Published December 5, 2008 | Version v1
Journal article

Ab initio calculations of phosphorus and arsenic clustering parameters for the improvement of process simulation models

  • 1. Integrated Systems Laboratory, ETH Zurich, Gloriastrasse 35, 8092 Zurich (Switzerland)
  • 2. Synopsys Switzerland LLC, Affolternstrasse 52, 8050 Zurich (Switzerland)

Description

We present the results of extensive ab initio simulations for phosphorus clusters, arsenic clusters and mixed phosphorus/arsenic clusters in silicon. The specific defects and the parameters that are investigated are selected according to the needs of state-of-the-art diffusion and activation models, taking into account the availability of experimental data, the capabilities of current ab initio methods and the requirements for advanced technology development. The calculated binding energies are used to determine a good starting point for the calibration of a new clustering model implemented in an atomistic process simulator. The defect species V, I, P, PV, PI, As, AsV, AsI and clusters containing up to four dopant atoms and up to one V or I are considered in all relevant charge states. The ab initio results are discussed as well as the challenges arising in the transfer of this information into the process simulation model

Availability note (English)

Available from http://dx.doi.org/10.1016/j.mseb.2008.09.047

Additional details

Identifiers

DOI
10.1016/j.mseb.2008.09.047;
PII
S0921-5107(08)00404-2;

Publishing Information

Journal Title
Materials Science and Engineering. B, Solid-State Materials for Advanced Technology
Journal Volume
154-155
Journal Page Range
p. 193-197
ISSN
0921-5107
CODEN
MSBTEK

Conference

Title
Symposium I: Front-end junction and contact formation in future silicon/germanium based devices
Acronym
EMRS 2008 spring meeting
Dates
26-30 May 2008
Place
Strasbourg (France)

INIS

Country of Publication
Netherlands
Country of Input or Organization
International Atomic Energy Agency (IAEA)
INIS RN
40085789
Subject category
S36: MATERIALS SCIENCE;
Resource subtype / Literary indicator
Numerical Data
Descriptors DEI
ARSENIC; AVAILABILITY; BINDING ENERGY; CALIBRATION; CHARGE STATES; CLUSTER MODEL; DEFECTS; EXPERIMENTAL DATA; MOLECULAR CLUSTERS; PHOSPHORUS; SILICON; SIMULATION
Descriptors DEC
DATA; ELEMENTS; ENERGY; INFORMATION; MATHEMATICAL MODELS; NONMETALS; NUCLEAR MODELS; NUMERICAL DATA; SEMIMETALS

Optional Information

Copyright
Copyright (c) 2008 Elsevier Science B.V., Amsterdam, The Netherlands, All rights reserved.