International Business Machines Corporation

Globalfoundries Inc.

James H Stathis

Lawrence Alfred Clevenger

Theodorus E Standaert

Michael Rizzolo

Benjamin David Briggs

Nicholas Anthony Lanzillo

Barry P Linder

Baozhen Li

Peilin Song

Keith Aelwyn Jenkins

Franco Stellari

Ernest Y Wu

Emmanuel Yashchin

Alan Weger

Raphael Peter Robertazzi

Emily A Ray

Kevin Geoffrey Stawiasz

Eduard Albert Cartier

Wagdi William Abadeer

Griselda Bonilla

Kai Zhao

Roger Aime Dufresne

David G Brochu, Jr

One or more processors determine a predicted sorting bin of a semiconductor device, based on measurement and test data performed on the semiconductor device subsequent to a current metallization layer. A current predicted sorting bin and a target sorting bin are determined by a machine learning model for the semiconductor device; the target bin include higher performance semiconductor devices than the predicted sorting bin. The model determines a performance level improvement attainable by adjustments made to process parameters of subsequent metallization layers of the semiconductor device. Adjustments to process parameters are generated, based on measurement and test data of the current metallization layer of semiconductor device, and the adjustment outputs for the process parameters of the subsequent metallization layers of the semiconductor device are made available to the one or more subsequent metallization layer processes by a feed-forward mechanism.

Optimizating semiconductor binning by feed-forward process adjustment

Methods and systems of detecting chip degradation are described. A processor may execute a test on a device at a first time, where the test includes executable instructions for the device to execute a task under specific conditions relating to a performance attribute. The processor may receive performance data indicating a set of outcomes from the task executed by the device during the test. The processor may determine a first value of a parameter of the performance attribute based on the identified subset. The processor may compare the first value with a second value of the parameter of the performance attribute. The second value is based on an execution of the test on the device at a second time. The processor may determine a degradation status of the device based on the comparison of the first value with the second value.

Detection of performance degradation in integrated circuits

One or more processors determine a predicted sorting bin of a semiconductor device, based on measurement and test data performed on the semiconductor device subsequent to a current metallization layer. A current predicted sorting bin and a target soring bin are determined by a machine learning model for the semiconductor device; the target bin include higher performance semiconductor devices than the predicted sorting bin. The model determines a performance level improvement attainable by adjustments made to process parameters of subsequent metallization layers of the semiconductor device. Adjustments to process parameters are generated, based on measurement and test data of the current metallization layer of semiconductor device, and the adjustment outputs for the process parameters of the subsequent metallization layers of the semiconductor device are made available to the one or more subsequent metallization layer processes by a feed-forward mechanism.

Optimizing semiconductor binning by feed-forward process adjustment

A semiconductor device includes a device magnetic tunnel junction (MTJ) and sensor MTJs. A spin polarization of a free layer of the device MTJ is configurable based at least in part on electrical energy supplied to the device MTJ. A spin polarization of a corresponding free layer of each sensor MTJ is configurable based at least in part on a magnetic field created by the spin polarization of the free layer of the device MTJ. A circuit disposed is in electrical communication with the plurality of sensor MTJs and configured to determine the corresponding free layer spin polarizations of each of the sensor MTJs based at least in part on electrical energy supplied to the sensor MTJs by the circuit. The circuit is configured to determine a magnetoresistance of the device MTJ based at least in part on the determined corresponding free layer spin polarizations of the sensor MTJ.

Magnetic tunnel junction performance monitoring based on magnetic field coupling

An electrical device structure including a magnetic tunnel junction structure having a first tunnel junction dielectric layer positioned between a free magnetization layer and a fixed magnetization layer. A magnetization enhancement stack present on the magnetic tunnel junction structure. The magnetization enhancement stack includes a second tunnel junction layer that is in contact with the free magnetization layer of the magnetic tunnel junction structure, a metal contact layer present on the second tunnel junction layer, and a metal electrode layer present on the metal contact layer. A metallic ring on a sidewall of the magnetic enhancement stack, wherein a base of the metallic ring may be in contact with the free magnetization layer of the magnetic tunnel junction structure.

Magnetic tunnel junction with low series resistance

Embodiments of the invention are directed to a semiconductor wafer test system. A non-limiting example of the test system includes a controller, a sensing system communicatively coupled to the controller, and a stress source communicatively coupled to the controller. The controller is configured to control the stress source to deliver an applied stress to a targeted stress area of a semiconductor wafer. The sensing system is configured to detect the applied stress and provide data of the applied stress to the controller. The controller is further configured to control the stress source based at least in part on the data of the applied stress.

Accelerated wafer testing using non-destructive and localized stress

An electronic apparatus for testing an integrated circuit (IC) that includes a ring oscillator is provided. The apparatus configures the ring oscillator to produce oscillation at a first frequency and configures the ring oscillator to produce oscillation at a second frequency. The apparatus then compares the second frequency with an integer multiple of the first frequency to determine a resistive voltage drop between a voltage applied to the IC and a local voltage at the ring oscillator. The ring oscillator has a chain of inverting elements forming a long ring and a short ring. The ring oscillator also has an oscillation selection circuit that is configured to disable the short ring so that the ring oscillator produces a fundamental oscillation based on signal propagation through the long ring and enable the short ring so that the ring oscillator produces a harmonic oscillation based on a signal propagation through the short ring and the long ring.

Ring oscillator structures to determine local voltage value

A method and system are provided for chip testing. The method includes selectively deploying a chip for future use or discarding the chip to prevent the future use, responsive to a stress history of the chip determined using a non-destructive test procedure. The test procedure includes ordering each of a plurality of functional patterns by a respective minimum operating period corresponding thereto. The test procedure further includes ranking each of the plurality of patterns based on at least one preceding available pattern to provide a plurality of pattern ranks. The test procedure also includes calculating a sum by summing the plurality of pattern ranks. The sum calculated during an initial performance of the test procedure is designated as a baseline, and the sum calculated during a subsequent performance of the test procedure is compared to a threshold derived from the baseline to determine the stress history of the chip.

Non-destructive analysis to determine use history of processor

A method and system are provided for chip testing. The method includes ascertaining a baseline for a functioning chip with no stress history by performing a non-destructive test procedure on the functioning chip. The method further includes repeating the test procedure on a chip under test using a threshold derived from the baseline as a reference point to determine a stress history of the chip under test. The test procedure includes ordering each of a plurality of functional patterns by a respective minimum operating period corresponding thereto, ranking each pattern based on at least one preceding available pattern to provide a plurality of pattern ranks, and calculating a sum by summing the pattern ranks. The sum calculated by the ascertaining step is designated as the baseline, and the sum calculated by the repeating step is compared to the threshold to determine the stress history of the chip under test.

Methods and test structures for testing the reliability of a dielectric material. The test structure may include a first row of contacts and a line comprised of a conductor. The line is laterally spaced in a direction at a minimum distance from the first row of contacts. The test structure further includes a second row of contacts laterally spaced in the direction from the first row of contacts by a distance equal to two times a minimum pitch. The line is laterally positioned between the first row of contacts and the second row of contacts.

Test structures for dielectric reliability evaluations

Methods and systems determine an original statistical variance of an original failure distribution of a component (that is common to all chips tested) that occurs during manufacturing of wafers containing such chips. These methods and systems determine a first statistical variance of a reconstructed failure distribution, relative to sample size; and determine a second statistical variance of a mean time to failure of the component, relative to sample size. The first and second statistical variances are combined into a total reconstruction variance. Methods and systems determine whether the original statistical variance is less than the total reconstruction variance to identify whether the process of creating the reconstructed failure distribution can be used. Therefore, these methods and systems prohibit testing of the additional wafers manufactured using the specific wafer design and manufacturing process when on the original statistical variance is less than the total reconstruction variance.

Determining appropriateness of sampling integrated circuit test data in the presence of manufacturing variations

Embodiments relate to methods, computer systems and computer program products for performing a dielectric reliability assessment for an advanced semiconductor. Embodiments include receiving data associated with a test of a macro of the advanced semiconductor to a point of dielectric breakdown. Embodiments also include scaling the data for the macro down to a reference area and extracting a parameter for a Weibull distribution from the scaled down data for the reference area. Embodiments further include deriving a cluster factor (&#x3b1;) from the scaled down data for the reference area and projecting a failure rate for a larger area of the advanced semiconductor based on the extracted parameter, the cluster factor and the recorded data associated with the dielectric breakdown of the macro.

Dielectric reliability assessment for advanced semiconductors

An apparatus and method for evaluating the performance of a test dielectric material for use as a gate dielectric. The method comprises exposing a coated layer of the dielectric to a concentration of atomic hydrogen. The method may comprise (a) measuring an initial value of interface-state density in the test dielectric, (b) exposing the coated test dielectric to a concentration of atomic hydrogen in a remote plasma, and then (c) measuring a post-exposure value of interface-state density in the test dielectric. Steps (b) and (c) may be repeated with incrementally higher concentrations of atomic hydrogen to determine a rate of change in interface-state density value as a function of atomic hydrogen concentration, which may then be related to the projected charge-to-breakdown or time-to-breakdown of the test dielectric layer when the dielectric is used as the gate dielectric. The method may be conducted on a remote-plasma hydrogen exposure apparatus comprising, in series, a source of a mixture of molecular and atomic hydrogen gas; a particle remover adapted to remove energetic, charged particles; a light sink; a hydrogen recombination device; and a wafer exposure chamber.

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Poughquag, NY, United States of America

James H Stathis