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Articles 1 - 3 of 3
Full-Text Articles in Nanoscience and Nanotechnology
Bayesian Calibration Tool, Sveinn Palsson, Martin Hunt, Alejandro Strachan
Bayesian Calibration Tool, Sveinn Palsson, Martin Hunt, Alejandro Strachan
The Summer Undergraduate Research Fellowship (SURF) Symposium
Fitting a model to data is common practice in many fields of science. The models may contain unknown parameters and often, the goal is to obtain good estimates of them. A variety of methods have been developed for this purpose. They often differ in complexity, efficiency and accuracy and some may have very limited applications. Bayesian inference methods have recently become popular for the purpose of calibrating model's parameters. The way they treat unknown quantities is completely different from any classical methods. Even though the unknown quantity is a constant, it is treated as a random variable and the desired …
Granular Matter: Microstructural Evolution And Mechanical Response, Aashish Ghimire, Ishan Srivastava, Timothy S. Fisher
Granular Matter: Microstructural Evolution And Mechanical Response, Aashish Ghimire, Ishan Srivastava, Timothy S. Fisher
The Summer Undergraduate Research Fellowship (SURF) Symposium
Heterogeneous (nano) composites, manufactured by the densification of variously sized grains, represent an important and ubiquitous class of technologically relevant materials. Typical grain sizes in such materials range from macroscopic to a few nanometers. The morphology exhibited by such disordered materials is complex and intricately connected with its thermal and electrical transport properties. It is important to quantify the geometric features of these materials and simulate the fabrication process. Additionally, granular materials exhibit complex structural and mechanical properties that crucially govern their reliability during industrial use. In this work, we simulate the densification of soft deformable grains from a low-density …
Nanosensor Data Processor In Quantum-Dot Cellular Automata, Fenghui Yao, Mohamed Saleh Zein-Sabatto, Guifeng Shao, Mohammad Bodruzzaman, Mohan Malkani
Nanosensor Data Processor In Quantum-Dot Cellular Automata, Fenghui Yao, Mohamed Saleh Zein-Sabatto, Guifeng Shao, Mohammad Bodruzzaman, Mohan Malkani
Computer Science Faculty Research
Quantum-dot cellular automata (QCA) is an attractive nanotechnology with the potential alterative to CMOS technology. QCA provides an interesting paradigm for faster speed, smaller size, and lower power consumption in comparison to transistor-based technology, in both communication and computation. This paper describes the design of a 4-bit multifunction nanosensor data processor (NSDP). The functions of NSDP contain (i) sending the preprocessed raw data to high-level processor, (ii) counting the number of the active majority gates, and (iii) generating the approximate sigmoid function. The whole system is designed and simulated with several different input data.