Multiple Length Scales Research Articles

Overcoming strength-ductility tradeoff with high pressure thermal treatment

Conventional material processing approaches often achieve strengthening of materials at the cost of reduced ductility. Here, we show that high-pressure and high-temperature (HPHT) treatment can help overcome the strength-ductility trade-off in structural materials. We report an initially strong-yet-brittle eutectic high entropy alloy simultaneously doubling its strength to 1150 MPa and its tensile ductility to 36% after the HPHT treatment. Such strength-ductility synergy is attributed to the HPHT-induced formation of a hierarchically patterned microstructure with coherent interfaces, which promotes multiple deformation mechanisms, including dislocations, stacking faults, microbands and deformation twins, at multiple length scales. More importantly, the HPHT-induced microstructure helps relieve stress concentration at the interfaces, thereby arresting interfacial cracking commonly observed in traditional eutectic high entropy alloys. These findings suggest a new direction of research in employing HPHT techniques to help develop next generation structural materials.

Photoresponsive Biomimetic Functions by Light-Driven Molecular Motors in Three Dimensionally Printed Liquid Crystal Elastomers.

Despite the fascinating developments in design and synthesis of artificial molecular machines operating at the nanoscales, translating molecular motion along multiple length scales and inducing mechanical motion of a three-dimensional macroscopic entity remains an important challenge. The key to addressing this amplification of motion relies on the effective organization of molecular machines in a well-defined environment. By taking advantage of long-range orientational order and hierarchical structures of liquid crystals and unidirectional rotation of light-driven molecular motors, we report here photoresponsive biomimetic functions of liquid crystal elastomers (LCEs) by the repetitive unidirectional rotation of molecular motors using 3D printing. Molecular motors were built in the main chain of liquid crystals oligomers to serve as photoactuators. The oligomers were then used as the ink, and liquid crystal elastomers with different morphologies were printed. The obtained LCEs are able to conduct multiple types of motions including bending, helical coiling, closing of petals, and flipping of wings of a butterfly upon UV illumination, which paves the way for future design of responsive materials with enhanced complex actuating functions.

Erratum: State-of-the-art multimodal scanning hard X-ray imaging and tomography sheds light at multiple length-scales on biomineralization related processes

Erratum: State-of-the-art multimodal scanning hard X-ray imaging and tomography sheds light at multiple length-scales on biomineralization related processes

Tunable Macroscopic Alignment of Self-Assembling Peptide Nanofibers.

Progress in the design and synthesis of nanostructured self-assembling systems has facilitated the realization of numerous nanoscale geometries, including fibers, ribbons, and sheets. A key challenge has been achieving control across multiple length scales and creating macroscopic structures with nanoscale organization. Here, we present a facile extrusion-based fabrication method to produce anisotropic, nanofibrous hydrogels using self-assembling peptides. The application of shear force coinciding with ion-triggered gelation is used to kinetically trap supramolecular nanofibers into aligned, hierarchical macrostructures. Further, we demonstrate the ability to tune the nanostructure of macroscopic hydrogels through modulating phosphate buffer concentration during peptide self-assembly. In addition, increases in the nanostructural anisotropy of fabricated hydrogels are found to enhance their strength and stiffness under hydrated conditions. To demonstrate their utility as an extracellular matrix-mimetic biomaterial, aligned nanofibrous hydrogels are used to guide directional spreading of multiple cell types, but strikingly, increased matrix alignment is not always correlated with increased cellular alignment. Nanoscale observations reveal differences in cell-matrix interactions between variably aligned scaffolds and implicate the need for mechanical coupling for cells to understand nanofibrous alignment cues. In total, innovations in the supramolecular engineering of self-assembling peptides allow us to decouple nanostructure from macrostructure and generate a gradient of anisotropic nanofibrous hydrogels. We anticipate that control of architecture at multiple length scales will be critical for a variety of applications, including the bottom-up tissue engineering explored here.

Intrinsic conformal order revealed in geometrically confined long-range repulsive particles

Abstract Elucidating long-range interaction guided organization of matter is a fundamental question in physical systems covering multiple length scales. Here, based on the hexagonal disk model, we analyze the characteristic inhomogeneity created by long-range repulsions, and reveal the intrinsic conformal order in particle packings in equilibrium. Specifically, we highlight the delicate angle-preserved bending of the lattice to match the inhomogeneity condition. The revealed conformal order is found to be protected by the surrounding topological defects. These results advance our understanding on long-range interacting systems, and open the promising possibilities of using long-range forces to create particle packings not accessible by short-range forces, which may have practical consequences.

Predicting yield stress in a nano-precipitate strengthened austenitic steel by integrating multi length-scale simulations and experiments

A promising high-strength Fe – 17.7Mn – 4.7Cr – 0.48C – 10Ni – 5Al – 4Cu wt.% Austenitic steel was solutionized, then aged for 3 or 10 h at 580 °C producing a pronounced precipitation hardening response primarily due to the formation of nanoscale NiAl precipitates. Density functional theory (DFT), molecular dynamics (MD), and discrete dislocation dynamics (DDD) calculations were combined with microstructural data from atom-probe tomography (APT), informing theoretical strengthening models to predict yield strength at different stages of precipitation as a function of NiAl size, volume fraction, and composition. These yield strength predictions were compared with experimental microhardness measurements of the various ageing conditions, including the peak microhardness of 490 HV, which corresponds to an estimated alloy yield strength of 1200 MPa. Comparing MD calculations with theoretical models showed that anti-phase boundary (APB) formation was the predominant barrier to dislocation motion posed by the NiAl precipitates. Using single dislocation particle strengthening models with NiAl APB energies calculated from DFT, good agreement was observed between DDD calculations and the 10 h peak-aged experimental measurements, while agreement with the 3 h experimental measurements required reducing the NiAl APB energy. These results demonstrate the utility of the undertaken approach integrating simulations and experiments across multiple length-scales, particularly the presented coarse-grained DDD simulation method towards modeling materials strengthened by very fine precipitates. The results further suggest that the observed NiAl precipitates may adopt an alternate crystal structure early in their formation.

Multiscale characterisation study on the effect of heat treatment on the microstructure of additively manufactured 316L stainless steel

Additively manufactured 316L components are known to exhibit complex three-dimensional microstructures on multiple length-scales. The effect of heat treatment on the stability of grains and dislocation cell structures within the microstructure has previously been investigated but there are appreciable disagreements surrounding the nature of the texture that is present in the specimens, and there is also limited published work on the compositional homogeneity of specimens, particularly on the atomic scale, after heat treatments. In this study, we investigate the effect of applying two different heat treatments to 316L components produced by laser powder bed fusion before characterising them using a combination of electron microscopy and atom probe tomography. The importance of using multiple characterisation techniques, which span from the nanometre to micrometre scale, in addition to carefully and accurately describing analysis methods when investigating the evolution of the microstructure of additively manufactured 316L steels is demonstrated. Our EBSD (Electron Back Scatter Diffraction) results show the presence of a strong texture in the build direction of the samples, and a reduction in morphological texture as a result of heat treatment. TEM (Transmission Electron Microscopy) results indicate a dissolution of the dislocation cell structure that forms during solidification. Atom probe tomography was used to investigate compositional homogeneity in the samples and indicated that there are regions enriched in Cr, Mn, Mo, and Ni in the As-Printed samples that are likely associated with the dislocation cell walls. The atom probe results also reveal the presence of impurities, such as Co, which were not detected in the feedstock powder.

Glioblastoma mechanobiology at multiple length scales

Glioblastoma multiforme (GBM), a primary brain cancer, is one of the most aggressive forms of human cancer, with a very low patient survival rate. A characteristic feature of GBM is the diffuse infiltration of tumor cells into the surrounding brain extracellular matrix (ECM) that provide biophysical, topographical, and biochemical cues. In particular, ECM stiffness and composition is known to play a key role in controlling various GBM cell behaviors including proliferation, migration, invasion, as well as the stem-like state and response to chemotherapies. In this review, we discuss the mechanical characteristics of the GBM microenvironment at multiple length scales, and how biomaterial scaffolds such as polymeric hydrogels, and fibers, as well as microfluidic chip-based platforms have been employed as tissue mimetic models to study GBM mechanobiology. We also highlight how such tissue mimetic models can impact the field of GBM mechanobiology.

Atherosclerotic Calcifications Have a Local Effect on the Peel Behavior of Human Aortic Media.

Aortic dissections, characterized by the propagation of a tear through the layers of the vessel wall, are critical, life-threatening events. Aortic calcifications are a common comorbidity in both acute and chronic dissections, yet their impact on dissection mechanics remains unclear. Using micro-computed tomography (CT) imaging, peel testing, and finite element modeling, this study examines the interplay between atherosclerotic calcifications and dissection mechanics. Samples cut from cadaveric human thoracic aortas were micro-CT imaged and subsequently peel-tested to map peel tension curves to the location of aortic calcifications. Empirical mode decomposition separated peel tension curves into high and low-frequency components, with high-frequency effects corresponding to interlamellar bonding mechanics and low-frequency effects to peel tension fluctuations. Finally, we used an idealized finite element model to examine how stiff calcifications affect aortic failure mechanics. Results showed that atherosclerosis influences dissection behavior on multiple length scales. Experimentally, atherosclerotic samples exhibited higher peel tensions and greater variance in the axial direction. The variation was driven by increased amplitudes of low-frequency tension fluctuations in diseased samples, indicating that more catastrophic propagations occur near calcifications. The simulations corroborated this finding, suggesting that the low-frequency changes resulted from the presence of a stiff calcification in the vessel wall. There were also modifications to the high-frequency peel mechanics, a response likely attributable to alterations in the microstructure and interlamellar bonding within the media. Considered collectively, these findings demonstrate that dissection mechanics are modified in aortic media nearby and adjacent to aortic calcifications.

Living Cell as a Self-Synchronized Chemical Reactor.

Thermal fluctuations power all processes inside living cells. Therefore, these processes are inherently random. However, myriad multistep chemical reactions act in concerto inside a cell, finally leading to this chemical reactor's self-replication. We speculate that an underlying mechanism in nature must exist that allows all of these reactions to synchronize at multiple time and length scales, overcoming in this way the random nature of any single process in a cell. This Perspective discusses what type of research is needed to understand this undiscovered synchronization law.

Synergy in bio-inspired hybrid composites with hierarchically structured fibrous reinforcements

In response to the global energy crisis, high-performance transportation sectors are rapidly embracing lightweight materials to enhance energy efficiency and sustainability, while grappling with the persistent challenges of developing structural materials that meet stringent safety standards with robust mechanical performance and ease of scalability. Thus, this work presents a combined experimental and theoretical framework to develop a profound understanding of the synergistic effect in hybrid composites with bio-inspired fibrous reinforcements, by elucidating the interfacial interactions across multiple length-scales, encompassing atomic covalent bonding to micro-morphology. A model hybrid composite system, containing a self-assembled fibrous reinforcement consisting of nano-sized Graphene Nanoplatelets (GnP) covalently bonded onto chemically-modified micro-sized Glass Fibers (GF), was utilized to showcase the synergistic effect and highlight its associated mechanisms. The interfacial interactions of the reinforcement were optimized by obtaining the maximum density of covalent bonds, which was achieved with 0.5 wt% GnP for the hybrid composites containing 10 wt% GF, increasing the work of adhesion by 33 %, compared to the biphasic GF composites. The composite’s morphology contains minimal agglomeration with ∼68 % of GnPs oriented with the melt flow, supressing high-stress concentration areas, while the formed crystalline microstructure, with ∼18 % β-crystals, allows the matrix to absorb substantial energy. Furthermore, the increased trans-crystallization encapsulating the hierarchical reinforcement induced nanoscale stiffness variations, increasing rigidity, and forming an ∼16 µm gradient interphase that facilitates load transfer. The greatest synergistic effect observed was ∼54 %, ∼37 %, and ∼75 % for the tensile modulus, tensile strength, and impact strength, respectively. Additionally, a theoretical framework accounting for the synergistic effect was formulated, using a two-step core/shell homogenization model, which shows great potential in expediting the design and optimization of innovative hybrid composite materials.

Rok from B. subtilis: Bridging genome structure and transcription regulation.

Bacterial genomes are folded and organized into compact yet dynamic structures, called nucleoids. Nucleoid orchestration involves many factors at multiple length scales, such as nucleoid-associated proteins and liquid-liquid phase separation, and has to be compatible with replication and transcription. Possibly, genome organization plays an intrinsic role in transcription regulation, in addition to classical transcription factors. In this review, we provide arguments supporting this view using the Gram-positive bacterium Bacillus subtilis as a model. Proteins BsSMC, HBsu and Rok all impact the structure of the B. subtilis chromosome. Particularly for Rok, there is compelling evidence that it combines its structural function with a role as global gene regulator. Many studies describe either function of Rok, but rarely both are addressed at the same time. Here, we review both sides of the coin and integrate them into one model. Rok forms unusually stable DNA-DNA bridges and this ability likely underlies its repressive effect on transcription by either preventing RNA polymerase from binding to DNA or trapping it inside DNA loops. Partner proteins are needed to change or relieve Rok-mediated gene repression. Lastly, we investigate which features characterize H-NS-like proteins, a family that, at present, lacks a clear definition.

A multi-scale modeling of Ca-based material for solar-driven calcium-looping energy storage process: From calcination reactor to energy carrier

The calcium looping (CaL) for thermochemical energy storage possesses a great potential to promote solar thermal utilization. However, the performance of CaL, especially for the Ca-based energy carrier, cannot satisfy the expectations of industrial application, requiring enhancement between multiple length scales. Hence, a model for solar-driven CaL energy storage process, coupled by three-dimensional reactor, two-dimensional light field and one-dimensional particle models, is proposed to study the multiprocess behavior on particle flow, photothermal conversion, calcination reaction, heat-mass transfer and stress response. It is found that moving-bed reactor contributes to achieving continuous calcination and reducing particle waste, while the rapid bouncing particles inhibit the performance of single particle, with up to 45.7 % reduction in conversion. Additionally, energy carrier with stable and continuous flow normally yields high energy storage efficiency and cycle stability when the conversion of outlet particle is closed to 1 and thermal stress is less than 50 MPa.

Data-driven simulations for training AI-based segmentation of neutron images

Neutron interferometry uniquely combines neutron imaging and scattering methods to enable characterization of multiple length scales from 1 nm to 10 µm. However, building, operating, and using such neutron imaging instruments poses constraints on the acquisition time and on the number of measured images per sample. Experiment time-constraints yield small quantities of measured images that are insufficient for automating image analyses using supervised artificial intelligence (AI) models. One approach alleviates this problem by supplementing annotated measured images with synthetic images. To this end, we create a data-driven simulation framework that supplements training data beyond typical data-driven augmentations by leveraging statistical intensity models, such as the Johnson family of probability density functions (PDFs). We follow the simulation framework steps for an image segmentation task including Estimate PDFs →\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\,\\rightarrow \\,$$\\end{document} Validate PDFs →\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\,\\rightarrow \\,$$\\end{document} Design Image Masks →\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\,\\rightarrow \\,$$\\end{document} Generate Intensities →\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\,\\rightarrow \\,$$\\end{document} Train AI Model for Segmentation. Our goal is to minimize the manual labor needed to execute the steps and maximize our confidence in simulations and segmentation accuracy. We report results for a set of nine known materials (calibration phantoms) that were imaged using a neutron interferometer acquiring four-dimensional images and segmented by AI models trained with synthetic and measured images and their masks.

Morphological entropy encodes cellular migration strategies on multiple length scales

Cell migration is crucial for numerous physiological and pathological processes. A cell adapts its morphology, including the overall and nuclear morphology, in response to various cues in complex microenvironments, such as topotaxis and chemotaxis during migration. Thus, the dynamics of cellular morphology can encode migration strategies, from which diverse migration mechanisms can be inferred. However, deciphering the mechanisms behind cell migration encoded in morphology dynamics remains a challenging problem. Here, we present a powerful universal metric, the Cell Morphological Entropy (CME), developed by combining parametric morphological analysis with Shannon entropy. The utility of CME, which accurately quantifies the complex cellular morphology at multiple length scales through the deviation from a perfectly circular shape, is illustrated using a variety of normal and tumor cell lines in different in vitro microenvironments. Our results show how geometric constraints affect the MDA-MB-231 cell nucleus, the emerging interactions of MCF-10A cells migrating on collagen gel, and the critical transition from proliferation to invasion in tumor spheroids. The analysis demonstrates that the CME-based approach provides an effective and physically interpretable tool to measure morphology in real-time across multiple length scales. It provides deeper insight into cell migration and contributes to the understanding of different behavioral modes and collective cell motility in more complex microenvironments.

Torsional force microscopy of van der Waals moirés and atomic lattices

In a stack of atomically thin van der Waals layers, introducing interlayer twist creates a moiré superlattice whose period is a function of twist angle. Changes in that twist angle of even hundredths of a degree can dramatically transform the system's electronic properties. Setting a precise and uniform twist angle for a stack remains difficult; hence, determining that twist angle and mapping its spatial variation is very important. Techniques have emerged to do this by imaging the moiré, but most of these require sophisticated infrastructure, time-consuming sample preparation beyond stack synthesis, or both. In this work, we show that torsional force microscopy (TFM), a scanning probe technique sensitive to dynamic friction, can reveal surface and shallow subsurface structure of van der Waals stacks on multiple length scales: the moirés formed between bi-layers of graphene and between graphene and hexagonal boron nitride (hBN) and also the atomic crystal lattices of graphene and hBN. In TFM, torsional motion of an Atomic Force Microscope (AFM) cantilever is monitored as it is actively driven at a torsional resonance while a feedback loop maintains contact at a set force with the sample surface. TFM works at room temperature in air, with no need for an electrical bias between the tip and the sample, making it applicable to a wide array of samples. It should enable determination of precise structural information including twist angles and strain in moiré superlattices and crystallographic orientation of van der Waals flakes to support predictable moiré heterostructure fabrication.

Local strain quantification of a porous carbon fiber network material

While porous materials’ wide range of attractive functional properties have led to their development for a variety of applications, their intrinsically stochastic microstructures prevent straightforward approaches to predicting their mechanical behavior. This is attributed to the mechanisms that govern the macroscale behavior of these materials operating on multiple microstructure-specific length scales spanning several orders of magnitude. The goal of this work was to experimentally observe these operative deformation mechanisms to better improve the development of mechanism-informed models that more accurately predict the behavior of these materials. In this study compression tests were conducted on a porous carbon fiber network material. The resulting macroscale mechanical properties and mesoscale deformation behavior were tied together through digital image correlation (DIC) strain mapping. It was shown that deformation accumulation occurred via both reversible (fiber bending and sliding) and irreversible (fiber and junction failure) ways. The presence of irreversible deformation is indicated by strain being retained after unloading, with values of up to 0.426 locally and 0.248 globally. Local and macroscopic recovery of up to 0.306 and 0.207 strain respectively showcase the operation of reversible deformation. Furthermore, the calculation of energy loss coefficients increasing from 0.016 to 0.371 illustrates that the deformation occurs via dissipative mechanisms.

Connecting continuum poroelasticity with discrete synthetic vascular trees for modelling liver tissue

The modelling of liver tissue across multiple length scales constitutes a significant challenge, primarily due to the multiphysics coupling of mechanical response and perfusion within the complex multiscale vascularization of the organ. In this paper, we present a modelling framework that connects continuum poroelasticity and discrete vascular tree structures to model liver tissue across disparate levels of the perfusion hierarchy. The connection is achieved through a series of modelling decisions, which include source terms in the pressure equation to model inflow from the supplying tree, pressure boundary conditions to model outflow into the draining tree, and contact conditions to model surrounding tissue. We investigate the numerical behaviour of our framework and apply it to a patient-specific full-scale liver problem that demonstrates its potential to help assess surgical liver resection procedures.

From Molecular Constraints to Macroscopic Dynamics in Associative Networks Formed by Ionizable Polymers: A Neutron Spin Echo and Molecular Dynamics Simulations Study.

The association of ionizable polymers strongly affects their motion in solutions, where the constraints arising from clustering of the ionizable groups alter the macroscopic dynamics. The interrelation between the motion on multiple length and time scales is fundamental to a broad range of complex fluids including physical networks, gels, and polymer-nanoparticle complexes where long-lived associations control their structure and dynamics. Using neutron spin echo and fully atomistic, multimillion atom molecular dynamics (MD) simulations carried out to times comparable to that of chain segmental motion, the current study resolves the dynamics of networks formed by suflonated polystryene solutions for sulfonation fractions 0 ≤ f ≤ 0.09 across time and length scales. The experimental dynamic structure factors were measured and compared with computational ones, calculated from MD simulations, and analyzed in terms of a sum of two exponential functions, providing two distinctive time scales. These time constants capture confined motion of the network and fast dynamics of the highly solvated segments. A unique relationship between the polymer dynamics and the size and distribution of the ionic clusters was established and correlated with the number of polymer chains that participate in each cluster. The correlation of dynamics in associative complex fluids across time and length scales, enabled by combining the understanding attained from reciprocal space through neutron spin echo and real space, through large scale MD studies, addresses a fundamental long-standing challenge that underline the behavior of soft materials and affect their potential uses.

Deposition voltages on the phase evolutions, microstructures, and oxidation behaviors of thermal-resistance Glass-MoSi2-SiC coating

ABSTRACT Due to the high oxidation activities at high temperatures, traditional SiC coating was difficult to act as an antioxidant material for ages. In this case, the multilayered Glass-MoSi2-SiC coating was fabricated on the C/C substrate, combined with hydrothermal electrophoresis deposition and simple embedding process. It was found that the composite obtained at 10 V performed outstanding combinations of oxidation resistance and thermal shock resistance properties. The weight loss of this Glass-MoSi2-SiC-C/C composite was only 0.99% after 212 h oxidation at 1773 K. After thermal shock for 130 times, the mass was just 0.05% lower than that of the initial. These excellent heat-resistant performances were much better than those in similar reports, which was attributed to the suitable coating composition and dense interlayer structure. As oxidized at 1773 K, the in-situ SiO2 phases had a self-healing ability to fill micropores and microcracks to protect the structure. The structure failure was related to SiO2 volatilization. This study emphasized the importance of simple techniques in the thermal-resistance coating fields at multiple length scales.