Abstract-Single halo p-MOSFETs with channel lengths down to 100 nm are optimized, fabricated, and characterized as part of this study. We show extensive device characterization results to study the effect of large angle adjust implant parameters on device performance and hot carrier reliability. Results on both conventionally doped and single halo p-MOSFETs have been presented for comparison purposes.

Abstract-This paper reports study of metal-oxide-semiconductor (MOS) capacitors with 2.2 nm dry and N O grown gate dielectrics. Interface trap generation during constant voltage stressing at different operating temperatures (from 22 C to 90 C) has been investigated. The effect of nitrogen annealing (20 min) at 400 C on high temperature stress-induced interface traps was also studied.Index Terms-Oxynitrides, SILC, temperature dependence of interface trap generation, ultra-thin oxides.

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<p>Power-law distributions occur in a diverse range of phenomena. Natural drainage networks also exhibit distinctive fractal properties and certain power-law scaling relationships irrespective of the underlined controls, such as geology, topography, and climate. Here we study the distribution of basin areas of continents as well as some islands. We used area-fraction vs. rank distribution, where the area fraction represents the area of a basin with respect to the total landscape area. To obtain the basin area distribution, we used HydroRivers data for the nine continent regions and performed DEM analysis for 12 islands. The results show that basin area distribution follows a power law in the case of all continents with scaling exponent ranging from -1.15 to -1.4. In the case of islands, the majority of them followed power law scaling with exponent ranging from -1.2 to around -2.5; however, distributions of some islands deviated from the power laws.</p> <p>We also looked at the basin area distribution with the optimal channel network model with all boundary pixels modelled as outlets. We got the scaling exponent around -1.8. Our recently proposed probabilistic model for drainage network evolution (Borse & Biswal, 2023) shows the capability to produce networks with different distributions. This model can capture the varying range of exponents with its flexible parameters. Further studies would be needed to understand the significance of this basin area distribution scaling exponent and whether it could be used as a metric to characterize landscapes.</p>

<p><span>River networks have been studied in geosciences and hydrology for many theoretical and practical purposes. Self-organization into self-similar tree-like network patterns is observed in many natural phenomena including river networks, blood vessels, vascular organization in plants, lightning etc. River networks self-organize into tree-like network patterns as a result of complex landscape evolution processes. All of these patterns follow certain statistical scaling laws. There have been attempts to explain river network evolution, but it is still unclear how networks self-organize into such patterns. These power-law scaling relationships mainly include Hack’s law, exceeding probability distribution for contributing area and upstream length. Although various models exist in the literature, many questions related to river-network evolution are yet to be answered. In particular, the existing models try little to explain the diversity of network characteristics. We propose a new modeling framework that explains drainage network evolution considering certain key physical processes associated with randomness. The model follows the growth of drainage networks in the headward direction based on probabilistic decisions. The model comprises two free parameters and is demonstrated using a planar matrix. The simulation results show the formation of tree-like drainage networks that exhibit power-law scaling relationships as observed in natural river networks. Furthermore, the model parameters provide flexibility to generate networks with different shapes and characteristics.</span></p>