Showing papers by "Eindhoven University of Technology published in 2013"

Leveraging External Sources of Innovation: A Review of Research on Open Innovation

Abstract: This article reviews research on open innovation that considers how and why firms commercialize external sources of innovations. It examines both the “outside-in” and “coupled” modes of Enkel et al. (2009). From an analysis of prior research on how firms leverage external sources of innovation, it suggests a four-phase model in which a linear process — (1) obtaining, (2) integrating and (3) commercializing external innovations — is combined with (4) interaction between the firm and its collaborators. This model is used to classify papers taken from the top 25 innovation journals identified by Linton and Thongpapan (2004), complemented by highly cited work beyond those journals. A review of 291 open innovation-related publications from these sources shows that the majority of these articles indeed address elements of this inbound open innovation process model. Specifically, it finds that researchers have front-loaded their examination of the leveraging process, with an emphasis on obtaining innovations from external sources. However, there is a relative dearth of research related to integrating and commercializing these innovations.Research on obtaining innovations includes searching, enabling, filtering, and acquiring — each category with its own specific set of mechanisms and conditions. Integrating innovations has been mostly studied from an absorptive capacity perspective, with less attention given to the impact of competencies and culture (including not-invented-here). Commercializing innovations puts the most emphasis on how external innovations create value rather than how firms capture value from those innovations. Finally, the interaction phase considers both feedback for the linear process and reciprocal innovation processes such as co-creation, network collaboration and community innovation.This review and synthesis suggests several gaps in prior research. One is a tendency to ignore the importance of business models, despite their central role in distinguishing open innovation from earlier research on inter-organizational collaboration in innovation. Another gap is a tendency in open innovation to use “innovation” in a way inconsistent with earlier definitions in innovation management. The article concludes with recommendations for future research that include examining the end-to-end innovation commercialization process, and studying the moderators and limits of leveraging external sources of innovation.

A meta-analysis of the cognitive and motivational effects of serious games

Abstract: It is assumed that serious games influences learning in 2 ways, by changing cognitive processes and by affecting motivation. However, until now research has shown little evidence for these assumptions. We used meta-analytic techniques to investigate whether serious games are more effective in terms of learning and more motivating than conventional instruction methods (learning: k = 77, N 5,547; motivation: k = 31, N 2,216). Consistent with our hypotheses, serious games were found to be more effective in terms of learning (d= 0.29, p .05) than conventional instruction methods. Additional moderator analyses on the learning effects revealed that learners in serious games learned more, relative to those taught with conventional instruction methods, when the game was supplemented with other instruction methods, when multiple training sessions were involved, and when players worked in groups.

Periodic event-triggered control for nonlinear systems

Abstract: Event-triggered control (ETC) is a control strategy that is especially suited for applications where communication resources are scarce. By updating and communicating sensor and actuator data only when needed for stability or performance purposes, ETC is capable of reducing the amount of communications, while still retaining a satisfactory closed-loop performance. In this paper, an ETC strategy is proposed by striking a balance between conventional periodic sampled-data control and ETC, leading to so-called periodic event-triggered control (PETC). In PETC, the event-triggering condition is verified periodically and at every sampling time it is decided whether or not to compute and to transmit new measurements and new control signals. The periodic character of the triggering conditions leads to various implementation benefits, including a minimum inter-event time of (at least) the sampling interval of the event-triggering condition. The PETC strategies developed in this paper apply to both static state-feedback and dynamical output-based controllers, as well as to both centralized and decentralized (periodic) event-triggering conditions. To analyze the stability and the L2-gain properties of the resulting PETC systems, three different approaches will be presented based on 1) impulsive systems, 2) piecewise linear systems, and 3) perturbed linear systems. Moreover, the advantages and disadvantages of each of the three approaches will be discussed and the developed theory will be illustrated using a numerical example.

Low-transition-temperature mixtures (LTTMs): a new generation of designer solvents.

Abstract: A new generation of designer solvents emerged in the last decade as promising green media for multiple applications, including separation processes: the low-transition-temperature mixtures (LTTMs). They can be prepared by mixing natural high-melting-point starting materials, which form a liquid by hydrogen-bond interactions. Among them, deep-eutectic solvents (DESs) were presented as promising alternatives to conventional ionic liquids (ILs). Some limitations of ILs are overcome by LTTMs, which are cheap and easy to prepare from natural and readily available starting materials, biodegradable, and renewable.

Business Process Management: A Comprehensive Survey

Abstract: Business Process Management (BPM) research resulted in a plethora of methods, techniques, and tools to support the design, enactment, management, and analysis of operational business processes. This survey aims to structure these results and provide an overview of the state-of-the-art in BPM. In BPM the concept of a process model is fundamental. Process models may be used to configure information systems, but may also be used to analyze, understand, and improve the processes they describe. Hence, the introduction of BPM technology has both managerial and technical ramifications and may enable significant productivity improvements, cost savings, and flow-time reductions. The practical relevance of BPM and rapid developments over the last decade justify a comprehensive survey.

Ion-association complexes unite classical and non-classical theories for the biomimetic nucleation of calcium phosphate

Abstract: Despite its importance in many industrial, geological and biological processes, the mechanism of crystallization from supersaturated solutions remains a matter of debate. Recent discoveries show that in many solution systems nanometre-sized structural units are already present before nucleation. Still little is known about the structure and role of these so-called pre-nucleation clusters. Here we present a combination of in situ investigations, which show that for the crystallization of calcium phosphate these nanometre-sized units are in fact calcium triphosphate complexes. Under conditions in which apatite forms from an amorphous calcium phosphate precursor, these complexes aggregate and take up an extra calcium ion to form amorphous calcium phosphate, which is a fractal of Ca(2)(HPO(4))(3)(2-) clusters. The calcium triphosphate complex also forms the basis of the crystal structure of octacalcium phosphate and apatite. Finally, we demonstrate how the existence of these complexes lowers the energy barrier to nucleation and unites classical and non-classical nucleation theories.

Towards stable catalysts by controlling collective properties of supported metal nanoparticles

Abstract: Supported metal nanoparticles play a pivotal role in areas such as nanoelectronics, energy storage/conversion and as catalysts for the sustainable production of fuels and chemicals. However, the tendency of nanoparticles to grow into larger crystallites is an impediment for stable performance. Exemplarily, loss of active surface area by metal particle growth is a major cause of deactivation for supported catalysts. In specific cases particle growth might be mitigated by tuning the properties of individual nanoparticles, such as size, composition and interaction with the support. Here we present an alternative strategy based on control over collective properties, revealing the pronounced impact of the three-dimensional nanospatial distribution of metal particles on catalyst stability. We employ silica-supported copper nanoparticles as catalysts for methanol synthesis as a showcase. Achieving near-maximum interparticle spacings, as accessed quantitatively by electron tomography, slows down deactivation up to an order of magnitude compared with a catalyst with a non-uniform nanoparticle distribution, or a reference Cu/ZnO/Al(2)O(3) catalyst. Our approach paves the way towards the rational design of practically relevant catalysts and other nanomaterials with enhanced stability and functionality, for applications such as sensors, gas storage, batteries and solar fuel production.

Factors Limiting Device Efficiency in Organic Photovoltaics

Abstract: The power conversion efficiency of the most efficient organic photovoltaic (OPV) cells has recently increased to over 10%. To enable further increases, the factors limiting the device efficiency in OPV must be identified. In this review, the operational mechanism of OPV cells is explained and the detailed balance limit to photovoltaic energy conversion, as developed by Shockley and Queisser, is outlined. The various approaches that have been developed to estimate the maximum practically achievable efficiency in OPV are then discussed, based on empirical knowledge of organic semiconductor materials. Subsequently, approaches made to adapt the detailed balance theory to incorporate some of the fundamentally different processes in organic solar cells that originate from using a combination of two complementary, donor and acceptor, organic semiconductors using thermodynamic and kinetic approaches are described. The more empirical formulations to the efficiency limits provide estimates of 10-12%, but the more fundamental descriptions suggest limits of 20-24% to be reachable in single junctions, similar to the highest efficiencies obtained for crystalline silicon p-n junction solar cells. Closing this gap sets the stage for future materials research and development of OPV.

Nucleation and growth of magnetite from solution.

Abstract: The formation of crystalline materials from solution is usually described by the nucleation and growth theory, where atoms or molecules are assumed to assemble directly from solution. For numerous systems, the formation of the thermodynamically stable crystalline phase is additionally preceded by metastable intermediates . More complex pathways have recently been proposed, such as aggregational processes of nanoparticle precursors or pre-nucleation clusters, which seem to contradict the classical theory. Here we show by cryogenic transmission electron microscopy that the nucleation and growth of magnetite-a magnetic iron oxide with numerous bio- and nanotechnological applications-proceed through rapid agglomeration of nanometric primary particles and that in contrast to the nucleation of other minerals, no intermediate amorphous bulk precursor phase is involved. We also demonstrate that these observations can be described within the framework of classical nucleation theory.

Discovering block-structured process models from event logs - a constructive approach

Abstract: Process discovery is the problem of, given a log of observed behaviour, finding a process model that 'best' describes this behaviour. A large variety of process discovery algorithms has been proposed. However, no existing algorithm guarantees to return a fitting model (i.e., able to reproduce all observed behaviour) that is sound (free of deadlocks and other anomalies) in finite time. We present an extensible framework to discover from any given log a set of block-structured process models that are sound and fit the observed behaviour. In addition we characterise the minimal information required in the log to rediscover a particular process model. We then provide a polynomial-time algorithm for discovering a sound, fitting, block-structured model from any given log; we give sufficient conditions on the log for which our algorithm returns a model that is language-equivalent to the process model underlying the log, including unseen behaviour. The technique is implemented in a prototypical tool.

Domain wall depinning governed by the spin Hall effect

Abstract: Perpendicularly magnetized materials have attracted significant interest owing to their high anisotropy, which gives rise to extremely narrow, nanosized domain walls. As a result, the recently studied current-induced domain wall motion (CIDWM) in these materials promises to enable a new class of data, memory and logic devices1, 2, 3, 4, 5. Here we propose the spin Hall effect as an alternative mechanism for CIDWM. We are able to carefully tune the net spin Hall current in depinning experiments on Pt/Co/Pt nanowires, offering unique control over CIDWM. Furthermore, we determine that the depinning efficiency is intimately related to the internal structure of the domain wall, which we control by the application of small fields along the nanowire. This manifestation of CIDWM offers an attractive degree of freedom for manipulating domain wall motion by charge currents, and sheds light on the existence of contradicting reports on CIDWM in perpendicularly magnetized materials6, 7, 8, 9, 10, 11.

Novel Process Windows for Enabling, Accelerating, and Uplifting Flow Chemistry

Abstract: Novel Process Windows make use of process conditions that are far from conventional practices. This involves the use of high temperatures, high pressures, high concentrations (solvent-free), new chemical transformations, explosive conditions, and process simplification and integration to boost synthetic chemistry on both the laboratory and production scale. Such harsh reaction conditions can be safely reached in microstructured reactors due to their excellent transport intensification properties. This Review discusses the different routes towards Novel Process Windows and provides several examples for each route grouped into different classes of chemical and process-design intensification.

Learning analytics dashboard applications

Abstract: This article introduces learning analytics dashboards that visualize learning traces for learners and teachers. We present a conceptual framework that helps to analyze learning analytics applications for these kinds of users. We then present our own work in this area and compare with 15 related dashboard applications for learning. Most evaluations evaluate only part of our conceptual framework and do not assess whether dashboards contribute to behavior change or new understanding, probably also because such assessment requires longitudinal studies.

Efficient Tandem and Triple-Junction Polymer Solar Cells

Abstract: We demonstrate tandem and triple-junction polymer solar cells with power conversion efficiencies of 8.9% and 9.6% that use a newly designed, high molecular weight, small band gap semiconducting polymer and a matching wide band gap polymer.

Climate adaptive building shells: state-of-the-art and future challenges

Abstract: Successful building design is becoming an increasingly complex task, due to a growing demand to satisfy more ambitious environmental, societal and economical performance requirements. The application of climate adaptive building shells (CABS) has recently been put forward as a promising alternative within this strive for higher levels of sustainability in the built environment. Compared to conventional facades, CABS offer potential opportunities for energy savings as well improvement of indoor environmental quality. By combining the complementary beneficial aspects of both active and passive building technologies into the building envelope, CABS can draw upon the concepts of adaptability, multi-ability and evolvability. The aim of this paper is to present a comprehensive review of research, design and development efforts in the field of CABS. Based on a structured literature review, a classification of 44 CABS is made to place the variety of concepts in context with each other, and concurrent developments. In doing so, the overall motivations, enabling technologies, and characteristic features that have contributed to the development of CABS are highlighted. Despite the positive perspectives, it was found that the concept of CABS cannot yet be considered mature. Future research needs and further challenges to be resolved are therefore identified as well.

High-Molecular-Weight Regular Alternating Diketopyrrolopyrrole-based Terpolymers for Efficient Organic Solar Cells†

Abstract: The work of K.H.H. was supported by the "Europees Fonds voor Regionale Ontwikkeling" (EFRO) in the Intereg IV-A project "Organext". The research leading to these results has received funding from the Ministry of Education, Culture and Science (Gravity program 024.001.035) and is part of the research program of the Dutch Polymer Institute (DPI project 660) and the Solliance Organic Photovoltaics Programme.

A survey on service quality description

Abstract: Quality of service (QoS) can be a critical element for achieving the business goals of a service provider, for the acceptance of a service by the user, or for guaranteeing service characteristics in a composition of services, where a service is defined as either a software or a software-support (i.e., infrastructural) service which is available on any type of network or electronic channel. The goal of this article is to compare the approaches to QoS description in the literature, where several models and metamodels are included. consider a large spectrum of models and metamodels to describe service quality, ranging from ontological approaches to define quality measures, metrics, and dimensions, to metamodels enabling the specification of quality-based service requirements and capabilities as well as of SLAs (Service-Level Agreements) and SLA templates for service provisioning. Our survey is performed by inspecting the characteristics of the available approaches to reveal which are the consolidated ones and which are the ones specific to given aspects and to analyze where the need for further research and investigation lies. The approaches here illustrated have been selected based on a systematic review of conference proceedings and journals spanning various research areas in computer science and engineering, including: distributed, information, and telecommunication systems, networks and security, and service-oriented and grid computing.

Memory-centric accelerator design for Convolutional Neural Networks

Abstract: In the near future, cameras will be used everywhere as flexible sensors for numerous applications. For mobility and privacy reasons, the required image processing should be local on embedded computer platforms with performance requirements and energy constraints. Dedicated acceleration of Convolutional Neural Networks (CNN) can achieve these targets with enough flexibility to perform multiple vision tasks. A challenging problem for the design of efficient accelerators is the limited amount of external memory bandwidth. We show that the effects of the memory bottleneck can be reduced by a flexible memory hierarchy that supports the complex data access patterns in CNN workload. The efficiency of the on-chip memories is maximized by our scheduler that uses tiling to optimize for data locality. Our design flow ensures that on-chip memory size is minimized, which reduces area and energy usage. The design flow is evaluated by a High Level Synthesis implementation on a Virtex 6 FPGA board. Compared to accelerators with standard scratchpad memories the FPGA resources can be reduced up to 13× while maintaining the same performance. Alternatively, when the same amount of FPGA resources is used our accelerators are up to 11× faster.

Discovering Block-Structured Process Models from Event Logs Containing Infrequent Behaviour

Abstract: Given an event log describing observed behaviour, process discovery aims to find a process model that ‘best’ describes this behaviour. A large variety of process discovery algorithms has been proposed. However, no existing algorithm returns a sound model in all cases (free of deadlocks and other anomalies), handles infrequent behaviour well and finishes quickly. We present a technique able to cope with infrequent behaviour and large event logs, while ensuring soundness. The technique has been implemented in ProM and we compare the technique with existing approaches in terms of quality and performance.

Plasmonics for solid-state lighting: enhanced excitation and directional emission of highly efficient light sources

Abstract: Light sources based on reliable and energy-efficient light-emitting diodes (LEDs) are instrumental in the development of solid-state lighting (SSL). Most research efforts in SSL have focused on improving both the intrinsic quantum efficiency (QE) and the stability of light emitters. For this reason, it is broadly accepted that with the advent of highly efficient (QE close to 1) and stable emitters, the fundamentalresearchphaseofSSLiscomingtoanend.Inthisstudy,wedemonstrateaverylargeimprovementinSSLemission(above 70-fold directional enhancement for p-polarized emission and 60-fold enhancement for unpolarized emission) using nanophotonic structures. This is attained by coupling emitters with very high QE to collective plasmonic resonances in periodic arrays of aluminum nanoantennas.OurresultsopenanewpathforfundamentalandappliedresearchinSSLinwhichplasmonicnanostructuresareableto mold the spectral and angular distribution of the emission with unprecedented precision. Light: Science & Applications (2013) 2, e66; doi:10.1038/lsa.2013.22; published online 10 May 2013

Efficient small bandgap polymer solar cells with high fill factors for 300 nm thick films.

Abstract: A high-molecular-weight conjugated polymer based on alternating electron-rich and electron-deficient fused ring systems provides efficient polymer solar cells when blended with C60 and C70 fullerene derivatives. The morphology of the new polymer/fullerene blend reduces bimolecular recombination and allows reaching high fill factors and power conversion efficiencies for films up to 300 nm thickness.

Universal Correlation between Fibril Width and Quantum Efficiency in Diketopyrrolopyrrole-Based Polymer Solar Cells

Abstract: For a series of six diketopyrrolopyrrole (DPP)-based conjugated polymers, we establish a direct correlation between their external quantum efficiencies (EQE) in organic solar cells and the fibrillar microstructure in the blend. The polymers consist of electron-deficient DPP units, carrying long branched 2′-decyltetradecyl (DT) side chains for solubility, that alternate along the main chain with electron-rich aromatic segments comprising benzene, thiophene, or fused aromatic rings. The high molecular weight DT-DPP polymers were incorporated in bulk heterojunction solar cells with [6,6]-phenyl-C71-butyric acid methyl ester ([70]PCBM) as acceptor. The morphology of the DT-DPP:[70]PCBM blends is characterized by a semicrystalline fibrillar microstructure with fibril widths between 4.5 and 30 nm as evidenced from transmission electron microscopy. A clear correlation is found between the widths of the fibrils and the EQE for photon to electron conversion. The highest EQEs (60%) and power conversion efficiencies...

The time-dependent pollution-routing problem

Abstract: The Time-Dependent Pollution-Routing Problem (TDPRP) consists of routing a fleet of vehicles in order to serve a set of customers and determining the speeds on each leg of the routes. The cost function includes emissions and driver costs, taking into account traffic congestion which, at peak periods, significantly restricts vehicle speeds and increases emissions. We describe an integer linear programming formulation of the TDPRP and provide illustrative examples to motivate the problem and give insights about the tradeoffs it involves. We also provide an analytical characterization of the optimal solutions for a single-arc version of the problem, identifying conditions under which it is optimal to wait idly at certain locations in order to avoid congestion and to reduce the cost of emissions. Building on these analytical results we describe a novel departure time and speed optimization algorithm for the cases when the route is fixed. Finally, using benchmark instances, we present results on the computational performance of the proposed formulation and on the speed optimization procedure.