System CDM Modeling for High-Speed Interface Devices

Conventional simulation methods for Charged Device Model (CDM) peak current estimation, based on separate tester and IC lumped-element models, fail to capture fast transient phenomena at ultra-high-speed interfaces. A more comprehensive modeling approach, including on-die and package distributed parasitics, yields better predictive capabilities with respect to CDM qualification test results.

Authors

K. Domański (ORCID: https://orcid.org/0000-0002-9741-0588)
Brett Carn
Jian Gong (ORCID: https://orcid.org/0000-0001-5786-713X)
Ralf Brederlow (ORCID: https://orcid.org/0000-0002-8118-757X)
Harald Goßner (ORCID: https://orcid.org/0000-0002-6280-3613)
V. Zia
Emanuele Groppo
Raj Dua

Institutions

Intel (United States) (US)
Intel (Germany) (DE)
Mission College (US)
Technical University of Munich (DE)

Publication Details

Published: 2024-09-16
DOI: https://doi.org/10.23919/eos/esd61719.2024.10702134
Citations: 2
Primary Topic: 3D IC and TSV technologies
Type: article
Field-Weighted Citation Impact: 0.42

Controls

|||

ALL TIME

JAN

FEB

MAR

APR

MAY

JUN

JUL

AUG

SEP

OCT

article

System CDM Modeling for High-Speed Interface Devices

K. Domański, Brett Carn, Jian Gong, Ralf Brederlow et al.

Sep 16, 2024

2 citations

3D IC and TSV technologies

0.42

article

System CDM Modeling for High-Speed Interface Devices

K. Domański, Brett Carn, Jian Gong, Ralf Brederlow, Harald Goßner, V. Zia, Emanuele Groppo, Raj Dua

September 16, 2024article en

2 citations

Abstract

Conventional simulation methods for Charged Device Model (CDM) peak current estimation, based on separate tester and IC lumped-element models, fail to capture fast transient phenomena at ultra-high-speed interfaces. A more comprehensive modeling approach, including on-die and package distributed parasitics, yields better predictive capabilities with respect to CDM qualification test results.

Intel (United States) (US), Intel (Germany) (DE), Mission College (US), Technical University of Munich (DE)

Affordable and clean energy

Openalex Percentile: Top 37%

3D IC and TSV technologies

0.42

DOI Source OpenAlex

AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.