Search results

This bibliometric analysis aims to comprehensively explore the intersection of artificial intelligence (AI) and high-to-room-temperature superconductors. Focusing on scientific literature, the study investigates trends, collaboration patterns and impactful publications in this interdisciplinary field.

The research employs an advanced search query in the Scopus database, targeting articles on the development of superconductors using artificial intelligence. Data collection involves executing the query, saving the results as a CSV file and analyzing it using R-Studio and VOSviewer. Statistical tools, T-tests, regression analysis and Python coding are utilized to enhance the depth of analysis.

The analysis spans various dimensions, including the overview of bibliometric characteristics, annual scientific production, average citations per year, sources of publications and source production over time. Noteworthy findings include a sustained growth in annual scientific production, a peak in average citations in specific years and the identification of influential journals shaping the field.

While the analysis provides valuable insights, limitations include the potential influence of research biases and the exclusion of non-English articles. Further exploration is encouraged to address these limitations and gain a more nuanced understanding of the field.

Practically, this study aids researchers, practitioners and stakeholders in staying informed, identifying collaboration opportunities and contributing meaningfully to the ongoing growth and impact of high-to-room-temperature superconductors using artificial intelligence.

Socially, the study underscores the collaborative and global nature of research in this field, emphasizing the shared endeavor worldwide to advance the understanding and application of superconductors through artificial intelligence.

This research contributes to the originality of the scientific landscape by offering a comprehensive analysis of the development of high-to-room-temperature superconductors with artificial intelligence. The utilization of advanced bibliometric techniques and the identification of key trends and sources enhance the understanding of this emerging and interdisciplinary research domain.

The mechanical properties, including elastic constants and moduli, indicate the material’s stiffness and stability. Our calculations reveal that CuMg2GaS4 is a direct bandgap semiconductor, 2.18 eV. A detailed analysis of the electronic structure provides an insight into the bonding characteristics and charge distribution within the material.

This work presents a comprehensive investigation of the structural, electronic, optical, mechanical properties of the CuMg2GaS4 compound using density functional theory (DFT) calculations. Unlike its counterpart CuMg2InS4, which exhibits a tetragonal WS structure, CuMg2GaS4 is found to be an energetically stable in the monoclinic phase.

The calculated effective masses of electrons (0.38 m0) and holes (1.28 m0) suggest promising charge carrier mobility within the compound. Furthermore, based on the evaluation of electronic structure and optical absorption properties of CuMg2GaS4 in relation with the redox potentials of water, this demonstrates its potential as a promising candidate for efficient photocatalytic water splitting under visible light irradiation. These findings contribute to the understanding of the structural and functional properties of CuMg2GaS4 and pave the way for its potential applications in optoelectronic and energy conversion devices.

The prime novelty is to employ ab initio self-consistent Full-Potential Linearized augmented plane wave + local orbital method (FP-LAPW + lo) and investigate the properties of CuMg2GaS4 of structural, mechanical, thermodynamic stabilities, linear optical response.

The purpose of this study is to analyze the titanium alloy under heat treated condition. Titanium alloy heat treatment, particularly Ti‐6Al‐4V alloy, has been an important field of study due to its wide variety of uses in the aerospace, automotive, and biomedical sectors. The mechanical characteristics of titanium alloys are heavily influenced by their microstructure. Cold‐rolled Ti‐alloys have strong bending and tensile strength due to extensive β‐phase precipitation on the α matrix. However, various heat treatment (HT) methods can affect the mechanical characteristics. The current study seeks to investigate the effects of various heat treatment procedures on the microstructural and mechanical changes of Ti‐6Al‐4V alloy, in order to achieve an optimal balance of strength, hardness, and ductility for a variety of real-world applications.

Three plates of Ti‐6Al‐4V alloy were heated above the β‐transus temperature for a certain period and then cooled via furnace, air, and sand. One extra plate was kept in ‘untreated’ condition and given name ‘as received’ plate. The three heat treated plates were evaluated and compared with ‘as received’ plate based on tensile strength, bending strength, hardness, and microstructural changes.

A considerable change in orientation of α and β was noted through optical microscopy upon heat treatment. The mechanical testing revealed that all the cooling methods adopted in the study have reduced the UTS and increased the YS of the plates. The ductility of the alloy was primarily enhanced by 'air cooling' and 'sand cooling' methods.

Notably, the hardness test findings indicated a significant drop in hardness for the ‘sand‐cooled’ sample. Furthermore, the ‘air cooled’ sample showed the maximum hardness due to the production of acicular α regions.

Based on previous research, we choose nickel alloy 718 as the research material and use finite element analysis (FEA) to simulate the hydrogen diffusion in lattice, grain, boundary grain and dislocation in different thermal loads, aiming to understand the intricate mechanisms underlying hydrogen diffusion in nickel-based alloys, which will contribute to driving progress in the field of hydrogen diffusion for understanding and management HE.

In this research, we focus on nickel alloy 718, creating a numerical model with traps to simulate the hydrogen diffusion in lattice, grain, boundary grain and dislocation with different thermal loads, by FEA.

The results demonstrated that traps improve the hydrogen saturation in materials, and because of thermal saturation and heat flux, higher temperatures decrease the hydrogen solubility and increase hydrogen diffusion velocity, which can decrease hydrogen saturation.

Based on our previous research and publications, we developed a finite element model to define the hydrogen trapping in different microstructural features of nickel-based superalloys. The model is very complex with a very large number of elements capable of obtaining very affordable results.

This study aims to perform a comprehensive comparative analysis of the performance of microchannel heat sinks (MCHS) across a wide range of operating conditions. It investigates the interplay between heat transfer efficiency, frictional effects and flow dynamics in different channel configurations and fluid types.

The analysis is conducted through numerical simulations, solving the governing equations for mass, momentum and energy conservation. Multiple channel geometries are evaluated, each incorporating specific strategies to disrupt the thermal boundary layer along the heated channel surface. The study also considers the influence of transverse vorticity effects arising from abrupt or smooth geometric variations. The performance is assessed for three distinct fluids – mercury, helium and water – to examine the complex interplay between fluid properties (e.g. viscosity and thermal diffusivity), momentum losses and heat transfer gains. Key parameters, including the Reynolds number and Prandtl number, are systematically varied to uncover their impact on heat transfer coefficients, vorticity distribution and flow stability.

The study reveals that microchannels with wavy geometries and double internal bifurcations consistently deliver superior thermal performance compared to other configurations, regardless of the working fluid. The results highlight that variations in the Prandtl number significantly influence the dimensional convective heat transfer coefficient, vorticity patterns and the onset of fluid-dynamic instabilities for a fixed Reynolds number and geometry. The authors introduce a correlation for the Nusselt number with the exponents for the Reynolds and Prandtl numbers being ½ and ¼, respectively; the authors also show that, in agreement with existing literature, the friction factor is primarily affected by the Reynolds number and channel shape, demonstrating no dependence on the Prandtl number.

This research provides novel insights into the non-linear scaling of heat transfer and momentum loss with fluid properties in MCHS. The systematic exploration of fluid and geometric interactions enriches the current understanding of microchannel heat transfer mechanisms, presenting actionable recommendations for real-world applications.

This study aims to contribute to the ongoing assessment of executive compensation by investigating the nexus between managerial entrenchment factors, adopting a multifaceted perspective encompassing both economic and non-economic dimensions.

This research employs pooled cross-sectional Ordinary Least Squares (OLS) regression and Least Squares with Dummy Variables (LSDV) models with fixed effects to examine the determinants of Chief Executive Officer (CEO) compensation.

This research identifies firm size, performance (via ROA and Tobin’s Q), and CEO characteristics (age, tenure, stock ownership, MBA degree) as significant determinants of executive compensation at the 0.05 level. In contrast, the prestige of educational institutions, doctoral degrees, and the MBA’s relevance to short-term performance, along with CEO tenure, do not significantly affect pay. Additionally, the study highlights the significance of industry type (manufacturing vs technology) in shaping compensation, emphasizing the role of firm metrics and CEO credentials in designing executive pay packages.

This research introduces an innovative approach to controlling unobserved heterogeneity and adjusting for the dynamic nature of CEO compensation attributes across diverse CEO characteristics. By integrating both pooled Ordinary Least Squares (OLS) and Least Squares Dummy Variable (LSDV) models, the study addresses the challenges posed by time-invariant variables and unobservable heterogeneity. Such issues have historically skewed the accuracy of traditional OLS models in identifying the comprehensive array of factors—both economic and non-economic—that influence CEO compensation. This novel methodological framework significantly advances the examination of unobservable variables that may vary not only across the firms selected for analysis but also over time periods, thereby offering a more detailed understanding of the determinants of CEO pay.

The construction sector is highly prone to accidents, traditionally assessed using subjective qualitative measurements. To enhance the allocation of risk management resources and identify high-risk projects during pre-construction, an objective and quantitative approach is necessary. This study introduces a three-step clustering methodology to quantitatively evaluate accident risk levels in construction projects.

In the first step, accident and total construction revenue by project were collected to calculate accident probabilities. In the second step, accident probabilities were calculated by project type using the data collected in the first step. After that, benchmark models were suggested using clustering methods to identify high-risk project types for risk management. Before suggesting the benchmark models, an uncertainty analysis was conducted due to the limited amount of data. In the third step, the suggested benchmark models were validated for accuracy.

The results categorized risk levels for fatalities and injuries into four distinct groups. Validation through ordinal logistic regression demonstrated high explanatory power, with fatality risk levels ranging from 79.9 to 100% and injury risk levels from 90.3 to 100%.

This benchmark model facilitates effective comparisons and analyses across various construction sectors and countries, offering a robust quantitative standard for risk management. By identifying high-risk projects such as “Dam,” this methodology enables better resource allocation during the pre-construction phase, thereby improving overall safety management in the construction industry and providing a basis for legislative applications.

A physically-based elasto-viscoplastic constitutive model is proposed to examine the size effects of the precipitate and blocks on the creep for martensitic heat-resistant steels with both the dislocation creep and diffusional creep mechanisms considered.

The model relies upon the initial dislocation density and the sizes of M₂₃C₆ carbide and MX carbonitride, through the use of internal variable based governing equations to address the dislocation density evolution and precipitate coarsening processes. Most parameters of the model can be obtained from existing literature, while a small subset requires calibration. Based on the least-squares fitting method, the calibration is successfully done by comparing the modeling and experimental results of the steady state creep rate at 600° C across a wide range of applied stresses.

The model predictions of the creep responses at various stresses and temperatures, the carbide coarsening and the dislocation density evolution are consistent with the experimental data in literature. The modeling results indicate that considerable effect of the sizes of precipitates occurs only during the creep at relatively high stress levels where dislocation creep dominates, while the martensite block size effect happens during creep at relatively low stress levels where diffusion creep dominates. The size effect of M₂₃C₆ carbide on the steady creep rate is more significant than that of MX precipitate.

The present study also reveals that the two creep mechanisms compete such that at a given temperature the contribution of the diffusion creep mechanism decreases with increasing stress, while the contribution of the dislocation creep mechanism increases.

In order to allow easy replication of this study, industry standard software that is easily attainable was used. Most of the programs used are free to download, and the ones that are not are available, students can still obtain them through their university or free download options for enrolled university students. There is also a large online community for new users to learn how to use the programs through online tutorials, message boards and free instructional material provided by the developers. As this paper expands on the work created during part 1, the models and information gathered for SLA, SLS and FDM processes were modified and updated in order to be used for the second phase. The models were created using 3ds Max, an industry standard 3D modeling program created by Autodesk Media and entertainment. All the models, textures and animations were created using 3ds Max. While the program is not free, Autodesk does allow students to download the program for free as long as they are enrolled in an accredited university. It is common for universities to get Autodesk licensing for computer labs if they have a technology program, making it possible for students to use the program through the university.

The VR system chosen was the Dell Visor: it offered the best combination of software support through SteamVR and Unity compatibility, low cost compared to other currently available VR systems, along with hardware and software requirements that could be met relatively easily (Chandramouli et al., 2018; Chandramouli et al., 2014a). Dell Visor requires 1 HDMI port and 1 USB 3.0 port to connect the headset to the computer, and can work with laptops. Dell Visor uses two hand controllers for movement tracking, Bluetooth connection is used to connect the hand controllers to the headset and computer in order to provide freedom of movement. This small number of ports and connecting wires required for the head set allows easy set up and increased flexibility of movement for the Dell Visor compared to most other VR headsets currently available. Dell Visor is also compatible with most computers, even older models thanks to use of adaptors. With the use of an adaptor and dongle for Bluetooth and HDMI support, even if the computer does not initially meet the hardware requirements of the system, it is still possible to run the Dell Visor on the computer.

The final simulation incorporates aspects of both the process and assembly aspects of the earlier scenes, but presents them using a constraint code added to sliding levers and pieces of the SLA 3D printer that lock into place when assembled. This simulation was created with the intent of being a demo for the capability of VR, as it uses the pre-build SteamVR code that is publicly available for use in Unity. This simulation uses a slide and lock constraint on a lever mechanism that allows the user to manually control the flow of the printer process, by moving the lever left and right, the user can rewind and fast forward through the printer animation as much as they wish to. There is also an assembly table to attach the individual parts of the SLA printer together. The pieces lock into place when put into the correct spot, using the base part of the printer as the starting point for them to build off.

While VR technology is still a relatively new field, the possible uses of this technology are becoming better understood in recent years. As both the general public and institutions become better acquainted with VR, more opportunities are created for instruction. VR has been associated with entertainment as the primary use for the technology, however, there is potential for VR in both business and educational as an effective learning tool. The main priority above all else for the simulations created for this study was to teach people about 3D printing in an accurate and interesting manner. Throughout the entire process this end goal was kept in mind, and achieving this goal shows the academic potential of VR for institutions. This study has provided a framework for how an institution can create a customized VR instructional model to fit their student’s needs. Using either freely available or academically partnered programs for use, any university can begin to create their own VR instructional materials that are compatible with both VR headset and desktop. Unity has a large online support network for students to troubleshoot and teach themselves how to use the software; it is compatible with modern computers so it is possible to create simulations that do not require a VR headset, and is free to use. This can allow universities to create simulations for relatively low cost and low barrier to entry, not factoring the initial cost of buying the necessary programs, hardware and time required for new users to learn the software.

Anchored in the theories of brand gestalt and stakeholder perspectives, this study aims to undertake a comprehensive examination of the brand gestalt concept, emphasizing its multidimensional nature and the process of co-creation.

Focused within the context of the Wonderful Indonesia brand, the research draws upon a rich qualitative data set derived from in-depth interviews conducted with 18 international tourists, supplemented by netnography (or internet ethnography) of websites, social media and online articles related to Wonderful Indonesia. Using grounded theory methodology, the qualitative data undergo rigorous analysis to identify emergent themes and patterns.

The research elucidates the four dimensions (4S) comprising brand gestalt: storyscapes, sensescapes, servicescapes and stakeholderscapes. Each dimension is further delineated into essential categories, providing a comprehensive understanding of brand gestalt. This study highlights the collaborative nature of brand gestalt, emphasizing the involvement of multiple stakeholders in shaping the brand's identity and perception. Consumer perceptions of co-creation are identified as significant contributors to brand gestalt, enhancing the brand's value proposition.

Destination management and practitioners can use the insights from the research to refine their brand management and marketing strategies by leveraging the dimensions of brand gestalt. Recognizing the collaborative construct of brand gestalt can guide businesses in fostering meaningful relationships with stakeholders and aligning branding efforts with collective visions. Understanding the role of consumer co-creation in brand development can inform strategies aimed at enhancing brand equity and fostering consumer loyalty.

This study extends existing literature on brand gestalt by providing a comprehensive examination of its four dimensions and essential categories. By emphasizing the collaborative nature of brand gestalt, this study contributes to advancing the understanding of brand co-creation paradigms. The identification of consumer perceptions of co-creation as a significant factor in brand gestalt adds novel insights to the literature, offering valuable implications for brand management and marketing strategies.