Length Scales Research Articles

Atomistic understanding of ductile-to-brittle transition in single crystal Si and GaAs under nanoscratch

Ensuring ductile removal in a grinding process is crucial for achieving the desired finish on a hard and brittle single crystal. This study provides new insights into the material removal processes in Si and GaAs single crystals, exploring their deformation behaviour using Berkovich and Conical tips to replicate contact from a fixed abrasive grit. Experimental observations are compared with Molecular Dynamic (MD) simulations to uncover the atomistic deformation mechanisms during the ductile-to-brittle transition (DBT). Notable plastic deformation and minimal cracking were consistently observed in Si, irrespective of the tips used. MD simulations supported this observation, revealing pronounced chip formation indicative of ductile material removal. The resistance to cracking in Si was attributed to amorphization induced by localized high contact stresses. In contrast, GaAs showed a propensity for cracking, with MD simulations revealing dislocation and slip band formation, and cracks emerging in the areas of substantial plastic deformation. These findings address phenomena not previously discernible in experimental studies due to the challenge of real-time observation. Moreover, the tip geometry was shown to significantly influence stress distribution, impacting deformation and crack formation in GaAs. This study also reveals limitations in predicting the critical depth for DBT in both Si and GaAs throught the amended Bifano, Dow, and Scattergood (aBDS) models and MD simulation, offering nuanced insights into these challenges that have not been extensively explored. It was found that the experimental results exceeded predictions by an order of magnitude. These discrepancies underscore the aBDS model's disregard for essential material properties and tip geometry, while the disparities between MD simulation and experiment are primarily attributed to the inherent limitations in the simulated length scales and challenges in detecting initial subsurface cracks.

Crossing length scales: X-ray approaches to studying the structure of biological materials.

Biological materials have outstanding properties. With ease, challenging mechanical, optical or electrical properties are realised from comparatively `humble' building blocks. The key strategy to realise these properties is through extensive hierarchical structuring of the material from the millimetre to the nanometre scale in 3D. Though hierarchical structuring in biological materials has long been recognized, the 3D characterization of such structures remains a challenge. To understand the behaviour of materials, multimodal and multi-scale characterization approaches are needed. In this review, we outline current X-ray analysis approaches using the structures of bone and shells as examples. We show how recent advances have aided our understanding of hierarchical structures and their functions, and how these could be exploited for future research directions. We also discuss current roadblocks including radiation damage, data quantity and sample preparation, as well as strategies to address them.

Multiferroicity in plastically deformed SrTiO3

Quantum materials have a fascinating tendency to manifest novel and unexpected electronic states upon proper manipulation. Ideally, such manipulation should induce strong and irreversible changes and lead to new relevant length scales. Plastic deformation introduces large numbers of dislocations into a material, which can organize into extended structures and give rise to qualitatively new physics as a result of the huge localized strains. However, this approach is largely unexplored in the context of quantum materials, which are traditionally grown to be as pristine and clean as possible. Here we show that plastic deformation induces robust magnetism in the quantum paraelectric SrTiO3, a property that is completely absent in the pristine material. We combine scanning magnetic measurements and near-field optical microscopy to find that the magnetic order is localized along dislocation walls and coexists with ferroelectric order along the walls. The magnetic signals can be switched on and off via external stress and altered by external electric fields, which demonstrates that plastically deformed SrTiO3 is a quantum multiferroic. These results establish plastic deformation as a versatile knob for the manipulation of the electronic properties of quantum materials.

The influence of water turbulence on surface deformations and the gas transfer rate across an air–water interface

We present experimental results of a study on oxygen transfer rates in a water channel facility with varying turbulence inflow conditions set by an active grid. We compare the change in gas transfer rate with different turbulence characteristics of the flow set by four different water channel and grid configurations. It was found that the change in gas transfer rate correlates best with the turbulence intensity in the vertical direction. The most turbulent cases increased the gas transfer rate by 30% compared to the low turbulence reference case. Between the two most turbulent cases studied here, the streamwise turbulence and largest length scales in the flow change, while the gas transfer rate is relatively unchanged. In contrast, for the two less turbulent cases where the magnitude of the fluctuations normal to the free surface are also smaller, the gas transfer rate is significantly reduced. Since the air–water interface plays an important role in the gas transfer process, special attention is given to the free-surface deformations. Despite taking measures to minimise it, the active grid also leaves a direct imprint on the free surface, and the majority of the waves on the surface originate from the grid itself. Surface deformations were, however, ruled out as a main driver for the increase in gas transfer because the increase in surface area is < 0.25%, which is two orders of magnitude smaller than the measured change in the gas transfer rate.

Study of oxygen transport in glassy polymers on a nanometer length scale utilizing the kinetic Monte Carlo simulations.

Diffusion-controlled deactivation of excited phenanthrene and oxidation of triplet aryl-nitrene by molecular oxygen were used to determine the energetics of oxygen jump rates in the set of glassy polymers: poly(methyl methacrylate), poly(n-butyl methacrylate), polycarbonate, polystyrene, and polysulfone. To interpret experimental results, a simple model based on the transition state theory of diffusion jump has been used. The kinetic Monte Carlo simulations of phenanthrene deactivation and nitrene oxidation were carried out in a cubic lattice that modeled a polymer matrix. The bonds of the lattice were assigned to be activation barriers for the diffusion jumps of oxygen molecules from one site of the lattice to another. The standard deviation, σ‡, and spatial correlation length, rc, of the free energy of diffusion jump have been determined. It is shown that the spatial correlation of oxygen jump rates on a nanometer scale and the entropic nature of the dynamic heterogeneity are common features of all the studied polymers.

Engineered Two-Dimensional Transition Metal Dichalcogenides for Energy Conversion and Storage.

Designing efficient and cost-effective materials is pivotal to solving the key scientific and technological challenges at the interface of energy, environment, and sustainability for achieving NetZero. Two-dimensional transition metal dichalcogenides (2D TMDs) represent a unique class of materials that have catered to a myriad of energy conversion and storage (ECS) applications. Their uniqueness arises from their ultra-thin nature, high fractions of atoms residing on surfaces, rich chemical compositions featuring diverse metals and chalcogens, and remarkable tunability across multiple length scales. Specifically, the rich electronic/electrical, optical, and thermal properties of 2D TMDs have been widely exploited for electrochemical energy conversion (e.g., electrocatalytic water splitting), and storage (e.g., anodes in alkali ion batteries and supercapacitors), photocatalysis, photovoltaic devices, and thermoelectric applications. Furthermore, their properties and performances can be greatly boosted by judicious structural and chemical tuning through phase, size, composition, defect, dopant, topological, and heterostructure engineering. The challenge, however, is to design and control such engineering levers, optimally and specifically, to maximize performance outcomes for targeted applications. In this review we discuss, highlight, and provide insights on the significant advancements and ongoing research directions in the design and engineering approaches of 2D TMDs for improving their performance and potential in ECS applications.

Formation of linear arrays of holes in self-assembled collagen films

Collagen is one of the main constituents of mammalian extracellular matrix and is used extensively as a coating for tissue culture dishes and medical implants to promote cell growth and proliferation. By modulating the topography of the collagen coating at the nanometer to micrometer length scales, it is possible to achieve spatial control over cell growth and morphology. In this work, we are exploring the self-assembly of a thin collagen film on a glass substrate as a way to create new nanoscale surface features. By controlling the collagen concentration and adding an oscillatory flow, we are able to enrich the collagen film surface with a localized pattern of ripples oriented perpendicular to the flow direction. We propose that these ripples are the result of dewetting of the collagen film that leads to the formation of adjacent holes. We observe that individual holes form with an anisotropic rim due to the microstructure of the deposited collagen fibril network. This intrinsic anisotropy and the oscillatory flow yield new holes being formed in the film next to existing rims. As holes keep growing deeper, the rims extend along the flow direction, and the holes appear rectangular in shape, which gives the linear array of holes the apparent morphology of a ripple. Overall, we are able to create localized ripples at the surface of collagen films that would be difficult to produce via standard nanofabrication techniques.

The Stress State in an Elastic Disk Due to a Temperature Variation in One Sector

Abstract Consider a linear elastic infinite disk, a sector of which, of arbitrary opening angle 2β, is subjected to a uniform temperature increase ΔT with respect to the complementary portion. An analytical solution is sought, imagining that the disk is first cut along the interface with the heated sector, now free to expand; then the two parts are re-joined and the thermal mismatch is annihilated by arrays of glide dislocations, distributed along the interfaces. A sequence of approximate solutions is found as the length of the arrays of reconciling dislocations is increased, characterized by a logarithmic stress singularity at the sector tip. However, modulo the particular case 2β=π, the stress grows unboundedly when the length of the dislocation arrays tends to infinity. This is in agreement with the predictions from dimensional analysis, because for the infinite disk problem there is no internal length scale. If the disk is finite in size, its radius R represents an additional length scale enriching the class of solutions, but the analytical treatment results much more complicated. Therefore, we propose to correlate the solution of this problem with that of an infinite disk for which the length of the arrays of reconciling dislocations is finite and depends upon R. An excellent agreement with numerical experiments in abaqus is thus found. An approach of this type can be useful in many engineering problems for which the limit condition of infinite body, though leading to analytic simplifications, could imply spurious results.

Pushing the limits of accessible length scales via a modified Porod analysis in small-angle neutron scattering on ordered systems.

Small-angle neutron scattering is a widely used technique to study large-scale structures in bulk samples. The largest accessible length scale in conventional Bragg scattering is determined by the combination of the longest available neutron wavelength and smallest resolvable scattering angle. A method is presented that circumvents this limitation and is able to extract larger length scales from the low-q power-law scattering using a modification of the well known Porod law connecting the scattered intensity of randomly distributed objects to their specific surface area. It is shown that in the special case of a highly aligned domain structure the specific surface area extracted from the modified Porod law can be used to determine specific length scales of the domain structure. The analysis method is applied to study the micrometre-sized domain structure found in the intermediate mixed state of the superconductor niobium. The analysis approach allows the range of accessible length scales to be extended from 1 µm to up to 40 µm using a conventional small-angle neutron scattering setup.

Measurement of Anisotropies in Supernova Remnant Observations and Their Interpretation Using Numerical Models

Supernova remnants (SNRs) exhibit varying degrees of anisotropy, which have been extensively modeled using numerical methods. We implement a technique to measure anisotropies in SNRs by calculating power spectra from their high-resolution images. To test this technique, we develop 3D hydrodynamical models of SNRs and generate synthetic X-ray images from them. Power spectra extracted from both the 3D models and the synthetic images exhibit the same dominant angular scale, which separates large-scale features from small-scale features due to hydrodynamic instabilities. The angular power spectrum at small length scales during relatively early times is too steep to be consistent with Kolmogorov turbulence, but it transitions to Kolmogorov turbulence at late times. As an example of how this technique can be applied to observations, we extract a power spectrum from a Chandra observation of Tycho’s SNR and compare with our models. Our predicted power spectrum picks out the angular scale of Tycho’s fleecelike structures and also agrees with the small-scale power seen in Tycho. We use this to extract an estimate for the density of the circumstellar gas (n ∼ 0.28 cm−3), consistent with previous measurements of this density by other means. The power spectrum also provides an estimate of the density profile of the outermost ejecta. Moreover, we observe additional power at large scales, which may provide important clues about the explosion mechanism itself.

Spider Silk: Rapid, Bottom‐Up Self‐Assembly of MaSp1 into Hierarchically Structured Fibers Through Biomimetic Processing

AbstractSpider dragline silk's exceptional mechanical performance, coupled with its benign production pathway, have inspired the design of diverse smart materials. Remarkably, relatively little is known about the self‐assembly process of major ampullate spidroin 1 (MaSp1) – the main protein constituent of dragline fiber – during its rapid conversion from soluble precursor protein into hierarchically structured mature silk fibers. Herein, the biomimetic potential of MaSp1 is explored using a new recombinant platform with full domain representation. MaSp1 is found to undergo efficient liquid‐liquid phase separation (LLPS) in response to kosmotropic ions, with notably higher propensity compared to MaSp2, and with MaSp1 exhibiting a more complex solubility profile relative to levels of sodium chloride. To further the understanding of silk spinning, the rapid assembly of mesoscale structures is monitored in real‐time in response to ion and pH gradients, revealing a progression from LLPS droplets toward aligned hierarchical fibers. Furthermore, using this biomimetic system, insoluble macroscopic MaSp1 fibers can be readily generated, wherein the application of mechanical deformation triggers the emergence of β‐sheet secondary structures. The insights gained from this study can have broader application in efforts to mimic the formation of biomaterials with spatially organized features across multiple length scales.

Simulating heavy neutral leptons with general couplings at collider and fixed target experiments

Heavy neutral leptons (HNLs) are motivated by attempts to explain neutrino masses and dark matter. If their masses are in the MeV to several GeV range, HNLs are light enough to be copiously produced at collider and accelerator facilities, but also heavy enough to decay to visible particles on length scales that can be observed in particle detectors. Previous studies evaluating the sensitivities of experiments have often focused on simple but not particularly well-motivated models in which the HNL mixes with only one active neutrino flavor. In this work, we accurately simulate models for HNL masses between 100 MeV and 10 GeV and arbitrary couplings to e, μ, and τ leptons. We include over 150 HNL production channels and over 100 HNL decay modes, including all of the processes that can be dominant in some region of the general parameter space. The result is , a user-friendly, fast, and flexible library to compute the properties of HNL models. As examples, we implement to extend the package to evaluate the prospects for HNL discovery at forward LHC experiments. We present sensitivity reaches for FASER and FASER2 in five benchmark scenarios with coupling ratios |Ue|2∶|Uμ|2∶|Uτ|2=1∶0∶0, 0∶1∶0, 0∶0∶1, 0∶1∶1, and 1∶1∶1, where the latter two have not been studied previously. Comparing these to current constraints, we identify regions of parameter space with significant discovery prospects. Published by the American Physical Society 2024

Role of intra-lamellar collagen and hyaluronan nanostructures in annulus fibrosus on lumbar spine biomechanics: insights from molecular mechanics-finite element-based multiscale analyses.

Annulus fibrosus' (AF) ability to transmit multi-directional spinal motion is contributed by a combination of chemical interactions among biomolecular constituents-collagen type I (COL-I), collagen type II (COL-II), and proteoglycans (aggrecan and hyaluronan)-and mechanical interactions at multiple length scales. However, the mechanistic role of such interactions on spinal motion is unclear. The present work employs a molecular mechanics-finite element (FE) multiscale approach to investigate the mechanistic role of molecular-scale collagen and hyaluronan nanostructures in AF, on spinal motion. For this, an FE model of the lumbar segment is developed wherein a multiscale model of AF collagen fiber, developed from COL-I, COL-II, and hyaluronan using the molecular dynamics-cohesive finite element multiscale method, is incorporated. Analyses show AF collagen fibers primarily contribute to axial rotation (AR) motion, owing to angle-ply orientation. Maximum fiber strain values of 2.45% in AR, observed at the outer annulus, are 25% lower than the reported values. This indicates native collagen fibers are softer, attributed to the softer non-fibrillar matrix and higher interfibrillar sliding. Additionally, elastic zone stiffness of 8.61 Nm/° is observed to be 20% higher than the reported range, suggesting native AF lamellae exhibit lower stiffness, resulting from inter-collagen fiber bundle sliding. The presented study has further implications towards the hierarchy-driven designing of AF-substitute materials.

Form factors, spectral and Källén-Lehmann representation in nonlocal quantum gravity

We discuss the conical region of convergence of exponential and asymptotically polynomial form factors and their integral representations. Then, we calculate the spectral representation of the propagator of nonlocal theories with entire form factors, in particular, of the above type. The spectral density is positive-definite and exhibits the same spectrum as the local theory. We also find that the piece of the propagator corresponding to the time-ordered two-point correlation function admits a generalization of the Källén-Lehmann representation with a standard momentum dependence and a spectral density differing from the local one only in the presence of interactions. These results are in agreement with what already known about the free theory after a field redefinition and about perturbative unitarity of the interacting theory. The spectral and Källén-Lehmann representations have the same standard local limit, which is recovered smoothly when sending the fundamental length scale ℓ* in the form factor to zero.

Josephson effect in a fractal geometry

The Josephson effect is a hallmark signature of the superconducting state, which, however, has been sparsely explored in non-crystalline superconducting materials. Motivated by this, we consider a Josephson junction consisting of two superconductors with a fractal metallic interlayer, which is patterned as a Sierpiński carpet by removing atomic sites in a self-similar and scale-invariant manner. We here show that the fractal geometry has direct observable consequences on the Josephson effect. In particular, we demonstrate that the form of the supercurrent–magnetic field relation as the fractal generation number increases can be directly related to the self-similar fractal geometry of the normal metallic layer. Furthermore, the maxima of the corresponding diffraction pattern directly encode the self-repeating fractal structure in the course of fractal generation, implying that the corresponding magnetic length directly probes the shortest length scale in the given fractal generation. Our results should motivate future experimental efforts to verify these predictions in designer quantum materials and motivate future pursuits regarding fractal-based SQUID devices.

On the Applications of a New Advanced PEPFG Mathematical Model for HTM Dynamic Behavior of SDF Sandwich Plates

Considering the crucial role of the flexoelectricity phenomena (the electrical polarization–strain gradient coupling) in the mechanical behavior of different structures on the micro/nanoscale, this paper is derives the motion equations of a size-dependent flexoelectric (SDF) sandwich plate to study its hygro-thermo-mechanical (HTM) dynamic behavior. The model is a three-layer microplate including a porous exponential and power–law functionally graded (PEPFG) mid-layer, and two flexoelectric face sheets. The whole structure is under hygrothermal loading and the Vlasov foundation serves as the stand for the structure. Then, Hamilton’s principle and modified couple stress theory (MCST) are implemented to derive the motion equations. The new PEPFG utilization besides evaluating the impact of the length scale parameter, hygrothermal loading, materials composition, porosity, foundation parameter, and boundary conditions on the normalized natural frequency (NNF) of such an SDF sandwich model is the novelty of this paper. It is revealed that the lateral ratio enhancement causes NNF and stiffness reduction in the model. Furthermore, among all considered boundary types, simply supported and clamped refer to the lowest and the highest NNFs, respectively. This paper serves as a good source to provide a better understanding of the dynamic response of high stiffness-to-weight ratio structures to different variable variations.

Mapping the Multiscale Proteomic Organization of Cellular and Disease Phenotypes.

While the primary sequences of human proteins have been cataloged for over a decade, determining how these are organized into a dynamic collection of multiprotein assemblies, with structures and functions spanning biological scales, is an ongoing venture. Systematic and data-driven analyses of these higher-order structures are emerging, facilitating the discovery and understanding of cellular phenotypes. At present, knowledge of protein localization and function has been primarily derived from manual annotation and curation in resources such as the Gene Ontology, which are biased toward richly annotated genes in the literature. Here, we envision a future powered by data-driven mapping of protein assemblies. These maps can capture and decode cellular functions through the integration of protein expression, localization, and interaction data across length scales and timescales. In this review, we focus on progress toward constructing integrated cell maps that accelerate the life sciences and translational research.

Exploring structural and dynamic characteristics of supercooled liquid silver under varying hydrostatic pressures: A molecular dynamics investigation

This study employs molecular dynamics simulations using the embedded-atom method to investigate the structural and dynamic properties of supercooled liquid silver (Ag) metal under varying external hydrostatic pressures ranging from 0 to 70 GPa. The investigation spans various length scales, analyzing short-to-medium-range order, crystalline order, and fractal dimension to discern patterns that indicate how increased pressure affects atomic arrangements. The results suggest that increased external hydrostatic pressure triggers a shift to more ordered atomic structures characterized by relative atomic positions corresponding to the fcc lattice structure, highlighting the system's heightened sensitivity to pressure conditions. Furthermore, the study reveals pressure-dependent changes in atomic diffusion behavior and shows a reduction in atomic mobility with increasing pressure. In particular, the values of the diffusion coefficient decrease from 3.719 × 10−8 to 1.564 × 10−9 cm2 s−1 for 0 and 70 GPa, respectively, demonstrating the direct influence of pressure on the dynamics of supercooled liquid Ag metal.

A Gaussian process embedded feature selection method based on automatic relevance determination

In Gaussian Process, feature importance is inversely proportional to the corresponding length scale when applying the Automatic Relevance Determination (ARD) structured kernel function. Features can be selected by ranking them according to their importance. Among the ARD-based feature selection methods, no uniform score exists for quantifying the output variation explained by feature subsets. This study proposes two feature selection approaches using two cumulative feature importance scores, one titled derivative decomposition ratio and the other normalized sensitivity, to determine the optimal feature subset. The performance of the approaches is assessed to test if irrelevant features are accurately identified and if the feature rankings are correct. The approaches are applied to identify relevant dimensionless inputs for a hybrid model estimating liquid entrainment fraction in two-phase flow. The results reveal that the proposed methods can identify the optimal feature subset for the hybrid model without significantly worsening its Root Mean Squared Error.

Synthesizing Lipid Nanoparticles by Turbulent Flow in Confined Impinging Jet Mixers.

Lipid nanoparticles (LNPs) have demonstrated their enormous potential as therapeutic delivery vehicles, as evidenced by the approval and global usage of two COVID-19 messenger RNA (mRNA) vaccines. On a small scale, LNPs are often made using microfluidics; however, the limitations of these devices preclude their use on a large scale. The COVID-19 vaccines are manufactured in large quantities using confined impinging jet (CIJ) turbulent mixers. CIJ technology enables production at a laboratory scale with the confidence that it can be scaled to production volumes. The key concepts in CIJ mixing are that the mixing length and time scale are determined by the turbulence intensity in the mixing cavity and that the nanoparticle formation occurs away from walls, eliminating the problem of deposition on surfaces and fouling. This work demonstrates the process of making LNPs using confined impinging jet mixer technology with two geometries: the two-jet CIJ and the four-jet multi-inlet vortex mixer (MIVM). The advantages and disadvantages of each mixing geometry are discussed. In these geometries, LNPs are formed by rapid mixing of an organic solvent stream (usually ethanol containing the ionizable lipids, co-lipids, and stabilizing PEG-lipids) with an aqueous anti-solvent stream (aqueous buffer containing RNA or DNA). The operating parameters for the CIJ and MIVM mixers are presented to prepare reproducible LNPs with controlled size, zeta potential, stability, and transfection effectiveness. The differences between LNPs made with poor mixing (pipetting solutions) compared to CIJ mixing are also presented.