In this review are developed insights from the current research work to develop the concept of functional materials. This is understood as real modified substrates for varied applications. So, functional and modified substrates focused on nanoarchitectures, microcapsules, and devices for new nanotechnologies highlighting life sciences applications were revised. In this context, different types of concepts to proofs of concepts of new materials are shown to develop desired functions. Thus, it was shown that varied chemicals, emitters, pharmacophores, and controlled nano-chemistry were used for the design of nanoplatforms to further increase the sizes of materials. In this regard, the prototyping of materials was discussed, affording how to afford the challenge in the design and fabrication of new materials. Thus, the concept of optical active materials and the generation of a targeted signal through the substrate were developed. Moreover, advanced concepts were introduced, such as the multimodal energy approach by tuning optical coupling from molecules to the nanoscale within complex matter composites. These approaches were based on the confinement of specific optical matter, considering molecular spectroscopics and nano-optics, from where the new concept nominated as metamaterials was generated. In this manner, fundamental and applied research by the design of hierarchical bottom-up materials, controlling molecules towards nanoplatforms and modified substrates, was proposed. Therefore, varied accurate length scales and dimensions were controlled. Finally, it showed proofs of concepts and applications of implantable, portable, and wearable devices from cutting-edge knowledge to the next generation of devices and miniaturized instrumentation.

Metal iodide materials as novel components of thermal biological and medical systems at the interface between heat transfer techniques and therapeutic systems. Due to their outstanding heat transfer coefficients, biocompatibility, and thermally activated sensitivity, metal iodides like silver iodide (AgI), copper iodide (CuI), and cesium iodide (CsI) are considered to be useful in improving the performance of medical instruments, thermal treatment processes, and diagnostics. They are examined for their prospective applications in controlling thermal activity, local heating therapy, and smart temperature-sensitive drug carrier systems. In particular, their application in hyperthermia therapy for cancer treatment, infrared thermal imaging for diagnosis, and nano-based drug carriers points to a place for them in precision medicine. But issues of stability of materials used, biocompatibility, and control of heat—an essential factor that would give the tools the maximum clinical value—remain a challenge. The present mini-review outlines the emerging area of metal iodides and their applications in medical technologies, with a special focus on the pivotal role of these materials in enhancing non-invasive, efficient, and personalized medicine. Over time, metal iodide-based systems scouted a new era of thermal therapies and diagnostic instrumentation along with biomedical science as a whole.

This work investigated the photocatalytic properties of polymorphic nanostructures based on silica (SiO₂) and magnetite (Fe₃O₄) for the photodegradation of tartrazine yellow dye. In this sense, a fast, easy, and cheap synthesis route was proposed that used sugarcane bagasse biomass as a precursor material for silica. The Fourier transform infrared (FTIR) spectroscopy results showed a decrease in organic content due to the chemical treatment with NaOH solution. This was confirmed through the changes promoted in the bonds of chromophores belonging to lignin, cellulose, and hemicellulose. This treated biomass was calcined at 800 ℃, and FTIR and X-ray diffraction (XRD) also confirmed the biomass ash profile. The FTIR spectrum showed the formation of silica through stretching of the chemical bonds of the silicate group (Si-O-Si), which was confirmed by DXR with the predominance of peaks associated with the quartz phase. Scanning electron microscopy (SEM) and energy dispersive X-ray spectroscopy (EDS) confirmed the morphological and chemical changes due to the chemical and thermal treatments applied to this biomass. Using the coprecipitation method, we synthesized Fe₃O₄ nanoparticles (Np) in the presence of SiO₂, generating the material Fe₃O₄/SiO₂-Np. The result was the formation of nanostructures with cubic, spherical, and octahedral geometries with a size of 200 nm. The SEM images showed that the few heterojunctions formed in the mixed material increased the photocatalytic efficiency of the photodegradation of tartrazine yellow dye by more than two times. The degradation percentage reached 45% in 120 min of reaction time. This mixed material can effectively decontaminate effluents composed of organic pollutants containing azo groups.

Photovoltaic systems have shown significant attention in energy systems due to the recent machine learning approach to addressing photovoltaic technical failures and energy crises. A precise power production analysis is utilized for failure identification and detection. Therefore, detecting faults in photovoltaic systems produces a considerable challenge, as it needs to determine the fault type and location rapidly and economically while ensuring continuous system operation. Thus, applying an effective fault detection system becomes necessary to moderate damages caused by faulty photovoltaic devices and protect the system against possible losses. The contribution of this study is in two folds: firstly, the paper presents several categories of photovoltaic systems faults in literature, including line-to-line, degradation, partial shading effect, open/close circuits and bypass diode faults and explores fault discovery approaches with specific importance on detecting intricate faults earlier unexplored to address this issue; secondly, VOSviewer software is presented to assess and review the utilization of machine learning within the solar photovoltaic system sector. To achieve the aims, 2258 articles retrieved from Scopus, Google Scholar, and ScienceDirect were examined across different machine learning and energy-related keywords from 1990 to the most recent research papers on 14 January 2025. The results emphasise the efficiency of the established methods in attaining fault detection with a high accuracy of over 98%. It is also observed that considering their effortlessness and performance accuracy, artificial neural networks are the most promising technique in finding a central photovoltaic system fault detection. In this regard, an extensive application of machine learning to solar photovoltaic systems could thus clinch a quicker route through sustainable energy production.

Electronic Word of Mouth (eWOM) has become a pivotal factor influencing consumers’ decisions, particularly in the context of hotel services. With the advent of social media, it provides individuals with powerful tools to share its experiences and opinions about hotels. In this digital age, customers increasingly rely on online reviews and recommendations from their peers when selecting accommodations. eWOM on social media platforms has a substantial impact on customers’ perceptions and decision-making processes. This study aims to better understand the influence of eWOM by social media platforms on purchase intention of hotel services. To understand the influence of eWOM, this study uses the information adoption model as the model has been widely used in previous eWOM studies. The information quantity construct has been added to strengthen the model. The online questionnaire was distributed to social media users by using Google forms via social media platforms and only 210 of them were responded. The SmartPLS 4.0 software is used to analyze the data as the Partial Least Square-Structural Equation Modelling (PLS-SEM) is a method to confirm the structural equation models and to test the link between inert developments. Based on results, the information quantity and information quality of hotel services on eWOM positively influences the information usefulness and the information usefulness of hotel services on eWOM positively influences the purchase intention. The results lead to increase sales of hotel services and contribute to economic growth.