Doping-Free Arsenene Heterostructure Metal-Oxide-Semiconductor Field Effect Transistors Enabled by Thickness Modulated Semiconductor to Metal Transition in Arsenene

Two-dimensional (2-D) materials such as MoS2 and phosphorene provide an ideal platform to realize extremely thin body metal-oxide-semiconductor field effect transistors (MOSFETs) which is highly immune to short channel effects in the ultra-scaled regime. Even with the excellent electrostatic integrity inherent in 2-D system, however, 2-D materials suffer from the lack of efficient doping method which is crucial in MOSFETs technology. Recently, an unusual phase transition from semiconductor to metal driven by the thickness modulation has been predicted in mono-elemental 2-D material arsenene. Utilizing this extraordinary property, we propose doping-free arsenene heterostructure MOSFETs based on the lateral multilayer (metallic source)/monolayer (semiconducting channel)/multilayer (metallic drain) arsenene heterostructure. Metallic multilayer arsenene in the source and drain can serve as electrodes without doping. We investigate the potential performance of arsenene heterostructure MOSFETs through atomistic simulations using density functional theory and nonequilibrium Green's function. The intrinsic upper limit of the on-state current in arsenene heterostructure MOSFETs is estimated by studying the effect of layer number in the source and drain. We comprehensively analyze the competitiveness of arsenene heterostructure MOSFETs through benchmarking with monolayer arsenene homostructure MOSFETs equipped with the highly degenerate doped source and drain, suggesting superior performance of heterostructure MOSFETs over homostructure MOSFETs

Flow shop rescheduling under different types of disruption

This is an Accepted Manuscript of an article published by Taylor & Francis in International Journal of Production Research on 2013, available online:http://www.tandfonline.com/10.1080/00207543.2012.666856Almost all manufacturing facilities need to use production planning and scheduling systems to increase productivity and to reduce production costs. Real-life production operations are subject to a large number of unexpected disruptions that may invalidate the original schedules. In these cases, rescheduling is essential to minimise the impact on the performance of the system. In this work we consider flow shop layouts that have seldom been studied in the rescheduling literature. We generate and employ three types of disruption that interrupt the original schedules simultaneously. We develop rescheduling algorithms to finally accomplish the twofold objective of establishing a standard framework on the one hand, and proposing rescheduling methods that seek a good trade-off between schedule quality and stability on the other.The authors would like to thank the anonymous referees for their careful and detailed comments that helped to improve the paper considerably. This work is partially financed by the Small and Medium Industry of the Generalitat Valenciana (IMPIVA) and by the European Union through the European Regional Development Fund (FEDER) inside the R + D program "Ayudas dirigidas a Institutos tecnologicos de la Red IMPIVA" during the year 2011, with project number IMDEEA/2011/142.Katragjini Prifti, K.; Vallada Regalado, E.; Ruiz García, R. (2013). Flow shop rescheduling under different types of disruption. International Journal of Production Research. 51(3):780-797. https://doi.org/10.1080/00207543.2012.666856S780797513Abumaizar, R. J., & Svestka, J. A. 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Stochastic lot sizing problem with nervousness considerations

© 2018 Elsevier Ltd In this paper, we consider the multistage stochastic lot sizing problem with controllable processing times under nervousness considerations. We assume that the processing times can be reduced in return for extra cost (compression cost). We generalize the static and static-dynamic uncertainty strategies to eliminate setup oriented nervousness and control quantity oriented nervousness. We restrict the quantity oriented nervousness by introducing a new concept called promised production amounts, and considering new range constraints and a nervousness cost function. We formulate the problem as a second-order cone mixed integer program (SOCMIP), and apply the conic strengthening. We observe the continuous mixing set substructure in our formulation that arises due the controllable processing times. We reformulate the problem by using an extended formulation for the continuous mixing set and solve the problem by a branch-and-cut approach. The computational experiments indicate that the reformulation reduces the root gaps and this helps to solve the problem in less computation times. Moreover, in our computational experiments we investigate the impact of new restrictions, specifically the additional cost of eliminating the setup oriented nervousness, on the total costs and the system nervousness. Our computational results clearly indicate that we could significantly reduce the nervousness costs and generate more stable production schedules with a relatively small increase in the total cost.status: publishe

Stochastic geometric programming with an application

summary:In applications of geometric programming, some coefficients and/or exponents may not be precisely known. Stochastic geometric programming can be used to deal with such situations. In this paper, we shall indicate which stochastic programming approaches and which structural and distributional assumptions do not destroy the favorable structure of geometric programs. The already recognized possibilities are extended for a tracking model and stochastic sensitivity analysis is presented in the context of metal cutting optimization. Illustrative numerical results are reported