Process and device simulations aimed at improving the emitter region performance of silicon PERC solar cells

Achieved levels of Silicon-based passivated emitter and rear cell (PERC) solar cells' laboratory and module-level conversion efficiencies are still far from the theoretically achievable Auger limit of 29.4% for silicon solar cells, prominently due to emitter recombination and resistive losses. The emitter region in PERC devices is formed by using either ion implantation followed by a diffusion process or POCl3 diffusion. In ion-implanted emitter-based PERC, the process variables such as dose, energy, diffusion time, and temperature play a vital role in defining the characteristics of the emitter region. Detailed investigation of these parameters could provide a pathway to mitigate the recombination as well as resistive losses; however, it requires a considerable budget to optimize these parameters through a purely experimental approach. Therefore, advanced industrial standard process and device simulation are perceived in this work to carry out the comprehensive study of process variables. Investigation of ion implantation and diffusion process parameters on the PV performance of an upright pyramid textured, industrial standard stacked dielectric passivated PERC solar cell is carried out to deliver 22.8% conversion efficiency with improved PV parameters such as short circuit current density (JSC) of 40.8 mA/cm2, open-circuit voltage (VOC) of 686 mV, and fill-factor (FF) of 81.54% at optimized implantation and diffusion parameters, such as implantation dose of 5×1015 cm-2 with energy 30 keV followed 950 oC diffusion temperature and 30 min of diffusion time. The performance of the optimized PERC device is compared with already published large area screen printed contact-based device. This work may open up a window for the experimental work to understand the influence of process parameters on the emitter region to develop the highly efficient PERC solar cell in the future.

Exploring cell membrane water exchange in aquaporin-4-deficient ischemic mouse brain using diffusion-weighted MRI

Background Aquaporin-4 is a membrane channel protein that is highly expressed in brain astrocytes and facilitates the transport of water molecules. It has been suggested that suppression of aquaporin-4 function may be an effective treatment for reducing cellular edema after cerebral infarction. It is therefore important to develop clinically applicable measurement systems to evaluate and better understand the effects of aquaporin-4 suppression on the living body. Methods Animal models of focal cerebral ischemia were created by surgically occluding the middle cerebral artery of wild-type and aquaporin-4 knockout mice, after which multi-b-value multi-diffusion-time diffusion-weighted imaging measurements were performed. Data were analyzed with both the apparent diffusion coefficient (ADC) model and a compartmental water-exchange model. Results ADCs were estimated for five different b value ranges. The ADC of aquaporin-4 knockout mice in the contralateral region was significantly higher than that of wild-type mice for each range. In contrast, aquaporin-4 knockout mice had significantly lower ADC than wild-type mice in ischemic tissue for each b-value range. Genotype-dependent differences in the ADC were particularly significant for the lowest ranges in normal tissue and for the highest ranges in ischemic tissue. The ADCs measured at different diffusion times were significantly different for both genotypes. Fitting of the water-exchange model to the ischemic region data found that the water-exchange time in aquaporin-4 knockout mice was approximately 2.5 times longer than that in wild-type mice. Conclusions Multi-b-value multi-diffusion-time diffusion-weighted imaging may be useful for in vivo research and clinical diagnosis of aquaporin-4-related diseases.

Adsorption kinetics and equilibria of two methanol samples with different water content on activated carbon

To investigate the influence of fluid purity on the adsorption properties, adsorption kinetics and adsorption equilibria of two methanol samples with different water content on an activated carbon were studied. The purity of the methanol samples was 98.5% and 99.9%. Measurements were conducted at 298 K and 318 K using a magnetic suspension balance and cover a wide p/p0 range. To determine effective diffusion time constants and mass transfer coefficients, adsorption kinetics were evaluated using an isothermal and a nonisothermal Fickian diffusion model, and the linear driving force model. The pressure dependence of the kinetic parameters was studied and discussed. A small influence of sample purity on the adsorption equilibria was observed, as the purer methanol sample showed slightly higher equilibrium loadings than the less pure sample. However, significantly faster adsorption kinetics were observed for the purer sample at all temperature and pressure conditions. Compared to the less pure sample, the determined effective diffusion time constants and the mass transfer coefficients were up to 98% and 35% higher, respectively.

Modeling and Simulation of Vacuum Low Pressure Carburizing Process in Gear Steel

A combination of simulation and experimental approaches to optimize the vacuum carburizing process is necessary to replace the costly experimental trial-and-error method in time and resources. In order to accurately predict the microstructure evolution and mechanical properties of the vacuum carburizing process, a multi-field multi-scale coupled model considering the interaction of temperature, diffusion, phase transformation, and stress was established. Meanwhile, the improved model is combined with the heat treatment software COSMAP to realize the simulation of the low-pressure vacuum carburizing process. The low-pressure vacuum carburizing process of 20CrMo gear steel was simulated by COSMAP and compared with the experimental results to verify the model. The results indicated that the model could quantitatively obtain the carbon concentration distribution, Fe-C phase fraction, and hardness distribution. It can be found that the carbon content gradually decreased from the surface to the center. The surface carbon concentration is relatively high only after the carburizing stage. With the increase in diffusion time, the surface carbon concentration decreases, and the carburized layer depth increases. The simulated surface carbon concentration results and experimental results are in good agreement. However, there is an error between calculations and observations for the depth of the carburized layer. The error between simulation and experiment of the depth of carburized layer is less than 6%. The simulated surface hardness is 34 HV lower than the experimental surface hardness. The error of surface hardness is less than 5%, which indicates that the simulation results are reliable. Furthermore, vacuum carburizing processes with different diffusion times were simulated to achieve the carburizing target under specific requirements. The results demonstrated that the optimum process parameters are a carburizing time of 42 min and a diffusion time of 105 min. This provides reference and guidance for the development and optimization of the vacuum carburizing process.

Diffusion in Sephadex Gel Structures: Time Dependency Revealed by Multi-Sequence Acquisition over a Broad Diffusion Time Range

It has been increasingly reported that in biological tissues diffusion-weighted MRI signal attenuation deviates from mono-exponential decay, especially at high b-values. A number of diffusion models have been proposed to characterize this non-Gaussian diffusion behavior. One of these models is the continuous-time random-walk (CTRW) model, which introduces two new parameters: a fractional order time derivative α and a fractional order spatial derivative β. These new parameters have been linked to intravoxel diffusion heterogeneities in time and space, respectively, and are believed to depend on diffusion times. Studies on this time dependency are limited, largely because the diffusion time cannot vary over a board range in a conventional spin-echo echo-planar imaging sequence due to the accompanying T2 decays. In this study, we investigated the time-dependency of the CTRW model in Sephadex gel phantoms across a broad diffusion time range by employing oscillating-gradient spin-echo, pulsed-gradient spin-echo, and pulsed-gradient stimulated echo sequences. We also performed Monte Carlo simulations to help understand our experimental results. It was observed that the diffusion process fell into the Gaussian regime at extremely short diffusion times whereas it exhibited a strong time dependency in the CTRW parameters at longer diffusion times.

Diffusive time evolution of the Grad–Shafranov equation for a toroidal plasma

We describe the evolution of a plasma equilibrium having a toroidal topology in the presence of constant electric resistivity. After outlining the main analytical properties of the solution, we illustrate its physical implications by reproducing the essential features of a scenario for the upcoming Italian experiment Divertor Tokamak Test Facility, with a good degree of accuracy. Although we find the resistive diffusion time scale to be of the order of $10^4$ s, we observe a macroscopic change in the plasma volume on a time scale of $10^2$ s, comparable to the foreseen duration of the plasma discharge by design. In the final part of the work, we compare our self-consistent solution to the more common Solov'ev one, and to a family of nonlinear configurations.

Gas Damping in Capacitive MEMS Transducers in the Free Molecular Flow Regime

We present a novel analysis of gas damping in capacitive MEMS transducers that is based on a simple analytical model, assisted by Monte-Carlo simulations performed in Molflow+ to obtain an estimate for the geometry dependent gas diffusion time. This combination provides results with minimal computational expense and through freely available software, as well as insight into how the gas damping depends on the transducer geometry in the molecular flow regime. The results can be used to predict damping for arbitrary gas mixtures. The analysis was verified by experimental results for both air and helium atmospheres and matches these data to within 15% over a wide range of pressures.