Natural Fibre Polymer (NFP) and Polylactic Acid (PLA) composites have received a lot of interest in a variety of sectors because they are environmentally friendly, renewable, and sustainable. Over the last decade, researchers have investigated the aspects of NFP/PLA composite development and optimization for a wide range of applications, including packaging materials, automotive components, construction materials, textile and apparel, biomedical devices, agricultural and horticultural applications, electronics, and consumer electronics. Furthermore, using Artificial Intelligence (AI) and Machine Learning (ML) methodologies has increased these polymer materials and associated technologies in their search for new potential ways to further progress in NFP and PLA composites. The purpose of this review paper is to present a complete overview of AI and machine learning applications in the synthesis and development of NFP/PLA composite materials. The subject matter includes the following research areas: material characterization, manufacturing, property prediction, durability assessment, sustainability analysis, and future perspectives, which demonstrate the potential and challenges of AI/ML in advancing NFP/PLA composite materials and technologies.

The advent of additive manufacturing (AM) technologies revolutionized design and production processes across various industries. In renewable energy, AM enabled new possibilities for optimizing solar e-hub (solar energy harvesting module) configurations, enhancing efficiency and performance. This study examined critical considerations such as material selection, durability, and cost-effectiveness in solar hub development. This fast-prototyping technique was controlled by computer-aided design (CAD) software like CREO Parametric 7.0 and Creality Slicer 4.8. Experimental results indicated that PLA (Polylactic acid) materials exhibited superior strength, with an impact energy of 4.8 Joules. The deformation study revealed that the maximum load of 22 MPa aligned with the ultimate tensile strength of PLA, and a hardness test result of 83.1 HRF featured its exemplary hardness properties. These findings advanced the understanding of using AM to investigate mechanical behaviours of PLA materials and optimize solar e-hub configurations for portable device applications, promoting sustainable energy solutions and the adoption of renewable energy technologies. In addition, the successful implementation of this approach will enable the renewable energy sectors to minimize the carbon foot-prints towards helping the global net-zero emissions by aligning the circular economy approach.

This research describes the physicochemical quality of harvested rainwater at four distinct locations in Peninsula Malaysia. The evaluation of rainwater quality across different geographic areas aims to provide valuable insights into potential variations and trends in rainwater quality to reduce water demand globally. This analysis is conducted to determine seven properties, namely ammoniacal nitrogen, biochemical oxygen demand (BOD5), chemical oxygen demand (COD), dissolved oxygen (DO), pH, total dissolved solids (TDS), and turbidity. The results demonstrate that the quality of harvested rainwater meets the raw water quality standards set by the World Health Organization (WHO) and the National Water Quality Standards for Malaysia (NWQSM), indicating good quality rainwater in Malaysia. However, the COD for rainwater in all locations exceeded the limit, with a range of 14.1 to 29.7 mg/L, while the maximum limit for COD set by WHO is 10 mg/L, and according to NWQSM standards, it is 10–100 mg/L. The average pH of the collected rainwater is acidic ranged from 4.7 to 5.56. BOD5 for the collected rainwater is excellent; however, L2 has a slightly higher BOD5 at 6.5 mg/L, whereas the recommended limit by WHO is 6 mg/L, and the NWQSM standard suggests a range of 1–12 mg/L, with a standard limit of 5–7 mg/L. Nevertheless, DO levels ranged from 7.71 to 7.76 mg/L, indicating an ambient gas concentration in the rainwater. The collected rainwater can be used for portable purposes, gardening, smart farming, and toilet flushing.

This work aims to design a granular filter-based carbon–neutral rainwater treatment system. Granular filters are capable of cleaning rainwater while leaving a carbon–neutral trace to promote environmentally friendly rainwater collection techniques by examining the filtration performance and impact on the environment. The elimination of pollutants and impurities from collected rainwater through granular filters highlights the significance of meeting water quality requirements. The system uses three filters (F1, F2, and F3) for the treatment process where palm (oil) fruit shell-activated carbon, coconut shell-activated carbon, coarse sand, and fine sand are used as raw materials. The physicochemical quality of rainwater (harvested at four different locations) in Selangor, Peninsula Malaysia, from February to March 2022 has been investigated in this study. The analysis covers seven essential properties, such as ammoniacal nitrogen, biochemical oxygen demand (BOD₅), chemical oxygen demand (COD), dissolved oxygen (DO), pH, total dissolved solids (TDS), and Turbidity. The obtained results indicate that the harvested purified rainwater generally meets World Health Organization (WHO), National Water Quality Standards for Malaysia (NWQSM), and Ministry of Health, Malaysia (MOH) standards, with pH ranging from 6.5 to 9 and BOD₅ within recommended limits. The parameters at the initial filtration maintain the acceptable limit for drinking water quality. However, after the feasibility study of 10–30 L of filtration, the DO range (7.77 to 8.67 mg/L) indicates ambient gas concentration. BOD₅ value exceeds the limit of 9.11 mg/L after 30 L of filtration for the F3 column. The system has potential applications in drinking, gardening, agriculture, and toilet flushing. Based on important physicochemical factors, the parameters at the first filtering keep the drinking water quality within an acceptable range. Nonetheless, further conductivity and mineral content testing is advised for a thorough study of drinking water. The results of this study thus support the larger objective of encouraging water sustainability and reducing the carbon footprint in water treatment procedures, which is to improve environmentally friendly rainwater harvesting technologies.

The emergence of additive manufacturing (AM) technologies has revolutionized design and production processes, offering new opportunities to enhance materials and optimize configurations across diverse industries, including renewable energy. This research focuses on the design and fabrication of a solar energy harvesting module (solar e-hub) using Polylactic Acid (PLA) material in AM techniques for 100-watt applications. In Malaysia, there is an increasing demand for energy adapted to small-scale and off-grid applications, particularly in rural areas where solar energy is readily available. Solar energy storage devices are crucial for these communities, as well as for campers and a reliable power source in remote locations. The research employs the Fused Deposition Modelling (FDM) method to fabricate solar e-hubs using sustainable green PLA materials. The process is controlled using computer-aided design (CAD) software like CREO Parametric 10.0 and slicing software Creatware V70.2, with parameters set to a heated bed temperature of 55°C, a printing temperature of 200°C, and a printing speed of 50 mms ⁻¹ with a cubic pattern of 25% infill. The static analysis yields an excellent safety factor of 533 for the solar e-hub, with a maximum von Mises stress obtained 4.876102 MPa. Pla is non-transparent, and the 10% absorption in the visible range suggests high longevity and reflective properties. The results demonstrate successful rapid prototyping of a complex design, yielding high-quality prints with excellent material strength and UV absorption properties.