25th Anniversary Article: A Soft Future: From Robots and Sensor Skin to Energy Harvesters

Scientists are exploring elastic and soft forms of robots, electronic skin and energy harvesters, dreaming to mimic nature and to enable novel applications in wide fields, from consumer and mobile appliances to biomedical systems, sports and healthcare. All conceivable classes of materials with a wide range of mechanical, physical and chemical properties are employed, from liquids and gels to organic and inorganic solids. Functionalities never seen before are achieved. In this review we discuss soft robots which allow actuation with several degrees of freedom. We show that different actuation mechanisms lead to similar actuators, capable of complex and smooth movements in 3d space. We introduce latest research examples in sensor skin development and discuss ultraflexible electronic circuits, light emitting diodes and solar cells as examples. Additional functionalities of sensor skin, such as visual sensors inspired by animal eyes, camouflage, self‐cleaning and healing and on‐skin energy storage and generation are briefly reviewed. Finally, we discuss a paradigm change in energy harvesting, away from hard energy generators to soft ones based on dielectric elastomers. Such systems are shown to work with high energy of conversion, making them potentially interesting for harvesting mechanical energy from human gait, winds and ocean waves.     

Floc-based sequential partial nitritation and anammox at full scale with contrasting N2O emissions

New Activated Sludge (NAS^®) is a hybrid, floc-based nitrogen removal process without carbon addition, based on the control of sludge retention times (SRT) and dissolved oxygen (DO) levels. The aim of this study was to examine the performance of a retrofitted four-stage NAS^® plant, including on-line measurements of greenhouse gas emissions (N₂O and CH₄). The plant treated anaerobically digested industrial wastewater, containing 264 mg N L⁻¹, 1154 mg chemical oxygen demand (COD) L⁻¹ and an inorganic carbon alkalinity of 34 meq L⁻¹. The batch-fed partial nitritation step received an overall nitrogen loading rate of 0.18-0.22 kg N m⁻³ d⁻¹, thereby oxidized nitrogen to nitrite (45-47%) and some nitrate (13-15%), but also to N₂O (5.1-6.6%). This was achieved at a SRT of 1.7 d and DO around 1.0 mg O₂ L⁻¹. Subsequently, anammox, denitrification and nitrification compartments were followed by a final settler, at an overall SRT of 46 d. None of the latter three reactors emitted N₂O. In the anammox step, 0.26 kg N m⁻³ d⁻¹ was removed, with an estimated contribution of 71% by the genus Kuenenia, which constituted 3.1% of the biomass. Overall, a nitrogen removal efficiency of 95% was obtained, yielding a dischargeable effluent. Retrofitting floc-based nitrification/denitrification with carbon addition to NAS^® allowed to save 40% of the operational wastewater treatment costs. Yet, a decrease of the N₂O emissions by about 50% is necessary in order to obtain a CO₂ neutral footprint. The impact of emitted CH₄ was 20 times lower.     

A review of hydrodynamic and energy-transport models for semiconductor device simulation

Since Stratton published his famous paper four decades ago, various transport models have been proposed which account for the average carrier energy or temperature in one way or another. The need for such transport models arose because the traditionally used drift-diffusion model cannot capture nonlocal effects which gained increasing importance in modern miniaturized semiconductor devices. In the derivation of these models from Boltzmann's transport equation, several assumptions have to be made in order to obtain a tractable equation set. Although these assumptions may differ significantly, the resulting final models show various similarities, which has frequently led to confusion. We give a detailed review on this subject, highlighting the differences and similarities between the models, and we shed some light on the critical issues associated with higher order transport models.     

Modeling Associative Recognition: A Comparison of Two-High-Threshold, Two-High-Threshold Signal Detection, and Mixture Distribution Models.

A 2-high-threshold signal detection (HTSDT) model, a mixture distribution (SON) model, and 2-highthreshold (HT) models with responses distributed over 1 or several response categories were fit to results of 6 experiments from 2 studies on associative recognition: R. Kelley and J. T. Wixted (2001) and A. P. Yonelinas (1997). HTSDT assumes that associative recognition is based on conscious recollection and familiarity assessment, whereas according to SON and HT, associative information results in a shift of familiarity. The modeling results cast doubt on the prominent role of conscious recollection, and as far as models are valid, parameter estimation suggests 2 processes in associative recognition: a shift in familiarity that is due to associative information and the determination of the source of familiarity of pairs. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Self-adaptive space and time grids in device simulation

For the solution of the three basic semiconductor equations in two space dimensions fully self-adaptive grids are a powerful tool to optimize the ratio between the number of unknowns and the accuracy of the solution. For the method of finite differences hardly any mathematically founded criterion for automatic grid control can be given which can be implemented in a computer program with acceptable effort. Therefore most of the strategies for self-adaptive grid control are totally heuristic or derived from physical properties. In this paper we present criteria for the design of an initial space grid. We discuss some conventional strategies for the automatic control of space grids (e.g. equidistribution of the local discretization error) and present new criteria (e.g. degree of coupling of the equations, physical properties like net generation rate). For the time grid an automatic step length control algorithm is presented and the interaction between space and time grid is analysed. Throughout the paper the results are illustrated by realistic examples.     

Knowledge-based control for finite element analysis

This paper shows that control logic may be separated from analysis software and that a knowledge-based expert system can use this logic to perform interactive computation. Heuristics that control a simple interactive finite element analysis program are represented using a rule-based format and are used by a goal-driven logic processor to invoke analysis activity.Traditional algorithm-oriented control and the proposed knowledge-based control are compared in a simple displacement computation scenario to identify the advantages/disadvantages of the two approaches. General activities and constraints, practical methods of reasoning and representation, and knowledge-based expert systems are discussed with emphasis on applications to interactive finite element analysis.An analysis control expert system has been developed for use in the numerical analysis of two-dimensional linear problems in solid and structural mechanics. An example problem is used to clarify the methods used to direct activity and to identify the problems associated with conditional task processing for interactive analysis.The main difference between the analysis program described in this paper and conventional analysis programs is related to the control architecture. The general conclusion of this paper is that knowledge-based control is more effective and flexible than algorithm-oriented control.     

Feature sampling in detection: Implications for the measurement of perceptual independence.

The article presents the feature sampling signal detection (FS-SDT) model, an extension of the multivariate signal detection (SDT) model. The FS-SDT model assumes that, because of attentional shifts, different subsets of features are sampled for different presentations of the same multidimensional stimulus. Contrary to the SDT model, the FS-SDT model enables the estimation of pure perceptual effects that are uncontaminated by strategic attention shifts. The consideration of feature sampling in detection and identification opens a new perspective on the problem of measuring, respectively, the separability and integrality of stimulus dimensions. Disregarding feature sampling as a component process in detection and identification usually results in biased estimations of perceptual independence concepts relevant for judgments of whether stimulus dimensions are processed independently. (PsycINFO Database Record (c) 2010 APA, all rights reserved)