Machine learning in biohydrogen production: a review

Biohydrogen is emerging as a promising carbon-neutral and sustainable energy carrier with high energy yield to replace conventional fossil fuels. However, biohydrogen commercial uptake is mainly hindered by the supply side. As a result, various operating parameters must be optimized to realize biohydrogen commercial uptake on a large-scale. Recently, machine learning algorithms have demonstrated the ability to handle large amounts of data while requiring less in-depth knowledge of the system and being capable of adapting to evolving circumstances. This review critically reviews the role of machine learning in categorizing and predicting data related to biohydrogen production. The accuracy and potential of different machine learning algorithms are reported. Also, the practical implications of machine learning models to realize biohydrogen uptake by the transportation sector are discussed. The review indicates that machine learning algorithms can successfully model non-linear and complex interactions between operational and performance parameters in biohydrogen production. Additionally, machine learning algorithms can help researchers identify the most efficient methods for producing biohydrogen, leading to a more sustainable and cost-effective energy source

Interfacing the IoT in composite manufacturing: An overview

It is a well-known fact that many sophisticated works consume a lot of human resources, leading to the need to find effective alternative. The manufacturing industry demands a lot of human resources, with around half of the global working population participating in this sector. Challenges such as sudden conflicts in the data, disasters, and loss of productivity are encountered by the manufacturing industries and can be overcome by monitoring machine performance data and automatically configuring the machines according to changing needs. This emphasizes the importance of the Internet of Things (IoT) in addressing niche areas of manufacturing. IoT is a buzzword heard everywhere around the globe. Implementing this technology makes most of the work more accessible than other conventional methods. This has created a lot of research interest on this topic. Among many manufacturing sectors, polymer composite material manufacturing is one of the most demanding. This review article purely focuses on polymer composite manufacturing and its allied processes. The consolidation of data is based on the influence of IoT on the extraction of fibers and manufacturing of polymer composite material using novel techniques, quality assessment of manufactured polymer composite material, challenges faced in exploring the use of IoT, and future scope. It can be stated from the survey that various researchers have minimally explored the incorporation of IoT, but its future looks very promising in terms of producing high-quality products at less time and lower cost by integrating this technique with conventional methods

A Critical Review on Hygrothermal and Sound Absorption Behavior of Natural-Fiber-Reinforced Polymer Composites

Increasing global environmental problems and awareness towards the utilization of eco-friendly resources enhanced the progress of research towards the development of next-generation biodegradable and environmentally friendly material. The development of natural-based composite material has led to various advantages such as a reduction in greenhouse gases and carbon footprints. In spite of the various advantages obtained from green materials, there are also a few disadvantages, such as poor interfacial compatibility between the polymer matrix and natural reinforcements and the high hydrophilicity of composites due to the reinforcement of hydrophilic natural fibers. This review focuses on various moisture-absorbing and sound-absorbing natural fiber polymer composites along with the synopsis of preparation methods of natural fiber polymer composites. It was stated in various studies that natural fibers are durable with a long life but their moisture absorption behavior depends on various factors. Such natural fibers possess different moisture absorption behavior rates and different moisture absorption behavior. The conversion of hydrophilic fibers into hydrophobic is deemed very important in improving the mechanical, thermal, and physical properties of the natural-fiber-reinforced polymer composites. One more physical property that requires the involvement of natural fibers in place of synthetic fibers is the sound absorption behavior. Various researchers have made experiments using natural-fiber-reinforced polymer composites as sound-absorbing materials. It was found from various studies that composites with higher thickness, porosity, and density behaved as better sound-absorbing materials