Dataset Information

Dehomogenized Elastic Properties of Heterogeneous Layered Materials in AFM Indentation Experiments.

ABSTRACT: Atomic force microscopy (AFM) is used to study mechanical properties of biological materials at submicron length scales. However, such samples are often structurally heterogeneous even at the local level, with different regions having distinct mechanical properties. Physical or chemical disruption can isolate individual structural elements but may alter the properties being measured. Therefore, to determine the micromechanical properties of intact heterogeneous multilayered samples indented by AFM, we propose the Hybrid Eshelby Decomposition (HED) analysis, which combines a modified homogenization theory and finite element modeling to extract layer-specific elastic moduli of composite structures from single indentations, utilizing knowledge of the component distribution to achieve solution uniqueness. Using finite element model-simulated indentation of layered samples with micron-scale thickness dimensions, biologically relevant elastic properties for incompressible soft tissues, and layer-specific heterogeneity of an order of magnitude or less, HED analysis recovered the prescribed modulus values typically within 10% error. Experimental validation using bilayer spin-coated polydimethylsiloxane samples also yielded self-consistent layer-specific modulus values whether arranged as stiff layer on soft substrate or soft layer on stiff substrate. We further examined a biophysical application by characterizing layer-specific microelastic properties of full-thickness mouse aortic wall tissue, demonstrating that the HED-extracted modulus of the tunica media was more than fivefold stiffer than the intima and not significantly different from direct indentation of exposed media tissue. Our results show that the elastic properties of surface and subsurface layers of microscale synthetic and biological samples can be simultaneously extracted from the composite material response to AFM indentation. HED analysis offers a robust approach to studying regional micromechanics of heterogeneous multilayered samples without destructively separating individual components before testing.

SUBMITTER: Lee JJ

PROVIDER: S-EPMC6129556 | biostudies-literature | 2018 Jun

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Dehomogenized Elastic Properties of Heterogeneous Layered Materials in AFM Indentation Experiments.

Lee Jia-Jye JJ Rao Satish S Kaushik Gaurav G Azeloglu Evren U EU Costa Kevin D KD

Biophysical journal 20180601 11

Atomic force microscopy (AFM) is used to study mechanical properties of biological materials at submicron length scales. However, such samples are often structurally heterogeneous even at the local level, with different regions having distinct mechanical properties. Physical or chemical disruption can isolate individual structural elements but may alter the properties being measured. Therefore, to determine the micromechanical properties of intact heterogeneous multilayered samples indented by A ...[more]

PMID: 29874620

Similar Datasets

Project description:AbstractThe performance in heterogeneous catalysis is an example of a complex materials function, governed by an intricate interplay of several processes (e.g., the different surface chemical reactions, and the dynamic restructuring of the catalyst material at reaction conditions). Modeling the full catalytic progression via first-principles statistical mechanics is impractical, if not impossible. Instead, we show here how a tailored artificial-intelligence approach can be applied, even to a small number of materials, to model catalysis and determine the key descriptive parameters ("materials genes") reflecting the processes that trigger, facilitate, or hinder catalyst performance. We start from a consistent experimental set of "clean data," containing nine vanadium-based oxidation catalysts. These materials were synthesized, fully characterized, and tested according to standardized protocols. By applying the symbolic-regression SISSO approach, we identify correlations between the few most relevant materials properties and their reactivity. This approach highlights the underlying physicochemical processes, and accelerates catalyst design.Impact statementArtificial intelligence (AI) accepts that there are relationships or correlations that cannot be expressed in terms of a closed mathematical form or an easy-to-do numerical simulation. For the function of materials, for example, catalysis, AI may well capture the behavior better than the theory of the past. However, currently the flexibility of AI comes together with a lack of interpretability, and AI can only predict aspects that were included in the training. The approach proposed and demonstrated in this IMPACT article is interpretable. It combines detailed experimental data (called "clean data") and symbolic regression for the identification of the key descriptive parameters (called "materials genes") that are correlated with the materials function. The approach demonstrated here for the catalytic oxidation of propane will accelerate the discovery of improved or novel materials while also enhancing physical understanding.Supplementary informationThe online version contains supplementary material available at 10.1557/s43577-021-00165-6.

Project description:The DNA packaging motor of the bacteriophage ϕ29, comprising head-tail connector, ATPase, and pRNA, transports the viral DNA inside the procapsid against pressure differences of up to ∼60 atm during replication. Several models for the DNA packaging mechanism have been proposed, which attribute different roles to the connector, and require specific mechanical properties of the connector. To characterize these properties at the atomic level, and to understand how the connector withstands this large pressure, we have carried out molecular dynamics simulations of the whole connector both in equilibrium and under mechanical stress. The simulations revealed a quite heterogeneous distribution of stiff and soft regions, resembling that of typical composite materials that are also optimized to resist mechanical stress. In particular, the conserved middle α-helical region is found to be remarkably stiff, similar only to structural proteins forming viral shell, silk, or collagen. In contrast, large parts of the peripheral interface to the ϕ29 procapsid turned out to be rather soft. Force probe and umbrella sampling simulations showed that large connector deformations are remarkably reversible, and served to calculate the free energies required for these deformations. In particular, for an untwisting deformation by 12°, as postulated by the untwist-twist model, more than four times' larger energy is required than is available from hydrolysis of one ATP molecule. Combined with previous experiments, this result is incompatible with the untwist-twist model. In contrast, our simulations support the recently proposed one-way revolution model and suggest in structural terms how the connector blocks DNA leakage. In particular, conserved loops at the rim of the central channel, which are in direct contact with the DNA, are found to be rather flexible and tightly anchored to the rigid central region. These findings suggest a check-valve mechanism, with the flexible loops obstructing the channel by interacting with the viral DNA.

Dataset Information

Dehomogenized Elastic Properties of Heterogeneous Layered Materials in AFM Indentation Experiments.

Publications

Dehomogenized Elastic Properties of Heterogeneous Layered Materials in AFM Indentation Experiments.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets