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Bumpless Cu/SiO₂ hybrid bonding, which this paper aims to, is a key technology of three-dimensional (3D) high-density integration to promote the integrated circuits industry’s continuous development, which achieves the stacks of chips vertically connected via through-silicon via. Surface-activated bonding (SAB) and thermal-compression bonding (TCB) are used, but both have some shortcomings. The SAB method is overdemanding in the bonding environment, and the TCB method requires a high temperature to remove copper oxide from surfaces, which increases the thermal budget and grossly damages the fine-pitch device.

In this review, methods to prevent and remove copper oxidation in the whole bonding process for a lower bonding temperature, such as wet treatment, plasma surface activation, nanotwinned copper and the metal passivation layer, are investigated.

The cooperative bonding method combining wet treatment and plasma activation shows outstanding technological superiority without the high cost and additional necessity of copper passivation in manufacture. Cu/SiO₂ hybrid bonding has great potential to effectively enhance the integration density in future 3D packaging for artificial intelligence, the internet of things and other high-density chips.

To achieve heterogeneous bonding at a lower temperature, the SAB method, chemical treatment and the plasma-assisted bonding method (based on TCB) are used, and surface-enhanced measurements such as nanotwinned copper and the metal passivation layer are also applied to prevent surface copper oxide.

This study aims to explore the spatial distribution characteristics and spactial reciprocity between industrial parks (IPs) and vocational education parks (VEPs): agglomeration density, functional matching, spatial organization efficiency, as well as space intensive utility. To achieve this objective, IPs and VEPs in urban centers of Jiangsu Province are selected as the objects of the study. First, spatial analysis of thermodynamic diagrams is employed in this study to qualitatively analyze the evolutionary characteristics of the spatial distribution of IPs and VEPs to explore the spatial aggregation characteristics of their clustering, integration, and comprehensive crossover. Second, a horizontal comparison of the data and indexes concerned reveals that areas with high agglomeration and functional matching exhibit a sound spatial reciprocity. Third, this study crystallizes the four structural prototpye paradigms formed during the reciprocity evolution between IPs and VEPs; it compares spatial organization efficiency, with the agglomeration–core structure ranking first, followed by the circle–core structure. Finally, SPSS is used to analyze the space intensive utility in order to verify the conclusions of qualitative analysis. The findings can comprehensively explain the regularities of the spatial distribution and reciprocity between IPs and VEPs. The findngs can also elucidate the design of regional industrial development and educational programs.

To answer the questions: what roles windows of opportunity act in the catchup process of latecomers, what strategies latecomer enterprises should adopt to size windows of opportunity to catch-up with incumbents even going beyond?

This paper studies the catch-up history of the Chinese mobile phone industry and proposes a sectoral innovation system under scenario of technology paradigm shifts. Then a history-friendly simulation model and counterfactual analysis are conducted to learn how different windows of opportunity and catch-up strategies influence the catch-up performance of latecomers.

Results show latecomers can catch up with technology ability by utilizing technology window and path-creating strategy. However, catching up with the market is not guaranteed. Demand window can help latecomers to catch up with market as it increases their survival rates, different sized windows benefit different strategies. However, it also enlarges incumbents' scale effect. Without technology window technology catch up is not guaranteed. Two windows have combination effects. Demand window affects the “degree” of change in survival rates, while the technology window affects the “speed” of change. Demand window provides security; technology window provides the possibility of a breakthrough for technology ability.

The findings of this paper provide theoretical guidance for latecomer enterprises to choose appropriate catch-up strategies to seize different opportunity windows.

This paper emphasizes the abrupt change of industrial innovation system caused by technology paradigm shifts, which makes up for the shortcomings of previous researches on industrial innovation system which either studied the influence of static factors or based on the influence of continuous changes.

This paper aims to collect the energy consumption data and carry out energy consumption analysis of chemical enterprises, which is helpful to grasp the working conditions of each equipment accurately and to perfect the demand side management (DSM) for the user in the terminal.

The paper proposes a load monitoring system of chemical enterprises to collect the energy consumption data and carry out energy consumption analysis. An Elman neural network based on sparrow search algorithm is proposed to predict the power consumption change and distribution trend of enterprises in the future production cycle. The calculation efficiency and prediction accuracy have been significantly improved.

The paper analyzes the energy saving effect of energy efficiency management as well as “avoiding peak and filling valley” measures, and reasonable control requirements and assumed conditions are put forward to study the operability of enterprise energy saving measures from the DSM.

Because of the chosen enterprise data, the prediction accuracy needs to be further improved. Therefore, researchers are encouraged to test the proposed methodology further.

The paper includes implications for the development of energy consumption analysis and load forecasting of chemical enterprises and perfects the DSM for the user.

This paper fulfills an identified need to study how to forecast the power load and improve the management efficiency of energy consumption.