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Atomic force microscopy (AFM) is a powerful tool for imaging and quantitatively mapping the mechanical properties of materials at the micro- and nanoscales. In AFM, a microcantilever with a sharp tip interacts with the sample over various time scales and the interaction force history over this short interval of time contains rich information from which the local physical properties of the sample can be extracted. However, these tip–sample interactions cannot be directly controlled or measured. Thus, no experimental observable is directly proportional to the tip–sample interactions while scanning a sample. Moreover, these nonlinear interaction forces between the tip and sample, microcantilever dynamics, tip sample geometry convolution, and the feedback control system cumulatively affect the resulting AFM images and thus the material property maps. Therefore, a better understanding of suitable operating conditions for a specific experiment is important for an experimentalist since the underlying nonlinear dynamics in AFM is complex and nonintuitive. Comprehensive simulations can provide an insight into what operating conditions to choose for a specific experiment. Here, we present the key capabilities of web-based simulation tools for AFM, Virtual Environment for Dynamic Atomic force microscopy (VEDA) which was first introduced by Melcher et al. [1] in 2008. The tool has been developed since then, and now it consists of different modules to simulate AFM experiments in both ambient and liquid environments [2] with 19 different tip–sample interaction models. This is a web–based tool that is freely available on nanoHUB [3] for AFM users and is the most widely used AFM simulation tool in the world with about 1700 users worldwide. AFM users can develop a deeper quantitative understanding of AFM with the aid of simulation tools like VEDA

Identification of multiple oscillation states of carbon nanotube tipped cantilevers interacting with surfaces in dynamic atomic force microscopy

Carbon nanotubes (CNTs) have gained increased interest in dynamic atomic force microscopy (dAFM) as sharp, flexible, conducting, nonreactive tips for high-resolution imaging, oxidation lithography, and electrostatic force microscopy. By means of theory and experiments we lay out a map of several distinct tapping mode AFM oscillation states for CNT tipped AFM cantilevers: namely, noncontact attractive regime oscillation, intermittent contact with CNT slipping or pinning, or permanent contact with the CNT in point or line contact with the surface while the cantilever oscillates with large amplitude. Each state represents fundamentally different origins of CNT-surface interactions, CNT tip-substrate dissipation, and phase contrast and has major implications for the use of these probes for imaging, compositional contrast, and lithography. In particular, we present a method that uses energy-dissipation spectroscopy to identify if the CNT slips laterally on the surface or remains pinned in the intermittent contact regime. By comparing phase contrast images and energy dissipation on graphite, graphene oxide, and silicon oxide surfaces, we demonstrate the utility of the method in identifying pinning or slipping of the CNT on the surface in the intermittent contact regime

Microfluidic Platform for Immobilizing Cells to Surfaces

Atomic Force Microscope (AFM) is an advanced nanotechnology tool for image mapping and cell properties measuring. One of the major challenges presented to the scientists in the field is the procedure for sample preparation. In order for a cell or virus to be measured by the AFM, it has to be firmly attached to the surface. Existing methods including chemical functionalization of surface for cells binding are often very slow process which hinders the possibility of high throughput measurement. Therefore, we propose a new method that utilizes a fluid circulation system to immobilize cells of interest to designated area to significantly speed up the process. To achieve this goal, a hole which are comparable to the size of a cell are fabricated on the surface. Suctions are applied at these pores using an external pressure controller. Furthermore, two different designs are constructed as well as compared against each other in terms of price and effectiveness. One key difference between these two designs is that one will circulate the fluid back to the platform while the other one keeps transporting fluid across the microfluidics chip

Multiple impact regimes in liquid environment dynamic atomic force microscopy

A canonical assumption in dynamic atomic force microscopy is that the probe tip interacts with the sample once per oscillation cycle. We show this key ansatz breaks down for soft cantilevers in liquid environments. Such probes exhibit drum roll like dynamics with sequential bifurcations between oscillations with single, double, and triple impacts that can be clearly identified in the phase of the response. This important result is traced to a momentary excitation of the second flexural mode induced by tip-sample forces and low quality factors. Experiments performed on supported biological membranes in buffer solutions are used to demonstrate the findings. (C) 2008 American Institute of Physics

Spatial spectrograms of vibrating atomic force microscopy cantilevers coupled to sample surfaces

Many advanced dynamic Atomic Force Microscopy (AFM) techniques such as contact resonance, force modulation, piezoresponse force microscopy, electrochemical strain microscopy, and AFM infrared spectroscopy exploit the dynamic response of a cantilever in contact with a sample to extract local material properties. Achieving quantitative results in these techniques usually requires the assumption of a certain shape of cantilever vibration. We present a technique that allows in-situ measurements of the vibrational shape of AFM cantilevers coupled to surfaces. This technique opens up unique approaches to nanoscale material property mapping, which are not possible with single point measurements alone. (C) 2013 AIP Publishing LLC

An Information Modeling Framework for Support of Sustainable Manufacturing System Design Decision Making

Manufacturing technology has continuously evolved and advanced over the past century; this has led to an increase in the production of consumer and industrial goods driven by simultaneous growth in population and wealth. Despite the resulting economic and labor growth, environmental impacts of manufacturing have increased dramatically due to the dependence on exhaustible material and energy resources necessary to meet these growing product demands. Increasing awareness and concern over these impacts has encouraged sustainable thinking toward managing material resources, alternative energy sources, and advanced manufacturing technologies. However, the primary emphasis of manufacturing system design decision making has remained focused on the reduction of cost of goods sold (in discrete part production) and total production cost (in continuous production). Manufacturing system design decision makers face challenges in defining, evaluating, and implementing sustainable manufacturing practices, which include the time-intensive nature of complex system design and analysis, data integrity, and deficiencies in assessment methods. In particular, the challenges of collecting, curating, analyzing, and presenting environmental, economic, and social metrics and indicators (sustainability performance information) remains a barrier to operational decision-making. Existing assessment methods and tools are not well-suited to evaluating the sustainability performance of manufacturing processes and systems, as they tend to be product-focused and have limited ability to adapt to changes at the manufacturing process or system level. The objective of this dissertation research is to facilitate sustainable manufacturing system design decision making by integrating a systematic and structured information modeling framework with a manufacturing system design approach. To accomplish this goal, the research approach involves four steps: (1) Performing a review of recent literature to identify the existing challenges in the development and application of sustainable manufacturing methods, tool, models, algorithms, metrics, and indicators; (2) Introducing a functional and object-oriented information modeling methodology to characterize the sustainability performance of unit manufacturing processes (UMPs) using the concepts of abstraction and instantiation, which is demonstrated by reusing and extending a manual milling UMP model for two and a half-axis milling process; (3) Applying information modeling approaches in characterizing the sustainability performance of manufacturing process flows composed of UMPs, which is demonstrated for a discrete part manufacturing system; and (4) Synthesizing the results of the prior steps to provide an information modeling framework for sustainable manufacturing system design decision making. The framework is applied to discrete and continuous product manufacturing to demonstrate the flexibility of this system design approach. The framework provides an accessible approach for detailed analysis of the sustainability performance of manufacturing processes and systems by enabling the reuse, extension, and composability of new and previously developed UMP models. The coupling of information modeling concepts (e.g., abstraction, instantiation, and polymorphism) along with hierarchical, structured, and systematic manufacturing system design enables the framework to address the challenges stated above, namely: (1) Modeling complexity is simplified through a bottom-up approach for characterizing individual UMPs, which are built up for system-level characterization; (2) Model development, verification, and validation efforts are reduced by reusing and extending UMP models, thereby also reducing the time-intensity of modeling; (3) Data reliability is improved, since the framework is agnostic of existing process-specific data sources, rather than restricting data sources and types necessary for analysis; and (4) Multi-criteria decision-making is facilitated by using a hierarchical data structure for model-quantified metrics of interest, which supports analysis using decision trees. The research lays a foundation for developing an ontologies based decision support for sustainable manufacturing system design, as ontologies describe relationships and links between systems and sub-systems which enables the framework to have high-fidelity and understanding of the manufacturing system model and data

Piezoelectric Fans using Higher Flexural Modes for Electronics Cooling Applications

Piezoelectric fans are gaining in popularity as low-power-consumption and low-noise devices for the removal of heat in confined spaces. The performance of piezoelectric fans has been studied by several authors, although primarily at the fundamental resonance mode. In this article the performance of piezoelectric fans operating at the higher resonance modes is studied in detail. Experiments are performed on a number of commercially available piezoelectric fans of varying length. Both finite element modeling and experimental impedance measure- ments are used to demonstrate that the electromechanical energy conversion (electromechanical coupling factors) in certain modes can be greater than in the first bending mode; however, losses in the piezoceramic are also shown to be higher at those modes. The overall power consumption of the fans is also found to increase with increasing mode number. Detailed flow visualizations are also performed to understand both the transient and steady-state fluid motion around these fans. The results indicate that certain advantages of piezoelectric fan operation at higher resonance modes are offset by increased power consumption and decreased fluid flow

Nuclear DDX3 expression predicts poor outcome in colorectal and breast cancer

Purpose: DEAD box protein 3 (DDX3) is an RNA helicase with oncogenic properties that shuttles between the cytoplasm and nucleus. The majority of DDX3 is found in the cytoplasm, but a subset of tumors has distinct nuclear DDX3 localization of yet unknown biological significance. This study aimed to evaluate the significance of and mechanisms behind nuclear DDX3 expression in colorectal and breast cancer. Methods: Expression of nuclear DDX3 and the nuclear exporter chromosome region maintenance 1 (CRM1) was evaluated by immunohistochemistry in 304 colorectal and 292 breast cancer patient samples. Correlations between the subcellular localization of DDX3 and CRM1 and the difference in overall survival between patients with and without nuclear DDX3 were studied. In addition, DDX3 mutants were created for in vitro evaluation of the mechanism behind nuclear retention of DDX3. Results: DDX3 was present in the nucleus of 35% of colorectal and 48% of breast cancer patient samples and was particularly strong in the nucleolus. Nuclear DDX3 correlated with worse overall survival in both colorectal (hazard ratio [HR] 2.34, P<0.001) and breast cancer (HR 2.39, P=0.004) patients. Colorectal cancers with nuclear DDX3 expression more often had cytoplasmic expression of the nuclear exporter CRM1 (relative risk 1.67, P=0.04). In vitro analysis of DDX3 deletion mutants demonstrated that CRM1-mediated export was most dependent on the N-terminal nuclear export signal. Conclusion: Overall, we conclude that nuclear DDX3 is partially CRM1-mediated and predicts worse survival in colorectal and breast cancer patients, putting it forward as a target for therapeutic intervention with DDX3 inhibitors under development in these cancer types