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Synthetic biology with nanomaterials
- Sanhita Ray, Ahana Mukherjee, Pritha Chatterjee, Kaushik Chakraborty, Anjan Kr Dasgupta
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- Journal:
- MRS Communications / Volume 8 / Issue 1 / March 2018
- Published online by Cambridge University Press:
- 19 March 2018, pp. 100-106
- Print publication:
- March 2018
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- Article
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Magnetic field has been used to trigger biofilm formation. Iron oxide nanoparticles were attached to bacterial cells and cells were aggregated by application of magnetic field. Artificial cellular crowding triggered quorum sensing and led to the formation of biofilm at the sub-threshold population. Aggregation process was monitored by studying temporal dynamics of capacitance and conductance profiles. Capacitive profile exhibited a plateau upon introduction of magnetic field which was retained even after field was removed. This hysteresis property signified biofilm initiation in response to artificial crowding. This work demonstrates how synthetic biology is enabled by including nanoparticles in the interactome.
11 - Self-healing for silicon-based mm-wave power amplifiers
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- By Steven M. Bowers, University of Virginia, Kaushik Sengupta, Princeton University, Kaushik Dasgupta, Intel, Ali Hajimiri, California Institute of Technology
- Edited by Hossein Hashemi, University of Southern California, Sanjay Raman, Virginia Polytechnic Institute and State University
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- Book:
- mm-Wave Silicon Power Amplifiers and Transmitters
- Published online:
- 05 April 2016
- Print publication:
- 04 April 2016, pp 419-456
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Summary
Background
Motivation for self-healing
The rise of digital computation and personal computing has led to continual advances in semiconductor technologies at an exponential pace, following Moore's Law. In each successive processing node, the minimum feature size decreases, improving performance, but also bringing some trade-offs in terms of variation between chips as well as between transistors on the same chip [1–4]. One major source of this variation is random dopant fluctuations (RDFs) in the channel of a transistor [5, 6]. A typical 130-nm complementary metal–oxide–silicon (CMOS) process will have several hundreds of dopant atoms in the channel region. In contrast, in a 32-nm process, only a few tens of dopants control important transistor characteristics like threshold voltage, etc. A second source of variation is line-width control in these advanced processes. Line-edge roughness (LER) caused by lithographic and etching steps directly impacts the overlap capacitances as well as other device parameters like drain-induced barrier lowering (DIBL) and threshold voltage [7]. Figure 11.1 shows how threshold voltage variations scale with process technology node. As can be seen, the variation is much more manageable at larger nodes, and the variation is expected to continue to increase at smaller nodes as the total number of dopant atoms as well as the channel length reduces even further. If the variation can be dealt with, however, the smaller transistors can enable new applications for mm-wave power generation, enabling transmitters and amplifiers at higher frequencies, powers, and efficiencies. Another issue that analog designers face is that, due to the digital processing market being the driving force pushing the scaling, the models provided by the foundries early in the node's development stage are primarily designed for digital use, and are often not reliable at mm-wave frequencies.
In addition to these static sources of variation, dynamic temperature variations across the same die can give rise to varying sub-threshold leakage, supply voltage variations thereby directly affecting overall system performance. Variability in operating environment of power generation systems can adversely affect their performance. This comes in the form of temperature variation, degradation due to aging [8], and, in the case of power amplifiers that are driving antennas, load impedance mismatch caused by voltage standing wave ratio (VSWR) events [9] that occur when objects in the environment interactin the near field of the antenna, as can be seen in Fig. 11.2.