Lithographers had hoped that single patterning would be enabled at the 20nm node by way of EUV lithography. However, due to delays in EUV readiness, double patterning with 193i lithography is currently relied upon for volume production for the 20nm node’s metal 1 layer. At the 14nm and likely at the 10nm node, LE-LE-LE triple patterning technology (TPT) is one of the favored options [1,2] for patterning local interconnect and Metal 1 layers. While previous research has focused on TPT for contact mask, metal layers offer new challenges and opportunities, in particular the ability to decompose design polygons across more than one mask. The extra flexibility offered by the third mask and ability to leverage polygon stitching both serve to improve compliance. However, ensuring TPT compliance – the task of finding a 3-color mask decomposition for a design – is still a difficult task. Moreover, scalability concerns multiply the difficulty of triple patterning decomposition which is an NP-complete problem. Indeed previous work shows that network sizes above a few thousand nodes or polygons start to take significantly longer times to compute [3], making full chip decomposition for arbitrary layouts impractical. In practice Metal 1 layouts can be considered as two separate problem domains, namely: decomposition of standard cells and decomposition of IP blocks. Standard cells typically include only a few 10’s of polygons and should be amenable to fast decomposition. Successive design iterations should resolve compliance issues and improve packing density. Density improvements are multiplied repeatedly as standard cells are placed multiple times. IP blocks, on the other hand, may involve very large networks. This paper evaluates multiple approaches to triple patterning decomposition for the Metal 1 layer. The benefits of polygon stitching, in particular, the ability to resolve commonly encountered non-compliant layout configurations and improve packing density, are weighed against the increased difficulty in finding an optimized, legal decomposition and coping with the increased scalability challenges.
Exploratory prototype DfM tools, methodologies and emerging physical process models are described. The examples
include new platforms for collaboration on process/device/circuits, visualization and quantification of manufacturing
effects at the mask layout level, and advances toward fast-CAD models for lithography, CMP, etch and photomasks. The
examples have evolved from research supported over the last several years by DARPA, SRC, Industry and the Sate of
California U.C. Discovery Program. DfM tools must enable complexity management with very fast first-cut accurate
models across process, device and circuit performance with new modes of collaboration. Collaborations can be promoted
by supporting simultaneous views in naturally intuitive parameters for each contributor. An important theme is to shift
the view point of the statistical variation in timing and power upstream from gate level CD distributions to a more
deterministic set of sources of variations in characterized processes. Many of these nonidealities of manufacturing can be
expressed at the mask plane in terms of lateral impact functions to capture effects not included in design rules. Pattern
Matching and Perturbation Formulations are shown to be well suited for quantifying these sources of variation.
A multi-student testchip aimed at characterizing lithography related variations with over 15,000 individually probable
test structures and transistors has been designed and a complementary 65nm process flow and data aggregation strategy
have also been implemented. Test structures have been strategically designed to have high sensitivities to non-idealities
such as defocus, LWR, misalignment and other systematic sources of variation. To enable automated measurement of
massive amounts of test structures, Enhanced Transistor Electrical CD (Critical Dimension) metrology has been used as
it offers high pattern density and almost no geometrical restrictions. Electrical testing at cryogenic temperatures will be
employed to study the impact of Line Width Roughness (LWR) versus Random Dopant Fluctuations (RDF), which will
not play a significant role at cryogenic temperatures, 4K. To facilitate data analysis and comparison of results between
students, a relational database has been designed and implemented. The database will be web accessible for each student
to use and update. It will serve as a collaborative platform for reinforcing conclusions, filtering out confounding data,
and involving outside parties that are interested in process variations at the 65nm node. Experimental data was not
available at the time this paper was written, so this paper will concentrate on the design and simulation results of test
structures.
Circuit performance variability is significantly impacted by variations in gate length caused in microlithographic
pattern transfer [1]. Previous studies [2] have shown through simulation that by completely reconciling sources of
deterministic variation, long-range (millimeter separation scale) spatial correlation in the remaining variation is virtually
zero. To complete the model for spatial variation and correlation in critical dimension (CD), a new set of electrical
linewidth metrology (ELM) test structures were then designed to target the sub-mm regime [3]. In this work, we report
measurement results from those micron-scale ELM test structures. The micron-scale (0.2μm to 1.15mm) variation can be
decomposed into a very large chip-to-chip component, a small and systematic density-dependent component, and a small
random component; spatial correlation in gate length for the micron-scale regime is negligible.
The growing impact of process variation on circuit performance requires statistical design approaches in which circuits
are designed and optimized subject to an estimated variation. Previous work [1] has shown that by including extra
margins in each of the gate delays and optimizing the gate sizes, the circuit delay variation can be reduced by half. Our
work goes further by deploying extended models that include delay variations due to Vth and Leff, as well as position
dependant variation. Two types of models have been proposed to account for various variations: 1) a model that
explicitly adds spatial correlation terms to the design objective; 2) a model that implicitly includes such effect through
the use of a modified version of Pelgrom's model. These design models are used to size a 32-bit Ladner-Fischer adder
and the circuit delay distributions are obtained from Monte Carlo simulations. The analysis shows that both types of
models have a noticeable performance improvements over the model presented in [1]. In addition, the second model
appears to be a more adequate method for modeling various variation components and has a better performance over the
first model; the drawback is a more complicated object function.
Systematic gate length variations caused by microlithographic processing [1] have a significant impact on the variability of circuit performance. In this work, rigorous simulation shows the importance of proper spatial modeling. More specifically, the Monte Carlo framework used in [2] has been recast into an analytical macromodel-based Matlab framework. With accuracy in the 2% range, this analytical model allows for much faster critical path variability analysis. The analytical framework has been used to evaluate the assumptions made about the structure of spatial variation in [2]. It has been shown that a more rigorously-defined nested variance model of spatial variation yields substantially different circuit performance variability results. To further establish the nature of spatial variation in the sub-mm regime, a new set of electrical linewidth metrology (ELM) test structures is proposed. These ELM structures enable the measurement of critical dimensions of neighboring polysilicon lines packed at maximum density. Dummy lines may also be inserted between the measurable polysilicon lines, allowing for measurement of near-neighbor lines and thereby increasing the total measurable range. With the fine granularity and wide range of these test structures, spatial variation and correlation in the separation range of 0.2μm to 1.0mm can be measured.
KEYWORDS: Process control, Critical dimension metrology, Monte Carlo methods, Lithography, Manufacturing, Data modeling, Metrology, Semiconducting wafers, Performance modeling, Device simulation
Pelgrom's model suggests that a spatial correlation structure is inherent in the physical properties of semiconductor devices; specifically, devices situated closely together will be subject to a higher degree of correlation than devices separated by larger distances. Since correlation of device gate length values caused by systematic variations in microlithographic processing is known to carry a significant impact on the variability of circuit performance, we attempt to extract and understand the nature of spatial correlation across an entire die. Based on exhaustive, full-wafer critical dimension measurements collected using electrical linewidth metrology for wafers processed in a standard 130nm lithography cell, we calculate a spatial correlation metric of gate length over a full-field range in both horizontal and vertical orientations. Using a rudimentary model fit to these results, we investigate the impact of correlation in the spatial distribution on the variability of circuit performance using a series of Monte Carlo analyses in HSPICE; it is confirmed that this correlation does indeed present a significant influence on performance variability.
From the same dataset, we also extract both the across-wafer (AW) and within-field (WIF) contributions to systematic variation. We find that the spatial correlation model’s shape is strongly related to these two components of variation (both in magnitude as well as by spatial fingerprint). By artificially reducing each of these components of systematic variation-thereby simulating the effects of active, across-field process compensation-we show that spatial correlation is significantly reduced, nearly to zero. This implies that Pelgrom's model may not apply to die-scale separation distances, and that a more accurate correlation theory would combine Pelgrom's model over very short separation distances with a systematic variation model that captures variability over longer distances by means of non-stationary distributions.
In this paper we investigate the impact of bake plate temperature variability throughout the entire bake trajectory on resulting critical dimension. For a poorly-controlled bake plate, it is found that the correlation between the temperature profile and CD distribution is high throughout the entire bake cycle, including the steady state sector. However, for a well-controlled, multiple-zone bake plate, the correlation is only significant during the transient heating sector, since in those cases the steady state plate behavior has already been optimized for CDU performance. An estimate of the potential improvement yet to be gained by improvement of transient heating uniformity is calculated.
KEYWORDS: Critical dimension metrology, Semiconducting wafers, Data modeling, Temperature metrology, Control systems, Lithography, Etching, Metrology, Process control, Thermal modeling
This paper describes a novel approach to improving across-wafer CD uniformity through the litho-etch sequence. Our approach is to compensate for systematic CD perturbations by employing all available control authority though the litho-etch process sequence. In particular, we find that the most effective control input for regulating spatial variations in CD is found in the post exposure bake (PEB) process step. More precisely, we construct offset models that relate the PEB temperature profiles of multi-zone bake plates to their zone offsets using wireless, in-situ temperature sensors from OnWafer Technologies. A second model relating across-wafer CD to PEB bake plate zone offsets is then identified from CD data measured by CD-SEM. The CD-to-offset model and the temperature-to-offset model are used with knowledge of the resist sensitivity to determine optimal bake plate zone offsets which minimize post-etch CD variation. This is done using constrained quadratic optimization techniques. Partial experimental work and simulation results show the promise of our approach. We demonstrate through simulation that across-wafer CD variation can be significantly reduced for 150nm technology node and beyond.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.