113 research outputs found
Improved Performance of GaAs-Based Terahertz Emitters via Surface Passivation and Silicon Nitride Encapsulation
Advancing functional connectivity research from association to causation
Cognition and behavior emerge from brain network interactions, such that investigating causal interactions should be central to the study of brain function. Approaches that characterize statistical associations among neural time series-functional connectivity (FC) methods-are likely a good starting point for estimating brain network interactions. Yet only a subset of FC methods ('effective connectivity') is explicitly designed to infer causal interactions from statistical associations. Here we incorporate best practices from diverse areas of FC research to illustrate how FC methods can be refined to improve inferences about neural mechanisms, with properties of causal neural interactions as a common ontology to facilitate cumulative progress across FC approaches. We further demonstrate how the most common FC measures (correlation and coherence) reduce the set of likely causal models, facilitating causal inferences despite major limitations. Alternative FC measures are suggested to immediately start improving causal inferences beyond these common FC measures
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Final report : compliant thermo-mechanical MEMS actuators, LDRD #52553.
Thermal actuators have proven to be a robust actuation method in surface-micromachined MEMS processes. Their higher output force and lower input voltage make them an attractive alternative to more traditional electrostatic actuation methods. A predictive model of thermal actuator behavior has been developed and validated that can be used as a design tool to customize the performance of an actuator to a specific application. This tool has also been used to better understand thermal actuator reliability by comparing the maximum actuator temperature to the measured lifetime. Modeling thermal actuator behavior requires the use of two sequentially coupled models, the first to predict the temperature increase of the actuator due to the applied current and the second to model the mechanical response of the structure due to the increase in temperature. These two models have been developed using Matlab for the thermal response and ANSYS for the structural response. Both models have been shown to agree well with experimental data. In a parallel effort, the reliability and failure mechanisms of thermal actuators have been studied. Their response to electrical overstress and electrostatic discharge has been measured and a study has been performed to determine actuator lifetime at various temperatures and operating conditions. The results from this study have been used to determine a maximum reliable operating temperature that, when used in conjunction with the predictive model, enables us to design in reliability and customize the performance of an actuator at the design stage
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