The Walker-Anderson half-space penetration model has long been successfully used for the rapid, efficient calculation of penetration depth by rigid and eroding rods. These models align well with detailed simulations for thick targets; however, existing extensions for finite targets struggle to accurately capture nose-tail velocity profiles in thinner targets. For stack-ups of thin-walled targets, this deficiency results in mischaracterized rod-erosion relative to hydro-simulations or experimental predictions. In this work, we leverage insights from detailed hydro-simulations to propose an updated modification to the Walker-Anderson model to correctly account for wave propagation within a given target. This addition improves results for thin targets while retaining good behavior for thick targets with zero additional model parameters. Our updated model exhibits strong agreement with detailed simulations for penetrations through multiple thin targets.
Proton exchange membrane water electrolyser (PEMWE) is a promising technology for large-scale green hydrogen production and fuel decarbonisation. However, degradation of the anodic gas diffusion layer (GDL) significantly increases cell voltage and reduces efficiency, thereby limiting PEMWE durability and economic competitiveness for industrial deployment. Previous studies have primarily focused on mitigating GDL degradation and extending component lifetime, while the GDL degradation process itself has received limited attention. In this study, an experimentally validated multiphysics macroscale (mm-scale) PEMWE model combined with a quasi-steady state simulation framework is developed to investigate the GDL degradation process and its influence on PEMWE performance. The results reveal that TiO2 film growth at the GDL-ACL interface follows a distinct spatial evolution sequence, initiating at the edges of the GDL solid under the bipolar plate (BPP) rib, propagating towards the GDL solid junctions, and eventually extending to GDL solid under the BPP flow channel. The GDL degradation process exhibits accelerating behaviour with increasing operating time, leading to progressively increased GDL-ACL interface contact resistance (ICR), non-uniform current and oxygen generation rate distributions, local oxygen accumulation, and increasing cell voltage. Furthermore, the GDL physical structure optimisation mitigates GDL degradation and improves PEMWE long-term performance and efficiency preservation. The cell voltage increase under severe GDL degradation condition is reduced by approximately 36.9 %. Overall, this study provides mechanistic insights into GDL degradation process in PEMWE and offers practical guidance for designing high-efficiency and durable green hydrogen production systems.
We propose and investigate a new multi-level Monte Carlo scheme for numerical solutions of the kinetic Boltzmann equation for neutral species in edge plasmas. In particular, this method explicitly exploits a key structural property of neutral particle dynamics: the prevalence of frequent collisions for which the outgoing velocity is determined by local plasma parameters. Using this property, we derive a multi-level algorithm based on collision event propagator and show, both analytically and through numerical experiments, that it reproduces the results of standard Monte Carlo methods. We further demonstrate that, in the context of coupled plasma-neutral edge simulations employing correlated Monte Carlo, the proposed scheme retains trajectory correlation to machine precision as the system evolves, whereas conventional methods exhibit rapid decorrelation. These results indicate that the propagator-based multi-level Monte Carlo scheme is a promising candidate for use in fully implicit Jacobian-free Newton-Krylov (JFNK) solvers for coupled plasma-neutral systems.
Building on Frenkel’s century-old theoretical foundation for understanding defects, modern computational methods for studying defects in semiconductors and insulators have evolved from the initial interpretive tools to predictive approaches capable of guiding technological applications. In this article, we examine the current state and future directions of computational approaches for studying point defects in semiconductors. Density functional theory (DFT) has become the primary tool for defect calculations, with hybrid functionals proving essential for accurately describing electronic structure and charge localization effects that standard DFT cannot capture. We discuss recent advances in treating excited states and calculating experimentally observable properties from first principles. Current methods can predict thermodynamic properties within 0.1 eV accuracy and luminescence spectra with meV precision through sophisticated electron–phonon coupling treatments. Emerging techniques include quantum-embedding methods and machine learning interatomic potentials that promise to extend current capabilities while reducing computational costs. Future developments in exchange–correlation functionals and beyond-DFT methods offer exciting possibilities for further advancing computational defect physics.
Abstract Agriculture depletes soil organic carbon (SOC), partly due to the exclusion of deep‐rooted perennials. Reintroducing deep‐rooted perennials to cultivated land may help to mitigate SOC loss. We quantified the effect of deep roots on SOC by comparing 8 to 30 year‐old stands of switchgrass (Panicum virgatum L.) with paired annual row crop fields at 12 sites across the central and eastern USA. We hypothesized that switchgrass would store more root C and SOC than neighboring shallow‐rooted annual crops, and that these effects would extend deeper than 30 cm. We also evaluated whether switchgrass stimulates decomposition of SOC at depth using radiocarbon (14C). Finally, we explored whether the effect of switchgrass on SOC is moderated by soil chemical and physical properties. While the effect of switchgrass on SOC in the surface 100 cm was positive at most sites, the average effect was not statistically significant (difference in SOC = 0.6 kg C m−2 [95% CI −0.8 to +1.9 kg C m−2]). By contrast, we found that root C was consistently more abundant under switchgrass, yielding an estimated additional 0.6 kg C m−2 in the surface 100 cm of soil [95% CI +0.5 to +0.7 kg C m−2]. 14C measurements suggested that root C inputs were adding to existing SOC without stimulating decomposition. The effect of switchgrass on belowground C was not strongly related to any of the soil properties that we evaluated. Our observations show that root C can contribute substantially to belowground C stocks when deep‐rooted perennials replace shallow‐rooted crops.
