Covalent Adaptable Microstructures via Combining Two-Photon Laser Printing and Alkoxyamine Chemistry: Toward Living 3D Microstructures

Manufacturing programmable materials, whose mechanical properties can be adapted on demand, is highly desired for their application in areas ranging from robotics, to biomedicine, or microfluidics. Herein, the inclusion of dynamic and living bonds, such as alkoxyamines, in a printable formulation suitable for two-photon 3D laser printing is exploited. On one hand, taking advantage of the dynamic covalent character of alkoxyamines, the nitroxide exchange reaction is investigated. As a consequence, a reduction of the Young´s Modulus by 50%, is measured by nanoindentation. On the other hand, due to its “living” characteristic, the chain extension becomes possible via nitroxide mediated polymerization. In particular, living nitroxide mediated polymerization of styrene results not only in a dramatic increase of the volume (≈8 times) of the 3D printed microstructure but also an increase of the Young's Modulus by two orders of magnitude (from 14 MPa to 2.7 GPa), while maintaining the shape including fine structural details. Thus, the approach introduces a new dimension by enabling to create microstructures with dynamically tunable size and mechanical properties.     

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.     

Estimating shear properties of walnut wood: a combined experimental and theoretical approach

In this study, several theoretical models to numerically estimate shear properties of orthotropic materials are introduced. These approaches are based on the combination of Hankinson’s empirically derived formula with other empirical and analytical calculations. Next to shear moduli, which are estimated from the elastic moduli and Poisson’s ratios, shear strengths are also estimated from the in-axis strengths. The models are validated by mechanical tests on walnut wood (Juglans regia L.), for which a sufficient data set can be found in literature. The Arcan test is used to estimate the shear moduli, while the shear block test is used to estimate the shear strengths. The results show that the model, which is based on a combined use of Hankinson’s formula and tensor rotation, gives the best estimation of shear moduli as evaluated by the minimum differences to the experimentally obtained results. For the shear strengths, a combination of Hankinson’s formula and Norris’ failure criterion shows the best agreement in comparison to the experimental data. The theoretical calculations may be used for a time efficient estimation of shear modulus and strength in comparison to the very time-consuming experimental estimation.     

Lateral Magnetically Modulated Multilayers by Combining Ion Implantation and Lithography

The combination of lithography and ion implantation is demonstrated to be a suitable method to prepare lateral multilayers. A laterally, compositionally, and magnetically modulated microscale pattern consisting of alternating Co (1.6 µm wide) and Co‐CoO (2.4 µm wide) lines has been obtained by oxygen ion implantation into a lithographically masked Au‐sandwiched Co thin film. Magnetoresistance along the lines (i.e., current and applied magnetic field are parallel to the lines) reveals an effective positive giant magnetoresistance (GMR) behavior at room temperature. Conversely, anisotropic magnetoresistance and GMR contributions are distinguished at low temperature (i.e., 10 K) since the O‐implanted areas become exchange coupled. This planar GMR is principally ascribed to the spatial modulation of coercivity in a spring‐magnet‐type configuration, which results in 180° Néel extrinsic domain walls at the Co/Co‐CoO interfaces. The versatility, in terms of pattern size, morphology, and composition adjustment, of this method offers a unique route to fabricate planar systems for, among others, spintronic research and applications.     

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.