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This study aims to explore the feasibility of adding Si₃N₄ nanoparticles to Sn58Bi and provides a theoretical basis for designing and applying new lead-free solder materials for the electronic packaging industry.

In this paper, Sn58Bi-xSi₃N₄ (x = 0, 0.2, 0.4, 0.6, 0.8, 1.0 Wt.%) was prepared for bonding Cu substrate, and the changes in thermal properties, wettability, microstructure, interfacial intermetallic compound and mechanical properties of the composite solder were systematically studied.

The experiment results demonstrate that including Si₃N₄ nanoparticles does not significantly impact the melting point of Sn58Bi solder, and the undercooling degree of solder only fluctuates slightly. The molten solder spreading area reached a maximum of 96.17 mm², raised by 19.41% relative to those without Si₃N₄, and the wetting angle was the smallest at 0.6 Wt.% of Si₃N₄, with a minimum value of 8.35°. When the Si₃N₄ nanoparticles reach 0.6 Wt.%, the solder joint microstructure is significantly refined. Appropriately adding Si₃N₄ nanoparticles will slightly increase the solder alloy hardness. When the concentration of Si₃N₄ reaches 0.6 Wt.%, the joints shear strength reached 45.30 MPa, representing a 49.85% increase compared to those without additives. A thorough examination indicates that legitimately incorporating Si₃N₄ nanoparticles into Sn58Bi solder can enhance its synthetical performance, and 0.6 Wt.% is the best addition amount in our test setting.

In this paper, Si₃N₄ nanoparticles were incorporated into Sn58Bi solder, and the effects of different contents of Si₃N₄ nanoparticles on Sn58Bi solder were investigated from various aspects.

Quantum computer design is a registration that utilises quantum-mechanical wonder, like superposition and entrapment, used to arrange the assets of a quantum computer. A deliberate layered system can be planned to handle the difficulties, which emerge during the advancement of a quantum figuring. The plan usefulness is isolated into layers where the subsystems are planned in such a manner with the goal that it can investigate the issues freely and measures better between the layers bringing about a superior arrangement. Right now, all adaptable quantum figuring innovations are recommendations and critical advances in assembling necessities needed to carry them to the real world. By and by, a few recommendations have less cumbersome innovative obstacles before them than others. Even though its applications are somewhat limited in the construction industry, steps have been taken towards its implementation across the industry as well as other industries.

The purpose of this study is to delve into the mechanism of Si3N4 nanowires (NWs) in Sn-based solder, thereby furnishing a theoretical foundation for the expeditious design and practical implementation of innovative lead-free solder materials in the electronic packaging industry.

This study investigates the effect of adding Si₃N₄ NWs to Sn58Bi solder in various mass fractions (0, 0.1, 0.2, 0.4, 0.6 and 0.8 Wt.%) for modifying the solder and joining the Cu substrate. Meanwhile, the melting characteristics and wettability of solder, as well as the microstructure, interfacial intermetallic compound (IMC) and mechanical properties of joint were evaluated.

The crystal plane spacing and lattice constant of Sn and Bi phase increase slightly. A minor variation in the Sn58Bi solder melting point was caused, while it does not impact its functionality. An appropriate Si₃N₄ NWs content (0.2∼0.4 Wt.%) significantly improves its wettability, and modifies the microstructure and interfacial IMC layer. The shear strength increases by up to 10.74% when adding 0.4 Wt.% Si₃N₄ NWs, and the failure mode observed is brittle fracture mainly. However, excessive Si₃N₄ will cause aggregation at the junction between the solder matrix and IMC layer, this will be detrimental to the joint.

The Si₃N₄ NWs were first used for the modification of lead-free solder materials. The relative properties of composite solder and joints were evaluated from different aspects, and the optimal ratio was obtained.

This paper aims to review in-memory computing (IMC) for machine learning (ML) applications from history, architectures and options aspects. In this review, the authors investigate different architectural aspects and collect and provide our comparative evaluations.

Collecting over 40 IMC papers related to hardware design and optimization techniques of recent years, then classify them into three optimization option categories: optimization through graphic processing unit (GPU), optimization through reduced precision and optimization through hardware accelerator. Then, the authors brief those techniques in aspects such as what kind of data set it applied, how it is designed and what is the contribution of this design.

ML algorithms are potent tools accommodated on IMC architecture. Although general-purpose hardware (central processing units and GPUs) can supply explicit solutions, their energy efficiencies have limitations because of their excessive flexibility support. On the other hand, hardware accelerators (field programmable gate arrays and application-specific integrated circuits) win on the energy efficiency aspect, but individual accelerator often adapts exclusively to ax single ML approach (family). From a long hardware evolution perspective, hardware/software collaboration heterogeneity design from hybrid platforms is an option for the researcher.

IMC’s optimization enables high-speed processing, increases performance and analyzes massive volumes of data in real-time. This work reviews IMC and its evolution. Then, the authors categorize three optimization paths for the IMC architecture to improve performance metrics.

The purpose of this paper is to present an improved model based on center potential instead of surface potential which is physically more relevant and accurate. Also, additional analytic insights have been provided to make the model independent and robust so that it can be extended to a full range compact model.

The design methodology used is center potential based analytical modeling using Psuedo-2D Poisson equation, with ingeniously developed boundary conditions, which help achieve reasonably accurate results. Also, the depletion width calculation has been suitably remodeled, to account for proper physical insights and accuracy.

The proposed model has considerable accuracy and is able to correctly predict most of the physical phenomena occurring inside the broken gate Tunnel FET structure. Also, a good match has been observed between the modeled data and the simulation results. I_on/I_ambipolar ratio of 10^(−8) has been achieved which is quintessential for low power SOCs.

The modeling approach used is different from the previously used techniques and uses indigenous boundary conditions. Also, the current model developed has been significantly altered, using very simple but intuitive technique instead of complex mathematical approach.

This paper aims to add further evidence to adoption criteria for “revolutionary” business techniques.

Adoption criteria for business techniques with a high degree of novelty have been developed earlier. The case of exchange-traded funds supports the earlier findings. The methodology applied is explicative.

The analysis supports findings that an effective response to a problem, the availability of a controllable procedure, the means to apply the procedure easily and the hardware jointly explain adopting “revolutionary” business techniques.

The results of case studies, in general, do not permit induction. More research might identify additional adoption criteria or falsify the presently obtained results. Therefore, further research is invited.

Managers seeking or being introduced to new techniques in business administration might use the criteria outlined here for their evaluation.

The author believes this paper corroborates earlier findings on adopting “revolutionary” business techniques that draw on theoretically developed technologies.

Upon graduating from university, many engineers will work in new product development and/or technology adoption for continuous improvement and production optimization. These jobs require employees to be cognizant of ethical practices and implications for design. However, little engineering coursework, outside the traditional ABET (Accreditation Board for Engineering and Technology) required Engineering Ethics course, accounts for the role of ethics within this process. Because of this, engineering students have few learning opportunities to practice and reflect on ethical decision-making.

This paper highlights one approach to integrating ethics into an engineering course (outside of engineering ethics). Specifically, the study is implemented within a five-week module with a focus on big data ethics, as part of a Supply Chain Management Technology course (required for Industrial Engineering Technology majors), using metacognition as the core assessment.

Four main themes were identified through the qualitative data analysis of the metacognitive reflections: (1) overreliance on content knowledge, (2) time management skills, (3) career connections and (4) knowledge extensions.

Three notable points emerged which contribute to the literature. First, this study showcased one example of how an ethics module can be integrated into an engineering course (other than Engineering Ethics). Second, this study demonstrated how metacognitive reflections can be used to reinforce student self-awareness of the learning process and connections to big data ethics in the workplace. Finally, this study exhibited how metacognitive reflection assignments can be deployed as a teaching and learning assessment tool, providing an opportunity for the instructor to make immediate changes as needed.

This case describes the growth of ReNew Power during its first decade of operation. Sumant Sinha, a first-generation entrepreneur and former banker, founded the company, which grew from a modest generator-cum-developer of wind energy-based electricity to one of India's largest companies in the renewable energy sector. With the entry of large, well-funded players such as Tata Power and Adani Green into the Indian renewable sector by the end of 2020, Sinha had to make a strategic decision: should ReNew continue to organically scale up its presence in an increasingly competitive yet expanding Indian renewable energy sector, should it diversify geographically, or should it pursue emerging opportunities for vertical or horizontal integration within the sector? The case provides an opportunity to discuss how alternative business models and competitive scenarios may facilitate or inhibit the growth of a player in the renewable energy sector.