Advances in chip manufacturing processes continue to increase the number of vertices to deal with in Optical Proximity Correction (OPC) and Mask Data Preparation (MDP). In order to manage the processing time, OPC in sub-nanometer now requires employing tens of thousands of CPU cores. A slight mishap can force the job to be re-run. Increased complexity in the computing environment, along with the length of time a job spends in it, makes a job more susceptible to various sources of failures, while the re-run penalty is also growing with the design complexity. Checkpointing is a technique that saves the state of a system that continuously transitions to another state. The purpose of creating a checkpoint for a job is to make it possible to restart an interrupted job from the saved state at a later time. With checkpointing, if a running job encounters termination before its normal completion, be it due to a hardware failure or a human intervention to make resources available for an urgent job, it can resume from the checkpoint closest to the point of termination and continue to its completion. Checkpointing applications can include 1) resume flow where a terminated job can be resumed from the point close to the termination, 2) repair flow to fix OPC hotspot areas without having to process the entire chip and 3) cloud usage where job migration may be necessary. In this paper, we study the runtime and storage impact with checkpointing and demonstrate virtually no runtime impact and very minimal increase in filer storage. Furthermore, we show how checkpointing can significantly reduce runtime in OPC hotspot repair applications
KEYWORDS: Chemical mechanical planarization, Manufacturing, Design for manufacturability, Semiconducting wafers, Silicon, Etching, Product engineering, Design for manufacturing, Data modeling, Calibration, Copper, Back end of line, Metals
As we move to advanced technology nodes, the requirements on within chip and across wafer planarity are becoming more demanding [1]. Also, the number of Chemical Mechanical Polishing (CMP) processes and steps used in microelectronic chip manufacturing is increasing rapidly, in an effort to meet the stringent planarity requirements [1]. However, the complex pattern dependencies inherent in CMP processes, and the cumulative nature of the topography generated by these processes make it challenging to meet the aforementioned stringent uniformity requirements for the variety of designs produced. Consequently, we expect to see an increased CMP and related hotspots on advanced node designs. Accurately detecting CMP and related hotspots (such as pooling, DOF hotspots, topography variation hotspots etc.) and providing guidelines to fix or prevent them is therefore critical for CMP process development, yield ramp up and shorter design and manufacturing cycles.
In this paper we present a hotspot detection and removal/prevention flow. The flow uses Cadence Design System’s manufacturing modeling methodology that predicts feature scale, within chip, and wafer level topography. The modeling methodology takes into account etch depth, deposition, and CMP variations across multiple levels in the design, and across multiple process steps within a given design level.
KEYWORDS: Chemical mechanical planarization, Front end of line, Back end of line, 3D modeling, Design for manufacturing, Process modeling, Manufacturing, Process engineering, Transistors, Copper, Calibration, Oxides, Data modeling, Polishing
Chemical mechanical polishing (CMP) has been a critical enabling technology in shallow trench isolation (STI), which is used in current integrated circuit fabrication process to accomplish device isolation. Excessive dishing and erosion in STI CMP processes, however, create device yield concerns. This paper proposes characterization and modeling techniques to address a variety of concerns in STI CMP. In the past, majority of CMP publications have been addressed on interconnect layers in backend- of-line (BEOL) process. However, the number of CMP steps in front-end-of-line (FEOL) has been increasing in more advanced process techniques like 3D-FinFET and replacement metal gate, as a results incoming topography induced by FEOL CMP steps can no longer be ignored as the topography accumulates and stacks up across multiple CMP steps and eventually propagating to BEOL layers. In this paper, we first discuss how to characterize and model STI CMP process. Once STI CMP model is developed, it can be used for screening design and detect possible manufacturing weak spots. We also work with process engineering team to establish hotspot criteria in terms of oxide dishing and nitride loss.
As process technologies move from planar transistor to 3D transistor like FinFet and multi-gate, it is important to accurately predict topography in FEOL CMP processes. These incoming topographies when stacked up can have huge impact in BEOL copper processes, where copper pooling becomes catastrophic yield loss. A calibration methodology to characterize STI CMP step is developed as shown in Figure 1; moreover, this STI CMP model is validated from silicon data collected from product chips not used in calibration stage. Additionally, wafer experimental setup and metrology plan are instrumental to an accurate model with high predictive power.
After a model is generated, spec limits and threshold to establish hotspots criteria can be defined. Such definition requires working closely with foundry process engineering and integration team and reviewing past failure analysis (FA) to come up a reasonable metrics. Conventionally, a potential STI weak point can be found when nitride residues remains in the active region after nitride strip. Another source of STI hotspots occurs when nitride erosion is too much, and active region can suffer severe damage.
Traditional RC extraction flows mostly consider interconnect thickness variations caused by etch and CMP processes in a way of rule-based approach where a form of tables or polynomials is used. While such rulebased approaches are easily incorporated into design flows, they are not inevitably accurate since tablelook- ups in rules are inherently taking simple (mostly one dimensional) typed patterns. Moreover, rules fail to account for the length scale and cumulative effects in both etch and CMP, thereby making them less accurate compared to physics-based models. In this paper, we introduce a model-based CMP aware RC extraction flow that uses the results of thickness simulations from Cadence CMP modeling tools. We apply the proposed model-based CMP aware RC extraction flow to several blocks in a 16 nm design, and compare the results of the proposed model-based flow with those of a traditional rule-based RC extraction flow. This paper also notes that running the model-based flow in conjunction with the traditional rule-based flow should cover the full range of RC variation along critical nets, and ensure faster timing closure.
KEYWORDS: Chemical mechanical planarization, Design for manufacturing, Computer aided design, Lithography, Metals, Copper, Data modeling, Neodymium, Curium, System on a chip
This paper presents the requirements for the Design for Manufacturability (DFM) checks such as lithography, and
Chemical and Mechanical Polishing (CMP) at 28nm technology node, and the need to perform these DFM checks, early
in the design phase and with minimum overhead. As a result, this reduces the risk of uncovering some DFM issues at the
design tape out time when the changes in a design become expensive. Because IP blocks can be targeted to multiple
designs, it is a key requirement that the lithography and CMP checks are accurate and designer-friendly and are easily
applied at block-level. This paper describes the block-based methodology that allows the IP designers to perform quickly
a comprehensive DFM analysis, including lithography and long-range CMP effects. This paper also explains the
integration of the DFM checks into the design flow and correlation results between the block and chip-level checks.
KEYWORDS: Chemical mechanical planarization, Copper, Design for manufacturing, Calibration, Design for manufacturability, Manufacturing, Model-based design, Process modeling, Curium, Data modeling
This paper presents a model-based Chemical Mechanical Polishing (CMP) Design for Manufacturability (DFM) ()
methodology that includes an accurate prediction of post-CMP copper interconnect topographies at the advanced
process technology nodes. Using procedures of extensive model calibration and validation, the CMP process model
accurately predicts post-CMP dimensions, such as erosion, dishing, and copper thickness with excellent correlation to
silicon measurements.
This methodology provides an efficient DFM flow to detect and fix physical manufacturing hotspots related to copper
pooling and Depth of Focus (DOF) failures at both block- and full chip level designs. Moreover, the predicted
thickness output is used in the CMP-aware RC extraction and Timing analysis flows for better understanding of
performance yield and timing impact. In addition, the CMP model can be applied to the verification of model-based
dummy fill flows.
KEYWORDS: Chemical mechanical planarization, Metals, Copper, System on a chip, Design for manufacturing, Manufacturing, Dielectrics, Polishing, Device simulation, Logic
Traditionally model based CMP check and hotspot detection are only done at the top level of the design because full
chip assembly is required to capture CMP long range effect. When manufacturing hotspots are found just before tape out
and layout modification is required, this can disrupt the overall schedule by repeating the verification steps with the
changed layout. Hence getting feedback at early design stage is critical to ensure that the design is correct by
construction. In this paper, we present a model-based CMP-DFM methodology which is used at early design phases to
avoid CMP related manufacturing failures. An accurate CMP model has been developed and used to predict surface
topographies for 32nm designs as well as physical hotspots caused by dishing, erosion, and depth of focus. We
demonstrate how to apply a characterized 32nm CMP physical model to run block level simulation with little or no
context information. The block level simulation methodology allows designers to check block robustness against any
possible surrounding environments in which the block may be placed. This approach can be taken for corner case
analysis in CMP-aware RC extraction.
KEYWORDS: Lithography, Chemical mechanical planarization, Design for manufacturing, Model-based design, System on a chip, Manufacturing, Metals, Databases, Design for manufacturability, Semiconductors
In this paper, we present the challenges of the realization of a large 45nm modern Media Processing SoC with multiple
design teams distributed across many countries and time zones. We also describe the complex design methodology
deployed to ensure the design is "closable" in the timing and manufacturability domain.
Silicon variability impacts both the physical integrity and the parametric performance of the design. Lithography and
CMP can cause enough context-dependent systematic variations, requiring exhaustive lithography and CMP physical
verification and optimization of the layout.
We present the physical and electrical DFM methodology at NXP. We will show how NXP has developed a
manufacturing-aware design flow based on early prevention, detection and fixing using a hierarchical approach for
model-based lithography checks and model-based CMP checks, from IP level to full-chip. We also present results of
variability-aware timing sign-off.
Chemical Mechanical Polishing (CMP) has been used in the manufacturing process for copper (Cu) damascene process.
It is well known that dishing and erosion occur during CMP process, and they strongly depend on metal density and line
width. The inherent thickness and topography variations become an increasing concern for today's designs running
through advanced process nodes (sub 65nm). Excessive thickness and topography variations can have major impacts on
chip yield and performance; as such they need to be accounted for during the design stage.
In this paper, we will demonstrate an accurate physics based CMP model and its application for CMP-related hotspot
detection. Model based checking capability is most useful to identify highly environment sensitive layouts that are prone
to early process window limitation and hence failure. Model based checking as opposed to rule based checking can
identify more accurately the weak points in a design and enable designers to provide improved layout for the areas with
highest leverage for manufacturability improvement. Further, CMP modeling has the ability to provide information on
interlevel effects such as copper puddling from underlying topography that cannot be captured in Design-for-
Manufacturing (DfM) recommended rules.
The model has been calibrated against the silicon produced with the 45nm process from Common Platform (IBMChartered-
Samsung) technology. It is one of the earliest 45nm CMP models available today. We will show that the
CMP-related hotspots can often occur around the spaces between analog macros and digital blocks in the SoC designs.
With the help of the CMP model-based prediction, the design, the dummy fill or the placement of the blocks can be
modified to improve planarity and eliminate CMP-related hotspots. The CMP model can be used to pass design
recommendations to designers to improve chip yield and performance.
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