BACKGROUND:Most pediatric patients present to general emergency departments, yet maintaining pediatric equipment, skilled staff, and resources remains a challenge for many hospitals. Pediatric readiness assessment is now a requirement for trauma center verification.OBJECTIVE:This study aims to assess the impact of a quality improvement initiative to improve emergency department pediatric readiness.METHODS:A pre- and poststudy design was used to evaluate a quality improvement initiative to improve the National Pediatric Readiness assessment survey results conducted at a Southwestern United States adult Level I trauma center from September 2022 to April 2023. The multicomponent initiative included implementing a pediatric emergency care coordinator, pediatric-specific policies and procedures, identifying pediatric-specific quality and performance indicators, and educating pediatric-specific staff. Study inclusion criteria were all patients younger than 18 years who presented to the emergency department. The primary outcome measure was the improvement in the weighted Pediatric Readiness Score. Secondary outcomes were throughput, nursing documentation of vital signs, and pain scores.RESULTS:A total of N = 2,356 patients met inclusion, of which n = 1,158 (49.2%) were in the preintervention group and n = 1,198 (50.8%) postintervention group. The weighted Pediatric Readiness Score improved by 45.4%. Transfers to a pediatric hospital increased from 4.1% to 8.6% (p = .016). Blood pressure documentation improved slightly from 88.3% to 88.6%. Pain score documentation decreased from 83.9% to 63.1% (p = .008). Pain medication and administration improved from 19.8% to 26.7% (p = .046).CONCLUSION:We found that participation in the quality improvement initiative was associated with emergency department pediatric readiness improvements.

This chapter explores the impact on supervision of recent changes in public health, and political and societal shifts. The revulsion at the murder of George Floyd and the Black Lives Matter movement have led organisations and individuals to examine how their attitudes are shaped by unconscious bias and privilege in terms of class, gender, race, ability and/or sexuality. This has affected relationships in the workplace between managers, trainees, colleagues and patients. During the pandemic, children were isolated and older relatives feared death and the future. Many children experienced increased parental violence and substance abuse without the protective eye of teachers, some went hungry. Adolescents were forced back into a position of dependence. Clinicians working online with children had to adapt to a new way of maintaining a therapeutic relationship with their patients, as online working could lead to a shift in the power dynamic. Children could switch off the screen or walk out, while the clinician could only look on. The author asks how the clinical supervisor can help the therapist manage these challenges to the therapeutic space? The author suggests that supervision in the future is going to be different from how it once was.

Modern semiconductor fabrication pushes the limits of chemistry and physics while simultaneously employing largescale, cutting-edge processing techniques. While fab expansion and capital expenditures continue to grow, the human element has become ever more demanding and prone to error. To assist with this issue, computer-aided process engineering, process control, and tool monitoring will continue to rise in the coming years. In this paper, we present an APC-integrated, customizable solution to an in-fab processing segment. Through machine learning, we combine information from design-specific extracted features with processing and metrology data to predict oxide deposition thickness. The result is a design-aware augmentation for current metrology that can recommend accurate process recipe conditions for new layouts. We also present experimental results highlighting the benefits of adding design-aware features with in-fab data to anchor and support each other across layouts and technologies. This result paves the way to decouple, isolate, and quantify the individual influences each processing step imposes on different designs at various stages of the fabrication flow.

ABSTRACT Background: Perceptions of autonomy in practice affect Neonatal Nurse Practitioner (NNP) job satisfaction, retention, and motivation to pursue NNP roles. However, Novice to Expert theory describes the processes for transitioning to nurse practitioner roles are not in relationship with NNP practice autonomy. Purpose: Relationships between Advanced Practice Registered Nurse (APRN) practice authority, state restrictions, APRN volume, and health care access exist. However, do APRN perceptions of autonomy relate to motivation to pursue practice authority? This study provides an exploration of perceptions of NNP practice autonomy in this context. Methodology: Semistructured interviews conducted with NNPs and neonatologists practicing in a restricted setting explored perceptions of practice expertise and autonomy, based on Patricia Benner's Novice to Expert theoretical framework. Laddered methodology organized survey questions, and the Framework Method was used for analysis of results. Results: The majority of eligible NNPs (n = 12, 67%) and neonatologists (n = 8, 67%) agreed to study participation. Identified themes were grouped into larger concepts, including “NNP practice authority,” “NNP expertise,” and “NNP autonomy.” For example, “NNP expertise” included the theme “determining NNP expertise” and associated factors included “procedural skills,” “years and acuity of practice level,” and “confidence in management plan and emergent situations.” Conclusions: Both neonatologists and NNPs perceived neonatologists as a practice authority with support for NNP autonomy. Factors indicating NNP expertise correlated with domains in Benner Novice to Expert theory. Implications: These findings support previous work concerning the evolution of expertise and transition to practice. More inquiry to understand perspectives of APRNs in restricted practice settings is indicated.

With 193nm optical lithography being extended to 12nm design rules and beyond, quality and performance requirements for photomasks are becoming increasingly challenged to support the increased pattern complexity. Additionally, interactions between mask, the lithography process, and OPC (Optical Proximity Correction) are becoming a more critical tool in tolerance reduction. One of the tools being used to reduce this variation is Mask Process Correction (MPC). Model-based Mask Process Correction (MB-MPC) is one of the key tools used to improve photomask Critical Dimension (CD) uniformity and provide high fidelity, and increase patterning stability of resolution limited features, such as assist features (SRAFs) at today’s leading-edge nodes. Since 2017, participants in the eBeam Initiative Mask Maker Survey have reported that MPC is considered a requirement for 16nm and below. Reduction of systematic photomask CD errors with MPC enables improvement of the accuracy of Optical Proximity Correction models by reducing mismatch between actual and modelled masks. While model-based MPC has been demonstrated to reduce mask fidelity and dimensional errors to sub 1nm on mask, one of the downsides is that it is a slow and resource intensive solution. An advanced model based MPC requires massive numbers of CPUs and their associated EDA licenses. In this paper, we will teach a technique for mitigation by use of a Rule-Based MPC (RB-MPC) solution with MB-MPC accuracy to reduce Mask Data Prep (MDP) runtime with no loss in patterning quality. We report on a full cycle of model to rule-based MPC simplification approaches and verification. We will describe the process by which we have been able to migrate a model-based MPC (MB-MPC) solution to a more cost effective, and equally accurate Rule-based MPC (RB-MPC) solution. This will included the methodology for derivation, implementation, and verification of the modified RB-MPC, which is based on both mask, and wafer performance metrics, and characterization of limitations of this process, as the challenges in converting to a RB-MPC from a MBMPC solution by application, including technology, mask process, target layer, and wafer-performance metrics.

The next generation beyond 7nm node potentially requires the implementation of Sub-Resolution Assist Features (SRAF) with EUV lithography. This paper aims at providing a clear SRAF strategy for the next generation beyond 7nm node designs through a series of experiments. Various factors are considered, including: stochastic effects, 3D mask effects, through-slit effects, aberrations, and pixelated SMO sources. EUV has 13.5nm as its wavelength, which is much smaller than the wavelength used in ArF lithography, and this gives very different imaging challenges compared to the ArF case. Due to the small wavelength and numerical aperture (NA) of the current EUV tools, depth of focus is not as significant of a concern as in DUV. Instead, EUV lithography is severely challenged by stochastic effects, which are directly linked to the slope of the intensity curve. DUV SRAF has been shown to be a powerful tool for improving NILS/ILS, as well as DOF, and here we explore how that translates into EUV imaging. In this paper, we consider Process Variability (PV) Bands with a variety of process conditions including focus/dose/mask bias changes and also the NILS/ILS as our objective functions, to determine what the best SRAF solution is for a set of test patterns. We have full investigations on both symmetric SRAF and asymmetric SRAF. SRAF can potentially mitigate image shift through focus, i.e. non-telecentricity, caused by EUV 3D shadowing effect. This shadowing effect is pattern dependent and contributes to the overlay variation. As we approach the next generation beyond 7nm node, this image shift can be more significant relative to the overlay budget, hence we further investigate the impact of SRAF placement to the image shift. Moreover, the Center of Focus shift due to the large 3D mask absorber thickness can be potentially mitigated by SRAF implementation. The common process window is significantly impacted by both the center of focus shift and the individual depth of focus. We study the change by adding SRAF using both a symmetric source (standard source) and an asymmetric source (SMO source). Once SRAF is inserted for the test patterns, the common process window is plotted to compare the solutions with and without SRAF. Finally, we understand the importance of using full flare map and full through slit model (including aberration variation through slit) in the main feature correction, but in this paper, we will further evaluate the need of using full models in SRAF insertion. This is a necessary step to determine the strategy of SRAF implementation for the next generation beyond 7nm node.

The next-generation beyond 7-nm node potentially requires the implementation of subresolution assist features (SRAF) with extreme ultraviolet (EUV) lithography. This paper aims at providing a clear SRAF strategy for the next-generation beyond 7-nm node designs through a series of experiments. Various factors are considered, including stochastic effects, three-dimensional (3-D) mask effects, through-slit effects, aberrations, and pixelated source mask optimization (SMO) sources. We consider process variability bands with a variety of process conditions, including focus/dose/mask bias changes and also the normalized image log-slope/image log-slope as our objective functions, to determine what the best SRAF solution is for a set of test patterns. Inverse lithography technology is implemented to optimize both the main feature (MF) mask and SRAF placement, in particular, asymmetric SRAF placement to balance the 3-D mask effects. SRAF can potentially mitigate image shift through-focus, i.e., nontelecentricity, caused by EUV 3-D shadowing effect. This shadowing effect is pattern-dependent and contributes to the overlay variation. As we approach the next-generation beyond 7-nm node, this image shift can be more significant relative to the overlay budget, hence, we further investigate the impact of SRAF placement to the image shift. Moreover, the center of focus shift due to the large 3-D mask absorber thickness can be potentially mitigated by SRAF implementation. The common process window is significantly impacted by both the center of focus shift and the individual depth of focus and is evaluated using both metal and contact layer test cases. We study the source impact to SRAF insertion by experimenting with both a symmetric source (standard source) and an asymmetric source (SMO source). Finally, we understand the importance of using full flare map and full through-slit model (including aberration variation through-slit) in the MF correction. Furthermore, we evaluate the need of using full models in SRAF insertion. This is a necessary step to determine the strategy of SRAF implementation for the next-generation beyond 7-nm node. (C) 2018 Society of Photo-Optical Instrumentation Engineers (SPIE)

Edge position variation in EUV patterns is significantly affected by stochastic phenomena that occur during the EUV exposure and the chemical processes in photoresist. Hence, it is important to understand and quantify the contribution of each of the stochastic effects to the edge roughness. In this work, various computational approaches are used based on the rigorous stochastic resist model in order to assess the stochastic contribution of photon absorption and random chemical reactions in EUV photoresist. The simulation results are presented for both the traditional chemically amplified EUV resists and resists utilizing alternative mechanisms of image formation, such as metal based-resists.

As the EUV lithography is extending beyond 7nm technology, design to mask strategy becomes more complex. New challenges including advanced OPC and ILT in mask optimization, curvilinear masks, shrinking Mask Rule Checking (MRC), Sub-Resolution Assist Features (SRAF) generation and formation, and other complex mask geometries drive the needs to study this synergy from different stages of the flow from Optical Proximity Correction (OPC), Mask Process Correction (MPC), fracturing, to mask writing and inspection. In this study, different OPC and SRAF mask formations including curvilinear masks, controlled Manhattanized approximations of curvilinear masks, and conventional masks are generated. We illustrate whether curvilinear masks have any demonstrable lithographic benefits. A quantitative comparison of how the Manhattanization impacts mask formation is carried out. The image quality metrics such as Image Log Slope (ILS), Process Viability (PV) Band, and Depth of Focus (DOF) from various OPC mask flavors including different MRC settings and different mask forms are compared and discussed. The mask manufacturability study is conducted to identify any major challenges and approaches to minimize them, including assessing the value and need for native curvilinear write tool support on a MultiBeam Mask Writer (MBMW) or a single beam Vector Shaped Beam (VSB) mask writer.

We report a systematic study of the feasibility of using directed self-assembly (DSA) in real product design for 7-nm fin field effect transistor (FinFET) technology. We illustrate a design technology co-optimization (DTCO) methodology and two test cases applying both line/space type and via/cut type DSA processes. We cover the parts of DSA process flow and critical design constructs as well as a full chip capable computational lithography framework for DSA. By co-optimizing all process flow and product design constructs in a holistic way using a computational DTCO flow, we point out the feasibility of manufacturing using DSA in an advanced FinFET technology node and highlight the issues in the whole DSA ecosystem before we insert DSA into manufacturing. (C) 2017 Society of Photo-Optical Instrumentation Engineers (SPIE)

The effects of thermal fluctuations in graphoepitaxy DSA are studied using simulations based on the self-consistent field theory (SCFT) model. The known method of using an external potential field to displace or deform the DSA cylinder is employed to study the dependencies of the fluctuations of the position and the size of the DSA cylinder as a function of the confinement well diameter. An explanation to local minima of these dependencies is proposed. A new and faster method to estimate the effects of fluctuations in DSA based on a family of transformations of SCFT potential fields is described and tested.

Minimization and control of line-edge roughness (LER) and contact-edge roughness (CER) is one of the current challenges limiting EUV line-space and contact hole printability. One significant contributor to feature roughness and CD variability in EUV is photon shot noise (PSN); others are the physical and chemical processes in photoresists, known as resist stochastic effect. Different approaches are available to mitigate each of these contributions. In order to facilitate this mitigation, it is important to assess the magnitude of each of these contributions separately from others. In this paper, we present and test a computational approach based on the concept of an 'ideal resist'. An ideal resist is assumed to be devoid of all resist stochastic effects. Hence, such an ideal resist can only be simulated as an 'ideal resist model' (IRM) through explicit utilization of the Poisson statistics of PSN2 or direct Monte Carlo simulation of photon absorption in resist. LER estimated using IRM, thus quantifies the exclusive contribution of PSN to LER. The result of the simulation study done using IRM indicates higher magnitude of contribution (60%) from PSN to LER with respect to total or final LER for a sufficiently optimized high dose 'state of the art' EUV chemically amplified resist (CAR) model.

The optimization problem of reducing EUV line edge roughness (LER) of a given feature, subject to the tolerance constraints on a CD of this feature at nominal EUV process conditions and several off-nominal conditions, is formulated. A stochastic rigorous Monte-Carlo EUV resist model is employed to solve this stochastic optimization problem. Several options for optimization algorithms, suitable for the solution of the formulated EUV LER optimization problem, are presented and discussed, along with the results of their tests.

In this paper, we discuss the lithographic qualification of high transmission (High T) mask for Via and contact hole applications in 10nm node and beyond. First, the simulated MEEF and depth of focus (DoF) data are compared between the 6% and High T attnPSM masks with the transmission of High T mask blank varying from 12% to 20%. The 12% High T blank shows significantly better MEEF and larger DoF than those of 6% attnPSM mask blank, which are consistent with our wafer data. However, the simulations show no obvious advantage in MEEF and DoF when the blank transmittance is larger than 12%. From our wafer data, it has been seen that the common process window from High T mask is 40nm bigger than that from the 6% attnPSM mask. In the elongated bar structure with smaller aspect ratio, 1.26, the 12% High T mask shows significantly less develop CD pull back in the major direction. Compared to the High T mask, the optimized new illumination condition for 6% attnPSM shows limited improvement in MEEF and the DoF through pitch. In addition, by using the High T mask blank, we have also investigated the SRAF printing, side lobe printing and the resist profile through cross sections, and no patterning risk has been found for manufacturing. As part of this work new 12% High T mask blank materials and processes were developed, and a brief overview of key mask technology development results have been shared. Overall, it is concluded that the High T mask, 12% transmission, provides the most robust and extendable lithographic solution for 10nm node and beyond.

Self-Aligned Via (SAV) process is commonly used in back end of line (BEOL) patterning. As the technology node advances, tightening CD and overlay specs require continuous improvement in model accuracy of the SAV process. Traditional single layer Variable Etch Bias (VEB) model is capable of describing the micro-loading and aperture effects associated with the reactive ion etch (RIE), but it does not include effects from under layers. For the SAV etch, a multi-layer VEB model is needed to account for the etch restriction from metal trenches. In this study, we characterize via post-etch dimensions through pitch and through metal trench widths, and show that VEB model prediction accuracy for SAV CDs after SAV formation can be significantly improved by applying a multi-layer scheme. Using a multi-layer VEB, it is demonstrated that the output via size changes with varying trench dimensions, which matches the silicon results. The model also reports via shape post-etch as a function of trench environment, where elliptical vias are correctly produced. The multi-layer VEB model can be applied both multi-layer correction and verification in full chip flow. This paper will also suggest that the multi-layer VEB model can be used in other FEOL layers with interlayer etch process effects, such as gate cut, to support the robustness of new model.

A methodology to determine the optimum measurement condition of extreme ultraviolet (EUV) resist patterns in a critical dimension scanning electron microscope has been established. Along with many parameters that need to be optimized simultaneously, there are conflicting requirements of small resist shrinkage and high measurement precision. To overcome these difficulties, we have developed a methodology for ArF resist patterns from shrinkages and precisions predicted by the Taguchi method. In this study, we examined the extendibility of the methodology to sub-20 nm EUV resist patterns. The predicted shrinkage by the Taguchi method for an 18 nm EUV resist pattern showed a large prediction error due to its different dependence on acceleration voltage from ArF, so we used the shrinkage curve to predict shrinkage instead of the Taguchi method, as shrinkage depends only on irradiated electron dose. In contrast, precision can be predicted well by the Taguchi method as with ArF. We propose a methodology that consists of separate prediction procedures for shrinkage and precision using the shrinkage curve and Taguchi method, respectively. The proposed method was applied to an 18-nm EUV resist pattern. The optimum measurement condition with shrinkage of 1.5 nm and precision of 0.12 nm was determined. (C) 2016 Society of Photo-Optical Instrumentation Engineers (SPIE)