Current trends in structural development and modification strategies for metal-organic frameworks (MOFs) towards photocatalytic H2 production: A review

Photocatalytic H₂ generation using semiconductor photocatalysts is considered as a cost-effective and eco-friendly technology for solar to energy conversion; however, the present photocatalysts have been recognized to depict low efficiency. Currently, porous coordination polymers known as metal-organic frameworks (MOFs) constituting flexible and modifiable porous structure and having excess active sites are considered to be appropriate for photocatalytic H₂ production. This review highlights current progress in structural development of MOF materials along with modification strategies for enhanced photoactivity. Initially, the review discusses the photocatalytic H₂ production mechanism with the concepts of thermodynamics and mass transfer with particular focus on MOFs. Elaboration of the structural categories of MOFs into Type I, Type II, Type III and classification of MOFs for H₂ generation into transition metal based, post-transition metal based, noble-metal based and hetero-metal based has been systematically discussed. The review also critically deliberate various modification approaches of band engineering, improvement of charge separation, efficient irradiation utilization and overall efficiency of MOFs including metal modification, heterojunction formation, Z-scheme formation, by introducing electron mediator, and dye based composites. Also, the MOF synthesized derivatives for photocatalytic H₂ generation are elaborated. Finally, future perspectives of MOFs for H₂ generation and approaches for efficiency improvement have been suggested.     

Green Measurements for Software Product Based on Sustainability Dimensions

Software is a central component in the modern world and vastly affects the environment’s sustainability. The demand for energy and resource requirements is rising when producing hardware and software units. Literature study reveals that many studies focused on green hardware; however, limited efforts were made in the greenness of software products. Green software products are necessary to solve the issues and problems related to the long-term use of software, especially from a sustainability perspective. Without a proper mechanism for measuring the greenness of a particular software product executed in a specific environment, the mentioned benefits will not be attained. Currently, there are not enough works to address this problem, and the green status of software products is uncertain and unsure. This paper aims to identify the green measurements based on sustainable dimensions in a software product. The second objective is to reveal the relationships between the elements and measurements through empirical study. The study is conducted in two phases. The first phase is the theoretical phase, where the main components, measurements and practices that influence the sustainability of a software product are identified. The second phase is the empirical study that involved 103 respondents in Malaysia investigating current practices of green software in the industrial environment and further identifying the main sustainability dimensions and measurements and their impact on achieving green software products. This study has revealed seven green measurements of software product: Productivity, Usability, Cost Reduction, Employee Support, Energy Efficiency, Resource Efficiency and Tool Support. The relationships are statistically significant, with a significance level of less than 0.01 (p = 0.000). Thus, the hypothesised relationships were all accepted. The contributions of this study revolve around the research perspectives of the measurements to attain a green software product.     

A strategic roadmap for large-scale green hydrogen demonstration and commercialisation in China: A review and survey analysis

Hydrogen is gaining increased attention from industries and policymakers in China. However, most of the current demonstration projects in the country have relied on conventional energy sources, including industrial byproduct hydrogen and grey hydrogen produced from fossil fuels. Moreover, strategies and policy frameworks leading to a shift to green or low-carbon hydrogen have neither been explored in-depth nor been identified clearly in the context of China. This study aims at bridging such gaps. Roadmapping techniques enhanced by the Delphi method and SWOT analysis are used to survey hydrogen energy experts from government bodies, industries, and academia to achieve basic agreement on strategically enabling large-scale green hydrogen demonstrations followed by commercialisation in China. The outcome of two rounds of surveys showed that experts' opinions converged on a strategic roadmap with three stages of development. The corresponding policies needed in each stage are evaluated and selected to form a systemic framework.     

A PV installation framework concerning electricity variable rates

This paper assesses building integrated photovoltaic (BIPV) installation parameters based on the profit generated by a photovoltaic system. It takes into consideration a home building case study and it investigates its monthly energy demand based on a specific location and a typical occupancy. The capability of a photovoltaic (PV) system to generate more profit occurs when solar intensity is maximum while the electric energy price is at its highest rate. The paper traces a framework that encompasses different aspects such as energy demand, energy price, and solar intensity. This framework identifies profit alternatives according to different installation parameters. A tool that predicts a PV installation hourly electric energy production is developed. The profit generated is simulated for home buildings located in Beirut (Lebanon) and Xihua (China), both at 33.8° latitude north. The paper highlights a new approach for BIPV installations, taking into account weather conditions, energy demand, and electric energy utility rates.     

基于启发式BP算法的软件缺陷预测模型

针对软件缺陷预测时缺陷数据集中存在的类别分布不平衡问题，结合上采样算法SMOTE与Edited Nearest Neighbor (ENN) 数据清洗策略，提出了一种基于启发式BP神经网络算法的软件缺陷预测模型。模型中采用上采样算法SMOTE增加少数类样本以改善项目中的数据不平衡状况，并针对采样后数据噪声问题进行ENN数据清洗，结合基于启发式学习的模拟退火算法改进四层BP神经网络后建立分类预测模型，在AEEEM数据库上使用交叉验证对提出的方案进行性能评估，结果表明所提出的算法能够有效提高模型在预测类不平衡数据时的分类准确度。     

Platinum nanoparticles decorated on graphitic carbon nitride-ZIF-67 composite support: An electrocatalyst for the oxidation of butanol in fuel cell applications

In the present study, we report an eco-friendly and simple route to design and synthesize novel nanocomposite catalyst based on platinum nanoparticles anchored on binary support of graphitic carbon nitride (g-C₃N₄) and cobalt-metal-organic framework (ZIF-67). For this purpose, ZIF-67 was prepared by precipitation method and g-C₃N₄ was prepared through thermal polymerization method. Later, ZIF-67 and g-C₃N₄ were hybridized through sonication to get homogeneous g–C₃N₄–ZIF-67 nanocomposite support material. Platinum nanoparticles (PtNPs) were uniformly deposited on g–C₃N₄–ZIF-67 by an electrochemical method. The as-developed nanocatalyst was characterized by morphological, structural and electrochemical techniques. The electrocatalytic activity of PtNPs@g–C₃N₄–ZIF-67 nanocatalyst towards butanol oxidation was evaluated via CV, CA, LSV and EIS in an alkaline medium. Results revealed that the proposed catalyst showed greatly enhanced electrooxidation of butanol in terms of high magnificent current density, lower oxidation potential, excellent long-term stability, large surface area, low charge transfer resistance and less toxic ability. Enhanced catalytic performance of the proposed catalyst could be ascribed to the synergistic effect of g–C₃N₄–ZIF-67 nanocomposite and PtNPs. The PtNPs@g–C₃N₄–ZIF-67 catalyst holds promising potential applications to be used as an anodic electrocatalyst for the development of high-performance alkaline fuel cells.     

An industrial case study on variability handling in large enterprise software systems

ContextEnterprise software systems (e.g., enterprise resource planning software) are often deployed in different contexts (e.g., different organizations or different business units or branches of one organization). However, even though organizations, business units or branches have the same or similar business goals, they may differ in how they achieve these goals. Thus, many enterprise software systems are subject to variability and adapted depending on the context in which they are used.ObjectiveOur goal is to provide a snapshot of variability in large scale enterprise software systems. We aim at understanding the types of variability that occur in large industrial enterprise software systems. Furthermore, we aim at identifying how variability is handled in such systems.MethodWe performed an exploratory case study in two large software organizations, involving two large enterprise software systems. Data were collected through interviews and document analysis. Data were analyzed following a grounded theory approach.ResultsWe identified seven types of variability (e.g., functionality, infrastructure) and eight mechanisms to handle variability (e.g., add-ons, code switches).ConclusionsWe provide generic types for classifying variability in enterprise software systems, and reusable mechanisms for handling such variability. Some variability types and handling mechanisms for enterprise software systems found in the real world extend existing concepts and theories. Others confirm findings from previous research literature on variability in software in general and are therefore not specific to enterprise software systems. Our findings also offer a theoretical foundation for describing variability handling in practice. Future work needs to provide more evaluations of the theoretical foundations, and refine variability handling mechanisms into more detailed practices.     

The concept of smartness in cyber–physical systems and connection to urban environment

The next-generation systems are expected to be largely cyber–physical systems (CPSs) that autonomously control physical processes, through sensors and actuators typically in real-time feedback and cooperative control loops distributed among physical and cyber environments. The rapid technological advancements enhance the smartness of these CPSs, pushing their boundaries of performance and efficiency by embedding new information and communication technologies. However, to what extent CPSs should be smarter so that they do not compromise safety and security of safety critical systems? is an open research question. Towards this goal, the purpose of this study is to establish a grounded theory to analyse what makes these systems smart? and eventually, how to find a balance between smartness and safety risks? In this precinct, this article aims to develop a conceptual framework, define the dimensions and derive the characteristics that make CPSs smart. The proposed approach combines an automated informetric and systematic analysis of literature pertinent to the topic of smartness across anthropology, science, engineering and technology. The analysis of a case study building and the discussions presented herein support the connection between the existing understanding of CPSs and smartness offered by the building design approach in urban environment.     

用于发光温度传感的金属有机框架材料

金属有机框架(Metal organic frameworks,MOFs)由于其显著的结构多样性和可调的发光性能,为制备不同种类的发光传感器提供了良好契机。近年来,利用发光MOFs探测温度传感技术受到了人们的广泛关注。结合对发光测温的描述后,总结了发光型MOF温度计的最新研究进展,重点介绍了双发射型MOF在温度传感领域中的广泛应用。