A comparative study of different emitter diffusion profiles on the performance of Si solar cells

We have investigated the effect of emitter design key parameters such as depth factor and the peak concentration for different types of emitter diffusion profiles (uniform, exponential, Gaussian, and Erfc) on the performance of silicon (Si) solar cells. The value of the depth factor is optimized as 0.1 µm for all these emitter diffusion profiles. Afterward, the peak concentration value is optimized for all the diffusion profiles. A close examination of relative diffusion lengths, conductivities, recombination rates, internal and external quantum efficiencies for these diffusion profiles revealed that among all the considered emitter diffusion profiles, the Erfc profile exhibits the maximum efficiency of 23.53% with an optimized peak concentration of 2×1020 cm-3 for emitter and 1×1019 cm-3 for the back surface filed doping. PC1D was used for all the simulations.

Low relative diffusion weighted image signal intensity can predict good prognosis after endovascular thrombectomy in patients with acute ischemic stroke

BackgroundIt is vital to identify a surrogate last-known-well time to perform proper endovascular thrombectomy in acute ischemic stroke; however, no established imaging biomarker can easily and quickly identify eligibility for endovascular thrombectomy and predict good clinical prognosis.ObjectiveTo investigate whether low relative diffusion-weighted imaging (DWI) signal intensity can be used as a predictor of good clinical outcome after endovascular thrombectomy in patients with acute ischemic stroke.MethodsWe retrospectively identified consecutive patients with acute ischemic stroke who were treated with endovascular thrombectomy within 24 hours of the last-known-well time and achieved successful recanalization (modified Thrombolysis in Cerebral Infarction score ≥2b). Relative DWI signal intensity was calculated as DWI signal intensity in the infarcted area divided by DWI signal intensity in the contralateral hemisphere. Good prognosis was defined as a modified Rankin Scale score of 0–2 at 90 days after stroke onset (good prognosis group).Results49 patients were included in the analysis. Relative DWI signal intensity was significantly lower in the group with good prognosis than in the those with poor prognosis (median (IQR) 1.32 (1.27–1.44) vs 1.56 (1.43–1.66); p<0.01), and the critical cut-off value for predicting good prognosis was 1.449 (area under the curve 0.78). Multiple logistic regression analysis revealed association of good prognosis after endovascular thrombectomy with low relative DWI signal intensity (OR=6.84; 95% CI 1.13 to 41.3; p=0.04).ConclusionsLow relative DWI signal intensity was associated with good prognosis after endovascular thrombectomy. Its ability to predict good clinical outcome shows potential for determining patient suitability for endovascular thrombectomy.

On Choosing the Optimal Impeller Exit Velocity Triangles in Preliminary Design

Impeller discharge flow plays an important role in centrifugal compressor performance and operability for two reasons. First, it determines the work factor and relative diffusion for the impeller. Second, it sets the flow into the downstream stationary diffusion system. The choice made in the preliminary design phase for the impeller exit velocity triangle is crucial for a successful design. The state-of-the-art design approach for determining the impeller exit velocity triangle in the preliminary design phase relies on several empirical guidelines, i.e. maximum work factor and diffusion ratio for an impeller, the optimal range of absolute flow angle, etc. However, as modern compressors continue pushing toward higher efficiency and higher work factor, this design approach falls short in providing exact guidance for choosing an optimal impeller exit velocity triangles due to its empirical nature as well as the competing mechanism of the two trends. In light of this challenge, this paper introduces a reduced-dimension, deterministic approach for the design of the impeller exit velocity triangle. The method gauges the design of the impeller exit velocity triangle from a different design philosophy using a relative diffusion effectiveness parameter and is validated using 6 impeller designs, representative of applications in both turbochargers and aero engines. Furthermore, with the deterministic method in place, optimal impeller exit velocity triangles are explored over a broad design space, and a one-to-one mapping from a selection of impeller total-to-total pressure ratios and backsweep angles to a unique optimal impeller exit velocity triangle is provided. This new approach is demonstrated, and discussions regarding the influences of impeller total-to-total pressure ratio, isentropic efficiency, and backsweep angle on the optimal impeller exit velocity triangle are presented.

A New Approach for Centrifugal Impeller Preliminary Design and Aerothermal Analysis

This paper introduces a new approach for the preliminary design and aerothermal analysis of centrifugal impellers using a relative diffusion effectiveness parameter. The relative diffusion effectiveness is defined as the ratio of the achieved diffusion to the maximum available diffusion in an impeller. It represents the quality of the relative diffusion process in an impeller. This parameter is used to evaluate impeller performance by correlating the relative diffusion effectiveness with the impeller isentropic efficiency using the experimental data acquired on a single-stage centrifugal compressor (SSCC). By including slip, which is appropriate considering it is an inviscid effect that should be included in the determination of maximum available diffusion in the impeller, a linear correlation between impeller efficiency and relative diffusion effectiveness resulted for all operating conditions. Additionally, a new method for impeller preliminary design was introduced using the relative diffusion effectiveness parameter, in which the optimal design is selected to maximize relative diffusion effectiveness. While traditional preliminary design methods are based on empirical loss models or empirical knowledge for selection of diffusion factor (DF) in the impeller, the new method does not require any such models, and it also provides an analytical approach for the selection of DF that gives optimal impeller performance. Validation of the method was performed using three classic impeller designs available in the open literature, and very good agreement was achieved. Furthermore, a sensitivity study shows that the method is robust in that the resulting flow angles at the impeller inlet and exit are insensitive to a wide range of blockage factors and various slip models.

Multimodal magnetic resonance imaging to identify stroke onset within 6 h in patients with large vessel occlusions

Introduction Mechanical thrombectomy within 6 h after stroke onset improves the outcome in patients with large vessel occlusions. The aim of our study was to establish a model based on diffusion weighted and perfusion weighted imaging to provide an accurate prediction for the 6 h time-window in patients with unknown time of stroke onset. Patients and methods A predictive model was designed based on data from the DEFUSE 2 study and validated in a subgroup of patients with large vessel occlusions from the AXIS 2 trial. Results We constructed the model in 91 patients from DEFUSE 2. The following parameters were independently associated with <6 h time-window and included in the model: interquartile range and median relative diffusion weighted imaging, hypoperfusion intensity ratio, core volume and the interaction between median relative diffusion weighted imaging and hypoperfusion intensity ratio as predictors of the 6 h time-window. The area under the curve was 0.80 with a positive predictive value of 0.90 (95%CI 0.79–0.96). In the validation cohort (N = 90), the area under the curve was 0.73 ( P for difference = 0.4) with a positive predictive value of 0.85 (95%CI 0.69–0.95). Discussion After validation in a larger independent dataset the model can be considered to select patients for endovascular treatment in whom stroke onset is unknown. Conclusion In patients with large vessel occlusion and unknown time of stroke onset an automated multivariate imaging model is able to select patients who are likely within the 6 h time-window.