Die-Level Thinning for Flip-Chip Integration on Flexible Substrates

Die-level thinning, handling, and integration of singulated dies from multi-project wafers (MPW) are often used in research, early-stage development, and prototyping of flexible devices. There is a high demand for thin silicon devices for several applications, such as flexible electronics. To address this demand, we study a novel post-processing method on two silicon devices, an electrochemical impedance sensor, and Complementary Metal Oxide Semiconductor (CMOS) die. Both are drawn from an MPW batch, thinned at die-level after dicing and singulation down to 60 µm. The thinned dies were flip-chip bonded to flexible substrates and hermetically sealed by two techniques: thermosonic bonding of Au stud bumps and anisotropic conductive paste (ACP) bonding. The performance of the thinned dies was assessed via functional tests and compared to the original dies. Furthermore, the long-term reliability of the flip-chip bonded thinned sensors was demonstrated to be higher than the conventional wire-bonded sensors

Flow-Velocity Measurement for Bulk Granular Solids in Pneumatic Conveyor Pipes Using Random-Data Correlator Architecture

Abstract-This paper discusses a correlative-measurement technique for the evaluation of the flow velocity of bulk granular solids moving through the pneumatic conveyor pipes in both the dense and dilute phases. Flow velocities are recovered from the cross-correlation functions between the pairs of signals produced by the noninvasive capacitive sensors placed in circular layers at a given distance on the conveyor pipe. A random-data correlator architecture is discussed as a cost-effective solution for the real-time computation of the multiple correlation functions used for the estimation of the cross-sectional tomographic model of the flow-velocity profile in the dilute phase. Index Terms-Dense phase, dilute phase, particle flow velocity, pneumatic transport of bulk granular solids, random-data correlator architecture

A Model-based Sensor Fusion Approach for Force and Shape Estimation in Soft Robotics

International audienceIn this paper, we address the challenge of sensor fusion in Soft Robotics for estimating forces and deformations. In the context of intrinsic sensing, we propose the use of a soft capacitive sensor to find a contact's location, and the use of pneumatic sensing to estimate the force intensity and the deformation. Using a FEM-based numerical approach, we integrate both sensing streams and model two Soft Robotics devices we have conceived. These devices are a Soft Pad and a Soft Finger. We show in an evaluation that external forces on the Soft Pad can be estimated and that the shape of the Soft Finger can be reconstructed