Agere Systems Inc.

Agere Systems Guardian Corp.

Lucent Technologies Inc.

Erik Cho Houge

John Martin McIntosh

Catherine B Vartuli

Larry E Plew

Fred Anthony Stevie

Michael J Antonell

Jeffrey Bruce Bindell

Terri Lynn Shofner

Frederick A Stevie

Scott Jessen

Kim Elshot

Tingkwan Cheung

Nitin Patel

Ryan Keith Maynard

Simon John Molloy

Isik C Kizilyalli

Brittin C Kane

Edward Rietman

Robert Francis Jones

Darrell L Simpson

Jennifer Lynn Drown

Jennifer A Antonell

Jennifer Juszczak

Steven Barry Valle

Brian Kempshall

Mike Antonell

Jennifer Lynne Drown

Pam Cavanagh

Stephen M Schwarz

Hui Ma

A system () for monitoring and controlling a fabrication process includes at least a first subsystem (), a crystallographic analysis subsystem (), and a second subsystem (), wherein the first subsystem and second subsystem perform respective fabrication steps on a workpiece. The crystallographic analysis subsystem may be coupled to both the first subsystem and second subsystem. The analysis subsystem acquires crystallographic information from the workpiece after the workpiece undergoes a fabrication step by the first subsystem and then provides information, based on the crystallographic information acquired, for modifying parameters associated with the respective fabrication steps. The system may also include neural networks () to adaptively modify, based on historical process data (), parameters provided to the respective fabrication steps. The analysis subsystem may include a electromagnetic source (), a detector (), a processor (), a controller () and a scanning actuator ().

Monitoring and control of a fabrication process

A system () for crystallography including a sample holder (), an electron source () for generating an electron beam, and a scanning actuator () for controlling the relative movement between the electron beam and the crystalline sample, the scanning actuator being controllable for directing the electron beam at a series of spaced apart points within the sample area. The system also includes an image processor () for generating crystallographic data based upon electron diffraction from the crystalline sample and for determining whether sufficient data have been acquired to characterize the sample area. The system further includes a controller () for controlling the scanning actuator to space the points apart such that acquired data is representative of a different grains within the crystalline sample. IN other embodiments, the invention includes one or more ion beams () for crystallography and a combination ion beam/electron beam ().

Crystallographic metrology and process control

A chemical mechanical polishing (CMP) process using a chemically active slurry having a polarity selected to affect the relative oxidation rates of respective crystalline planes of a polycrystalline surface being polished. The slurry polarity is controlled to equilibrate the material removal rates from the respective crystalline planes during the CMP process. A polar solute may be added to a base solvent to achieve the desired polarity. A CMP process for a tungsten film may utilize a water-based slurry containing an abrasive agent, an oxidizing agent, and a solute having a polarity less than that of water. The abrasive agent may be colloidal silica, the oxidizing agent may be hydrogen peroxide, and the solute may be benzene.

Chemical mechanical polishing of dual orientation polycrystalline materials

The present invention provides a method for detecting defects in a material and a system for accomplishing the same. The method includes obtaining an image of at least a portion of a material's surface and converting the image into an intensity profile. The method further includes determining a defect in the material's surface from the intensity profile. In one exemplary embodiment, the image is an electron image obtained using a scanning electron microscope. The method may further be used to determine a defect density in the material's surface.

Method for detecting defects in a material and a system for accomplishing the same

The present invention provides and apparatus and method for scanning a crystalline sample comprising a sample holder, an electron source for generating an electron beam and a scanning actuator for controlling the relative movement between the electron beam and the crystalline sample. In addition, an image processor is provided for processing images from electrons from the crystalline sample and a controller for controlling the scanning actuator to space points on the crystalline sample, at which the electron beam is directed. The points are preferably spaced apart a distance that is at least as large as a known grain size of the crystalline sample. The controller determines a grain orientation with respect to each point within a series of points within a scan area of the crystalline sample. The controller determines an average grain orientation for the crystalline sample for current image and a previously processed image. The controller monitors a variance in the average deviation and terminates the scanning when the variance in the average grain orientation approaches a predetermined value.

Apparatus for scanning a crystalline sample and associated methods

The present invention for a method and apparatus for detection of chemical mechanical planarization endpoint and device planarity comprises imparting at least one variation of an atomic mass of at least one material within the layer. The variation of the atomic mass within the layer is indicative of the layer thickness. The removal of the layer is monitored by detecting the variation in the atomic mass, and/or a change in concentration of the at least one material, during removal of the layer. Once the concentration of the material reaches a minimum threshold, or an atomic mass is detected at a minimum intensity, within a predetermined time duration, the removal of the layer is terminated. The variation in atomic mass, and/or concentration of materials within the layer is used to measure a planarity of the device.

Method and apparatus for detection of chemical mechanical planarization endpoint and device planarity

A method and apparatus used to calibrate high-resolution electron microscopes where a single standard provides multiple samples, each having a different atomic structure, permits rapid accurate calibration of the entire range of magnifications. The different atomic structure dimensions possess known reference measurement data. The S/TEM is adjusted to focus onto the crystal lattice structure of each sample in a selected sequence. Measurements of these lattice spacings are compared to known dimensions. If S/TEM measurements do not agree with the lattice spacing dimensions, the S/TEM magnification is adjusted to reflect known dimensions. Typical standard exchange and associated processing steps are eliminated by the use of the single standard comprising of a plurality of samples.

Calibration standard for high resolution electron microscopy

A probe comprising a probe body having a body longitudinal axis and a shoulder, and a microstylet mechanically coupled to the shoulder, and a method of manufacturing the same. The microstylet extends from the shoulder and has a microstylet longitudinal axis coincident the body longitudinal axis with the microstylet having a cross section substantially smaller than a cross section of the probe body.

Probe having a microstylet

A manufacturing method using a modular substrate-based processing scheme for producing semiconductor devices, provides multiple modular processing units which may be arranged together to form any of various cohesive processing units or individually or sequentially processed through standard semiconductor processing equipment. The cohesive processing units are processed unitarily providing for multiple modular processing units to be processed simultaneously. The modular processing units may be formed of a thick semiconductor substrate or a semiconductor substrate mounted on a further substrate such as a ceramic material. The modular processing units may each contain ribs, grooves, posts or other features to aid in handling and placement of the individual units.

Semiconductor manufacturing using modular substrates

A system and method of metrology ( ) whereby a three dimensional shape profile is defined ( ) for a surface feature on a substrate by applying ( ) a transform function F(x) to an image intensity map I(x,y) obtained ( ) by inspecting the substrate with a scanning electron microscope ( ). The transform function F(x) is developed ( ) by correlating the image intensity map of a first wafer ( ) to a height vector ( ) obtained by inspecting the first wafer with a more accurate metrology tool, for example a stylus nanoprofilometer ( ). A simple ratio-based transform may be used to develop F(x). An asymmetric multiple parameter characterization of the three dimensional shape profile may be developed ( ) by plotting critical space and width dimensions (S , S , W , W ) from a vertical axis (C&mdash;C) as a function of height of the feature.

Three dimensional reconstruction metrology

A semiconductor manufacturing automation method for analyzing a patterned feature formed on a semiconductor layer is disclosed. At least one patterned feature is scanned to generate an amplitude modulated waveform signal of the line and neighboring space characteristics. Signal processing is automatically performed on this waveform by an in-line computational source to extract known patterned features based on the profile of the amplitude modulated waveform signal. The extracted waveform segments are subjected to known geometric shapes to determine if the waveform indicates a normal or abnormal patterned feature on a semiconductor layer.

Abnormal photoresist line/space profile detection through signal processing of metrology waveform

A method and apparatus for minimizing the surface contamination of semiconductor wafers ( ) during the semiconductor device manufacturing process. Semiconductor wafers ( ) are stored in a storage cassette ( ) with their face sides ( ) facing downward and their back sides ( ) facing upward. Particulate contamination present on the back sides of the wafers is thereby secured to the wafers by the force of gravity, and the faces of the wafers are shielded from falling debris. An automated wafer handling device ( ) is provided with a rotary joint ( ) to accomplish the wafer flipping motion before inserting a wafer into a cassette and after removing the wafer from the cassette.

Method and apparatus for minimizing semiconductor wafer contamination

In-line process control for 120 nm and 100 nm lithography using the installed scanning electron microscope (SEM) equipment base. A virtual three-dimensional representation of a photoresist feature is developed by applying a transform function to SEM intensity data representing the feature. The transform function correlates highly accurate height vector data, such as provided by a stylus nanoprofilometer or scatterometer, with the highly precise intensity data from the SEM. A multiple parameter characterization of at least one critical dimension of the virtual feature is compared to an acceptance pattern template, with the results being used to control a downstream etch process or an upstream lithography process. A multiple parameter characteristic of a three dimensional representation of the resulting post-etch final feature may be compared to device performance data to further refine the acceptance pattern template.

Process control using three dimensional reconstruction metrology

An integrated metrology and lithography/etch system and method ( ) for micro-electronics device manufacturing. A process control neural network ( ) is used to develop an estimated process control parameter ( ) for controlling an etching process ( ). The process control neural network is responsive to a multi-parameter characterization of a patterned resist feature MPC(PR) ( ) developed on a substrate. The process control parameter is used as a feed-forward control for the etching process to develop an actual final mask feature. A multi-parameter characterization of the actual final mask feature MPC(HM) ( ) is used as an input to a training neural network ( ) for mapping to an ideal process control parameter. The ideal process control parameter is compared to the estimated control parameter to develop an error parameter ( ), which is then used to train the process control neural network.

Control of semiconductor processing

The present invention relates to a device for testing particles for composition and concentration. The device includes a particle counter, a collector screen, and a mass spectrometer. In one embodiment, the collector screen is positioned to receive particles received by the particle counter, and the mass spectrometer is positioned to receive counted particles retained on the collector screen.

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Orlando, FL, United States of America

Erik Cho Houge