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Home > Press > Multiple uses for the JPK NanoWizard AFM system in the Smart Interfaces in Environmental Nanotechnology Group at the University of Illinois at Urbana-Champaign Abstract: JPK Instruments, a world-leading manufacturer of nanoanalytic instrumentation for research in life sciences and soft matter, reports on the breadth of research applications where their NanoWizard® AFM system is being used in the Smart Interfaces in Environmental Nanotechnology Group under the leadership of Associate Professor, Rosa M Espinosa-Marzal. Dr Rosa M Espinosa-Marzal is an Associate Professor in the Department of Civil & Environmental Engineering at the University of Illinois at Urbana-Champaign. The goal of her research is to design innovative systems and improved materials that can solve environmental problems of our society by applying fundamentals of surface and colloidal science, materials chemistry, and nanotechnology. The central theme of her research group, Smart Interfaces in Environmental Nanotechnology (SIEN), is to design, synthesize, characterize and develop a fundamental understanding of bioinspired materials and of (bio) interfaces, also under nanoconfinement. Atomic force microscopy, AFM, is a vital tool for these studies. Speaking about her group and their experiences since the starting of their use of the JPK NanoWizard® AFM system, Dr Espinosa-Marzal says “My team of researchers is looking at a broad range of materials which require imaging in fluids to a high level resolution. The ability to measure low noise, high resolution force curves is of particular value as is the capability of working in liquid environments without the fear of damaging the piezo or sample. My students have made many positive comments which are important to me. I am confident that their imaging is of the quality they need to complete their research assignments.” Picking out some of the projects where the NanoWizard® is being successfully used, it is revealing to hear the comments of the SIEN group members describe what makes them particularly pleased with the performance of the system. In one project which is setting out to understand the structure of water at the interface with 2D materials such as graphene, the biggest challenge is to make high resolution, force spectroscopy measurements. Operating in liquid the NanoWizard® has produced high resolution phase images in AC mode that reveal the contamination on the graphene surface. Ultimately, the group hopes to study the layering of water molecules and ions on the graphene surface, which can be used as a possible interface for water purification. Imaging soft structures in aqueous environments is the challenge of the researchers developing model cell membranes. These are tri-layered soft structures, with interfacial and mechanical properties similar to a cell membrane. These require a low noise system to both image and perform nanomechanical characterization with QI™ mode of individual layers and the complete stratified structure. In a biofilm study, one researcher is looking to understand the precipitation of calcite in biofilms found in drinking water distribution systems. Here, colloidal AFM probes are applied to make surface force measurements on heterogeneous soft composites. These are used to determine mechanical forces of the films including adhesion and detachment forces. The combination of AFM with an inverted microscope has been invaluable here using JPK's patented Direct Overlay™ feature to identify appropriate areas to image and ultimately to generate force maps which allow the understanding of the spatial variability of the mechanical properties for mineralized and non-mineralized samples. Other projects include the study of biomineralization (imaging amorphous calcium carbonate) and how ionic liquids respond to nanoscale confinement and to surface heterogeneities. These just further illustrate the versatility of the JPK NanoWizard® in a multi-user research group. For more details about JPK's NanoWizard® AFM and their applications for the bio & nano sciences, please contact JPK on +49 30726243 500. Alternatively, please visit the web site: www.jpk.com or see more on Facebook: www.jpk.com/facebook and on You Tube: www.youtube.com/jpkinstruments. About JPK Instruments JPK Instruments AG is a world-leading manufacturer of nanoanalytic instruments - particularly atomic force microscope (AFM) systems and optical tweezers - for a broad range of applications reaching from soft matter physics to nano-optics, from surface chemistry to cell and molecular biology. From its earliest days applying atomic force microscope (AFM) technology, JPK has recognized the opportunities provided by nanotechnology for transforming life sciences and soft matter research. This focus has driven JPK's success in uniting the worlds of nanotechnology tools and life science applications by offering cutting-edge technology and unique applications expertise. Headquartered in Berlin and with direct operations in Dresden, Cambridge (UK), Singapore, Tokyo, Shanghai (China), Paris (France) and Carpinteria (USA), JPK maintains a global network of distributors and support centers and provides on the spot applications and service support to an ever-growing community of researchers. For more information, please click If you have a comment, please us. Issuers of news releases, not 7th Wave, Inc. or Nanotechnology Now, are solely responsible for the accuracy of the content.


News Article | September 29, 2016
Site: www.cemag.us

New research, led by the University of Southampton, has demonstrated that a nanoscale device, called a memristor, could be the “missing link” in the development of implants that use electrical signals from the brain to help treat medical conditions. Monitoring neuronal cell activity is fundamental to neuroscience and the development of neuroprosthetics — biomedically engineered devices that are driven by neural activity. However, a persistent problem is the device being able to process the neural data in real-time, which imposes restrictive requirements on bandwidth, energy and computation capacity. In a new study, published in Nature Communications, the researchers showed that memristors could provide real-time processing of neuronal signals (spiking events) leading to efficient data compression and the potential to develop more precise and affordable neuroprosthetics and bioelectronic medicines. Memristors are electrical components that limit or regulate the flow of electrical current in a circuit and can remember the amount of charge that was flowing through it and retain the data, even when the power is turned off. Lead author Isha Gupta, Postgraduate Research Student at the University of Southampton, says, “Our work can significantly contribute towards further enhancing the understanding of neuroscience, developing neuroprosthetics and bio-electronic medicines by building tools essential for interpreting the big data in a more effective way.” The research team developed a nanoscale Memristive Integrating Sensor (MIS) into which they fed a series of voltage-time samples, which replicated neuronal electrical activity. Acting like synapses in the brain, the metal-oxide MIS was able to encode and compress (up to 200 times) neuronal spiking activity recorded by multi-electrode arrays. Besides addressing the bandwidth constraints, this approach was also very power efficient — the power needed per recording channel was up to 100 times less when compared to current best practice. Co-author Dr. Themis Prodromakis, Reader in Nanoelectronics and EPSRC Fellow in Electronics and Computer Science at the University of Southampton, says, “We are thrilled that we succeeded in demonstrating that these emerging nanoscale devices, despite being rather simple in architecture, possess ultra-rich dynamics that can be harnessed beyond the obvious memory applications to address the fundamental constraints in bandwidth and power that currently prohibit scaling neural interfaces beyond 1,000 recording channels.” The Prodromakis Group at the University of Southampton is acknowledged as world-leading in this field, collaborating among others with Leon Chua (a Diamond Jubilee Visiting Academic at the University of Southampton), who theoretically predicted the existence of memristors in 1971. This interdisciplinary work was supported by an FP7 project (the European Union's Research and Innovation funding) and brought together engineers from the Nanoelectronics and Nanotechnology Group at the University of Southampton with biologists from the University of Padova and the Max Planck Institute, Germany, using the state-of-art facilities of the Southampton Nanofabrication Centre.


News Article | October 7, 2016
Site: www.cemag.us

Lead author Dr. Alex Serb, from Electronics and Computer Science at the University of Southampton, says, “If we want to build artificial systems that can mimic the brain in function and power we need to use hundreds of billions, perhaps even trillions of artificial synapses, many of which must be able to implement learning rules of varying degrees of complexity. Whilst currently available electronic components can certainly be pieced together to create such synapses, the required power and area efficiency benchmarks will be extremely difficult to meet -if even possible at all- without designing new and bespoke “synapse components.” “Memristors offer a possible route towards that end by supporting many fundamental features of learning synapses (memory storage, on-line learning, computationally powerful learning rule implementation, two-terminal structure) in extremely compact volumes and at exceptionally low energy costs. If artificial brains are ever going to become reality, therefore, memristive synapses have to succeed.” Acting like synapses in the brain, the metal-oxide memristor array was capable of learning and re-learning input patterns in an unsupervised manner within a probabilistic winner-take-all (WTA) network. This is extremely useful for enabling low-power embedded processors (needed for the Internet of Things) that can process in real-time big data without any prior knowledge of the data. Co-author Dr. Themis Prodromakis, Reader in Nanoelectronics and EPSRC Fellow in Electronics and Computer Science at the University of Southampton, says, “The uptake of any new technology is typically hampered by the lack of practical demonstrators that showcase the technology’s benefits in practical applications. Our work establishes such a technological paradigm shift, proving that nanoscale memristors can indeed be used to formulate in-silico neural circuits for processing big-data in real-time; a key challenge of modern society. “We have shown that such hardware platforms can independently adapt to its environment without any human intervention and are very resilient in processing even noisy data in real-time reliably. This new type of hardware could find a diverse range of applications in pervasive sensing technologies to fuel real-time monitoring in harsh or inaccessible environments; a highly desirable capability for enabling the Internet of Things vision.” This interdisciplinary work was supported by a CHIST-ERA net award project and the Engineering and Physical Sciences Research Council. It brought together engineers from the Nanoelectronics and Nanotechnology Group at the University of Southampton with theoretical computer scientists at the Graz University of Technology, using the state-of-art facilities of the Southampton Nanofabrication Centre. The Prodromakis Group at the University of Southampton is acknowledged as world-leading in this field, collaborating among others with Leon Chua (a Diamond Jubilee Visiting Academic at the University of Southampton), who theoretically predicted the existence of memristors in 1971.


Chitsazzadeh M.,Nanotechnology Group | Shahverdi H.,Nanotechnology Group | Shokrieh M.M.,Composites Research Laboratory
Defect and Diffusion Forum | Year: 2011

Excellent physical and mechanical properties of carbon nanotubes (CNTs) make them outstanding candidate as fillers to fabricate multi-functional polymer composites. It is assumed that a high level of dispersion in the preparation stage may lead to a more effective nanocomposite. In this research, the dispersion state of multi-walled carbon nanotubes (MWNTs) at various contents in an unsaturated vinyl ester resin is investigated during fabrication by on-line monitoring the viscosity of suspensions as a function of sonication time and energy introduced. The results show that initial viscosities of suspensions increase by adding more MWNTs to the resin. The viscosities gradually increase during the sonication and reach to maximum values, when it is assumed that the dispersion is completed. After this step the viscosity subsequently decreases. The energy density required to achieve a good dispersion of MWNTs in vinyl ester is obtained. The qualities of dispersion in cured composites are characterized by examining the sections using the scanning electron microscope (SEM) to confirm the results of viscosity measurements. The stabilization of MWNTs is achieved by adding a commercial dispersant and stabilizer, BYK-P 104S, by 0.0375 wt%. The results indicate that adding more surfactant to the suspension makes it unstable and leads to flocculation. The stabilization of suspensions is investigated by using viscosity measurement. Also, FT-IR is used to determine the possible mechanism of surfactant to stabilize the MWNTs in vinyl ester. © (2011) Trans Tech Publications.


Butterworth J.A.,University of Colorado at Boulder | Pao L.Y.,University of Colorado at Boulder | Abramovitch D.Y.,Nanotechnology Group
Proceedings of the 2010 American Control Conference, ACC 2010 | Year: 2010

In previous work, we evaluated the performance of two control architectures applied to atomic force microscopes (AFM) [1]. Experimental results in [1] indicated that the closed-loop-injection (FFCLI) architecture outperformed the plant-injection (FFPI) architecture when using a specific model-inversion feedforward technique for the tracking of a raster pattern. Empirical work suggested that a nontraditional variation upon the experimentally inferior FFPI architecture may allow it to track a raster pattern at a performance level in the neighborhood of the FFCLI architecture. This variation is manifested as additional delay inserted in the feedforward control system. An online adaptive technique is used to determine the required amount of additional delay. Experimental results show that the performance level of the FFCLI architecture and the adaptive-delay FFPI architecture are comparable. © 2010 AACC.


Butterworth J.A.,University of Colorado at Boulder | Pao L.Y.,University of Colorado at Boulder | Abramovitch D.Y.,Nanotechnology Group
Proceedings of the American Control Conference | Year: 2011

In previous work, we compared the raster tracking performance of two distinct combined feedforward/feedback control architectures while using model-inverse-based feedforward control [1], [2]. In this paper, we extend that work into the application of parallel and serial iterative learning control (ILC) architectures. These ILC architectures naturally relate to the two previously studied combined feedforward/feedback control architectures, feedforward closed-loop injection (FFCLI) and feedforward plant injection (FFPI). Experimental learning results from an atomic force microscope (AFM) raster scanner are provided as well as results comparing the FFPI and FFCLI architectures with those of the learned performance for parallel and series ILC. We show that the value of ILC over model-inverse-based feedforward methods is increased in the presence of model uncertainty or variation. © 2011 AACC American Automatic Control Council.


Patrocinio W.S.,Nanotechnology Group | Ribeiro Jr. M.,Nanotechnology Group | Fonseca L.R.C.,Nanotechnology Group
Materials Science and Engineering B: Solid-State Materials for Advanced Technology | Year: 2012

Silicon nitride, with a permittivity mid-way between SiO 2 and common high-k materials such as HfO 2, is widely used in microelectronics as an insulating layer on top of oxides where it serves as an impurity barrier with the positive side effect of increasing the dielectric constant of the insulator when it is SiO 2. It is also employed as charge storage in nonvolatile memory devices thanks to its high concentration of charge traps. However, in the case of memories, it is still unclear which defects are responsible for charge trapping and what is the impact of defect concentration on the structural and electronic properties of SiN x. Indeed, for the amorphous phase the band gap was measured in the range 5.1-5.5 eV, with long tails in the density of states penetrating the gap region. It is still not clear which defects are responsible for the tails. On the other hand, the K-center defects have been associated with charge trapping, though its origin is assigned to one Si back bond. To investigate the contribution of defect states to the band edge tails and band gap states, we adopted the β phase of stoichiometric silicon nitride (β-Si 3N 4) as our model material and calculated its electronic properties employing ab initio DFT/LDA simulations with self-energy correction to improve the location of defect states in the SiN x band gap through the correction of the band gap underestimation typical of DFT/LDA. We considered some important defects in SiN x, as the Si anti-site and the N vacancy with H saturation, in two defect concentrations. The location of our calculated defect levels in the band gap correlates well with the available experimental data, offering a structural explanation to the measured band edge tails and charge trapping characteristics. © 2012 Elsevier B.V.


Kardous F.,Nanotechnology Group | Kardous F.,University of Franche Comte | Yahiaoui R.,CNRS Femto ST Institute | Aoubiza B.,University of Franche Comte | Manceau J.-F.,CNRS Femto ST Institute
Sensors and Actuators, A: Physical | Year: 2014

Liquid mixing at micro-scale is considered a challenge which is even tougher to overcome in the case of discrete microfluidic. Many researchers have developed strategies and tried to be pioneer in mixing solutions for lab on chip. In this paper, we present a parallel microdroplet mixer based on acoustic field generation using a low frequency vibration (up to few hundreds of kilohertz). This device can be used for lab on chip applications, since the liquid characteristics are not disturbed by the plugged energy and involve relatively simple microfabrication techniques. We designed, fabricated, evaluated, presented experiments showing the microdroplet active mixing, and investigated the thermal effect of the created acoustic energy. © 2014 Elsevier B.V.


Kissel P.,ETH Zurich | Van Heijst J.,ETH Zurich | Enning R.,Nanotechnology Group | Stemmer A.,Nanotechnology Group | And 2 more authors.
Organic Letters | Year: 2010

(Figure presented) New macrocyclic amphiphiles with two or three integrated 1,8-anthrylenes have been synthesized by an iterative Sonogashira cross-coupling protocol. The final cyclization has been conducted with 80% yield under cuprous-free dilution conditions. Formation of a monolayer at the air/water interface has also been demonstrated. These results open the intriguing possibility to construct large 2D supramolecular/macromolecular systems for which unique photophysical and -chemical properties are expected. © 2010 American Chemical Society.

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