapor deposition of halide perovskites has, to date, remained challenging due to the dissimilar volatilities of the precursors, limiting the controlled transfer of multiple elements at once. Here, we demonstrate that pulsed laser deposition (PLD) addresses the rate-control challenges of single-source evaporation, enabling perovskite solar cells with power conversion efficiencies above 19% after passivation. Combining dry mechanochemical synthesis and PLD, we fabricated (Cl-passivated) MA1−xFAxPbI3 films from a single-source target. These films grow on hole-selective self-assembled monolayers, initially forming a thin PbI2-rich layer, which fully converts to perovskite. An oleylammonium iodide (OAmI) post-treatment is then applied to passivate the perovskite’s top surface by forming a 2D perovskite film. Incorporating PbCl2 in the target and applying OAmI-based 2D passivation results in a remarkable 19.7% efficiency for p-i-n perovskite solar cells with enhanced device stability. This highlights the appeal of PLD to fully unlock the potential of single-source vapor-deposited perovskites.

Soto-Montero, Tatiana↗

A machine-learning approach to measure 3D sample properties from 2D Transmission Electron Microscopy images

Transmission Electron Microscopy (TEM) is a powerful tool for the characterization of materials at the nanoscale; however, its inherent two-dimensional (2D) nature poses significant challenges to accurately measure three-dimensional (3D) properties. We introduce a supervised machine-learning model that predicts 3D structural information, such as sample thickness and curvature, from a series of conventional 2D TEM images. The model, a U-Net convolutional neural network, is trained on a large synthetic dataset generated from dynamical diffraction simulations that model TEM’s complex, nonlinear image formation, accounting for sample thickness and curvature. This physically realistic framework enables exploration of a broad parameter space impractical to sample experimentally. We demonstrate that the trained model has accurate predictions for experimental single-crystal silicon samples, achieving performance comparable to established measurement techniques. This work highlights the critical role of robust, simulation-based training in overcoming the limitations of real-world imaging artifacts and inconsistent sample geometries. By integrating machine learning with numerical simulations, we offer an efficient and scalable framework for quantitative TEM analysis, paving the way for more sophisticated 3D characterization of complex materials.

Dynamical diffraction↗

Spin excitations and dynamics in 2D magnets: An overview of magnons and magnetic skyrmions

van der Waals magnetic materials open up exciting possibilities to investigate fundamental spin properties in low-dimensional systems and to build compact functional spintronic structures. This review focuses on the recent progress in two-dimensional (2D) magnets that explore beyond the homogenous magnetically ordered state, including magnons (spin waves), magnetic skyrmions, and complex magnetic domains. Properties of these spin and topology excitations in 2D magnets provide insights into spin-orbit interactions and other forms of coupling between electrons, phonons, and spin-dependent excitations. Such spin-based quasiparticles can also serve as information carriers for next-generation high-speed computing elements. Furthermore, we will first lay out the general theoretical basis of dynamical responses in magnetic systems, followed by detailed descriptions of experimental progress in magnons and spin textures (including magnetic domains and skyrmions). Discussion on the experimental techniques and future perspectives are also included.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Sculpting 2D Crystals via Membrane Contractions before and during Solidification

When phospholipids crystallize within the otherwise fluid membranes of giant unilamellar vesicles, the resulting molecularly thin “2D” solids exhibit great variety in their morphology evolution. For example, within membranes containing moderate amounts of the crystallizing component, crystals grow with a fixed morphology depending on vesicle size. Conversely for membranes containing large amounts of the crystallizing species, we find small compact crystals on vesicles of all sizes. However, on large vesicles, growing crystals sprout flower petals that lengthen progressively. These behaviors result from two combined mechanisms: first, like other 2D solids, the shear rigidity of phospholipid crystals renders them intolerant to morphologies with nonzero Gaussian curvature. As a result and especially at elevated membrane tension, the cost of bending elasticity is reduced at the expense of line energy by the formation of flowers as opposed to compact crystals. Second, the composition-dependent tension rise during cooling relaxes via water permeation of the membrane with a time constant scaling as R2. The amount of crystal formed for a small decrease in temperature determines this composition-dependent increase in stress from thermal contractions versus solidification. Surface Evolver computations were motivated using the predicted tension evolution to develop a processing space that maps to experimental observations for initial and growing crystal morphology. Important variable groups are identified, including a scaled ratio of bending to line energy, a vesicle-size-independent group for membrane contractions, and a time constant for stress relaxation. Though processing stresses ultimately relax, the crystal morphology persists well beyond the processing window.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Protein-Enabled Size-Selective Defect-Sealing of Atomically Thin 2D Membranes for Dialysis and Nanoscale Separations

Atomically thin 2D materials present the potential for advancing membrane separations via a combination of high selectivity (from molecular sieving) and high permeance (due to atomic thinness). However, the creation of a high density of precise nanopores (narrow-size-distribution) over large areas in 2D materials remains challenging, and nonselective leakage from nanopore heterogeneity adversely impacts performance. Here, we demonstrate protein-enabled size-selective defect sealing (PDS) for atomically thin graphene membranes over centimeter scale areas by leveraging the size and reactivity of permeating proteins to preferentially seal larger nanopores (≥4 nm) while preserving a significant amount of smaller nanopores (via steric hindrance). Our defect-sealed nanoporous atomically thin membranes (NATMs) show stability up to ~35 days during size-selective diffusive separations with a model dialysis biomolecule fluorescein isothiocyanate (FITC)-Ficoll 70 in phosphate buffer saline (PBS) solution as well as outperform state-of-the-art commercially available dialysis membranes (molecular-weight-cutoff ~3.5–5 kDa and ~8–10 kDa) with significantly higher permeance for smaller solutes KCl (~0.66 nm) ~5.1–6 × 10 –5 ms –1 and vitamin B12 (B12, ~1.5 nm) ~2.8–4 × 10 –6 ms –1 compared to small protein lysozyme (Lz, ~4 nm) ~4–6.4 × 10 –8 m s –1 , thereby allowing unprecedented selectivity for B12/Lz ~70 and KCl/Lz ~1280. Our work introduces proteins as nanoscale tools for size-selective defect sealing in atomically thin membranes to overcome persistent issues and advance separations for dialysis, protein desalting, small molecule separations/purification, and other bioprocesses.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Proximity-Induced Superconductivity in a 2D Kondo Lattice of an f -Electron-Based Surface Alloy

Realizing hybrids of low-dimensional Kondo lattices and superconducting substrates leads to fascinating platforms for studying the exciting physics of strongly correlated electron systems with induced superconducting pairing. Here, we report a scanning tunneling microscopy and spectroscopy study of a new type of two-dimensional (2D) La–Ce alloy grown epitaxially on a superconducting Re(0001) substrate. We observe the characteristic spectroscopic signature of a hybridization gap evidencing the coherent spin screening in the 2D Kondo lattice realized by the ultrathin La–Ce alloy film on normal conducting Re(0001). Upon lowering the temperature below the critical temperature of rhenium, a superconducting gap is induced exhibiting an energy asymmetry of the coherence peaks that arises from the interaction of residual unscreened magnetic moments with the superconducting substrate. A positive correlation between the Kondo hybridization gap and the asymmetry of the coherence peaks is found.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Multifunctional Polar 2D Lead Iodide Perovskites Exhibiting Persistent Spin Texture

Ferroelectric Rashba semiconductors are a rare class of multifunctional materials promising for spin–orbitronics due to the possibility of electrically switchable spin textures. Hybrid organic–inorganic metal halide perovskites offer exceptional tunability that can be harnessed to target noncentrosymmetry; however, the complex interactions between organic and inorganic components are not rationally understood. Here, we use an asymmetric spacer cation with a strong molecular dipole moment (2-fluorobenzylammonium, 2FBZ) and increase the intrinsic quantum well thickness to n > 1 to synthesize three new polar 2D lead iodide perovskites (2FBZ) 2 (A) n-1 Pb n I 3n+1 with A = methylammonium (MA) or formamidinium (FA) and n = 2, 3. Single-crystal structure analysis reveals the C 2v symmetry of these crystal structures and substantial structural distortions, which enable Rashba and Dresselhaus band splitting and persistent spin texture, confirmed by DFT calculations. Measurements of the resulting symmetry-dependent properties, such as second harmonic generation, switchable photovoltaic effect, ferroelectric polarization, and low temperature photoluminescence show switchable ferroelectric semiconducting properties. Furthermore, these results introduce a general chemical design strategy toward polar symmetry by exploiting the complex interplay between asymmetric spacer cations and A-site cations in quasi-2D (n > 1) halide perovskites to realize new classes of multifunctional materials for future spin–orbitronic applications.

Cations↗

A 2D chiral microcavity based on apparent circular dichroism

Abstract Engineering asymmetric transmission between left-handed and right-handed circularly polarized light in planar Fabry–Pérot (FP) microcavities would enable a variety of chiral light-matter phenomena, with applications in spintronics, polaritonics, and chiral lasing. Such symmetry breaking, however, generally requires Faraday rotators or nanofabricated polarization-preserving mirrors. We present a simple solution requiring no nanofabrication to induce asymmetric transmission in FP microcavities, preserving low mode volumes by embedding organic thin films exhibiting apparent circular dichroism (ACD); an optical phenomenon based on 2D chirality. Importantly, ACD interactions are opposite for counter-propagating light. Consequently, we demonstrated asymmetric transmission of cavity modes over an order of magnitude larger than that of the isolated thin film. Through circular dichroism spectroscopy, Mueller matrix ellipsometry, and simulation using theoretical scattering matrix methods, we characterize the spatial, spectral, and angular chiroptical responses of this 2D chiral microcavity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Alkali cation stabilization of defects in 2D MXenes at ambient and elevated temperatures

Transition metal carbides have been adopted in energy storage, conversion, and extreme environment applications. Advancements in their 2D counterparts, known as MXenes, enable the design of unique structures at the ~1 nm thickness scale. Alkali cations have been essential in MXenes manufacturing processing, storage, and applications, however, exact interactions of these cations with MXenes are not fully understood. In this study, using Ti 3 C 2 T x , Mo 2 TiC 2 T x , and Mo 2 Ti 2 C 3 T x MXenes, we present how transition metal vacancy sites are occupied by alkali cations, and their effect on MXene structure stabilization to control MXene’s phase transition. We examine this behavior using in situ high-temperature x-ray diffraction and scanning transmission electron microscopy, ex situ techniques such as atomic-layer resolution secondary ion mass spectrometry, and density functional theory simulations. In MXenes, this represents an advance in fundamentals of cation interactions on their 2D basal planes for MXenes stabilization and applications. Broadly, this study demonstrates a potential new tool for ideal phase-property relationships of ceramics at the atomic scale.

42 ENGINEERING↗

Bayesian inference of anisotropic 2D small-angle scattering from sparse measurement

Here, we present a Bayesian inference framework for reconstructing anisotropic two-dimensional small-angle scattering (2D SAS) patterns from sparse, noisy, or partially missing data. The method combines a symmetry-aware angular basis with radial Gaussian process priors to enable accurate, training-free interpolation and denoising. Computational benchmarks demonstrate reliable recovery of both isotropic and high-order anisotropic features under severe data reduction. Experimental validations on stretched polymers, sheared wormlike micelles, and carbon fibers show improved fidelity and resolution compared to raw measurements, achieving comparable accuracy with up to 50-fold fewer detected neutrons. This approach enables quantitative structural analysis under low-flux, time-limited, or single-shot conditions, extending the applicability of 2D SAS techniques to compact neutron sources and mechanically driven soft matter systems undergoing transient structural changes.

Tung, Chi-Huan [Oak Ridge National Laboratory (ORN↗

Reconstruction of 2D line-integrated electron density using angular filter refractometry and a fast marching Eikonal solver

Refraction of an optical probe beam by a plasma can be measured with angular filter refractometry (AFR), which produces an image of the beam’s 2D spatial profile that contains intensity contours corresponding to curves of constant refraction angle. Further analysis is required to reconstruct the underlying line-integrated electron density. Most prior efforts to calculate density from AFR data have been limited to 1D analysis or forward-fitting techniques. Here, in this paper, we detail the use of a fast-marching Eikonal solver to directly invert AFR data and obtain the full 2D line-integrated electron density. The analysis method is first verified with synthetic data and then applied to experimental measurements of single and colliding plasma plumes collected at the OMEGA EP Laser Facility. The calculated densities agree with 1D results and are shown to be consistent with the original AFR measurements via forward modeling. We also discuss ways to improve the precision of this technique.

McCluskey, B. [Princeton Univ., NJ (United States)↗

Isolating solvent–solute hydrogen bonding interactions via 2D IR solvation shell spectroscopy

The solvation shell around a solute is a fundamental feature of liquid-phase solutions, determining the behavior and properties of both the solute and the overall solution. Direct experimental measurements of the solvation shell properties are challenging due to the strong signals generated from the bulk solvent, which overwhelm the small contribution of the solvation shell. Here, we use ultrafast two dimensional infrared (2D IR) spectroscopy and intermolecular cross-peaks to isolate the IR absorption spectrum of methanol molecules in the solvation shell surrounding the solute N-methylacetamide. We demonstrate that the intermolecular coupling between the solvent and solute vibrations is indirectly mediated by a low-frequency hydrogen-bonding mode, suggesting an important mechanism for anharmonic coupling induced by hydrogen bonds. From the relative frequency shifts and cross-peak anisotropy, we find that methanol molecules surrounding N-methylacetamide form stronger and distinctly oriented hydrogen bonds than those in the bulk solvent. Here, we also compare these results with the solvent spectra of the solute N,N-dimethylacetamide to investigate how solute structural changes alter the solvation shell and the contribution of N–H hydrogen bond donation. Our results are supported by molecular dynamics simulations, which provide detailed insights into the hydrogen-bonding distributions. Through these results, we demonstrate 2D solvation shell spectroscopy to be a valuable method for investigating solvation structures and dynamics without interference from the bulk solvent.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

2D photofragmentation LIF imaging of H 2 O 2 and HO 2 in the effluent of an atmospheric-pressure plasma jet: effects of solid and liquid interfaces

Two-dimensional (2D) absolute measurements of hydrogen peroxide (H 2 O 2 ) and approximations of the hydroperoxyl radical (HO 2 ) in the effluent of a COST Reference Microplasma Jet operated with a He/H 2 O feed gas are presented. Gas-phase densities are mapped using photofragmentation laser-induced fluorescence (PF-LIF) under three boundary conditions: open effluent, a solid target, and a liquid target. A novel method is presented for separating PF-LIF signals from H 2 O 2 and HO 2 using comparative measurements in oxygen-rich and oxygen-free environments to exploit the preferential formation of HO 2 in the presence of molecular oxygen. This separation strategy is supported by results from a plug-flow plasma chemistry model. Measured densities agree closely with model predictions in both magnitude and trend, while the 2D experimental distributions provide additional insight into the spatial dependencies of these species. In particular, the results show distinct differences in species transport depending on the target type: solid surfaces induce lateral deflection and reduced centerline densities, whereas liquid interfaces promote axial accumulation and higher near-axis concentrations.

atmospheric-pressure plasma jet (APPJ)↗

Statistical inference of anomalous thermal transport with uncertainty quantification for interpretive 2D SOL models

The critical task of inferring anomalous cross-field transport coefficients is addressed in simulations of boundary plasmas with fluid models. A workflow for parameter inference in the UEDGE fluid code is developed using Bayesian optimization with parallelized sampling and integrated uncertainty quantification. In this workflow, transport coefficients are inferred by maximizing their posterior probability distribution, which is generally multidimensional and non-Gaussian. Uncertainty quantification is integrated throughout the optimization within the Bayesian framework that combines diagnostic uncertainties and model limitations. As a concrete example, we infer the anomalous electron thermal diffusivity $\chi_\perp$ from an interpretive 2D model describing electron heat transport in the conduction-limited region with radiative power loss. The workflow is first benchmarked against synthetic data and then tested on H-, L-, and I-mode discharges to match their midplane temperature and divertor heat flux profiles. We demonstrate that the workflow efficiently infers diffusivity and its associated uncertainty, generating 2D profiles that match 1D measurements. Future efforts will focus on incorporating more complicated fluid models and analyzing transport coefficients inferred from a large database of experimental results.

Bayesian optimization↗