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Mani, Seethambal S.

Publications and source records attributed to Mani, Seethambal S..

At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Method of fabricating photosensitive devices with reduced process-temperature budget

A method is provided for fabricating a backside-illuminated photodetector in which a device wafer is joined to a readout wafer in an IC hybridization step. Before the IC hybridization step, the device layer is defined in the device wafer, and an LPCVD layer is formed over the device layer. The LPCVD layer may be a passivation layer, an antireflection coating, or both. The side of the device wafer having the LPCVD layer is bonded to a handle wafer, the IC is hybridized by mating the device wafer to the readout wafer, and the handle wafer is then removed, exposing the LPCVD layer. Because the LPCVD layer is formed before the active devices are fabricated, it can be made by high-temperature techniques for deposition and processing. Accordingly, a layer of high quality can be fabricated without any hazard to the active devices.

Kay, Randolph R.↗
DOE OSTI2018

Born Qualified Grand Challenge LDRD Final Report

This SAND report fulfills the final report requirement for the Born Qualified Grand Challenge LDRD. Born Qualified was funded from FY16-FY18 with a total budget of ~$13M over the 3 years of funding. Overall 70+ staff, Post Docs, and students supported this project over its lifetime. The driver for Born Qualified was using Additive Manufacturing (AM) to change the qualification paradigm for low volume, high value, high consequence, complex parts that are common in high-risk industries such as ND, defense, energy, aerospace, and medical. AM offers the opportunity to transform design, manufacturing, and qualification with its unique capabilities. AM is a disruptive technology, allowing the capability to simultaneously create part and material while tightly controlling and monitoring the manufacturing process at the voxel level, with the inherent flexibility and agility in printing layer-by-layer. AM enables the possibility of measuring critical material and part parameters during manufacturing, thus changing the way we collect data, assess performance, and accept or qualify parts. It provides an opportunity to shift from the current iterative design-build-test qualification paradigm using traditional manufacturing processes to design-by-predictivity where requirements are addressed concurrently and rapidly. The new qualification paradigm driven by AM provides the opportunity to predict performance probabilistically, to optimally control the manufacturing process, and to implement accelerated cycles of learning. Exploiting these capabilities to realize a new uncertainty quantification-driven qualification that is rapid, flexible, and practical is the focus of this effort.

36 MATERIALS SCIENCE↗