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.

A Self-Consistent, Semiclassical Electrothermal Modeling Framework for Mott Devices

Abstract: Mott materials have been investigated since late 1950s for their remarkably abrupt insulator to metal transition (IMT) in response to changes in temperature, strain, or electrical stimulus. Interest in these materials has been revived by recent demonstration of nanosecond-scale switching along with reproducible and fully reversible transitions in VO2-based thin film devices. These phenomena make VO2-based Mott insulator devices technologically relevant for various applications, such as memory selectors, logic switches, and building blocks for neuromorphic computing. Several groups have provisionally attributed the IMT switching to Joule heating. However, an electrothermal device simulation framework that self-consistently reproduces IMT phase transition, and in addition, explaining a variety of electrical/optical phenomena associated with IMT is still lacking. In this paper, we develop a self-consistent electrothermal device simulation framework which captures these key experimental attributes of IMT using VO2 as a model material. This framework will enable predictive modeling as well as provide insight on switching mechanisms and design of novel Mott insulator devices.

Memory Technology: Innovations needed for continued technology scaling and enabling advanced computing systems

Abstract: An increasing demand for data generation, storage, and intelligence generation from data is driving advances in memory technology and advanced computing applications. Memory performance is starting to define modern day computing in both mobile and server environments. There is an absolute need to continue the tremendous pace of memory technology improvements to deliver performance gains while managing the associated economics of scaling. In this paper, we present the current status of primary memory technology (DRAM and NAND) and their scaling path while highlighting the importance of emerging memory options – their shortcomings and advantages. We will also discuss the economics of scaling and need for continued innovation in memory technology and system enablement to deliver to diverse end application requirements.

Methods of forming field effect transistors; methods of forming DRAM circuitry

Abstract: Embodiments of the present invention provide methods of forming field effect transistors (FETs) that include at least partially forming a patterned transistor gate stack, at least partially defining a channel region therebeneath, and at least partially forming source/drain regions operably adjacent the gate stack and the channel region. Such embodiments include conducting one or more ion implantations through the at least partially formed gate stack and the at least partially formed source/drain regions to appropriately form Vt adjust regions within the channel regions and minority carrier barrier regions below formed, or to be formed, source/drain regions. Some embodiments of the present invention encompass forming such regions for memory FETs employed in DRAM or other memory circuitry.

Method of forming a memory device having a storage transistor

Abstract: A memory device and a method of forming the memory device. The memory device comprises a storage transistor at a surface of a substrate comprising a body portion between first and second source/drain regions, wherein the source/drain regions are regions of a first conductivity type. The storage transistor also comprises a gate structure that wraps at least partially around the body portion in at least two spatial planes. A bit line is connected to the first source/drain region and a word line connected to the gate structure. The memory device does not require an additional capacitive storage element.

Transistors and methods of forming transistors

Abstract: Some embodiments include a transistor having a drain region and a source region. A conductive gate is between the source and drain regions. First channel material is between the gate and the source region. The first channel material is spaced from the gate by one or more insulative materials. Second channel material is between the first channel material and the source region, and directly contacts the source region. The first and second channel materials are transition metal chalcogenide. One of the source and drain regions is a hole reservoir region and the other is an electron reservoir region. Tunnel dielectric material may be between the first and second channel materials.

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.