Multiple Length Research Articles

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

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 mechanical 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.

A hybrid approach combining OFC and FSO for multichannel connectivity

Abstract This paper presents a novel approach of establishing a multichannel optical communication link, combining optical fiber cable (OFC) and free space optics (FSO) technology. By leveraging multiple lengths of optical fiber and FSO links, along with optical amplifiers to counteract attenuation, our proposed hybrid system incorporates four channels operating within the 1550 nm window. This model is specifically designed to address communication challenges in scenarios such as unplanned urban layouts, multistory buildings, or rugged terrains where traditional optical fiber deployment is impractical. By integrating FSO for the fronthaul and optical fiber for the backhaul, our system enhances transmission capacity, thereby supporting the requirements of next-generation networks and alleviating bottlenecks and connectivity issues at the last or first mile. This innovative approach holds promise for internet service providers, enterprises, and industrial networks operating in demanding environments. Furthermore, it can serve as a vital tool for restoring emergency communication links in the aftermath of disasters such as earthquakes or floods, where traditional wired optical infrastructure may be compromised.

Programmable Enzymatic Reaction Network in Artificial Cell-Like Polymersomes.

The ability to precisely control in vitro enzymatic reactions in synthetic cells plays a crucial role in the bottom-up design of artificial cell models that can recapitulate the key cellular features and functions such as metabolism. However, integration of enzymatic reactions has been limited to bulk or microfluidic emulsions without a membrane, lacking the ability to design more sophisticated higher-order artificial cell communities for reconstituting spatiotemporal biological information at multiple length scales. Herein, droplet microfluidics is utilized to synthesize artificial cell-like polymersomes with distinct molecular permeability for spatiotemporal control of enzymatic reactions driven by external signals and fuels. The presence of a competing reverse enzymatic reaction that depletes the active substrates is shown to enable demonstration of fuel-driven formation of sub-microcompartments within polymersomes as well as realization of out-of-equilibrium systems. In addition, the different permeability characteristics of polymersome membranes are exploited to successfully construct a programmable enzymatic reaction network that mimics cellular communication within a heterogeneous cell community through selective molecular transport.

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.

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.

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.

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.

Dynamic nonreversibility view of intrinsic brain organization and brain dynamic analysis of repetitive transcranial magnitude stimulation.

Intrinsic neural activities are characterized as endless spontaneous fluctuation over multiple time scales. However, how the intrinsic brain organization changes over time under local perturbation remains an open question. By means of statistical physics, we proposed an approach to capture whole-brain dynamics based on estimating time-varying nonreversibility and k-means clustering of dynamic varying nonreversibility patterns. We first used synthetic fMRI to investigate the effects of window parameters on the temporal variability of varying nonreversibility. Second, using real test-retest fMRI data, we examined the reproducibility, reliability, biological, and physiological correlation of the varying nonreversibility substates. Finally, using repetitive transcranial magnetic stimulation-fMRI data, we investigated the modulation effects of repetitive transcranial magnetic stimulation on varying nonreversibility substate dynamics. The results show that: (i) as window length increased, the varying nonreversibility variance decreased, while the sliding step almost did not alter it; (ii) the global high varying nonreversibility states and low varying nonreversibility states were reproducible across multiple datasets and different window lengths; and (iii) there were increased low varying nonreversibility states and decreased high varying nonreversibility states when the left frontal lobe was stimulated, but not the occipital lobe. Taken together, these results provide a thermodynamic equilibrium perspective of intrinsic brain organization and reorganization under local perturbation.

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.

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.

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.

Comparison of the effectiveness of two adjustable negative pressure ureteral access sheaths combined with flex ureteroscopy for ≤ 2cm renal stones.

To compare the safety and effectiveness of the combination of intelligent intrarenal pressure control platforms (IPCP) and flexible ureteral access sheath (FUAS) combined with retrograde intrarenal surgery (RIRS) for the treatment of renal stones less than 2cm. We retrospectively collected 383 patients with renal stones who underwent RIRS in our department from June 2022 to October 2023. Inclusion criteria: stone length or the sum of multiple stone lengths ≤ 2cm. Finally, 99 cases were included and divided into an IPCP group (n = 40) and FUAS group (n = 59) based on surgical methods. The main endpoint was the stone-free rate (SFR) at third months after surgery, with no residual stones or stone fragments less than 2mm defined as stone clearance. The secondary endpoints were surgical time and perioperative complications, including fever, sepsis, septic shock, and perirenal hematoma. There was no statistically significant difference in general information between the two groups, including age, gender, body mass index, comorbidities, stone side, stone location, stone length, urine bacterial culture, and hydronephrosis. The operation time for IPCP group and FUAS group was 56.83 ± 21.33 vs 55.47 ± 19.69min (p = 0.747). The SFR of IPCP group and FUAS group on the first postoperative day was 75.00% vs 91.50% (p = 0.024). The SFR was 90.00% vs 94.90% in the third month (p = 0.349).In IPCP group, there were 11 cases with stones located in the lower renal calyces and 17 cases in FUAS group. The SFR of the two groups on the first day and third months after surgery were 45.50% vs 88.20% (p = 0.014) and 63.60% vs 94.10% (p = 0.040), respectively, with statistical differences. For kidney stones ≤ 2cm, there was no difference in SFR and the incidence of infection-related complications between IPCP and FUAS combined with RIRS, both of which were superior to T-RIRS. For lower renal caliceal stones, FUAS has a higher SFR compared to IPCP.

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.

Response of various carbon sources for in vitro culture establishment and shoot proliferation of banana cv. Chinichampa (AAB) through shoot tip

Bananas are one of the most important tropical fruits in the world market, a significant staple food and a major export commodity. In vitro propagated banana plants are steadily becoming the planting material of choice because of disease free, uniformity and the possibility of rapid multiplication. The present investigation was carried out at the tissue culture laboratory, Department of Horticulture, School of Agricultural Sciences, Nagaland University, Medziphema campus during the year 2019-2022. Data recorded for different parameters viz. days to greening, days required for multiple buds’ initiation, number of multiple buds produced per explant and length of multiple buds after 30 days were subjected to completely randomized design (CRD). The present study revealed the importance of various carbon sources and its role in micropropagation of banana through shoot tip culture. The minimum day to greening, multiple buds initiation and maximum length of multiple buds was observed in shoot proliferation medium supplemented (SPM S) with 30g sucrose. The highest number of multiple buds was recorded in shoot proliferation medium supplemented with 30g table sugar. The results indicate the significance of sucrose as carbon sources in micropropagation of banana. They improved plant regeneration and facilitated rapid multiplication of disease and virus free banana plantlets.

Advances in Small Angle Neutron Scattering on Polysaccharide Materials.

Polysaccharide materials and biomaterials gain the focus of intense research owing to their great versatility in chemical structures and modification possibilities, as well as their biocompatibility, degradability, and sustainability features. This review focuses on the recent advances in the application of SANS on polysaccharide systems covering a broad range of materials such as nanoparticulate assemblies, hydrogels, nanocomposites, and plant-originating nanostructured systems. It motivates the use of SANS in its full potential by demonstrating the features of contrast variation and contrast matching methods and by reporting the methodologies for data analysis and interpretation. As these soft matter systems may be organized in multiple length scales depending on the interactions and chemical bonds between their components, SANS offers exceptional and unique opportunities for advanced characterization and optimization of new nanostructured polysaccharide materials.

Overcoming strength-toughness trade-off in a eutectic high entropy alloy by optimizing chemical and microstructural heterogeneities

The well-known strength-toughness trade-off has long been an obstacle in the pursuit of advanced structural alloys. Here, we develop a eutectic high entropy alloy that effectively overcomes this limitation. Our alloy is composed of face-centered cubic and body-centered cubic crystalline phases, and demonstrates attractive mechanical properties by harnessing microstructural hybridization and a strain-induced phase transition between phases. Unlike conventional eutectic alloys, the compositionally complexity of our alloy allows control of its microstructural and chemical heterogeneities across multiple length scales, ranging from atomic- and nano-scales to meso-scales. Optimizing these microstructural and chemical heterogeneities within our alloy enables high strength and ductility because of enhanced fracture resistance, outperforming alternative high and medium entropy alloys with similar compositions and microstructures.