Robust Strategies for Automated AFM Force Curve Analysis—I. Non-adhesive Indentation of Soft, Inhomogeneous Materials

2006 ◽  
Vol 129 (3) ◽  
pp. 430-440 ◽  
Author(s):  
David C. Lin ◽  
Emilios K. Dimitriadis ◽  
Ferenc Horkay
Keyword(s):  
Young’S Modulus ◽  
Elastic Properties ◽  
Large Scale ◽  
Young's Modulus ◽  
Soft Materials ◽  
Data Sets ◽  
Inhomogeneous Materials ◽  
Afm Indentation ◽  
Large Scale Analysis ◽  
Engineered Cartilage

The atomic force microscope (AFM) has found wide applicability as a nanoindentation tool to measure local elastic properties of soft materials. An automated approach to the processing of AFM indentation data, namely, the extraction of Young’s modulus, is essential to realizing the high-throughput potential of the instrument as an elasticity probe for typical soft materials that exhibit inhomogeneity at microscopic scales. This paper focuses on Hertzian analysis techniques, which are applicable to linear elastic indentation. We compiled a series of synergistic strategies into an algorithm that overcomes many of the complications that have previously impeded efforts to automate the fitting of contact mechanics models to indentation data. AFM raster data sets containing up to 1024 individual force-displacement curves and macroscopic compression data were obtained from testing polyvinyl alcohol gels of known composition. Local elastic properties of tissue-engineered cartilage were also measured by the AFM. All AFM data sets were processed using customized software based on the algorithm, and the extracted values of Young’s modulus were compared to those obtained by macroscopic testing. Accuracy of the technique was verified by the good agreement between values of Young’s modulus obtained by AFM and by direct compression of the synthetic gels. Validation of robustness was achieved by successfully fitting the vastly different types of force curves generated from the indentation of tissue-engineered cartilage. For AFM indentation data that are amenable to Hertzian analysis, the method presented here minimizes subjectivity in preprocessing and allows for improved consistency and minimized user intervention. Automated, large-scale analysis of indentation data holds tremendous potential in bioengineering applications, such as high-resolution elasticity mapping of natural and artificial tissues.

Robust Strategies for Automated AFM Force Curve Analysis—II: Adhesion-Influenced Indentation of Soft, Elastic Materials

2007 ◽  
Vol 129 (6) ◽  
pp. 904-912 ◽  
Author(s):  
David C. Lin ◽  
Emilios K. Dimitriadis ◽  
Ferenc Horkay
Keyword(s):  
Young’S Modulus ◽  
Young's Modulus ◽  
Full Range ◽  
Soft Materials ◽  
Adhesive Contact ◽  
Colloid Interface ◽  
Inhomogeneous Materials ◽  
Dugdale Model ◽  
Normal Contact ◽  
Adhesive Interactions

In the first of this two-part discourse on the extraction of elastic properties from atomic force microscopy (AFM) data, a scheme for automating the analysis of force-distance curves was introduced and experimentally validated for the Hertzian (i.e., linearly elastic and noninteractive probe-sample pairs) indentation of soft, inhomogeneous materials. In the presence of probe-sample adhesive interactions, which are common especially during retraction of the rigid tip from soft materials, the Hertzian models are no longer adequate. A number of theories (e.g., Johnson–Kendall–Roberts and Derjaguin–Muller–Toporov), covering the full range of sample compliance relative to adhesive force and tip radius, are available for analysis of such data. We incorporated Pietrement and Troyon’s approximation (2000, “General Equations Describing Elastic Indentation Depth and Normal Contact Stiffness Versus Load,” J. Colloid Interface Sci., 226(1), pp. 166–171) of the Maugis–Dugdale model into the automated procedure. The scheme developed for the processing of Hertzian data was extended to allow for adhesive contact by applying the Pietrement–Troyon equation. Retraction force-displacement data from the indentation of polyvinyl alcohol gels were processed using the customized software. Many of the retraction curves exhibited strong adhesive interactions that were absent in extension. We compared the values of Young’s modulus extracted from the retraction data to the values obtained from the extension data and from macroscopic uniaxial compression tests. Application of adhesive contact models and the automated scheme to the retraction curves yielded average values of Young’s modulus close to those obtained with Hertzian models for the extension curves. The Pietrement–Troyon equation provided a good fit to the data as indicated by small values of the mean-square error. The Maugis–Dugdale theory is capable of accurately modeling adhesive contact between a rigid spherical indenter and a soft, elastic sample. Pietrement and Troyon’s empirical equation greatly simplifies the theory and renders it compatible with the general automation strategies that we developed for Hertzian analysis. Our comprehensive algorithm for automated extraction of Young’s moduli from AFM indentation data has been expanded to recognize the presence of either adhesive or Hertzian behavior and apply the appropriate contact model.

scholarly journals A Quasi-Static Quantitative Ultrasound Elastography Algorithm Using Optical Flow

Sensors ◽  
2021 ◽  
Vol 21 (9) ◽  
pp. 3010
Author(s):  
Raphael Lamprecht ◽  
Florian Scheible ◽  
Marion Semmler ◽  
Alexander Sutor
Keyword(s):  
Optical Flow ◽  
Young’S Modulus ◽  
Elastic Properties ◽  
Young's Modulus ◽  
Image Data ◽  
Maximum Error ◽  
Ultrasound Elastography ◽  
Static Compression ◽  
Tissue Properties ◽  
A Performance

Ultrasound elastography is a constantly developing imaging technique which is capable of displaying the elastic properties of tissue. The measured characteristics could help to refine physiological tissue models, but also indicate pathological changes. Therefore, elastography data give valuable insights into tissue properties. This paper presents an algorithm that measures the spatially resolved Young’s modulus of inhomogeneous gelatin phantoms using a CINE sequence of a quasi-static compression and a load cell measuring the compressing force. An optical flow algorithm evaluates the resulting images, the stresses and strains are computed, and, conclusively, the Young’s modulus and the Poisson’s ratio are calculated. The whole algorithm and its results are evaluated by a performance descriptor, which determines the subsequent calculation and gives the user a trustability index of the modulus estimation. The algorithm shows a good match between the mechanically measured modulus and the elastography result—more precisely, the relative error of the Young’s modulus estimation with a maximum error 35%. Therefore, this study presents a new algorithm that is capable of measuring the elastic properties of gelatin specimens in a quantitative way using only the image data. Further, the computation is monitored and evaluated by a performance descriptor, which measures the trustability of the results.

scholarly journals A parametric prediction of the Young’s modulus of polymers enhanced with ΜWCNTs

2018 ◽  
Vol 233 ◽  
pp. 00025
Author(s):  
P.V. Polydoropoulou ◽  
K.I. Tserpes ◽  
Sp.G. Pantelakis ◽  
Ch.V. Katsiropoulos
Keyword(s):  
Young’S Modulus ◽  
Elastic Properties ◽  
Young's Modulus ◽  
Experimental Results ◽  
Scale Model ◽  
Fe Model ◽  
Multi Scale ◽  
Unit Cells ◽  
Random Dispersion

In this work a multi-scale model simulating the effect of the dispersion, the waviness as well as the agglomerations of MWCNTs on the Young’s modulus of a polymer enhanced with 0.4% MWCNTs (v/v) has been developed. Representative Unit Cells (RUCs) have been employed for the determination of the homogenized elastic properties of the MWCNT/polymer. The elastic properties computed by the RUCs were assigned to the Finite Element (FE) model of a tension specimen which was used to predict the Young’s modulus of the enhanced material. Furthermore, a comparison with experimental results obtained by tensile testing according to ASTM 638 has been made. The results show a remarkable decrease of the Young’s modulus for the polymer enhanced with aligned MWCNTs due to the increase of the CNT agglomerations. On the other hand, slight differences on the Young’s modulus have been observed for the material enhanced with randomly-oriented MWCNTs by the increase of the MWCNTs agglomerations, which might be attributed to the low concentration of the MWCNTs into the polymer. Moreover, the increase of the MWCNTs waviness led to a significant decrease of the Young’s modulus of the polymer enhanced with aligned MWCNTs. The experimental results in terms of the Young’s modulus are predicted well by assuming a random dispersion of MWCNTs into the polymer.

scholarly journals High-Temperature Elastic Properties of Yttrium-Doped Barium Zirconate

Metals ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 968
Author(s):  
Fumitada Iguchi ◽  
Keisuke Hinata
Keyword(s):  
High Temperature ◽  
Young’S Modulus ◽  
Elastic Properties ◽  
Measurement Method ◽  
Young's Modulus ◽  
Barium Zirconate ◽  
Shear Moduli ◽  
Ceramic Fuel ◽  
Yttrium Concentration ◽  
Ceramic Fuel Cells

The elastic properties of 0, 10, 15, and 20 mol% yttrium-doped barium zirconate (BZY0, BZY10, BZY15, and BZY20) at the operating temperatures of protonic ceramic fuel cells were evaluated. The proposed measurement method for low sinterability materials could accurately determine the sonic velocities of small-pellet-type samples, and the elastic properties were determined based on these velocities. The Young’s modulus of BZY10, BZY15, and BZY20 was 224, 218, and 209 GPa at 20 °C, respectively, and the values decreased as the yttrium concentration increased. At high temperatures (>20 °C), as the temperature increased, the Young’s and shear moduli decreased, whereas the bulk modulus and Poisson’s ratio increased. The Young’s and shear moduli varied nonlinearly with the temperature: The values decreased rapidly from 100 to 300 °C and gradually at temperatures beyond 400 °C. The Young’s modulus of BZY10, BZY15, and BZY20 was 137, 159, and 122 GPa at 500 °C, respectively, 30–40% smaller than the values at 20 °C. The influence of the temperature was larger than that of the change in the yttrium concentration.

scholarly journals Multi-material direct ink writing of photocurable elastomeric foams

2021 ◽  
Vol 2 (1) ◽  
Author(s):  
Osman Dogan Yirmibesoglu ◽  
Leif Erik Simonsen ◽  
Robert Manson ◽  
Joseph Davidson ◽  
Katherine Healy ◽  
...  
Keyword(s):  
Young’S Modulus ◽  
Young's Modulus ◽  
Transient Behavior ◽  
Soft Materials ◽  
Ammonium Bicarbonate ◽  
Structure Property ◽  
Direct Ink Writing ◽  
Material Chemistry ◽  
New Applications ◽  
Double Networks

AbstractDevelopments in additive manufacturing have enabled the fabrication of soft machines that can safely interface with humans, creating new applications in soft robotics, wearable technologies, and haptics. However, designing custom inks for the 3D printing of soft materials with Young’s modulus less than 100 kPa remains a challenge due to highly coupled structure-property-process relationship in polymers. Here, we show a three-stage material chemistry process based on interpenetrating silicone double networks and ammonium bicarbonate particles that decouples the transient behavior during processing from the final properties of the material. Evaporation of ammonium bicarbonate particles at the final stage creates gaseous voids to produce foams with a low effective Young’s modulus in the 25 kPa −90 kPa range. Our photoirradiation-assisted direct ink writing system demonstrates the ability to maintain high resolution while enabling controlled loading of ammonium bicarbonate particles. The resultant multi-material possesses programmed porosity and related properties such as density, stiffness, Shore hardness, and ultimate strength in a monolithic object. Our multi-hardness synthetic hand and self-righting buoyant structure highlight these capabilities.

scholarly journals Approximate Dynamic Programming Based Control of Proppant Concentration in Hydraulic Fracturing

Mathematics ◽  
2018 ◽  
Vol 6 (8) ◽  
pp. 132 ◽  
Author(s):  
Harwinder Singh Sidhu ◽  
Prashanth Siddhamshetty ◽  
Joseph Kwon
Keyword(s):  
Mechanical Properties ◽  
Dynamic Programming ◽  
Hydraulic Fracturing ◽  
Young’S Modulus ◽  
Large Scale ◽  
Approximate Dynamic Programming ◽  
Young's Modulus ◽  
Computational Cost ◽  
Control Technique ◽  
Rock Mechanical Properties

Hydraulic fracturing has played a crucial role in enhancing the extraction of oil and gas from deep underground sources. The two main objectives of hydraulic fracturing are to produce fractures with a desired fracture geometry and to achieve the target proppant concentration inside the fracture. Recently, some efforts have been made to accomplish these objectives by the model predictive control (MPC) theory based on the assumption that the rock mechanical properties such as the Young’s modulus are known and spatially homogenous. However, this approach may not be optimal if there is an uncertainty in the rock mechanical properties. Furthermore, the computational requirements associated with the MPC approach to calculate the control moves at each sampling time can be significantly high when the underlying process dynamics is described by a nonlinear large-scale system. To address these issues, the current work proposes an approximate dynamic programming (ADP) based approach for the closed-loop control of hydraulic fracturing to achieve the target proppant concentration at the end of pumping. ADP is a model-based control technique which combines a high-fidelity simulation and function approximator to alleviate the “curse-of-dimensionality” associated with the traditional dynamic programming (DP) approach. A series of simulations results is provided to demonstrate the performance of the ADP-based controller in achieving the target proppant concentration at the end of pumping at a fraction of the computational cost required by MPC while handling the uncertainty in the Young’s modulus of the rock formation.

scholarly journals Dynamic Radiation Effects Induced by Short-Pulsed GeV U-Ion Beams in Graphite and h-BN Targets

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Philipp Bolz ◽  
Philipp Drechsel ◽  
Alexey Prosvetov ◽  
Pascal Simon ◽  
Christina Trautmann ◽  
...  
Keyword(s):  
Boron Nitride ◽  
Young’S Modulus ◽  
Radiation Effects ◽  
Large Scale ◽  
Hexagonal Boron Nitride ◽  
Young's Modulus ◽  
Target Surface ◽  
High Dose ◽  
Velocity Signal ◽  
Isotropic Graphite

Targets of isotropic graphite and hexagonal boron nitride were exposed to short pulses of uranium ions with ∼1 GeV kinetic energy. The deposited power density of ∼3 MW/cm³ generates thermal stress in the samples leading to pressure waves. The velocity of the respective motion of the target surface was measured by laser Doppler vibrometry. The bending modes are identified as the dominant components in the velocity signal recorded as a function of time. With accumulated radiation damage, the bending mode frequency shifts towards higher values. Based on this shift, Young’s modulus of irradiated isotropic graphite is determined by comparison with ANSYS simulations. The increase of Young’s modulus up to 3 times the pristine value for the highest accumulated fluence of 3 × 1013 ions/cm2 is attributed to the beam-induced microstructural evolution into a disordered structure similar to glassy carbon. Young’s modulus values deduced from microindentation measurements are similar, confirming the validity of the method. Beam-induced stress waves remain in the elastic regime, and no large-scale damage can be observed in graphite. Hexagonal boron nitride shows lower radiation resistance. Circular cracks are generated already at low fluences, risking material failure when applied in high-dose environment.

scholarly journals Large-scale analysis of high-speed atomic force microscopy data sets using adaptive image processing

2012 ◽  
Vol 3 ◽  
pp. 747-758 ◽  
Author(s):  
Blake W Erickson ◽  
Séverine Coquoz ◽  
Jonathan D Adams ◽  
Daniel J Burns ◽  
Georg E Fantner
Keyword(s):  
High Speed ◽  
Large Scale ◽  
Data Sets ◽  
Force Microscopy ◽  
Topographic Features ◽  
Atomic Force ◽  
Large Scale Analysis ◽  
Adaptive Image Processing ◽  
True Representation ◽  
Microscopy Data

Modern high-speed atomic force microscopes generate significant quantities of data in a short amount of time. Each image in the sequence has to be processed quickly and accurately in order to obtain a true representation of the sample and its changes over time. This paper presents an automated, adaptive algorithm for the required processing of AFM images. The algorithm adaptively corrects for both common one-dimensional distortions as well as the most common two-dimensional distortions. This method uses an iterative thresholded processing algorithm for rapid and accurate separation of background and surface topography. This separation prevents artificial bias from topographic features and ensures the best possible coherence between the different images in a sequence. This method is equally applicable to all channels of AFM data, and can process images in seconds.

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