Mitigating Detrimental Effect of Self-Doping Near the Anode in Highly Efficient Organic Solar Cells

Poly(3,4-ethylenedioxythiophene):polystyrene sulfonate (PEDOT:PSS) has been one of the most established hole transport layers (HTL) in organic solar cells (OSCs) for several decades. However, the presence of PSS⁻ ions is known to deteriorate device performance via a number of mechanisms including diffusion to the HTL-active layer interface and unwanted local chemical reactions. In this study, it is shown that PSS⁻ ions can also result in local p-doping in the high efficiency donor:non-fullerene acceptor blends – resulting in photocurrent loss. To address these issues, a facile and effective approach is reported to improve the OSC performance through a two-component hole transport layer (HTL) consisting of a self-assembled monolayer of 2PACz ([2-(9H-Carbazol-9-yl)ethyl]phosphonic acid) and PEDOT:PSS. The power conversion efficiency (PCE) of 17.1% using devices with PEDOT:PSS HTL improved to 17.7% when the PEDOT:PSS/2PACz two-component HTL is used. The improved performance is attributed to the overlaid 2PACz layer preventing the formation of an intermixed p-doped PSS⁻ ion rich region (≈5–10 nm) at the bulk heterojunction-HTL contact interface, resulting in decreased recombination losses and improved stability. Moreover, the 2PACz monolayer is also found to reduce electrical shunts that ultimately yield improved performance in large area devices with PCE enhanced from 12.3% to 13.3% in 1 cm² cells.     

A graph-based framework for model-driven optimization facilitating impact analysis of mutation operator properties

Optimization problems in software engineering typically deal with structures as they occur in the design and maintenance of software systems. In model-driven optimization (MDO), domain-specific models are used to represent these structures while evolutionary algorithms are often used to solve optimization problems. However, designing appropriate models and evolutionary algorithms to represent and evolve structures is not always straightforward. Domain experts often need deep knowledge of how to configure an evolutionary algorithm. This makes the use of model-driven meta-heuristic search difficult and expensive. We present a graph-based framework for MDO that identifies and clarifies core concepts and relies on mutation operators to specify evolutionary change. This framework is intended to help domain experts develop and study evolutionary algorithms based on domain-specific models and operators. In addition, it can help in clarifying the critical factors for conducting reproducible experiments in MDO. Based on the framework, we are able to take a first step toward identifying and studying important properties of evolutionary operators in the context of MDO. As a showcase, we investigate the impact of soundness and completeness at the level of mutation operator sets on the effectiveness and efficiency of evolutionary algorithms.

     

Iron working at Zambana el Vato (TN), Italy

ABSTRACT

The workshop of Zambana el Vato (region Trentino, Northern Italy), is dated to the period between the 7th-6th and the 5th century BC. Iron working activities are clearly recognizable from the various finds. Among them there are working slag, heated clay, fragments of hearth or forge, hammerscale and more residues that can be referred to iron technology. A number of selected specimens were sectioned and mounted for photomicroscopy to identify the structure and some of the mounted samples were also examined by scanning electron microscopy (SEM) using both a back scattered electron detector and energy dispersive (EDS) x-ray analysis. This paper presents the results of these studies. The hearths were regularly repaired, as their fragments were found mixed with working slag. The hammerscale samples indicate that there were three iron-working areas. The fragments of forge with traces of tuyeres indicate that bellows were employed. Refining slag was identified among the debris. This is particularly significant as for the moment no iron refining centers are known in this area.     

Powell–Sabin B‐splines and unstructured standard T‐splines for the solution of the Kirchhoff–Love plate theory exploiting Bézier extraction

The equations that govern Kirchhoff–Love plate theory are solved using quadratic Powell–Sabin B‐splines and unstructured standard T‐splines. Bézier extraction is exploited to make the formulation computationally efficient. Because quadratic Powell–Sabin B‐splines result in ‐continuous shape functions, they are of sufficiently high continuity to capture Kirchhoff–Love plate theory when cast in a weak form. Unlike non‐uniform rational B‐splines (NURBS), which are commonly used in isogeometric analysis, Powell–Sabin B‐splines do not necessarily capture the geometry exactly. However, the fact that they are defined on triangles instead of on quadrilaterals increases their flexibility in meshing and can make them competitive with respect to NURBS, as no bending strip method for joined NURBS patches is needed. This paper further illustrates how unstructured T‐splines can be modified such that they are ‐continuous around extraordinary points, and that the blending functions fulfil the partition of unity property. The performance of quadratic NURBS, unstructured T‐splines, Powell–Sabin B‐splines and NURBS‐to‐NURPS (non‐uniform rational Powell–Sabin B‐splines, which are obtained by a transformation from a NURBS patch) is compared in a study of a circular plate. Copyright © 2015 John Wiley & Sons, Ltd.     

An approach for robust PDE-constrained optimization with application to shape optimization of electrical engines and of dynamic elastic structures under uncertainty

We present a robust optimization framework that is applicable to general nonlinear programs (NLP) with uncertain parameters. We focus on design problems with partial differential equations (PDE), which involve high computational cost. Our framework addresses the uncertainty with a deterministic worst-case approach. Since the resulting min–max problem is computationally intractable, we propose an approximate robust formulation that employs quadratic models of the involved functions that can be handled efficiently with standard NLP solvers. We outline numerical methods to build the quadratic models, compute their derivatives, and deal with high-dimensional uncertainties. We apply the presented approach to the parametrized shape optimization of systems that are governed by different kinds of PDE and present numerical results.     

Ultra-dense planar metallic nanowire arrays with extremely large anisotropic optical and magnetic properties

A nanofabrication method for the production of ultra-dense planar metallic nanowire arrays scalable to wafer-size is presented. The method is based on an efficient template deposition process to grow diverse metallic nanowire arrays with extreme regularity in only two steps. First, III–V semiconductor substrates are irradiated by a low-energy ion beam at an elevated temperature, forming a highly ordered nanogroove pattern by a “reverse epitaxy” process due to self-assembly of surface vacancies. Second, diverse metallic nanowire arrays (Au, Fe, Ni, Co, FeAl alloy) are fabricated on these III–V templates by deposition at a glancing incidence angle. This method allows for the fabrication of metallic nanowire arrays with periodicities down to 45 nm scaled up to wafer-size fabrication. As typical noble and magnetic metals, the Au and Fe nanowire arrays produced here exhibited large anisotropic optical and magnetic properties, respectively. The excitation of localized surface plasmon resonances (LSPRs) of the Au nanowire arrays resulted in a high electric field enhancement, which was used to detect phthalocyanine (CoPc) in surface-enhanced Raman scattering (SERS). Furthermore, the Fe nanowire arrays showed a very high in-plane magnetic anisotropy of approximately 412 mT, which may be the largest in-plane magnetic anisotropy field yet reported that is solely induced via shape anisotropy within the plane of a thin film.

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Investigation of charge carrier depletion in freestanding nanowires by a multi-probe scanning tunneling microscope

Profiling of the electrical properties of nanowires (NWs) and NW heterocontacts with high spatial resolution is a challenge for any application and advanced NW device development. For appropriate NW analysis, we have established a four-point prober, which is combined in vacuo with a state-of-the-art vapor-liquid-solid preparation, enabling contamination-free NW characterization with high spatial resolution. With this ultrahigh-vacuum-based multi-tip scanning tunneling microscopy (MT-STM), we obtained the resistance and doping profiles of freestanding NWs, along with surface-sensitive information. Our in-system 4-probe STM approach decreased the detection limit for low dopant concentrations to the depleted case in upright standing NWs, while increasing the spatial resolution and considering radial depletion regions, which may originate from surface changes. Accordingly, the surface potential of oxide-free GaAs NW {112} facets has been estimated to be lower than 20 mV, indicating a NW surface with very low surface state density.

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Toward a theory of managing creativity-intensive processes: a creative industries study

This paper reports the results of an exploratory, theory-building study on the impact of creativity on business processes, their management, and the use of information technology (IT) in particular. The empirical evidence was derived from organizations within the creative industries, specifically film and visual effects (VFX) production. An adapted grounded theory approach was employed in order to analyze the data. The study identifies the dynamics of business processes that can be described as highly dependent on creativity, intensively involving the client, complex, and interdependent. It explains the processes’ organizational context as well as strategies and IT systems that organizations use in order to manage these processes. The study suggests that creativity-intensive processes are characterized by high levels of uncertainty with regard to outcome, process structure, and required resources. Creative organizations pursue both creative and operational process performance while simultaneously mitigating creative and operational risk.