LIC-CGAN: fast lithography latent images calculation method for large-area masks using deep learning.

Latent image calculation for large-area masks is an indispensable but time-consuming step in lithography simulation. This paper presents LIC-CGAN, a fast method for three-dimensional (3D) latent image calculation of large-area masks using deep learning. Initially, the library of mask clips and their corresponding latent images is established, which is then used to train conditional generative adversarial networks (CGANs).

Mask structure optimization for beyond EUV lithography.

Beyond extreme ultraviolet (BEUV) lithography with a 6 × nm wavelength is regarded as a future technique to continue the pattern shirking in integrated circuit (IC) manufacturing. This work proposes an optimization method for the mask structure to improve the imaging quality of BEUV lithography. Firstly, the structure of mask multilayers is optimized to maximize its reflection coefficient.

Cluster sampling and scalable Bayesian optimization with constraints for negative tone development resist model calibration.

As the semiconductor technology node continues to shrink, achieving smaller critical dimension in lithography becomes increasingly challenging. Negative tone development (NTD) process is widely employed in advanced node due to their large process window. However, the unique characteristics of NTD, such as shrinkage effect, make the NTD resist model calibration more complex.

SCAPSM: attenuated phase-shift mask structure for EUV lithography.

The attenuated phase-shift mask (Att. PSM) is proven to be a promising resolution enhancement technology (RET) to improve the imaging performance in extreme ultraviolet (EUV) lithography. However, due to the reflective nature of the mask structure, the serious shadowing effect can affect the diffraction near field of the mask intensely and further impact the lithography imaging.

Method for optical proximity correction based on a vector imaging model.

Optical proximity correction (OPC) has become an indispensable step in integrated circuit manufacturing. It requires a huge amount of calculation to obtain a sufficiently accurate OPC model and implement pattern correction. In this paper, the authors proposed an edge-based OPC method built on a vector imaging model, where the analytical correlation between the cost function and movement of each edge segment is established by the chain rule.

Dynamic budget analysis of multiple parameters in a lithography system based on the superposition of light intensity fluctuations.

Lithography is one of the most critical processes in the manufacturing of micro- and nano-devices. As device critical dimensions continue to shrink, variations in system parameters during the lithography process often result in heavy deviations from the intended targets, making control of these parameters crucial to ensure that lithography results meet process requirements. Gaining a thorough comprehension of how various parameters interact and contribute to lithography errors is significant, and it is equally important to offer precise suggestions for managing these parameters in extreme ultraviolet lithography (EUVL) scanners.

Aberration budget analysis of EUV lithography from the imaging performance of a contact layer in a 5 nm technology node.

By analyzing the impact of aberration in an extreme ultraviolet lithography projector on the imaging indicators of the test patterns for a contact layer in a 5 nm technology node, this paper establishes a mathematical aberration model based on the back propagating neutral network. On the basis of an aberration model, a method for estimating the aberration budget is proposed, which can help reduce the difficulty of achieving imaging performance thresholds in actual production. The performance of the results given by this method is verified by using a rigorous simulation.

Fast diffraction model of an EUV mask based on asymmetric patch data fitting.

Calculating the diffraction near field (DNF) of a three-dimensional (3D) mask is a key problem in the extreme ultraviolet (EUV) lithography imaging modeling. This paper proposes a fast DNF model of an EUV mask based on the asymmetric patch data fitting method. Due to the asymmetric imaging characteristics of the EUV lithography system, a DNF library is built up including the training mask patches posed in different orientations and their rigorous DNF results.

Decomposition-learning-based thick-mask model for partially coherent lithography system.

The simulation of thick-mask diffraction near-field (DNF) is an indispensable process in aerial image calculation of immersion lithography. In practical lithography tools, the partially coherent illumination (PCI) is applied since it can improve the pattern fidelity. Therefore, it is necessary to precisely simulate the DNFs under PCI.

Plasmonic lithography fast imaging model based on the decomposition machine learning method.

Plasmonic lithography can make the evanescent wave at the mask be resonantly amplified by exciting surface plasmon polaritons (SPPs) and participate in imaging, which breaks through the diffraction limit in conventional lithography. It provides a reliable technical way for the study of low-cost, large-area and efficient nanolithography technology. This paper introduces the characteristics of plasmonic lithography, the similarities and the differences with traditional DUV projection lithography.

Study on forbidden pitch in plasmonic lithography: taking 365 nm wavelength thin silver film-based superlens imaging lithography as an example.

Plasmonic lithography can make the evanescent wave at the mask be resonantly amplified by exciting surface plasmon polariton (SPP) and participate in imaging, which can break through the diffraction limit in conventional lithography. It provides a reliable technical way for the study of low-cost, large-area and efficient nanolithography technology. However, there is also a phenomenon in plasmonic lithography similar to the forbidden pitch in conventional projection lithography.

High-precision lithography thick-mask model based on a decomposition machine learning method.

The thick-mask model had been used to simulate the diffraction behavior of the three-dimensional photomask in optical lithography system. By exploring the edge interference effect that appears in the diffraction near-field (DNF), an improved thick-mask model with high precision is proposed. The diffraction transfer matrix (DTM) is introduced to represent the transformation from the layout pattern to the corresponding DNF.

Fast aerial image model for EUV lithography using the adjoint fully convolutional network.

The effects of thick-mask and oblique incidence in extreme ultraviolet (EUV) lithography system make the aerial image calculation a challenging task. This paper develops a fast EUV lithography aerial image model based on a new kind of deep learning framework called adjoint fully convolutional network (AFCN). The AFCN consists of two adjoint data paths to respectively recover the real part and imaginary part of the complex mask diffraction-near-field (DNF).

Poly (lactic acid) blends with excellent low temperature toughness: A comparative study on poly (lactic acid) blends with different toughening agents.

Poly (lactic acid) (PLA) blends with different toughening agents were prepared by melt compounding, and the effects of toughening agents on the toughness of PLA, especially the low-temperature toughness, were investigated. All blends were immiscible systems, but the rheological Cole-Cole diagram showed that the blends had certain compatibility, and the interfacial bonding of PLA/Ethylene/butyl methacrylate/Glycidyl Methacrylate Terpolymer (GEBMA) blend was the best. With addition of the toughening agents, all blends showed improvement of the tensile and impact toughness both at room temperature and low temperature.

Compensation of EUV lithography mask blank defect based on an advanced genetic algorithm.

Mask blank defect is one of the most important factors that degrades the image quality of extreme ultraviolet (EUV) lithography system, and further leads to a yield lose. In order to compensate the amplitude and phase distortions caused by the EUV mask blank defects, this paper proposes an advanced algorithm to optimize the mask absorber pattern based on genetic algorithm. First, a successive approximation correction method is used to roughly compensate the effect of mask blank defect.

Improvement of the strength and toughness of biodegradable polylactide/silica nanocomposites by uniaxial pre-stretching.

Highly toughened polylactide (PLA) nanocomposites with balanced stiffness and strength were successfully prepared by combining the modification of 5 wt% silica (SiO) nanoparticles and uniaxial pre-stretching. The PLA/5 wt% SiO nanocomposites fractured in a brittle way due to the network structure composed of cohesional entanglements. After pre-stretching, the elongation at break was increased to 168% at pre-stretching ratio (PSR) of only 0.

Preparation and properties of poly(L-lactic acid) blends with excellent low-temperature toughness by blending acrylic ester based impact resistance agent.

Poly(L-lactic acid) (PLLA) blends with excellent low-temperature toughness and strength were prepared by melt compounding with acrylic ester based impact resistance agent (AEIR). The morphology, thermal properties, mechanical properties and biodegradability of the blends were investigated. Morphology observations revealed the blend was immiscible but had good compatibility with the dispersed phase size of about 200-300 nm.

Aberration optimization in an extreme ultraviolet lithography projector via a BP neural network and simulated annealing algorithm.

Extreme ultraviolet lithography (EUVL) presents promise for the advanced technology node in the manufacturing of integrated circuits. The imaging performance of EUVL is significantly affected by the aberration of projection optics. To obtain one optimum aberration for different test patterns, an inverse optimization method for aberration is proposed in this paper.

Analysis and modulation of aberration in an extreme ultraviolet lithography projector via rigorous simulation and a back propagation neural network.

Lens aberration is a critical factor affecting lithography, one that deteriorates the image fidelity and contrast. As the perfect lens does not exist, the aberration control is important for real optical systems, especially for extreme ultraviolet lithography (EUVL). By choosing the process variation band (PVB) and pattern shift (PS) as the lithographic performance indicators, the inverse analysis model for aberration control is proposed in this paper.

EUV multilayer defect characterization via cycle-consistent learning.

Extreme ultraviolet (EUV) lithography mask defects may cause severe reflectivity deformation and phase shift in advanced nodes, especially like multilayer defects. Geometric parameter characterization is essential for mask defect compensation or repair. In this paper, we propose a machine learning framework to predict the geometric parameters of multilayer defects on EUV mask blanks.

Fast extreme ultraviolet lithography mask near-field calculation method based on machine learning.

Near-field calculation for a three-dimensional (3D) mask is a fundamental task in extreme ultraviolet (EUV) lithography simulations. This paper develops a fast 3D mask near-field calculation method based on machine learning for EUV lithography. First, the training libraries of rigorous mask near fields are built based on a set of representative mask samples and reference source points.

Study on miscibility, thermal properties, degradation behaviors, and toughening mechanism of poly(lactic acid)/poly (ethylene-butylacrylate-glycidyl methacrylate) blends.

In the work, the poly(lactic acid) (PLA)/poly (ethylene-butylacrylate-glycidyl methacrylate) (PTW) blends were prepared by melt compounding. PTW as a toughening agent for PLA, the PLA/PTW blends had good compatibility due to the chemical reaction between the epoxy groups of PTW and the end group of PLA during the blending process. With increasing PTW content from 0 to 20%, the impact strength of PLA/PTW blends was enhanced from 4.

Learning-based compressive sensing method for EUV lithographic source optimization.

Extreme ultraviolet (EUV) lithography emerges as a promising technique to fabricate next-generation integrated circuits. In order to improve the lithography imaging fidelity, source optimization (SO) technique is widely used to compensate for the imaging distortion. This paper develops an efficient learning-based SO approach for EUV lithography under the compressive sensing (CS) framework.

Ductile and biodegradable poly (lactic acid) matrix film with layered structure.

Polylactide (PLA), as a biodegradable packing material, has attracted plenty of attention. However, some problems still limit the application of PLA in packing industry such as the inherent brittleness and low crack propagation resistance. In order to overcome these challenges, we blended PLA with a reactive toughening agent (Ethylene-Acrylic ester-Glycidyl methacrylate terpolymer) during extrusion and film processing.

Effect of molecular stereoregularity on the transcrystallinization properties of poly(l-lactide)/basalt fiber composites.

A comparative study on interfacial crystallization of poly(l-lactic acid) (PLLA) with different stereoregularity (PLLA2003D 96.0%, PLLA4032D 98.5%, and PLLA290 99.