Drug delivery through the skin offers many advantages such as avoidance of hepatic first-pass metabolism, maintenance of steady plasma concentration, safety, and compliance over oral or parenteral pathways. However, the biggest challenge for transdermal delivery is that only a limited number of potent drugs with ideal physicochemical properties can passively diffuse and intercellularly permeate through skin barriers and achieve therapeutic concentration by this route. Significant efforts have been made toward the development of approaches to enhance transdermal permeation of the drugs. Among them, microneedles represent one of the microscale physical enhancement methods that greatly expand the spectrum of drugs for transdermal and intradermal delivery. Microneedles typically measure 0.1–1 mm in length. In this review, microneedle materials, fabrication routes, characterization techniques, and applications for transdermal delivery are discussed. A variety of materials such as silicon, stainless steel, and polymers have been used to fabricate solid, coated, hollow, or dissolvable microneedles. Their implications for transdermal drug delivery have been discussed extensively. However, there remain challenges with sustained delivery, efficacy, cost-effective fabrication, and large-scale manufacturing. This review discusses different modes of characterization and the gaps in manufacturing technologies associated with microneedles. This review also discusses their potential impact on drug delivery, vaccine delivery, disease diagnostic, and cosmetics applications.

Microneedles are micron-sized devices that are used for the transdermal administration of a wide range of active pharmaceutics substances with minimally invasive pain. In the past decade, various additive manufacturing technologies have been used for the fabrication of microneedles; however, they have limitations due to material compatibility and bioavailability and are time-consuming and expensive processes. Additive manufacturing (AM), which is popularly known as 3D-printing, is an innovative technology that builds three-dimensional solid objects (3D). This article provides a comprehensive review of the different 3D-printing technologies that have the potential to revolutionize the manufacturing of microneedles. The application of 3D-printed microneedles in various fields, such as drug delivery, vaccine delivery, cosmetics, therapy, tissue engineering, and diagnostics, are presented. This review also enumerates the challenges that are posed by the 3D-printing technologies, including the manufacturing cost, which limits its viability for large-scale production, the compatibility of the microneedle-based materials with human cells, and concerns around the efficient administration of large dosages of loaded microneedles. Furthermore, the optimization of microneedle design parameters and features for the best printing outcomes is of paramount interest. The Food and Drug Administration (FDA) regulatory guidelines relating to the safe use of microneedle devices are outlined. Finally, this review delineates the implementation of futuristic technologies, such as artificial intelligence algorithms, for 3D-printed microneedles and 4D-printing capabilities.

Additive Manufacturing (AM) requires integrated networking, embedded controls and cloud computing technologies to increase their efficiency and resource utilisation. However, currently there is no readily applicable system that can be used for cloud-based AM. The objective of this research is to develop a framework for designing a cyber additive manufacturing system that integrates an expert system with Internet of Things (IoT). An Artificial Neural Network (ANN) based expert system was implemented to classify input part designs based on CAD data and user inputs. Three ANN algorithms were trained on a knowledge base to identify optimal AM processes for different part designs. A two-stage model was used to enhance the prediction accuracy above 90% by increasing the number of input factors and datasets. A cyber interface was developed to query AM machine availability and resource capability using a Node-RED IoT device simulator. The dynamic AM machine identification system developed using an application programme interface (API) that integrates inputs from the smart algorithm and IoT interface for real-time predictions. This research establishes a foundation for the development of a cyber additive design for manufacturing system which can dynamically allocate digital designs to different AM techniques over the cyber network.

Nanomanufacturing and digital manufacturing (DM) are defining the forefront of the fourth industrial revolution—Industry 4.0—as enabling technologies for the processing of materials spanning several length scales. This review delineates the evolution of nanomaterials and nanomanufacturing in the digital age for applications in medicine, robotics, sensory technology, semiconductors, and consumer electronics. The incorporation of artificial intelligence (AI) tools to explore nanomaterial synthesis, optimize nanomanufacturing processes, and aid high-fidelity nanoscale characterization is discussed. This paper elaborates on different machine-learning and deep-learning algorithms for analyzing nanoscale images, designing nanomaterials, and nano quality assurance. The challenges associated with the application of machine- and deep-learning models to achieve robust and accurate predictions are outlined. The prospects of incorporating sophisticated AI algorithms such as reinforced learning, explainable artificial intelligence (XAI), big data analytics for material synthesis, manufacturing process innovation, and nanosystem integration are discussed.

Additive manufacturing (AM) also known as 3D printing is a technology that builds three-dimensional (3-D) solid objects. Customized 3D objects with complex geometries and integrated functional designs can be created using 3D printing. A comprehensive review of AM process with emphasis on recent advances achieved by various researchers and industries is discussed. Summary of each 3D printing technology capabilities, advantages and limitations is provided. This article reviews significant developments of 3D printing applications in different fields such as electronics, medical industry, aerospace, automobile, construction, fashion and food industry.

The ever-increasing global energy demand necessitates the development of efficient, sustainable, and high-performance energy storage systems. Nanotechnology, through the manipulation of materials at the nanoscale, offers significant potential for enhancing the performance of energy storage devices due to unique properties such as increased surface area and improved conductivity. This review paper investigates the crucial role of nanotechnology in advancing energy storage technologies, with a specific focus on capacitors and batteries, including lithium-ion, sodium–sulfur, and redox flow. We explore the diverse applications of nanomaterials in batteries, encompassing electrode materials (e.g., carbon nanotubes, metal oxides), electrolytes, and separators. To address challenges like interfacial side reactions, advanced nanostructured materials are being developed. We also delve into various manufacturing methods for nanomaterials, including top–down (e.g., ball milling), bottom–up (e.g., chemical vapor deposition), and hybrid approaches, highlighting their scalability considerations. While challenges such as cost-effectiveness and environmental concerns persist, the outlook for nanotechnology in energy storage remains promising, with emerging trends including solid-state batteries and the integration of nanomaterials with artificial intelligence for optimized energy storage.