Efficient prediction of the substrate noise generated by digital sections is currently a major challenge in System-on-a-Chip design. In this paper a macromodel to accurately and efficiently predict the substrate noise generated by digital standard cells is presented. The macromodel accuracy is demonstrated for some simple circuits.
Efficient prediction of the substrate noise generated by large digital sections is currently a major challenge in System-on-a-Chip design. A macromodel to accurately and efficiently predict the substrate noise generated by digital standard cells is presented. The macromodel is generated from identification of the physical elements relevant to noise… (More)
This work proposes the use of quartz crystal microbalances (QCMs) as a method to analyze and characterize magnetorheological (MR) fluids. QCM devices are sensitive to changes in mass, surface interactions, and viscoelastic properties of the medium contacting its surface. These features make the QCM suitable to study MR fluids and their response to variable… (More)
Polymeric magnetic microparticles have been created using a microfluidic device via ultraviolet (UV) polymerization of double emulsions, resulting in cores of magnetorheological (MR) fluids surrounded by polymeric shells. We demonstrate that the resultant particles can be manipulated magnetically to achieve triggered rupture of the capsules. This… (More)
Substrate noise generated by large digital circuits degrades the performance of analog circuits sharing the same substrate. To simulate this performance degradation, the total amount of substrate noise must be known. For large digital circuits, the substrate simulation is however not feasible with a transistor-level simulator due to the long simulation… (More)