Kla-tencor Technologies Corporation

Kla Tencor Corporation

Applied Spectral Imaging Ltd.

Tigi Ltd.

Kla Corporation

Ci Systems (israel) Ltd.

Kla-tenor Corp.

Ci Systems Ltd.

Michael E Adel

Mark Ghinovker

Ady Levy

Walter Dean Mieher

Vladimir Levinski

Michael Friedmann

Ian R Smith

John Fielden

Dan Wack

Daniel Kandel

Anatoly Fabrikant

Boris Golovanesky

Christopher F Bevis

Joel L Seligson

John Charles Robinson

Noah Bareket

Dario Cabib

Pavel Izikson

Chris Mack

Ellis Chang

Robert A Buckwald

Amir Widmann

Boris Golovanevsky

Nuriel Amir

Shimon Klier

Piotr S Zalicki

Paola Dececco

Amnon Manassen

Leonid Poslavsky

Thaddeus Gerard Dziura

Eran Amit

Mark Davis Smith

Kenneth P Gross

DongSub Choi

Dana Klein

Tal Itzkovich

Jorge Poplawski

Aviv Frommer

Boris Simkin

David Tulipman

Tal Shusterman

Roie Volkovich

Moshe E Preil

Barak Bringoltz

Liran Yerushalmi

Mark Wagner

Alexander Svizher

Tal Marciano

Myungjun Lee

Inna Tarshish-Shapir

Sharon Aharon

Chen Dror

Elyakim Kassel

Vidya Ramanathan

Janay Camp

John Madsen

Robert Peters

Zvika Klier

Royi Efron

Andrei V Shchegrov

Stilian Pandev

Yoel Feler

Allen Park

Kevin M Monahan

Kris Bhaskar

Daria Negri

Yuri Paskover

Guy Cohen

Yuval Lubashevsky

Ibrahim Abdulhalim

Jonathan M Madsen

Pradeep Subrahmanyan

Roel Gronheid

Eitan Hajaj

Tzahi Grunzweig

William Pierson

Songnian Rong

Evgeni Gurevich

David Wine

Mengmeng Ye

Paola deCecco

David Gready

Nadav Carmel

Dror Alumot

Moshe Baruch

Ben Tsai

Jeffrey Byers

Yaron Ish-Shalom

Sergey Borodyansky

Hoyoung Heo

Ori Tadmor

Ken Gross

Shiming Wei

Eitan Herzel

Brad Eichelberger

Eli Horn

Pati Sekula

Atsuhiko Kato

Avi Cohen

Noam Knoll

Metrology methods, modules and targets are provided, for measuring tilted device designs. The methods analyze and optimize target design with respect to the relation of the Zernike sensitivity of pattern placement errors (PPEs) between target candidates and device designs. Monte Carlo methods may be applied to enhance the robustness of the selected target candidates to variation in lens aberration and/or in device designs. Moreover, considerations are provided for modifying target parameters judiciously with respect to the Zernike sensitivities to improve metrology measurement quality and reduce inaccuracies.

Metrology target design for tilted device designs

Metrology target design methods and verification targets are provided. Methods comprise using OCD data related to designed metrology target(s) as an estimation of a discrepancy between a target model and a corresponding actual target on a wafer, and adjusting a metrology target design model to compensate for the estimated discrepancy. The dedicated verification targets may comprise overlay target features and be size optimized to be measureable by an OCD sensor, to enable compensation for inaccuracies resulting from production process variation. Methods also comprise modifications to workflows between manufacturers and metrology vendors which provide enable higher fidelity metrology target design models and ultimately higher accuracy of metrology measurements.

Verification metrology targets and their design

Methods are provided for designing metrology targets and estimating the uncertainty error of metrology metric values with respect to stochastic noise such as line properties (e.g., line edge roughness, LER). Minimal required dimensions of target elements may be derived from analysis of the line properties and uncertainty error of metrology measurements, by either CDSEM (critical dimension scanning electron microscopy) or optical systems, with corresponding targets. The importance of this analysis is emphasized in view of the finding that stochastic noise may have increased importance with when using more localized models such as CPE (correctables per exposure). The uncertainty error estimation may be used for target design, enhancement of overlay estimation and evaluation of measurement reliability in multiple contexts.

Determining the impacts of stochastic behavior on overlay metrology data

The disclosure is directed to designing and using an overlay target with orthogonal underlayer dummyfill. According to various embodiments, an overlay target may include one or more segmented overlay pattern elements forming at least one overlay target structure. The overlay target may further include one or more inactive pattern elements forming at least one dummyfill target structure. Each of the one or more inactive pattern elements may include dummyfill segmented along an axis orthogonal to a segmentation axis of at least one proximately disposed overlay pattern element. In some embodiments, each of the target structures or layers may be formed from a separate process layer successively disposed upon a substrate, such as a silicon wafer. In some embodiments, the overlay and dummyfill target structures may be twofold or fourfold rotationally symmetric to allow for certain manufacturing or metrology advantages.

Overlay targets with orthogonal underlayer dummyfill

Metrology methods and modules are provided, which comprise carrying out recipe setup procedure(s) and/or metrology measurement(s) using zonal analysis with respect to respective setup parameter(s) and/or metrology metric(s). The zonal analysis comprises relating to spatially variable values of the setup parameter(s) and/or metrology metric(s) across one or more wafers in one or more lots. Wafer zones may be discrete or spatially continuous, and be used to weight one or more parameter(s) and/or metric(s) during any of the stages of the respective setup and measurement processes.

Recipe optimization based zonal analysis

Systems and method are provided for analyzing target, process and metrology configuration sensitivities to a wide range of parameters, according to external requirements or inner development and verification needs. Systems comprise the following elements. An input module is arranged to receive parameters relating to targets, target metrology conditions and production processes, to generate target data. A metrology simulation unit is arranged to simulate metrology measurements of targets from the target data and to generate multiple metrics that quantify the simulated target measurements. A sensitivity analysis module is arranged to derive functional dependencies of the metrics on the parameters and to define required uncertainties of the parameters with respect to the derived functional dependencies. Finally, a target optimization module is arranged to rank targets and target metrology conditions with respect to the simulated target measurements.

Target and process sensitivity analysis to requirements

Metrology target design methods and verification targets are provided. Methods include using OCD data related to designed metrology target(s) as an estimation of a discrepancy between a target model and a corresponding actual target on a wafer, and adjusting a metrology target design model to compensate for the estimated discrepancy. The dedicated verification targets may include overlay target features and be size optimized to be measurable by an OCD sensor, to enable compensation for inaccuracies resulting from production process variation. Methods also include modifications to workflows between manufacturers and metrology vendors which provide enabled higher fidelity metrology target design models and ultimately higher accuracy of metrology measurements.

Verification metrology target and their design

Metrology targets and target design methods are provided, in which target elements are defined by replacing elements from a periodic pattern having a pitch p, by assist elements having at least one geometric difference from the replaced elements, to form a composite periodic structure that maintains the pitch p as a single pitch. Constructing targets within the bounds of compatibility with advanced multiple patterning techniques improves the fidelity of the targets and fill factor modulation enables adjustment of the targets to produce sufficient metrology sensitivity for extracting the overlay while achieving process compatibility of the targets.

Process compatibility improvement by fill factor modulation

Disclosed is a method for determining an overlay error between at least two layers in a multiple layer sample. An imaging optical system is used to measure multiple measured optical signals from multiple periodic targets on the sample, and the targets each have a first structure in a first layer and a second structure in a second layer. There are predefined offsets between the first and second structures A scatterometry overlay technique is used to analyze the measured optical signals of the periodic targets and the predefined offsets of the first and second structures of the periodic targets to thereby determine an overlay error between the first and second structures of the periodic targets. The scatterometry overlay technique is a phase based technique, and the imaging optical system is configured to have an illumination and/or collection numerical aperture (NA) and/or spectral band selected so that a specific diffraction order is collected and measured for the plurality of measured optical signals. In one aspect, the number of periodic targets equals half the number of unknown parameters.

Apparatus and methods for detecting overlay errors using scatterometry

A process control system may include a controller configured to receive after-development inspection (ADI) data after a lithography step for the current layer from an ADI tool, receive after etch inspection (AEI) overlay data after an exposure step of the current layer from an AEI tool, train a non-zero offset predictor with ADI data and AEI overlay data to predict a non-zero offset from input ADI data, generate values of the control parameters of the lithography tool using ADI data and non-zero offsets generated by the non-zero offset predictor, and provide the values of the control parameters to the lithography tool for fabricating the current layer on the at least one production sample.

Overlay control with non-zero offset prediction

A semiconductor fabrication system includes a target design device and a multi-stage fabrication tool configured to fabricate one or more layers of a sample using the fabrication process. The target design device receives metrology design rules associated with a metrology tool in which the metrology design rules include criteria for one or more physical attributes of metrology targets measurable with the metrology tool. The target design device may further receive process design rules associated with a fabrication process in which the process design rules include criteria for determining process stages of the fabrication process required to fabricate structures with selected physical attributes. The target design device may further generate a target design library including a plurality of metrology targets that satisfy the metrology design rules for the metrology tool and the process design rules for the fabrication process, wherein the target design library includes specifications for fabricating the plurality of metrology targets using two or more process stages of the fabrication process based on the process design rules.

Metrology target identification, design and verification

A system for solar assisted water heating provides hot water to a user at a lower cost, higher energy efficiency, and with a quicker response time than conventional systems, reducing energy losses, and improving user comfort. The basic architecture includes four main components: a solar collector, a heat exchanger, an in-line heater, and a control system. A transient heat profile of a first temperature in a primary loop is measured while a first flow generator Gis active for the primary loop. Solar assisted heating of water in a secondary loop is provided based on: a flow of water in the secondary loop; a current first temperature; and the transient heat profile of the first temperature by activating: the first flow generator in the primary loop and an in-line water heater in the secondary loop.

In-line heated solar thermal storage collector

Method, metrology modules and RCA tool are provided, which use the behavior of resonance region(s) in measurement landscapes to evaluate and characterize process variation with respect to symmetric and asymmetric factors, and provide root cause analysis of the process variation with respect to process steps. Simulations of modeled stacks with different layer thicknesses and process variation factors may be used to enhance the analysis and provide improved target designs, improved algorithms and correctables for metrology measurements. Specific targets that exhibit sensitive resonance regions may be utilize to enhance the evaluation of process variation.

Analyzing root causes of process variation in scatterometry metrology

It is provided a solar energy module for converting solar radiation to thermal energy. The module includes a thermally insulating element transmissive to solar radiation and having low transmissivity to thermal infra-red radiation, an absorbing element, a sealed enclosure, and a variable portion in the envelope of the sealed enclosure. This portion is adapted for varying the volume available to gas enclosed in the enclosure in accordance with changing temperature of the enclosed gas. Also, it is provided a solar energy module which includes a thermally insulating element, an absorbing surface and liquid pipes for absorbing the solar radiation, and an air duct thermally coupled thereof. The heated liquid and the heated air are usable for a variety of thermal applications. A heat storage may be thermally coupled to the absorbing surface and to the liquid pipes. The air duct has several air valves, and is associated with a controller for regulating air flow through the air duct. The controller may regulate heat flow in accordance with an optimization program, receiving inputs from several sources, like a sensor monitoring a building, a sensor monitoring the solar energy module, and an environment sensor.

Solar thermal collecting system

Methods and metrology tool modules embodying the methods are provided. Methods comprise measuring characteristics of intermediate features such as guiding lines in a directed self-assembly (DSA) process, deriving exposure parameters from the measured characteristics; and adjusting production parameters for producing consecutive target features according to the derived exposure parameters. The methods and modules enhance the accuracy of the DSA-produced structures and related measurements.

On-product derivation and adjustment of exposure parameters in a directed self-assembly process

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Zichron Yaakov, Israel

Michael E Adel