Advanced Transistor Process Technology from 22- to 14-nm Node

Transistor performance meets great technical challenges as the critical dimension (CD) shrinking beyond 32/28-nm nodes. A series of innovated process technologies such as high-k/metal gate, strain engineering, and 3D FinFET to overcome these challenges are reviewed in this chapter. The principle, developing route, and main prosperities of these technologies are systematically described with theoretical analysis and experimental results. Especially, the material choice, film stack design, and process flow integration approach with high-k/metal gate for sub-22-nm node is introduced; the film growth technique, process optimization, and flow integration method with advanced strain engineering are investigated; the architecture design, critical process definition, and integration scheme matching with traditional planar 2D transistor for 14-nm 3D FinFET are summarized

A maximal clique based multiobjective evolutionary algorithm for overlapping community detection

Detecting community structure has become one im-portant technique for studying complex networks. Although many community detection algorithms have been proposed, most of them focus on separated communities, where each node can be-long to only one community. However, in many real-world net-works, communities are often overlapped with each other. De-veloping overlapping community detection algorithms thus be-comes necessary. Along this avenue, this paper proposes a maxi-mal clique based multiobjective evolutionary algorithm for over-lapping community detection. In this algorithm, a new represen-tation scheme based on the introduced maximal-clique graph is presented. Since the maximal-clique graph is defined by using a set of maximal cliques of original graph as nodes and two maximal cliques are allowed to share the same nodes of the original graph, overlap is an intrinsic property of the maximal-clique graph. Attributing to this property, the new representation scheme al-lows multiobjective evolutionary algorithms to handle the over-lapping community detection problem in a way similar to that of the separated community detection, such that the optimization problems are simplified. As a result, the proposed algorithm could detect overlapping community structure with higher partition accuracy and lower computational cost when compared with the existing ones. The experiments on both synthetic and real-world networks validate the effectiveness and efficiency of the proposed algorithm

Leakage current simulations of Low Gain Avalanche Diode with improved Radiation Damage Modeling

We report precise TCAD simulations of IHEP-IME-v1 Low Gain Avalanche Diode (LGAD) calibrated by secondary ion mass spectroscopy (SIMS). Our setup allows us to evaluate the leakage current, capacitance, and breakdown voltage of LGAD, which agree with measurements' results before irradiation. And we propose an improved LGAD Radiation Damage Model (LRDM) which combines local acceptor removal with global deep energy levels. The LRDM is applied to the IHEP-IME-v1 LGAD and able to predict the leakage current well at -30 $^{\circ}$C after an irradiation fluence of $\Phi_{eq}=2.5 \times 10^{15} ~n_{eq}/cm^{2}$. The charge collection efficiency (CCE) is under development

Discussion of “from experiment to the field: the case of a price formation model based on laboratory findings”

Xin (2022) proposes a new approach that builds a model based on insights from laboratory findings. The model can uncover the process through which individual investor behavior drives macro-level stock market phenomena. This short discussion notes that the approach advocated by Xin (2022) allows us to easily extend the model and to incorporate other behavioral assumptions based on lab findings to understand empirical regularities that were documented in prior accounting studies.Submitted/Accepted versio

Can employees exercise control over managers? The role of the employees’ knowledge of manager behavior and manager discretion

I investigate whether organizations can use the "power of the employee" to reduce managers' opportunistic behavior toward others. I predict that revealing this behavior to employees makes managers less inclined to act opportunistically. Employees' knowledge has a stronger impact on reducing managers' opportunistic behavior when managers have discretion over employee rewards versus when they do not. I further predict that the effect of employee-based control depends on whether managers are other-interested versus self-interested. Revealing manager actions alone is sufficient to reduce other-interested managers' opportunism, even when they lack discretion over employee rewards. Revealing manager actions alone has no discernible influence on self-interested managers' opportunism, but pairing this action with granting them discretion over employee compensation does reduce their opportunism. Results of two experiments support my predictions, and these results have important implications. By relying on the power of the employee, organizations can induce (even selfish) managers to act less opportunistically

Think twice before going for incentives: Social norms and the principal's decision on compensation contracts

Principals make decisions on various issues, ranging from contract design to control system implementation. Few studies examine the principal's active role in these decisions. We experimentally investigate this role by studying how a principal's choice for a truth-telling incentive contract, compared to a fixed-salary contract without truth-telling incentives, affects the honesty of their agents’ cost reporting. Results show that besides an incentive effect and a principal trust effect (Christ et al. [2012]), the active choice for incentives produces a negative “information leakage” effect. When principals use incentives, their choices not only incentivize truthful reporting and signal distrust, but they also leak important information about the social norm; namely, that other agents are likely to report dishonestly. Agents conform to this social norm by misrepresenting cost information more. Our results have important practical implications. Managers must recognize that their decisions can leak information to their agents, which may produce unanticipated consequences for the social norms of the organization

The effects of emotion-understanding ability and tournament incentives on supervisors’ propensity to acquire subordinate-type information to use in control decisions

We investigate how emotion-understanding ability, a component of emotional intelligence, and tournament incentives jointly influence supervisors' propensity to acquire information about their subordinates' trustworthiness and tailor their control decisions to this information. We predict and find that when receiving piece-rate incentives, high emotion-understanding supervisors are more likely than low emotion-understanding supervisors to acquire subordinate-type information and use it in their control decisions. In addition, relative to piece-rate incentives, tournament incentives increase supervisors’ propensity to acquire subordinate-type information more for low emotion-understanding supervisors than high emotion-understanding supervisors. Taken together, our results suggest that hiring high emotion-understanding supervisors and giving supervisors tournament incentives are at least partial substitutes in motivating supervisors to acquire and, thus, use subordinate-type information in their control decisions. Our results offer important insights into the process through which supervisors make discretionary control decisions and contribute to the understanding of the forces that shape managerial controls within organizations.Ministry of Education (MOE)We gratefully acknowledge the financial support provided by Singapore Ministry of Education Academic Research Fund Tier 1 (RG58/20)