Does desorption affect the length distributions of nanowires?

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Continuous development of thin film deposition technologies is essential for the fabrication of films that meet the specific requirements of their target applications and working conditions. Therefore, it is necessary to increase the number of accessible a ...

The purpose of this article is to develop and study a decentralized strategy for Pareto optimization of an aggregate cost consisting of regularized risks. Each risk is modeled as the expectation of some loss function with unknown probability distribution, ...

Application of a single metal or alloy is often restricted by its properties from optimal combination of performance and cost. Therefore, there is a vast need of joining dissimilar metals for various applications in biomedical, aerospace, automobile and ma ...

Electron transport layers (ETLs) used as components of photocathodes for light-driven CO2 reduction (CO2R) in aqueous media should have good electronic transport, be stable under CO2R conditions, and, ideally, be catalytically inert for the competing hydro ...

The ubiquity of distributed machine learning (ML) in sensitive public domain applications calls for algorithms that protect data privacy, while being robust to faults and adversarial behaviors. Although privacy and robustness have been extensively studied ...

Stencil lithography (SL), which uses a perforated membrane as a reusable shadow mask to locally add material patterns on substrates provides a simple but versatile approach for the fabrication of functional devices on a large variety of substrate materials ...

We study the problem of learning unknown parameters of stochastic dynamical models from data. Often, these models are high dimensional and contain several scales and complex structures. One is then interested in obtaining a reduced, coarse-grained descript ...

Outliers in discrete choice response data may result from misclassification and misreporting of the response variable and from choice behaviour that is inconsistent with modelling assumptions (e.g. random utility maximisation). In the presence of outliers, ...

One major challenge in distributed learning is to efficiently learn for each client when the data across clients is heterogeneous or non iid (not independent or identically distributed). This provides a significant challenge as the data of the other client ...

Image noise can often be accurately fitted to a Poisson-Gaussian distribution. However, estimating the distribution parameters from a noisy image only is a challenging task. Here, we study the case when paired noisy and noise-free samples are accessible. N ...

The goal of this paper is to characterize function distributions that general neural networks trained by descent algorithms (GD/SGD), can or cannot learn in polytime. The results are: (1) The paradigm of general neural networks trained by SGD is poly-time ...

Machine learning (ML) applications are ubiquitous. They run in different environments such as datacenters, the cloud, and even on edge devices. Despite where they run, distributing ML training seems the only way to attain scalable, high-quality learning. B ...

There is sustained and widespread interest in understanding the limit, if there is any, to the human life span. Apart from its intrinsic and biological interest, changes in survival in old age have implications for the sustainability of social security sys ...

This thesis reports on the study and use of low temperature processes for the deposition of indium gallium nitride (InGaN) thin films in order to alleviate some of the present drawbacks of its monolitic deposition on silicon for photovoltaic applications. ...

Does desorption affect the length distributions of nanowires?

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