Length Scales Research Articles

Tracking heterogenous protein aggregation at nanoscale through fluorescence correlation spectroscopy.

Various biophysical techniques have been extensively employed to study protein aggregation due to its significance. Traditionally, these methods detect aggregation at micrometer length scales and micromolar concentrations. However, unlike invitro, protein aggregation typically occurs at nanomolar concentrations invivo. Here, using fluorescence correlation spectroscopy (FCS), we captured bromelain aggregation at concentrations as low as ~20 nM, surpassing the detection limit of traditional methods like thioflavin T fluorescence, scattering, and fluorescence microscopy by more than one order of magnitude. Moreover, using thioflavin T fluorescence-based FCS, we have detected larger aggregates at higher bromelain concentrations, which is undetectable in FCS otherwise. Importantly, our study reveals inherent heterogeneity in bromelain aggregation, inaccessible to ensemble-averaged techniques. The presented report may provide a platform for the characterization of premature aggregates at very low protein concentrations, which are thought to be functionally significant species in protein aggregation-induced diseases.

Large bubble drives circular DNA melting.

We investigate the melting transition of non-supercoiled circular DNA of different lengths, employing Brownian dynamics simulations. In the absence of supercoiling, we find that melting of circular DNA is driven by a large bubble, which agrees with the previous predictions of circular DNA melting in the presence of supercoiling. By analyzing sector-wise changes in average base-pair distance, our study reveals that the melting behavior of circular DNA closely resembles that of linear DNA. Additionally, we find a marked difference in the thermal stability of circular DNA over linear DNA at very short length scales, an effect that diminishes as the length of circular DNA increases. The stability of smaller circular DNA is linked to the occurrence of transient small bubbles, characterized by a lower probability of growth.

Scale Characteristics of Six Fish Species of the Genus Cyprinion (Teleostei: Cypriniformes): A Microscopic Analysis.

This study investigated the morphological characteristics of scales in six Cyprinion species, using light and scanning electron microscopy focusing on key features such as scale type, key scales, lateral line scales, radius/radii, rostral margin, focus, circuli, lepidonts, tubercles, and scale indices. The research analyzed the scales using ultramicroscopy and light microscopy imaging, categorizing them based on size classes and body regions. The morphological variations in scale characteristics were examined across different species, regions, and size classes. Notable findings included the tetra-sectioned form of scales, representing a unique characteristic of the Cyprinion genus. Morphological changes in scale features were observed with fish growth, particularly in the overall shape, focus shape, and size. Quantitative analysis revealed variations in average relative scale length and width among different species, regions, and size classes. The study utilized canonical discriminant analysis for multivariate assessment, classifying the species into distinct groups based on morphometric indices. The findings contribute to the understanding of scale morphology in Cyprinion species and exploring morphological variation between the examined species.

Computer Simulation for Determination of Critical Buckling Temperatures of Sandwich Microplates with Cellular Core and CNT-RC Piezoelectric Patches via MSGT

This study introduces a computational simulation which leads to obtaining the critical buckling temperatures of a sandwich microplate which is modeled based on the modified strain gradient theory. This theory includes three material length scale parameters. The core of the microstructure is made from cellular materials which is treated with piezoelectric carbon nanotubes-reinforced composite patches. An advanced trigonometric hyperbolic shear deformation theory, eliminating the need for shear correction factors, is employed to analyze the microstructure. Thickness-dependent variations in structural characteristics are observed based on predefined functions. The equilibrium equations are derived using the virtual displacement principle. Fourier series functions provide an analytical way of solving these equations. The findings are verified by comparison with earlier research that was published and used fewer complex combinations. The study looks at how several important factors affect the structure’s reaction to thermal buckling.

Structure and scaling of Kitaev chain across a quantum critical point in real space.

The spatial Kibble-Zurek mechanism (KZM) is applied to the Kitaev chain with inhomogeneous pairing interactions that vanish in half of the lattice and result in a quantum critical point separating the superfluid and normal-gas phases in real space. The weakly-interacting BCS theory predicts scaling behavior of the penetration of the pair wavefunction into the normal-gas region different from conventional power-law results due to the non-analytic dependence of the BCS order parameter on the interaction. The Bogoliubov-de Gennes (BdG) equation produces numerical results confirming the scaling behavior and hints complications in the strong-interaction regime. The limiting case of the step-function quench reveals the dominance of the BCS coherence length in absence of additional length scale. Furthermore, the energy spectrum and wavefunctions from the BdG equation show abundant in-gap states from the normal-gas region in addition to the topological edge states.

Rapid detection of rare events from in situX-ray diffraction data using machine learning.

High-energy X-ray diffraction methods can non-destructively map the 3D microstructure and associated attributes of metallic polycrystalline engineering materials in their bulk form. These methods are often combined with external stimuli such as thermo-mechanical loading to take snapshots of the evolving microstructure and attributes over time. However, the extreme data volumes and the high costs of traditional data acquisition and reduction approaches pose a barrier to quickly extracting actionable insights and improving the temporal resolution of these snapshots. This article presents a fully automated technique capable of rapidly detecting the onset of plasticity in high-energy X-ray microscopy data. The technique is computationally faster by at least 50 times than the traditional approaches and works for data sets that are up to nine times sparser than a full data set. This new technique leverages self-supervised image representation learning and clustering to transform massive data sets into compact, semantic-rich representations of visually salient characteristics (e.g. peak shapes). These characteristics can rapidly indicate anomalous events, such as changes in diffraction peak shapes. It is anticipated that this technique will provide just-in-time actionable information to drive smarter experiments that effectively deploy multi-modal X-ray diffraction methods spanning many decades of length scales.

The transition between the collision-dominated and ballistic electron transport regimes as the device length is reduced: A continuum analysis

Noting that the conventional collision-dominated electron transport perspective is only relevant when the length scale over which the transit occurs is greater than the electron’s mean free path, one can conceptually partition the electron transport “space” into collision-dominated and ballistic electron transport regimes. As the boundaries between these regimes are quite porous, in this analysis, we devise a means of quantitatively examining the transition between electron transport regimes as the length scale is reduced on a continuum basis. Our approach introduces a collision-dominated fractional scattering parameter, this parameter quantifying the fraction of the total scattering rate that arises purely from bulk scattering processes, contact scattering also contributing to the total scattering rate. We pursue this analysis for two conventional semiconductors of interest, silicon and gallium arsenide. A determination of the dependence of the results on both the length scale and the crystal temperature is pursued. Finally, for the specific case of room temperature, a comparison with the results of experiment is performed.

Dispersive interaction between two atoms in Proca quantum electrodynamics

We analyze the influence of a massive photon in the dispersive interaction between two atoms in their fundamental states. We work in the context of Proca quantum electrodynamics. The photon mass not only introduces a new length scale but also gives rise to a longitudinal polarization for the electromagnetic field. We obtain explicitly the interaction energy between the atoms for any distance regime and consider several particular cases. We show that, for a given interatomic distance, the greater the photon mass the better it is the nonretarded approximation. Published by the American Physical Society 2024

GCMe: Efficient Implementation of the Gaussian Core Model with Smeared Electrostatic Interactions for Molecular Dynamics Simulations of Soft Matter Systems.

In recent years, molecular dynamics (MD) simulations have emerged as an essential tool for understanding the structure, dynamics, and phase behavior of charged soft matter systems. To explore phenomena across greater length and time scales in MD simulations, molecules are often coarse-grained for better computational performance. However, commonly used force fields represent particles as hard-core interaction centers with point charges, which often overemphasizes the packing effect and short-range electrostatics, especially in systems with bulky deformable organic molecules and systems with strong coarse-graining. This underscores the need for an efficient soft-core model to physically capture the effective interactions between coarse-grained particles. To this end, we implement a soft-core model uniting the Gaussian core model with smeared electrostatic interactions that is phenomenologically equivalent to recent theoretical models. We first parametrize it generically using water as the model solvent. Then, we benchmark its performance in the OpenMM toolkit for different boundary conditions to highlight a computational speedup of up to 34 × compared to commonly used force fields and existing implementations. Finally, we demonstrate its utility by investigating how boundary polarizability affects the adsorption behavior of a polyelectrolyte solution on perfectly conducting and nonmetal boundaries.

Ocean Currents Resolved on Regional Length Scales

Ocean Currents Resolved on Regional Length Scales

Dynamic loading platforms coupled to ultra-high speed X-ray imaging at beamline ID19 of the European Synchrotron ESRF

ABSTRACT The intersection of dynamic compression, high-rate material response and X-ray science has seen rapid growth, leading to the establishment of specialized end-stations at international facilities such as Linac Coherent Light Source LCLS (Matter at Extreme Conditions – MEC) and Advanced Photon Source APS (Dynamic Compression Sector – DCS), both USA. Although these facilities excel in working with X-rays tailored for small material volumes (i.e. < 1 mm 3 ), it needs a different approach to delve into subsequent processes. This is particularly the case in the transition from the micro- to mesoscale: here the ESRF distinguishes itself. The large beam size (several cm2) of the ID19 beamline, in conjunction with a strong high energy component, source flux density, and outstanding imaging sensitivity, enables sub-surface visualization of engineering-scale structures as well as natural systems in representative volume, under high rate and shock. This is particularly valuable when studying materials with complex mesostructures and heterogeneities on relevant volumetric scales, which often dominate the dynamic material response. The study of the behavior of materials under dynamic loading presents a unique challenge due to inherently spanning over multiple lengths- and timescales. The evolution of sudden (thermo)mechanical excitation, starting from the lattice scale and progressing through grains, phase domains, and ultimately to structures, exhibits a spectrum of responses spanning from the microscopic to bulk length scales. Consequently, a diverse range of diagnostics as well as driver instrumentation is required to identify, study, and characterize this material response spectrum. This article shall introduce platforms available at beamline ID19 and underline their potential by selected showcase applications. Community access proposals such as the beamtime Block Allocation Group (BAG) allow for access in a routine manner.

AI-NERD: Elucidation of relaxation dynamics beyond equilibrium through AI-informed X-ray photon correlation spectroscopy

Understanding and interpreting dynamics of functional materials in situ is a grand challenge in physics and materials science due to the difficulty of experimentally probing materials at varied length and time scales. X-ray photon correlation spectroscopy (XPCS) is uniquely well-suited for characterizing materials dynamics over wide-ranging time scales. However, spatial and temporal heterogeneity in material behavior can make interpretation of experimental XPCS data difficult. In this work, we have developed an unsupervised deep learning (DL) framework for automated classification of relaxation dynamics from experimental data without requiring any prior physical knowledge of the system. We demonstrate how this method can be used to accelerate exploration of large datasets to identify samples of interest, and we apply this approach to directly correlate microscopic dynamics with macroscopic properties of a model system. Importantly, this DL framework is material and process agnostic, marking a concrete step towards autonomous materials discovery.

Whispering gallery mode sensing through the lens of quantum optics, artificial intelligence, and nanoscale catalysis

Ultra-sensitive sensors based on the resonant properties of whispering gallery modes (WGMs) can detect fractional changes in nanoscale environments down to the length and time scales of single molecules. However, it is challenging to isolate single-molecule signals from competing noise sources in experiments, such as thermal and mechanical sources of noise, and—at the most fundamental level—the shot noise limit of classical light. Additionally, in contrast to traditional bulk refractive index measurements, analyzing single-molecule signals is complicated by the localized nature of their interactions with nanoscale field gradients. This perspective discusses multifaceted solutions to these challenges, including the use of quantum light sources to boost the signal-to-noise ratio in experiments and leveraging the power of supercomputers to predict the electronic response of molecules to WGM optoplasmonic fields. We further discuss the role of machine learning in WGM sensing, including several advanced models that can predict molecular polarizability and solvent effects. These advancements in WGM spectroscopy and computational modeling can help to decipher the molecular mechanics of enzymes, enable studies of catalysis on the nanoscale, and probe the quantum nature of molecules.

Effective and adaptable: Four studies on the shortened attitude toward the color blue marker variable scale.

This research is an extension of the recent scale development efforts for the marker variable Attitude Toward the Color Blue (ATCB), which addresses the efficacy of multiple shorter permutations of the scale. The purpose of this study is to develop a shorter version of an ideal marker variable scale used to detect common method variance. Potential uses of the shorter version of ATCB include intensive longitudinal studies, implementation of experience sampling methodology, or any brief survey for which the original version might be cumbersome to implement repeatedly or appear very odd to the respondent when paired with only a few other substantive items. Study 1, uses all six-, five-, and four-item versions of ATCB in confirmatory factor analysis (CFA) marker technique tests on a bivariate relationship. Study 2 analyzes the best- and worst-performing versions of reduced lengths of the ATCB scale found in the first study on another bivariate relationship. Study 3 compares the original seven-item version, as well as randomly selected reduced length versions in a data set with 15 model relationships. Study 4 uses an experiment to determine the efficacy of providing respondents with one of three shorter ATCB scales in a model of three substantive variables. Our findings indicate that ATCB of different permutations and lengths can detect CMV successfully, and that researchers should choose the length of scale based on their survey length. We conclude that ATCB is adaptable for a variety of research situations, presenting it as a valuable tool for high-quality research.

Terahertz spectroscopy of collective charge density wave dynamics at the atomic scale

AbstractCharge density waves are wave-like modulations of a material’s electron density that display collective amplitude and phase dynamics. The interaction with atomic impurities induces strong spatial heterogeneity of the charge-ordered phase. Direct real-space observation of phase excitation dynamics of such defect-induced charge modulation is absent. Here, by utilizing terahertz pump–probe spectroscopy in a scanning tunnelling microscope, we measure the ultrafast collective dynamics of the charge density wave in the transition metal dichalcogenide 2H-NbSe2 with atomic spatial resolution. The tip-enhanced electric field of the terahertz pulses excites oscillations of the charge density wave that vary in magnitude and frequency on the scale of individual atomic impurities. Overlapping phase excitations originating from the randomly distributed atomic defects in the surface create this spatially structured response of the charge density wave. This ability to observe collective charge order dynamics with local probes makes it possible to study the dynamics of correlated materials at the intrinsic length scale of their underlying interactions.

Curvature programming of freestanding 3D mesostructures and flexible electronics based on bilayer ribbon networks

Three-dimensional (3D) buckling assembly of flexible electronics from strategically designed two-dimensional (2D) precursor structures has enabled important applications in a variety of areas, owing to its versatile applicability to a broad range of length scales and high-performance materials, as well as to a rich diversity of 3D topologies. Rational design methods that allow direct mapping of 3D mesostructures onto unknown 2D precursor structures and loading parameters are foundational to these assembly technologies, but face scientific challenges, such as the high nonlinearity of spatial deformations and tricky bifurcation behaviors. While a few inverse design methods based on the beam theory, topology optimization and machine learning algorithms have been reported, the shape programming of freestanding 3D mesostructures/electronics with highly complex curvature distributions remains elusive. In this work, we propose a curvature programming method based on bilayer ribbon networks, along with a mold-assisted assembly strategy, as a new route to customizable freestanding 3D mesostructures and electronics. Combined mechanics modeling, finite element analyses and experimental measurements allow a clear understanding of nonlinear bending-stretching coupled deformations of bilayer ribbon networks during the 2D-to-3D transformation. A parameter domain with one-to-one mapping of the dimensionless curvature and the bending stiffness ratio is identified, offering a theoretical basis of the curvature programming. By introducing a discretization strategy, a variety of regular (e.g., circles, ellipses, spirals and toroids) and biomimetic 3D curved ribbons and mesosurfaces (e.g., mimicking wavy vines, diatoms and arbitrarily curled leaves) were inversely designed and experimentally realized. A device demonstration capable of strain/temperature sensing and micro-LEDs indication suggests application opportunities in bioelectronics and microelectromechanical systems.

Measurement of the depth-dependent local dynamics in thin polymer films through rejuvenation of ultrastable glasses

The depth dependence of structural relaxation dynamics is a key part of understanding thin glassy films. Despite this importance and decades of research, a method to provide this information has proved elusive. We measure the isothermal rejuvenation of stable glass films of poly(styrene), and demonstrate that the propagation of the front responsible for the transformation to a supercooled-liquid state serves as a highly localized probe of the local dynamics of the supercooled liquid. We use this connection to probe the depth-dependent relaxation rate with nanometric precision for a series of polystyrene films over a range of temperatures near the bulk glass transition temperature. The analysis shows the spatial extent of enhanced surface mobility and reveals the existence of an unexpected large dynamical length scale in the system. The results are compared with the cooperative-string model for glassy dynamics. The data reveals that the film-thickness dependence of whole film properties arises mainly from the volume fraction of the near-surface region. While the dynamics farthest from the free surface shows the expected bulk-like temperature dependence, the dynamics in the near-surface region shows very little dependence on temperature. This technique can be used in a broad range of thin film materials to gain previously unattainable information about localized structural relaxation.

Intermediate scattering function for polymer molecules: An approach based on relaxation mode analysis.

The theory of polymer dynamics describes the intermediate scattering function for a polymer molecule in terms of relaxation modes defined by normal coordinates for the corresponding coarse-grained model. However, due to the difficulty of defining the normal coordinates for arbitrary polymer molecules, it is generally challenging to express the intermediate scattering function for a polymer molecule in terms of relaxation modes. To overcome this challenge, we propose a general method to calculate the intermediate scattering function for a polymer molecule on the basis of a relaxation mode analysis approach [Takano and Miyashita, J. Phys. Soc. Jpn. 64, 3688 (1995)]. In the proposed method, relaxation modes defined by eigenfunctions in a Markov process are evaluated on the basis of the simulation results for a polymer molecule and used to calculate the intermediate scattering function for that molecule. To demonstrate the effectiveness of the present method, we simulate the dynamics of a linear polymer molecule in a dilute solution and apply it to the calculation of the intermediate scattering function for the polymer molecule. The evaluation results regarding the relaxation modes reasonably describe the intermediate scattering function on the length scale of the radius of gyration of the polymer molecule. Accordingly, we examine the contributions of the pure relaxation and oscillatory relaxation processes to the entire intermediate scattering function.

Mesoscale Acid-Base Complexes Display Size-Associated Photophysical Property and Photochemical Activity.

The properties of single molecules and molecular aggregates can differ dramatically, leading to a long-standing interest in mesoscale aggregation processes. Herein, a series of acid-base molecular complexes is developed by using a tetraphenylethylene-backboned fluorophore, and investigated the photophysical properties and photochemical activities at different aggregation length scales. This fluorophore, with two basic diethylamine groups and two acidic tetrazole groups, exhibits sparse solubility due to multivalent interactions that cause infinite aggregation. The addition of a third acid leads to the formation of fluorophore/acid complexes with good dispersibility and colloidal stability. This assembly process can be controlled by the use of different acids and their stoichiometry, resulting in aggregates ranging in size from a few to hundreds of nanometers. A crystalline structure is obtained to illustrate the complex properties of the acid-base network. Unlike the single molecule, these complexes show a trend of size-related properties for photoluminescence efficiency and photochemical activity. As the amount of acid added increases, the size of the complexes decreases, the aggregation effect of the complexes on fluorescence emission increases, and the rates of the oxidative photocyclization and photodecomposition slow down. This work may help to understand size-controlled molecular materials at the mesoscale for functional design.

Frictional resistance and delamination mechanisms in 2D tungsten diselenide revealed by multi-scale scratch and in-situ observations

Friction phenomena in two-dimensional (2D) materials are conventionally studied at atomic length scales in a few layers using low-load techniques. However, the advancement of 2D materials for semiconductor and electronic applications requires an understanding of friction and delamination at a few micrometers length scale and hundreds of layers. To bridge this gap, the present study investigates frictional resistance and delamination mechanisms in 2D tungsten diselenide (WSe2) at 10 µm length and 100–500 nm depths using an integrated atomic force microscopy (AFM), high-load nanoscratch, and in-situ scanning electron microscopic (SEM) observations. AFM revealed a heterogenous distribution of frictional resistance in a single WSe2 layer originating from surface ripples, with the mean increasing from 8.7 to 79.1 nN as the imposed force increased from 20 to 80 nN. High-load in-situ nano-scratch tests delineated the role of the individual layers in the mechanism of multi-layer delamination under an SEM. Delamination during scratch consists of stick-slip motion with friction force increasing in each successive slip, manifested as increasing slope of lateral force curves with scratch depth from 10.9 to 13.0 (× 103) Nm−1. Delamination is followed by cyclic fracture of WSe2 layers where the puckering effect results in adherence of layers to the nanoscratch probe, increasing the local maximum of lateral force from 89.3 to 205.6 µN. This establishment of the interconnectedness between friction in single-layer and delamination at hundreds of layers harbors the potential for utilizing these materials in semiconductor devices with reduced energy losses and enhanced performance.