InterNano Nanomanufacturing Repository
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On-chip Variation Sensor for Systematic Variation Estimation in Nanoscale Fabrics
No full textParameter variations caused by manufacturing imprecision at the nanoscale are expected to cause large deviations in electrical characteristics of emerging nanodevices and nano-fabrics leading to performance deterioration and yield loss. Parameter variation is typically addressed pre-fabrication, with circuit design targeting worst-case timing scenarios. By contrast, if variation is estimated post-manufacturing, adaptive techniques or reconfiguration could be used to provide more optimal level of tolerance. This paper presents a new on-chip sensor design for nanoscale fabrics that from its own variation, can estimate the extent of systematic variation in neighboring regions. A Monte Carlo simulation framework is used to validate the sensor design. Known variation cases are injected and based on sensor outputs, the extent of systematic variation in physical parameters is calculated. Our results show that the sensor has less than 1.2% error in estimation of physical parameters in 100% of injected variation cases. Based on published experimental data, the sensor estimation is shown to be accurate to within 2% of the actual physical parameter value for a range of up to 7mm
A Surprise from 1954: Siloxane Equilibration Is a Simple, Robust, and Obvious Polymer Self-Healing Mechanism
No full textDetermination of the Intracellular Stability of Gold Nanoparticle Monolayers Using Mass Spectrometry
No full textEffect of Surface Charge on the Uptake and Distribution of Gold Nanoparticles in Four Plant Species
No full textNanoinformatics workshop report: current resources, community needs and the proposal of a collaborative framework for data sharing and information integration
No full textThe quantity of information on nanomaterial properties and behavior continues to grow rapidly. Without a concerted effort to collect, organize and mine disparate information coming out of current research efforts, the value and effective use of this information will be limited at best. Data will not be translated to knowledge. At worst, erroneous conclusions will be drawn and future research may be misdirected. Nanoinformatics can be a powerful approach to enhance the value of global information in nanoscience and nanotechnology. Much progress has been made through grassroots efforts in nanoinformatics resulting in a multitude of resources and tools for nanoscience researchers. In 2012, the nanoinformatics community believed it was important to critically evaluate and refine currently available nanoinformatics approaches in order to best inform the science and support the future of predictive nanotechnology. The Greener Nano 2012: Nanoinformatics Tools and Resources Workshop brought together informatics groups with materials scientists active in nanoscience research to evaluate and reflect on the tools and resources that have recently emerged in support of predictive nanotechnology. The workshop goals were to establish a better understanding of current nanoinformatics approaches and to clearly define immediate and projected informatics infrastructure needs of the nanotechnology community. The theme of nanotechnology environmental health and safety (nanoEHS) was used to provide real-world, concrete examples on how informatics can be utilized to advance our knowledge and guide nanoscience. The benefit here is that the same properties that impact the performance of products could also be the properties that inform EHS. From a decision management standpoint, the dual use of such data should be considered a priority. Key outcomes include a proposed collaborative framework for data collection, data sharing and information integration
