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Institution

University of California

EducationOakland, California, United States
About: University of California is a education organization based out in Oakland, California, United States. It is known for research contribution in the topics: Population & Layer (electronics). The organization has 55175 authors who have published 52933 publications receiving 1491169 citations. The organization is also known as: UC & University of California System.


Papers
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Journal ArticleDOI
TL;DR: In this article, the role of ionicity in metal-semiconductor Schottky barriers was investigated by examining interfaces of increasing semiconductor ionicity, and the electronic structure of four separate interfaces consisting of jellium (of Al density) in contact with the (111) surface of Si and the (110) surfaces of GaAs, ZnSe, and ZnS was investigated through the use of a self-consistent pseudopotential method.
Abstract: We have investigated the role of ionicity in metal-semiconductor Schottky barriers by examining interfaces of increasing semiconductor ionicity. The electronic structure of four separate interfaces consisting of jellium (of Al density) in contact with the (111) surface of Si and the (110) surfaces of GaAs, ZnSe, and ZnS is investigated through the use of a self-consistent pseudopotential method. The barrier height and the surface density of states in the semiconductor band gap are determined. The phenomenological index of interface behavior S (studied by Kurtin, McGill, and Mead for semiconductors of different ionicity) is discussed in terms of a simple model involving metal-induced states in the semiconductor gap.

249 citations

Journal ArticleDOI
TL;DR: In this article, the use of molecularly thin organic films as release and anti-stiction coatings for MEMS is discussed, followed by a discussion of the current limitations and areas for improvements for this coating technology.
Abstract: Despite much progress in surface micromachining technology, adhesion, friction and wear remain key issues, severely limiting the realization and reliability of many microelectromechanical systems (MEMS) devices. In this article, we focus on the use of molecularly thin organic films as release and anti-stiction coatings for MEMS. The various classes of organic films explored for MEMS are reviewed here, followed by a discussion of the current limitations and areas for improvements for this coating technology.

249 citations

Proceedings Article
01 Jan 2017
TL;DR: This work introduces inverse reward design (IRD) as the problem of inferring the true objective based on the designed reward and the training MDP, and introduces approximate methods for solving IRD problems, and uses their solution to plan risk-averse behavior in test MDPs.
Abstract: Autonomous agents optimize the reward function we give them. What they don't know is how hard it is for us to design a reward function that actually captures what we want. When designing the reward, we might think of some specific training scenarios, and make sure that the reward will lead to the right behavior in those scenarios. Inevitably, agents encounter new scenarios (e.g., new types of terrain) where optimizing that same reward may lead to undesired behavior. Our insight is that reward functions are merely observations about what the designer actually wants, and that they should be interpreted in the context in which they were designed. We introduce inverse reward design (IRD) as the problem of inferring the true objective based on the designed reward and the training MDP. We introduce approximate methods for solving IRD problems, and use their solution to plan risk-averse behavior in test MDPs. Empirical results suggest that this approach can help alleviate negative side effects of misspecified reward functions and mitigate reward hacking.

249 citations

Journal ArticleDOI
TL;DR: The partnership process that guided the design as well as the Scaffolded Knowledge Integration framework that gave the partnership a head start on creating effective materials are described.
Abstract: The Knowledge Integration Environment (KIE) activities were designed to promote lifelong science learning. This paper describes the partnership process that guided the design as well as the Scaffolded Knowledge Integration framework that gave the partnership a head start on creating effective materials. KIE activities take advantage of internet materials to engage students in debate of science questions like 'how far does light go?', to make scientifically oriented design decisions, and to critique science claims in the popular press. Other papers in this collection describe the design studies carried out to improve KIE activities. These studies have implications for improving the Scaffolded Knowledge Integration framework and can inform future designers of science instruction.

249 citations

Book ChapterDOI
TL;DR: By modifying the characteristics of nonlinear memristors, the memristor DTCNN can perform almost all functions of Memristor cellular automaton and can perform more than one function at the same time, that is, it allows multitasking.
Abstract: In this paper, we design a cellular automaton and a discrete-time cellular neural network (DTCNN) using nonlinear passive memristors. They can perform a number of applications, such as logical operations, image processing operations, complex behaviors, higher brain functions, etc. By modifying the characteristics of nonlinear memristors, the memristor DTCNN can perform almost all functions of memristor cellular automaton. Furthermore, it can perform more than one function at the same time, that is, it allows multitasking.

249 citations


Authors

Showing all 55232 results

NameH-indexPapersCitations
Meir J. Stampfer2771414283776
George M. Whitesides2401739269833
Michael Karin236704226485
Fred H. Gage216967185732
Rob Knight2011061253207
Martin White1962038232387
Simon D. M. White189795231645
Scott M. Grundy187841231821
Peidong Yang183562144351
Patrick O. Brown183755200985
Michael G. Rosenfeld178504107707
George M. Church172900120514
David Haussler172488224960
Yang Yang1712644153049
Alan J. Heeger171913147492
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202322
2022105
2021775
20201,069
20191,225
20181,684