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The poly (vinylidene fluoride–trifluoroethylene–chlorofluoroethylene) P(VDF-TrFE-CFE) terpolymer has been identified as a promising candidate for the effective conversion of low-frequency mechanical vibrations into electricity. In this study, we provide a comprehensive and systematic investigation of the solvent-dependent mechanical, microstructural, electrical, frictional properties and triboelectric output performance of a relaxor ferroelectric P(VDF-TrFE-CFE) terpolymer. The P(VDF-TrFE-CFE) terpolymer films obtained from high dipole moment solvents have a longer rod-shaped grain than those from low dipole moment solvents. The crystallinity, Young's modulus and dielectric constant of P(VDF-TrFE-CFE) terpolymer become larger as the dipole moment of solvents increases, while the remnant polarization remains almost the same. The P(VDF-TrFE-CFE) terpolymer film obtained from the highest dipole moment solvent generates almost 1.55 times larger triboelectric charge than that obtained from the lowest moment. We attributed this large difference to the greatly enhanced lateral friction of terpolymer film obtained from high dipole moment solvents. [ABSTRACT FROM AUTHOR]

The direct growth of ferroelectric films onto flexible substrates has garnered significant interest in the advancement of portable and wearable electronic devices. However, the search for an optimized bottom electrode that can provide a large and stable remnant polarization is still ongoing. In this study, we report the optimization of an oxide-based LaNiO3 (LNO) electrode for high-quality Pb(Zr0.52Ti0.48)O3 (PZT) thick films. The surface morphology and electrical conductivity of sol-gel-grown LNO films on a fluorophlogopite mica (F-mica) substrate were optimized at a crystallization temperature of 800 °C and a film thickness of 120 nm. Our approach represents the promising potential pairing between PZT and LNO electrodes. While LNO-coated F-mica maintains stable electrical conductivity during 1.0%-strain and 104-bending cycles, the upper PZT films exhibit a nearly square-like polarization–electric field behavior under those stress conditions. After 104 cycles at 0.5% strain, the remnant polarization shows decreases as small as ~14%. Under flat (bent) conditions, the value decreases to just 81% (49%) after 1010 fatigue cycles and to 96% (85%) after 105 s of a retention test, respectively. [ABSTRACT FROM AUTHOR]

We introduce and analyze a model that explicitly considers the timing effect of intertemporal pricing--the concept, found in practice, that demand during a sale is increasing in the time since [...]

A timely introduction of a new product has become invaluable to the firm since the competitors are capable of introducing new or similar products once the driving technology becomes available. In order to generate a high profit from a new product, managers in other departments, such as marketing and production, have to plan ahead of time so that a seamless series of operations can be executed from product development to mass production. Needless to say, a competitive edge is given to the firm with better knowledge on product development process. Such knowledge, nonetheless, is not easy to acquire since a typical product development process is a complex network of many relationships among activities, which we call patterns. In addition to its complex topology, the product development process is often uncertain, iterative, and evolving over time; therefore, even studying individual islands of relationships (patterns) is challenging. Although there were some existing models that shed lights on some of these patterns, very little has been done to systematically analyze the product development process as a whole. In this paper, we develop analytical models that capture essential properties, including uncertainty, iteration and evolution, and estimate the cycle time of each pattern. With our proposed models, the cycle time of a set of patterns (or the whole product development process) can be effectively estimated. As demonstrated in a case study, our model provides valuable insights on how product development process progresses over time, while the corresponding time estimate can help managers to set appropriate manufacturing and marketing strategies. Index Terms--Cycle time estimation, iteration, overlapping, process pattern, product development (PD) process.

When designing an assortment, a fundamental trade‐off exists between estimating consumer behavior more precisely and solving the corresponding optimization problem efficiently. For instance, a mixture of logit model can closely approximate any random‐utility choice model; however, it is not suitable for optimization when the number of customer segments and the number of products considered are large. As many companies are using big data and marketing analytics toward microsegmenting consumers, a choice model that is amenable in the problem size becomes necessary for assortment design. In this work, we provide a new approach to approximate any random‐utility choice model by characterizing the estimation errors in a classical exogenous demand model and significantly improving its performance with a rescaling method. We show that the resulting approximation is exact for Multinomial Logit (MNL). If, however, the underlying true choice model is not MNL, we show numerically that the approximation under our so‐called rescaled two‐attempt model outperforms the widely used MNL approximation, and provides performance close to the Markov chain approximation (in some cases, it performs better than the Markov chain approximation). Our proposed approximation can be used to solve a general assortment optimization problem with a variety of (linear) real‐world constraints. In contrast to the more direct Mixed Integer Optimization (MIO) approach that utilizes Latent Class Multinomial Logit (LC‐MNL), whose running time increases exponentially in the number of mixtures, our approximation yields an alternative MIO formulation whose empirical running time is independent of the number of mixtures. [ABSTRACT FROM AUTHOR]