CMOS Temperature Sensor Using a PTAT-voltage biasing Common-source Amplifier with a Source-degeneration Polycrystalline Silicon Resistor

In the current paper, common source Low Noise Amplifier using inductively degenerated technique is designed to meet Radio Frequency (RF) range 2.45 GHz-2.85 GHz. The designed LNA is implemented using single and multi-finger transistor logic. The transistor geometry greater than 300 μm has been split into multiple fingers using multi-finger technology. The schematic is captured using ADS. The performance of LNA for various technologies has been analyzed using PTM 180 nm, PTM 130 nm and PTM 90 nm models. The amplifier with single transistor achieves minimum noise figure of 0.178 dB noise figure and maximum gain of 20.045 dB using 130 nm model technology for Bluetooth applications. Similarly 0.288 dB of minimum noise figure and peak gain of 17.971 dB are obtained using multi-finger MOSFET of PTM 90 nm technologyrespectively.The reverse isolation (S12) below -50 dB is achieved.

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Balun LNA Thermal Noise Analysis and Balancing With Common-Source Degeneration Resistor

IEEE Access ◽

10.1109/access.2020.2984314 ◽

2020 ◽

Vol 8 ◽

pp. 64949-64958 ◽

Cited By ~ 1

Author(s):

Qusai M. Abubaker ◽

Lutfi Albasha

Keyword(s):

Thermal Noise ◽

Noise Analysis ◽

Common Source ◽

Source Degeneration

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A High-linearity CMOS Temperature Sensor Using a PTAT-voltage Driving Common-source Amplifier with a Source Resistor

Procedia Engineering ◽

10.1016/j.proeng.2015.08.818 ◽

2015 ◽

Vol 120 ◽

pp. 1209-1212

Author(s):

Ying-Zong Jung ◽

Ruey-Lue Wang ◽

Hann-Huei Tsai ◽

Hsin-Hao Liao ◽

Yi-Fan Hao ◽

...

Keyword(s):

Temperature Sensor ◽

Common Source ◽

High Linearity

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Preparation of TEM samples by focused ion beams

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100138968 ◽

1995 ◽

Vol 53 ◽

pp. 518-519

Author(s):

John F. Walker ◽

J C Reiner ◽

C Solenthaler

Keyword(s):

Integrated Circuit ◽

Polycrystalline Silicon ◽

Field Effect Transistor ◽

High Spatial Resolution ◽

Ion Beam ◽

Ion Beams ◽

Focused Ion Beams ◽

Precise Location ◽

Effect Transistor ◽

Circuit Technology

The high spatial resolution available from TEM can be used with great advantage in the field of microelectronics to identify problems associated with the continually shrinking geometries of integrated circuit technology. In many cases the location of the problem can be the most problematic element of sample preparation. Focused ion beams (FIB) have previously been used to prepare TEM specimens, but not including using the ion beam imaging capabilities to locate a buried feature of interest. Here we describe how a defect has been located using the ability of a FIB to both mill a section and to search for a defect whose precise location is unknown. The defect is known from electrical leakage measurements to be a break in the gate oxide of a field effect transistor. The gate is a square of polycrystalline silicon, approximately 1μm×1μm, on a silicon dioxide barrier which is about 17nm thick. The break in the oxide can occur anywhere within that square and is expected to be less than 100nm in diameter.

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Interface morphology of thermal oxide grown on polycrystalline silicon by different processes

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100131619 ◽

1992 ◽

Vol 50 (2) ◽

pp. 1396-1397

Author(s):

H. Yen ◽

E. P. Kvam ◽

R. Bashir ◽

S. Venkatesan ◽

G. W. Neudeck

Keyword(s):

Integrated Circuits ◽

Polycrystalline Silicon ◽

Silicon Films ◽

Interface Morphology ◽

Oxide Interface ◽

Poly Silicon ◽

Thermal Oxide ◽

Grain Orientations ◽

Polycrystalline Silicon Films ◽

P Type

Polycrystalline silicon, when highly doped, is commonly used in microelectronics applications such as gates and interconnects. The packing density of integrated circuits can be enhanced by fabricating multilevel polycrystalline silicon films separated by insulating SiO2 layers. It has been found that device performance and electrical properties are strongly affected by the interface morphology between polycrystalline silicon and SiO2. As a thermal oxide layer is grown, the poly silicon is consumed, and there is a volume expansion of the oxide relative to the atomic silicon. Roughness at the poly silicon/thermal oxide interface can be severely deleterious due to stresses induced by the volume change during oxidation. Further, grain orientations and grain boundaries may alter oxidation kinetics, which will also affect roughness, and thus stress.Three groups of polycrystalline silicon films were deposited by LPCVD after growing thermal oxide on p-type wafers. The films were doped with phosphorus or arsenic by three different methods.

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Identifying groups of airborne particles by ordination

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100172012 ◽

1994 ◽

Vol 52 ◽

pp. 856-857

Author(s):

M. Shlepr ◽

C. M. Vicroy

Keyword(s):

Elemental Analysis ◽

Energy Dispersive Spectroscopy ◽

Manufacturing Process ◽

Spatial Representation ◽

Airborne Particles ◽

Common Source ◽

Data Set ◽

Microelectronics Industry ◽

Induced Changes ◽

Source Materials

The microelectronics industry is heavily tasked with minimizing contaminates at all steps of the manufacturing process. Particles are generated by physical and/or chemical fragmentation from a mothersource. The tools and macrovolumes of chemicals used for processing, the environment surrounding the process, and the circuits themselves are all potential particle sources. A first step in eliminating these contaminants is to identify their source. Elemental analysis of the particles often proves useful toward this goal, and energy dispersive spectroscopy (EDS) is a commonly used technique. However, the large variety of source materials and process induced changes in the particles often make it difficult to discern if the particles are from a common source.Ordination is commonly used in ecology to understand community relationships. This technique usespair-wise measures of similarity. Separation of the data set is based on discrimination functions. Theend product is a spatial representation of the data with the distance between points equaling the degree of dissimilarity.

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