Chandra Mouli

Bio: Chandra Mouli is an academic researcher from Micron Technology. The author has contributed to research in topics: Transistor & Field-effect transistor. The author has an hindex of 32, co-authored 216 publications receiving 3289 citations. Previous affiliations of Chandra Mouli include Aptina.

Low capacitance through substrate via structures

Abstract: Apparatuses and methods are disclosed herein for the formation of low capacitance through substrate via structures. An example apparatus includes an opening formed in a substrate, wherein the opening has at least one sidewall, a first dielectric at least formed on the sidewall of the opening, a first conductor at least formed on the first dielectric, a second dielectric at least formed on the first conductor, and a second conductor at least formed on a sidewall of the second dielectric.

Semiconductor device structures including energy barriers, and related methods

Abstract: A semiconductor device structure includes a transistor with an energy barrier beneath its transistor channel. The energy barrier prevents leakage of stored charge from the transistor channel into a bulk substrate. Methods for fabricating semiconductor devices that include energy barriers are also disclosed.

Capacitor-less memory cell, device, system and method of making same

Abstract: A capacitor-less memory cell, memory device, system and process of forming the capacitor-less memory cell includes forming the memory cell in an active area of a substantially physically isolated portion of the bulk semiconductor substrate. A pass transistor is formed on the active area for coupling with a word line. The capacitor-less memory cell further includes a read/write enable transistor vertically configured along at least one vertical side of the active area and operable during a reading of a logic state with the logic state being stored as charge in a floating body area of the active area, causing different determinable threshold voltages for the pass transistor.

Fin field effect transistors including energy barriers

Abstract: A semiconductor device structure includes a transistor with an energy barrier beneath its transistor channel. The energy barrier prevents leakage of stored charge from the transistor channel into a bulk substrate. Methods for fabricating semiconductor devices that include energy barriers are also disclosed.

Methods of forming transistor devices associated with semiconductor-on-insulator constructions

Abstract: The invention encompasses a method of forming a semiconductor on-insulator construction. A substrate is provided. The substrate includes a semiconductor-containing layer over an insulative mass. The insulative mass comprises silicon dioxide. A band of material is formed within the insulative mass. The material comprises one or more of nitrogen argon, fluorine, bromine, chlorine, iodine and germanium.

Semiconductor device, and manufacturing method thereof

Abstract: An object is to provide a semiconductor device of which a manufacturing process is not complicated and by which cost can be suppressed, by forming a thin film transistor using an oxide semiconductor film typified by zinc oxide, and a manufacturing method thereof. For the semiconductor device, a gate electrode is formed over a substrate; a gate insulating film is formed covering the gate electrode; an oxide semiconductor film is formed over the gate insulating film; and a first conductive film and a second conductive film are formed over the oxide semiconductor film. The oxide semiconductor film has at least a crystallized region in a channel region.

Practical Poissonian-Gaussian Noise Modeling and Fitting for Single-Image Raw-Data

Abstract: We present a simple and usable noise model for the raw-data of digital imaging sensors This signal-dependent noise model, which gives the pointwise standard-deviation of the noise as a function of the expectation of the pixel raw-data output, is composed of a Poissonian part, modeling the photon sensing, and Gaussian part, for the remaining stationary disturbances in the output data We further explicitly take into account the clipping of the data (over- and under-exposure), faithfully reproducing the nonlinear response of the sensor We propose an algorithm for the fully automatic estimation of the model parameters given a single noisy image Experiments with synthetic images and with real raw-data from various sensors prove the practical applicability of the method and the accuracy of the proposed model

Systems and methods for processing analyte sensor data

Abstract: Systems and methods for applying time-dependent algorithmic compensation functions to data output from a continuous analyte sensor. Some embodiments determine a time since sensor implantation and/or whether a newly initialized sensor has been used previously.

Cyclops: In Situ Image Sensing and Interpretation in Wireless Sensor Networks

Abstract: Despite their increasing sophistication, wireless sensor networks still do not exploit the most powerful of the human senses: vision. Indeed, vision provides humans with unmatched capabilities to distinguish objects and identify their importance. Our work seeks to provide sensor networks with similar capabilities by exploiting emerging, cheap, low-power and small form factor CMOS imaging technology. In fact, we can go beyond the stereo capabilities of human vision, and exploit the large scale of sensor networks to provide multiple, widely different perspectives of the physical phenomena. To this end, we have developed a small camera device called Cyclops that bridges the gap between the computationally constrained wireless sensor nodes such as Motes, and CMOS imagers which, while low power and inexpensive, are nevertheless designed to mate with resource-rich hosts. Cyclops enables development of new class of vision applications that span across wireless sensor network. We describe our hardware and software architecture, its temporal and power characteristics and present some representative applications.

Cyclops: in situ image sensing and interpretation in wireless sensor networks

Abstract: Despite their increasing sophistication, wireless sensor networks still do not exploit the most powerful of the human senses: vision. Indeed, vision provides humans with unmatched capabilities to distinguish objects and identify their importance. Our work seeks to provide sensor networks with similar capabilities by exploiting emerging, cheap, low-power and small form factor CMOS imaging technology. In fact, we can go beyond the stereo capabilities of human vision, and exploit the large scale of sensor networks to provide multiple, widely different perspectives of the physical phenomena.To this end, we have developed a small camera device called Cyclops that bridges the gap between the computationally constrained wireless sensor nodes such as Motes, and CMOS imagers which, while low power and inexpensive, are nevertheless designed to mate with resource-rich hosts. Cyclops enables development of new class of vision applications that span across wireless sensor network. We describe our hardware and software architecture, its temporal and power characteristics and present some representative applications.