Semiconductor Wafer Inspection Research Articles

Multiphysics modeling and simulations of laser-sustained plasmas

Laser-sustained plasma (LSP), which can be utilized for a novel radiation light source, has advantages such as high irradiance, broad spectral range, and stable emission, demonstrating significant applications in wafer inspection in the field of the semiconductor industry. This paper revisits the historical development of LSP research and introduces fundamental physical processes in LSP. The mathematical description equations for LSP and methods of calculating plasma parameters are provided, thereby a time-dependent two-dimensional fluid model is established by taking into consideration a laser-thermal-hydrodynamic coupling effect. The propagation of the laser in plasma is investigated based on the established model, and the fundamental processes in LSP, including the initial evolution process, laser energy deposition, steady-state characteristics, and instability, are explored. The effectiveness of the simulation model is confirmed through comparing with the experimental results of high-pressure Xe LSP. The findings indicate that the mode, power, <i>F</i>-number of incident lasers, as well as parameters including components, pressure, and flow velocity of gas, can all affect the steady-state properties of LSPs. Under the identical power and <i>F-</i>number conditions, Gaussian mode laser and annular mode laser both produce LSPs with different shapes and positions. Notably, under the conditions of high-power annular laser incidence, large laser <i>F-</i>number, and high flow velocity, the simulation results reveal temporal and spatial instability in LSP. These simulation results contribute significantly to a more in-depth understanding of the underlying physical mechanisms of the LSP. Furthermore, they provide a theoretical basis for designing the light source system and optimizing the multiple parameters. The influence of laser parameters on LSP properties elucidated in this study not only advances the fundamental understanding of LSP but also offers crucial insights for designing and optimizing the light source systems in various applications, particularly in the field of optical detection for semiconductor wafer inspection.

Modelling of the backside pattern transfer in magic mirror (Makyoh) imaging

A model of magic-mirror (Makyoh) imaging with the mirror backside relief as the input is described. The mechanical pattern transfer is modelled by a convolution approach while the optical imaging using a nonlinear geometrical optical model, more general than previous approaches. Characteristic features of the imaging is analysed and the linear approximation is examined. Diffraction effects are also treated. Characteristic features for the ancient mirror and applications in semiconductor wafer inspection are discussed.

Simultaneous Absorption and Near‐Infrared Emission Enhancement of Cr3+ Ions in MgGa2O4 Spinel Oxide via Anionic F‐Substitution

AbstractNear‐infrared (NIR) phosphor‐converted light‐emitting diodes (pc‐LEDs) are newly emerging broadband NIR light sources. However, the lack of high‐performance NIR‐emitting materials limits their popularization. Herein, an anionic F‐substitution strategy is presented to regulate the light absorption and emission of MgGa2O4:Cr3+ phosphors. Accordingly, absorption enhancement as well as emission redshift and broadening are achieved for F‐substituted MgGa2O4:Cr3+ (MGOF:Cr3+) phosphors, simultaneously with high efficiency and excellent thermal stability. Upon blue light excitation, the MGOF:0.02Cr3+ phosphor exhibits a broadband NIR emission (650–1200 nm) with a peak wavelength (λmax) of 835 nm and a full width at half maximum of ≈250 nm. Furthermore, MGOF:0.02Cr3+ has a near‐unity internal quantum efficiency and its emission intensity at 150 °C maintains 94% of the initial value. A record external quantum efficiency of 60.6% is further achieved for MGOF:0.08Cr3+ with a redshifted λmax of 870 nm. The Cr3+ local structural alteration with F‐substitution is revealed to account for the outstanding NIR luminescence characteristics of MGOF:Cr3+ in view of systematic structural characterization and spectroscopic analysis. A broadband NIR pc‐LED device with good optical performance is fabricated and its application in semiconductor wafer inspection is demonstrated. This study initiates a new way to design high‐performance NIR phosphors.

Tracking and Synchronization with Inversion-Based ILC for a Multi-Actuator-Driven Wafer Inspection Cartridge Transport Robot System

This paper proposes a simple tracking and synchronization control of a dual-drive system using inversion-based iterative learning control (IILC), which reformulates the model at each iteration based on input/output data. By the power of the IILC, this work simplifies the dual-actuator-driven dynamic system control problem that is normally addressed with a MIMO method. This work also shows the potential of the IILC for nonlinear system applications by reformulating the model at each iteration based on the input/output data. An analytical representation of the iteration-varying IILC followed by simulations is provided. A set of physical system testings with a dual-motor gantry and a semiconductor wafer inspection robotic system are carried out to verify the control method.

Lateral resolution improvement of laser-scanning imaging for nano defects detection

Abstract Demand for higher efficiency in the semiconductor manufacturing industry is continually increasing. In particular, nano defects measurement on patterned or bare Si semiconductor wafer surfaces is an important quality control factor for realizing high productivity and reliability of semiconductor device fabrication. Optical methods and electron beam methods are conventionally used for the inspection of semiconductor wafers. Because they are nondestructive and suitable for high-throughput inspection, optical methods are preferable to electron beam methods such as scanning electron microscopy, transmission electron microscopy, and so on. However, optical methods generally have an essential disadvantage about lateral spatial resolution than electron beam methods, because of the diffraction limit depending on the optical wavelength. In this research, we aim to develop a novel laser-scanning imaging method that can be applied to nano-/micro manufacturing processes such as semiconductor wafer surface inspection to allow lateral spatial super-resolution imaging with resolution beyond the diffraction limit. In our proposed method, instead of detecting the light intensity value from the beam spot on the inspection surface, the light intensity distribution, which is formed with infinity corrected optical system, coming from the beam spot on the inspection surface is detected. In addition, nano scale shifts in the beam spot are applied for laser spot scanning using a conventional laser-scanning method in which the spots are shifted at about a 100 nm pitch. By detecting multiple light intensity distributions due to the nano scale shifts, a super-resolution image reconstruction with resolution beyond the diffraction limit can be expected. In order to verify the feasibility of the proposed method, several numerical simulations were carried out.

반도체 웨이퍼 고속 검사를 위한 GPU 기반 병렬처리 알고리즘

In a the present day, many vision inspection techniques are used in productive industrial areas. In particular, in the semiconductor industry the vision inspection system for wafers is a very important system. Also, inspection techniques for semiconductor wafer production are required to ensure high precision and fast inspection. In order to achieve these objectives, parallel processing of the inspection algorithm is essentially needed. In this paper, we propose the GPU (Graphical Processing Unit)-based parallel processing algorithm for the fast inspection of semiconductor wafers. The proposed algorithm is implemented on GPU boards made by NVIDIA Company. The defect detection performance of the proposed algorithm implemented on the GPU is the same as if by a single CPU, but the execution time of the proposed method is about 210 times faster than the one with a single CPU.

Photonic nanojet focusing for hollow-core photonic crystal fiber probes

Large-pitch kagome-lattice hollow-core photonic crystal fibers (HC-PCFs) offer appealing optical properties for beam delivery and remote sensing. However, focusing their optical mode on a submicrometer spot can be challenging due to the large mode diameter and low numerical aperture of these fibers. Here, we demonstrate that a 30 μm latex microsphere directly set at the HC-PCF end-face provides an efficient means to focus the fiber mode down to a spot of 540 nm full width at half-maximum thanks to a photonic nanojet effect. The system is used for fluorescence imaging and direct laser writing on a thin absorbing layer. Potential applications include inspection of semiconductor wafers, photolithography, laser surgery, fluorescence sensing, or optical transfection.

New principles of designing multibeam electron-optical microsystems for diagnostics of semiconductor structures

A new approach to fabrication of diagnostic electron-optical systems of high (10–30 nm) and ultrahigh (to 2 nm) resolution for defect inspection of large-diameter semiconductor wafers is proposed. Electron optical calculation of electron-optical systems with different configurations is performed. The efficiency of using thin films for increasing quality of electron-optical systems is estimated.

Defect Monitor Method Based on Sampling Review Plan

Hi-speed and highly sensitive visual inspection tools are in practical use in the field of semiconductor wafer inspection. Defect review is a critical step to grasp the defect condition, that is, to know what types of defects are occurred on the wafer. However, it is not practical to review whole defects on the wafer because of a quantitative gap between the detected defects and defects to be reviewed within certain practical time. To bridge this gap, a visual pattern detection algorithm of spatially distributed defect points and an optimum defect sampling plan are proposed. Experimental result shows that partial defect review is enough to grasp the defect occurrence condition all over the wafer. by applying the proposed method for defect review.

Computerized flow field analysis: oriented texture fields

An approach to the solution of signal-to-symbol transformation in the domain of flow fields, such as oriented texture fields and velocity vector fields, is discussed. The authors use the geometric theory of differential equations to derive a symbol set based on the visual appearance of phase portraits which are a geometric representation of the solution curves of a system of differential equations. They also provide the computational framework to start with a given flow field and derive its symbolic representation. Specifically, they segment the given texture, derive its symbolic representation, and perform a quantitative reconstruction of the salient features of the original texture based on the symbolic descriptors. Results of applying this technique to several real texture images are presented. This technique is useful in describing complex flow visualization pictures, defects in lumber processing, defects in semiconductor wafer inspection, and optical flow fields.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

A classification scheme for visual defects arising in semiconductor wafer inspection

In this paper we describe a novel scheme to characterize surface defects and flaws that arise in semiconductor wafer processing. This is done by analyzing the texture of an image of the defect. We have developed a taxonomy for textures, which classifies textures into the broad classes of disordered, strongly ordered and weakly ordered. Disordered textures are described in terms of their fractal dimension, strongly ordered textures are by the placement of primitives, and weakly ordered textures by the underlying orientation field. We have developed an algorithm to measure the fractal dimension of a given texture. We use the qualitative theory of differential equations to devise a symbol set for the weakly ordered textures in terms of singularities. We have devised an algorithm to process an image of a defect and extract qualitative descriptions based on this theory.