A new test structure for the detection and localization of short and open defects in large-scale integrated intralayer wiring processes is proposed. In the structure, an open-monitoring element in the first metal layer meanders around lines of short-monitoring elements placed in contact with N-type diffusion regions to make the structure compact. The proposed structure allows defective test structures to be screened through electrical measurements and killer defects to be localized through voltage contrast or optical microscopy methods.

An advanced defect-monitoring test structure for electrical screening and defect localization

A characterization vehicle includes a substrate having at least one layer (300), and a plurality of pairs of nested serpentine lines on a single surface of a single layer of the substrate (301a...301h, 302a...302h), each pair of nested serpentine lines having a shared pad between them (312a...312h).

Extraction method of defect density and size distributions

A test chip (200) comprises at least one level having an array of regions (201). Each region (201) is capable of including at least one test structure (202). At least some of the regions (201) include respective test structures (202). The level has a plurality of driver lines (D1-D5) that provide input signals to the test structures (202). The level has a plurality of receiver lines (R1-R8) that receive output signals from the test structures (202). The level has a plurality of devices for controlling current flow. Each test structure (202) is connected to at least one of the driver lines with a first one of the devices in between. East test structure is connected to at least one of the receiver lines (R1-R8) with a second one of the devices in between, so that each of the test structures (202) can be individually addressed for testing using the driver lines (D1-D5) and receiver lines (R1-R8).

Method and configuration for connecting test structures or line arrays for monitoring integrated circuit manufacturing

The design methodology called design for manufacturing (DFM) includes a set of techniques to modify the design of ICs in order to make them more manufacturable, i.e. to improve their functional yield, parametric yield, or reliability. Traditionally DFM in the prenanometer era consisted of different methodologies aimed at relaxing the mask layout shapes of an IC at the full chip level in order to minimize its failure probability, for example, increasing the feature spacing and width, and adding redundant contacts and vias where possible.

/pdf/an-effective-dfm-strategy-requires-accurate-process-and-ip-283gfn2ak5.pdf

An effective DFM strategy requires accurate process and IP pre-characterization

The authors propose a new accurate yield prediction method for system-LSI embedded memories to improve the productivity of chips. Their new method is based on the failure-related yield prediction method in which failure bits in memory are tested to see whether they are repairable or not by using built-in redundancies. The important concept of the new method is called "repairable matrix'' (RM). In RM, rm/sub ij/=1 means that i row redundancy sets and j column redundancy sets are needed for repair, where rm/sub ij/ is an element of the matrix. Here, RM can indicate all the candidate combinations of the number of row and column redundancy sets for repair. The new yield prediction method using RM solves two problems, "asymmetric repair'' and "link set.'' These have a significant effect on accurate yield prediction but have not yet been approached by conventional analytical methods. The calculation of yield by the new method is demonstrated in two kinds of advanced memory devices that have different design rules, failure situations, and redundancy designs. The calculated results are consistent with the actual yield. On average, the difference in accuracy between the new method and conventional analytical methods is about 5%.

/pdf/a-new-accurate-yield-prediction-method-for-system-lsi-5d93n7xayj.pdf

A new accurate yield prediction method for system-LSI embedded memories

Defect inspection is required for process control and to enhance chip yield. Electrical measurements of test structures are commonly used to detect faults. To improve accuracy of electrically based determination of defect densities and defect size distributions, we present a novel NEST structure. There, many nested serpentine lines will be placed within a single layer only. This mask will be used as a short flow to guarantee a short turn around time for fast process data extraction. Data analysis procedures will provide densities and size distributions of killer defects that will have an impact on product chip yield.

/pdf/fast-extraction-of-defect-size-distribution-using-a-single-ytupkdazrr.pdf

Fast extraction of defect size distribution using a single layer short flow NEST structure

Fast extraction of killer defect density and size distribution using a single layer short flow NEST structure

Handle everyday research tasks with reliable, citation-backed results

Your personal Research Agent to handle research tasks with citation-backed results

Popular Tasks used by Researchers

How can I help with your research?

Meet SciSpace

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

D. Stashower

Author Tools

Chat about Author

Papers

Fast extraction of defect size distribution using a single layer short flow NEST structure

Fast extraction of killer defect density and size distribution using a single layer short flow NEST structure