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Based on the bidirectional evolutionary structural optimization (BESO) method, the present article proposes an optimization method for a thermal structure involving design-dependent convective boundaries. Because the BESO method is incapable of keeping track of convection boundaries, virtual elements are introduced to assist in identifying the convection boundaries of the structure. In order to solve the difficult issue of element assignment under a design-dependent convection boundary, label matrixes are employed to modify the heat transfer matrix and the equivalent temperature load vector of elements over topology iterations. Additionally, the optimization objective is set to minimize the maximum temperature of the structure in order to deal with the objective reasonableness, and the p-norm method is then used to fit the objective function to calculate sensitivity. Finally, several cases, including 2D and 3D structures under various heat transfer boundary conditions, are provided to illustrate the effectiveness and good convergence of the proposed method.

Although concomitant nonalcoholic steatohepatitis (NASH) is common in chronic hepatitis B (CHB), the impact of viral factors on NASH and the outcome of CHB patients concomitant with NASH remain unclear. We aimed to investigate the outcomes of NASH in CHB patients receiving antiviral treatment.In the post-hoc analysis of a multicenter trial, naïve CHB patients receiving 72-week entecavir treatment were enrolled. We evaluated the biochemical, viral and histopathological responses of these patients. The histopathological features of NASH were also evaluated, using paired liver biopsies at baseline and week 72.A total of 1000 CHB patients were finally enrolled for analysis, with 18.2% of whom fulfilling the criteria of NASH. A total of 727 patients completed entecavir antiviral treatment and received the second biopsy. Serum HBeAg loss, HBeAg seroconversion and HBV-DNA undetectable rates were similar between patients with or without NASH (P0.05). Among patients with NASH, the hepatic steatosis, ballooning, lobular inflammation scores and fibrosis stages all improved during follow-up (all P0.001), 46% (63/136) achieved NASH resolution. Patients with baseline body mass index (BMI) ≥ 23 kg/mLower BMI and weight reduction but not virologic factors determine NASH resolution in CHB. The value of weight management in CHB patients during antiviral treatment deserves further evaluation.

The distribution and evolution of air in airliner cabins is an important basis for the study of cabin thermal environment and pollutant propagation. Due to the complex heat and mass transfer problems caused by forced and natural convection in a large-scale space, the accurate prediction of air distribution in airliner cabins still faces huge challenges. This study takes the cabin of the Airbus A320 as the research object. The accurate numerical simulation of the flow and heat transfer process in an airliner cabin under mixing ventilation mode was carried out using the Hybrid Thermal Lattice Boltzmann Method (HTLBM) combined with GPU (Graphics Processing Unit) acceleration technology, and the influence of human thermal plumes on air distribution and evolution characteristics in an airliner cabin was analyzed. The research shows that the human thermal plume changes the air distribution in the passenger cabin. The thermal plume slows down the jet attenuation, increases the energy exchange in the area near the passengers, and offsets the jet trajectory. The airflow self-locking effect is easier to form in the passenger breathing area, which increases the time for the flow field to develop into the steady state. The influence of human thermal plumes on the airflow distribution in the passenger cabin cannot be ignored.

Chronic hepatitis B (CHB) and liver fibrosis are associated with a high risk of hepatocellular carcinoma (HCC) development. We assessed whether entecavir (ETV) plus Biejia-Ruangan compound (BRC), an anti-fibrotic traditional Chinese medicine, can further reduce the risk of HCC in treatment-naïve Chinese patients with CHB and an Ishak fibrosis score of ≥3 points derived from our parent double-blind randomized placebo-controlled trial.After a 72-week comparison between ETV+BRC and ETV+placebo treatment, participants were eligible to enter an open-label treatment phase and were followed up every 6 months. The primary [secondary] endpoints were the incidence of HCC [liver-related deaths, non-HCC events, and non-liver-related deaths]. Modified intention-to-treat (mITT), intention-to-treat (ITT), and per-protocol (PP) populations were defined for the time-to-event analysis.A total of 1,000 patients were recruited; the median age was 42.0 years; 69.9% were male and 58.3% were HBeAg positive. In the mITT population, the 7-year cumulative incidence of HCC [liver-related deaths] was 4.7% [0.2%] for ETV+BRC, which was significantly lower than 9.3% [2.2%] for ETV monotherapy (p = 0.008 [p = 0.030]). Notably, ETV+BRC treatment yielded a lower incidence of HCC in those who did not achieve regression of fibrosis at week 72 than ETV monotherapy (p = 0.018). There were no differences in the other 2 secondary endpoints or safety profiles between the groups. Multivariable Cox proportional regression analysis, including the treatment allocation as a parameter, also demonstrated that ETV+BRC treatment was associated with a reduced incidence of HCC. The ITT and PP analyses showed consistent results.ETV plus BRC combination treatment could further reduce the risk of HCC and liver-related deaths in patients with CHB and advanced fibrosis or cirrhosis, which may have important clinical implications for HCC prevention.Patients with chronic hepatitis B virus infection are at an increased risk of developing liver cancer (specifically hepatocellular carcinoma [HCC]). While there are effective antiviral treatments that can suppress the virus in chronically infected patients, the risk of HCC remains. Herein, we show that adding a traditional Chinese medicine called Biejia-Ruangan compound to an antiviral reduced the risk of HCC in patients with chronic hepatitis B.

A new method for simultaneously reconstructing surface and internal transient temperature distributions in structures is presented by ultrasonic measurements. The principle of ultrasonic thermometry is based on temperature dependence of the velocity of ultrasonic wave (acoustic velocity) propagating through heated structures. Considering the bending effect of ultrasonic propagation path in non-uniform temperature field, an approach for predicting two-dimensional ultrasonic propagation path is developed using the Fermat theory. Combining the advantages of the ultrasonic pulse-echo measurements and an inverse analysis of thermo-acoustic coupling problem, a reconstruction algorithm is proposed to estimate two-dimensional surface and internal temperature fields. The presented approach is discussed in some detail and a number of examples are given as verification to demonstrate the feasibility and reliability of this method. The surface and internal temperature profiles determined by ultrasound agree well with the exact values. In addition, the influences of bending effect of wave propagation, measurement error of ultrasonic wave propagation time, number and position of measurement points on the reconstruction of temperature fields are analyzed in detail. It shows that the presented method is a promising means for high-accurately and nondestructively determining surface and internal transient temperature distributions in heated structures.

The structural anisotropy of open-cell foam leads to the anisotropy of effective thermal conductivity (ETC). To quantitatively analyze the effect of structural anisotropy on the anisotropy of ETC, a new predicting model for the ETC of anisotropic open-cell foam was proposed based on an anisotropy tetrakaidecahedron cell (ATC). Feret diameters in three orthogonal directions obtained by morphological analysis of real foam structures were used to characterize the anisotropy of ATC. To validate our proposed anisotropic model, the ETCs of real foam structures in three orthogonal directions predicted by it were compared with the numerical results, for which the structures of numerical models are reconstructed by X-ray computed tomography (X-CT). Using the present anisotropic model, the influences of the thermal conductivity ratio (TCR) and porosity of the foams on the anisotropic ratios of ETCs are also investigated. Results show that there is good consistency between the ETCs obtained by the anisotropic model and the numerical method. The maximum relative errors between them are 2.84% and 13.57% when TCRs are 10 and 100, respectively. The present anisotropic model can not only predict the ETCs in different orthogonal directions but also quantitatively predict the anisotropy of ETC. The anisotropies of the ETCs decrease with porosity because the proportion of the foam skeleton decreases. However, the anisotropies of ETCs increase with TCR, and there exist asymptotic values in anisotropic ratios of ETCs as TCR approaches infinity and they are equal to the relative Feret diameters in different orthogonal directions.

Objective. To explore the clinical value of the specific plasma cell detection and specific T lymphocyte detection test in diagnosing hypersensitivity caused by antituberculosis drugs. Methods. A total of 266 patients with pulmonary tuberculosis who developed hypersensitivity during the treatment of primary pulmonary tuberculosis in our hospital and 266 patients without hypersensitivity during the treatment of pulmonary tuberculosis in our hospital were selected as the control group. The admission time is from January 2013 to June 2020. The specific plasma cell test and specific T lymphocyte test were used as the criteria to determine which drugs induced hypersensitivity, and the diagnostic value of these two methods in the diagnosis of hypersensitivity induced by four first-line antituberculosis drugs (isoniazid (INH), ethambutol (EMB), rifampicin (RFP), and pyrazinamide (PZA)) was analyzed. Results. The sensitivity of the specific plasma cell test in the diagnosis of hypersensitivity induced by INH, EMB, RFP, and PZA was 63.42%, 51.20%, 47.81%, and 56.37%, respectively, and the specificity was 95.33%, 99.87%, 96.52%, and 99.99%, respectively. The sensitivity of the specific T lymphocyte test in the diagnosis of hypersensitivity induced by INH, EMB, RFP, and PZA was 66.47%, 52.88%, 49.91%, and 58.54%, respectively, and the specificity was 97.28%, 99.99%, 98.38%, and 100.00%, respectively. Conclusion. The specific plasma cell test and specific T lymphocyte test have high specificity in the diagnosis of hypersensitivity caused by antituberculosis drugs, and the specific T lymphocyte test is better than the specific plasma cell test. It is of great significance to guide the clinical application of antituberculosis drugs.

Background The clinical manifestations and factors associated with the severity of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections outside of Wuhan are not clearly understood. Methods All laboratory-confirmed cases with SARS-Cov-2 infection who were hospitalized and monitored in Guangzhou Eighth People’s Hospital were recruited from January 20 to February 10. Results A total of 275 patients were included in this study. The median patient age was 49 years, and 63.6% had exposure to Wuhan. The median virus incubation period was 6 days. Fever (70.5%) and dry cough (56.0%) were the most common symptoms. A decreased albumin level was found in 51.3% of patients, lymphopenia in 33.5%, and pneumonia based on chest computed tomography in 86%. Approximately 16% of patients (n = 45) had severe disease, and there were no deaths. Compared with patients with nonsevere disease, those with severe disease were older, had a higher frequency of coexisting conditions and pneumonia, and had a shorter incubation period (all P Conclusions Most of the patients infected with SARS-CoV-2 in Guangzhou, China are not severe cases and patients with older age, male, and decreased albumin level were more likely to develop into severe ones.

As feature resolution and process variations continue to shrink for new nodes of both DUV and EUV lithography, the density and number of devices on advanced semiconductor masks continue to increase rapidly. These advances cause significantly increased pressure on the accuracy and efficiency of OPC and assist feature (AF) optimization methods for each subsequent process technology. To meet manufacturing yield requirements, significant wafer retargeting from the original design target is often performed before OPC to account for both lithographic limitations and etch effects. As retargeting becomes more complex and important, rule-table based approaches become ineffective. Alternatively, modelbased optimization approaches using advanced solvers, e.g., inverse lithography technology (ILT), have demonstrated process window improvement over rule-based approaches. However, model-based target optimization is computationally expensive which typically limits its use to smaller areas like hotspot repairs. In this paper, we present results of a method that uses machine-learning (ML) to predict optimal retargeting for line-space layers. In this method, we run ILT co-optimization of the wafer target and process window to generate the training data used to train a machine learning model to predict the optimum wafer target. We explore methods to avoid ML model overfitting and show the ML infrastructure used to integrate ML solution into a manufacturable OPC flow. Both lithographic quality and runtime performance are evaluated for an ML enabled retargeting flow, an ILT flow and a simple rule table flow at advanced node test cases.

Memory cells and access structures consume a large percentage of area in embedded devices so there is a high return from shrinking the cell area as much as possible. This aggressive scaling leads to very difficult resolution, 2D CD control and process window requirements. As the scaling drives lithography even deeper into the low-k1 regime, cooptimization of design layout, mask, and lithography is critical to deliver a production-worthy patterning solution. Computational lithography like Inverse Lithography Technology (ILT) has demonstrated it is an enabling technology to derive improved solutions over traditional OPC as reported in multiple prior publications. In this paper, we will present results of a study on advanced memory cell design optimization with Cell-Level ILT (CL-ILT) where significant design hierarchy can be retained during ILT optimization. Large numbers of cell design variations are explored with automatically generated patterns from ProteusTM Test Pattern Generator (TPG). Fully automated flows from pattern generation to mask synthesis with ILT, data analysis and results visualization are built on ProteusTM Work Flow (PWF) for exploring a fully parameterized design space of interest. Mask complexity including assist features (AF) types, rule or model based, and main feature segmentation are also studied to understand the impact on wafer lithographic performance. A heatmap view of results generated from this design exploration provides a clear and intuitive way to identify maximum design limits of memory cells. Comparison of results from ILT and traditional OPC will be presented as well with both wafer and simulation data.

Aircraft icing is a complex phenomenon involving flow, heat transfer, and phase transition, and the in-flight accretion of ice on aerodynamic surfaces presents a significant threat to the performance and safety of aircraft. The icing conditions have not only significant influence on the macroscopic morphology, physical and mechanical properties of the ice, but also great influence on the microstructure of icing characteristics. Fine prediction of icing process is an important foundation for assessing the impact of icing on aerodynamic characteristics and flight performance, and developing the aircraft icing protection system. Focusing on the microstructural features of aircraft icing, a phase-field method is developed for simulating the crystallization of supercooled water, and the influence of supercooling degree on crystal growth is investigated in this work. Based on the combination of icing tunnel experiment and microscopic image recognition, the relationship between the supercooling degree and nucleation rate of icing is obtained. Based on the phase-field method, the numerical simulation method for the prediction of microstructural features of aircraft icing is developed, and the microstructural evolution of icing under different supercooling conditions is analyzed. The results indicate that the phase-field method can predict the microstructural features effectively under supercooled conditions, which will be beneficial to understand the evolution mechanisms of aircraft icing and provide important basis for the characterization of icing features from qualitative to quantitative. The results are intended to illustratively show the potential of the phase-field model in computing and analyzing complex pattern formations in icing process, which will lay the foundation for fine prediction of aircraft icing.

This paper deals with the surface thermochemical effects on TPS-coupled aerothermodynamics in hypersonic Martian gas flow. An interface condition with finite-rate thermochemistry was established to balance the three-dimensional Navier-Stokes solver and TPS thermal response solver, and a series of coupled simulations of chemical non-equilibrium aerothermodynamics and structure heat transfer with various surface catalycities were performed for hypersonic Mars entries. The analysis of surface thermochemistry reveals that the surface chemical reactions have great contribution to aerodynamic heating, and the temperature-dependence of finite-rate catalysis highly influences the evolution of the coupling aerodynamic heating in the coupling process. For fixed free stream parameters with proper catalytic excitation energy, a “leap” phenomenon of the TPS-coupled heat flux with the coupling time appears in the initial stage of the coupling process, due to the strong thermochemical effects on the TPS surface.

Surface chemical effects have great influence on the prediction of hypersonic nonequilibrium aerodynamic heating, and they are particularly complex in a dissociated carbon–oxygen environment for th...

Aerodynamics, aerothermodynamics and thermal protection system response in high-enthalpy and high-speed flow is heat transfer with interface effects in nature. Modelling and simulation of these phenomena are of vital significance to ensure high-speed flight thermal safety. The heat transfer phenomena related with gas-surface interaction, interface heterogeneous reactions and microstructure morphology in high-enthalpy and high-speed flow were summarized. The modelling of interface effects and the corresponding coupling algorithms for computational fluid dynamics (CFD) and related approaches were reviewed. Recent research activities for interface problems in high-enthalpy and high-speed flow at China Aerodynamics Research and Development Center were discussed. They mainly focus on practical solutions of computational fluid dynamics with viscous wall boundary conditions, multi-zone coupling for fluid-thermal interaction and cross-scale algorithms of CFD coupled with smaller scale theoretical approaches. Finally, further perspectives about heat transfer with interface effects were proposed, including mesoscale experimental verification, interface cross-scale modelling and accuracy/uncertainty of coupling algorithms.

The anisotropic micro-structure of fiber will lead to the macroscopic anisotropic properties of fiber reinforced composites in both heat transfer and mechanical strength. However, few experimental studies have be made on the anisotropic heat transfer properties of fiber reinforced composites. In this study, the anisotropic thermal conductivities of two-dimensional (2D) plain woven and twill woven carbon-fiber/epoxy composites are measured at different temperature with the one-dimensional (1D) steady-state method, transient plane source (TPS) method and transient hot wire method, respectively. The out-of-plane thermal conductivity and in-plane thermal conductivity at the temperature ranging from −45 °C to 160 °C are obtained and comparisons are made among the three methods. The results show that all the three methods can be used to measure the anisotropic thermal conductivity of fiber/epoxy woven composites. Both the out-of-plane thermal conductivity and in-plane thermal conductivity of carbon-fiber/epoxy woven composites increase with temperature, and the in-plane thermal conductivity is approximately four times as high as the out-of-plane thermal conductivity for the plain woven composites. Compared with the results of 1D steady-state method, the max deviations of TPS method and hot wire method are 18.1% and 17.1%, respectively. The sources of error that leading to the deviations are also discussed.

Background: HBeAg-positive chronic infection is a unique phase of chronic hepatitis B virus (HBV) infection. Current guidelines advise against starting antiviral treatment for HBeAg-positive chronic hepatitis B virus (HBV) infection patients, some data suggest treating such patients may reduce the risk of hepatocellular carcinoma. We aimed to explore whether these patients can have evident histological liver injury (EHLI), and develop a non-invasive model for identifying EHLI in such patients. Method: We assessed whether HBeAg-positive chronic HBV infection patients can have EHLI defined by Ishak fibrosis stage ≥3 and/or histologic activity index ≥ 9 in a prospective multicenter study. Logistic and Lasso regression was used to select the optimal predictors. We used Akaike information criterion, discrimination improvement, net reclassification improvement to develop and validate models predicting EHLI risk in training cohort and two external validation cohorts. Findings: Of these 336 patients met the inclusion criteria, 181(54%) were HBeAg-positive chronic HBV infection, of whom 60 patients (33%) had EHLI, the proportion of significant fibrosis was higher than that of significant inflammation (33% vs. 8%, P

The difficulties involved in ramping EUV lithography to volume manufacturing have highlighted the critical task of understanding process, layout design and device interactions, and also of optimizing the overall product integration to reduce undesirable interactions. In this paper, we demonstrate mask synthesis methods that using rigorous EUV lithography models together with inverse lithography technology (ILT) for EUV process window and CD control improvement. To enable this new capability, we have linked the broad EUV physical effect modeling capability of our rigorous lithography simulator, Sentaurus Lithography (S-Litho), with our highly flexible production proven ILT mask synthesis solution (Proteus ILT). This new combined capability can take advantage of the wide range of EUV modeling capabilities including rigorous electromagnetic mask/substrate modeling. The advantages of using S-Litho rigorous simulation for ILT optimization is further benefited from significant speed enhancements using new high performance EUV mask 3D capabilities. ILT has been extensively used in a range of lithographic areas for DUV and EUV including logic hot-spot fixing, memory layout correction, dense memory cell optimization, assist feature (AF) optimization, source optimization, complex patterning design rules and design-technology co-optimization (DTCO). The combined optimization capability of these two technologies therefore will have a wide range of useful EUV applications. We will highlight the specific benefits of the rigorous DUV and EUV ILT functionality for several advanced applications including resist profile optimization for resist top- oss and resist descumming and process window improvement.

Hypersonic aircrafts and aero-engine combustion chambers both generate non-equilibrium and high-enthalpy flows and bring complex material-relied heat convection performance. The convective heating prediction is difficult due to unknown surface thermal state, leading to poor usability of wall temperature correlation method (WTCM). This paper aims at improving WTCM for convective heating prediction in chemically reacting flows through coupling computation of catalysis on thermal protection materials. Modified WTCM for chemically reacting flows accounts for two distinct physical events driven by temperature gradient and species reaction, which follow the Fourier’s and Fick’s laws, respectively. Preliminary validation testing demonstrates the feasibility of the modified WTCM to rapidly evaluate aerodynamic heating with limited deviation. The current research provides essential technical support for the evaluation and design of hypersonic aircrafts and aero-engine combustion chambers.

Hypersonic carbon dioxide reacting gas-surface interaction occurs on the heat shield of high-speed Mars entry capsules, which has great influences on the heat transfer characteristics. Based on hypersonic reacting flow solver with complex surface thermochemistry, the hypersonic chemical non-equilibrium flow with oxygen/carbon gas mixture was numerically simulated, and the interaction between non-equilibrium flow and surface reactions was numerically analyzed to reveal the mechanism of aerodynamic heating from surface thermochemistry. Numerical results of catalytic effects show that the near-wall thermochemical behaviors are essentially dominated by the near-wall diffusion and chemical reactions. Various surface reactions alter the flow structure in the boundary layer, and generate different aerodynamic heating patterns. Results from ablating simulations indicate that the ablating surface can induce additional near-wall diffusion and injection energy though their influence on the thermal boundary layer structure is neglectably small. The modeling of reacting gas-surface interaction can be of benefit to promoting the fidelity and precision of aerodynamic heating with complex surface thermochemistry.

Despite the large difficulties involved in extending 193i multiple patterning and the slow ramp of EUV lithography to full manufacturing readiness, the pace of development for new technology node variations has been accelerating. Multiple new variations of new and existing technology nodes have been introduced for a range of device applications; each variation with at least a few new process integration methods, layout constructs and/or design rules. This had led to a strong increase in the demand for predictive technology tools which can be used to quickly guide important patterning and design co-optimization decisions. In this paper, we introduce a novel hybrid predictive patterning method combining two patterning technologies which have each individually been widely used for process tuning, mask correction and process-design cooptimization. These technologies are rigorous lithography simulation and inverse lithography technology (ILT). Rigorous lithography simulation has been extensively used for process development/tuning, lithography tool user setup, photoresist hot-spot detection, photoresist-etch interaction analysis, lithography-TCAD interactions/sensitivities, source optimization and basic lithography design rule exploration. ILT has been extensively used in a range of lithographic areas including logic hot-spot fixing, memory layout correction, dense memory cell optimization, assist feature (AF) optimization, source optimization, complex patterning design rules and design-technology co-optimization (DTCO). The combined optimization capability of these two technologies will therefore have a wide range of useful applications. We investigate the benefits of the new functionality for a few of these advanced applications including correction for photoresist top loss and resist scumming hotspots.

Background: Non-invasive evaluation for liver fibrosis is of great clinical interest and value, but current models fail to accurately stage and differentiate each stage of liver fibrosis, especially in patients with chronic hepatitis B (CHB), and never taking off to be used clinically. Methods: This multicenter, prospective study used unbiased penalized logistic regression, assessed 30 variables referencing to histologic fibrosis stage in a large training cohort (n=800), and established simpler novel non-invasive program score (SNNPS). An independent validation cohort (n=400) was used to validate the SNNPS. Finally, a mobile program was then developed for one-step detailed calculation of certain hepatic fibrosis staging. Findings: Five variables-liver stiffness measurement (LSM), platelet counts, age, serum hyaluronic acid and spleen diameter, were identified as independent predictors for fibrosis stage and developing SNNPS that has AUCs of 0.893, 0.897, and 0.909 for significant fibrosis, advanced fibrosis, and cirrhosis, respectively. Using sub-models of SNNPS, S1 score ≤ 2.875 was 86% specific and 82% sensitive for mild fibrosis, S2 score ≤ 4.06 was 85% specific and 86% sensitive for significant fibrosis, and S3 score ≤ 4.402 or > 4.402 was 93% specific and 91% sensitive for advanced fibrosis or cirrhosis. In validation set, AUCs for significant fibrosis, advanced fibrosis, and cirrhosis were 0.904, 0.912, and 0.897, respectively. The SNNPS with highest LR and lowest LR- was significantly more specific and sensitive than AAR, APRI, LSM alone and Hepascore, and can be calculated via a mobile program in one-step. Interpretation: Using sophisticated mathematic modelling and a large multicenter study data developed and validated SNNPS that is superior to previously reported models, and can be easily calculated via mobile program to accurately diagnose various hepatic fibrosis stages in CHB patients in a wider range. Trial Registration Number: ClinicalTrials.gov. Identifier: NCT65418 Funding Information: National Major Science and Technology Special Project of China (2013ZX10005002). Competing Interest Declaration: The authors declare that there is no conflict of interest in this study Ethical Approval Statement: The study meets the requirements of Declaration of Helsinki, and protocol was approved by the ethics committee of each participating institution, and a written informed consent was obtained from all patients.

The Mars Science Laboratory (MSL) entry capsule has been designed as a lifting entry for sufficient deceleration and precise landing performance. This paper presents the static aerodynamics analysis of the MSL capsule in the hypersonic entry process for exploration mission to Mars. Hypersonic static coefficients were derived from fully three-dimensional computational fluid dynamics solutions with a specified effective specific heat ratio on a typical trajectory state. Aerodynamic performance analysis ascertains the trim characteristics and static stability of the capsule with respect to the center of gravity (CG) location. Analysis results obtained show that CG location determines the trim characteristics and the static stability, and certain CG radial and axial shift alters the lifting entry performance, so that proper aerodynamic configuration and inner equipment layout is needed for CG adjustment to satisfy the static aerodynamics requirements.

The 5nm and 7nm technology nodes will continue recent scaling trends and will deliver significantly smaller minimum features, standard cell areas and SRAM cell areas vs. the 10nm node. There are tremendous economic pressures to shrink each subsequent technology, though in a cost-effective and performance enhancing manner. IC manufacturers are eagerly awaiting EUV so that they can more aggressively shrink their technology than they could by using complicated MPT. The current 0.33NA EUV tools and processes also have their patterning limitations. EUV scanner lenses, scanner sources, masks and resists are all relatively immature compared to the current lithography manufacturing baseline of 193i. For example, lens aberrations are currently several times larger (as a function of wavelength) in EUV scanners than for 193i scanners. Robustly patterning 16nm L/S fully random logic metal patterns and 40nm pitch random logic rectangular contacts with 0.33NA EUV are tough challenges that will benefit from advanced OPC/RET. For example, if an IC manufacturer can push single exposure device layer resolution 10% tighter using improved ILT to avoid using DPT, there will be a significant cost and process complexity benefit to doing so. ILT is well known to have considerable benefits in finding flexible 193i mask pattern solutions to improve process window, improve 2D CD control, improve resolution in low K1 lithography regime and help to delay the introduction of DPT. However, ILT has not previously been applied to EUV lithography. In this paper, we report on new developments which extend ILT method to EUV lithography and we characterize the benefits seen vs. traditional EUV OPC/RET methods.

Many different advanced devices and design layers currently employ double patterning technology (DPT) as a means to overcome lithographic and OPC limitations at low k1 values. Certainly device layers with k1 value below 0.25 require DPT or other pitch splitting methodologies. DPT has also been used to improve patterning of certain device layers with k1 values slightly above 0.25, due to the difficulty of achieving sufficient pattern fidelity with only a single exposure. Unfortunately, this broad adoption of DPT also came with a significant increase in patterning process cost. In this paper, we discuss the development of a single patterning technology process using an integrated Inverse Lithography Technology (ILT) flow for mask synthesis. A single pattering technology flow will reduce the manufacturing cost for a k1 > 0.25 full chip random contact layer in a memory device by replacing the more expensive DPT process with ILT flow, while also maintaining good lithographic production quality and manufacturable OPC/RET production metrics. This new integrated flow consists of applying ILT to the difficult core region and traditional rule-based assist features (RBAFs) with OPC to the peripheral region of a DRAM contact layer. Comparisons of wafer results between the ILT process and the non-ILT process showed the lithographic benefits of ILT and its ability to enable a robust single patterning process for this low-k1 device layer. Advanced modeling with a negative tone develop (NTD) process achieved the accuracy levels needed for ILT to control feature shapes through dose and focus. Details of these afore mentioned results will be described in the paper.

EUV lithography is viewed as a highly desirable technology for 5nm and 7nm node patterning cost reduction and process simplicity. However, for the 5nm and 7nm nodes EUV not only needs to function in a low-K1 resolution environment but has several new and complex patterning issues which will need accurate compensation by mask synthesis tools and flows. The main new issues are: long-range flare variation across the chip, feature dependent focus offsets due to high mask topography, asymmetry inducing shadowing effects which vary across the lens slit, significantly higher lens aberrations, illumination source changes (across the lens and with time) and new resist exposure mechanisms. These solutions must be successfully deployed at low K1 values and must be integrated together to create OPC/RET flows which have high resolution, high accuracy, and are fast to deploy. Therefore, the combined requirements of low-K1 resolution, full reticle correction accuracy and process window can be even more challenging than in current optical lithography mask synthesis flows. Advanced computational methods such as ILT and model-based SRAF optimization are well known to have considerable benefits in process window and resolution for low-K1 193 lithography. However, these methods have not been well studied to understand their benefits for lower-K1 EUV lithography where fabs must push EUV resolution, 2D accuracy and process window to their limits. In this paper, we investigate where inverse lithography methods can improve EUV patterning weaknesses vs. traditional OPC/RET. We first show how ILT can be used to guide a better understanding of optimal solutions for EUV mask synthesis. We then provide detailed comparisons of ILT and traditional methods on a wide range of mask synthesis applications.

New inverse methods such as model-based SRAF placement, model-based SRAF optimization, and full main + assist feature ILT are well known to have considerable benefits in finding flexible mask pattern solutions to improve process window and CD control. These methods have traditionally relied on compact models that are tuned to match resist measurements at a single z-height or slice. At this slice in the resist, some critical failure modes such as top loss and scumming are not detected. In this paper, we describe and present results for a methodology to extend ILT’s process window improvement capabilities, and to co-optimize mask patterns with awareness of the resist profile. These improvements are proven to reduce the risk of patterning failures at the bottom and top of critical resist features, which a typical mask correction process would not alleviate. Ideally, mask optimization would use a full rigorous TCAD resist model to guide the correction at multiple heights in the resist. However, TCAD models are significantly slower than compact models in simulations and ILT already has high computational requirements. Therefore, we have generated compact models which are fitted to the TCAD model resist profile data. We show the significant process window improvements obtained with this new resist 3D aware ILT methodology.

The objective of the study was to investigate the heat transfer characteristics of a phase-change energy storage unit for thermal management. Considering the conduction in the solid and natural convection in the liquid, a physical and mathematical model for heat transfer was formulated. The governing conservation equations were solved using the finite-volume method on fixed grids. An enthalpy-porosity method was used for modeling the melting phenomenon of a phase-change energy storage unit. The time and space movement of the phase front, the temperature distribution, and the heat dissipation rate have been analyzed based on the model. The influence of the unit geometry, heat source location, and types of phase-change materials on the thermal performance of the energy storage unit were investigated. The model and numerical method were evaluated by comparing the numerical predictions with the experimental results. There was found to be excellent agreement between the calculation and experiment, indicating that the numerical method for heat transfer simulation of a phase-change energy storage unit is accurate. The results from the analysis elucidate the thermal performance of the phase-change energy storage unit and will provide the basis for the design and optimization of thermal management systems.

For semiconductor manufacturers moving toward advanced technology nodes -32nm, 22nm and below - lithography presents the greatest challenge, because it is fundamentally constrained by basic principles of optical physics. Because no major lithography hardware improvements are expected over the next couple years, Computational Lithography has been recognized by the industry as the key technology needed to drive lithographic performance. This implies not only simultaneous co-optimization of all the lithographic enhancement tricks that have been learned over the years, but that they also be pushed to the limit by powerful computational techniques and systems. Inspection presents another great challenge; Most mask rules are imposed not because of mask manufacturing constraints, but due to limitations of mask inspection tools. In addition, at the most advanced technology nodes, such as 32nm and 22nm, aggressive OPC and Sub-Resolution Assist Features (SRAFs), ILT, and SMO are required. Their use results in significantly increased mask complexity, making mask defect inspection and disposition more challenging than ever. In this paper, a single computational lithography and computational inspection framework based on Level Set Method is presented and explained in non-mathematical language. Results at the 32nm node and below are presented which demonstrate the benefits of Level-Set-Method-based ILT and IIT in design rule optimization, SMO, full-chip correction, and mask inspection.

In the first implimentation by Luminescent of ILT-enabled Source-Mask Optimization (SMO), an ILT-optimized mask was generated for each designated illumination condition as the source was swept through various parameter settings in order to find the best combination of source and mask. This approach has been successfully applied to explore and select lithography processes and design rules for advanced semiconductor technology nodes. In Luminescent's latest implimentation of ILT-enabled SMO, the same Level Set Method used in the mask optimization is used in the source optimization; in other words, the source map is represented by a level set function. During the optimization process, the level set function evolves to achieve a minimized cost function, where the cost function is defined as the difference between aerial image and ideal image (MEEF and DOF can also be used in the cost function) via a gradient flow, and the gradient flow is based on the cost function itself. This flow is interlaceded with the mask inversion flow so that a simultaneous mask & source co-optimization is achieved. In this paper a number of memory and logic device results at the 32nm node and below are presented to demonstrate the benefits of ILT-enabled SMO.

Background Chronic hepatitis B (CHB) can progress to cirrhosis, hepatocellular carcinoma (HCC) and ultimately liver-related death. Although oral antiviral therapy for patients with CHB reduces the risk of such complications, once cirrhosis is established, the benefits of antiviral therapy are not robustly demonstrated. According to traditional Chinese medicine (TCM), some Chinese herbal medicines promote blood circulation and soften hard masses, and therefore they may block and reverse hepatic fibrosis. The aim of this study is to evaluate the effects of TCM tablets of the compound biejia ruangan (RGT) administered for fibrosis, and entecavir (ETV), on the development of HCC in patients with CHB or hepatitis B virus (HBV)-related compensated cirrhosis. Methods/design This multicenter, centrally randomized, double-blind, placebo-controlled, parallel-group study is planned to complete within 5 years. For the study, 1,000 with CHB or HBV-related compensated cirrhosis are randomly assigned in a 1:1 ratio to a treatment group (0.5 mg ETV once daily; 2 g RGT three times daily) or a control group (0.5 mg ETV once daily; 2 g RGT dummy agent three times daily). The primary end points are the development of HCC and liver-related death. Secondary end points include disease progression and overall survival. Discussion Although antiviral therapy can achieve sustained suppression of HBV replication, thereby preventing cirrhosis, patients with CHB treated with nucleos(t)ide analogs (NUCs) retain a higher risk for HCC compared with patients with inactive disease. Although previous clinical trials with RGT have confirmed the efficacy of blocking and reversing hepatic fibrosis in patients with CHB or compensated cirrhosis, the long-term risk for HCC or disease progression in these patients treated with combination of RGT and NUCs compared with NUCs alone is unclear. Therefore, it is necessary to investigate the effects of the RGT blockade and reversal of hepatic fibrosis on the development of HCC in patients with CHB or HBV-related compensated cirrhosis in large, prospective, multicenter, double-blind, randomized, controlled trials in China. Trial registration ClinicalTrials.gov Identifier: NCT01965418. Date registered: 17 October 2013

Traditional segment-based model-based OPC methods have been the mainstream mask layout optimization techniques in volume production for memory and embedded memory devices for many device generations. These techniques have been continually optimized over time to meet the ever increasing difficulties of memory and memory periphery patterning. There are a range of difficult issues for patterning embedded memories successfully. These difficulties include the need for a very high level of symmetry and consistency (both within memory cells themselves and between cells) due to circuit effects such as noise margin requirements in SRAMs. Memory cells and access structures consume a large percentage of area in embedded devices so there is a very high return from shrinking the cell area as much as possible. This aggressive scaling leads to very difficult resolution, 2D CD control and process window requirements. Additionally, the range of interactions between mask synthesis corrections of neighboring areas can extend well beyond the size of the memory cell, making it difficult to fully take advantage of the inherent designed cell hierarchy in mask pattern optimization. This is especially true for non-traditional (i.e., less dependent on geometric rule) OPC/RET methods such as inverse lithography techniques (ILT) which inherently have more model-based decisions in their optimizations. New inverse methods such as model-based SRAF placement and ILT are, however, well known to have considerable benefits in finding flexible mask pattern solutions to improve process window, improve 2D CD control, and improve resolution in ultra-dense memory patterns. They also are known to reduce recipe complexity and provide native MRC compliant mask pattern solutions. Unfortunately, ILT is also known to be several times slower than traditional OPC methods due to the increased computational lithographic optimizations it performs. In this paper, we describe and present results for a methodology to greatly improve the ability of ILT to optimize advanced embedded memory designs while retaining significant hierarchy and cell design symmetry, therefore, have good turnaround time and CD uniformity. This paper will explain the enhancements which have been developed in order to overcome the traditional difficulties listed above. These enhancements are in the categories of local CD control, global chip processing options, process window benefit, turn-around time and hierarchy retention.

Model-driven target optimization using an ILT hotspot fixer is applied to line collapsing defects of 2- dimensional randomtest pattern of a very low K1 process. The target is moved by minimizing the process variation band and the pitches of hotspot points are relaxed.The image quality improvement is thenchecked. Model driven target optimized NILS and MEEF at the weakest hotspot point are improved to 1.22 and 5.5 from the values 0.79 and 10.6 of a traditional OPCwith advanced solver, respectively. The pattern collapsing hotspot is then validated to be repaired by optimizing target position. A full hotspot fixer flow including model-driven target optimization using ILT can also be extended into DFM applications.

A simple procedure for obtaining a background-free backscattering spectrum of a light-mass film on a heavy-mass substrate by a normal incidence/grazing exit geometry has been described. Using this method such films can be aligned rapidly and accurately, and the impurity or defect information on the films can be obtained without need for realignment. Example is given from MeV Li-3+ analysis of a deposited film of Si on a single crystal substrate of yttria-stabilized, cubic zirconia.

It is well known in the industry that the technology nodes from 30nm and below will require model based SRAF / OPC for critical layers to meet production required process windows. Since the seminal paper by Saleh and Sayegh[1][2] thirty years ago, the idea of using inverse methods to solve mask layout problems has been receiving increasing attention as design sizes have been steadily shrinking. ILT in its present form represents an attempt to construct the inverse solution to a constrained problem where the constraints are all possible phenomena which can be simulated, including: DOF, sidelobes, MRC, MEEF, EL, shot-count, and other effects. Given current manufacturing constraints and process window requirements, inverse solutions must use all possible degrees of freedom to synthesize a mask. Various forms of inverse solutions differ greatly with respect to lithographic performance and mask complexity. Factors responsible for their differences include composition of the cost function that is minimized, constraints applied during optimization to ensure MRC compliance and limit complexity, and the data structure used to represent mask patterns. In this paper we describe the level set method to represent mask patterns, which allows the necessary degrees of freedom for required lithographic performance, and show how to derive Manhattan mask patterns from it, which can be manufactured with controllable complexity and limited shot-counts. We will demonstrate how full chip ILT masks can control e-beam write-time to the level comparable to traditional OPC masks, providing a solution with maximized lithographic performance and manageable cost of ownership that is vital to sub-30nm node IC manufacturing.

For low k1 lithography the resolution of critical patterns on large designs can require advanced resolution enhancement techniques for masks including scattering bars, complicated mask edge segmentation and placement, etc. Often only a portion of a large layout will need this sophisticated mask design (the hotspot), with the remainder of layout being relatively simple for OPC methods to correct. In this paper we show how inverse lithography technology (ILT) can be used to correct selected regions of a large design after standard OPC has been used to correct the simple portions of the layout. The hotspot approach allows a computationally intensive ILT to be used in a limited way to correct the most difficult portions of a design. We will discuss the most important issues such as: model matching between ILT and OPC corrections; transition region corrections near the ILT and OPC boundary region; mask complexity; total combined runtime. We will show both simulated and actual wafer lithographic improvements in the hotspot regions.