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Overlay is a crucial indicator of manufacturing processing between layers. Currently, diffraction-based overlay (DBO) is widely adopted in overlay metrology. In response to existing challenges in DBO metrology, this study applied the concept of optical computing to establish a DBO metrology with an optical convolution layer that can predict the overlay of a DBO target, thereby providing a promising measurement method that increases the intuitiveness and efficiency of overlay metrology. In this study, pupil images from DBO metrology were directly output to the optical convolution layer and integrated with subsequent CNN layers in electronic hardware. A total of 630 pupil images with 21 types of designed overlay were generated for network training and testing. The experimental testing results revealed that the root mean square error of the predicted values of 90 pieces of testing pupil image data was 0.17 nm. The completed optical convolution layer is the fundamental unit for establishing an optical interconnection with the functions of weighting and matrix summation, which will contribute to further exploration of the DBO technique.

Resolution enhancement techniques compatible with an ArF (193 nm) immersion optical lithography system may constitute an effective means of minimizing the size of technology nodes of the dynamic random access memory. This paper investigated one such technique, namely mask optimization (MO), and applied sub-resolution assist features (SRAFs) in the MO to improve the aerial image quality of a target pattern that had undergone optical proximity correction (OPC). This paper first developed an optical model based on the Hopkins model to create an interference map, which was then used to create a cut-level map. The cut-level map was instrumental in predicting potential SRAF sites and randomly generating SRAFs that would serve as the initial population for a genetic algorithm (GA). Chromosomes were defined as a section map and encoded genes were used to define SRAF and target pattern. Using a GA to identify SRAF geometric measurements and placement was revealed to increase the process window and improve the image performance of the target pattern. This paper used 1D and 2D line/space (L/S) images as the baseline to test the convergence of the proposed method. 2D images were also used to test improvements in aerial image performance. The results indicated that the 1D L/S pattern converged at the 100th iteration. Furthermore, the depths of the focus of the 2D L/S array and 2D contact hole patterns were successfully increased by 113 and 21 nm, respectively. The proposed SRAF method, which integrated the GA and interference map, was able to ensure the diversity of potential SRAF solutions. Moreover, it was able to restrict the SRAF solutions to rectangular structures through the application of mask rules, thereby reducing the cost and improving the feasibility of photomasks.

This paper describes the use of ArF immersion lithography to verify the feasibility of a self-developed freeform illumination source that exposes features on masks and forms resist patterns. After development inspection (ADI) was used to measure the results and inspect whether the critical dimension (CD), process window, line-edge roughness (LER), and line-width roughness (LWR) of the resist pattern attained the standards of existing manufacturing processes. The testing features include nine horizontal and eight vertical features. Ant colony optimization (ACO) can provide optimal freeform illumination sources for these horizontal and vertical features. This paper considers each feature's particular weighting in order to test the complexity and adaptability of the ACO algorithm applied to semiconductor manufacturing processes. The results of source calculations show that all 17 testing features can be satisfied with the X symmetry freeform source. When using this freeform source in an ArF lithography system, the ADI resist CD of all testing features is located within ±10% target CD tolerance. The ADI target CD set by dense patterns is 40 nm. Resist pattern ADI CD measurements show that, under a through-focus condition, the resist pattern CD between 40 and 42 nm is within tolerance, the depth of focus can reach up to 0.1 μm , LER is approximately 5 nm, and LWR is approximately 7 nm. These ADI CD measurements show that this ACO-based freeform source can be integrated into existing advanced semiconductor lithography processes.

This paper applied a radial basis function network (RBFN) in coherent Fourier scatterometry (CFS) to reconstruct the linewidth of periodic line/space (L/S) patterns. The fast, nondestructive, and repeatable measurement capability of CFS enables its integration with intelligent lithography systems. Two steps to reconstruct the linewidth of the L/S patterns were performed in this paper. The first step was to use the finite difference time domain numerical electromagnetic tool to rigorously establish the library of modeled diffraction signatures by using the L/S patterns. Each modeled signature was converted to an intensity vector as the training data to construct the RBFN. The trained RBFN has a simple architecture consisting of three layers: input, hidden, and output layers. The second step was to collect the experimental signatures and feed them into the trained RBFN model to predict the linewidth of L/S patterns. This paper used the transverse electric polarized incident beam at the wavelength of 632 nm in the experimental setup of the CFS. Five L/S patterns were used to test the constructed RBFN. The experimental results indicated that the maximal difference was 13 nm between the CFS and the atomic force microscopy (AFM) measurements for the sample D with an L/S of 200 nm. The minimum difference was 2 nm for the sample A with an L/S of 140 nm. The correlation coefficient between the CFS and AFM metrology measurement running through five samples was 0.972. The high correlation between the CFS with the proposed RBFN measurements and the AFM revealed the potential to implement the radial basis learning kernel in optical metrology to achieve intelligent lithography.

This paper investigates the manufacturability-aware process of p-n junction formation for photovoltaic cells involving with Si nanoparticle layer. The furnace-based dopant diffusion process of forming a p-n junction consumes a substantial amount of energy. In addition, repetitive production steps prevent the possibility of Si ink-based cells integrating onto flexible substrates. This research examined the local heating dopant diffusion process by using a fiber laser at a wavelength of 1064 nm. The infrared beam is delivered onto the wafer stack with a nanoparticle carbon layer and n-type Si ink layer on p-type Si substrates. The nanoparticle carbon film absorbs infrared beam energy and converts photon energy as a thermal source to diffuse the n-type dopant in Si ink into the p-type Si wafer. The Si ink in this paper contains a mixture of Si nanoparticles and an n-type spin-on dopant solution. The TEM results show that Si nanoparticles are uniformly dispersed on the Si wafer surface. This research investigated sheet resistance as a function of laser parameters, including laser power, scanning speed, and pulse frequency for the samples coated with Si ink. Secondary ion mass spectroscopy measurements indicate the presence of an n-type dopant in p-type substrates, with an approximate diffusion depth of 100 nm. The results indicate that the proposed infrared laser treatment technique is promising for the formation of p-n junctions with Si ink-based photovoltaic cells.

Diffraction-based overlay (DBO) accuracy is critical to the intelligent nanolithography process control for producing advanced semiconductor fabrication nodes. Optical gratings located on various layers are commonly used as the targets for the detection of the overlay displacement offset in DBO measurement. The asymmetry in intensity between the 1st and -1st beams diffracted by the targets is used for the prediction of grating displacement offset. This paper describes the effect of grating targets with sidewall angles (SWAs) on asymmetry in intensity and proposes an artificial neural network (ANN) method for enhancing the accuracy of grating displacement offset prediction. Grating targets with a 1:3 line-to-pitch ratio and SWA profiles varying from 86° to 90° were employed in this paper. The asymmetry in the intensity of the designed targets was computed for incident beams with transverse-electric and transverse-magnetic polarization at visible wavelength. An ANN feed-forward model was developed for the displacement offset prediction. The ANN, the conventional linear model, and the regression models were evaluated using diffraction data calculated by a numerical electromagnetic solver. The mean square error and the mean of the residual indicated that using the ANN model and incident beams at wavelengths of 600, 650, and 750 nm is substantially more effective for prediction than the conventional linear model is.

Core-shell-isolated nanoparticles are commonly used in the surface-enhanced Raman scattering (SERS) technique to detect binding events and in analyte identification at the molecule level. In this paper, an opticalscattering theoretical model was used in which the core-shell-isolated nanoparticles are considerably smaller than incident light wavelengths, and the finite difference time domain method of numerical electromagnetics was adopted to compute the scattered opticalpower density per unit volume of the nanoparticles. In addition, the power densities were analyzed using various shell materials and the influences of differing parameters (i.e., the size of metal nanoparticles, shell thickness, nanoparticle size, and the distance between nanoparticles) on power-density functions were explored. The results indicated that when the nanoparticle shells were coated with silicon dioxide (SiO2) and aluminum oxide (Al2O3) to a thickness of 1 nm and the nanoparticle core was gold (Au), a particle size of 35 nm was the optimal design. The optimal distance between Au nanoparticles possessing SiO2 shells was 5 nm and that between Au nanoparticles possessing Al2O3 or titanium dioxide (TiO2) shells was 10 nm. Based on the format results of nanoparticle arrangement, the distance between the shell-isolated Au nanoparticles was 10 nm and generated a stronger scattered power density with an asymmetric arrangement than that generated using symmetrically arranged nanoparticles. The advantage of the proposed method in this paper over the conventional method is its ability to relate the scattered power density to the required number of nanoparticles used in the SERS technique. [ABSTRACT FROM PUBLISHER]

This paper discusses the integration of an end-to-end optical interconnect testbed on printed circuit boards using inexpensive off-the-shelf, bare die, optoelectronic components. We developed a process for efficient and simultaneous in-plane optical coupling between edge emitting laser and waveguides, and between photodetector and waveguide. We demonstrated an optically smooth buffer layer separating the printed circuit layer from the optical transport layer. The demonstrated radically new optical interconnect technology, which we refer to as interface optical coupling, is able to efficiently and simultaneously form optical interfaces between waveguides, lasers and photodetectors by photolithographic technique, thereby eliminating the need for microlenses and manual alignment. The measured laser to waveguide coupling efficiency is 45% and measured waveguide to photodetector coupling is 35%. The optical link is demonstrated to operate at 10 Gbps. [ABSTRACT FROM AUTHOR]