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The data provided by the atmospheric water channels of SEASAT's Scanning Multichannel Microwave Radiometer (SMMR) is used to investigate mesoscale structure at various stages of the development of a midlatitude cyclone. Seasonal and graphic differences in the storms are also studied.
A grand challenge in materials science is to identify the impact of molecular composition and structure across a range of length scales on macroscopic properties. We demonstrate a unified experimental–theoretical framework that coordinates experimental measurements of mesoscale structure with molecular-level physical modeling to bridge multiple scales of physical behavior. Here we apply this framework to understand charge transport in a semiconducting polymer. Spatially-resolved nanodiffraction in a transmission electron microscope is combined with a self-consistent framework of the polymer chain statistics to yield a detailed picture of the polymer microstructure ranging from the molecular to device relevant scale. Using these data as inputs for charge transport calculations, the combined multiscale approach highlights the underrepresented role of defects in existing transport models. Short-range transport is shown to be more chaotic than is often pictured, with the drift velocity accounting for a small portion of overall charge motion. Local transport is sensitive to the alignment and geometry of polymer chains. At longer length scales, large domains and gradual grain boundaries funnel charges preferentially to certain regions, creating inhomogeneous charge distributions. While alignment generally improves mobility, these funneling effects negatively impact mobility. The microstructure is modified in silico to explore possible design rules, showing chain stiffness and alignment to be beneficial while local homogeneity has no positive effect. This combined approach creates a flexible and extensible pipeline for analyzing multiscale functional properties and a general strategy for extending the accesible length scales of experimental and theoretical probes by harnessing their combined strengths.
The mesoscale structures of the wedge-shaped pressure ridge and the coastal front associated with the Appalachian ice storm of January 13-14, 1980 is analyzed using a mesoscale model. The characteristic features of the mesoscale model, which uses 15 vertical levels, 50-km grid length, and multilevel, boundary-layer parameterization, are described. The simulation of the surface layer winds and temperature, the evolution of the vertical temperature structure of the wedge-ridge region, and model simulations of the low-level jets and the coastal front are examined. Trajectories based on the 24-hr simulation of the winds are discussed.
Abstract The potential for creating hierarchical domain structures, or mixtures of energetically degenerate phases with distinct patterns that can be modified continually, in ferroelectric thin films offers a pathway to control their mesoscale structure beyond lattice‐mismatch strain with a substrate. Here, it is demonstrated that varying the strontium content provides deterministic strain‐driven control of hierarchical domain structures in Pb 1− x Sr x TiO 3 solid‐solution thin films wherein two types, c / a and a 1 / a 2 , of nanodomains can coexist. Combining phase‐field simulations, epitaxial thin‐film growth, detailed structural, domain, and physical‐property characterization, it is observed that the system undergoes a gradual transformation (with increasing strontium content) from droplet‐like a 1 / a 2 domains in a c / a domain matrix, to a connected‐labyrinth geometry of c / a domains, to a disconnected labyrinth structure of the same, and, finally, to droplet‐like c / a domains in an a 1 / a 2 domain matrix. A relationship between the different mixed‐phase modulation patterns and its topological nature is established. Annealing the connected‐labyrinth structure leads to domain coarsening forming distinctive regions of parallel c / a and a 1 / a 2 domain stripes, offering additional design flexibility. Finally, it is found that the connected‐labyrinth domain patterns exhibit the highest dielectric permittivity.
Flow-assisted alignment of anisotropic nanoparticles is a promising route for the bottom-up assembly of advanced materials with tunable properties. While aligning processes could be optimized by controlling factors such as solvent viscosity, flow deformation, and the structure of the particles themselves, it is necessary to understand the relationship between these factors and their effect on the final orientation. In this study, we investigated the flow of surface-charged cellulose nanocrystals (CNCs) with the shape of a rigid rod dispersed in water and propylene glycol (PG) in an isotropic tactoid state. In situ scanning small-angle X-ray scattering (SAXS) and rheo-optical flow-stop experiments were used to quantify the dynamics, orientation, and structure of the assigned system at the nanometer scale. The effects of both shear and extensional flow fields were revealed in a single experiment by using a flow-focusing channel geometry, which was used as a model flow for nanomaterial assembly. Due to the higher solvent viscosity, CNCs in PG showed much slower Brownian dynamics than CNCs in water and thus could be aligned at lower deformation rates. Moreover, CNCs in PG also formed a characteristic tactoid structure but with less ordering than CNCs in water owing to weaker electrostatic interactions. The results indicate that CNCs in water stay assembled in the mesoscale structure at moderate deformation rates but are broken up at higher flow rates, enhancing rotary diffusion and leading to lower overall alignment. Albeit being a study of cellulose nanoparticles, the fundamental interplay between imposed flow fields, Brownian motion, and electrostatic interactions likely apply to many other anisotropic colloidal systems.
Protein salting-out is a well established phenomenon that in many cases leads to amorphous structures and protein gels, which are usually not considered to be useful for protein structure determination. Here, microstructural measurements of several different salted-out protein dense phases are reported, including of lysozyme, ribonuclease A and an IgG1, showing that salted-out protein gels unexpectedly contain highly ordered protein nanostructures that assemble hierarchically to create the gel. The nanocrystalline domains are approximately 10–100 nm in size, are shown to have structures commensurate with those of bulk crystals and grow on time scales in the order of an hour to a day. Beyond revealing the rich, hierarchical nanoscale to mesoscale structure of protein gels, the nanocrystals that these phases contain are candidates for structural biology on next-generation X-ray free-electron lasers, which may enable the study of biological macromolecules that are difficult or impossible to crystallize in bulk.
In highly concentrated electrolyte solutions, where classical models often fail, specific ion–solvent interactions dictate bulk properties. Here, in this study, we combine small-angle X-ray scattering (SAXS) and Raman spectroscopy to link molecular coordination to mesoscale structure across alkali nitrate and nitrite solutions. Our results reveal a structural hierarchy driven by cation identity in that smaller cations (Li + , Na + ) form discrete contact ion pairs, while larger cations (K + , Rb + ) promote increasingly disordered local coordination and extended solute–solvent networks. Using nitrite salts as a structural control, we confirm this organizing principle across different anion geometries. Cs + undergoes a concentration-induced transition to a uniquely ordered state, resulting in a highly structured solution. This work provides a direct, mechanistic explanation for how cation choice dictates the ‘rules’ of solution architecture, offering a predictive basis for understanding phase behavior in complex industrial and environmental systems.
The atomic pair distribution function (aPDF) analysis technique, also known as the total scattering method, which considers both Bragg and diffuse scattering, has been used extensively to probe local atomic arrangements in crystalline and disordered materials. In contrast, there have been limited applications of the PDF in self-assembled nanomaterials, which represent a class of materials built from nanoscale objects, such as nano-colloids, micelles and proteins. As distinguished from atoms, nano-objects have polydispersity in size and shape, and such form-factor effects complicate the application of PDF analysis to nano-systems. Here, in this paper, the application of the PDF is extended to spherical nano-object assemblies and the formulae for the nano-PDF (nPDF) are derived, showing some differences from the aPDF. By numerical simulations, the properties of the nPDF (peak broadening and pattern profile) are studied systematically as a function of structural features, such as nano-object parameters (size and size polydispersity) and assembly structural features (size, shape, structure type and lattice disorder), and of data processing parameters ( q cut-off and `missing' data in ultra-small-angle regions). The nPDF analysis method is found to provide an effective route to revealing not only nanoscale but also mesoscale structural properties, for example the morphology of a nano-assembly.
Convection‐permitting models (CPMs) explicitly resolve deep convection yet under‐resolve the organized lateral exchanges among drafts and their environment that control entrainment/detrainment, precipitation efficiency, and mesoscale structure. In this work, we introduce the Optimized Advection Scheme (OAS), which introduces a small rotation of the Cartesian frame of reference for the horizontal winds relative to other variables used in advection that induces cross‐gradient transport to mimic under‐resolved convective mixing. The rotation angle is selected to minimize the Kullback–Leibler divergence between the simulated and satellite observed precipitation intensity distributions, yielding a physically consistent perturbation that is computationally inexpensive and portable. Optimized Advection Scheme is implemented in WRF and evaluated over Amazon (April 2014). It shifts precipitation–precipitable‐water joint distributions toward lighter rain, reduces overly intense rates, and improves mesoscale convective system (MCS) lifetime and propagation. Mechanistically, the added cross‐gradient transport promotes convective detrainment and environmental mixing, which cools and moistens the mid‐troposphere, weakens downward momentum transport, alleviates excessive downwelling shortwave biases, and warms the surface temperature. The optimized rotation angle yields comparable improvements at 4‐km and 1‐km grid spacing, demonstrating resolution‐independent benefits across the CPM gray zone. By targeting the dynamical root of under‐mixed convective circulations, rather than tuning model microphysics or closures, OAS delivers robust, scale‐aware improvements in precipitation statistics, cloud vertical structure, and characteristics of MCS (MCSs), offering a practical pathway to more reliable CPM simulations for weather and climate applications.
Patterns in the horizontal distribution of integrated water vapor, integrated liquid water and rainfall rate derived from the Seasat Scanning Multichannel Microwave Radiometer (SMMR) during a September 10-12, 1978 North Pacific cyclone are studied. These patterns are compared with surface analyses, ship reports, radiosonde data, and GOES-West infrared satellite imagery. The SMMR data give a unique view of the large mesoscale structure of a midlatitude cyclone. The water vapor distribution is found to have characteristic patterns related to the location of the surface fronts throughout the development of the cyclone. An example is given to illustrate that SMMR data could significantly improve frontal analysis over data-sparse oceanic regions. The distribution of integrated liquid water agrees qualitatively well with corresponding cloud patterns in satellite imagery and appears to provide a means to distinguish where liquid water clouds exist under a cirrus shield. Ship reports of rainfall intensity agree qualitatively very well with SMMR-derived rainrates. Areas of mesoscale rainfall, on the order of 50 km x 50 km or greater are detected using SMMR derived rainrates.
We investigated how organic matter may, directly and indirectly, modify the porosity of Ferralsols, that is, deeply weathered soils of the tropics and subtropics. Although empirical and anecdotal evidence suggests that organic matter accumulation may increase porosity, a mechanistic understanding of the processes underlying this beneficial effect is lacking, especially so for Ferralsols. To achieve our end, we leveraged the fact that the Profundihumic qualifier of Ferralsols (PF) is distinguished from Haplic Ferralsols (HF) by both a much larger average carbon content in the first 1 m of soil depth (19 kg C m -3 in PF vs. 10 kg C m -3 in HF) and a significantly lower bulk density (1.05 ± 0.08 kg L -1 in PF vs. 1.21 ± 0.05 kg L -1 in HF). Through exhaustive modelling of carbon – bulk density relationships, we demonstrate that the lower bulk density of PF cannot be satisfactorily explained by a simple dilution effect. Rather, we found that bulk density correlated with carbon content when combined with carbon: nitrogen ratio (r 2 = 0.51), black carbon content (r 2 = 0.75), and Δ 14 C (r 2 =0.81). Total pore space was greater in PF (61± 3%) than in HF (55 ± 2%), but x-ray computed tomography revealed that pore space inside soil aggregates of 4–5 mm diameter does not vary between the studied Ferralsols. We further observed nearly twice as many roots and burrows in PF compared with HF. We thus infer that the mechanism responsible for the increase in porosity is most likely an enhancement of resource availability (e.g., energy, carbon, and nutrients) for the organisms (earthworms, ants, termites, etc.) that physically displace soil particles and promote soil aggregation. As a result of increased resource availability, soil organisms can create especially the mesoscale structural soil features necessary for unrestricted water flow and rapid gas exchange. In conclusion, this insight paves the way for the development of land management technologies to optimize the physical shape and capacity of the soil bioreactor.
Resonant soft X-ray scattering (RSoXS) is an emerging, powerful technique to probe the nano-to-mesoscale structure of polymers and other molecules. It joins together small-angle X-ray scattering (a statistical nanoprobe) with X-ray spectroscopy that brings with it unique chemical and bond-orientation sensitivity. Through over a decade of discovery and development, RSoXS is moving from a niche technique applied to organic electronic thin films to a mature tool applicable to a plethora of polymeric and molecular systems, encompassing new modalities, analyses, and simulation methods. This development promises to deliver increasingly quantitative answers to challenging questions in polymer science as well as expand its usefulness to complementary fields. Here, this review presents a full synopsis of the technique, including background on the theoretical underpinnings, measurement best practices, and examples of recent RSoXS applications and discoveries provided here to accelerate the transition to a broader range of soft matter and polymeric fields.
Materials synthesis via additive manufacturing gives unprecedented control over the solidified microstructure. While a number of studies have demonstrated the ability to produce spatially varying microstructures, little work exists to understand the behavior of such “composite” materials. In this work, we utilized electron beam melting to process Ni-based superalloy Haynes 282 and produce compact tension samples with a spatially varying mesoscale structure. Fatigue crack growth experiments reveal that the crack growth rate is dependent on the degree of microstructural heterogeneity. This work demonstrates that the crack growth resistance can be tailored within a component using electron beam melting additive manufacturing.
Ordered mesoscale structures in 2D materials induced by small misorientations have allowed for a wide variety of electronic, ferroelectric, and quantum phenomena to be explored. Until now, the only mechanism to induce this periodic ordering was via mechanical rotations between the layers, with the periodicity of the resulting moiré pattern being directly related to twist angle. Here we report a fundamentally distinct mechanism for emergence of mesoscopic periodic patterns in multilayer sulfur-containing metal phosphorus trichalcogenide, MnPS3, induced by the electron beam. The formation under the beam of periodic hexagonal patterns with several characteristic length scales, nucleation and transitions between the phases, and local dynamics are demonstrated. The associated mechanisms are attributed to the relative contraction of the layers caused by beam-induced sulfur vacancy formation with subsequent ordering and lattice parameter change. As a result, the plasmonic response of the system is locally altered, suggesting an element of control over plasmon resonances by electron beam patterning. To conclude, we pose that harnessing this phenomenon provides both insight into fundamental physics of quantum materials and enables device applications by enabling controlled periodic potentials on the atomic scale.
Creation of complex nanostructured materials through oriented attachment (OA) requires the manipulation of interparticle forces, including electrostatic repulsion, which depends strongly on surface potentials and can be modified through the effect of solution environment on interfacial chemistry. Here we show that time-dependent anisotropies in surface potential driven by competitive ion adsorption can alter facet-selectivity during OA. This phenomenon enables the synthesis of branched cubic Pt mesocrystals. Initially, Pt nanoparticles attach preferentially at their {100} facets to form a well-defined cubic core. Over time, changes in ion adsorption shift the attachment preference to the {111} facets, promoting branch formation. In both stages, anisotropic surface potentials generate electrostatic torques that align the particles prior to attachment. These findings demonstrate a generalizable strategy for directing the architecture of nanomaterials through time-resolved control of interfacial chemistry during OA, offering new pathways for the design of complex mesoscale structures.
Conjugated polymer thin films offer a unique combination of tunable optoelectronic properties and mechanical flexibility, making them as promising materials for intrinsically stretchable optoelectronic devices. However, achieving both mechanical robustness and high device performance remains a key challenge. Addressing this requires a fundamental understanding of how molecular and mesoscale structures evolve under mechanical strain. Here, we employ a comprehensive suite of X-ray spectroscopy and scattering techniques to investigate the multiscale structural evolution of conjugated polymer thin films during uniaxial deformation. We uncover a two-stage morphological response: an initial stage characterized by polymer chain alignment and rapid crystallite disruption, followed by continued chain orientation accompanied by intrachain torsion at higher strains. These correlative structural adaptations govern key material properties, including stress dissipation, optical absorption, and photovoltaic performance. Our findings establish a mechanistic framework for understanding deformation in semiconducting polymers and provide design principles for developing mechanically robust, high-performance stretchable electronics.
Electron, optical, and scanning probe microscopy methods are generating ever increasing volume of image data containing information on atomic and mesoscale structures and functionalities. This necessitates the development of the machine learning methods for discovery of physical and chemical phenomena from the data, such as manifestations of symmetry breaking phenomena in electron and scanning tunneling microscopy images, or variability of the nanoparticles. Variational autoencoders (VAEs) are emerging as a powerful paradigm for the unsupervised data analysis, allowing to disentangle the factors of variability and discover optimal parsimonious representation. Here, we summarize recent developments in VAEs, covering the basic principles and intuition behind the VAEs. The invariant VAEs are introduced as an approach to accommodate scale and translation invariances present in imaging data and separate known factors of variations from the ones to be discovered. We further describe the opportunities enabled by the control over VAE architecture, including conditional, semi-supervised, and joint VAEs. Several case studies of VAE applications for toy models and experimental datasets in Scanning Transmission Electron Microscopy are discussed, emphasizing the deep connection between VAE and basic physical principles. Python codes and datasets discussed in this article are available at https://github.com/saimani5/VAE-tutorials and can be used by researchers as an application guide when applying these to their own datasets.
The ability to fabricate materials and devices at small scales by design has resulted in tremendous technological progress. However, the need for engineered three-dimensional (3D) nanoscale materials requires new strategies for organizing nanocomponents. Here we demonstrate an inverse design approach for the assembly of nanoparticles into hierarchically ordered 3D organizations using DNA voxels with directional, addressable bonds. By identifying intrinsic symmetries in repeating mesoscale structural motifs, we prescribe a set of voxels, termed a mesovoxel, that are assembled into target 3D crystals. The relationship between different degrees of encoded information used for voxel bonds and the fidelity of assembly is investigated using experimental and computational methods. We apply this assembly strategy to create periodic 3D nanoparticle ordered organizations, including structures with low-dimensional elements, helical motifs, a nanoscale analogue of a face-centred perovskite crystal and a distributed Bragg reflector based on a crystal with plasmonic and photonic length-scale regimes.