Carl E. Picciotto

Alignment for imprint lithography using nDSE and shallow molds

We present a low-cost overlay alignment metrology solution for nanoimprint lithography that uses optical microscopy, displacement-sensing algorithms, and specially-designed imprint molds that include shallow alignment marks that are visible to the optical system but do not pattern the wafer. This innovation reduces measurement distances to near zero, the optimal distance for displacement-sensing algorithms, and allows for alignment marks to occupy the same piece of wafer real estate without interfering in any way, thus saving silicon area. Additionally, the method we present does not require the comparison of alignment marks between the wafer and the mold, thus removing process variations as a variable. We fabricate the shallow-mark molds, show that the shallow alignment marks indeed do not leave a mark on the wafer, and, implementing our nDSE (nanoscale displacement sensing and estimation) techniques, we demonstrate nanoscale alignment to a precision of 35 nm, 1-sigma. Given sufficient engineering refinement, we would fully anticipate achieving alignment errors down to the 1 nm range using these methods.

From nanoscale displacement sensing and estimation to nanoscale alignment

In this article, the authors present theoretical background and practical procedures for linking displacement sensing and estimation to nanoscale alignment. The authors discuss the application of nanoscale displacement sensing and estimation (nDSE)-based overlay metrology tool. The authors propose a new look at what constitutes displacement and alignment. From there, the authors develop several frameworks to bridge these two concepts based on a set of new pseudodisplacement concepts and on the careful selection of references. Direct displacement-measurement-based alignment (DDMA) is the first method the authors have used to generate reliable alignment results. The authors achieved sub-100-nm (down to 21nm) alignment accuracy. Indirect displacement-measurement-based alignment (IDMA) is the most accurate method in theory. IDMA truly utilizes nDSE to achieve precision coplacement between different layers and processes. IDMA and DDMA, along with a group of other nDSE-based algorithms/procedures, are vibration...

Overlay alignment using optical microscopy and arbitrary surface features

In this article, we present our nanoscale displacement sensing and estimation (nDSE) theory,which describes the theoretical limitations of displacement-sensing and predicts thepracticality of measuring nanoscale displacements using optical microscopy, and indirect displacement-measurement-based alignment (IDMA), an application framework for achieving precision alignment using individual displacement sensing rather than directly comparing nominally identical alignment marks. We propose that IDMA may form the basis for low-cost overlay alignment metrology for emerging fabrication techniques such as nanoimprint lithography. As a first step in experimentally investigating IDMA on a nanoimprinting tool, we present a variation, direct displacement-measurement-based alignment (DDMA), and we describe proof-of-concept experiments performed using an in-house nanoimprinter. We demonstrate that DDMA, enabled by nDSE, can measure misalignments in the tens of microns to a precision easily better than 100nm. We maintain...

nDSE-based overlay alignment: enabling technology for nano metrology and fabrication

Displacement sensing and estimation (DSE) is important preprocessing task for many image-based processing systems that extract information from multiple images. In last two years, we gained significant insight of the nature of DSE and developed theory and algorithm framework named nanoscale displacement sensing and estimation (nDSE). We also build procedures to apply nDSE to overlay alignment down to the nanoscale. We will introduce two basic theories: Phase Delay Detection (PDD) and Derivatives-based Maximum Likelihood Estimation (DML) and associated DSE algorithms, noticeably Near-Neighbor-Navigation (N-Cubed) algorithm. We presented our best nDSE experimental result of 1 nm (1σ) while tracking 5 nm stepping. To develop nDSE-based nanoscale alignment, we introduced our definition of displacement, alignment and pseudo-displacement. We presented both theoretical and practical procedures to use nDSE to achieve nano-alignment down to the 10s of nano-meters and beyond. Then we compared nDSE-based nano-alignment to other industry standard alignment method and attempt to show the substantial advantages of nDSE based alignment in terms of cost and simplicity of the system design.